Feeding through your gills and turning a toxicant into a resource: how the dogfish shark scavenges ammonia from its environment
Bibliographic record
Abstract
ABSTRACT Nitrogen (N) appears to be a limiting dietary resource for elasmobranchs, required not only for protein growth but also for urea-based osmoregulation. Building on recent evidence that the toxicant ammonia can be taken up actively at the gills of the shark and made into the valuable osmolyte urea, we demonstrate that the uptake exhibits classic Michaelis–Menten saturation kinetics with an affinity constant (Km) of 379 µmol l−1, resulting in net N retention at environmentally realistic ammonia concentrations (100–400 µmol l−1) and net N loss through stimulated urea-N excretion at higher levels. Ammonia-N uptake rate increased or decreased with alterations in seawater pH, but the changes were much less than predicted by the associated changes in seawater PNH3, and more closely paralleled changes in seawater NH4+ concentration. Ammonia-N uptake rate was insensitive to amiloride (0.1 mmol l−1) or to a 10-fold elevation in seawater K+ concentration (to 100 mmol l−1), suggesting that the mechanism does not directly involve Na+ or K+ transporters, but was inhibited by blockade of glutamine synthetase, the enzyme that traps ammonia-N to fuel the ornithine–urea cycle. High seawater ammonia inhibited uptake of the ammonia analogue [14C]methylamine. The results suggest that branchial ammonia-N uptake may significantly supplement dietary N intake, amounting to about 31% of the nitrogen acquired from the diet. They further indicate the involvement of Rh glycoproteins (ammonia channels), which are expressed in dogfish gills, in normal ammonia-N uptake and retention.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".