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Type 1 diabetes, one of the common chronic conditions in children and adolescents, is a serious lifelong condition requiring daily treatment with exogenous insulin for survival. Descriptive epidemiology is important for planning of adequate diabetes health-care provision and could provide clues to aetiology. Over the past few decades, standardised diabetes incidence registries have provided a wealth of data from selected countries.
Prebiotics research in the last decade has come a long way due to the maturation of omics technologies (genomics, transcriptomics, proteomics, metabolomics, and foodomics) and bioinformatics tools.
T-cell lymphoblastic lymphoma (T-LBL) is a rare and aggressive lymphatic cancer, often diagnosed at a young age. Patients are treated with intensive chemotherapy, potentially followed by a hematopoietic stem cell transplantation. Although prognosis of T-LBL has improved with intensified treatment protocols, they are associated with side effects and 10-20% of patients still die from relapsed or refractory disease. Given this, the search toward less toxic anti-lymphoma therapies is ongoing.
Findings from longitudinal research, globally, repeatedly emphasise the importance of a taking an early life course approach to mental health promotion; one that invests in the formative years of development, from early childhood to young adulthood, just prior to the transition to parenthood for most. While population monitoring systems have been developed for this period, they are typically designed for use within discrete stages.
Supratentorial RELA fusion (ST-RELA) ependymomas (EPNs) are resistant tumors without an approved chemotherapeutic treatment. Unfortunately, the molecular mechanisms that lead to chemoresistance traits of ST-RELA remain elusive. The aim of this study was to assess RELA fusion-dependent signaling modules, specifically the role of the Hedgehog (Hh) pathway as a novel targetable vulnerability in ST-RELA.
Against a backdrop ofwidespread global transmission, a number of countries have successfully brought large outbreaks of COVID-19 under control and maintained near-elimination status. A key element of epidemic response is the tracking of disease transmissibility in near real-time. During major out-breaks, the effective reproduction number can be estimated froma time-series of case, hospitalisation or death counts. In low or zero incidence settings, knowing the potential for the virus to spread is a response priority.
Osteoporosis is a chronic skeletal condition characterized by low bone mass and deteriorated microarchitecture of bone tissue and puts tens of millions of people at high risk of fractures. New therapeutic agents like i-bodies, a class of next-generation single-domain antibodies, are needed to overcome some limitations of conventional treatments.
Respiratory syncytial virus is the second most common cause of infant mortality and a major cause of morbidity and mortality in older adults (aged >60 years). Efforts to develop a respiratory syncytial virus vaccine or immunoprophylaxis remain highly active.
Despite the large body of research on missing value distributions and imputation, there is comparatively little literature with a focus on how to make it easy to handle, explore, and impute missing values in data. This paper addresses this gap. The new methodology builds upon tidy data principles, with the goal of integrating missing value handling as a key part of data analysis workflows.
Prenatal depressive symptoms are linked to negative child behavioral and cognitive outcomes and predict later psychopathology in adolescent children. Prior work links prenatal depressive symptoms to child brain structure in regions like the amygdala; however, the relationship between symptoms and the development of brain structure over time remains unclear.