Glucagon‐like peptide‐1 receptor is a regulator of glucose clearance in oxidative tissues independent of insulin
Bibliographic record
Abstract
Activation of the glucagon‐like peptide‐1 receptor (GLP‐1R) stimulates insulin secretion. GLP‐1R also plays a role in the control of glucose homeostasis via mechanisms that are independent of this incretin action. Exercise was used to unmask glucoregulatory properties of GLP‐1R related to increased insulin‐independent glucose flux. Wild type (WT) and GLP‐1R knockout (KO) mice (n=7–8) were catheterized in the carotid artery (sampling) and jugular vein (infusion). 7 days later, 5h fasted mice underwent treadmill exercise (30 min @ 16.6 m/min) or remained sedentary. Fasting glucose (mg/dL) was higher in KO than WT (233±6 vs 198±9) and rose with exercise in KO but not WT (263±16 vs 201±11). Tissue glucose clearance (Kg μl/g tissue /min) was determined using 2[ 3 H]deoxyglucose. Sedentary heart Kg was higher in KO than WT (84±17 vs 48±11) and did not increase further with exercise (ΔKg 6±14 vs 76±19). Sedentary diaphragm Kg was equal in WT and KO and increased with exercise in KO but not WT (ΔKg 29±10 vs 2±5). Insulin levels were equal in both groups. Oxygen consumption (VO 2 , ml/kg/min) was equal in WT and KO at rest but was higher in KO during moderate (75% VO 2 max 103±3 vs 121±4) and maximal (VO 2 max 132±4 vs 141±2) exercise. In summary, deletion of GLP‐1R leads to a) elevated sedentary cardiac glucose uptake to levels observed in exercised WT mice and b) increased diaphragm glucose uptake and higher VO 2 during exercise. Thus exercise studies reveal the insulin‐independent glucoregulatory properties of GLP‐1R. Supported by DK50277.
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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".