Analysis of Interleukin-1β-induced Cell Signaling Activation in Rat Hippocampus following Exposure to Gamma Irradiation
Bibliographic record
Abstract
Among the many reported effects of irradiation in cells is activation of the stress-activated protein kinase, c-Jun N-terminal kinase (JNK), which has been shown to result in apoptotic cell death. The trigger that leads to JNK activation has not been identified, although, in rat hippocampus at least, irradiation-induced apoptosis has been coupled with increased accumulation of reactive oxygen species (ROS). Significantly, irradiation-induced changes in hippocampus are abrogated by treatment of rats with the polyunsaturated fatty acid, eicosapentaenoic acid (EPA). A close coupling between ROS accumulation and concentration of the pro-inflammatory cytokine, interleukin-1 beta (IL-1 beta) in hippocampus has been reported, and the evidence suggests that IL-1 beta may be responsible for the enhanced ROS production. Here we set out to assess the possibility that whole body gamma-irradiation increases IL-1 beta concentration in hippocampus and to investigate the consequences of such a change. We present evidence that reveals that the irradiation-induced increase in IL-1 beta concentration in hippocampus is accompanied by increased expression of IL-1 type I receptor and IL-1 accessory protein and increased activation of IL-1 receptor-activated kinase. These changes, which were coupled with increased activation of JNK and evidence of apoptotic cell death, were absent in hippocampus of rats that received EPA treatment. Significantly, EPA treatment enhanced hippocampal IL-10 concentration that was inversely correlated with IL-1 beta concentration. The data are consistent with the idea that EPA exerts anti-inflammatory and neuroprotective effects in the central nervous system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".