A 10-y-old female green tree python ( Morelia viridis) died of fungal pneumonia caused by Purpureocillium lilacinum, which was confirmed histologically and by PCR and subsequent DNA sequencing. The same fungal species was cultivated from a swab taken from the terrarium in which the snake was housed. Clinical and environmental P. lilacinum isolates were indistinguishable by the typing method applied, strongly suggesting clonal relatedness of both isolates. Because no other underlying predisposing respiratory infection could be detected by virus-specific PCR or histopathology, P. lilacinum was considered a primary pulmonary pathogen in this tree python.
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http://dx.doi.org/10.1177/1040638717750430 | DOI Listing |
Int J Gen Med
January 2025
Department of Intensive Care Unit, China Aerospace Science & Industry Corporation 731 hospital, Beijing, People's Republic of China.
Background: The aim of this study was to use five machine learning approaches and logistic regression to design and validate the acute kidney injury (AKI) prediction model for critically ill individuals with cardiogenic shock (CS).
Methods: All patients who diagnosed with CS from the MIMIC-IV database, the eICU database, and Zhongnan hospital of Wuhan university were included in this study. Clinical information, including demographics, comorbidities, vital signs, critical illness scores and laboratory tests was retrospectively collected.
BMC Endocr Disord
January 2025
Department of Public Health Studies, Elon University, Elon, NC, USA.
Background: The increasing prevalence of type 2 diabetes mellitus (T2DM) in lower and middle - income countries call for preventive public health interventions. Studies from Africa including those from Ghana, consistently reveal high T2DM-related mortality rates. While previous research in the Ho municipality has primarily examined risk factors, comorbidity, and quality of life of T2DM patients, this study specifically investigated mortality predictors among these patients.
View Article and Find Full Text PDFHealthcare (Basel)
December 2024
Department of Computer Science, School of Arts, Humanities and Social Sciences, University of Roehampton, London SW15 5PH, UK.
: Diabetes is a metabolic disorder characterized by increased blood sugar levels. Early detection of diabetes could help individuals to manage and delay the progression of this disorder effectively. Machine learning (ML) methods are important in forecasting the progression and diagnosis of different medical problems with better accuracy.
View Article and Find Full Text PDFJ Phys Chem B
January 2025
Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York 10065, United States.
ModeHunter is a modular Python software package for the simulation of 3D biophysical motion across spatial resolution scales using modal analysis of elastic networks. It has been curated from our in-house Python scripts over the last 15 years, with a focus on detecting similarities of elastic motion between atomic structures, coarse-grained graphs, and volumetric data obtained from biophysical or biomedical imaging origins, such as electron microscopy or tomography. With ModeHunter, normal modes of biophysical motion can be analyzed with various static visualization techniques or brought to life by dynamics animation in terms of single or multimode trajectories or decoy ensembles.
View Article and Find Full Text PDFJ Contam Hydrol
January 2025
Department of Computer Science, Instituto Nacional de Astrofísica, Optica y Electrónica, Luis Enrique Erro 1, Tonantzintla, 72840 Puebla, México; Consejo Nacional de Humanidades, Ciencias y Tecnologías (Conahcyt), Insurgentes Sur 1582, Mexico City 03940, Mexico. Electronic address:
This study addresses the critical challenge of assessing the quality of groundwater and surface water, which are essential resources for various societal needs. The main contribution of this study is the application of machine learning models for evaluating water quality, using a national database from Mexico that includes groundwater, lotic (flowing), lentic (stagnant), and coastal water quality parameters. Notably, no comparable water quality classification system currently exists.
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