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A functional method for estimating the hip joint center of rotation in children with cerebral palsy

Gait & Posture 2023年 106卷 S176-S177页

作者： Ravera, Emiliano Pablo Rozumalski, Adam CONICET - National University of Entre Ríos Group of Analysis- Modeling- Processing and Clinician Implementation of Biomechanical Signals and Systems- Bioengineering and Bioinformatics Institute Oro Verde Argentina National University of Entre Ríos Human Movement Research Laboratory- School of Engineering Oro Verde Argentina Gillette Children's Specialty Healthcare James R. Gage Center for Gait and Motion Analysis St. Paul- MN USA

IntroductionMost clinical gait laboratories utilize the conventional gait model or one of its variants for planning and evaluating treatment in children with cerebral palsy (CP). Estimation of the hip joint center (HJC) is identified as a major source of error that can influence the model outcomes [Peters2010]. Predictive and functional approaches have been proposed in the literature for HJC estimation. Functional approaches are recommended for subjects with adequate hip range of motion (ROM), while predictive approaches are suggested for subjects with limitations in hip ROM, such as children with CP [Kainz2015]. Because functional approaches require multiplane tasks like StarArc movement to calibrate it. Recently, Ravera and Peterson (2021) proposed a regularized version of the well-known symmetric center of rotation estimation method (SCoRE)[Erigh2006] that does not require additional movements for HJC estimation, called RSCoRE. Research questionIs it feasible to estimate the HJC in children with CP using RSCoRE without the need for additional functional calibration tasks? MethodsThis study included 128 individuals with cerebral palsy who visited the Gait and Motion Analysis Lab at Gillette Children’s Specialty Healthcare in 2020. As per standard clinical practice, each participant underwent one static trial and five walking trials. Additionally, functional calibration tasks consisting of one trial of two consecutive StarArc movements were conducted for each *** Procrustes algorithm was applied to the data to enforce rigid body constraints on segmental markers. The StarArc movement and walking trials were used to perform the SCoRE and RSCoRE methods, respectively. To adapt RSCoRE to CP walking patterns, we included the range variation of each segment in its anisotropic matrix (refer to equation B.4 in Ravera and Peterson (2021)). The accuracy of the functional methods (SCoRE and RSCoRE) was evaluated, and the residual was used to quantify the global accuracy o

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Corrigendum to "Selective dorsal rhizotomy and its effect on muscle force during walking: A comprehensive study" [J. Biomech. 164 (2024) 111968]

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Journal of biomechanics 2024年 168卷 112106页

作者： Emiliano Pablo Ravera Adam Rozumalski Group of Analysis Modeling Processing and Clinician Implementation of Biomechanical Signals and Systems Bioengineering and Bioinformatics Institute CONICET-UNER Oro Verde Argentina Human Movement Research Laboratory School of Engineering National University of Entre Ríos (UNER) Oro Verde Argentina. Electronic address: emiliano.ravera@uner.edu.ar. The James R. Gage Center for Gait & Motion Analysis Gillette Children's Specialty Healthcare St. Paul MN USA. Electronic address: arozumalski@***.

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Biomedical data and AI

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Science China Life Sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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The Budapest amyloid predictor and its applications

arXiv

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arXiv 2020年

作者： Keresztes, László Szögi, Evelin Varga, Bálint Farkas, Viktor Perczel, András Grolmusz, Vince PIT Bioinformatics Group Eötvös University BudapestH-1117 Hungary Uratim Ltd. BudapestH-1118 Hungary MTA-ELTE Protein Modeling Research Group Eötvös University BudapestH-1117 Hungary Laboratory of Structural Chemistry and Biology Eötvös University BudapestH-1117 Hungary

Summary: The amyloid state of proteins is widely studied with relevancy in neurology, biochemistry, and biotechnology. In contrast with amorphous aggregation, the amyloid state has a well-defined structure, consisting of parallel and anti-parallel β-sheets in a periodically repeated formation. The understanding of the amyloid state is growing with the development of novel molecular imaging tools, like cryogenic electron microscopy. Sequence-based amyloid predictors were developed by using mostly artificial neural networks (ANNs) as the underlying computational techniques. From a good neural network-based predictor, it is a very difficult task to identify those attributes of the input amino acid sequence, which implied the decision of the network. Here we present a Support Vector Machine (SVM)-based predictor for hexapeptides with correctness higher than 84%, i.e., it is at least as good as the published ANN-based tools. Unlike the artificial neural networks, the decision of the SVMs are much easier to analyze, and from a good predictor, we can infer rich biochemical knowledge. Availability and Implementation: The Budapest Amyloid Predictor webserver is freely available at https://***/bap. Copyright © 2020, The Authors. All rights reserved.

