AIF Antibody

About the Target

AIFM1 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.

Reported 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.

Research Context

AIFM1 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.

Consider these angles when interpreting target-level changes:

• apparent redistribution between cytoplasm, membrane, and mitochondrion across matched conditions
• compartment-specific patterns relevant to neuronal polarity, transport, or synaptic context
• changes linked to vascular, contractile, or hemodynamic cell-state cues
• responses linked to nutrient status, mitochondrial state, or metabolic rewiring

Variant Considerations

If 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.

Standardize 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.

For 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.