Neuroadaptations to antipsychotic drugs: Insights from pre-clinical and human post-mortem studies
Bibliographic record
Abstract
Antipsychotic drugs, all of which block the dopamine D2 receptor to a greater or lesser extent, are the mainstay for the pharmacological treatment of schizophrenia. Engaging in a deeper understanding of how antipsychotics act on the brain and body, at the cellular, molecular and physiological level is vital to comprehend both the beneficial and potentially harmful actions of these medications and stimulate development of novel therapeutics. To address this, we review recent advances in our understanding of neuroadaptations to antipsychotics, focusing on (1) treatment efficacy, (2) impact on brain volume and (3) evidence from human post-mortem studies that attempt to dissect neuropathological effects of antipsychotic drugs from organic schizophrenia neurobiology and (4) cardio-metabolic side effects. Our aim is to stimulate discussion on these highly clinically relevant topics and consider how we might use current and evolving knowledge and new methodologies in the fields of neuropharmacology and neuroscience, to advance our understanding of the long-term impact of antipsychotic treatment. Ultimately, this may inform the clinical use of these drugs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.002 | 0.001 |
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".