Exploring the Interconnected Mechanisms of Transgenerational Epigenetic Inheritance
Bibliographic record
Abstract
It is estimated that around 70% of all adults around the world have faced trauma in their lives (Benjet et al., 2016). Trauma can cause individuals to undergo epigenetic changes which can lead to health complications in the future (Alegría-Torres et al., 2011). Epigenetics is defined as the study of molecular modifications to DNA through DNA methylation, histone modifications, and non-coding RNAs that can regulate gene expression independent of DNA sequences (Li, 2021). New evidence suggests that epigenetic changes may be passed down to offspring. However, the exact pathway for transgenerational epigenetic inheritance to occur is unknown. While existing theories, including intrauterine programming, miRNA-mediated pathways, and genomic imprinting, offer possible pathways, none can fully account for the spectrum of transgenerational inheritance. This paper will review the three models proposed and will explore the possibility of their combined influence on transgenerational epigenetic inheritance. Exploring epigenetic mechanisms can help offer potential intervention points to relieve the negative impact of trauma on several generations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".