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Computational-aided rational mutation design of pertuzumab to overcome active HER2 mutation S310F through antibody-drug conjugates.
Proc Natl Acad Sci U S A
January 2025
Laboratory of Precision Medicine and Biopharmaceuticals, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Recurrent missense mutations in the human epidermal growth factor receptor 2 (HER2) have been identified across various human cancers. Among these mutations, the active S310F mutation in the HER2 extracellular domain stands out as not only oncogenic but also confers resistance to pertuzumab, an antibody drug widely used in clinical cancer therapy, by impeding its binding. In this study, we have successfully employed computational-aided rational design to undertake directed evolution of pertuzumab, resulting in the creation of an evolved pertuzumab variant named Ptz-SA.
View Article and Find Full Text PDFDevelopment and Validation of the Digital Sensitivity Scale for Adults: Cross-Sectional Observational Study.
J Med Internet Res
January 2025
Department of Psychiatry, Yongin Severance Hospital, Yongin, Republic of Korea.
Background: The COVID-19 pandemic has accelerated the digitalization of modern society, extending digital transformation to daily life and psychological evaluation and treatment. However, the development of competencies and literacy in handling digital technology has not kept pace, resulting in a significant disparity among individuals. Existing measurements of digital literacy were developed before widespread information and communications technology device adoption, mainly focusing on one's perceptions of their proficiency and the utility of device operation.
View Article and Find Full Text PDFHospital Medicare Spending per Beneficiary: A Longitudinal Study.
J Healthc Manag
January 2025
Division of Health Care Delivery Research, Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Jacksonville, Florida.
Goal: While studies have examined quality and health outcomes related to the Centers for Medicare & Medicaid Services' (CMS's) Hospital Value-Based Purchasing (HVBP) Program, a significant gap exists in the literature regarding the relationship between pay-for-performance initiatives and hospital financial performance in the program's Efficiency and Cost Reduction domain. This study examined the association between hospitals' cost inefficiency and participation in the HVBP Program by estimating the probability and magnitude of improvement or achievement in the program's Efficiency and Cost Reduction domain.
Methods: The 2014-2019 Efficiency and Cost Reduction domain data were obtained from CMS and merged with the American Hospital Association's Annual Survey Database.
A Susceptible Cell-Selective Delivery (SCSD) of mRNA-Encoded Cas13d Against Influenza Infection.
Adv Sci (Weinh)
January 2025
National Key Laboratory of Veterinary Public Health and Safety, College of Veterinary Medicine, China Agricultural University, Beijing, 100193, China.
To bolster the capacity for managing potential infectious diseases in the future, it is critical to develop specific antiviral drugs that can be rapidly designed and delivered precisely. Herein, a CRISPR/Cas13d system for broad-spectrum targeting of influenza A virus (IAV) from human, avian, and swine sources is designed, incorporating Cas13d mRNA and a tandem CRISPR RNA (crRNA) specific for the highly conserved regions of viral polymerase acidic (PA), nucleoprotein (NP), and matrix (M) gene segments, respectively. Given that the virus targets cells with specific receptors but is not limited to a single organ, a Susceptible Cell Selective Delivery (SCSD) system is developed by modifying a lipid nanoparticle with a peptide mimicking the function of the hemagglutinin of influenza virus to target sialic acid receptors.
View Article and Find Full Text PDFClustering time-evolving networks using the spatiotemporal graph Laplacian.
Chaos
January 2025
School of Mathematical & Computer Sciences, Heriot-Watt University, EH14 4AS Edinburgh, United Kingdom.
Time-evolving graphs arise frequently when modeling complex dynamical systems such as social networks, traffic flow, and biological processes. Developing techniques to identify and analyze communities in these time-varying graph structures is an important challenge. In this work, we generalize existing spectral clustering algorithms from static to dynamic graphs using canonical correlation analysis to capture the temporal evolution of clusters.
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