Beyond just hemoglobin: Red blood cell potentiation of hemoglobin-oxygen unloading in fish
Bibliographic record
Abstract
Teleosts comprise 95% of fish species, almost one-half of all vertebrate species, and represent one of the most successful adaptive radiation events among vertebrates. This is thought to be in part because of their unique oxygen (O2) transport system. In salmonids, recent in vitro and in vivo studies indicate that hemoglobin-oxygen (Hb-O2) unloading to tissues may be doubled or even tripled under some conditions without changes in perfusion. This is accomplished through the short circuiting of red blood cell (RBC) pH regulation, resulting in a large arterial-venous pH difference within the RBC and induced reduction in Hb-O2affinity. This system has three prerequisites: 1) highly pH-sensitive hemoglobin, 2) rapid RBC pH regulation, and 3) a heterogeneous distribution of plasma-accessible CA in the cardiovascular system (presence in the tissues and absence at the gills). Although data are limited, these attributes may be general characteristics of teleosts. Although this system is not likely operational to the same degree in other vertebrates, some of these prerequisites do exist, and the generation and elimination of pH disequilibrium states at the RBC will likely enhance Hb-O2unloading to some degree. In human disease states, there are conditions that may partly satisfy those for enhanced Hb-O2unloading, tentatively an avenue for future work that may improve treatment efficacy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".