Allometric scaling in centrarchid fish: origins of intra- and inter-specific variation in oxidative and glycolytic enzyme levels in muscle
Bibliographic record
Abstract
The influence of body size on metabolic rate, muscle enzyme activities and the underlying patterns of mRNA for these enzymes were explored in an effort to explain the genetic basis of allometric variation in metabolic enzymes. We studied two pairs of sister species of centrarchid fish: black bass (largemouth bass Micropterus salmoides and smallmouth bass Micropterus dolomieui) and sunfish (pumpkinseed Lepomis gibbosus and bluegill Lepomis macrochirus). Our goal was to assess the regulatory basis of both intraspecific and interspecific variation relative to body size, as well as to gain insights into the evolutionary constraints within lineages. Whole animal routine metabolic rate showed scaling coefficients not significantly different from 1, ranging from (+0.87 to +0.96). However, there were significant effects of body size on the specific activities of oxidative and glycolytic enzymes. Mass-specific activity of the oxidative enzyme citrate synthase (CS) scaled negatively with body size in each species, with scaling coefficients ranging from -0.15 to -0.19, whereas the glycolytic enzyme pyruvate kinase (PK) showed positive scaling, with scaling coefficients ranging from +0.08 to +0.23. The ratio of mass-specific enzyme activity in PK to CS increased with body size, whereas the ratio of mRNA transcripts of PK to CS was unaffected, suggesting the enzyme relationships were not due simply to transcriptional regulation of both genes. The mass-dependent differences in PK activities were best explained by transcriptional regulation of the muscle PK gene; PK mRNA was a good predictor of PK specific enzyme activity within species and between species. Conversely, CS mRNA did not correlate with CS specific enzyme activities, suggesting post-transcriptional mechanisms may explain the observed inter-specific and intraspecific differences in oxidative enzymes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".