Insights into Cardiovascular Defects and Cardiac Epigenome in the Context of COVID-19
Bibliographic record
Abstract
Although few in number, studies on epigenome of the heart of COVID-19 patients show that epigenetic signatures such as DNA methylation are significantly altered, leading to changes in expression of several genes. It contributes to pathogenic cardiac phenotypes of COVID-19, e.g., low heart rate, myocardial edema, and myofibrillar disarray. DNA methylation studies reveal changes which likely contribute to cardiac disease through unknown mechanisms. The incidence of severe COVID-19 disease, including hospitalization, requiring respiratory support, morbidity, and mortality, is disproportionately higher in individuals with co-morbidities. This poses unprecedented strains on the global healthcare system. While their underlying conditions make patients more susceptible to severe COVID-19 disease, strained healthcare systems, lack of adequate support, or sedentary lifestyles from ongoing lockdowns have proved detrimental to their underlying health conditions, thus pushing them to severe risk of congenital heart disease (CHD) itself. Prophylactic vaccines against COVID-19 have ushered new hope for CHD. A common connection between COVID-19 and CHD is SARS-CoV-2's host receptor ACE2, because ACE2 regulates and protects organs, including the heart, in various ways. ACE2 is a common therapeutic target against cardiovascular disease and COVID-19 which damages organs. Hence, this review explores the above regarding CHDs, cardiovascular damage, and cardiac epigenetics, in COVID-19 patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 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".