One Health (OH) is an integrated approach aiming at improving the health of people, animals, and ecosystems. It recognizes the interconnectedness of human health with the health of animals, plants, and the environment. Since Somali people's livelihoods are mainly based on livestock, agriculture, marine resources, and their shared environment, OH-oriented initiatives could significantly impact the country toward reducing complex problems affecting the health of humans, animals, and the environment. The term "One Health" was first introduced into the global scientific community in September 2004 and in 2013 in Somalia. After ten years, there is still a long road ahead for implementing the OH approach in the country. Herein, we present the status, opportunities, and challenges of OH in Somalia and recommend ways to promote and institutionalize it. The country has been involved in various OH initiatives solely driven by external funding, focusing on research, capacity development, and community interventions, apart from university-led initiatives such as Somali One Health Centre. In Somalia, OH initiatives face numerous challenges, ranging from limited infrastructure and resources to weak governance and institutional capacity. We urge the Somali government to address these challenges and prioritize OH as the main approach to tackling critical health issues. We suggest the Somali government institutionalize and implement OH actions at all administrative levels, including Federal, State, District, and community, through a mechanism to improve multisectoral coordination and collaboration to predict, prevent, detect, control, and respond to communicable and non-communicable diseases at the human-animal-ecosystem interface for improving health outcomes for all.
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http://dx.doi.org/10.1016/j.onehlt.2023.100666 | DOI Listing |
Sci Rep
December 2024
Department of Medical Microbiology, Radboudumc, Nijmegen, The Netherlands.
The aetiology of Alzheimer's disease (AD) and Parkinson's disease (PD) are unknown and tend to manifest at a late stage in life; even though these neurodegenerative diseases are caused by different affected proteins, they are both characterized by neuroinflammation. Links between bacterial and viral infection and AD/PD has been suggested in several studies, however, few have attempted to establish a link between fungal infection and AD/PD. In this study we adopted a nanopore-based sequencing approach to characterise the presence or absence of fungal genera in both human brain tissue and cerebrospinal fluid (CSF).
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December 2024
School of Physical Education, Southwest Petroleum University, Chengdu, 610500, China.
Stroke is one of the leading causes of death in developing countries, and China bears the largest global burden of stroke. This study aims to investigate the relationship between different dimensions of physical activity levels and stroke risk using a nationally representative database. We performed a cross-sectional analysis using data from the China Health and Retirement Longitudinal Study (CHARLS) 2020.
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December 2024
KAUST Center of Excellence for Smart Health (KCSH), King Abdullah University of Science and Technology, Thuwal, 23955, Saudi Arabia.
Analyzing microbial samples remains computationally challenging due to their diversity and complexity. The lack of robust de novo protein function prediction methods exacerbates the difficulty in deriving functional insights from these samples. Traditional prediction methods, dependent on homology and sequence similarity, often fail to predict functions for novel proteins and proteins without known homologs.
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December 2024
Department of Diagnostic Radiology, Dalhousie University, Halifax, Canada.
The goal of this study was to determine how radiologists' rating of image quality when using 0.5T Magnetic Resonance Imaging (MRI) compares to Computed Tomography (CT) for visualization of pathology and evaluation of specific anatomic regions within the paranasal sinuses. 42 patients with clinical CT scans opted to have a 0.
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December 2024
School of Mechanical Engineering, Liaoning Engineering Vocational College, Tieling, 112008, Liaoning, People's Republic of China.
The paper proposes a multi-rigid-body system state identification method based on self-healing model in order to improve the accuracy and reliability of CNC machine tools. Firstly, considering the influence of the joint surface, the Lagrange method is used to establish the mechanical model of the multi-rigid-body system. We input acceleration information and use the second-order modulation function to complete the online real-time identification of the joint surface parameters, thereby establishing the self-healing mechanical model of the multi-rigid-body system.
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