The development of multifunctional nanofibrous membranes (NFMs) that enable anti-viral protection during air purification and respiratory disease diagnosis for health management is of increasing importance. Herein, we unraveled a heterostructure-enhanced electro-induced stereocomplexation (HEIS) strategy to fabrication of poly(lactic acid) (PLA) NFMs enabling a combination of efficient PM removal, respiratory monitoring and self-sterilization. The strategy involved an electro-induced stereocomplexation (EIS) approach to trigger the generation of hydrogen bonds between enantiomeric poly(-lactic acid) (PLLA) and poly(-lactic acid) (PDLA) chains, promoting CO dipole alignment and molecular polarization during electrospinning. This was further enhanced by incorporation of Ag-doped TiO (Ag-TIO) nanodielectrics to promote the electroactivity and surface activity, conferring profound refinement of PLA nanofibers (from 460 nm to an ultralow level of 168 nm) and high porosities of over 91 %. Arising from the sustainable generation of plentiful charges based on triboelectric nanogenerator (TENG) mechanisms, the electroactive PLA NFMs exhibited remarkable triboelectric properties even in high-humidity environments (80 %RH), excellent PM filtration efficiency with an ultralow pressure drop (93.1 %, 31.8 Pa, 32 L/min), and 100 % antimicrobial efficiency against both E. coli and S. aureus. Moreover, a deep-learning algorithm based on convolutional neural network (CNN) was proposed to recognize various respiratory patterns. The proposed strategy confers the biodegradable NFMs an unusual combination of ultralow-resistance air purification and machine learning-assisted health management, signifying promising prospects in environmental protection and personal healthcare.
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http://dx.doi.org/10.1016/j.jhazmat.2024.135862 | DOI Listing |
Sci Rep
December 2024
Medical Genomics Research Department, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.
In order to plan and facilitate the culture of personalized / precision medicine in medical practices within any healthcare institution, it is requisite for healthcare professionals like clinicians to have a clear understanding and approach towards the practices of personalized genetic testing. This nationwide cross-sectional study aimed to measure the perceptions and knowledge of clinicians towards personalized genetic testing and assess their current practices of personalized genetic testing in clinical settings through an online self-administered questionnaire in Saudi Arabia. The results of the study revealed that almost two-fifths of participants were responsible for ordering genetic tests directly (39.
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December 2024
Department of Chemical and Biological Engineering, Gachon University, Seongnam, 13120, Republic of Korea.
The Crimean Congo virus has been reported to be a part of the spherical RNA-enveloped viruses from the Bunyaviridae family. Crimean Congo fever (CCHF) is a fatal disease with having fatality rate of up to 40%. It is declared endemic by the World Health Organization.
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December 2024
Department of Clinical Pharmacy, Baoshan Hospital Affiliated to, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
This study investigates the potential treatment of breast cancer utilizing Gentiana robusta King ex Hook. f. (QJ) through an integrated approach involving network pharmacology, molecular docking, and molecular dynamics simulation.
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December 2024
Research Centre for Biomedical Engineering (RCBE), School of Science and Technology, City, University of London, Northampton Square, London, EC1V 0HB, UK.
Traditional methods for management of mental illnesses in the post-pandemic setting can be inaccessible for many individuals due to a multitude of reasons, including financial stresses and anxieties surrounding face-to-face interventions. The use of a point-of-care tool for self-management of stress levels and mental health status is the natural trajectory towards creating solutions for one of the primary contributors to the global burden of disease. Notably, cortisol is the main stress hormone and a key logical indicator of hypothalamic-pituitary adrenal (HPA) axis activity that governs the activation of the human stress system.
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December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
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