A computational framework is proposed for virtual optimization of implant configurations of type 1 thyroplasty based on patient-specific laryngeal structures reconstructed from MRI images. Through integration of a muscle mechanics-based laryngeal posturing model, a flow-structure-acoustics interaction voice production model, a real-coded genetic algorithm, and virtual implant insertion, the framework acquires the implant configuration that achieves the optimal acoustic objectives. The framework is showcased by successfully optimizing an implant that restores acoustic features of a diseased voice resulted from unilateral vocal fold paralysis (UVFP) in producing a sustained vowel utterance. The sound intensity is improved from 62 dB (UVFP) to 81 dB (post-correction).
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http://dx.doi.org/10.1121/10.0009084 | DOI Listing |
Proc Natl Acad Sci U S A
January 2025
Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139.
Protein language models (PLMs) have demonstrated impressive success in modeling proteins. However, general-purpose "foundational" PLMs have limited performance in modeling antibodies due to the latter's hypervariable regions, which do not conform to the evolutionary conservation principles that such models rely on. In this study, we propose a transfer learning framework called Antibody Mutagenesis-Augmented Processing (AbMAP), which fine-tunes foundational models for antibody-sequence inputs by supervising on antibody structure and binding specificity examples.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125.
Cognition relies on transforming sensory inputs into a generalizable understanding of the world. Mirror neurons have been proposed to underlie this process, mapping visual representations of others' actions and sensations onto neurons that mediate our own, providing a conduit for understanding. However, this theory has limitations.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
California Institute for Quantitative Biosciences, University of California, Berkeley, CA 94720.
Polysaccharide monooxygenase (PMO) catalysis involves the chemically difficult hydroxylation of unactivated C-H bonds in carbohydrates. The reaction requires reducing equivalents and will utilize either oxygen or hydrogen peroxide as a cosubstrate. Two key mechanistic questions are addressed here: 1) How does the enzyme regulate the timely and tightly controlled electron delivery to the mononuclear copper active site, especially when bound substrate occludes the active site? and 2) How does this electron delivery differ when utilizing oxygen or hydrogen peroxide as a cosubstrate? Using a computational approach, potential paths of electron transfer (ET) to the active site copper ion were identified in a representative AA9 family PMO from (PMO9E).
View Article and Find Full Text PDFPLoS One
January 2025
Taiyuan University, Taiyuan, China.
Internal auditing demands innovative and secure solutions in today's business environment, with increasing competitive pressure and frequent occurrences of risky and illegal behaviours. Blockchain along with secure databases like encryption improves internal audit security through immutability and transparency. Hence integrating blockchain with homomorphic encryption and multi-factor authentication improves privacy and mitigates computational overhead.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Biomedical and Health Informatics, Tsui Laboratory, Children's Hospital of Philadelphia, Philadelphia, PA, United States of America.
Semantical text understanding holds significant importance in natural language processing (NLP). Numerous datasets, such as Quora Question Pairs (QQP), have been devised for this purpose. In our previous study, we developed a Siamese Convolutional Neural Network (S-CNN) that achieved an F1 score of 82.
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