Low temperature directly activates the initial glycerol antifreeze response in isolated rainbow smelt (<i>Osmerus mordax</i>) liver cells
Bibliographic record
Abstract
Rainbow smelt (Osmerus mordax) accumulate high levels of glycerol in winter that serve as an antifreeze. Liver glycogen is a source of glycerol during the early stages of glycerol accumulation, whereas dietary glucose and amino acids are essential to maintain rates of glycerol synthesis. We presently report rates of glycerol and glucose production by isolated hepatocytes. Cells from fish held at 0.4 to -1.5 degrees C and incubated at 0.4 degrees C were metabolically quiescent with negligible rates of glycerol or glucose production. Hepatocytes isolated from fish maintained at 8 degrees C and incubated at 8 degrees C produced glucose but not glycerol. Glycerol production was activated in cells isolated from 8 degrees C fish and incubated at 0.4 degrees C without substrate or when glucose, aspartate, or pyruvate was available in the medium. Incubation at 0.4 degrees C without substrate resulted in similar molar rates of glucose and glycerol production in concert with glycogen mobilization. Glycogenolysis and glycerol production were associated with increases in total in vitro activities of glycogen phosphorylase and glycerol-3-phosphate dehydrogenase. Maximal in vitro activities of hexokinase and glucokinase were not influenced by temperature, but high activities of a low-K(m) hexokinase may serve to redirect glycogen-derived glucose to glycolysis as opposed to releasing it from the cells. Rates of glycerol production were not enhanced in cells from fish held at 8 degrees C and incubated at 0.4 degrees C with adrenergic or glucocorticoid stimulation. As such, low temperature alone is sufficient to activate the glycerol production mechanism and results in a shift from glucose to a mix of glucose and glycerol production.
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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".