Characterization of Brainstem Phenylethanolamine N‐methyltransferase Gene Expression in Fetal Programming of Hypertension
Bibliographic record
Abstract
An unfavourable fetal environment results in low birth weight offsprings and the development of hypertension later in life. This concept of fetal programming proposes that elevated levels of glucocorticoids during fetal development leads to alterations in blood pressure regulatory mechanisms. Adrenaline, a neurotransmitter synthesized by the enzyme phenylethanolamine N‐methyltransferase (PNMT), is involved in the sympathetic control of blood pressure and is elevated in hypertensive patients. Dysregulation of the PNMT gene has been linked to the pathogenesis of hypertension and is therefore a candidate gene involved in fetal programming of hypertension. Results from this study show that Wistar Kyoto rats exposed to dexamethasone (DEX: 10, 50 or 100 μg/kg/day) in the third trimester, developed elevated blood pressure as adults. The elevations in arterial blood pressures correlate with the increased dose of prenatal DEX exposure. In addition, PNMT mRNA in the C1, C2 and C3 adrenergic brainstem regions were elevated in prenatally DEX exposed adult rats. Analysis of transcriptional regulators of the PNMT gene shows a dose‐dependent upregulation in the mRNA for Sp1, EGR‐1 and AP2 in the C2 and C3 regions; whereas GR mRNA was increased in the C3 region only. These results suggest that prenatal glucocorticoid exposure increases brainstem PNMT gene expression via altered transcriptional regulatory mechanisms.
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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".