Wolbachia-Based Approaches to Controlling Mosquito-Borne Viral Threats: Innovations, AI Integration, and Future Directions in the Context of Climate Change.

Wolbachia-based mosquito control strategies have gained significant attention as a sustainable approach to reduce the transmission of vector-borne diseases such as dengue, Zika, and chikungunya. These endosymbiotic bacteria can limit the ability of mosquitoes to transmit pathogens, offering a promising alternative to traditional chemical-based interventions. With the growing impact of climate change on mosquito population dynamics and disease transmission, Wolbachia interventions represent an adaptable and resilient strategy for mitigating the public health burden of vector-borne diseases.

Machine-learning models for shoulder rehabilitation exercises classification using a wearable system.

Purpose: The objective of this study is to train and test machine-learning (ML) models to automatically classify shoulder rehabilitation exercises.

Methods: The cohort included both healthy and patients with rotator-cuff (RC) tears. All participants performed six shoulder rehabilitation exercises, following guidelines developed by the American Society of Shoulder and Elbow Therapists.

The Use of Contact Tracing Technologies for Infection Prevention and Control Purposes in Nosocomial Settings: A Systematic Literature Review.

Background: Pandemic management and preparedness are more needed than ever before and there is widespread governmental interest in learning from the COVID-19 pandemic in order to ensure the availability of evidence-based Infection Prevention and Control measures. Contact tracing is integral to Infection Prevention and Control, facilitating breaks in the chain of transmission in a targeted way, identifying individuals who have come into contact with an infected person, and providing them with instruction/advice relating to testing, medical advice and/or self-isolation.

Aim: This study aims to improve our understanding of the use of contact tracing technologies in healthcare settings.

Risk score model to automatically detect prostate cancer patients by integrating diagnostic parameters.

Introduction: Prostate cancer (PCa) is one of the prevailing forms of cancer among men. At present, multiparametric MRI is the imaging method for localizing tumors and staging cancer. Radiomics plays a key role and hold potential for PCa detection, reducing the need for unnecessary biopsies, characterizing tumor aggression, and overseeing PCa recurrence post-treatment.