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Pathways to One Health: Enhancing Inter-Sectoral Collaboration in Pakistan.

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Health Services Academy, Chak Shahzad, Park Road, Islamabad, 44000, Pakistan.

One Health is an integrative approach aiming to achieve optimal health outcomes by recognizing the interconnection between humans, animals, and the environment. This study explores the understanding, perspectives, hurdles, and implications of intersectoral collaboration within Pakistan's human health system, focusing on One Health principles. A qualitative phenomenological approach was employed, involving 17 key informant interviews with purposively selected stakeholders from public health, agriculture, veterinary medicine, agriculture and environmental science.

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Nextflow4MS-DIAL: A Reproducible Nextflow-Based Workflow for Liquid Chromatography-Mass Spectrometry Metabolomics Data Processing.

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January 2025

Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida 32611, United States.

Reproducibility in untargeted metabolomics data processing remains a significant challenge due to software limitations and the complex series of steps required. To address these issues, we developed Nextflow4MS-DIAL, a reproducible workflow for liquid chromatography-mass spectrometry (LC-MS) metabolomics data processing, validated with publicly available data from MetaboLights (MTBLS733). Nextflow4MS-DIAL automates LC-MS data processing to minimize human errors from manual data handling.

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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.

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Inherited genetics represents an important contributor to risk of esophageal adenocarcinoma (EAC), and its precursor Barrett's esophagus (BE). Genome-wide association studies have identified ∼30 susceptibility variants for BE/EAC, yet genetic interactions remain unexamined. To address challenges in large-scale G×G scans, we combined knowledge-guided filtering and machine learning approaches, focusing on genes with (A) known/plausible links to BE/EAC pathogenesis (n=493) or (B) prior evidence of biological interactions (n=4,196).

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β-secretase (BACE1) is instrumental in amyloid-β (Aβ) production, with overexpression noted in Alzheimer's disease (AD) neuropathology. The interaction of Aβ with the receptor for advanced glycation endproducts (RAGE) facilitates cerebral uptake of Aβ and exacerbates its neurotoxicity and neuroinflammation, further augmenting BACE1 expression. Given the limitations of previous BACE1 inhibition efforts, the study explores reducing BACE1 expression to mitigate AD pathology.

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