Preconditioning with morphine protects hippocampal CA1 neurons from ischemia–reperfusion injury via activation of the mTOR pathway
Bibliographic record
Abstract
The signaling pathway of chronic morphine treatment to prevent neuronal damage following transient cerebral ischemia is not clear. In this study, we examined the role of mammalian target of rapamycin (mTOR) to identify the neuroprotective effects of chronic morphine preconditioning on the hippocampus following ischemia-reperfusion (I/R) injury. Morphine was administered for 5 days, twice a day, before inducing I/R injury. The possible role of mTOR was evaluated by the injection of rapamycin (5 mg/kg body weight, by intraperitoneal injection) before I/R was induced. The passive avoidance test was used to evaluate memory performance. Neuronal density and apoptosis were measured in the CA1 region, 72 h after I/R injury. The expressions of mTOR and phosphorylated mTOR (p-mTOR), as well as superoxide dismutase (SOD) activity were determined 24 h after I/R injury. Chronic morphine treatment attenuated apoptosis and neuronal loss in the hippocampus after I/R injury, which led to improvement in memory (P < 0.05 vs. untreated I/R) and increase in the expression of p-mTOR (P < 0.05 vs. untreated I/R) and SOD activity (P < 0.05 vs. untreated I/R) in the hippocampus. Pretreatment with rapamycin abolished all the above-mentioned protective effects. These results describe novel findings whereby chronic morphine preconditioning in hippocampal CA1 neurons is mediated by the mTOR pathway, and through increased phosphorylation of mTOR can alleviate oxidative stress and apoptosis, and eventually protect the hippocampus from I/R injury.
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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 | 0.001 |
| 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".