Reinforcing effects of fentanyl analogs found in illicit drug markets.

RATIONALE: The potent synthetic opioid fentanyl, and its analogs, continue to drive opioid-related overdoses. Although the pharmacology of fentanyl is well characterized, there is little information about the reinforcing effects of clandestine fentanyl analogs (FAs). OBJECTIVES: Here, we compared the effects of fentanyl and the FAs acetylfentanyl, butyrylfentanyl, and cyclopropylfentanyl on drug self-administration in male and female rats. These FAs feature chemical modifications at the carbonyl moiety of the fentanyl scaffold. METHODS: Sprague-Dawley rats fitted with intravenous jugular catheters were placed in chambers containing two nose poke holes. Active nose poke responses resulted in drug delivery (0.2 mL) over 2 s on a fixed-ratio 1 schedule, followed by a 20 s timeout. Acquisition doses were 0.01 mg/kg/inj for fentanyl and cyclopropylfentanyl, and 0.03 mg/kg/inj for acetylfentanyl and butyrylfentanyl. After 10 days of acquisition, dose-effect testing was carried out, followed by 10 days of saline extinction. RESULTS: Self-administration of fentanyl and FAs was acquired by both male and female rats, with no sex differences in acquisition rate. Fentanyl and FAs showed partial inverted-U dose-effect functions; cyclopropylfentanyl and fentanyl had similar potency, while acetylfentanyl and butyrylfentanyl were less potent. Maximal response rates were similar across drugs, with fentanyl and cyclopropylfentanyl showing maximum responding at 0.001 mg/kg/inj, acetylfentanyl at 0.01 mg/kg/inj, and butyrylfentanyl at 0.003 mg/kg/inj. No sex differences were detected for drug potency, efficacy, or rates of extinction. CONCLUSIONS: Our work provides new evidence that FAs display significant abuse liability in male and female rats, which suggests the potential for compulsive use in humans.

LabGym: Quantification of user-defined animal behaviors using learning-based holistic assessment.

Quantifying animal behavior is important for biological research. Identifying behaviors is the prerequisite of quantifying them. Current computational tools for behavioral quantification typically use high-level properties such as body poses to identify the behaviors, which constrains the information available for a holistic assessment. Here we report LabGym, an open-source computational tool for quantifying animal behaviors without this constraint. In LabGym, we introduce "pattern image" to represent the animal's motion pattern, in addition to "animation" that shows all spatiotemporal details of a behavior. These two pieces of information are assessed holistically by customizable deep neural networks for accurate behavior identifications. The quantitative measurements of each behavior are then calculated. LabGym is applicable for experiments involving multiple animals, requires little programming knowledge to use, and provides visualizations of behavioral datasets. We demonstrate its efficacy in capturing subtle behavioral changes in diverse animal species.