Neuronal apoptosis inhibitory protein is expressed in developing kidney and is regulated by PAX2
Bibliographic record
Abstract
During fetal kidney development, the extent of ureteric bud (UB) branching will determine final nephron endowment for life. Nephron number varies widely among normal humans and those who are born at the low end of the nephron number spectrum may be at risk for essential hypertension in adulthood. Little is known about how nephron number is set. However, we previously showed that the transcription factor, Pax2, suppresses apoptosis in UB cells during kidney development and optimizes branching morphogenesis. Here, we report that PAX2 directly binds to a specific recognition motif in the human neuronal apoptosis inhibitory protein (NAIP) gene promoter. NAIP is an endogenous inhibitor of apoptosis, inactivating caspase-3 and caspase-7 in neuronal tissues. PAX2 activates NAIP gene transcription (7-fold) in vitro and NAIP transcript level is increased fourfold in HEK293 cells stably transfected with PAX2. We show that Naip is expressed in embryonic day 15 (E15) fetal kidney tissue (RT-PCR) and NAIP protein is demonstrated by immunohistochemistry in E15 mouse kidney collecting ducts and P1 proximal tubules. Naip mRNA is significantly reduced (50%) in heterozygous Pax2 mutant mice. Finally, we show that an antisense Naip1 cDNA transfected into murine collecting duct cells doubles caspase-3/7 activity induced by Baxalpha. These observations suggest that the powerful effects of PAX2 on renal branching morphogenesis and final nephron number may be mediated by activation of Naip which then suppresses apoptosis in UB cells.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 0.000 |
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".