Heads or tails? Stressor-specific expression of corticotropin-releasing factor and urotensin I in the preoptic area and caudal neurosecretory system of rainbow trout
Bibliographic record
Abstract
Corticotropin-releasing factor (CRF)- and urotensin I (UI)-expressing cells of the preoptic area (POA) and caudal neurosecretory system (CNSS) are considered key contributors to the regulation of the stress response in fish; however, the expression pattern of these neurons to environmental and social challenges have not been compared in a single study. Therefore, we characterized in rainbow trout (Oncorhynchus mykiss) the central distribution of CRF and UI expression and quantified the POA and CNSS mRNA levels of both transcripts in response to hyperammonemia, hypoxia, isolation, or subordination. The tissue distribution demonstrated that the POA and the CNSS are dominant sites of CRF and UI expression. Comparison of the plasma cortisol levels in response to the diverse treatments showed that subordination was the most severe stressor followed by hyperammonemia, isolation, and hypoxia. In the POA, with the exception of subordination that had no effect on UI expression, all stressors resulted in increase in CRF and UI mRNA levels. In the CNSS, while hyperammonemia was associated with increase in CRF and UI mRNA levels, and hypoxia induced an increase in CRF expression, isolation caused a decrease in the expression of both transcripts, and subordination had no effect. Independent of the stressor, we found strong positive correlations between CRF and UI expression in the POA and the CNSS, and no correlation in the expression of either gene between regions. Overall, the results demonstrate that the contribution of POA and CNSS CRF and UI neurons to the stress response in rainbow trout is stressor-, time-, and region-specific.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".