关键词： Glycoproteins

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Molecular dynamics of the immune checkpoint Programmed Cell Death Protein I, PD-1: Conformational changes of the BC-loop upon binding of the ligand PD-L1 and the monoclonal antibody nivolumab

Molecular dynamics of the immune checkpoint Programmed Cell ...

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IEEE International Conference on bioinformatics and Biomedicine

作者： Bernhard Roither Chris Oostenbrink Wolfgang Schreiner Institute of Biosimulation and Bioinformatics Medical University of ViennaViennaAustria Institute of Molecular Modeling and Simulation University of Natural Resources and Life Science ViennaViennaAustria Institute of Biosimulation and Bioinformatic

ISBN: (纸本)9781728118680

The immune checkpoint receptor programmed cell death protein I (PD-1) has been identified as a key target in immunotherapy. PD-1 reduces the risk of autoimmunity by inducing apoptosis in antigen-specific T cells upon interaction with programmed cell death protein ligand I (PD-L1). Various cancer types overexpress PD-L1 to evade the immune system by inducing apoptosis in tumor-specific CD8+ T cells. The clinically used blocking antibody nivolumab binds to PD-1 and inhibits the immunosuppressive interaction with PD-L1. Even though PD-1 is already used as a drug target the exact mechanism of the receptor is still unclear. For instance, the signal transduction from the extra- to the intracellular domain of PD-1 is still a matter of debate. It is hypothesized that the signal transduction is based on an active conformation of PD-1. Here we present the results of the first molecular dynamics simulations of PD-1 with a complete extracellular domain with a focus on the role of the BC-loop of PD-1 upon binding PD-L1 or nivolumab. We could identify that the BC-loop can form three conformations. Nivolumab binds to the BC-loop according to the conformational selection model whereas PD-L1 induces allosterically a conformational change of the BC-loop. Based on the structural differences of the BC-loop a signal transduction based on active conformation cannot be ruled out.

关键词： biochemistry cancer cellular biophysics drug delivery systems drugs molecular biophysics molecular configurations molecular dynamics method nanomedicine patient diagnosis proteins tumours CD274 gene Molecular Conformation cellular biophysics patient diagnosis molecular biology molecular dynamics method Drug Liberation Nanomedicine Signal Transduction PDCD1 gene Apoptosis biochemistry Tumours Pharmaceutical Preparations

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Moltiverse: Molecular Conformer Generation Using Enhanced Sampling Methods

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Journal of chemical information and modeling 2025年 2025 May 27页

作者： Mauricio Bedoya Francisco Adasme-Carreño Paula Andrea Peña-Martínez Camila Muñoz-Gutiérrez Luciano Peña-Tejo José C E Márquez Montesinos Erix W Hernández-Rodríguez Wendy González Leandro Martínez Jans Alzate-Morales Centro de Investigación de Estudios Avanzados del Maule (CIEAM) Vicerrectoría de Investigación y Postgrado Universidad Católica del Maule Talca 3480112 Chile. Laboratorio de Bioinformática y Química Computacional (LBQC) Departamento de Medicina Traslacional Facultad de Medicina Universidad Católica del Maule Talca 3480112 Chile. Doctorado en Ciencias Agrarias Facultad de Ciencias Agrarias Universidad de Talca Talca 3460000 Chile. Center for Bioinformatics Simulation and Modeling (CBSM) and Department of Bioinformatics Faculty of Engineering Universidad de Talca Talca 3460000 Chile. Unidad de Bioinformática Clínica Centro Oncológico Facultad de Medicina Universidad Católica del Maule Talca 3480094 Chile. Institute of Chemistry and Center for Computing in Engineering & Science University of Campinas Campinas 13083-861 SP Brazil.

Accurately predicting the diverse bound-state conformations of small molecules is crucial for successful drug discovery and design, particularly when detailed protein-ligand interactions are unknown. Established tools exist, but efficiently exploring the vast conformational space remains challenging. This work introduces Moltiverse, a novel protocol using enhanced sampling molecular dynamics (MD) simulations for conformer generation. The extended adaptive biasing force (eABF) algorithm combined with metadynamics, guided by a single collective variable (radius of gyration, RDGYR), efficiently samples the conformational landscape of a small molecule. Moltiverse demonstrates comparable accuracy and, in some cases, superior quality when benchmarked against established software like RDKit, CONFORGE, Balloon, iCon, and Conformator in the Platinum Diverse Data set for drug-like small molecules and the Prime data set for macrocycles. We present multiple quantitative metrics and statistical analysis for robust conformer generation algorithm comparisons and provide recommendations for their improvement based on our findings. Our extensive evaluation shows that Moltiverse is particularly effective for challenging systems with high conformational flexibility, such as macrocycles, where it achieves the highest accuracy among the tested algorithms. The physics-based approach employed by Moltiverse effectively handles a wide range of molecular complexities, positioning it as a valuable tool for computational drug discovery workflows requiring accurate representation of molecular flexibility.

