The Risk of Heart Failure and Cardiometabolic Complications in Obesity May Be Masked by an Apparent Healthy Status of Normal Blood Glucose
Bibliographic record
Abstract
Although many obese individuals are normoglycemic and asymptomatic of cardiometabolic complications, this apparent healthy state may be a misnomer. Since heart failure is a major cause of mortality in obesity, we investigated the effects of heme-oxygenase (HO) on heart failure and cardiometabolic complications in obese normoglycemic Zucker-fatty rats (ZFs). Treatment with the HO-inducer, hemin, reduced markers of heart failure, such as osteopontin and osteoprotegerin, abated left-ventricular (LV) hypertrophy/fibrosis, extracellular matrix/profibrotic proteins including collagen IV, fibronectin, TGF-β1, and reduced cardiac lesions. Furthermore, hemin suppressed inflammation by abating macrophage chemoattractant protein-1, macrophage-inflammatory protein-1 alpha, TNF-α, IL-6, and IL-1β but enhanced adiponectin, atrial-natriuretic peptide (ANP), HO activity, insulin sensitivity, and glucose metabolism. Correspondingly, hemin improved several hemodynamic/echocardiographic parameters including LV-diastolic wall thickness, LV-systolic wall thickness, mean-arterial pressure, arterial-systolic pressure, arterial-diastolic pressure, LV-developed pressure, +dP/dt, and cardiac output. Contrarily, the HO-inhibitor, stannous mesoporphyrin nullified the hemin effect, exacerbating inflammatory/oxidative insults and aggravated insulin resistance (HOMA-index). We conclude that perturbations in insulin signaling and cardiac function may be forerunners to overt hyperglycemia and heart failure in obesity. Importantly, hemin improves cardiac function by suppressing markers of heart failure, LV hypertrophy, cardiac lesions, extracellular matrix/profibrotic proteins, and inflammatory/oxidative mediators, while concomitantly enhancing the HO-adiponectin-ANP axis.
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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) | 0.000 | 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".