Development of an Experimental Model to Study the Relationship Between Day-to-Day Variability in Blood Pressure and Aortic Stiffness
Bibliographic record
Abstract
We aimed to develop an animal model of long-term blood pressure variability (BPV) and to investigate its consequences on aortic damage. We hypothesized that day-to-day BPV produced by discontinuous treatment of spontaneously hypertensive rats (SHR) by valsartan may increase arterial stiffness. For that purpose, rats were discontinuously treated, 2 days a week, or continuously treated by valsartan (30 mg/kg/d in chow) or placebo. Telemetered BP was recorded during 2 min every 15 min, 3 days a week during 8 weeks to cover the full BP variations in response to the treatment schedule. Pulse wave velocity (PWV) and aortic structure evaluated by immunohistochemistry were investigated in a second set of rats treated under the same conditions. Continuous treatment with valsartan reduced systolic BP (SBP) and reversed the aortic structural alterations observed in placebo treated SHR (decrease of medial cross-sectional area). Discontinuous treatment with valsartan decreased SBP to a similar extent but increased the day-to-day BPV, short term BPV, diastolic blood pressure (DBP), and PWV as compared with continuous treatment. Despite no modifications in the elastin/collagen ratio and aortic thickness, an increase in PWV was observed following discontinuous treatment and was associated with a specific accumulation of fibronectin and its αv-integrin receptor compared with both groups of rats. Taken together the present results indicate that a discontinuous treatment with valsartan is able to induce a significant increase in day-to-day BPV coupled to an aortic phenotype close to that observed in hypertension. This experimental model should pave the way for future experimental and clinical studies aimed at assessing how long-term BPV increases aortic stiffness.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".