Immune regulation of systemic hypertension, pulmonary arterial hypertension, and preeclampsia: shared disease mechanisms and translational opportunities
Bibliographic record
Abstract
Systemic hypertension, preeclampsia, and pulmonary arterial hypertension (PAH) are diseases of high blood pressure in the systemic or pulmonary circulation. Beyond the well-defined contribution of more traditional pathophysiological mechanisms, such as changes in the renin–angiotensin–aldosterone system, to the development of these hypertensive disorders, there is substantial clinical evidence supporting an important role for inflammation and immunity in the pathogenesis of each of these three conditions. Over the last decade, work in small animal models, bearing targeted deficiencies in specific cytokines or immune cell subsets, has begun to clarify the immune-mediated mechanisms that drive changes in vascular structure and tone in hypertensive disease. By summarizing the clinical and experimental evidence supporting a contribution of the immune system to systemic hypertension, preeclampsia, and PAH, the current review highlights the cellular and molecular pathways that are common to all three hypertensive disorders. These mechanisms are centered on an imbalance in CD4+helper T cell populations, defined by excessive Th17 responses and impaired Tregactivity, as well as the excessive activation or impairment of additional immune cell types, including macrophages, dendritic cells, CD8+T cells, B cells, and natural killer cells. The identification of common immune mechanisms in systemic hypertension, preeclampsia, and PAH raises the possibility of new therapeutic strategies that target the immune component of hypertension across multiple disorders.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".