Characterization of two novel ammonia transporters, Hiat1a and Hiat1b, in the teleost model system <i>Danio rerio</i>
Bibliographic record
Abstract
Ammonia excretion in fish excretory epithelia is a complex interplay of multiple membrane transport proteins and mechanisms. Using the model system of zebrafish (Danio rerio) larvae, here we identified three paralogues of a novel ammonia transporter, hippocampus-abundant transcript 1 (DrHiat1), also found in most vertebrates. When functionally expressed in Xenopus laevis oocytes, DrHiat1a and DrHiat1b promoted methylamine uptake in a competitive manner with ammonia. In situ hybridization experiments showed that both transporters were expressed as early as the 4-cell stage in zebrafish embryos and could be identified in most tissues 4 days post-fertilization. Larvae experiencing morpholino-mediated knockdown of DrHiat1b exhibited significantly lower whole-body ammonia excretion rates compared with control larvae. Markedly decreased site-specific total ammonia excretion of up to 85% was observed in both the pharyngeal region (site of developing gills) and the yolk sac (region shown to have the highest NH4+ flux). This study is the first to identify DrHiat1b/DrHIAT1 in particular as an important contributor to ammonia excretion in larval zebrafish. Being evolutionarily conserved, these proteins are likely involved in multiple other general ammonia-handling mechanisms, making them worthy candidates for future studies on nitrogen regulation in fishes and across the animal kingdom.
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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".