Publications by authors named "J V Lupo"

Background: Benfotiamine, a prodrug of thiamine, raises blood levels by 50-100 times to achieve pharmacologic effects. It provides a novel therapeutic direction addressing a well-characterized brain tissue thiamine deficiency and related changes in glucose metabolism in AD. BenfoTeam is a seamless phase 2A-2B "proof of concept" (POC), double-blind, placebo-controlled RCT investigating tolerability, safety, and efficacy of benfotiamine, as a first-in-class small molecule treatment for early AD.

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Article Synopsis
  • * The study analyzed data from nearly 20,000 HD participants to examine how sex and disease burden affect clinical measures and brain imaging markers, using models to account for various variables.
  • * Results indicate that females have less brain volume loss but experience more severe declines in motor and cognitive functions with disease progression, highlighting the need for sex-specific approaches in HD treatment and analysis.
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Unlabelled: Neutralizing antibody titers and binding antibody levels are considered correlates of protection against severe SARS-CoV-2 infection. The clinical utility of serology should be reevaluated in light of the emergence of escape variants, as commercial antibody-binding assays have not been adapted to the virus' antigenic evolution. We compared anti-SARS-CoV-2 antibody titers in four quantitative serological tests based on variable ancestral spike antigens (three in-house ELISAs and the prototype VIDAS SARS-CoV-2 IgG QUANT assay) and neutralization assays against the pseudotyped Wuhan, BA.

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Article Synopsis
  • Technological advancements are enhancing the use of computational methods in fields like health care, particularly in neuro-oncology, to improve clinical decision-making through various biomarkers.
  • Artificial intelligence (AI) algorithms, including radiomics, are being increasingly integrated, but challenges like generalizability and validation hinder their widespread application.
  • This Policy Review aims to provide recommendations for standardizing AI practices in health care, focusing on neuro-oncology, while discussing the importance of reliable AI for future clinical trials.
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The development, application, and benchmarking of artificial intelligence (AI) tools to improve diagnosis, prognostication, and therapy in neuro-oncology are increasing at a rapid pace. This Policy Review provides an overview and critical assessment of the work to date in this field, focusing on diagnostic AI models of key genomic markers, predictive AI models of response before and after therapy, and differentiation of true disease progression from treatment-related changes, which is a considerable challenge based on current clinical care in neuro-oncology. Furthermore, promising future directions, including the use of AI for automated response assessment in neuro-oncology, are discussed.

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