Wildlife policy, the food system and One Health: a complex systems analysis of unintended consequences for the prevention of emerging zoonoses in China, the Democratic Republic of the Congo and the Philippines.

Introduction: Evolving human-wildlife interactions have contributed to emerging zoonoses outbreaks, and pandemic prevention policy for wildlife management and conservation requires enhanced consideration from this perspective. However, the risk of unintended consequences is high. In this study, we aimed to assess how unrecognised complexity and system adaptation can lead to policy failure, and how these dynamics may impact zoonotic spillover risk and food system outcomes.

Exploring Machine Learning Applications in Pediatric Asthma Management: Scoping Review.

Background: The integration of machine learning (ML) in predicting asthma-related outcomes in children presents a novel approach in pediatric health care.

Objective: This scoping review aims to analyze studies published since 2019, focusing on ML algorithms, their applications, and predictive performances.

Methods: We searched Ovid MEDLINE ALL and Embase on Ovid, the Cochrane Library (Wiley), CINAHL (EBSCO), and Web of Science (core collection).

Role of Antioxidant Therapy in the Treatment and Prognosis of COVID-19: A Systematic Review and Meta-analysis of Randomized Controlled Trials.

Background: A significant aspect of the SARS-CoV-2 pathology involves oxidative stress, characterized by an imbalance between the production of harmful free radicals and the body's antioxidant defenses. With the ongoing evolution of SARS-CoV-2, the investigation into non-virus-specific therapeutic options, such as antioxidant therapy, has gained importance.

Objectives: This systematic review and meta-analysis aimed to summarize data from randomized control trials (RCTs) to evaluate the effectiveness and safety of antioxidant therapy in patients with SARS-CoV-2 infection.