Rodent models of hypertension
Bibliographic record
Abstract
Elevated blood pressure (BP), or hypertension, is the main risk factor for cardiovascular disease. As a multifactorial and systemic disease that involves multiple organs and systems, hypertension remains a challenging disease to study. Models of hypertension are invaluable to support the discovery of the specific genetic, cellular and molecular mechanisms underlying essential hypertension, as well as to test new possible treatments to lower BP. Rodent models have proven to be an invaluable tool for advancing the field. In this review, we discuss the strengths and weaknesses of rodent models of hypertension through a systems approach. We highlight the ways how target organs and systems including the kidneys, vasculature, the sympathetic nervous system (SNS), immune system and the gut microbiota influence BP in each rodent model. We also discuss often overlooked hypertensive conditions such as pulmonary hypertension and hypertensive-pregnancy disorders, providing an important resource for researchers. LINKED ARTICLES: This article is part of a themed issue on Preclinical Models for Cardiovascular disease research (BJP 75th Anniversary). To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v179.5/issuetoc.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".