Abstract 18802: Differential Chamber and Cell-specific Expression of MicroRNAs in Experimental Heart Failure
Bibliographic record
Abstract
Background: Heart failure (HF) causes differential remodeling of left atrium (LA) vs left ventricle (LV), with much more prominent fibrosis in LA. Fibroblasts (FB) are central in fibrotic responses, with microRNAs (miRs) important regulators. This study determined the profile of miR expression changes underlying LA/LV remodeling, as well as FB/cardiomyocyte (CM) selectivity during the development of experimental HF. Methods: HF was induced in dogs by ventricular tachypacing (240 bpm) for 0 (CTL), 12, 24 hrs, 1 and 2 wks (n=5-12/group). FB and CMs were freshly isolated from LA and LV of each dog. Gene expression was assessed by qPCR. MiRs were selected based on preliminary microarray data. Results: HF changed the expression of 7/10 miRs in FB, while they were unchanged in CMs (miR-29b, miR-26a/b, miR-1, miR-208b and miR-133a/b, Table 1). Of these, FB selective miRs decreased only in LA (miR-29b decreased by ∼65%* and miR-26a/b by ∼57%*-79%*** beginning at 12 hrs), while the CM selective miRs decreased in both LA and LV (miR-1 by ∼37%-93%**, miR-208b by ∼67%-91%*), or only in LV (miR-133a/b by ∼77%***-89%***). MiRs downregulated in LA target multiple ECM genes, which showed LA-predominant increases in FB: miR-29b targets COL1A1 (increased by ∼11-fold*** from 1 wk) and COL3A1 (increased by ∼4.7-fold*** from 1 wk). MiR-29b and miR-208b both target fibrillin1 (increased by ∼1.9-fold** at 2 wks). MiR-1 may also participate in ECM remolding as it targets fibronectin1 (increased by ∼4.8*-14***-fold from 1 wk). The expression of miR-208a, miR-30a and miR-21 changed in both atrial FB and CMs, with smaller or nonsignificant changes in ventricular cells (Table 1), suggesting that these miRs play roles both in FB and CMs. Conclusions: Experimental HF causes greater FB-selective miR and ECM changes in LA compared to LV. The FB expression-profiles of ECM-targeting miRs in LA, accompanied by related ECM expression changes, implicate miRs in HF related LA-selective structural remodeling.
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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) | 0.003 | 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".