{"title":"Cardiovascular","description":"","products":[{"product_id":"acta2-antibody-sc-f0017","title":"α-Smooth Muscle Actin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eACTA2 is a target of interest in many antibody-based workflows. α-smooth muscle actin (α-SMA) is an actin isoform that plays a key role in generating mechanical tension within cells. While it is typically found in vascular smooth muscle cells, SMA can also be expressed in certain non-muscle cells, particularly myofibroblasts. These cells are found in healing wounds, scars, and fibrocontractive lesions, where they contribute to fibrosis. Depending on the literature source, ACTA2 may also be discussed as alpha-Smooth Muscle Actin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and cytoskeleton, which can matter when signal is compared across treatments or changing cell states. Following ACTA2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eACTA2 is commonly interpreted in the context of cardiovascular, developmental biology, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and cytoskeleton, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and cytoskeleton across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ACTA2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ACTA2 reflect biology rather than handling. When interpreting ACTA2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ACTA2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577379955033,"sku":"F0017-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577379987801,"sku":"F0017-100UL","price":379.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577380020569,"sku":"F0017-2X100UL","price":569.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0017-IF-Mouse-Small-Intestine.jpg?v=1773598081"},{"product_id":"rho12-antibody-sc-f0072","title":"Rho A Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eRHO12 is a target of interest in many antibody-based workflows. RhoA is a member of the Rho family of small GTPases that functions as a molecular switch to regulate cytoskeletal dynamics, cell shape, motility, and adhesion. RhoA encompasses a conserved GTPase domain that cycles between an inactive GDP-bound and an active GTP-bound state, controlling its interaction with downstream effectors. Depending on the literature source, RHO12 may also be discussed as Rho A and Transforming protein RhoA.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell projection, cytoplasm, and cytoskeleton, which can matter when signal is compared across treatments or changing cell states. Following RHO12 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eRHO12 is commonly interpreted in the context of neuroscience, cardiovascular, and developmental biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cell projection, and cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cell projection, and cytoplasm across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for RHO12. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in RHO12 reflect biology rather than handling. When interpreting RHO12, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep RHO12 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577382740313,"sku":"F0072-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577382773081,"sku":"F0072-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577382805849,"sku":"F0072-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0072-IF.png?v=1773598110"},{"product_id":"cd31-antibody-sc-f0131","title":"CD31 (PECAM-1) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePlatelet\/endothelial cell adhesion molecule-1 (PECAM-1), also known as CD31, is a vital cell adhesion and signaling molecule predominantly found in endothelial cells, circulating platelets, monocytes, neutrophils, and some T cells. It plays a crucial role in maintaining vascular integrity by facilitating homophilic interactions that concentrate PECAM-1 at endothelial junctions, thereby supporting vascular permeability and leukocyte migration. Depending on the literature source, CD31 may also be discussed as CD31 (PECAM-1) and PECAM-1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction, cell membrane, and membrane, which can matter when signal is compared across treatments or changing cell states. Following CD31 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eCD31 is commonly interpreted in the context of immunology, cardiovascular, and angiogenesis research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell junction, cell membrane, and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell junction, cell membrane, and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003edifferences related to endothelial activation, vessel remodeling, or growth-factor exposure\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for CD31. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in CD31 reflect biology rather than handling. When interpreting CD31, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep CD31 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577384214873,"sku":"F0131-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577384247641,"sku":"F0131-100UL","price":379.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577384280409,"sku":"F0131-2X100UL","price":569.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0131-IHC1.jpg?v=1773598132"},{"product_id":"aifm1-antibody-sc-f0268","title":"AIF Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eAIFM1 is a target of interest in many antibody-based workflows. Apoptosis-inducing factor (AIF), also known as programmed cell death 8 (Pdcd8), is a conserved flavoprotein with pyridine nucleotide-disulphide oxidoreductase and DNA binding domains. In vivo, AIF protects against neuronal apoptosis caused by oxidative stress. However, in vitro, AIF has a proapoptotic role where it translocates to the nucleus upon induction of the mitochondrial death pathway, leading to chromatin condensation and DNA fragmentation. Depending on the literature source, AIFM1 may also be discussed as AIF.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, membrane, mitochondrion, and mitochondrion inner membrane, which can matter when signal is compared across treatments or changing cell states. Following AIFM1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eAIFM1 is commonly interpreted in the context of neuroscience, cardiovascular, and metabolism research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, membrane, and mitochondrion, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, membrane, and mitochondrion across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for AIFM1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in AIFM1 reflect biology rather than handling. When interpreting AIFM1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep AIFM1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577436348761,"sku":"F0268-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577436381529,"sku":"F0268-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577436414297,"sku":"F0268-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0268-IF.png?v=1773598265"},{"product_id":"ptgs2-antibody-sc-f0327","title":"COX2 \/ Cyclooxygenase 2 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePTGS2 is a target of interest in many antibody-based workflows. COX-1 and COX-2 are isoenzymes. COX-2 expression is rapidly induced by various stimuli such as proinflammatory cytokines, lipopolysaccharides, mitogens, oncogenes, growth factors, hormones, and disorders of water-electrolyte hemostasis. This induction leads to increased synthesis of prostaglandins in inflamed and neoplastic tissues. Depending on the literature source, PTGS2 may also be discussed as COX2 \/ Cyclooxygenase 2 and Prostaglandin G\/H synthase 2.\u003c\/p\u003e\u003cp\u003eReported cellular context includes endoplasmic reticulum, membrane, microsome, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following PTGS2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePTGS2 is commonly interpreted in the context of cancer, immunology, and inflammation research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans endoplasmic reticulum, membrane, and microsome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between endoplasmic reticulum, membrane, and microsome across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PTGS2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PTGS2 reflect biology rather than handling. When interpreting PTGS2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PTGS2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577443688793,"sku":"F0327-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577443721561,"sku":"F0327-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577443754329,"sku":"F0327-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0327-IF.png?v=1773598344"},{"product_id":"nos3-antibody-sc-f0354","title":"Phospho-eNOS (Ser1177) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eEndothelial nitric oxide synthase (eNOS) is crucial for the regulation and maintenance of a healthy cardiovascular system. The significance of eNOS is highlighted by genetic polymorphisms in the eNOS gene, disruption of eNOS dimerization, and its complex signaling regulation. eNOS is encoded by the NOS3 gene, located in the 7q35-7q36 region of chromosome 7 in humans. Depending on the literature source, NOS3 may also be discussed as Phospho-eNOS (Ser1177) and eNOS (phospho S1177).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasm, cytoskeleton, and golgi apparatus, which can matter when signal is compared across treatments or changing cell states. Following NOS3 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eNOS3 is commonly interpreted in the context of cardiovascular and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cytoplasm, and cytoskeleton, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cytoplasm, and cytoskeleton across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for NOS3. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in NOS3 reflect biology rather than handling. When interpreting NOS3, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep NOS3 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577445785945,"sku":"F0354-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577445818713,"sku":"F0354-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577445851481,"sku":"F0354-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0354-wb.gif?v=1773598368"},{"product_id":"hsp60-antibody-sc-f0482","title":"HSP60 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eHeat shock protein 60 (HSP60) is a highly conserved protein found abundantly in both prokaryotic and eukaryotic cells. In mammals, HSP60 is mainly localized in the mitochondria, where it partners with HSP10 to aid in mitochondrial protein folding. However, HSP60 is also present in the cytoplasm, plasma membrane, and extracellular space. Depending on the literature source, HSP60 may also be discussed as Heat Shock Protein 60.