Organ-specific dietary fatty acid uptake in humans using positron emission tomography coupled to computed tomography
Bibliographic record
Abstract
A noninvasive method to determine postprandial fatty acid tissue partition may elucidate the link between excess dietary fat and type 2 diabetes. We hypothesized that the positron-emitting fatty acid analog 14(R,S)-[(18)F]fluoro-6-thia-heptadecanoic acid ((18)FTHA) administered orally during a meal would be incorporated into chylomicron triglycerides, allowing determination of interorgan dietary fatty acid uptake. We administered (18)FTHA orally at the beginning of a standard liquid meal ingested in nine healthy men. There was no significant (18)FTHA uptake in the portal vein and the liver during the 1st hour. Whole body PET/CT acquisition revealed early appearance of (18)FTHA in the distal thoracic duct, reaching a peak at time 240 min. (18)FTHA mean standard uptake value increased progressively in the liver, heart, quadriceps, and subcutaneous and visceral adipose tissues between time 60 and 240 min. Most circulating (18)F activity between time 0 and 360 min was recovered into chylomicron triglycerides. Using Triton WR-1339 treatment in rats that received (18)FTHA by gavage, we confirmed that >90% of this tracer reached the circulation as triglycerides. This novel noninvasive method to determine tissue dietary fatty acid distribution in humans should prove useful in the study of the mechanisms leading to lipotoxicity.
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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".