Radioligand therapy is a targeted cancer treatment modality in which radioisotopes are utilized in the delivery of radiation at targeted cancer cells, with the goal of sparing normal cells. Prostate cancer is a well-known radiosensitive disease, historically treated with radioisotopes such as Strontium-89, Samarium-153, and Radium-223 for palliation of bone metastases. Recently, prostate specific membrane antigen (PSMA) has recently been employed as a radioligand target due to its unique properties of high expression on the surface of prostate cancer cells, limited expression in normal tissue, function as an internalizing cell surface receptor, and increased expression with androgen deprivation therapy.
View Article and Find Full Text PDFTransforming abundant thermal energy into electrical energy is an essential and sustainable solution to meet the rapidly growing global energy demand. In this communication, we report an electrical poling-free molecular complex [Zn(bpy)](ClO)·HO (1) with an appreciable pyroelectric coefficient value of 25 μC m K. This allowed us to harvest waste heat energy using a pyroelectric nanogenerator (PyG) device of 1, a relatively unexplored area for molecular complexes.
View Article and Find Full Text PDFThe TonB system of resolves the dilemma posed by its outer membrane that protects it from a variety of external threats, but also constitutes a diffusion barrier to nutrient uptake. Our working model involves interactions among a set of cytoplasmic membrane-bound proteins: tetrameric ExbB that serves as a scaffold for a dimeric TonB complex (ExbB -TonB ), and also engages dimeric ExbD (ExbB -ExbD ). Through a set of synchronized conformational changes and movements these complexes are proposed to cyclically transduce cytoplasmic membrane protonmotive force to energize active transport of nutrients through TonB-dependent transporters in the outer membrane (described in Gresock et , J.
View Article and Find Full Text PDFChoosing an appropriate collective variable (CV) for any biomolecular process is a challenging task. Researchers are developing methods to solve this issue using a variety of methodologies, most recently using machine learning (ML) methods. In this work, we investigate the mechanism of collapse transition across various lengths of polymer systems through adaptively sampled multiple short trajectories utilizing the Time Lagged Independent Component Analysis (TICA) framework.
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