Plasma Circulating Extracellular RNAs in Left Ventricular Remodeling Post-Myocardial Infarction
Bibliographic record
Abstract
Despite substantial declines in mortality following myocardial infarction (MI), subsequent left ventricular remodeling (LVRm) remains a significant long-term complication. Extracellular small non-coding RNAs (exRNAs) have been associated with cardiac inflammation and fibrosis and we hypothesized that they are associated with post-MI LVRm phenotypes. RNA sequencing of exRNAs was performed on plasma samples from patients with "beneficial" (decrease LVESVI ≥ 20%, n = 11) and "adverse" (increase LVESVI ≥ 15%, n = 11) LVRm. Selected differentially expressed exRNAs were validated by RT-qPCR (n = 331) and analyzed for their association with LVRm determined by cardiac MRI. Principal components of exRNAs were associated with LVRm phenotypes post-MI; specifically, LV mass, LV ejection fraction, LV end systolic volume index, and fibrosis. We then investigated the temporal regulation and cellular origin of exRNAs in murine and cell models and found that: 1) plasma and tissue miRNA expression was temporally regulated; 2) the majority of the miRNAs were increased acutely in tissue and at sub-acute or chronic time-points in plasma; 3) miRNA expression was cell-specific; and 4) cardiomyocytes release a subset of the identified miRNAs packaged in exosomes into culture media in response to hypoxia/reoxygenation. In conclusion, we find that plasma exRNAs are temporally regulated and are associated with measures of post-MI LVRm.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".