Reduced<i>Vglut2/Slc17a6</i>Gene Expression Levels throughout the Mouse Subthalamic Nucleus Cause Cell Loss and Structural Disorganization Followed by Increased Motor Activity and Decreased Sugar Consumption
Bibliographic record
Abstract
The subthalamic nucleus (STN) plays a central role in motor, cognitive, and affective behavior. Deep brain stimulation (DBS) of the STN is the most common surgical intervention for advanced Parkinson’s disease (PD), and STN has lately gained attention as target for DBS in neuropsychiatric disorders, including obsessive compulsive disorder, eating disorders, and addiction. Animal studies using STN-DBS, lesioning, or inactivation of STN neurons have been used extensively alongside clinical studies to unravel the structural organization, circuitry, and function of the STN. Recent studies in rodent STN models have exposed different roles for STN neurons in reward-related functions. We have previously shown that the majority of STN neurons express the vesicular glutamate transporter 2 gene (Vglut2/Slc17a6) and that reduction of Vglut2 mRNA levels within the STN of mice [conditional knockout (cKO)] causes reduced postsynaptic activity and behavioral hyperlocomotion. The cKO mice showed less interest in fatty rewards, which motivated analysis of reward-response. The current results demonstrate decreased sugar consumption and strong rearing behavior, whereas biochemical analyses show altered dopaminergic and peptidergic activity in the striatum. The behavioral alterations were in fact correlated with opposite effects in the dorsal versus the ventral striatum. Significant cell loss and disorganization of the STN structure was identified, which likely accounts for the observed alterations. Rare genetic variants of the humanVGLUT2gene exist, and this study shows that reducedVglut2/Slc17a6gene expression levels exclusively within the STN of mice is sufficient to cause strong modifications in both the STN and the mesostriatal dopamine system.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".