\u003c\/p\u003e\u003cp\u003eReported cellular context includes mitochondrion, which can matter when signal is compared across treatments or changing cell states. Following HSP60 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eHSP60 is commonly interpreted in the context of cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans mitochondrion, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within mitochondrion relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for HSP60. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in HSP60 reflect biology rather than handling. When interpreting HSP60, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep HSP60 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577463382361,"sku":"F0482-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577463415129,"sku":"F0482-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577463447897,"sku":"F0482-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0482-IHC1.jpg?v=1773598521"},{"product_id":"nos1-antibody-sc-f0615","title":"nNOS Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNOS1 is a target of interest in many antibody-based workflows. Nitric oxide synthase (nNOS) is a crucial enzyme in the production of nitric oxide (NO), essential for maintaining vascular homeostasis and overall cardiovascular health. The nNOS gene encodes a protein that primarily functions in its active dimeric form. Its regulation involves complex mechanisms, including intrinsic factors like auto-inhibitory domains and extrinsic factors such as phosphorylation and protein interactions. Depending on the literature source, NOS1 may also be discussed as nNOS and Nitric Oxide Synthase I.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell projection, membrane, and synapse, which can matter when signal is compared across treatments or changing cell states. Following NOS1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eNOS1 is commonly interpreted in the context of neuroscience, cardiovascular, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cell projection, and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cell projection, and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for NOS1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in NOS1 reflect biology rather than handling. When interpreting NOS1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep NOS1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577491562841,"sku":"F0615-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577491595609,"sku":"F0615-100UL","price":319.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577491628377,"sku":"F0615-2X100UL","price":479.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0615-IF-Mouse-Cerebellum.jpg?v=1773598693"},{"product_id":"opa1-antibody-sc-f0741","title":"OPA1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eOPA1 (Optic Atrophy 1) is a pivotal protein governing mitochondrial dynamics crucial for maintaining optimal function and morphology in skeletal and cardiac muscle. It regulates the fusion of the inner mitochondrial membrane (IMM), which enhances the efficiency of oxidative phosphorylation (OXPHOS) and ATP production, thereby meeting the high energy demands of muscle tissues.\u003c\/p\u003e\u003cp\u003eReported cellular context includes membrane, mitochondrion, and mitochondrion inner membrane, which can matter when signal is compared across treatments or changing cell states. Following OPA1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eOPA1 is commonly interpreted in the context of cardiovascular and metabolism research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans membrane, mitochondrion, and mitochondrion inner membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between membrane, mitochondrion, and mitochondrion inner membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for OPA1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in OPA1 reflect biology rather than handling. When interpreting OPA1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep OPA1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577511125337,"sku":"F0741-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577511158105,"sku":"F0741-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577511190873,"sku":"F0741-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0741-IF.png?v=1773598864"},{"product_id":"serpine1-antibody-sc-f0743","title":"PAI-1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eSERPINE1 is a target of interest in many antibody-based workflows. PAI-1, a protein secreted into the extracellular space, belongs to the serine proteinase inhibitor (serpin) superfamily. Its primary function is to inhibit urokinase and tissue plasminogen activators (uPA and tPA), thus hindering the conversion of inactive plasminogen to plasmin. Consequently, PAI-1 plays a crucial role in regulating fibrinolysis and contributes significantly to vessel patency and tissue remodeling. Depending on the literature source, SERPINE1 may also be discussed as PAI-1 and Serpin E1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes secreted, which can matter when signal is compared across treatments or changing cell states. Following SERPINE1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eSERPINE1 is commonly interpreted in the context of cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within secreted relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for SERPINE1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in SERPINE1 reflect biology rather than handling. When interpreting SERPINE1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep SERPINE1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577511387481,"sku":"F0743-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577511420249,"sku":"F0743-100UL","price":399.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577511453017,"sku":"F0743-2X100UL","price":599.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0743-IHC1.jpg?v=1773598868"},{"product_id":"tra-1-60-antibody-sc-f0746","title":"PODXL Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTRA-1-60 is a target of interest in many antibody-based workflows. Podocalyxin-like protein (PODXL) is a heavily glycosylated type I transmembrane protein, closely associated with CD34. It is primarily localized in the cytoplasm of tumor cells, sometimes extending towards the cell membrane, but not found within the nucleus. The gene encoding PODXL is situated on chromosome 7q32-q33. Depending on the literature source, TRA-1-60 may also be discussed as PODXL and Podocalyxin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell projection, and membrane, which can matter when signal is compared across treatments or changing cell states. Following TRA-1-60 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTRA-1-60 is commonly interpreted in the context of cancer, neuroscience, and cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cell projection, and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cell projection, and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TRA-1-60. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TRA-1-60 reflect biology rather than handling. When interpreting TRA-1-60, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TRA-1-60 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577511977305,"sku":"F0746-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577512010073,"sku":"F0746-100UL","price":349.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577512042841,"sku":"F0746-2X100UL","price":519.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0746-IHC1.jpg?v=1773598871"},{"product_id":"cdh1-cdh2-cdh3-cdh4-cdh5-antibody-sc-f0771","title":"Pan Cadherin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePan Cadherin is a target of interest in many antibody-based workflows. Cadherins are cell-cell adhesion molecules embedded in the cell membrane, found across various metazoan organisms, and they are vital for tissue morphogenesis and maintenance. They regulate tissue morphogenesis by governing both the adhesion between cells and cell signaling processes. Cadherins play a crucial role in shaping and positioning cells within tissues. Depending on the literature source, Pan Cadherin may also be discussed as Pan Cadherin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction, cell membrane, and membrane, which can matter when signal is compared across treatments or changing cell states. Following Pan Cadherin across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state. In practice, this target is often considered at the family or isoform-group level, so experimental interpretation benefits from matched controls and clear comparison logic.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePan Cadherin is commonly interpreted in the context of immunology, neuroscience, and cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell junction, cell membrane, and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell junction, cell membrane, and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Pan Cadherin. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Pan Cadherin reflect biology rather than handling. When interpreting Pan Cadherin, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Pan Cadherin trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577517252953,"sku":"F0771-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577517285721,"sku":"F0771-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577517318489,"sku":"F0771-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0771-IF.png?v=1773598917"},{"product_id":"c23-antibody-sc-f0790","title":"Nucleolin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eC23 is a target of interest in many antibody-based workflows. Nucleolin (NCL) is a multifunctional protein found in different parts of eukaryotic cells, including the nucleoplasm, nucleolus, cytoplasm, and plasma membrane. It consists of approximately 700 amino acids and contains two low-complexity, intrinsically disordered domains (IDDs) located at both the N-terminal and C-terminal regions. Its main functions include regulating ribosome biogenesis and the synthesis of ribosomal RNA (rRNA). Depending on the literature source, C23 may also be discussed as Nucleolin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following C23 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eC23 is commonly interpreted in the context of neuroscience, cardiovascular, and epigenetics research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003elinks between target behavior and transcriptional or chromatin-state changes\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for C23. