Strains of antibiotic-resistant bacteria have become more and more prevalent. This has attracted the attention of health agencies worldwide, leading to an urgent search for mechanisms to put a stop to this phenomenon. This study focuses on estimating the probability of a person in Ecuador (at potential risk) contracting an infection due to ampicillin-resistant through the consumption of contaminated water, for which a residence area of people was considered in urban or rural areas. The analysis was carried out using the Bayes Theorem and the results show that in the rural population the probability of contracting an infection of this kind is 8.41% whilst in the urban area the probability is 3.57%. These results show an urgent need to provide safe water sources to the population, as well as to instigate an environmental legislation reform that allows for controlling the release of emerging pollutants, including antibiotics.
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http://dx.doi.org/10.12688/f1000research.14356.1 | DOI Listing |
BMC Oral Health
January 2025
Sub-Institute of Public Safety Standardization, China National Institute of Standardization, No.4 Zhichun Road, Haidian District, Beijing, 100191, PR China.
Background: This study aimed to establish a model for predicting the difficulty of mandibular third molar extraction based on a Bayesian network to meet following requirements: (1) analyse the interaction of the primary risk factors; (2) output quantitative difficulty-evaluation results based on the patient's personal situation; and (3) identify key surgical points and propose surgical protocols to decrease complications.
Methods: Relevant articles were searched to identify risk factors. Clinical knowledge and experience were used to analyse the risk factors to establish the Bayesian network.
Transl Psychiatry
January 2025
Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
Depression treatment responses vary widely among individuals. Identifying objective biomarkers with predictive accuracy for therapeutic outcomes can enhance treatment efficiency and avoid ineffective therapies. This study investigates whether functional near-infrared spectroscopy (fNIRS) and clinical assessment information can predict treatment response in major depressive disorder (MDD) through machine-learning techniques.
View Article and Find Full Text PDFBiometrics
January 2025
Department of Biostatistics, University of Michigan at Ann Arbor, Ann Arbor, MI 48109, United States.
Graphical models are powerful tools to investigate complex dependency structures in high-throughput datasets. However, most existing graphical models make one of two canonical assumptions: (i) a homogeneous graph with a common network for all subjects or (ii) an assumption of normality, especially in the context of Gaussian graphical models. Both assumptions are restrictive and can fail to hold in certain applications such as proteomic networks in cancer.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Obstetrics and Gynecology, Yonsei University Wonju College of Medicine, 20, Ilsan-ro, Wonju-si 26426, Republic of Korea.
Endometriosis is a complex disease with diverse etiologies, including hormonal, immunological, and environmental factors; however, its exact pathogenesis remains unknown. While surgical approaches are the diagnostic and therapeutic gold standard, identifying endometriosis-associated genes is a crucial first step. Five endometriosis-related gene expression studies were selected from the available datasets.
View Article and Find Full Text PDFBMC Psychol
January 2025
School of Public Health, Xuzhou Medical University, 209 Tong Shan Road, Xuzhou, Jiangsu, 221004, China.
Background: This study aims to examine the temporal changes in the incidence, prevalence, and disability-adjusted life years (DALYs) of depressive disorders as well as its association with age, period, and birth cohort among Chinese from 1990 to 2021, and forecast the future trends of incidence rates and numbers from 2022 to 2030.
Methods: Data for analysis were obtained from the Global Burden of Disease (GBD) 2021. Joinpoint analysis was used to calculate the annual percentage change (APC) and average annual percent change (AAPC) to describe the rates of depressive disorders.
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