Total Postprandial Hepatic Nonesterified and Dietary Fatty Acid Uptake Is Increased and Insufficiently Curbed by Adipose Tissue Fatty Acid Trapping in Prediabetes With Overweight
Bibliographic record
Abstract
Excessive lean tissue uptake of fatty acids (FAs) is important in the development of insulin resistance and may be caused by impaired dietary FA (DFA) storage and/or increased nonesterified FA (NEFA) flux from adipose tissue intracellular lipolysis. Cardiac and hepatic total postprandial FA uptake of NEFA+DFA has, however, never been reported in prediabetes with overweight. In this study, 20 individuals with impaired glucose tolerance (IGT) and 19 participants with normal glucose tolerance (NGT) and normal fasting glucose underwent postprandial studies with whole-body positron emission tomography/computed tomography (PET/CT) with oral [18F]fluoro-thia-heptadecanoic acid and dynamic PET/CT with intravenous [11C]palmitate. Hepatic (97 [range 36-215] mmol/6 h vs. 68 [23-132] mmol/6 h, P = 0.03) but not cardiac (11 [range 4-24] mmol/6 h vs. 8 [3-20] mmol/6 h, P = 0.09) uptake of most sources of postprandial FA (NEFA + DFA uptake) integrated over 6 h was higher in IGT versus NGT. DFA accounted for lower fractions of total cardiac (21% [5-47] vs. 25% [9-39], P = 0.08) and hepatic (19% [6-52] vs. 28% [14-50], P = 0.04) uptake in IGT versus NGT. Increased adipose tissue DFA trapping predicted lower hepatic DFA uptake and was associated with higher total cardiac FA uptake. Hence, enhanced adipose tissue DFA trapping in the face of increased postprandial NEFA flux is insufficient to fully curb increased postprandial lean organ FA uptake in prediabetes with overweight (ClinicalTrials.gov; NCT02808182).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".