Eating Disorders, Heredity and Environmental Activation: Getting Epigenetic Concepts into Practice
Bibliographic record
Abstract
Epigenetic mechanisms are believed to link environmental exposures to alterations in gene expression, and in so doing, to provide a physical substrate for the activation of hereditary potentials by life experiences. In keeping with this idea, accumulating data suggest that epigenetic processes are implicated in eating-disorder (ED) etiology. This paper reviews literature on putative links between epigenetic factors and EDs, and examines ways in which epigenetic programming of gene expression could account for gene-environment interactions acting in the EDs. The paper also presents evidence suggesting that epigenetic processes link malnutrition and life stresses (gestational, perinatal, childhood, and adult) to risk of ED development. Drawing from empirical evidence and clinical experience, we propose that an epigenetically informed understanding of ED etiology can benefit patients, caregivers, and clinicians alike, in the sense that the perspective can reduce judgmental or blameful attitudes on the part of clinicians and caregivers, and increase self-acceptance and optimism about recovery on the part of those affected.
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".