The impact of hypoxia and heat stress on Corella inflata heart characteristics adds evidence to the functional role of heartbeat reversals
Bibliographic record
Abstract
Marine habitats are experiencing changes in temperature and dissolved oxygen due to climate change, but how these changes are influencing the physiology of sessile invertebrates in the subtidal zone has not been well studied. Tunicates are a common subtidal invertebrate with a unique heart, in that their heartbeat can reverse directions. Tunicate heartbeat can be influenced by environmental stressors, but how combined low oxygen (hypoxia) and heat influence heart rate and heartbeat reversal is unknown. Corella inflata were collected and acclimated to lab conditions for 16-24 hours (∼13°C, ∼92% O2), then exposed to heat (∼18°C), hypoxic (∼31% O2), or heat and hypoxic (∼17°C and ∼31% O2) conditions for six hours. Heart rate and time between heartbeat reversals were measured after acclimation to lab conditions, exposure to a stressor, and recovery from the stressor. Heart rate increased with exposure to heat, hypoxia, and heat and hypoxia, with the greatest increase after exposure to both stressors. Time between heartbeat reversals increased with exposure to hypoxia and heat and hypoxia, but not heat. Our findings show that temperature and oxygen availability influence C. inflata heart rate and time between heartbeat reversals and suggests that tunicates may use heartbeat reversals to optimize oxygen and nutrient movement when exposed to stressors, which we propose as the Efficiency Hypothesis. Additionally, these findings provide insight into how tunicates may respond to changing ocean conditions in the future.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".