Low <i>n</i>-6/<i>n</i>-3 PUFA ratio improves inflammation and myocardial ischemic reperfusion injury
Bibliographic record
Abstract
This study investigated the potential effect of n-6/n-3 polyunsaturated fatty acids (PUFA) on inflammation and myocardial ischemic reperfusion injury (MIRI) in rats, together with the underlying protective mechanisms, and screen out most effective ratio of n-6/n-3 within limits. The rats with pre-infarct treatment were distributed among 5 groups according to the n-6/n-3 ratio (36:1; 1:1, 5:1, 10:1, 50:1); for the post-infarct treatment, the rats were distributed among 6 groups, including the control group (36:1) which was subjected to a sham procedure; the model group (36:1); and 4 test groups (n-6/n-3 ratio: 1:1, 5:1, 10:1, 50:1). All of the rats were fed a purple perilla seed oil and safflower oil-based fatty emulsion. The serum levels of monocyte chemoattractant protein-1 (MCP-1), interleukin (IL)-1β, IL-6, and tumor necrosis factor (TNF)-α were determined using enzyme-linked immunosorbent assay. Staining with triphenyl tetrazolium chloride, hematoxylin and eosin, or Masson’s trichrome was performed for histological examination. Cardiomyocyte apoptosis was examined by TUNEL assay. Western blotting was performed to examine the expression levels of apoptosis-related proteins and signaling pathway proteins. Our data indicate that in both the pre-infarct treatment and post-infarct treatment, low ratios of n-6/n-3 PUFAs significantly inhibited the levels of serum inflammatory factors, the infarct size of MIRI rats, number of cardiomyocytes undergoing apoptosis, and the expression levels of caspase-3, Bcl-2, and Bax in the MIRI group. Thus a low ratio of n-6/n-3 PUFAs ameliorates inflammation and myocardial ischemic reperfusion 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".