Astrocytic VMAT2 in the developing prefrontal cortex is required for normal grooming behavior in mice
Bibliographic record
Abstract
Abstract Astrocytes control synaptic activity by modulating peri-synaptic concentrations of ion and neurotransmitters including dopamine and, as such, can be critically involved in the modulation of some aspect of mammalian behavior. Here we report that genetic mouse model with a reduced medial prefrontal cortex (mPFC) dopamine levels, arising from astrocyte-specific conditional deletion of vesicular monoamine transporter 2 (VMAT2; aVMTA2cKO mice) shows excessive grooming and anxiety-like behaviour. The VMAT2cKO mice also develop a synaptic pathology, expressed through increased relative AMPA vs. NMDA receptor currents in synapses of the dorsal striatum receiving inputs from the mPFC. Importantly, behavioural and synaptic phenotypes are prevented by reexpression of mPFC VMAT2, showing that the deficits are driven by mPFC astrocytes. By analysing human tissue samples, we found that VMAT2 is expressed in human mPFC astrocytes, corroborating the potential translational relevance of our observations in mice. Our study shows that impairments of the astrocytic-control of dopamine in the mPFC has a profound impact on circuit function and behaviours, which resemble symptoms of anxiety disorders and obsessive compulsive disorder (OCD).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".