Interplay between cardiomyocytes and nonmyocytes plays a vital role in cardiac metabolism and function: early-phase metabolic syndrome and short QT
Bibliographic record
Abstract
The heart is a complex organ composed of diverse cell types, primarily cardiomyocytes and nonmyocytes, which engage in intricate intercellular communication. This dynamic multicellular network is essential for maintaining cardiac function and metabolic homeostasis under physiological conditions. However, in the context of early- and late-phase metabolic syndrome (MetS), particularly induced by a high-carbohydrate diet, this cellular crosstalk becomes differentially disrupted. Among them, the early phase of MetS, characterized by hyperglycemia, insulin resistance, and dyslipidemia, promotes structural and functional remodeling of the heart, including metabolic reprogramming and increased susceptibility to arrhythmia, characterized by a short QT interval (SQT) in electrocardiograms. Concurrently, SQT, a cardiac channelopathy affecting ventricular repolarization, can exacerbate these electrophysiological disturbances. Emerging evidence suggests that interactions between cardiomyocytes and nonmyocytes mainly regulate mitochondrial dynamics, substrate metabolism, and inflammatory signaling pathways, which are crucial processes involved in both the progression of MetS and arrhythmogenic remodeling. This review examines the role of cardiomyocyte-nonmyocyte interactions in maintaining cardiac metabolic balance. It highlights how their disruption contributes to arrhythmias, such as SQT, in the early phase of MetS. Understanding this cellular interplay offers potential therapeutic avenues to restore metabolic flexibility and preserve cardiac electrophysiological integrity in metabolic and channelopathic disease states.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".