Short-term obesity results in detrimental metabolic and cardiovascular changes that may not be reversed with weight loss in an obese dog model
Bibliographic record
Abstract
The time course of metabolic and cardiovascular changes with weight gain and subsequent weight loss has not been elucidated. The goal of the present study was to determine how weight gain, weight loss and altered body fat distribution affected metabolic and cardiovascular changes in an obese dog model. Testing was performed when the dogs were lean (scores 4-5 on a nine-point scale), after ad libitum feeding for 12 and 32 weeks to promote obesity (>5 score), and after weight loss. Measurements included serum glucose and insulin, plasma leptin, adiponectin and C-reactive protein, echocardiography, flow-mediated dilation and blood pressure. Body fat distribution was assessed by computed tomography. Fasting serum glucose concentrations increased significantly with obesity (P< 0·05). Heart rate increased by 22 (SE 5) bpm after 12 weeks of obesity (P= 0·003). Systolic left ventricular free wall thickness increased after 12 weeks of obesity (P= 0·002), but decreased after weight loss compared with that observed in the lean phase (P= 0·03). Ventricular free wall thickness was more strongly correlated with visceral fat (r 0·6, P= 0·001) than with total body fat (r 0·4, P= 0·03) and was not significantly correlated with subcutaneous body fat (r 0·3, P= 0·1). The present study provides evidence that metabolic and cardiovascular alterations occur within only 12 weeks of obesity in an obese dog model and are strongly predicted by visceral fat. These results emphasise the importance of obesity prevention, as weight loss did not result in the return of all metabolic indicators to their normal levels. Moreover, systolic cardiac muscle thickness was reduced after weight loss compared with the pre-obesity levels, suggesting possible acute adverse cardiovascular effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".