Integration of Functional Imaging, Cytometry, and Unbiased Proteomics Reveals New Features of Endothelial-to-Mesenchymal Transition in Ischemic Mitral Valve Regurgitation in Human Patients
Bibliographic record
Abstract
Background: Following myocardial infarction, mitral regurgitation (MR) is a common complication. Previous animal studies demonstrated the association of endothelial-to-mesenchymal transition (EndMT) with mitral valve (MV) remodeling. Nevertheless, little is known about how MV tissue responds to ischemic heart changes in humans. Methods: MVs were obtained by the Cardiothoracic Surgical Trials Network from 17 patients with ischemic mitral regurgitation (IMR). Echo-doppler imaging assessed MV function at time of resection. Cryosections of MVs were analyzed using a multi-faceted histology and immunofluorescence examination of cell populations. MVs were further analyzed using unbiased label-free proteomics. Echo-Doppler imaging, histo-cytometry measures and proteomic analysis were then integrated. Results: MVs from patients with greater MR exhibited proteomic changes associated with proteolysis-, inflammatory- and oxidative stress-related processes compared to MVs with less MR. Cryosections of MVs from patients with IMR displayed activated valvular interstitial cells (aVICs) and double positive CD31+ αSMA+ cells, a hallmark of EndMT. Univariable and multivariable association with echocardiography measures revealed a positive correlation of MR severity with both cellular and geometric changes (e.g., aVICs, EndMT, leaflet thickness, leaflet tenting). Finally, proteomic changes associated with EndMT showed gene-ontology enrichment in vesicle-, inflammatory- and oxidative stress-related processes. This discovery approach indicated new candidate proteins associated with EndMT regulation in IMR. Conclusion: We describe an atypical cellular composition and distinctive proteome of human MVs from patients with IMR, which highlighted new candidate proteins implicated in EndMT-related processes, associated with maladaptive MV fibrotic remodeling.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".