Neuronal expression and regulation of rat inhibitor of apoptosis protein‐2 by kainic acid in the rat brain
Bibliographic record
Abstract
Inhibitors of apoptosis proteins (IAPs) define a protein family with the ability to counteract cell death by the inhibition of different caspases activated during apoptosis. These proteins are present in different cells, however, the function and roles of IAPs in brain tissue are not fully understood. We report here that RIAP-2, the rat homologue of human cIAP-1/HIAP-2, is expressed in different areas of rat brain as shown by in situ hybridization and immunohistochemistry. Brain regions with relatively high expression of RIAP-2 mRNA included cortex, cerebellum and different subregions of rat hippocampus. Double labelling using a specific anti-RIAP antibody and markers for neurons and glial cells, showed that RIAP-2 is predominantly expressed by nerve cells. Kainic acid treatment, which induces seizures, transiently up-regulated RIAP-2 mRNA levels in cerebral cortex, in the CA1 and dentate gyrus regions of hippocampus, which returned to normal levels at 24 h. However in the CA3 region, RIAP-2 mRNA was decreased at 6 h following an early up-regulation. This region contains neurons particularly vulnerable to kainic acid induced cell degeneration. The decrease in RIAP-2 following kainic acid was also observed using immunohistochemistry. RIAP-2 protein did not colocalize with TUNEL labelling present in cells undergoing cell death. The results show that in the adult rat brain RIAP-2 is expressed mainly by neurons, and that the levels are regulated by kainic acid, which activates glutamate receptors. The decrease in RIAP-2 in specific neuronal populations may contribute to cell degeneration in vulnerable brain regions observed after kainic acid treatment.
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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".