Cardiovascular physiology of decapod crustaceans: from scientific inquiry to practical applications
Bibliographic record
Abstract
Until recently, the decapod crustacean heart was regarded as a simple, single ventricle, contraction of which forces haemolymph out into seven arteries. Differential tissue perfusion is achieved by contraction and relaxation of valves at the base of each artery. In this Review, we discuss recent work that has shown that the heart is bifurcated by muscular sheets that may effectively divide the single ventricle into 'chambers'. Preliminary research shows that these chambers may contract differentially; whether this enables selective tissue perfusion remains to be seen. Crustaceans are unusual in that they can stop their heart for extended periods. These periods of cardiac arrest can become remarkably rhythmic, accounting for a significant portion of the cardiac repertoire. As we discuss in this Review, in crustaceans, changes in heart rate have been used extensively as a measurement of stress and metabolism. We suggest that the periods of cardiac pausing should also be quantified in this context. In the past three decades, an exponential increase in crustacean aquaculture has occurred and heart rate (and changes thereof) is being used to understand the stress responses of farmed crustaceans, as well as providing an indicator of disease progression. Furthermore, as summarized in this Review, heart rate is now being used as an effective indicator of humane methods to anaesthetize, stun or euthanize crustaceans destined for the table or for use in scientific research. We believe that incorporation of new biomedical technology and new animal welfare policies will guide future research directions in this field.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".