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http://dx.doi.org/10.1111/pbi.14329 | DOI Listing |
Cell Oncol (Dordr)
January 2025
College of Life Science and Technology, Innovation Center of Molecular Diagnostics, Beijing University of Chemical Technology, Beijing, 100029, China.
Purpose: Intrahepatic cholangiocarcinoma (ICC) is a common primary hepatic tumors with a 5-year survival rate of less than 20%. Therefore, it is crucial to elucidate the molecular mechanisms of ICC. Recently, the advance of high-throughput chromosome conformation capture (Hi-C) technology help us look insight into the three-dimensional (3D) genome structure variation during tumorigenesis.
View Article and Find Full Text PDFJSLS
January 2025
Department of Obstetrics and Gynecology, NYU Langone Health Grossman School of Medicine, New York, New York, USA. (Drs. V. Shah, Munoz, and Huang).
Background And Objectives: Operating rooms (ORs) are critical for hospital revenue and cost management, with utilization efficiency directly affecting financial outcomes. Traditional surgical scheduling often results in suboptimal OR use. We aim to build a machine learning (ML) model to predict incision times for robotic-assisted hysterectomies, enhancing scheduling accuracy and hospital finances.
View Article and Find Full Text PDFHeliyon
January 2025
The Institute for Drug Research of the School of Pharmacy, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
RNA-targeting small molecules, particularly RIBOnuclease TArgeting Chimeras (RIBOTACs), represent a powerful and promising therapeutic approach by selectively degrading RNAs through ribonuclease (RNase) recruitment. Despite their potential, the development of effective RNase recruitment tools is still in its early stages and remains a critical area of research. Ribonuclease L (RNase L) is a key ribonuclease targeted by RIBOTACs, yet the tools available for studying RNase L are limited.
View Article and Find Full Text PDFChem Mater
January 2025
Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
New computational tools for solid-state synthesis recipe design are needed in order to accelerate the experimental realization of novel functional materials proposed by high-throughput materials discovery workflows. This work contributes a cellular automaton simulation framework for predicting the time-dependent evolution of intermediate and product phases during solid-state reactions as a function of precursor choice and amount, reaction atmosphere, and heating profile. The simulation captures the effects of reactant particle spatial distribution, particle melting, and reaction atmosphere.
View Article and Find Full Text PDFProteins that selectively bind to a target of interest are foundational components of research pipelines , diagnostics , and therapeutics . Current immunization-based , display- based , and computational approaches for discovering binders are laborious and time- consuming - taking months or more, suffer from high false positives - necessitating extensive secondary screening, and have a high failure rate, especially for disordered proteins and other challenging target classes. Here we establish Phage-Assisted Non-Continuous Selection of Protein Binders (PANCS-binders), an selection platform that links the life cycle of M13 phage to target protein binding though customized proximity-dependent split RNA polymerase biosensors, allowing for complete and comprehensive high-throughput screening of billion-plus member protein variant libraries with high signal-to-noise.
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