Cold acclimation causes fiber type-specific responses in glucose and fat metabolism in rat skeletal muscles
Bibliographic record
Abstract
Abstract This study investigated fiber type-specific metabolic responses and the molecular mechanisms that regulate glucose and fat metabolism in oxidative and glycolytic muscles upon cold acclimation. Male Wistar rats were exposed to cold (4 °C) for 7 days, and then glycogen synthesis and content, glucose and palmitate oxidation, and the molecular mechanisms underlying these metabolic pathways were assessed in soleus (Sol), extensor digitorum longus (EDL), and epitrochlearis (Epit) muscles. Cold acclimation increased glycogen synthesis, glycogen content, glucose oxidation, and reduced glycogen synthase (GS) phosphorylation only in Sol muscles. Protein kinase B (AKT), glycogen synthase kinase 3 (GSK3), and AMP-activated protein kinase (AMPK) phosphorylation increased in all three muscles upon cold acclimation. Cold acclimation increased palmitate oxidation, gene expression of the transcriptional co-activator Pgc-1α, lipoprotein lipase (Lpl), fatty acid transporter (Cd36), and Sarco/endoplasmic reticulum Ca2+-ATPase (Serca) in Sol, EDL, and Epit muscles. Sarcolipin was only detected and had its content increased in Sol muscles. In conclusion, cold-induced thermogenesis activated similar signaling pathways in oxidative and glycolytic muscles, but the metabolic fate of glucose differed in skeletal muscles with distinct fiber type composition. Furthermore, only muscles rich in type I fibers appeared to have the capacity for sarcolipin-mediated SERCA uncoupling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.001 |
| 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".