Prior treatment with the AMPK activator AICAR induces subsequently enhanced glucose uptake in isolated skeletal muscles from 24-month-old rats
Bibliographic record
Abstract
5′ AMP-activated protein kinase (AMPK) activation may be part of the exercise-induced process that enhances insulin sensitivity. Independent of exercise, acute prior treatment of skeletal muscles isolated from young rats with a pharmacological AMPK activator, 5-aminoimidazole-4-carboxamide-1-β-d-ribofuranoside (AICAR), causes subsequently improved insulin-stimulated glucose uptake (GU). However, efficacy of a single prior AICAR exposure on insulin-stimulated GU in muscles from old animals has not been studied. The purpose of this study was to determine whether brief, prior exposure to AICAR (3.5 h before GU assessment) leads to subsequently increased GU in insulin-stimulated skeletal muscles from old rats. Epitrochlearis muscles from 24-month-old male rats were isolated and initially incubated ±AICAR (60 min), followed by incubation without AICAR (3 h), then incubation ±insulin (50 min). Muscles were assessed for GU (via 3-O-methyl-[3H]-glucose accumulation) and site-specific phosphorylation of key proteins involved in enhanced GU, including AMPK, Akt, and Akt substrate of 160 kDa (AS160), via Western blotting. Prior ex vivo AICAR treatment resulted in greater GU by insulin-stimulated muscles from 24-month-old rats. Prior AICAR treatment also resulted in greater phosphorylation of AMPK (T172) and AS160 (S588, T642, and S704). Glucose transporter type 4 (GLUT4) protein abundance was unaffected by prior AICAR and/or insulin treatment. These findings demonstrate that skeletal muscles from older rats are susceptible to enhanced insulin-stimulated GU after brief activation of AMPK by prior AICAR. Consistent with earlier research using muscles from young rodents, increased phosphorylation of AS160 is implicated in this effect, which was not attributable to altered GLUT4 glucose transporter protein abundance.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 0.001 |
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".