Analyzing the anti-ischemia–reperfusion injury effects of ginsenoside Rb1 mediated through the inhibition of p38α MAPK
Bibliographic record
Abstract
Recent studies have demonstrated that ginsenoside Rb1 protects the myocardium from ischemia-reperfusion (I/R) injury. However, the precise mechanisms for this protection have not been determined. This study aimed to determine whether the attenuation of I/R-induced myocardial injury by ginsenoside Rb1 (GS Rb1) is due to inhibition of p38α mitogen-activated protein kinase (MAPK). Sprague-Dawley rats were distributed among 6 treatment groups: sham group; I/R group; p38 MAPK inhibitor SB203580 group (SB + I/R); GS Rb1 group (GS + I/R); p38 MAPK agonist anisomycin group (Ani + I/R); and the GS Rb1 + Ani group (GS + Ani + I/R). All of the anaesthetized rats, except those in the sham group, underwent an open-chest procedure that involved 30 min of myocardial ischemia followed by 2 h of reperfusion. Myocardial infarction size (MIS), caspase-3 activity, and levels of the cytokine tumor necrosis factor alpha (TNF-α) in the myocardium were monitored. The expressions of p38α MAPK, caspase-3, and TNF-α in the myocardium were assayed. GS Rb1 reduced MIS and attenuated caspase-3 activity and the levels of TNF-α in the myocardium. Protein expression of total p38α MAPK was not significantly altered. In the Ani + I/R and I/R groups, the levels of phospho-p38α MAPK were significantly increased compared with the sham group, and these increased levels were reduced with GS Rb1. Hemodynamic parameters were not significantly different between the GS + I/R and SB + I/R groups. GS Rb1 exerts an anti-apoptotic effect that protects against I/R injury by inhibiting p38α MAPK phosphorylation, suggesting that GS Rb1-mediated protection requires the inhibition of p38α MAPK.
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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) | 0.000 | 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".