Life Experience and DNA Polymorphisms Influence the Brain Epigenome
Bibliographic record
Abstract
Although not strictly fitting the category of translational neuroscience, I believe the implications of this study where it was found that variability in DNA sequence, a single nucleotide polymorphism (SNP), can influence the epigenetic status of DNA and this is influenced by childhood trauma should be of wide interest. Epigenetics is a burgeoning field of study that seeks to understand how alterations in DNA structure influence a wide range of biological outcomes ranging from cancer susceptibility to behaviour. Across this spectrum, two basic kinds of structure are most often examined. The first is covalent modification of DNA by methylation and second is the interaction between DNA binding proteins (histones for example) and DNA. Both influence the three dimensional structure of DNA and therefore gene expression. Importantly these dynamics are thought to be influenced by environmental conditions that may be positive or detrimental. For example, fetal alcohol syndrome has been shown to alter the methylation status of DNA accounting for the facial/cranial abnormalities that are often observed in these patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".