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Wastewater Monitoring During the COVID-19 Pandemic in the Veneto Region, Italy: Longitudinal Observational Study.
JMIR Public Health Surveill
January 2025
Unit of Biostatistics, Epidemiology and Public Health, Department of Cardio-Thoraco-Vascular Sciences and Public Health, University of Padova, Via Loredan 18, Padova, Italy, 39 049 8275384.
Background: As the COVID-19 pandemic has affected populations around the world, there has been substantial interest in wastewater-based epidemiology (WBE) as a tool to monitor the spread of SARS-CoV-2. This study investigates the use of WBE to anticipate COVID-19 trends by analyzing the correlation between viral RNA concentrations in wastewater and reported COVID-19 cases in the Veneto region of Italy.
Objective: We aimed to evaluate the effectiveness of the cumulative sum (CUSUM) control chart method in detecting changes in SARS-CoV-2 concentrations in wastewater and its potential as an early warning system for COVID-19 outbreaks.
A study on the relationship between physical exercise and feelings of inferiority among college students: the chain mediating effect of social support and emotional regulation ability.
Front Psychol
January 2025
Sports Training Academy, Chengdu Sport University, Chengdu, Sichuan, China.
Objective: This study aims to explore the impact of physical exercise on feelings of inferiority among college students, focusing on the mediating roles of social support and emotional regulation ability. The research investigates both direct and indirect pathways to understand how physical exercise enhances psychological resilience and mitigates negative self-perceptions.
Methods: A sample of 2,036 college students from 15 provinces in China was surveyed using validated scales for physical exercise, feelings of inferiority, social support, and emotional regulation ability.
Macrophage heterogeneity and oncogenic mechanisms in lung adenocarcinoma: insights from scRNA-seq analysis and predictive modeling.
Front Immunol
January 2025
Tianjin Chest Hospital, Tianjin University, Tianjin, China.
Background: Macrophages play a dual role in the tumor microenvironment(TME), capable of secreting pro-inflammatory factors to combat tumors while also promoting tumor growth through angiogenesis and immune suppression. This study aims to explore the characteristics of macrophages in lung adenocarcinoma (LUAD) and establish a prognostic model based on macrophage-related genes.
Method: We performed scRNA-seq analysis to investigate macrophage heterogeneity and their potential pseudotime evolutionary processes.
Combining single-cell analysis and molecular docking techniques to construct a prognostic model for colon adenocarcinoma and uncovering inhibin subunit βb as a novel therapeutic target.
Front Immunol
January 2025
Department of Preventive Medicine, Shantou University Medical College, Shantou, China.
Background: Colon adenocarcinoma (COAD) is a malignancy with a high mortality rate and complex biological characteristics and heterogeneity, which poses challenges for clinical treatment. Anoikis is a type of programmed cell death that occurs when cells lose their attachment to the extracellular matrix (ECM), and it plays a crucial role in tumor metastasis. However, the specific biological link between anoikis and COAD, as well as its mechanisms in tumor progression, remains unclear, making it a potential new direction for therapeutic strategy research.
View Article and Find Full Text PDFDetecting anomalies in smart wearables for hypertension: a deep learning mechanism.
Front Public Health
January 2025
Department of Computer Science, College of Engineering and Computer Science, Jazan University, Jazan, Saudi Arabia.
Introduction: The growing demand for real-time, affordable, and accessible healthcare has underscored the need for advanced technologies that can provide timely health monitoring. One such area is predicting arterial blood pressure (BP) using non-invasive methods, which is crucial for managing cardiovascular diseases. This research aims to address the limitations of current healthcare systems, particularly in remote areas, by leveraging deep learning techniques in Smart Health Monitoring (SHM).
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