Nitric oxide inhibition of NaCl secretion in the opercular epithelium of seawater-acclimated killifish, <i>Fundulus heteroclitus</i>
Bibliographic record
Abstract
Nitric oxide (NO) modulates epithelial ion transport pathways in mammals, but this remains largely unexamined in fish. We explored the involvement of NO in controlling NaCl secretion by the opercular epithelium of seawater killifish using an Ussing chamber approach. Pharmacological agents were used to explore the mechanism(s) triggering NO action. A modified Biotin-switch technique was used to investigate S-nitrosation of proteins. Stimulation of endogenous NO production via the nitric oxide synthase (NOS) substrate L-arginine (2.0 mmol l−1), and addition of exogenous NO via the NO donor SNAP (10−6 mol l−1 to 10−4 mol l−1), decreased the epithelial short-circuit current (Isc). Inhibition of endogenous NO production by the NOS inhibitor L-NAME (10−4 mol l−1) increased Isc and revealed a tonic control of ion transport by NO in unstimulated opercular epithelia. The NO scavenger PTIO (10−5 mol l−1) supressed the NO-mediated decrease in Isc, and confirmed that the effect observed was elicited by release of NO. The effect of SNAP on Isc was abolished by inhibitors of the soluble guanylyl cyclase (sGC), ODQ (10−6 mol l−1) and methylene blue (MB; 10−4 mol l−1), revealing NO signalling via the sGC/cGMP pathway. Incubation of opercular epithelium and gill tissues with SNAP (10−4 mol l−1) led to S-nitrosation of proteins, including Na+/K+-ATPase. Blocking of NOS with L-NAME (10−6 mol l−1) or scavenging of NO with PTIO during hypotonic shock suggested an involvement of NO in the hypotonic-mediated decrease in Isc. Yohimbine (10−4 mol l−1), an inhibitor of α2-adrenoceptors, did not block NO effects suggesting that NO is not involved in the α-adrenergic control of NaCl secretion.
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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".