Genome Tectonics: Linking Dynamic Genome Organization with Cellular Nutrients
Bibliographic record
Abstract
BACKGROUND: Our daily intake of food provides nutrients for the maintenance of health, growth, and development. The field of nutrigenomics aims to link dietary intake/nutrients to changes in epigenetic status and gene expression. SUMMARY: Although the relationship between our diet and our genes in under intense investigation, there is still a significant aspect of our genome that has received little attention with regard to this. In the past 15 years, the importance of genome organization has become increasingly evident, with research identifying small-scale local changes to large segments of the genome dynamically repositioning within the nucleus in response to/or mediating change in gene expression. The discovery of these dynamic processes and organization maybe as significant as dynamic plate tectonics is to geology, there is little information tying genome organization to specific nutrients or dietary intake. KEY MESSAGES: Here, we detail key principles of genome organization and structure, with emphasis on genome folding and organization, and link how these contribute to our future understand of nutrigenomics.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".