How the expression of green fluorescent protein and human cardiac actin in the heart influences cardiac function and aerobic performance in zebrafish <scp><i>Danio rerio</i></scp>
Bibliographic record
Abstract
The present study examined how the expression of enhanced green fluorescent protein (eGFP) and human cardiac actin (ACTC) in zebrafish Danio rerio influences embryonic heart rate (RH) and the swim performance and metabolic rate of adult fish. Experiments with the adults involved determining the critical swimming speed (Ucrit, the highest speed sustainable and measure of aerobic capacity) while measuring oxygen consumption. Two different transgenic D. rerio lines were examined: one expressed eGFP in the heart (tg(cmlc:egfp)), while the second expressed ACTC in the heart and eGFP throughout the body (tg(cmlc:actc,ba:egfp)). It was found that RH was significantly lower in the tg(cmlc:actc,ba:egfp) embryos 4 days post‐fertilization compared to wild‐type (WT) and tg(cmlc:egfp). The swim experiments demonstrated that there was no significant difference in Ucrit between the transgenic lines and the wild‐type fish, but metabolic rate and cost of transport (oxygen used to travel a set distance) was nearly two‐fold higher in the tg(cmlc:actc,ba:egfp) fish compared to WT at their respective Ucrit. These results suggest that the expression of ACTC in the D. rerio heart and the expression of eGFP throughout the animal, alters cardiac function in the embryo and reduces the aerobic efficiency of the animal at high levels of activity.
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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".