The N‐acylethanolamines (NAEs) and 2‐arachidonoylglycerol (2‐AG) are bioactive lipids that can modulate inflammatory responses and protect neurons against glutamatergic excitotoxicity. We have used a model of focal cerebral ischemia in young adult mice to investigate the relationship between focal cerebral ischemia and endogenous NAEs. Over the first 24 h after induction of permanent middle cerebral artery occlusion, we observed a time‐dependent increase in all the investigated NAEs, except for anandamide. Moreover, we found an accumulation of 2‐AG at 4 h that returned to basal level 12 h after induction of ischemia. Accumulation of NAEs did not depend on regulation of N‐acylphosphatidylethanolamine‐hydrolyzing phospholipase D or fatty acid amide hydrolase. Treatment with the fatty acid amide hydrolase inhibitor URB597 (cyclohexyl carbamic acid 3′‐carbamoyl‐biphenyl‐3‐yl ester; 1 mg/kg; i.p.) 1.5 h before arterial occlusion decreased the infarct volume in our model system. Our results suggest that NAEs and 2‐AG may be involved in regulation of neuroprotection during focal cerebral ischemia in mice.

Opioid doses in 63 patients after hip fracture surgery were analyzed by repeated time-to-event approach, more richly demonstrating the lengthening time course of dosing over time and the effect of other variables, including time of day. Background: Reduction in consumption of opioid rescue medication is often used as an endpoint when investigating analgesic efficacy of drugs by adjunct treatment, but appropriate methods are needed to analyze analgesic consumption in time. Repeated time-to-event (RTTE) modeling is proposed as a way to describe analgesic consumption by analyzing the timing of consecutive analgesic events. Methods: Retrospective data were obtained from 63 patients receiving standard analgesic treatment including morphine on request after surgery following hip fracture. Times of analgesic events up to 96 h after surgery were extracted from hospital medical records. Parametric RTTE analysis was performed with exponential, Weibull, or Gompertz distribution of analgesic events using NONMEM^®, version 7.2 (ICON Development Solutions, USA). The potential influences of night versus day, sex, and age were investigated on the probability. Results: A Gompertz distribution RTTE model described the data well. The probability of having one or more analgesic events within 24 h was 80% for the first event, 55% for the second event, 31% for the third event, and 18% for fourth or more events for a typical woman of age 80 yr. The probability of analgesic events decreased in time, was reduced to 50% after 3.3 days after surgery, and was significantly lower (32%) during night compared with day. Conclusions: RTTE modeling described analgesic consumption data well and could account for time-dependent changes in probability of analgesic events. Thus, RTTE modeling of analgesic events is proposed as a valuable tool when investigating new approaches to pain management such as opioid-sparing analgesia.