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in C23 reflect biology rather than handling. When interpreting C23, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep C23 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577520005465,"sku":"F0790-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577520038233,"sku":"F0790-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577520071001,"sku":"F0790-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0790-IHC1.jpg?v=1773598947"},{"product_id":"pdgfrb-antibody-sc-f0804","title":"Phospho-PDGF Receptor β (Tyr1009) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePDGFRB is a target of interest in many antibody-based workflows. Platelet-derived growth factor receptor β (PDGFRβ) is a type III tyrosine kinase receptor that plays a vital role in cell proliferation, migration, and survival. Structurally, it consists of five extracellular Ig-like domains, a single transmembrane domain, and an intracellular region with a conserved tyrosine kinase domain and juxtamembrane region. Depending on the literature source, PDGFRB may also be discussed as Phospho-PDGF Receptor beta (Tyr1009).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasmic vesicle, lysosome, and membrane, which can matter when signal is compared across treatments or changing cell states. Following PDGFRB across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePDGFRB is commonly interpreted in the context of cardiovascular and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cytoplasmic vesicle, and lysosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cytoplasmic vesicle, and lysosome across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PDGFRB. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PDGFRB reflect biology rather than handling. When interpreting PDGFRB, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PDGFRB trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577520857433,"sku":"F0804-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577520890201,"sku":"F0804-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577520922969,"sku":"F0804-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0804-wb.gif?v=1773598956"},{"product_id":"foxp1-antibody-sc-f0887","title":"FoxP1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe Fox (forkhead box P) factors are large transcriptional repressors with a highly conserved forkhead DNA-binding domain. They are crucial for regulating genes involved in cell proliferation and differentiation. Among the four subfamily members, Foxp1 is located on chromosome 3p14.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following FOXP1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eFOXP1 is commonly interpreted in the context of cancer, cardiovascular, and developmental biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within nucleus relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eWhere appropriate, pairing FOXP1 with orthogonal markers can improve confidence in interpretation, especially when experimental questions extend from baseline characterization into comparative or perturbation-driven studies.\u003c\/p\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for FOXP1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in FOXP1 reflect biology rather than handling. When interpreting FOXP1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep FOXP1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577552347481,"sku":"F0887-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577552380249,"sku":"F0887-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577552413017,"sku":"F0887-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0887-IHC1.jpg?v=1773599056"},{"product_id":"smyd2-antibody-sc-f0913","title":"SMYD2 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eSMYD2 (SET and MYND domain-containing protein 2) is a protein methyltransferase that methylates histone H3 at lysines 4 (H3K4) and 36 (H3K36), as well as various nonhistone proteins, influencing transcriptional regulation and post-translational modification crosstalk. Structurally, SMYD2 features five domains-S-sequence, MYND domain, insertion SET domain, cysteine-rich post-SET domain, and tetratricopeptide repeat (TPR) domain-forming a bilobal structure with an autoinhibited conformation regulated by the C-terminal domain.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following SMYD2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eSMYD2 is commonly interpreted in the context of cardiovascular and epigenetics research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003elinks between target behavior and transcriptional or chromatin-state changes\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for SMYD2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in SMYD2 reflect biology rather than handling. When interpreting SMYD2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep SMYD2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577564078425,"sku":"F0913-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577564111193,"sku":"F0913-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577564143961,"sku":"F0913-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0913-wb.gif?v=1773599089"},{"product_id":"atp2a2-antibody-sc-f0927","title":"SERCA2 ATPase Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eATP2A2 is a target of interest in many antibody-based workflows. SERCAs belong to the P-type ATPase family, along with H+\/K+ ATPase, Na+\/K+ ATPase, and plasma membrane Ca2+ ATPase. They facilitate the transport of Ca2+ ions across membranes using energy derived from ATP hydrolysis. The SERCA pumps consist of multiple isoforms, SERCA2a is the predominant isoform found in the sarcoplasmic reticulum of muscle cells, particularly in the adult myocardium, where it constitutes approximately 40% of total SR proteins. Depending on the literature source, ATP2A2 may also be discussed as SERCA2 ATPase and ATP2A2\/SERCA2.\u003c\/p\u003e\u003cp\u003eReported cellular context includes endoplasmic reticulum membrane, which can matter when signal is compared across treatments or changing cell states. Following ATP2A2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eATP2A2 is commonly interpreted in the context of cardiovascular and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans endoplasmic reticulum membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within endoplasmic reticulum membrane relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ATP2A2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ATP2A2 reflect biology rather than handling. When interpreting ATP2A2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ATP2A2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577571549529,"sku":"F0927-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577571582297,"sku":"F0927-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577571615065,"sku":"F0927-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0927-IHC1.jpg?v=1773599107"},{"product_id":"ptgs1-antibody-sc-f0984","title":"Cyclooxygenase 1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePTGS1 is a target of interest in many antibody-based workflows. Cyclooxygenase (COX), also known as prostaglandin H synthase or prostaglandin endoperoxide synthase, is the enzyme responsible for synthesizing prostanoids. Prostanoids are potent bioactive lipid messengers with various physiological and pathological functions. There are two distinct isoforms of COX: COX-1 and COX-2. Depending on the literature source, PTGS1 may also be discussed as Cyclooxygenase 1 and Cox1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes microsome membrane, peripheral membrane protein, and endoplasmic reticulum membrane, which can matter when signal is compared across treatments or changing cell states. Following PTGS1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePTGS1 is commonly interpreted in the context of neuroscience, inflammation, and cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans microsome membrane, peripheral membrane protein, and endoplasmic reticulum membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between microsome membrane, peripheral membrane protein, and endoplasmic reticulum membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PTGS1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PTGS1 reflect biology rather than handling. When interpreting PTGS1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PTGS1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577583640921,"sku":"F0984-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577583673689,"sku":"F0984-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577583706457,"sku":"F0984-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0984-IHC1.jpg?v=1773599155"},{"product_id":"ptx1-antibody-sc-f1024","title":"C Reactive Protein Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePTX1 is a target of interest in many antibody-based workflows. C-reactive protein (CRP) is a highly conserved, homopentameric plasma protein classified as an acute-phase inflammatory marker. During infection or inflammation, CRP levels can increase dramatically-by as much as 1,000-fold. In the presence of calcium, CRP binds to phosphocholine (PCh) and other polysaccharide structures found on microbial surfaces, initiating the classical complement cascade by interacting with C1q, thereby contributing to innate immune defense. Depending on the literature source, PTX1 may also be discussed as C Reactive Protein and CRP.