Combined Infusion of Epinephrine and Norepinephrine During Moderate Exercise Reproduces the Glucoregulatory Response of Intense Exercise
Bibliographic record
Abstract
Intense exercise (IE) (>80% O(2max)) causes a seven- to eightfold increase in glucose production (R(a)) and a fourfold increase in glucose uptake (R(d)), resulting in hyperglycemia, whereas moderate exercise (ME) causes both to double. If norepinephrine (NE) plus epinephrine (Epi) infusion during ME produces the plasma levels and R(a) of IE, this would prove them capable of mediating these responses. Male subjects underwent 40 min of 53% O(2max) exercise, eight each with saline (control [CON]), or with combined NE + Epi (combined catecholamine infusion [CCI]) infusion from min 26-40. In CON and CCI, NE levels reached 7.3 +/- 0.7 and 33.1 +/- 2.9 nmol/l, Epi 0.94 +/- 0.08 and 7.06 +/- 0.44 nmol/l, and R(a) 3.8 +/- 0.4 and 12.9 +/- 0.8 mg. kg(-1). min(-1) (P < 0.001), respectively, at 40 min. R(d) increased to 3.5 +/- 0.4 vs. 11.2 +/- 0.8 mg. kg(-1). min(-1) and glycemia 5.2 +/- 0.2 mmol/l in CON vs. 6.5 +/- 0.2 mmol/l in CCI (P < 0.001). The glucagon-to-insulin ratio did not differ. Comparing CCI data to those from 14-min IE (n = 16), peak NE (33.6 +/- 5.1 nmol/l), Epi (5.32 +/- 0.93 nmol/l), and R(a) (13.0 +/- 1.0 mg. kg(-1). min(-1)) were comparable. The induced increments in NE, Epi, and R(a), all of the same magnitude as in IE, strongly support that circulating catecholamines can be the prime regulators of R(a) in IE.
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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 | 0.001 |
| 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".