Ammonia excretion in the Atlantic hagfish (<i>Myxine glutinosa</i>) and responses of an Rhc glycoprotein
Bibliographic record
Abstract
Hagfishes, the most ancient of the extant craniates, demonstrate a high tolerance for a number of unfavorable environmental conditions, including elevated ammonia. Proposed mechanisms of ammonia excretion in aquatic organisms include vesicular NH(4)(+) transport and release by exocytosis in marine crabs, and passive NH(3) diffusion, active NH(4)(+) transport, and paracellular leakage of NH3 or NH(4)(+) across the gills of fishes. Recently, an emerging paradigm suggests that Rhesus glycoproteins play a vital role in ammonia transport in both aquatic invertebrates and vertebrates. This study has identified an Rh glycoprotein ortholog from the gills of Atlantic hagfish. The hagfish Rhcg shares a 56-60% amino acid identity to other vertebrate Rhcg cDNAs. Sequence information was used to produce an anti-hagfish Rhcg (hRhcg) antibody. We have used hRhcg to localize protein expression to epithelial cells of the gill and the skin. In addition, we have quantified hRhcg expression following exposure to elevated plasma ammonia levels. Animals exposed to a 3 mmol/kg NH(4)Cl load resulted in significantly elevated plasma ammonia concentrations compared with controls for up to 4 h postinjection. This correlated with net ammonia excretion rates that were also significantly elevated for up to 4 h postinjection. Rhcg mRNA expression in both the gill and skin was significantly elevated by 15 min and 1 h, respectively, and hRhcg protein expression in gills was significantly elevated at 2, 4, and 8 h postinjection. These results demonstrate a potential role for Rhcg in the excretion of ammonia in the Atlantic hagfish.
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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".