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Advances in Heavy Metal Sensing: Utilizing Immobilized Chromogenic Reagents, Nanomaterials Perovskite and Nanonzymes.
Crit Rev Anal Chem
January 2025
Department of Chemistry, University of Delhi, New Delhi, India.
Heavy metal pollution is a major environmental and health problem due to the toxicity and persistence of metals such as lead, mercury, cadmium, and arsenic in water, soil, and air. Advances in sensor technology have significantly improved the detection and quantification of heavy metals, providing real-time monitoring and mitigation tools. This review explores recent developments in heavy metal detection, focusing on innovative uses of immobilized chromogenic reagents, nanomaterials, perovskites, and nanozymes.
View Article and Find Full Text PDFHealth commodity management information system (Dagu-2 Software) implementation status in public health facilities of South-western Oromia, Ethiopia: a mixed method study.
BMC Health Serv Res
January 2025
Logistics Education (LEED) at Kühne Foundation, Hamburg, Germany.
Background: To ensure the complete traceability of healthcare commodities, robust end-to-end data management protocols are needed for the supply chain. In Ethiopia, digital tools like Dagu-2 are used in the lower levels of the healthcare supply chain. However, there is a lack of information regarding the implementation status, factors, and challenges of Dagu-2, as it is a recent upgrade from the offline Dagu-1 application.
View Article and Find Full Text PDFEffectiveness of nurse-led care in patients with rheumatoid arthritis: a systematic review and meta-analysis.
BMJ Open Qual
January 2025
Rheumatology and immunology department, The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China
Objectives: This study sought to assess the effectiveness of nurse-led care (NLC) in patients with rheumatoid arthritis (RA).
Methods: We conducted a comprehensive search of the Cochrane Library, Web of Science, PubMed, Embase, CINAHL, ClinicalTrials.gov databases and the references from relevant literature published prior to May 2023.
Machine learning to predict the decision to perform surgery in hepatic echinococcosis.
HPB (Oxford)
December 2024
Fondazione IRCCS Policlinico San Matteo, SC Chirurgia Generale 1, Pavia, Italy. Electronic address:
Background: Cystic echinococcosis (CE) is a significant public health issue, primarily affecting the liver. While several management strategies exist, there is a lack of predictive tools to guide surgical decisions for hepatic CE. This study aimed to develop predictive models to support surgical decision-making in hepatic CE, enhancing the precision of patient allocation to surgical or non-surgical management pathways.
View Article and Find Full Text PDFFacilitators and Barriers of Large Language Model Adoption Among Nursing Students: A Qualitative Descriptive Study.
J Adv Nurs
January 2025
Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Aim: To explore nursing students' perceptions and experiences of using large language models and identify the facilitators and barriers by applying the Theory of Planned Behaviour.
Design: A qualitative descriptive design.
Method: Between January and June 2024, we conducted individual semi-structured online interviews with 24 nursing students from 13 medical universities across China.
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