Getting to the Heart of Things: Does Heart Rate Determine the Thermal Tolerance of Nile Tilapia (Oreochromis niloticus)?
Bibliographic record
Abstract
This research examined the cardiac thermal tolerance of Nile tilapia across different levels of biological organization to better understand the heart’s role in determining fish thermal tolerance. First, we performed critical thermal minimum and maximum tests (at 2℃ h-1 ) on 25℃-acclimated adult tilapia (~ 350 g) fitted with Transonic® flow probes [to measure cardiac output (Q) and heart rate (fH )] until the loss of equilibrium (LOE), which occured at ~9.5 and 40.5℃, respectfully. Given that these fish relied predominantly on fH to modulate Q, and that LOE occurs due to the loss of homeostasis at the tissue/cellular level, we then measured cardiac electrocardiograms and electrical conduction in isolated hearts from fingerlings (<10 g) to acute changes in temperature (±0.5℃ min-1 ) until they experienced AV block. Cardiac failure in vitro occurred at ~ 14 and 38℃, respectively, suggesting that isolated hearts had a constrained thermal window (by ~22%). Futher, tilapia studied in vitro had: 1) higher values for both minimum and maximum fH (by 61 and 17%, respectively); 2) a similar absolute scope for fH (i.e., 115.5 beats min-1 in vitro vs. 110.7 beats min-1 in vivo); and 3) a temperature at maximum fH that was 5℃ lower than in vivo. Collectively, these data suggest that while fH (pacemaker function and electical conductance across the AV junction) largely determine the survival of tilapiain vivowhen exposed to acute changes in temperature, other important cardioprotective mechanisms (e.g., hormonal modulation and cholinergic tone) are crucial to preserving cardiac function.
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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".