Bibliographic record
Abstract
Synaptic transmission between ventral tegmental area and nucleus accumbens (NAc) is critically involved in reward-motivated behaviors and thought to be altered in addiction. In addition to dopamine (DA), glutamate is packaged and released by a subset of mesolimbic DA neurons, eliciting EPSCs onto medium spiny neurons in NAc. Little is known about the properties and modulation of glutamate release from DA midbrain terminals and the effect of cocaine. Using an optogenetic approach to selectively activate midbrain DA fibers, we compared the properties and modulation of DA transients and EPSCs measured using fast-scan cyclic voltammetry and whole-cell recordings in mouse brain slices. DA transients and EPSCs were inhibited by DA receptor D2R agonist and showed a marked paired-pulse depression that required 2 min for full recovery. Cocaine depressed EPSCs amplitude by 50% but enhanced the overall DA transmission from midbrain DA neurons. AMPA and NMDA receptor-mediated EPSCs were equally inhibited by cocaine, suggesting a presynaptic mechanism of action. Pharmacological blockage and genetic deletion of D2R in DA neurons prevented the cocaine-induced inhibition of EPSCs and caused a larger increase in DA transient peak, confirming the involvement of presynaptic D2R. These findings demonstrate that acute cocaine inhibits DA and glutamate release from midbrain DA neurons via presynaptic D2R but has differential overall effects on their transmissions in the NAc. We postulate that cocaine, by blocking DA reuptake, prolongs DA transients and facilitates the feedback inhibition of DA and glutamate release from these terminals.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.194 | 0.080 |
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".