Partial deletion of ROCK2 protects mice from high-fat diet-induced cardiac insulin resistance and contractile dysfunction
Bibliographic record
Abstract
Obesity is associated with cardiac insulin resistance and contractile dysfunction, which contribute to the development of heart failure. The RhoA-Rho kinase (ROCK) pathway has been reported to modulate insulin resistance, but whether it is implicated in obesity-induced cardiac dysfunction is not known. To test this, wild-type (WT) and ROCK2(+/-) mice were fed normal chow or a high-fat diet (HFD) for 17 wk. Whole body insulin resistance, determined by an insulin tolerance test, was observed in HFD-WT, but not HFD-ROCK2(+/-), mice. The echocardiographically determined myocardial performance index, a measure of global systolic and diastolic function, was significantly increased in HFD-WT mice, indicating a deterioration of cardiac function. However, no change in myocardial performance index was found in hearts from HFD-ROCK2(+/-) mice. Speckle-tracking-based strain echocardiography also revealed regional impairment in left ventricular wall motion in hearts from HFD-WT, but not HFD-ROCK2(+/-), mice. Activity of ROCK1 and ROCK2 was significantly increased in hearts from HFD-WT mice, and GLUT4 expression was significantly reduced. Insulin-induced phosphorylation of insulin receptor substrate (IRS) Tyr(612), Akt, and AS160 was also impaired in these hearts, while Ser(307) phosphorylation of IRS was increased. In contrast, the increase in ROCK2, but not ROCK1, activity was prevented in hearts from HFD-ROCK2(+/-) mice, and cardiac levels of TNFα were reduced. This was associated with normalization of IRS phosphorylation, downstream insulin signaling, and GLUT4 expression. These data suggest that increased activation of ROCK2 contributes to obesity-induced cardiac dysfunction and insulin resistance and that inhibition of ROCK2 may constitute a novel approach to treat this condition.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".