Cocaine‐induced chromatin modifications are associated with increased gene expression and DNA‐DNA interactions of AUTS2
Bibliographic record
Abstract
Exposure to drugs of abuse alters the epigenetic landscape of the brain's reward regions. We investigated how a combination of chromatin modifications (as previously measured by ChIP‐sequencing) affects genes that are relevant for cocaine response. Autism‐candidate 2 (AUTS2), a gene linked to human evolution and autism, is among the genes with most cocaine‐induced chromatin modifications. We observed by FACS sorting that Auts2 gene‐expression is increased specifically in nucleus accumbens (Nac) D2‐neurons of male cocaine‐IP injected mice. Auts2 mRNA is also up‐regulated potmortem in Nac of male human cocaine addicts. Additionally, by using chromatin conformation capture (3 and 4C) approaches, we found evidence that the Auts2 gene forms a cocaine‐inducible DNA‐loop which enables Auts2 to bind and potentially regulate the expression of Caln1. Cell‐type specific HSV‐mediated overexpression of Auts2 and Caln1 reveals a role for these genes in D2‐neurons during cocaine place preference. We are currently characterizing the character and function of these genes after cocaine exposure. Our results may help to identify how a given gene can mediate a drug‐induced phenotype on the mRNA as well as DNA‐level.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".