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Computationally optimized broadly reactive antigens (COBRAs) induce broad and protective immune responses across multiple viral vaccine platforms. However, their suitability for incorporation into live attenuated influenza vaccines (LAIVs) remains uncertain, as antigen modifications could potentially impact LAIV generation, replication, stability, or immunogenicity. In this study, COBRA hemagglutinin (HA) and neuraminidase (NA) antigens designated Y2 and N1I, respectively, of the influenza H1N1 subtype were reverse-engineered into A/Puerto Rico/8/1934 (PR8)-based LAIVs. The impact of HA stability and NA composition on LAIV properties was evaluated in cell culture, mice, and ferrets. COBRA LAIV yields were higher in MDCK cells compared to Vero cells, and a higher HA activation pH was associated with increased LAIV growth in cell culture. The COBRA LAIVs elicited broad antibody responses against pandemic H1N1 viruses and provided robust protection in both mice and ferrets. The standard COBRA LAIV, containing unmodified HA Y2 and NA N1I, had virus inactivation pH and HA activation pH values of 5.4 and 5.6, respectively. In contrast, a modified COBRA LAIV, containing an HA2-K153E mutation and NA from the vaccine strain A/Hawaii/70/2019 (HI19), had a virus inactivation pH of 5.3 and an elevated HA activation pH of 6.0. This modified LAIV had improved growth in cell culture and greater protection from challenge virus lung titers in elderly ferrets. These studies demonstrate the successful integration of COBRA antigen engineering into a LAIV platform. Furthermore, fine-tuning HA stability and NA composition appears to be a promising strategy to enhance LAIVs containing modifications to computationally optimized antigens.
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http://dx.doi.org/10.1016/j.vaccine.2025.127090 | DOI Listing |
J Chem Theory Comput
September 2025
State Key Laboratory of Fine Chemicals, Frontiers Science Center for Smart Materials Oriented Chemical Engineering, Department of Pharmaceutical Sciences, Institute of Chemical Process Systems Engineering, School of Chemical Engineering, Dalian University of Technology, Dalian 116024, China.
Organometallic catalysis lies at the heart of numerous industrial processes that produce bulk and fine chemicals. The search for transition states and screening for organic ligands are vital in designing highly active organometallic catalysts with efficient reaction kinetics. However, identifying accurate transition states necessitates computationally intensive quantum chemistry calculations.
View Article and Find Full Text PDFMed Phys
September 2025
Department of Radiation Oncology, Mayo Clinic in Florida, Jacksonville, Florida, USA.
Background: Dose-driven continuous scanning (DDCS) enhances the efficiency and precision of proton pencil beam delivery by reducing beam pauses inherent in discrete spot scanning (DSS). However, current DDCS optimization studies using traveling salesman problem (TSP) formulations often rely on fixed beam intensity and computationally expensive interpolation for move spot generation, limiting efficiency and methodological robustness.
Purpose: This study introduces a Break Spot-Guided (BSG) method, combined with two acceleration strategies-dose rate skipping and bounding-to optimize beam intensity while minimizing beam delivery time (BDT).
Nat Biomed Eng
September 2025
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Phenotype-driven approaches identify disease-counteracting compounds by analysing the phenotypic signatures that distinguish diseased from healthy states. Here we introduce PDGrapher, a causally inspired graph neural network model that predicts combinatorial perturbagens (sets of therapeutic targets) capable of reversing disease phenotypes. Unlike methods that learn how perturbations alter phenotypes, PDGrapher solves the inverse problem and predicts the perturbagens needed to achieve a desired response by embedding disease cell states into networks, learning a latent representation of these states, and identifying optimal combinatorial perturbations.
View Article and Find Full Text PDFSci Rep
September 2025
Department of Information Engineering, University of Padova, Via Giovanni Gradenigo, 6, 35131, Padova, PD, Italy.
Three approaches to fair ranking in retrieval systems are compared in this paper: mPFR, which is based on the theory of preferences and eigensystems; cRR, which is a simple' 'round robin" method; and mMLP, which is based on linear programming. In order to increase fairness without sacrificing retrieval effectiveness, the techniques post-process the rankings that a retrieval system sends back to users. The findings demonstrate that when it comes to protecting elements, mPFR and cRR accomplish the same level of effectiveness and fairness.
View Article and Find Full Text PDFJ Org Chem
September 2025
School of Chemical and Biopharmaceutical Sciences, Technological University Dublin, City Campus, Grangegorman, Dublin D07 EWV4, Ireland.
A series of unsymmetrically substituted BODIPY dyes featuring fused benzo- or naphtho-fragments on one pyrrolic unit were synthesized from the corresponding pyrrolic precursors. The synthetic route was optimized using a modular approach based on the condensation of formylpyrroles with alkylpyrroles, enabling the identification of precursor combinations that minimize byproduct formation and improve preparative yields. The resulting benzo- and naphtho-fused BODIPYs display intense fluorescence in the red region, with emission maxima spanning 590-680 nm and fluorescence quantum yields ranging from 0.
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