Developmental pathway genes and neural plasticity underlying emotional learning and stress-related disorders
Bibliographic record
Abstract
The manipulation of neural plasticity as a means of intervening in the onset and progression of stress-related disorders retains its appeal for many researchers, despite our limited success in translating such interventions from the laboratory to the clinic. Given the challenges of identifying individual genetic variants that confer increased risk for illnesses like depression and post-traumatic stress disorder, some have turned their attention instead to focusing on so-called “master regulators” of plasticity that may provide a means of controlling these potentially impaired processes in psychiatric illnesses. The mammalian homolog of Tailless (TLX), Wnt, and the homeoprotein Otx2 have all been proposed to constitute master regulators of different forms of plasticity which have, in turn, each been implicated in learning and stress-related disorders. In the present review, we provide an overview of the changing distribution of these genes and their roles both during development and in the adult brain. We further discuss how their distinct expression profiles provide clues as to their function, and may inform their suitability as candidate drug targets in the treatment of psychiatric disorders.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".