Osmoregulation of the transcriptome of the hypothalamic supraoptic nucleus: A resource for the community
Bibliographic record
Abstract
The hypothalamic supraoptic nucleus (SON) is a core osmoregulatory control centre that deciphers information about the metabolic state of the organism and orchestrates appropriate homeostatic (endocrine) and allostatic (behavioural) responses. We have used RNA sequencing to describe the polyadenylated transcriptome of the SON of the male Wistar Han rat. These data have been mined to generate comprehensive catalogues of functional classes of genes (enzymes, transcription factors, endogenous peptides, G protein coupled receptors, transporters, catalytic receptors, channels and other pharmacological targets) expressed in this nucleus in the euhydrated state, and that together form the basal substrate for its physiological interactions. We have gone on to show that fluid deprivation for 3 days (dehydration) results in changes in the expression levels of 2247 RNA transcripts, which have similarly been functionally catalogued, and further mined to describe enriched gene categories and putative regulatory networks (Regulons) that may have physiological importance in SON function related plasticity. We hope that the revelation of these genes, pathways and networks, most of which have no characterised roles in the SON, will encourage the neuroendocrine community to pursue new investigations into the new 'known-unknowns' reported in the present study.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".