Abstract 179: Targeted Inhibition of Plasminogen Activator Inhibitor-1 Attenuates Weight Gain and Prevents Vascular Dysfunction Following a High Fat Diet
Bibliographic record
Abstract
Introduction: Elevated plasminogen activator inhibitor-1 (PAI-1) is associated with obesity, but there is controversy whether PAI-1 causes or is a consequence of obesity. We sought to determine whether targeted PAI-1 inhibition with a novel small molecule antagonist (TM5441) alters the development of obesity and/or obesity-induced vascular dysfunction in a diet-induced obesity model. Methods and Results: C57BL/6J mice were fed control, high fat diet (HFD), or high fat diet with TM5441 (HFD+TM5441) for 12 weeks. The HFD had marked weight gain (77±5%) as compared with control (32±2%). TM5441 significantly attenuated weight gain (49±8%, p=0.0075, Figure). HFD-induced hepatic triglyceride accumulation was attenuated by TM5441 (116±31 vs. 76±35 mg trig/g liver, p=0.03). Energy expenditure was reduced in the HFD compared to control (11.1±0.4 vs. 12.9±0.4 kcal/h/kg, p=0.005). However, HFD+TM5441 maintained a level of energy expenditure that was similar to control (13.2±0.6 kcal/h/kg, p=NS). The HFD group demonstrated higher systolic and diastolic blood pressure (141±3; 112±3 mm Hg) compared with control (122±7, 94±8; P<0.05 for both), while administration of TM5441 prevented diet-associated increase (120±6; 93±7 mm Hg, p=NS compared to control) at week 12. Pressure myography of mesenteric arteries in the HFD showed a significant rightward shift in the constrictor response to phenylephrine as compared to control (EC50: 14.5uM vs. 25.1uM, p=0.002). The HFD+TM5441 was similar to control (p=NS). Conclusions: Inhibition of PAI-1 with TM5441 attenuates weight gain, enhances energy expenditure, and prevents obesity-related vascular dysfunction in a murine model of obesity.
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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 | 0.000 |
| 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) | 0.004 | 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".