Methyl nutrients, <scp>DNA</scp> methylation, and cardiovascular disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Diet plays an important role in the development and prevention of cardiovascular disease (CVD), but the molecular mechanisms are not fully understood. DNA methylation has been implicated as an underlying molecular mechanism that may account for the effect of dietary factors on the development and prevention of CVD. DNA methylation is an epigenetic process that provides "marks" in the genome by which genes are set to be transcriptionally activated or silenced. Epigenomic marks are heritable but are also responsive to environmental shifts, such as changes in nutritional status, and are especially vulnerable during development. S-adenosylmethionine is the methyl group donor for DNA methylation and several nutrients are required for the production of S-adenosylmethionine. These methyl nutrients include vitamins (folate, riboflavin, vitamin B12, vitamin B6, choline) and amino acids (methionine, cysteine, serine, glycine). As such, imbalances in the metabolism of these nutrients have the potential to affect DNA methylation. The focus of this review is to provide an overview on the current understanding of the relationship between methyl nutrient status and DNA methylation patterns and the potential role of this interaction in CVD pathology.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 it