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Traditionally, amber (Succinite) has been used to alleviate all types of pain, skin allergies, and headaches. However, no studies have been conducted on its antidiabetic and antioxidant effects. In this study, differentiated skeletal muscle C2C12 cells were used to demonstrate the protective effects of amber (AMB) against H2O2-induced cell death. In addition, the effects of AMB on glucose uptake and ATP production were investigated. Our results showed that AMB at 10, 25, and 50 μg/mL suppressed the elevation of ROS production induced by H2O2 in a dose-dependent manner. Moreover, AMB enhanced glucose utilization in C2C12 cells through the improvement of ATP production and an increase in PGC-1α gene expression resulting in an amelioration of mitochondrial activity. On the other hand, AMB significantly increased the gene expression of glucose transporters GLUT4 and GLUT1. Our finding suggests that AMB can be used as a natural supplement for diabetes treatment and for the promotion of skeletal muscle function. [ABSTRACT FROM AUTHOR]

Cross-education has been studied extensively with adults, examining the training effects on contralateral homologous muscles. There is less information on the cross-education effects on contralateral heterologous muscles and scant information comparing these responses between adults and youth. The objective was to compare cross-education training effects in male youth and adults to contralateral homologous and heterologous muscles. Forty-two male children (10-13-years) and 42 adults (18-21-years) were tested before and following an 8-week unilateral, dominant or nondominant arm, chest press (CP) training program or control group (14 subjects each). Unilateral testing assessed dominant and nondominant limb strength with leg press and CP 1 repetition maximum (1RM), knee extensors, elbow extensors (EE), elbow flexors, and handgrip maximum voluntary isometric contraction (MVIC) strength and shot put distance and countermovement jump height. Upper-body tests demonstrated large magnitude increases, with children overall exceeding adults (p = 0.05- p < 0.0001, η² : 0.51, 10.4 ± 11.1%). The dominant trained limb showed significantly higher training adaptations than the nondominant limb for the adults with CP 1RM ( p = 0.03, η² : 0.26, 6.7 ± 11.5%) and EE ( p = 0.008, η² : 0.27, 8.8 ± 10.3%) MVIC force. Unilateral CP training induced significantly greater training adaptations with the ipsilateral vs. contralateral limb ( p = 0.008, η² : 0.93, 27.8 ± 12.7%). In conclusion, children demonstrated greater training adaptations than adults, upper-body strength increased with no significant lower-body improvements, and ipsilateral training effects were greater than contralateral training in adults. [ABSTRACT FROM AUTHOR]

Aims: Monitoring drug safety in real‐world settings is the primary aim of pharmacovigilance. Frequent adverse drug reactions (ADRs) are usually identified during drug development. Rare ones are mostly characterized through post‐marketing scrutiny, increasingly with the use of data mining and disproportionality approaches, which lead to new drug safety signals. Nonetheless, waves of excessive numbers of reports, often stirred up by social media, may overwhelm and distort this process, as observed recently with levothyroxine or COVID‐19 vaccines. As human resources become rarer in the field of pharmacovigilance, we aimed to evaluate the performance of an unsupervised co‐clustering method to help the monitoring of drug safety. Methods: A dynamic latent block model (dLBM), based on a time‐dependent co‐clustering generative method, was used to summarize all regional ADR reports (n = 45 269) issued between 1 January 2012 and 28 February 2022. After analysis of their intra and extra interrelationships, all reports were grouped into different cluster types (time, drug, ADR). Results: Our model clustered all reports in 10 time, 10 ADR and 9 drug collections. Based on such clustering, three prominent societal problems were detected, subsequent to public health concerns about drug safety, including a prominent media hype about the perceived safety of COVID‐19 vaccines. The dLBM also highlighted some specific drug–ADR relationships, such as the association between antiplatelets, anticoagulants and bleeding. Conclusions: Co‐clustering and dLBM appear as promising tools to explore large pharmacovigilance databases. They allow, 'unsupervisedly', the detection, exploration and strengthening of safety signals, facilitating the analysis of massive upsurges of reports. [ABSTRACT FROM AUTHOR]

Since March 2022, the centralized cytotoxic preparation unit at the Lille University Hospital (Lille, France) is equipped with augmented reality eyewear for preparation and quality control. The technology enables a user-friendly guided step by step preparation process. It also assists the user by identifying vials through data matrix scan and recording photos at different stages of preparation in order to replace the in-process double visual inspection which will now be carried out a posteriori during the release control. In this paper, we evaluate user feedback and model the learning curve for this new tool. The team's feedback was evaluated using the System Usability Scale (SUS) and Short User Experience Questionnaire (SUEQ). Both questionnaires showed very good acceptance of the tool by our teams, with scores of 79.7 for the SUS and 2.014 for the UEQ. Finally, a learning curve was drawn up according to Wright, showing a learning curve of 91%. This study shows that the tool has been very well integrated into our preparation unit. [ABSTRACT FROM AUTHOR]