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Sleep quality and physical fitness as modifiable contributors of fatigue in childhood cancer survivors.
J Cancer Surviv
January 2025
Department of Oncology, KU Leuven, Louvain, Belgium.
Purpose: Advances in cancer treatment have increased childhood cancer patient's survival rates. However, many childhood cancer survivors (CCS) face long-term effects such as fatigue. This study assessed fatigue in CCS and healthy controls (HCs), its contributors, and associated outcomes.
View Article and Find Full Text PDFNeutralizing antibody immune correlates in COVAIL trial recipients of an mRNA second COVID-19 vaccine boost.
Nat Commun
January 2025
Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA.
Neutralizing antibody titer has been a surrogate endpoint for guiding COVID-19 vaccine approval and use, although the pandemic's evolution and the introduction of variant-adapted vaccine boosters raise questions as to this surrogate's contemporary performance. For 985 recipients of an mRNA second bivalent or monovalent booster containing various Spike inserts [Prototype (Ancestral), Beta, Delta, and/or Omicron BA.1 or BA.
View Article and Find Full Text PDFConformational Antibodies to Proteolipid Protein-1 and Its Peripheral Isoform DM20 in Patients With CNS Autoimmune Demyelinating Disorders.
Neurol Neuroimmunol Neuroinflamm
March 2025
Neuroimmunology Laboratory and Neuroimmunology Research Section, IRCCS Mondino Foundation, Pavia, Italy.
Background And Objectives: Antibodies to proteolipid protein-1 (PLP1-IgG), a major central myelin protein also expressed in the peripheral nervous system (PNS) as the isoform DM20, have been previously identified mostly in patients with multiple sclerosis (MS), with unclear clinical implications. However, most studies relied on nonconformational immunoassays and included few patients with non-MS CNS autoimmune demyelinating disorders (ADDs). We aimed to investigate conformational PLP1-IgG in the whole ADD spectrum.
View Article and Find Full Text PDFPredicting Paediatric Brain Disorders from MRI Images Using Advanced Deep Learning Techniques.
Neuroinformatics
January 2025
Department of CSE, Chandigarh Group of Colleges, Landran, Mohali, India.
The problem at hand is the significant global health challenge posed by children's diseases, where timely and accurate diagnosis is crucial for effective treatment and management. Conventional diagnosis techniques are typical, use tedious processes and generate inaccurate results since they are executed by human beings and cause delays in treatment that can be fatal. Considering these and other shortcomings there exists a need to have more efficient and accurate solutions based on artificial intelligence.
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