Associations between Weight Loss-Induced Changes in Plasma Organochlorine Concentrations, Serum T3 Concentration, and Resting Metabolic Rate
Bibliographic record
Abstract
Organochlorine compounds are released from body fat into the bloodstream during weight loss. Because these compounds may impair thyroid status, which is implicated in the control of resting metabolic rate (RMR), the aim of this study was to determine if the augmentation in plasma organochlorine concentrations might be associated with the decrease in serum T(3) concentration and RMR observed in response to body weight loss. Plasma organochlorine concentrations, serum T(3) concentration, and RMR were measured before and after weight loss in 16 obese men who followed a nonmacronutrient-specific energy-restricted diet for 15 weeks. As expected, a significant decrease in serum T(3) concentration and RMR was observed after the program, whereas concentrations of most detected organochlorines were significantly increased. Changes in organochlorine concentrations were negatively associated with changes in serum T(3) concentration (significantly for p,p'-DDT, HCB, Aroclor 1260, PCB 28, PCB 99, PCB 118, and PCB 170) and with changes in RMR adjusted for weight loss (significantly for HCB and PCB 156). In conclusion, organochlorines released in plasma during weight loss are associated with the documented decrease in serum T(3) concentration and RMR. Further studies are needed to verify whether these findings are causally related.
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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) | 0.001 | 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".