\u003c\/p\u003e\u003cp\u003eReported cellular context includes secreted, which can matter when signal is compared across treatments or changing cell states. Following PTX1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePTX1 is commonly interpreted in the context of immunology, inflammation, and cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within secreted relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PTX1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PTX1 reflect biology rather than handling. When interpreting PTX1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PTX1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577592193369,"sku":"F1024-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577592226137,"sku":"F1024-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577592258905,"sku":"F1024-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1024-wb.gif?v=1773599201"},{"product_id":"dpp4-antibody-sc-f1035","title":"DPP4 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eDipeptidyl peptidase-4 (DPP4) is an enzyme that falls under the category of serine proteases, responsible for cleaving peptides with specific N-terminal properties. It plays a role in regulating various physiological processes, including lipid metabolism, oxidative stress, inflammation, endothelial and mitochondrial function, and insulin action. DPP4 levels are elevated in senescent human vascular smooth muscle cells and atherosclerotic plaques. Depending on the literature source, DPP4 may also be discussed as CD26.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction, cell membrane, cell projection, and membrane, which can matter when signal is compared across treatments or changing cell states. Following DPP4 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eDPP4 is commonly interpreted in the context of immunology, inflammation, and cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell junction, cell membrane, and cell projection, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell junction, cell membrane, and cell projection across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for DPP4. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in DPP4 reflect biology rather than handling. When interpreting DPP4, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep DPP4 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577594421593,"sku":"F1035-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577594454361,"sku":"F1035-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577594487129,"sku":"F1035-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1035-IHC1.jpg?v=1773599206"},{"product_id":"adrb2-antibody-sc-f1057","title":"β2 Adrenergic Receptor Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eBeta-2 adrenergic receptor (ADRB2) is part of the large superfamily of seven transmembrane helix G-protein-coupled receptors (GPCRs), activated by the stress hormones epinephrine and norepinephrine. There are three subtypes of beta-adrenoceptors: beta-1, beta-2, and beta-3. Beta-2 adrenoceptors are a type of G protein-coupled receptor whose activity depends on the alpha subunit of the Gs protein. Depending on the literature source, ADRB2 may also be discussed as beta2 Adrenergic Receptor.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, endosome, golgi apparatus, and lysosomes, which can matter when signal is compared across treatments or changing cell states. Following ADRB2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eADRB2 is commonly interpreted in the context of neuroscience and cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, endosome, and golgi apparatus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, endosome, and golgi apparatus across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ADRB2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ADRB2 reflect biology rather than handling. When interpreting ADRB2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ADRB2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577600024921,"sku":"F1057-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577600057689,"sku":"F1057-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577600090457,"sku":"F1057-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1057-IHC1.jpg?v=1773599231"},{"product_id":"esr1-antibody-sc-f1063","title":"Estrogen Receptor α Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eESR1 is a target of interest in many antibody-based workflows. Estrogen receptor α (ERα) is a ligand-dependent transcription factor and part of the nuclear hormone receptor (NHR) superfamily. It has a globular ligand-binding domain (LBD) that facilitates hormone binding, dimerization, and interaction with coregulators. The human ERα gene is located on chromosome 6, and the full-length protein consists of 595 amino acids with a molecular size of 66 kDa. Depending on the literature source, ESR1 may also be discussed as Estrogen Receptor alpha.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasm, golgi apparatus, and membrane, which can matter when signal is compared across treatments or changing cell states. Following ESR1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eESR1 is commonly interpreted in the context of cancer, cardiovascular, and metabolism research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cytoplasm, and golgi apparatus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cytoplasm, and golgi apparatus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ESR1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ESR1 reflect biology rather than handling. When interpreting ESR1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ESR1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577601630553,"sku":"F1063-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577601663321,"sku":"F1063-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577601696089,"sku":"F1063-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1063-IF.png?v=1773599236"},{"product_id":"ve-cadherin-antibody-sc-f1068","title":"VE-cadherin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eVE-cadherin, also known as vascular endothelial cadherin or CD144, is a critical transmembrane protein predominantly expressed in endothelial cells, where it plays a vital role in maintaining cell-cell junctions that regulate vascular permeability and integrity. As a member of the cadherin superfamily, VE-cadherin features a unique structure composed of an extracellular domain responsible for homophilic binding to adjacent VE-cadherin molecules, a single transmembrane domain and an intracellular domain that interacts with catenins such as β-catenin and p120-catenin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction, cell membrane, cytoplasm, and membrane, which can matter when signal is compared across treatments or changing cell states. Following VE-CADHERIN across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eVE-CADHERIN is commonly interpreted in the context of immunology, cardiovascular, and angiogenesis research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell junction, cell membrane, and cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell junction, cell membrane, and cytoplasm across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003edifferences related to endothelial activation, vessel remodeling, or growth-factor exposure\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for VE-CADHERIN. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in VE-CADHERIN reflect biology rather than handling. When interpreting VE-CADHERIN, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep VE-CADHERIN trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577603137881,"sku":"F1068-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577603170649,"sku":"F1068-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577603203417,"sku":"F1068-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1068-wb.gif?v=1773599246"},{"product_id":"vcam1-antibody-sc-f1145","title":"VCAM1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eVCAM1 is a 90-kDa glycoprotein that belongs to the immunoglobulin superfamily. It acts as an adhesion molecule expressed on activated endothelial surfaces, which helps in the adhesion and movement of leukocytes across epithelial barriers, thus initiating inflammatory responses. It plays a vital role in the engraftment of hematopoietic stem cells during transplantation.\u003c\/p\u003e\u003cp\u003eReported cellular context includes membrane, which can matter when signal is compared across treatments or changing cell states. Following VCAM1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eVCAM1 is commonly interpreted in the context of cancer, immunology, and cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within membrane relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for VCAM1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in VCAM1 reflect biology rather than handling. When interpreting VCAM1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep VCAM1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577627844953,"sku":"F1145-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577627877721,"sku":"F1145-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577627910489,"sku":"F1145-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1145-IF.png?v=1773599347"},{"product_id":"des-antibody-sc-f1188","title":"Desmin - Cytoskeleton Marker Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eDesmin is a muscle-specific type III intermediate filament protein belonging to the intermediate filament family, essential for maintaining the structural and mechanical integrity of muscle cells. It is composed of three main domains: a conserved α-helical rod domain that forms coiled-coil dimers, a variable non-helical N-terminal head domain important for filament assembly, and a carboxy-terminal tail domain responsible for filament integration and interactions with other proteins and organelles. Depending on the literature source, DES may also be discussed as Desmin - Cytoskeleton Marker and Desmin.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasm, intermediate filament, and membrane, which can matter when signal is compared across treatments or changing cell states. Following DES across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eDES is commonly interpreted in the context of cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cytoplasm, and intermediate filament, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cytoplasm, and intermediate filament across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for DES. