Hydrostatic-pressure and temperature effects on the molecular order of erythrocyte membranes from deep-, shallow-, and non-diving mammals
Bibliographic record
Abstract
Little is known about the cellular mechanisms involved in the tolerance of deep-diving marine mammals to hydrostatic pressures that cause serious pathologies when experienced by other mammals. We compared fatty-acid composition, cholesterol content, and the effects of pressure on the molecular order of erythrocyte membranes from deep-, shallow-, and non-diving mammals to determine how these properties may be related to diving performance. Erythrocytes were collected from two deep-diving phocid pinnipeds (northern elephant seal (Mirounga angustirostris) and harbor seal (Phoca vitulina)), a relatively shallow-diving otariid pinniped (northern fur seal (Callorhinus ursinus)), and several nondiving terrestrial mammals (dog (Canis familiaris), horse (Equus caballus), and cow (Bos taurus)). Fatty-acid composition clearly distinguished the phocids from the other species. The monoene content of erythrocyte membranes was substantially lower (3 vs.»20%), whereas the lipid unsaturation indices, the ratio of α- to γ-linolenic acids, and the proportions of long-chain polyunsaturated fatty acids were substantially higher in the phocids. The cell-membrane cholesterol content was also significantly lower in erythrocytes from the deep-diving phocids (cholesterol:phospholipid ratios 0.20.3) than from most other mammals (1.0). Membranes from the phocids were more ordered than those from the shallow- and non-divers, and were also more sensitive to changes in pressure and temperature. The physiological significance of these differences in cell-membrane structure, which affect the order and sensitivity of cell membranes to hydrostatic pressure, is unknown, but they may be important adaptations that allow repeated and prolonged exposure to great hydrostatic pressure.
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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".