Is immune system‐related hypertension associated with ovarian hormone deficiency?
Bibliographic record
Abstract
NEW FINDINGS: What is the topic of this review? This review summarizes recent data on the role of ovarian hormones and sex in inflammation-related hypertension. What advances does it highlight? The adaptive immune system has recently been implicated in the development of hypertension in males but not in females. The role of the immune system in the development of hypertension in women and its relationship to ovarian hormone production are highlighted. The immune system is known to contribute to the development of high blood pressure in males. However, the role of the immune system in the development of high blood pressure in females and the role of ovarian hormones has only recently begun to be studied. In animal studies, both the sex of the host and the T cell are critical biological determinants of susceptibility and resistance to hypertension induced by angiotensin II. In women, natural menopause is known to result in significant changes in the expression of genes regulating the immune system. Likewise, in animal models, ovariectomy results in hypertension and an upregulation in T-cell tumour necrosis factor-α-related genes. Oestrogen replacement results in decreases in inflammatory genes in the brain regions involved in blood pressure regulation. Together, these studies suggest that the response of the adaptive immune system to ovarian hormone deficiency is a significant contributor to hypertension in women.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".