Limited extracellular but complete intracellular acid-base regulation during short-term environmental hypercapnia in the armoured catfish,<i>Liposarcus pardalis</i>
Bibliographic record
Abstract
Environmental hypercapnia induces a respiratory acidosis that is usually compensated within 24-96 h in freshwater fish. Water ionic composition has a large influence on both the rate and degree of pH recovery during hypercapnia. Waters of the Amazon are characteristically dilute in ions, which may have consequences for acid-base regulation during environmental hypercapnia in endemic fishes. The armoured catfish Liposarcus pardalis, from the Amazon, was exposed to a water P(CO(2)) of 7, 14 or 42 mmHg in soft water (in micromol l(-1): Na(+), 15, Cl(-), 16, K(+), 9, Ca(2+), 9, Mg(2+), 2). Blood pH fell within 2 h from a normocapnic value of 7.90+/-0.03 to 7.56+/-0.04, 7.34+/-0.05 and 6.99+/-0.02, respectively. Only minor extracellular pH (pH(e)) recovery was observed in the subsequent 24-96 h. Despite the pronounced extracellular acidosis, intracellular pH (pH(i)) of the heart, liver and white muscle was tightly regulated within 6 h (the earliest time at which these parameters were measured) via a rapid accumulation of intracellular HCO(3)(-). While most fish regulate pH(i) during exposure to environmental hypercapnia, the time course for this is usually similar to that for pH(e) regulation. The degree of extracellular acidosis tolerated by L. pardalis, and the ability to regulate pH(i) in the face of an extracellular acidosis, are the greatest reported to date in a teleost fish. The preferential regulation of pH(i) in the face of a largely uncompensated extracellular acidosis in L. pardalis is rare among vertebrates, and it is not known whether this is associated with the ability to air-breathe and tolerate aerial exposure, or living in water dilute in counter ions, or with other environmental or evolutionary selective pressures. The ubiquity of this strategy among Amazonian fishes and the mechanisms employed by L. pardalis are clearly worthy of further study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".