We investigated element accumulation in the arbuscular mycorrhizal fungus Glomus intraradices. Fungal spores and mycelia growing in monoxenic cultures were analyzed. The elemental composition was quantified using particle-induced X-ray emission (PIXE) in combination with scanning transmission ion microscopy. In the spores, Ca and Fe were associated mainly with the spore wall, while P and K showed patchy distributions and their concentrations were correlated. Excess of P in the hyphal growth medium increased the P and Si concentrations in spores and increased the K/Ca ratio in spores. Increased P availability decreased the concentration of Zn and Mn in spores. We concluded that the availability of P influences the uptake and accumulation of several elements in spores. It is demonstrated that PIXE analysis is a powerful tool for quantitative analysis of elemental accumulation in fungal mycelia.
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http://dx.doi.org/10.1128/AEM.00376-08 | DOI Listing |
Nat Rev Gastroenterol Hepatol
January 2025
Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
In patients with disorders of gut-brain interaction (DGBI), overlapping non-gastrointestinal conditions such as fibromyalgia, headaches, gynaecological and urological conditions, sleep disturbances and fatigue are common, as is overlap among DGBI in different regions of the gastrointestinal tract. These overlaps strongly influence patient management and outcome. Shared pathophysiology could explain this scenario, but details are not fully understood.
View Article and Find Full Text PDFJ Public Health (Oxf)
January 2025
Division of Nursing, Midwifery and Social Work, School of Health Sciences, The University of Manchester, Jean McFarlane Building, Oxford Road, Manchester M13 9PL, UK.
Background: As the UK COVID-19 vaccination programme progressed, greater emphasis was placed on the implementation of localized targeted vaccination activities to address inequalities in vaccination coverage. This study examines one UK region's approach to the delivery of targeted vaccination activities and identifies key factors influencing implementation.
Methods: Qualitative interviews were conducted with a purposive sample of key individuals involved in vaccination delivery across Greater Manchester (GM).
Acad Radiol
January 2025
Medical Image Processing Group, 602 Goddard building, 3710 Hamilton Walk, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104 (M.L., M.A., J.K.U., Y.T., C.W., N.P., S.M., D.A.T.). Electronic address:
Rationale And Objectives: Cardiovascular toxicity is a well-known complication of thoracic radiation therapy (RT), leading to increased morbidity and mortality, but existing techniques to predict cardiovascular toxicity have limitations. Predictive biomarkers of cardiovascular toxicity may help to maximize patient outcomes.
Methods: The machine learning optimal biomarker (OBM) method was employed to predict development of cardiotoxicity (based on serial echocardiographic measurements of left ventricular ejection fraction and longitudinal strain) from computed tomography (CT) images in patients with thoracic malignancy undergoing RT.
Curr Top Dev Biol
January 2025
Daniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology and Genomic Medicine, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, United States. Electronic address:
All-trans retinoic acid (ATRA) signaling is a major pathway regulating numerous differentiation, proliferation, and patterning processes throughout life. ATRA biosynthesis depends on the nutritional availability of vitamin A and other retinoids and carotenoids, while it is sensitive to dietary and environmental toxicants. This nutritional and environmental influence requires a robustness response that constantly fine-tunes the ATRA metabolism to maintain a context-specific, physiological range of signaling levels.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
South African Medical Research Council/University of Johannesburg Pan African Centre for Epidemics Research Extramural Unit, Faculty of Health Sciences, University of Johannesburg, Johannesburg, South Africa.
Background: HIV testing is the cornerstone of HIV prevention and a pivotal step in realizing the Joint United Nations Program on HIV/AIDS (UNAIDS) goal of ending AIDS by 2030. Despite the availability of relevant survey data, there exists a research gap in using machine learning (ML) to analyze and predict HIV testing among adults in South Africa. Further investigation is needed to bridge this knowledge gap and inform evidence-based interventions to improve HIV testing.
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