Rh proteins and NH4+-activated Na+-ATPase in the Magadi tilapia (<i>Alcolapia grahami</i>), a 100% ureotelic teleost fish
Bibliographic record
Abstract
The small cichlid fish Alcolapia grahami lives in Lake Magadi, Kenya, one of the most extreme aquatic environments on Earth (pH ~10, carbonate alkalinity ~300 mequiv l(-1)). The Magadi tilapia is the only 100% ureotelic teleost; it normally excretes no ammonia. This is interpreted as an evolutionary adaptation to overcome the near impossibility of sustaining an NH3 diffusion gradient across the gills against the high external pH. In standard ammoniotelic teleosts, branchial ammonia excretion is facilitated by Rh glycoproteins, and cortisol plays a role in upregulating these carriers, together with other components of a transport metabolon, so as to actively excrete ammonia during high environmental ammonia (HEA) exposure. In Magadi tilapia, we show that at least three Rh proteins (Rhag, Rhbg and Rhcg2) are expressed at the mRNA level in various tissues, and are recognized in the gills by specific antibodies. During HEA exposure, plasma ammonia levels and urea excretion rates increase markedly, and mRNA expression for the branchial urea transporter mtUT is elevated. Plasma cortisol increases and branchial mRNAs for Rhbg, Rhcg2 and Na(+),K(+)-ATPase are all upregulated. Enzymatic activity of the latter is activated preferentially by NH4(+) (versus K(+)), suggesting it can function as an NH4(+)-transporter. Model calculations suggest that active ammonia excretion against the gradient may become possible through a combination of Rh protein and NH4(+)-activated Na(+)-ATPase function.
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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".