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in DES reflect biology rather than handling. When interpreting DES, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep DES trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577644622169,"sku":"F1188-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577644654937,"sku":"F1188-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577644687705,"sku":"F1188-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1188-IF.png?v=1773599406"},{"product_id":"notch4-antibody-sc-f1202","title":"NOTCH4 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNOTCH4 is a target of interest in many antibody-based workflows. Notch proteins, encompassing Notch1-4, are a family of transmembrane receptors pivotal for developmental processes and cell fate determination. These receptors are synthesized and arranged as heterodimeric proteins, each composed of a large extracellular ligand-binding domain, a single-pass transmembrane domain, and a smaller cytoplasmic subunit known as Notch intracellular domain (NICD).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, membrane, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following NOTCH4 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eNOTCH4 is commonly interpreted in the context of cancer, cardiovascular, and developmental biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, membrane, and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, membrane, and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for NOTCH4. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in NOTCH4 reflect biology rather than handling. When interpreting NOTCH4, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep NOTCH4 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577649537369,"sku":"F1202-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577649570137,"sku":"F1202-100UL","price":319.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577649602905,"sku":"F1202-2X100UL","price":479.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1202-wb.gif?v=1773599428"},{"product_id":"myl9-antibody-sc-f1242","title":"Phospho-Myosin Light Chain 2 (Thr18\/Ser19) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eMYL9 is a target of interest in many antibody-based workflows. Phospho-Myosin Light Chain 2 (Thr18\/Ser19) (MLC2) refers to the regulatory light chain of myosin II, which is phosphorylated at threonine 18 (Thr18) and serine 19 (Ser19) residues by myosin light chain kinase (MLCK) and other kinases. Structurally, MLC2 is composed of a single polypeptide associated with the myosin heavy chain, and its N-terminal region contains the key phosphorylation sites that regulate myosin motor activity. Depending on the literature source, MYL9 may also be discussed as Phospho-Myosin Light Chain 2 (Thr18\/Ser19) and Myosin regulatory light polypeptide 9.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and cytoskeleton, which can matter when signal is compared across treatments or changing cell states. Following MYL9 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eMYL9 is commonly interpreted in the context of cardiovascular and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and cytoskeleton, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and cytoskeleton across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for MYL9. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in MYL9 reflect biology rather than handling. When interpreting MYL9, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep MYL9 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577670050137,"sku":"F1242-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577670082905,"sku":"F1242-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577670115673,"sku":"F1242-2X100UL","price":589.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1242-IF.png?v=1773599491"},{"product_id":"irap-antibody-sc-f1253","title":"IRAP Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eIRAP (Insulin-Regulated Aminopeptidase) is an enzyme encoded by the LNPEP gene in humans. It is present in various tissues, such as the heart, brain, spleen, and neuronal cells. Structurally, IRAP is a type-II membrane-spanning protein that undergoes post-translational modifications like glycosylation, which impact its functional properties and overall structure.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, membrane, and secreted, which can matter when signal is compared across treatments or changing cell states. Following IRAP across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eIRAP is commonly interpreted in the context of neuroscience, cardiovascular, and endocrinology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, membrane, and secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, membrane, and secreted across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eresponses to hormone-dependent signaling or endocrine feedback context\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for IRAP. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in IRAP reflect biology rather than handling. When interpreting IRAP, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep IRAP trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577673097561,"sku":"F1253-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577673130329,"sku":"F1253-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577673163097,"sku":"F1253-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1253-IF.png?v=1773599497"},{"product_id":"nkx2-5-antibody-sc-f1256","title":"NKX2.5 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNKX2.5 is a target of interest in many antibody-based workflows. NKX2. 5, a member of the NKX homeobox transcription factor family, plays a crucial role in embryonic heart development as one of the earliest factors expressed in the cardiac lineage. In mice, the Nkx2-5 gene is active in precardiac mesoderm and myocardium during embryonic and fetal stages.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following NKX2.5 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eNKX2.5 is commonly interpreted in the context of cardiovascular and developmental biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within nucleus relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for NKX2.5. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in NKX2.5 reflect biology rather than handling. When interpreting NKX2.5, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep NKX2.5 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577673294169,"sku":"F1256-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577673326937,"sku":"F1256-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577673359705,"sku":"F1256-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1256-IF.png?v=1773599500"},{"product_id":"pdgfrb-antibody-sc-f1260","title":"Phospho-PDGF Receptor β (Tyr1021) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePDGFRB is a target of interest in many antibody-based workflows. Phospho-PDGF Receptor β (Tyr 1021) refers to the activated form of the platelet-derived growth factor receptor beta (PDGFRβ) phosphorylated at tyrosine 1021, a critical event for receptor activation and signal transduction. PDGFRβ is a receptor tyrosine kinase composed of an extracellular domain with five immunoglobulin-like regions, a single transmembrane domain, and an intracellular tyrosine kinase domain. Depending on the literature source, PDGFRB may also be discussed as Phospho-PDGF Receptor beta (Tyr1021).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasmic vesicle, lysosome, and membrane, which can matter when signal is compared across treatments or changing cell states. Following PDGFRB across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePDGFRB is commonly interpreted in the context of immunology, cardiovascular, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cytoplasmic vesicle, and lysosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cytoplasmic vesicle, and lysosome across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PDGFRB. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PDGFRB reflect biology rather than handling. When interpreting PDGFRB, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PDGFRB trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577673654617,"sku":"F1260-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577673687385,"sku":"F1260-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577673720153,"sku":"F1260-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1260-wb.gif?v=1773599505"},{"product_id":"ephb4-antibody-sc-f1330","title":"EphB4 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eEphB4, or Ephrin type-B receptor 4, is a receptor tyrosine kinase (RTK) encoded by the EPHB4 gene, belonging to the Eph family of RTKs, which are crucial for various developmental processes, including nervous system and vascular development. EphB4 interacts with its ligand ephrinB2 to regulate cellular repulsion and adhesion, playing a key role in cardiovascular formation, neuronal guidance, and endothelial cell growth during embryogenesis and adulthood. Depending on the literature source, EPHB4 may also be discussed as Eph receptor B4\/HTK.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, which can matter when signal is compared across treatments or changing cell states. Following EPHB4 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eEPHB4 is commonly interpreted in the context of cancer, neuroscience, and cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within cell membrane relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for EPHB4. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in EPHB4 reflect biology rather than handling. When interpreting EPHB4, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep EPHB4 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577691447641,"sku":"F1330-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577691480409,"sku":"F1330-100UL","price":339.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577691513177,"sku":"F1330-2X100UL","price":499.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1330-IF.png?v=1773599598"},{"product_id":"gja1-antibody-sc-f1346","title":"Phospho-Connexin 43 (Ser368) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eGJA1 is a target of interest in many antibody-based workflows. Connexin 43 (Cx43) is a key gap junction protein essential for intercellular communication, allowing small molecules and signaling messengers to pass between cells. It is abundantly expressed in the heart and brain, particularly in ventricular and astrocytic tissues. Phosphorylation of Cx43 at its C-terminal tail, including sites such as Ser368 by protein kinase C (PKC), regulates the permeability of gap junctions and hemichannels. Depending on the literature source, GJA1 may also be discussed as Phospho-Connexin 43 (Ser368) and Connexin 43 \/ GJA1 (phospho S368).