Difference in leptin response to a high-fat meal between lean and obese men
Bibliographic record
Abstract
The aim of this study was to compare the leptin responses to a high-fat meal in lean and obese men, and to investigate whether the net leptin response (area under the incremental curve) after the meal was related to the thermic effect of food (TEF). Blood samples were collected after an overnight fast and every 2 h for 8 h after a high-fat breakfast (60 g of fat/m(2) body surface area) in 12 lean and 12 obese men for determination of glucose, insulin and leptin. The TEF was calculated as postprandial energy expenditure minus fasting energy expenditure, as measured by indirect calorimetry. Fasting plasma glucose levels were similar in lean and obese men, and increased in the same way after the meal. Fasting and postprandial plasma insulin concentrations were significantly greater in obese than in lean men (P<0.01 and P<0.05 respectively). Accordingly, obese men showed a significantly higher net insulin response than lean subjects (P<0.001). Fasting plasma leptin levels were greater in obese than in lean men (P<0.001). After the meal, plasma leptin increased significantly in lean men, whereas it decreased in obese men (group by time interaction, P<0.01). The net response of leptin was greater in lean than in obese men, but this did not reach statistical significance (P=0.07). Moreover, the TEF was similar in the two groups. No significant relationship was observed between either the net insulin response or the net leptin response after the high-fat meal and the TEF of lean subjects (-0.05 <r<0.31). In obese men, the net response of insulin was correlated significantly with TEF (r=0.70, P<0.05), whereas the net response of leptin was not (r=-0.40). These results suggest that obesity is related to an impaired regulation of leptin by insulin, since leptin levels increased in lean men but decreased in obese men following a high-fat meal. Moreover, the fact that the postprandial leptin responses of both lean and obese men were not significantly related to the TEF suggests that the ob gene product is probably not acutely involved in the control of this energy expenditure component in humans.
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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 | 0.001 |
| 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 | 0.000 |
| 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".