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Prolonged pediatric intensive care unit (PICU) admission, challenges in diagnosis and treatment in a child with hyper IgM syndrome in a tertiary hospital in Tanzania: a case report.
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Hyper immunoglobulin M (IgM) syndromes are a collection of uncommon primary combined immunodeficiency disorders. They are characterized by recurrent bacterial infections due to low levels of IgG, IgA, and IgE, while IgM levels remain normal or high. These conditions stem from a mutation in the CD40 ligand gene or disruptions in the CD40-signaling pathway.
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View Article and Find Full Text PDFSignificance of supervision sampling in control of communicable respiratory disease simulated by a new model during different stages of the disease.
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School of Mathematics and Statistics, Central South University, Changsha, 410083, China.
The coronavirus disease 2019 (COVID-19) interventions in interrupting transmission have paid heavy losses politically and economically. The Chinese government has replaced scaling up testing with monitoring focus groups and randomly supervising sampling, encouraging scientific research on the COVID-19 transmission curve to be confirmed by constructing epidemiological models, which include statistical models, computer simulations, mathematical illustrations of the pathogen and its effects, and several other methodologies. Although predicting and forecasting the propagation of COVID-19 are valuable, they nevertheless present an enormous challenge.
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The fungal disease chytridiomycosis (caused by Batrachochytrium dendrobatidis [Bd]) is a primary contributor to amphibian declines. The frog metamorphic stages, characterised by extensive physiological reorganisation and energy expenditure, have heightened susceptibility to Bd. However, little is known about how these metamorphic stages respond immunologically to Bd infection.
View Article and Find Full Text PDFForest fire probability zonation using dNBR and machine learning models: a case study at the Similipal Biosphere Reserve (SBR), Odisha, India.
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Department of Geography, Fakir Mohan University, Vyasa Vihar, Nuapadhi, Balasore, 756089, Odisha, India.
Forests play a vital role in environmental balance, supporting biodiversity and contributing to atmospheric purification. However, forest fires threaten this balance, making the identification of forest fire probability (FFP) areas crucial for effective mitigation. This study assesses forest fire trends and susceptibility in the Similipal Biosphere Reserve (SBR) from 2012 to 2023 using four machine learning models-extreme gradient boosting tree (XGBTree), AdaBag, random forest (RF), and gradient boosting machine (GBM).
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