Temperature and serine phosphorylation regulate glycerol-3-phosphate dehydrogenase in skeletal muscle of hibernating Richardson’s ground squirrels
Bibliographic record
Abstract
Glycerol-3-phosphate dehydrogenase (G3PDH) bridges carbohydrate and lipid metabolism by interconverting glycerol-3-phosphate (G3P) and dihydroxyacetone phosphate (DHAP). This reversible reaction converts G3P derived from triglyceride hydrolysis to DHAP that can then enter glycolysis or gluconeogenesis and, in the reverse reaction, makes G3P for use in triglyceride biosynthesis. Small hibernating mammals rely almost exclusively on triglyceride reserves as their fuel for energy production during torpor and the recovery of glycerol after lipolysis is an important source of carbohydrate over the nonfeeding winter months. G3PDH (∼37 kDa) was purified from skeletal muscle of euthermic and hibernating Richardson's ground squirrels (Urocitellus richardsonii) using three column chromatography steps. Analysis of enzyme kinetic properties revealed that G3PDH from hibernator muscle had higher affinities for G3P and NAD at low (5 °C) assay temperature compared with high (21 or 37 °C) and a greater stability in the presence of denaturing agents (urea, guanidine hydrochloride) or high temperature (50 °C). Immunoblotting showed that hibernator muscle G3PDH had a higher phosphoserine content than the enzyme from euthermic controls and incubation studies showed that enzyme affinity for G3P changed significantly by stimulating endogenous protein kinases or phosphatases. Overall, this study suggests that the properties of ground squirrel muscle G3PDH are modulated by temperature and post-translational phosphorylation to alter enzyme function under euthermic versus hibernating states.
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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".