Sodium metabisulfite is widely used as a preservative in many food and beverage products, yet its potential effects on cognitive and motor functions at low concentrations remain poorly understood. Evaluating learning, short-term memory, and motor activity is essential, as these functions are critical indicators of neurological health and could be impacted by low-level exposure to sodium metabisulfite. The aim of this study was to investigate the effects of sublethal concentrations of sodium metabisulfite on cognitive and motor functions using (fruit flies) as the model organism.
View Article and Find Full Text PDFBackground: Cardiac arrests often occur in public places, but despite the undisputed impact of bystander CPR, it is debated whether one should act as a rescuer after alcohol consumption due to the perceived adverse effects. We provide the first objective data on the impact of alcohol levels on CPR-skills.
Methods: Pre-specified analysis of a randomised study at the Lowlands music festival (August 2019, the Netherlands) on virtual reality vs face-to-face CPR-training.
Importance: Increased bystander cardiopulmonary resuscitation (CPR) is essential to improve survival after cardiac arrest. Although most studies focus on technical CPR skills, the randomized Lowlands Saves Lives trial prespecified a follow-up survey on other important aspects that affect the widespread performance of CPR.
Objective: To investigate bystander willingness to perform CPR on a stranger, theoretical knowledge retention, and dissemination of CPR awareness 6 months after undergoing short face-to-face and virtual reality (VR) CPR trainings.
Introduction: On-scene detection of acute coronary occlusion (ACO) during ongoing ventricular fibrillation (VF) may facilitate patient-tailored triage and treatment during cardiac arrest. Experimental studies have demonstrated the diagnostic potential of the amplitude spectrum area (AMSA) of the VF-waveform to detect myocardial infarction (MI). In follow-up, we performed this clinical pilot study on VF-waveform based discriminative models to diagnose acute MI due to ACO in real-world VF-patients.
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