Regulation of Clusterin in the Heart and Plasma of Mice After Transverse Aortic Constriction
Bibliographic record
Abstract
Chronic pressure overload induces adverse cardiac remodelling characterised by left ventricular (LV) hypertrophy and fibrosis, leading to heart failure (HF). Identification of new biomarkers for adverse cardiac remodelling enables us to better understand this process and, consequently, to prevent HF. We recently identified clusterin (CLU) as a biomarker of cardiac remodelling and HF after myocardial infarction. The aim of this study was to investigate whether CLU expression is regulated in the heart and could be used as an indicator of adverse cardiac remodelling in response to pressure overload. We quantified CLU in the LV of mice subjected to transverse aortic constriction (TAC) and observed increased CLU mRNA levels and its mature protein form (m-CLU) compared to the sham. Interestingly, CLU mRNA levels were positively correlated with pro-hypertrophic (ANP, BNP, B-MHC), pro- and anti-fibrotic (TGFb, ColI and CILP) genes. In addition, m-CLU was positively correlated with LV hypertrophy, LV end diastolic and systolic diameters, and negatively correlated with LV ejection fraction. Finally, we observed that m-CLU levels only increased in TAC mice with severe cardiac remodelling and dysfunction without any significant difference in plasma CLU levels. This is the first study to demonstrate that cardiac expression of CLU is induced in the LV of TAC mice during adverse cardiac remodelling. However, plasma CLU levels could not be used as biomarkers of TAC-induced cardiac remodelling and dysfunction.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".