A Multicompartmental Model of In Vivo Adipose Tissue Glycerol Kinetics and Capillary Permeability in Lean and Obese Humans
Bibliographic record
Abstract
Lipolysis of adipose tissue triglycerides releases glycerol. Twenty-four volunteers, of whom 6 were obese and 13 were women, received a primed-constant infusion of 2H5-glycerol for 120 min during postabsorptive steady-state conditions. Arterial, abdominal venous, and interstitial (microdialysis) samples were taken, and a four-compartment model was applied to assess subcutaneous abdominal adipose tissue glycerol kinetics. Adipose tissue blood flow was measured using 133Xe washout. Venous glycerol concentrations (median 230 micromol/l [interquartile range 210-268]) were consistently greater than those of arterial blood (69.1 micromol/l [56.5-85.5]), while glycerol isotopic enrichments (tracer-to-tracee ratio) were greater in arterial blood (8.34% [7.44-10.1]) than venous blood (2.34% [1.71-2.69], P < 0.01). Microdialysate glycerol enrichment was 1.44% (1.11-1.79), indicating incomplete permeability of glycerol between capillary blood and interstitium. Calculated interstitial glycerol concentrations were between 270 micromol/l (256-350) and 332 micromol/l (281-371) (examining different boundary conditions). The calculated capillary diffusion capacity (ps) was between 2.21 ml . 100 g tissue(-1) . min(-1) (1.31-3.13) and 3.09 ml . 100 g tissue(-1) . min(-1) (1.52-4.90) and correlated inversely with adiposity (Rs< or = -0.45, P < 0.05). Our results support previous estimates of interstitial glycerol concentration within adipose tissue and reveal capillary diffusion capacity is reduced in obesity.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".