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction, cell membrane, endoplasmic reticulum, and gap junction, which can matter when signal is compared across treatments or changing cell states. Following GJA1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eGJA1 is commonly interpreted in the context of cardiovascular and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell junction, cell membrane, and endoplasmic reticulum, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell junction, cell membrane, and endoplasmic reticulum across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for GJA1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in GJA1 reflect biology rather than handling. When interpreting GJA1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep GJA1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577699344729,"sku":"F1346-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577699377497,"sku":"F1346-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577699410265,"sku":"F1346-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1346-wb.gif?v=1773599625"},{"product_id":"pln-antibody-sc-f1349","title":"Phospholamban Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePhospholamban (PLN) is a major phosphoprotein component of the sarcoplasmic reticulum (SR), consisting of 52 amino acids and weighing 6 kDa. It is a membrane-spanning protein that can form stable homo-oligomers even in the presence of SDS. While PLN is highly expressed in cardiac tissue, it is also present in skeletal and smooth muscle. Depending on the literature source, PLN may also be discussed as Phospholamban and PLB.\u003c\/p\u003e\u003cp\u003eReported cellular context includes endoplasmic reticulum, membrane, mitochondrion, and sarcoplasmic reticulum, which can matter when signal is compared across treatments or changing cell states. Following PLN across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePLN is commonly interpreted in the context of cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans endoplasmic reticulum, membrane, and mitochondrion, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between endoplasmic reticulum, membrane, and mitochondrion across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PLN. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PLN reflect biology rather than handling. When interpreting PLN, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PLN trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577701638489,"sku":"F1349-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577701671257,"sku":"F1349-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577701704025,"sku":"F1349-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1349-wb.gif?v=1773599628"},{"product_id":"tropomyosin-1-antibody-sc-f1379","title":"Tropomyosin-1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTropomyosin-1 (TPM1) is an actin-binding protein from the tropomyosin family, expressed in various cell types. In muscle cells, TPM1 works with the troponin complex to regulate calcium-dependent muscle contraction, while in non-muscle cells, it stabilizes the cytoskeleton. The four TPM genes produce tropomyosin proteins, either 248 amino acids (low molecular weight) or 284 amino acids (high molecular weight). Depending on the literature source, TROPOMYOSIN-1 may also be discussed as Tropomyosin (Sarcomeric).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and cytoskeleton, which can matter when signal is compared across treatments or changing cell states. Following TROPOMYOSIN-1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTROPOMYOSIN-1 is commonly interpreted in the context of cancer, cardiovascular, and metabolism research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and cytoskeleton, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and cytoskeleton across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TROPOMYOSIN-1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TROPOMYOSIN-1 reflect biology rather than handling. When interpreting TROPOMYOSIN-1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TROPOMYOSIN-1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577713533273,"sku":"F1379-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577713566041,"sku":"F1379-100UL","price":319.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577713598809,"sku":"F1379-2X100UL","price":479.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1379-wb.gif?v=1773599668"},{"product_id":"lgals3-antibody-sc-f1417","title":"Galectin-3\/LGALS3 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eLGALS3 is a target of interest in many antibody-based workflows. Galectin-3 is a member of the lectin family, which plays a crucial role in various cellular processes, including cell-cell adhesion, cell-matrix interactions, and modulation of immune responses. Galectin-3, present in the extracellular matrix and circulation, interacts with integrin receptors and glycoproteins, playing a dual role in cell adhesion. Depending on the literature source, LGALS3 may also be discussed as Galectin-3\/LGALS3 and galectin-3.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, nucleus, secreted, and spliceosome, which can matter when signal is compared across treatments or changing cell states. Following LGALS3 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eLGALS3 is commonly interpreted in the context of immunology and cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, nucleus, and secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, nucleus, and secreted across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for LGALS3. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in LGALS3 reflect biology rather than handling. When interpreting LGALS3, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep LGALS3 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577728606553,"sku":"F1417-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577728639321,"sku":"F1417-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577728672089,"sku":"F1417-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1417-IF.png?v=1773599718"},{"product_id":"tie2-antibody-sc-f1427","title":"Tie2 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTie2, a tyrosine-protein kinase receptor predominantly found on vascular endothelial cells, is critical for maintaining vascular system stability. In humans, Tie2 interacts with three known ligands: angiopoietin-1 (Ang1), angiopoietin-2 (Ang2), and angiopoietin-4 (Ang4), all of which bind Tie2 with similar affinity. Ang1 activates Tie2 by stimulating its kinase activity, whereas Ang2 primarily acts as an antagonist to Ang1, though it can function as a partial agonist in certain contexts. Depending on the literature source, TIE2 may also be discussed as CD202b and TEK.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction, cell membrane, cytoplasm, and cytoskeleton, which can matter when signal is compared across treatments or changing cell states. Following TIE2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTIE2 is commonly interpreted in the context of cardiovascular, angiogenesis, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell junction, cell membrane, and cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell junction, cell membrane, and cytoplasm across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003edifferences related to endothelial activation, vessel remodeling, or growth-factor exposure\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TIE2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TIE2 reflect biology rather than handling. When interpreting TIE2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TIE2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577734078809,"sku":"F1427-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577734111577,"sku":"F1427-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577734144345,"sku":"F1427-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1427-wb.gif?v=1773599734"},{"product_id":"zyxin-antibody-sc-f1478","title":"Phospho-Zyxin (Ser142\/143) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePhospho-zyxin (Ser 142\/143) is the phosphorylated form of zyxin, a mechanosensitive LIM domain-containing focal adhesion protein critical for actin cytoskeleton organization and cell signaling. Expressed in various cell types, particularly endothelial and muscle cells, its phosphorylation at serine residues 142 and 143-mediated by kinases like PKA-enhances its interaction with actin filaments and focal adhesion components. Depending on the literature source, ZYXIN may also be discussed as Phospho-Zyxin (Ser142\/143).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction, cytoplasm, cytoskeleton, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following ZYXIN across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eZYXIN is commonly interpreted in the context of cardiovascular and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell junction, cytoplasm, and cytoskeleton, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell junction, cytoplasm, and cytoskeleton across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ZYXIN. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ZYXIN reflect biology rather than handling. When interpreting ZYXIN, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ZYXIN trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577759474009,"sku":"F1478-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577759506777,"sku":"F1478-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577759539545,"sku":"F1478-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1478-wb.gif?v=1773599798"},{"product_id":"nkcc1-antibody-sc-f1486","title":"NKCC1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe Na+-K+-2Cl− cotransport protein (e. g., NKCC1) is crucial for transporting Na+, K+, and Cl− in and out of cells, ensuring the proper functioning of physiological systems such as cardiac, vascular, renal, nervous, and sensory systems. NKCC1 also plays a role in regulating blood pressure and left ventricular pressure.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane and membrane, which can matter when signal is compared across treatments or changing cell states. Following NKCC1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eNKCC1 is commonly interpreted in the context of neuroscience, cardiovascular, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for NKCC1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in NKCC1 reflect biology rather than handling. When interpreting NKCC1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep NKCC1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577761800537,"sku":"F1486-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577761833305,"sku":"F1486-100UL","price":379.