Bibliographic record
Abstract
Current understanding of lactate metabolism in fish is based almost entirely on the interpretation of concentration measurements that cannot be used to infer changes in flux. The goals of this investigation were: (1) to quantify baseline lactate fluxes in rainbow trout (Oncorhynchus mykiss) under normoxic conditions; (2) to establish how changes in rates of lactate appearance (R(a)) and disposal (R(d)) account for the increase in blood lactate elicited by hypoxia; and (3) to identify the tissues responsible for lactate production. R(a) and R(d) lactate of rainbow trout were measured in vivo by continuous infusion of [U-(14)C]lactate in trout exposed to 25% O(2) saturation or maintained in normoxia for 90 min. In normoxic fish, R(a) lactate decreased from 18.2 to 13.1 μmol kg(-1) min(-1) and R(d) lactate from 19.0 to 12.8. R(a) and R(d) were always matched, thereby maintaining a steady baseline blood lactate concentration of ∼0.8 mmol l(-1). By contrast, the hypoxic fish increased blood lactate to 8.9 mmol l(-1) and R(a) lactate from 18.4 to 36.5 μmol kg(-1) min(-1). This stimulation of anaerobic glycolysis was unexpectedly accompanied by a 52% increase in R(d) lactate from 19.9 to 30.3 μmol kg(-1) min(-1). White muscle was the main producer of lactate, which accumulated to 19.2 μmol g(-1) in this tissue. This first study of non-steady-state lactate kinetics in fish shows that the increase in lactate disposal elicited by hypoxia plays a strategic role in reducing the lactate load on the circulation. Without this crucial response, blood lactate accumulation would double.
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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 | 0.001 |
| 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".