Glucokinase and hexokinase expression and activities in rainbow trout tissues: changes with food deprivation and refeeding
Bibliographic record
Abstract
The expression and activities of glucokinase (GK) and hexokinase (HK) were assessed in different tissues of rainbow trout (Oncorhynchus mykiss) under different feeding conditions (fed, fasted for 14 days, and refed for 7 days). Two different HK-I cDNAs were identified with different tissue distributions. One transcript named heart or H-HK-I was observed in the four brain regions assessed, white muscle, kidney, and gills but not in liver or erythrocytes. A second transcript named liver or L-HK-I was found in all tissues surveyed. GK mRNA was identified only in liver and the four brain regions. GK expression was altered by feeding conditions, especially in liver and hypothalamus where food deprivation decreased and re-feeding increased expression; changes in expression reflected activity changes and changes in tissue glycogen levels. In contrast, feeding conditions did not alter expression of either HK-I transcript but did alter tissue HK activities. The reduced phosphorylating capacity noted with food deprivation correlates primarily with changes in tissue HK, whereas increased capacity, as with refeeding, was associated with changes in GK; these changes fit with the different K(m) values of the GK and HK enzymes. These results provide evidence for the hypothalamus acting as a glucosensor in trout, as hyperglycemia produced increased GK expression and activity, as well as increased glycogen levels. Thus, even though trout use glucose poorly, none of the parameters tested here relate to this inability to use glucose and suggest that, at least, rainbow trout, if given an appropriate carbohydrate diet, could metabolically adjust to such a diet.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".