Publications by authors named "C Sainte Rose"

Background: Infection by Cryptococcus gattii can lead to pulmonary or central nervous system (CNS) disease, or both. Whether site of infection and disease severity are associated with C. gattii species and lineages or with certain underlying medical conditions, or both is unclear.

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The accurate, repeatable, and cost-effective quantitative characterization of mild traumatic brain injuries (mTBIs) is crucial for safeguarding the long-term health and performance of high-risk groups, including athletes, emergency responders, and military personnel. However, gaps remain in optimizing mTBI assessment methods, especially regarding the integration of neuromechanical metrics such as reaction time (RT) in predictive models. This review synthesizes existing research on the use of neuromechanical probabilistic models as tools for assessing mTBI, with an emphasis on RT's role in predictive diagnostics.

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Based on the success of cancer immunotherapy, personalized cancer vaccines have emerged as a leading oncology treatment. Antigen presentation on MHC class I (MHC-I) is crucial for the adaptive immune response to cancer cells, necessitating highly predictive computational methods to model this phenomenon. Here, we introduce HLApollo, a transformer-based model for peptide-MHC-I (pMHC-I) presentation prediction, leveraging the language of peptides, MHC, and source proteins.

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Background/objective: Little is known about the rates of rheumatic disease diagnosis among children during the COVID-19 pandemic. We examined the impact of the pandemic on the diagnosis of juvenile idiopathic arthritis (JIA) in the United States.

Methods: We performed a historical cohort study using US commercial insurance data (2016-2021) to identify children aged <18 years without prior JIA diagnosis or treatment in the prior ≥12 months.

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Brain organoids offer unprecedented insights into brain development and disease modeling and hold promise for drug screening. Significant hindrances, however, are morphological and cellular heterogeneity, inter-organoid size differences, cellular stress, and poor reproducibility. Here, we describe a method that reproducibly generates thousands of organoids across multiple hiPSC lines.

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