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577761866073,"sku":"F1486-2X100UL","price":569.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1486-IF.png?v=1773599809"},{"product_id":"ace2-antibody-sc-f1542","title":"ACE2 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eAngiotensin-converting enzyme 2 (ACE2) is a type I integral membrane protein that serves as a critical regulator of the renin-angiotensin system (RAS), playing a key role in blood pressure regulation and cardiovascular function. ACE2 was identified as the functional receptor for SARS-CoV and SARS-CoV-2, the viruses responsible for severe acute respiratory syndrome (SARS) and COVID-19, respectively.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell projection, cytoplasm, and membrane, which can matter when signal is compared across treatments or changing cell states. Following ACE2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eACE2 is commonly interpreted in the context of cardiovascular, infectious disease, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cell projection, and cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cell projection, and cytoplasm across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ACE2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ACE2 reflect biology rather than handling. When interpreting ACE2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ACE2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577771532633,"sku":"F1542-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577771565401,"sku":"F1542-100UL","price":399.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577771598169,"sku":"F1542-2X100UL","price":599.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1542-IHC1.jpg?v=1773599852"},{"product_id":"rock2-rock1-antibody-sc-f1558","title":"ROCK2 + ROCK1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eROCK2 + ROCK1 are serine\/threonine kinases of the AGC family that act as downstream effectors of the small GTPases RhoA, RhoB, and RhoC, regulating actin cytoskeleton dynamics, cell adhesion, motility, proliferation, and apoptosis. Structurally, both isoforms contain an N-terminal kinase domain, a coiled-coil region with a Rho-binding domain (RBD) that interacts with active Rho-GTP, and a C-terminal Pleckstrin homology (PH) domain that regulates autoinhibition. Depending on the literature source, ROCK2 + ROCK1 may also be discussed as ROCK2 + ROCK1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasm, cytoskeleton, and membrane, which can matter when signal is compared across treatments or changing cell states. Following ROCK2 + ROCK1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state. In practice, this target is often considered at the family or isoform-group level, so experimental interpretation benefits from matched controls and clear comparison logic.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eROCK2 + ROCK1 is commonly interpreted in the context of cancer, neuroscience, and cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cytoplasm, and cytoskeleton, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cytoplasm, and cytoskeleton across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ROCK2 + ROCK1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ROCK2 + ROCK1 reflect biology rather than handling. When interpreting ROCK2 + ROCK1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ROCK2 + ROCK1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577776742745,"sku":"F1558-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577776775513,"sku":"F1558-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577776808281,"sku":"F1558-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1558-wb.gif?v=1773599872"},{"product_id":"tnnt2-antibody-sc-f1576","title":"Cardiac Troponin T Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTNNT2 is a target of interest in many antibody-based workflows. Troponin, in conjunction with tropomyosin, acts as a molecular switch that regulates muscle contraction in response to changes in intracellular Ca2+ levels. It is composed of three subunits: the Ca2+-binding troponin C (TnC), the tropomyosin-binding troponin T (TnT), and the inhibitory troponin I (TnI). Upon β-adrenergic stimulation in the heart, troponin I (TnI) is phosphorylated at Ser23 and Ser24 by PKA and PKC. Depending on the literature source, TNNT2 may also be discussed as Cardiac Troponin T and Troponin T-C.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following TNNT2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTNNT2 is commonly interpreted in the context of cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within cytoplasm relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TNNT2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TNNT2 reflect biology rather than handling. When interpreting TNNT2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TNNT2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577782640985,"sku":"F1576-20UL","price":95.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577782673753,"sku":"F1576-100UL","price":289.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577782706521,"sku":"F1576-2X100UL","price":459.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1576-IHC1.jpg?v=1773599897"},{"product_id":"flt1-antibody-sc-f1598","title":"VEGF Receptor 1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eFLT1 is a target of interest in many antibody-based workflows. Vascular endothelial growth factor receptor 1 (VEGFR-1, also known as Flt-1) is a 180 kDa receptor tyrosine kinase that belongs to the VEGFR (Flt) family. The receptor structure includes seven extracellular Ig-like domains, a single transmembrane region, and a cytoplasmic tail containing an active kinase domain. Depending on the literature source, FLT1 may also be discussed as VEGF Receptor 1 and Vascular Endothelial Growth Factor Receptor-1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, endosome, secreted, and cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following FLT1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eFLT1 is commonly interpreted in the context of cardiovascular, angiogenesis, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, endosome, and secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, endosome, and secreted across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003edifferences related to endothelial activation, vessel remodeling, or growth-factor exposure\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for FLT1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in FLT1 reflect biology rather than handling. When interpreting FLT1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep FLT1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577789587801,"sku":"F1598-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577789620569,"sku":"F1598-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577789653337,"sku":"F1598-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1598-IHC1.jpg?v=1773599922"},{"product_id":"claudin-5-antibody-sc-f1668","title":"Claudin 5 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eClaudin 5 is a target of interest in many antibody-based workflows. Claudin-5, a member of the claudin multigene family, is a critical tight junction protein primarily found in endothelial cells of the brain, lungs, liver, kidney, and skin, with its highest expression in the brain. It plays a crucial role in maintaining the integrity of the blood-brain barrier (BBB) by forming tight junctions that restrict paracellular permeability to small molecules.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction and cell membrane, which can matter when signal is compared across treatments or changing cell states. Following Claudin 5 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eClaudin 5 is commonly interpreted in the context of neuroscience, cardiovascular, and developmental biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell junction and cell membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell junction and cell membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Claudin 5. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Claudin 5 reflect biology rather than handling. When interpreting Claudin 5, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Claudin 5 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577814819161,"sku":"F1668-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577814851929,"sku":"F1668-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577814884697,"sku":"F1668-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1668-IF.png?v=1773600006"},{"product_id":"cryab-antibody-sc-f1698","title":"α Crystallin B Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCRYAB (αB-Crystallin) is part of the small heat shock protein family (sHSP, also known as HSP20). Initially identified for its high expression in the eye lens, CRYAB is also abundant in heart and skeletal muscle tissues. It primarily functions as a molecular chaperone, helping to manage cellular stress by binding to unfolded proteins and preventing their aggregation. Depending on the literature source, CRYAB may also be discussed as alpha Crystallin B.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, lysosome, nucleus, and secreted, which can matter when signal is compared across treatments or changing cell states. Following CRYAB across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eCRYAB is commonly interpreted in the context of neuroscience, cardiovascular, and oxidative stress research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, lysosome, and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, lysosome, and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eredox-associated shifts that may alter abundance, localization, or pathway coupling\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for CRYAB. