Speaker 4: Gustavo Turecki, Canada
Bibliographic record
Abstract
Title: Regulation of aggressive and impulsive behaviours by a novel lincRNA Abstract High impulsive and aggressive traits associate with poor behavioural self-control and are important predictors of suicide risk. At present, the regulation of these disruptive behavioural traits is poorly understood. Here, we studied the hippocampus of suicides with high impulsive-aggressive traits and identified and characterized a novel long intergenic non-coding RNA (lincRNA), which we called MAOA-Associated lincRNA (MAALIN), due to its ability to regulate the expression of the monoamine oxidase A (MAOA) gene. Using 3 different human cohorts combining brain tissue, neurons and blood samples, we reported consistent hypomethylation in MAALIN’s promoter across tissues. In suicide brains, MAALIN’s promoter hypomethylation was associated with higher MAALIN and lower MAOA expression. MAALIN’s methylation levels were also inversely correlated with measures of impulsivity and aggression behaviors in humans. Luciferase assays confirmed the regulatory role of DNA methylation on MAALIN’s expression. Finally, we used viral mediated gene transfer in mouse brain and showed that MAALIN regulates several indices of aggressive and impulsive behaviours. In conclusion, our findings suggest that changes in DNA methylation patterns allows the expression of a novel lincRNA which, the brain, modulates impulsive and aggression behaviors by interfering with MAOA expression.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.357 | 0.101 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".