Metabolomics Reveals Metabolically Healthy and Unhealthy Obese Individuals Differ in their Response to a Caloric Challenge
Bibliographic record
Abstract
OBJECTIVE: To determine if metabolically healthy obese (MHO) individuals have a different metabolic response to a standardized diet compared to lean healthy (LH) and metabolically unhealthy obese (MUO) individuals. METHODS: Thirty adults (35-70 yrs) were classified as LH, MHO, and MUO according to anthropometric and clinical measurements. Participants consumed a standardized high calorie meal (~1330 kcal). Blood glucose and insulin were measured at fasting, and 15, 30, 60, 90 and 120 min postprandially. Additional blood samples were collected for the targeted analysis of amino acids (AAs) and derivatives, and fatty acids (FAs). RESULTS: The postprandial response (i.e., area under the curve, AUC) for serum glucose and insulin were similar between MHO and LH individuals, and significantly lower than MUO individuals (p < 0.05). Minor differences were found in postprandial responses for AAs between MHO and MUO individuals, while three polyunsaturated FAs (linoleic acid, γ-linolenic acid, arachidonic acid) showed smaller changes in serum after the meal in MHO individuals compared to MUO. Fasting levels for various AAs (notably branched-chain AA) and FAs (e.g., saturated myristic and palmitic acids) were found to correlate with glucose and insulin AUC. CONCLUSION: MHO individuals show preserved insulin sensitivity and a greater ability to adapt to a caloric challenge compared to MUO individuals.
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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 | 0.000 |
| 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".