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in CRYAB reflect biology rather than handling. When interpreting CRYAB, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep CRYAB trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577822781785,"sku":"F1698-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577822814553,"sku":"F1698-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577822847321,"sku":"F1698-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1698-wb.gif?v=1773600039"},{"product_id":"myh6-antibody-sc-f1709","title":"heavy chain cardiac Myosin Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe myosin heavy chain is the major contractile protein of the sarcomeric thick filament and is a critical component to sustain muscle contraction. The heart muscle is composed of two myosin heavy chain isoforms, alpha (MYH6) and beta (MYH7), which exhibit distinct functional properties, with MYH7 predominantly expressed in the ventricles and associated with slower, more energy-efficient contractions compared to the faster alpha isoform found mainly in the atria. Depending on the literature source, MYH6 may also be discussed as heavy chain cardiac Myosin and Myosin Heavy Chain.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and thick filament, which can matter when signal is compared across treatments or changing cell states. Following MYH6 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eMYH6 is commonly interpreted in the context of cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and thick filament, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and thick filament across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for MYH6. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in MYH6 reflect biology rather than handling. When interpreting MYH6, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep MYH6 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577828843865,"sku":"F1709-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577828876633,"sku":"F1709-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577828909401,"sku":"F1709-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1709-wb.gif?v=1773600061"},{"product_id":"endothelial-cell-antibody-sc-f1713","title":"Endothelial Cell Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eEndothelial cells form a single, thin monolayer lining the interior surfaces of blood and lymphatic vessels, serving as a critical barrier between circulating fluids and surrounding tissues. They are connected by tight junctions and anchored to a basement membrane, with specialized surface proteins such as VE-cadherin and PECAM-1 that maintain vessel integrity and mediate immune cell interactions.\u003c\/p\u003e\u003cp\u003eFollowing Endothelial Cell across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eEndothelial Cell is commonly interpreted in the context of cancer and cardiovascular research, and readouts are often stronger when a study separates expression changes from broader shifts in cell state. A defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eWhere appropriate, pairing Endothelial Cell with orthogonal markers can improve confidence in interpretation, especially when experimental questions extend from baseline characterization into comparative or perturbation-driven studies.\u003c\/p\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Endothelial Cell. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Endothelial Cell reflect biology rather than handling. When interpreting Endothelial Cell, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Endothelial Cell trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577829040473,"sku":"F1713-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577829073241,"sku":"F1713-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577829106009,"sku":"F1713-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1713-IHC1.jpg?v=1773600064"},{"product_id":"tsp1-antibody-sc-f1912","title":"Thrombospondin 1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTSP1 is a large extracellular matrix glycoprotein forming a homotrimer via disulfide bonds, with each monomer containing distinct domains such as an N-terminal heparin-binding domain, procollagen-like domain, type 1 repeats (TSRs), type 2 EGF-like repeats, type 3 calcium-binding repeats, and a C-terminal globular domain. These domains facilitate interactions with cell surface receptors, including CD36, CD47, integrins, and extracellular matrix components, mediating diverse biological functions. Depending on the literature source, TSP1 may also be discussed as Thrombospondin 1 and Glycoprotein G.\u003c\/p\u003e\u003cp\u003eReported cellular context includes endoplasmic reticulum, extracellular matrix, sarcoplasmic reticulum, and secreted, which can matter when signal is compared across treatments or changing cell states. Following TSP1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTSP1 is commonly interpreted in the context of cancer, immunology, and cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans endoplasmic reticulum, extracellular matrix, and sarcoplasmic reticulum, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between endoplasmic reticulum, extracellular matrix, and sarcoplasmic reticulum across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TSP1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TSP1 reflect biology rather than handling. When interpreting TSP1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TSP1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577832153433,"sku":"F1912-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577832186201,"sku":"F1912-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577832218969,"sku":"F1912-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1912-IF.png?v=1773600077"},{"product_id":"anxa5-antibody-sc-f2106","title":"Annexin V\/ANXA5 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eANXA5 is a target of interest in many antibody-based workflows. Annexin V, or PAP-1 or Lipocortin V, is a ~30 kDa calcium-dependent phospholipid-binding protein that plays a crucial role in several biological processes, including membrane organization, coagulation, and anti-inflammatory responses. It inhibits the protein kinase C (PKC) pathway and regulates vascular endothelial cell proliferation by interacting with the VEGFR-2 receptor. Depending on the literature source, ANXA5 may also be discussed as Annexin V\/ANXA5 and Annexin V.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytosol, endothelial microparticle, and membrane, which can matter when signal is compared across treatments or changing cell states. Following ANXA5 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eANXA5 is commonly interpreted in the context of cardiovascular, angiogenesis, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytosol, and endothelial microparticle, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, cytosol, and endothelial microparticle across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003edifferences related to endothelial activation, vessel remodeling, or growth-factor exposure\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ANXA5. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ANXA5 reflect biology rather than handling. When interpreting ANXA5, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ANXA5 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577862955353,"sku":"F2106-20UL","price":159.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577862988121,"sku":"F2106-100UL","price":399.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577863020889,"sku":"F2106-2X100UL","price":599.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2106-IF.png?v=1773600176"},{"product_id":"ppp1cb-antibody-sc-f2108","title":"PPP1CB Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eProtein Phosphatase 1 Catalytic Subunit Beta (PPP1CB) is an essential serine\/threonine phosphatase isoform within the PP1 family, responsible for catalyzing more than half of all phosphoserine\/threonine dephosphorylation reactions in mammalian cells. PPP1CB regulates a wide range of critical cellular processes, including cell cycle progression, protein synthesis, muscle contractility, glycogen metabolism, neuronal signaling, apoptosis, and RNA splicing. Depending on the literature source, PPP1CB may also be discussed as Serine\/threonine-protein phosphatase PP1-beta catalytic subunit and PP-1B.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following PPP1CB across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePPP1CB is commonly interpreted in the context of neuroscience, cardiovascular, and metabolism research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PPP1CB. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PPP1CB reflect biology rather than handling. When interpreting PPP1CB, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PPP1CB trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577864102233,"sku":"F2108-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577864135001,"sku":"F2108-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577864167769,"sku":"F2108-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2108-IF.png?v=1773600179"},{"product_id":"tlr4-antibody-sc-f2122","title":"TLR4 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eToll-like receptor 4 (TLR4) is part of the pattern recognition receptor (PRR) family, which are highly conserved receptors that detect pathogen-associated molecular patterns (PAMPs). This makes them essential for the initial defense against infections. TLR4 is present on the cell surface of both hematopoietic and non-hematopoietic cells, including endothelial cells, cardiac myocytes, and cells within the central nervous system (CNS). Depending on the literature source, TLR4 may also be discussed as Toll-like Receptor 4.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell projection, endosome, and membrane, which can matter when signal is compared across treatments or changing cell states. Following TLR4 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTLR4 is commonly interpreted in the context of inflammation, cardiovascular, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cell projection, and endosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cell projection, and endosome across matched conditions\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TLR4. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TLR4 reflect biology rather than handling. When interpreting TLR4, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TLR4 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577870000473,"sku":"F2122-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577870033241,"sku":"F2122-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577870066009,"sku":"F2122-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2122-IF.png?v=1773600200"}],"url":"https:\/\/absource.de\/collections\/cardiovascular.oembed?page=68","provider":"Absource Diagnostics","version":"1.0","type":"link"}