Sex differences in cocaine self-administration behaviour under Long Access versus Intermittent Access conditions
Bibliographic record
Abstract
A widely accepted rodent model to study cocaine addiction involves allowing animals continuous access to drug during long self-administration sessions (Long-access or LgA). This produces continuously high brain concentrations of drug during each session. This might not model the pharmacokinetics of cocaine use in experienced human users, which are thought to involve intermittently spiking brain cocaine concentrations within and between bouts of use. Intermittent-access (IntA) cocaine self-administration models this spiking pattern in rats. IntA is also particularly effective in increasing incentive motivation for drug. Most IntA studies have been conducted in male rats. Both humans and non-human animals can show sex differences in all phases of the addiction process. We compared cocaine use in female and male rats that self-administered the drug (0.25 mg/kg/injection, i.v.) during 10 daily, 6-h LgA or IntA sessions. Cocaine intake was greatest under LgA, and female LgA rats escalated their intake. However, only IntA rats (both sexes) developed locomotor sensitization to self-administered cocaine and sensitization was greatest in the females. Five and 25 days after the last self-administration session, we quantified incentive motivation for cocaine by measuring breakpoints for the drug (0.083-0.75 mg/kg/injection) under progressive ratio. Breakpoints were similar in IntA and LgA rats. There were no sex differences in breakpoints under LgA. However, under IntA, females reached higher breakpoints for cocaine than males. Thus, LgA might be best suited to study sex differences in cocaine intake, while IntA might be best suited to study sex differences in incentive motivational processes in cocaine addiction.
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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 | 0.001 | 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 | 0.001 |
| 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".