Norepinephrine Infusion during Moderate-Intensity Exercise Increases Glucose Production and Uptake<sup>1</sup>
Bibliographic record
Abstract
A role for the increase in circulating norepinephrine (NE) during intense exercise [IE; > or = 80% maximum O(2) uptake (VO(2max))] in the marked increment in glucose rate of production (Ra) during IE is hypothesized. Seven fit male subjects (27 +/- 2 yr old; body mass index, 23 +/- 1 kg/m(2); VO(2max), 63 +/- 5 mL/kg.min) underwent 40 min of postabsorptive moderate-intensity (53% VO(2max)) cycle ergometer exercise (126 +/- 14 W), once without [control (CON)] and once with NE infusion (0.1 microg/kg.min) from 30-40 min (NE). With infusion, plasma NE reached 15.9 +/- 1.0 nM (8-fold rest, 2-fold CON). Ra doubled to 4.40 +/- 0.44 in CON, but rose to 7.55 +/- 0.68 mg/kg.min with NE infusion (P = 0.003). Ra correlated strongly (r(2) = 0.92, P < 0.02) with plasma NE during and immediately after infusion. With NE infusion, peak glucose uptake [rate of disappearance (Rd), 6.57 +/- 0.59 vs. 4.53 +/- 0.55 mg/kg.min, P < 0.02] and glucose metabolic clearance rate (P < 0.05) were higher than in CON. Glycemia rose minimally during the NE infusion but did not differ between groups at any time during exercise. Glucagon-to-insulin ratio increased minimally, and epinephrine increased approximately 2.5- to 3-fold at peak but did not differ between groups. Thus, NE infusion during moderate exercise led to increments in Ra and Rd in fit individuals, supporting a possible contributory role for the increase of plasma NE in IE. NE effects on Rd and metabolic clearance rate during exercise may differ from its effects at rest.
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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 | 0.000 |
| 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".