The Trace Amine 1 receptor knockout mouse: an animal model with relevance to schizophrenia
Bibliographic record
Abstract
Trace amines have been implicated in a number of neuropsychiatric disorders including depression and schizophrenia. Although long known to modulate neurotransmission indirectly through the release of catecholamines, the identification of the Trace Amine 1 receptor (TA1) offers a mechanism by which trace amines can influence synaptic activity directly. TA1 binds and is activated by trace amines such as beta-phenylethylamine and tyramine. Our pharmacological characterization of mouse TA1 showed that, as in rat and primate, amphetamine is an agonist at this receptor but with surprisingly high potency. Without selective ligands for TA1 that do not also possess catecholamine-releasing properties, however, it has not been possible to study its physiological role in the central nervous system. To that end, a line of mice lacking the TA1 receptor was generated to characterize its contribution to the regulation of behavior. Compared with wild-type littermates, TA1 knockout (KO) mice displayed a deficit in prepulse inhibition. Knockout animals, in which the TA1-agonist influence of amphetamine was absent, showed enhanced sensitivity to the psychomotor-stimulating effect of this drug, which was temporally correlated with significantly larger increases in the release of both dopamine and norepinephrine in the dorsal striatum and associated with a 262% increase in the proportion of striatal high-affinity D2 receptors. TA1 therefore appears to play a modulatory role in catecholaminergic function and represents a potentially novel mechanism for the treatment of neuropsychiatric disorders. Furthermore, the TA1 KO mouse may provide a useful model for the development of treatments for some positive symptoms of schizophrenia.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".