Effect of cold exposure on fuel utilization in humans: plasma glucose, muscle glycogen, and lipids
Bibliographic record
Abstract
The relative roles of circulatory glucose, muscle glycogen, and lipids in shivering thermogenesis are unclear. Using a combination of indirect calorimetry and stable isotope methodology ([U-13C]glucose ingestion), we have quantified the oxidation rates of these substrates in men acutely exposed to cold for 2 h (liquid conditioned suit perfused with 10 degrees C water). Cold exposure stimulated heat production by 2.6-fold and increased the oxidation of plasma glucose from 39.4 +/- 2.4 to 93.9 +/- 5.5 mg/min (+138%), of muscle glycogen from 126.6 +/- 7.8 to 264.2 +/- 36.9 mg glucosyl units/min (+109%), and of lipids from 46.9 +/- 3.2 to 176.5 +/- 17.3 mg/min (+376%). Despite the observed increase in plasma glucose oxidation, this fuel only supplied 10% of the energy for heat generation. The major source of carbohydrate was muscle glycogen (75% of all glucose oxidized), and lipids produced as much heat as all other fuels combined. During prolonged, low-intensity shivering, we conclude that total heat production is unequally shared among lipids (50%), muscle glycogen (30%), plasma glucose (10%), and proteins (10%). Therefore, future research should focus on lipids and muscle glycogen that provide most of the energy for heat production.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".