Transcriptome Analysis Reveals Downregulation of Urocortin Expression in the Hypothalamo-Neurohypophysial System of Spontaneously Hypertensive Rats
Bibliographic record
Abstract
The chronically increased blood pressure characteristic of essential hypertension represents an insidious and cumulative risk for cardiovascular disease. Essential hypertension is a multifactorial condition, with no known specific aetiology but a strong genetic component. The Spontaneously Hypertensive rat (SHR) shares many characteristics of human essential hypertension, and as such is a commonly used experimental model. The mammalian hypothalamo-neurohypophyseal system (HNS) plays a pivotal role in the regulation of blood pressure, volume and osmolality. In order to better understand the possible role of the HNS in hypertension, we have used microarray analysis to reveal differential regulation of genes in the HNS of the SHR compared to a control normotensive strain, the Wistar Kyoto rat (WKY). These results were validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). One of the genes identified and validated as being downregulated in SHR compared to WKY was that encoding the neuropeptide urocortin (Ucn). Immunohistochemical analyses revealed Ucn to be highly expressed within magnocellular neurons of the PVN and SON, with pronounced localisation in dendritic projections containing oxytocin and vasopressin. When Ucn was overexpressed in the PVN of the SHR by in vivo lentiviral mediated gene transfer, blood pressure was unaffected but there were significant, transient reductions in the VLF spectra of systolic blood pressure consistent with an action on autonomic balance. We suggest that Ucn may act, possibly via dendritic release, to subtly regulate neurohumoral aspects of arterial pressure control.
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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".