Impact of Nutritional Epigenomics on Disease Risk and Prevention: Introduction
Bibliographic record
Abstract
This special issue of the Journal of Nutrigenetics and Nutrigenomics covers an emerging topic that has been implicated in disease risk and prevention: nutritional epigenomics. Although the impact of epigenetics has been addressed for the last 3 decades in cancer research, only in recent years has interest surfaced in other fields, including cardiovascular and neurodegenerative diseases, obesity, diabetes and nutrition. Many definitions have been proposed for epigenetics in the literature, but most often epigenetics refers to heritable changes in gene expression that are not accompanied by alterations in DNA sequence [1] . Although there is some debate on which processes fall into this definition, DNA methylation, histone posttranslational modifications and more recently microRNAs are considered the main epigenetic phenomena. Methylation of cytosines, acetylation and methylation of lysine residues in histone proteins and microRNAs influence chromatin architecture and thus gene expression. They are involved in many biological processes including DNA-protein interactions, suppression of transposable element mobility, cellular differentiation, embryogenesis, Xchromosome inactivation and genomic imprinting. Accumulating evidence shows that these epigenetic processes can be influenced by nutritional components. For example, folate and vitamin B 12 participate in the 1-carbon metabolism and are necessary for chromatin methylation reactions. Furthermore, several bioactive food components have been shown to modulate the activity of enzymes that integrate the epigenetic machinery, including DNA methyltransferases and histone deacetylases and acetyltransferases. Thus, nutritional modulation of epigenetic processes adds a further layer of complexity to gene-nutrient interactions and should be considered for the definition of strategies for health promotion and disease prevention. Because epigenetic marks are potentially reversible and are implicated in the pathogenesis of diverse non-communicable diseases representing major public health problems in both developed and developing countries, the epigenome becomes an attractive target for Published online: February 22, 2012
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".