Discoordinate re-expression of cardiac fetal genes in Nω-nitro-?-arginine methyl ester (?-NAME) hypertension
Bibliographic record
Abstract
OBJECTIVE: Hypertension produced by chronic inhibition of nitric oxide (NO) synthase by N(omega)-nitro-L-arginine methyl ester (L-NAME) was used to determine the effect of severe pressure overload with or without left ventricular (LV) hypertrophy on the transcriptional activation of the cardiac fetal genes encoding for the natriuretic peptides (NP) atrial natriuretic factor (ANF) and brain natriuretic peptide (BNP), and for beta-myosin heavy chain (MHC) in both atrial and ventricular muscle. A previously reported association of LV hypertrophy with the activation of cardiac renin and angiotensin-converting enzyme (ACE) in this hypertension model was also investigated. METHODS: Male Sprague-Dawley rats received L-NAME (75 mg/kg/day) or were left untreated for 4 (n=12) or 8 (n=12) weeks. RESULTS: L-NAME-treated rats became severely hypertensive in both treatment groups but only five out of 12 8-week treatment animals showed a significantly increased LV weight to body weight (BW) ratio (LVW/BW). LV ANF mRNA, but not LV BNP mRNA, correlated significantly with LVW/BW only in animals showing LV hypertrophy. No changes were observed in atrial gene expression or plasma concentration of ANF or BNP. A significant correlation was found between LVW/BW and LV renin mRNA and LV ACE activity in rats with LV hypertrophy. LV beta-MHC mRNA levels were significantly increased in the LV of rats with or without LV hypertrophy at both 4 and 8 weeks of treatment. CONCLUSIONS: It is concluded that pressure overload per se does not promote NP or cardiac renin-angiotensin system gene expression while increased beta-MHC expression is a marker of LV pressure overload even in the absence of LV hypertrophy. It is apparent that L-NAME causes a disruption in the coordinated transcriptional activation of cardiac fetal genes expected of hypertrophic stimuli acting on the LV.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".