Bibliographic record
Abstract
PURPOSE OF REVIEW: Experimental evidences are strong for a role of long-chain saturated fatty acids in the development of insulin resistance and type 2 diabetes. Ectopic accretion of triglycerides in lean organs is a characteristic of prediabetes and type 2 diabetes and has been linked to end-organ complications. The contribution of disordered dietary fatty acid (DFA) metabolism to lean organ overexposure and lipotoxicity is still unclear, however. DFA metabolism is very complex and very difficult to study in vivo in humans. RECENT FINDINGS: We have recently developed a novel imaging method using PET with oral administration of 14-R,S-F-fluoro-6-thia-heptadecanoic acid (FTHA) to quantify organ-specific DFA partitioning. Our studies thus far confirmed impaired storage of DFA per volume of fat mass in abdominal adipose tissues of individuals with prediabetes. They also highlighted the increased channeling of DFA toward the heart, associated with subclinical reduction in cardiac systolic and diastolic function in individuals with prediabetes. SUMMARY: In the present review, we summarize previous work on DFA metabolism in healthy and prediabetic states and discuss these in the light of our novel findings using PET imaging of DFA metabolism. We herein provide an integrated view of abnormal organ-specific DFA partitioning in prediabetes 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".