Ischemia/reperfusion‐induced myocardial injury in mice with diabetes mellitus: role of silent information regulator 1
Bibliographic record
Abstract
The aims of this study is to determine whether silent information regulator 1 (Sirt1) is involved in the increased susceptibility of the diabetic myocardium to ischemia/reperfusion‐induced (I/R) injury. Methods In vivo: mouse model of diabetes was induced by streptozotocin and myocardial levels of Sirt1 assessed (Western). In vitro: isolated cardiomyocytes were conditioned with high glucose (HG) followed by anoxia/reoxygenation (A/R) challenge. Myocyte Sirt1, Dynamin‐related protein 1 (Drp1) expression (Western) and myocyte apoptosis (Caspase 3 activity and cell death ELISA) were assessed. Results Myocardial levels of Sirt1 were decreased in mice with diabetes. Sirt1 expression in myocytes with HG was down‐regulated. Myocytes with HG incurred reduced Drp1 S637 phosphorylation and increased apoptosis as compared to naive myocytes challenged with A/R. The effects were prevented by pretreatment of the myocytes with Sirt1 activator or over‐expression of Sirt1 in cardiomyocytes with HG. Conclusion Increased vulnerability of diabetic myocardium to I/R injury may be attributed to decreased Sirt1 and subsequent Drp1 activation. (*Corresponding author) Support or Funding Information IRF of Lawson Health Research Institute (IRF 2014‐25); National Natural Science Foundation of China (81370333); Natural Science Foundation of Jiangsu Province, China (BK2015‐1332)
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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) | 0.002 | 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".