Bibliographic record
Abstract
PURPOSE OF REVIEW: In this review we summarize the recent evidence that highlights the involvement of low-grade inflammation in the development and pathophysiology of hypertension. RECENT FINDINGS: Essential hypertension is characterized by increased peripheral vascular resistance to blood flow, due in large part to vascular remodeling. Vascular changes in hypertension are associated with mechanical and humoral factors that modulate signaling events, resulting in abnormal function, media growth, extracellular matrix deposition and inflammation. Recent evidence suggests that inflammation is present in the vasculature in animal models of hypertension. Inflammatory markers, such as C-reactive protein, are associated with vascular lesions in humans, and are predictive of cardiovascular outcome. In animal and human studies, pro-inflammatory components of the renin-angiotensin-aldosterone system have been demonstrated in large conduit and small arteries in the kidney and heart. Peroxisome proliferator-activated receptor activators are drugs with metabolic properties that have been demonstrated to exert anti-inflammatory effects on the vasculature, and there is now evidence that these actions may be protective for blood vessels. SUMMARY: Inflammatory processes are important participants in the pathophysiology of hypertension and cardiovascular disease. The identification of the mechanisms leading to the activation of inflammation should contribute to the development of specific therapeutic approaches to apply in hypertension and its complications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".