Higher Fasting and Postprandial Free Fatty Acid Levels Are Associated With Higher Muscle Insulin Resistance and Lower Insulin Secretion in Young Non-Obese Women
Bibliographic record
Abstract
BACKGROUND: To assess the relationship of the shape of glucose concentration curve during a standardized meal test to serum free fatty acid (FFA) concentrations, insulin resistance and insulin secretion in young non-obese women. METHODS: Thirty-five young women had a standardized meal for breakfast with measurement of glucose, insulin and FFA concentrations at 0 (fasting), 30, 60 and 120 min; the areas under the concentration curves were calculated (AUCg, AUCi and AUCffa, respectively). Meal-induced insulin response (MIR) was calculated as the ratio between the incremental insulin and glucose concentrations during the first 30 min of meal tests. In two women (group A), post-breakfast glucose (PBG) returned to levels below fasting plasma glucose (FPG) at 30 min; in 15 and 11 women, PBG returned to levels below FPG at 60 and 120 min (groups B and C, respectively). In the remaining seven women (group D), PBG never fell below FPG. RESULTS: Despite no difference in fasting insulin and AUCi, fasting FFA, AUCg and AUCffa were the lowest in group A, increased linearly from group B to C and plateaued in group D, whereas MIR might be the highest in group A, decreased from group B to C and plateaued in group D. CONCLUSION: Young women whose PBG returned to FPG more slowly had higher muscle insulin resistance and lower MIR associated with higher fasting and postprandial FFA levels compared with young women whose PBG returned to baseline more quickly.
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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) | 0.002 | 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".