RIPC provides neuroprotection against ischemic stroke by suppressing apoptosis via the mitochondrial pathway
Bibliographic record
Abstract
Ischemic stroke is a common disease with high morbidity and mortality. Remote ischemic preconditioning (RIPC) can stimulate endogenous protection mechanisms by inducing ischemic tolerance to reduce subsequent damage caused by severe or fatal ischemia to non-ischemic organs. This study was designed to assess the therapeutic properties of RIPC in ischemic stroke and to elucidate their underlying mechanisms. Neurobehavioral function was evaluated with the modified neurological severity score (mNSS) test and gait analysis. PET/CT was used to detect the ischemic volume and level of glucose metabolism. The protein levels of cytochrome c oxidase-IV (COX-IV) and heat shock protein 60 (HSP60) were tested by Western blotting. TUNEL and immunofluorescence staining were used to analyze apoptosis and to observe the nuclear translocation and colocalization of apoptosis-inducing factor (AIF) and endonuclease G (EndoG) in apoptotic cells. Transmission electron microscopy (TEM) was used to detect mitochondrial-derived vesicle (MDV) production and to assess mitochondrial ultrastructure. The experimental results showed that RIPC exerted significant neuroprotective effects, as indicated by improvements in neurological dysfunction, reductions in ischemic volume, increases in glucose metabolism, inhibition of apoptosis, decreased nuclear translocation of AIF and EndoG from mitochondria and improved MDV formation. In conclusion, RIPC alleviates ischemia/reperfusion injury after ischemic stroke by inhibiting apoptosis via the endogenous mitochondrial pathway.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
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".