Neurexins Regulate GABA Co-release by Dopamine Neurons
Bibliographic record
Abstract
Summary Midbrain dopamine (DA) neurons are key regulators of basal ganglia functions. The axonal domain of these neurons is highly complex, with a large subset of non-synaptic release sites and a smaller subset of synaptic terminals from which glutamate or GABA are released. The molecular mechanisms regulating the connectivity of DA neurons and their neurochemical identity are unknown. Here we tested the hypothesis that the trans-synaptic cell adhesion molecules neurexins (Nrxns) regulate DA neuron neurotransmission. Conditional deletion of all Nrxns in DA neurons (DAT::Nrxns KO) showed that loss of Nrxns does not impair the basic development and ultrastructural characteristics of DA neuron terminals. However, loss of Nrxns caused an impairment of DA transmission revealed as a reduced rate of DA reuptake following activity-dependent DA release, decreased DA transporter levels, increased vesicular monoamine transporter expression, and impaired amphetamine-induced locomotor activity. Strikingly, electrophysiological recording revealed an increase of GABA co-release from DA neuron axons in the striatum of the KO mice. These findings suggest that Nrxns act as key regulators of DA neuron connectivity and DA-mediated functions. Highlights The study provides the first direct evidence of the role of neurexins in dopaminergic neurons. The synaptic adhesion molecules, neurexins, are not required for maintaining the structure of dopamine neuron terminals. Neurexins regulate dopaminergic neurotransmission through regulation of dopamine reuptake, impacting amphetamine-induced locomotion. Deletion of Nrxns in DA neurons causes a region-specific increase of GABA release by DA neurons.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".