Investigating cocaine- and abstinence-induced effects on astrocyte gene expression in the nucleus accumbens
Bibliographic record
Abstract
In recent years, astrocytes have been increasingly implicated in cellular mechanisms of substance use disorders (SUD). Astrocytes are structurally altered following exposure to drugs of abuse; specifically, astrocytes within the nucleus accumbens (NAc) exhibit significantly decreased surface area, volume, and synaptic colocalization after operant self-administration of cocaine and extinction or protracted abstinence (45 days). However, the mechanisms that elicit these morphological modifications are unknown. The current study aims to elucidate the molecular modifications that lead to observed astrocyte structural changes in rats across cocaine abstinence using astrocyte-specific RiboTag and RNA-seq, as an unbiased, comprehensive approach to identify genes whose transcription or translation change within NAc astrocytes following cocaine self-administration and extended abstinence. Using this method, our data reveal cellular processes including cholesterol biosynthesis that are altered specifically by cocaine self-administration and abstinence, suggesting that astrocyte involvement in these processes is changed in cocaine-abstinent rats. Overall, the results of this study provide insight into astrocyte functional adaptations that occur due to cocaine exposure or during cocaine withdrawal, which may pinpoint further mechanisms that contribute to cocaine-seeking behavior.
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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".