Distribution of Neuronal Apoptosis Inhibitory Protein in Human Tissues
Bibliographic record
Abstract
The neuronal apoptosis inhibitory protein (NAIP) gene, also known as the baculovirus inhibitor of apoptosis repeat-containing protein 1 (BIRC1) gene, is a member of the inhibitors of apoptosis (IAP) family and was first characterized as a candidate gene for spinal muscular atrophy (SMA). The expression of NAIP has been thoroughly studied in the central nervous system and overlaps the pattern of neurodegeneration in SMA. Recent studies have pointed to a role for NAIP in non-neuronal cells. We report here the production of a specific anti-NAIP antibody and the profile of NAIP expression in human adult tissues by Western blot and immunohistochemical detection methods. NAIP was detected in a number of tissues by Western blot analysis, but immunohistochemistry revealed that NAIP's presence in certain tissues, such as liver, lung, and spleen, is most likely due to macrophage infiltration. In the small intestine, the expression of NAIP coincides with the expression of p21(WAF1). This observation, coupled with findings from other groups, suggests a role for NAIP in increasing the survival of cells undergoing terminal differentiation as well as the possibility that the protein serves as an intestinal pathogen recognition protein. This manuscript contains online supplemental material at http://www.jhc.org. Please visit this article online to view these materials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".