Extracellular hyperosmotic stress stimulates glucose uptake in incubated fast-twitch rat skeletal muscle
Bibliographic record
Abstract
The influence of hyperosmotic stress on glucose uptake, handling, and signaling processes remains unclear in mammalian skeletal muscle. Thus, the purpose of this study was to investigate alterations in glucose uptake and handling during extracellular hyperosmotic stress in isolated fast-twitch mammalian skeletal muscle. Using an established in vitro isolated whole-muscle model, extensor digitorum longus (EDL) muscles were dissected from male rats (4-6 weeks of age) and incubated (30-60 min) in an organ bath, containing Sigma Medium-199 with 8 mmol·L(-1) D-glucose, and mannitol was added to the targeted osmolalities (ISO, iso-osmotic, 290 mmol·kg(-1); HYPER, hyperosmotic, 400 mmol·kg(-1)). Results demonstrate that relative water content decreased in HYPER. HYPER resulted in significant alterations in muscle metabolite concentrations (lower glycogen, elevated lactate, and glucose-6-phosphate), suggesting a decrease in energy charge. Glucose uptake was also found to be higher in HYPER, and AS160 (implicated in insulin- and contraction-mediated glucose uptake) was found to be significantly more phosphorylated in HYPER than in ISO after 30 min. In conclusion, glucose uptake and handling is altered with hyperosmotic extracellular stress in the fast-twitch EDL. The increases in glucose uptake might be facilitated through alterations in AS160 signaling after 30 to 60 min of osmotic stress.
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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".