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Discovery of New Synthetic Routes of Amino Acids in Prebiotic Chemistry.
JACS Au
December 2024
Faculty of Synthetic Biology, Shenzhen University of Advanced Technology, Shenzhen 518055, China.
The origin of life on Earth remains one of the most perplexing challenges in biochemistry. While numerous bottom-up experiments under prebiotic conditions have provided valuable insights into the spontaneous chemical genesis of life, there remains a significant gap in the theoretical understanding of the complex reaction processes involved. In this study, we propose a novel approach using a roto-translationally invariant potential (RTIP) formulated with pristine Cartesian coordinates to facilitate the simulation of chemical reactions.
View Article and Find Full Text PDFWeakly supervised learning in thymoma histopathology classification: an interpretable approach.
Front Med (Lausanne)
December 2024
Department of Pathology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Introduction: Thymoma classification is challenging due to its diverse morphology. Accurate classification is crucial for diagnosis, but current methods often struggle with complex tumor subtypes. This study presents an AI-assisted diagnostic model that combines weakly supervised learning with a divide-and-conquer multi-instance learning (MIL) approach to improve classification accuracy and interpretability.
View Article and Find Full Text PDFRobust thoracic CT image registration with environmental adaptability using dynamic Welsch's function and hierarchical structure-awareness strategy.
Quant Imaging Med Surg
December 2024
Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, China.
Article Synopsis
- Developed a new algorithm for thoracic CT image registration that addresses issues like motion, noise, and high-density objects common in medical imaging.
- The methodology uses an anatomical structure-aware approach, utilizing a divide-and-conquer strategy to tailor dissimilarity metrics and regularization to different image regions, while dynamically adapting to noise levels.
- Experimental results indicate that the new method performs as well as, or better than, existing techniques, showing enhanced robustness in noisy environments.
Design of pseudosymmetric protein hetero-oligomers.
Nat Commun
December 2024
Department of Biochemistry, University of Washington, Seattle, WA, 98195, USA.
Pseudosymmetric hetero-oligomers with three or more unique subunits with overall structural (but not sequence) symmetry play key roles in biology, and systematic approaches for generating such proteins de novo would provide new routes to controlling cell signaling and designing complex protein materials. However, the de novo design of protein hetero-oligomers with three or more distinct chains with nearly identical structures is a challenging unsolved problem because it requires the accurate design of multiple protein-protein interfaces simultaneously. Here, we describe a divide-and-conquer approach that breaks the multiple-interface design challenge into a set of more tractable symmetric single-interface redesign tasks, followed by structural recombination of the validated homo-oligomers into pseudosymmetric hetero-oligomers.
View Article and Find Full Text PDFMachine Learning-Engineered Nanozyme System for Synergistic Anti-Tumor Ferroptosis/Apoptosis Therapy.
Small
December 2024
Materials Genome Institute, Shanghai Engineering Research Center for Integrated Circuits and Advanced Display Materials, and Shanghai Engineering Research Center of Organ Repair, Shanghai University, Shanghai, 200444, China.
Nanozymes with multienzyme-like activity have sparked significant interest in anti-tumor therapy via responding to the tumor microenvironment (TME). However, the consequent induction of protective autophagy substantially compromises the therapeutic efficacy. Here, a targeted nanozyme system (Fe-Arg-CDs@ZIF-8/HAD, FZH) is shown, which enhances synergistic anti-tumor ferroptosis/apoptosis therapy by leveraging machine learning (ML).
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