Overall, iLYTAC converts non-neutralizing antibodies into functional degraders of viral proteins, enabling effective suppression of infection and providing a potential platform for broad-spectrum antiviral therapeutics.
Saiya Ma, Jie Zhang, Sijie Zhou et al.· International Journal of Bio...· 0 citations
Reused liquid batter systems in retail food-establishment represent a potential yet poorly studied source of seafood allergen cross-contact. This study quantified the accumulation of shrimp and cod proteins in a liquid batter across 20 sequential preparation batches, each representing a single portion (20-25 g), and ev...
Xin-Jing Jiang, B. Remington, Stefano Luccioli et al.· Journal of Food Protection· 0 citations
EMS applied during LPS-induced systemic inflammation exacerbated skeletal muscle atrophy and was associated with activation of IL-6/STAT3-C/EBPδ signaling and proteolytic pathways.
Shino Matsukawa, Shinichi Kai, Hideya Seo et al.· Anesthesia and Analgesia· 0 citations
Current structure-based drug design generative models often struggle to faithfully recapitulate genuine ligand-protein binding interactions. Instead, under the coupling of implicit learning architectures and biased training data, they tend to learn spurious statistical correlations. To address this, we propose EIP-Diff...
Huabin Du, Mingyang Wang, M. Luo et al.· Journal of the American Chem...· 0 citations
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A review of recent advances in the structural diversity, evolutionary distribution, and functional specialization of DnaJ proteins across model plants and crops highlights DnaJ proteins as promising molecular targets for crop improvement and climate‐smart agriculture aimed at increasing productivity, stress tolerance,...
Muhammad Arif, H. M. Rehman, S. Bashir et al.· The Plant Genome· 0 citations
This paper introduces Caduceus, a family of MoE-enhanced foundation models built with a hierarchical pre-training paradigm to jointly integrate biological and natural language, and incorporates a multi-task instruction tuning phase, enabling robust protein parsing and natural language question answering.
Mingze Yin, Yiheng Zhu, Jialu Wu et al.· Proceedings of the 32nd ACM...· 0 citations
This work believes this is the first evidence demonstrating an association between these clinically relevant biomarkers of Alzheimer’s disease and phenotypes of brain aging in nonhuman primates, underscoring their importance as models of aging and neurodegenerative disease.
M. Mulholland, Elizabeth R. Magden, Angela M. Achorn et al.· bioRxiv· 0 citations
These findings highlight benzimidazole derivatives, particularly 16a and 17b and their nanoparticle formulations, as promising anticancer candidates, driven primarily by strong cellular potency and favorable safety, substantiating their potential as lead candidates for further optimization and therapeutic development.
Mai Montaser Abdullah, Rania M. Hathout, Reham S. Elezaby et al.· RSC Medicinal Chemistry· 0 citations
Data indicate that platelets support greater activity of FVIII than PLV through stabilization against dissociation of the A2 domain and protection from degradation by APC.
Valerie A Novacovic, Jialan Shi, G. Gilbert· Blood Advances· 0 citations
It is shown that cellulosomal principles can operate in highly reduced cohesin‐dockerin systems, and two additional candidate interacting partners for ClcC appear to bind via a non‐canonical interface.
John Allan, Amias Alstrom-Moore, G. W. Black· FEBS Open Bio· 0 citations
HydroGym is introduced, a solver-independent reinforcement learning platform providing more than 60 validated, openly available flow control environments spanning from canonical laminar flows to complex turbulent flows, with systematic progression in the Reynolds number up to Re = 4 × 105, and Mach number variations in...
Christian Lagemann, Sajeda Mokbel, Miro Gondrum et al.· Nature· 1 citation
It is suggested that biogenically synthesized MgO NPs hold considerable promise as antibacterial and antibiofilm agents against MDR Gram-negative pathogens.
Rafia Anwer, Safdar Ali, Muhammad Shahid Mehmood et al.· International Microbiology· 0 citations
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
