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Dataset supporting results of article described at title [prova]

Background: Cannabinoids induce biphasic effects on memory depending on stress levels. We previously demonstrated that different stress intensities, experienced soon after encoding, impaired rat short-term recognition memory in a time-of-day-dependent manner, and that boosting endocannabinoid anandamide (AEA) levels restored memory performance. Here, we examined if two different stress intensities and time-of-day alter hippocampal endocannabinoid tone, and whether these changes modulate short-term memory. Methods: Male Sprague-Dawley rats were subjected to an object recognition task and exposed, at two different times of the day (i.e., morning or afternoon), to low or high stress conditions, immediately after encoding. Memory retention was assessed 1 hr later. Hippocampal AEA and 2-arachidonoyl glycerol (2-AG) content and the activity of their primary degrading enzymes, fatty acid amide hydrolase (FAAH) and monoacylglycerol lipase (MAGL), were measured soon after testing. Results: Consistent with our previous findings, low stress impaired 1-hr memory performance only in the morning, whereas exposure to high stress impaired memory independently of testing time. Stress exposure decreased AEA levels independently of memory alterations. Interestingly, exposure to high stress decreased 2-AG content and, accordingly, increased MAGL activity, selectively in the afternoon. Thus, to further evaluate 2-AG's role in the modulation of short-term recognition memory, rats were given bilateral intra-hippocampal injections of the 2-AG hydrolysis inhibitor KML29 immediately after training, then subjected to low or high stress conditions and tested 1 hr later. Conclusions: KML29 abolished the time-of-day-dependent impairing effects of stress on short-term memory, ameliorating short-term recognition memory performance.

This dataset contains sensor values from Force Myography (FMG) sensors and Inertial Measurement Units (IMUs) and corresponding Ankle Joint Power and Ground Reaction Force. The FMG strap was positioned about two inches above the ankle of the left leg. Four IMUs were positioned on foot, distal shank, distal thigh, and proximal thigh of the left leg. There are sensors values and corresponding reference values from nine participants and five different walking speeds (0.4 m/s, 0.7 m/s, 1.0 m/s, 1.3 m/s, and 1.6 m/s). This dataset portrays how values from different sensors vary with respect to Ankle Joint Power and Ground Reaction Force. The dataset can be utilized to train machine learning models to predict Ankle Joint Power and Ground Reaction Force using FMG and IMUs sensor values, which in turn can eliminate the requirement of a complex biomechanical setup to measure Ankle Joint Power and Ground Reaction Force.