β <sub>3</sub> -adrenergic browning of pericardial adipose tissue controls cardiac function
Bibliographic record
Abstract
Abstract Dysfunctional adipose tissue (AT) is strongly linked to the development of cardiovascular diseases (CVD). Accumulation of AT around vital organs is detrimental to their respective function and overall health. Although there is strong evidence linking the accumulation of pericardial AT with CVD development, a comprehensive investigation on the adaptation of pAT in obesity is scarce. Here, by applying pair-wise bottom-up proteomics in pAT of humans and mice, we found pAT presents a browning signature, as demonstrated by enrichment of mitochondria, presence of UCP1, and greater metabolic capacity compared to subcutaneous AT. In mice fed a high-fat diet or obese patients, the pAT undergoes whitening, characterized by adipocyte hypertrophy, reduced mitochondrial content, respiratory capacity, and UCP1 levels. Lipectomy of pAT from obese mice decreased pathological ventricular hypertrophy. Conversely, selective β 3 -adrenergic agonist treatment rescued pAT browning status and is associated with improved heart structure and function, including ventricular thickness, and fibrosis in obese mice. Importantly, lipectomy of pAT abrogated the positive effects of β 3 -adrenergic agonism in cardiac function of obese mice. Altogether, our work positions pAT as a mechanistic driver of obesity-related cardiac dysfunction and establish β 3 -adrenergic-mediated browning of pAT as a novel therapeutic treatment strategy.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".