Transcriptome responses to heat stress in the nucleated red blood cells of the rainbow trout (<i>Oncorhynchus mykiss</i>)
Bibliographic record
Abstract
The retention of a nucleus in the mature state of fish red blood cells (RBCs) and the ability to easily collect and manipulate blood in nonterminal experiments make blood an ideal tissue on which to study the cellular stress response in fish. Through the use of the cGRASP 16K salmonid microarray, we investigated differences in RBC global gene transcription in fish held under control conditions (11 degrees C) and exposed to heat stress (1 h at 25 degrees C followed by recovery at 11 degrees C). Repeated blood sampling (via a dorsal aorta cannula) enables us to examine the individual stress response over time. Samples were taken preheat stress (representing individual control) and at 4 and 24 h postheat stress (representing early and late transcriptional regulation). Approximately 3,000 microarray features had signal above threshold when hybridized with RBC RNA-derived targets, and cannulation did not have a detectable effect on RBC mRNA expression at the investigated time points. Genes involved in the stress response, immune response, and apoptosis were among those showing the highest dysregulation during both early and late transcriptional regulation. Additionally, genes related to the differentiation and development of blood cells were transcriptionally upregulated at the 24 h time point. This study provides a broader understanding of the mechanisms underpinning the stress response in fish and the discovery of novel genes that are regulated in a stress specific manner. Moreover, salmonid transcripts that are consistently dysregulated in blood in response to heat stress are potential candidates of nonlethal biomarkers of exposure to this particular stressor.
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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".