Abnormal Striatal Dopamine Transmission in Schizophrenia
Bibliographic record
Abstract
Despite numerous revisions and reformulations, dopamine (DA) hypothesis of schizophrenia remains a pivotal neurochemical hypothesis of this illness. The aim of this review is to expose and discuss findings from positron emission tomography (PET) or single-photon- emission computed tomography (SPECT) studies investigating DA function in the striatum of medicated, drug-naive or drug-free patients with schizophrenia and in individuals at risk compared with healthy volunteers. DA function was studied at several levels: i) at a presynaptic level where neuroimaging studies investigating DOPA uptake capacity clearly show an increase of DA synthesis in patients with schizophrenia; ii) at a synaptic level where neuroimaging studies investigating dopamine transporter availability (DAT) does not bring any evidence of dysfunction; iii) and finally, neuroimaging studies investigating DA receptor density show a mild increase of D2 receptor density in basic condition and, an hyperreactivity of DA system in dynamic condition. These results are discussed regarding laterality, sub-regions of striatum and implications for the at-risk population. Striatal DA abnormalities are now clearly demonstrated in patients with schizophrenia and at risk population and could constitute an endophenotype of schizophrenia. Subtle sub-clinical striatal DA abnormalities in at risk population could be a biomarker of transition from a vulnerability state to the expression of frank psychosis.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".