Gene profiling of left ventricle eccentric hypertrophy in aortic regurgitation in rats: rationale for targeting the β-adrenergic and renin-angiotensin systems
Bibliographic record
Abstract
Aortic valve regurgitation (AR) imposes a severe volume overload to the left ventricle (LV), which results in dilation, eccentric hypertrophy, and eventually loss of function. Little is known about the impact of AR on LV gene expression. We, therefore, conducted a gene expression profiling study in the LV of rats with acute and severe AR. We identified 64 genes that were specifically upregulated and 29 that were downregulated out of 21,910 genes after 2 wk. Of the upregulated genes, a good proportion was related to the extracellular matrix. We subsequently studied a subset of 19 genes by quantitative RT-PCR (qRT-PCR) to see if the modulation seen in the LV after 2 wk persisted in the chronic phase (after 6 and 12 mo) and found that it did persist. Knowing that the adrenergic and renin-angiotensin systems are overactivated in our animal model, we were interested to see if blocking those systems using metoprolol (25 mg.kg(-1).day(-1)) and captopril (100 mg.kg(-1).day(-1)) would alter the expression of some upregulated LV genes in AR rats after 6 mo. By qRT-PCR, we observed that upregulations of LV mRNA levels encoding for procollagens type I and III, fibronectin, atrial natriuretic peptide, transforming growth factor-beta(2), and connective tissue growth factor were totally or partially reversed by this treatment. These observations provide a molecular rationale for a medical strategy aiming these systems in the medical treatment of AR and expand the paradigm in the study of this form of LV volume overload.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".