Plasma adiponectin concentration is strongly associated with VLDL‐TG catabolism in postmenopausal women
Bibliographic record
Abstract
Objective: To investigate associations between plasma adiponectin concentration and VLDL‐TG secretion and catabolism in 30 postmenopausal women. Methods: Plasma adiponectin concentration was measured by ELISA. Insulin sensitivity was assessed by a 2‐h euglycemic‐hyperinsulinemic clamp. Fasting plasma glucose (FPG) and 2‐hour plasma glucose (2hPG) were measured during an OGTT. The VLDL‐TG total secretion rate (TSR) and the VLDL‐TG fractional catabolic rate (FCR) were measured by electron impact ionization gas chromatography‐mass spectrometry. The MIDA approach was used to measure VLDL‐TG TSR following a 10h‐infusion of [1‐ 13 C] acetate and the calculation of VLDL‐TG FCR was based on the monoexponential decrease of TG‐[ 2 H 5 ] glycerol values obtained following the administration of a 2 H 5 ‐glycerol bolus. Results: Plasma adiponectin concentration was negatively associated with VLDL‐TG TSR (r=−0.42; p<0.02) and positively with VLDL‐TG FCR (r=0.60; p<0.0005). This latter association remained significant after statistical adjustments for insulin sensitivity, HDL‐C, TG, FPG and 2hPG. In a multivariate model, plasma adiponectin level was the best predictor of VLDL‐TG FCR. Conclusion: Elevated plasma adiponectin concentration is associated with favourable VLDL‐TG metabolism. This study was supported by the Canadian Institutes of Health Research and the Heart and Stroke Foundation of Canada.
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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".