关键词： Conformations

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Understanding the impact of selective dorsal rhizotomy in muscle energy expenditure during walking through neuro-musculoskeletal modeling

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Gait & Posture 2022年 97卷 S237-S238页

作者： Pablo Ravera, E. Rozumalski, A. National University of Entre Ríos Human Movement Research Laboratory- School of Engineering Oro Verde Argentina CONICET-UNER Group of Analysis- Modeling- Processing and Clinician Implementation of Biomechanical Signals and Systems- Bioengineering and Bioinformatics Institute Oro Verde Argentina Gillette Children's Specialty Healthcare James R. Gage Center for Gait and Motion Analysis St. Paul MN USA

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modeling muscle force alteration during walking after selective dorsal rhizotomy

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Gait & Posture 2022年 97卷 S244-S245页

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Molecular interactions of glucocorticoid and mineralocorticoid receptors define novel transcription and biological functions

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Journal of Biological Chemistry 2025年第5期301卷 108488页

作者： Sueyoshi, Tatsuya Petrillo, Maria G. Jewell, Christine M. Bortner, Carl D. Perera, Lalith Xu, Xiaojiang Aguayo, Felipe I. Diaz-Jimenez, David Robinson, Anastasia G. Cook, Molly E. Oakley, Robert H. Cidlowski, John A. Molecular Endocrinology Group Signal Transduction Laboratory NIEHS NIH DHHS RaleighNC United States Flow Cytometry Center NIEHS NIH DHHS RaleighNC United States Computational Chemistry & Molecular Modeling Support Group Genomic Integrity & Structural Biology Laboratory NIEHS NIH DHHS RaleighNC United States Integrative Bioinformatics Group NIEHS NIH DHHS RaleighNC United States Department of Pathology and Laboratory Medicine Tulane University School of Medicine New OrleansLA United States Epigenomics and DNA Sequence Core Facility NIEHS NIH DHHS RaleighNC United States

Glucocorticoids are primary stress hormones necessary for life that function to maintain homeostasis. These hormones and their synthetic derivatives are widely used in the clinic to combat disease but are limited by development of resistance and by severe side effects. Understanding how glucocorticoids signal is crucial for developing safer and more effective glucocorticoids. Mechanistically glucocorticoid ligands induce glucocorticoid receptor (GR) homodimerization and regulation of gene expression. Here, we show that GR and mineralocorticoid receptor (MR) form molecular complexes with distinct transcriptional responses that alter the biological roles of GR. MR inhibited GR interaction with genomic DNA and diminished glucocorticoid-regulated gene expression as well as suppressed cell apoptosis induced by GR signaling. Provocatively, multiple therapeutic glucocorticoids differentially induced the GR–MR interaction revealing unknown drug effects that are exploitable for fine-tuning glucocorticoid drug treatments. Molecular modeling of the GR–MR complex predicted an interaction interface residing in the LBD of both GR and MR. Mutation of a key amino acid in the interface of GR compromised GR–MR interaction without affecting GR activity in a gene reporter assay. Overall, our findings uncovered unique crosstalk mechanisms between distinct nuclear receptors providing a novel mechanism of diversity in the action of glucocorticoids that may contribute to context-dependent GR signaling in human health and disease. © 2025

关键词： Transcription

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Corrigendum to “Vascular adhesion protein-1-targeted PET imaging in autoimmune myocarditis” [J Nucl Cardiol 30 (2023) 2760–2772]

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Journal of Nuclear Cardiology 2024年 35卷

作者： Arghavan Jahandideh Jenni Virta Xiang-Guo Li Heidi Liljenbäck Olli Moisio Jesse Ponkamo Noora Rajala Marion Alix Jukka Lehtonen Mikko I. Mäyränpää Tiina A. Salminen Juhani Knuuti Sirpa Jalkanen Antti Saraste Anne Roivainen Turku PET Centre University of Turku Åbo Akademi University and Turku University Hospital 20520 Turku Finland InFLAMES Research Flagship Center University of Turku Turku Finland Department of Chemistry University of Turku Turku Finland Turku Center for Disease Modeling University of Turku Turku Finland Structural Bioinformatics Laboratory Åbo Akademi University Turku Finland Heart and Lung Center Helsinki University and Helsinki University Hospital Helsinki Finland Department of Pathology Helsinki University and Helsinki University Hospital Helsinki Finland MediCity Research Laboratory and Institute of Biomedicine University of Turku Turku Finland Heart Center Turku University Hospital and University of Turku Turku Finland

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