Article
Chemistry, Medicinal
Tareq Hameduh, Michal Mokry, Andrew. D. D. Miller, Zbynek Heger, Yazan Haddad
Summary: Side-chain rotamer prediction is a critical stage in protein 3D structure building, and advanced algorithms have been developed to optimize this process. We investigated the sources of rotamer errors and found that they are associated with solvent accessibility and the tendency of certain amino acid residues to adopt non-canonical rotamers. Understanding the impact of solvent accessibility is crucial for improving side-chain prediction accuracies.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Computer Science, Interdisciplinary Applications
Qing Chang, Jieming Zhang
Summary: Lung image registration is challenging due to the large deformations caused by breath. We propose an unsupervised heterogeneous multi-resolution network (UHMR-Net) that uses an image detail registration module (IDRM) and a lightweight feature local correlation layer to handle complex and small deformations as well as large deformations. The UHMR-Net outperforms classic conventional methods and advanced deep-based methods on the public DIR-Lab 4DCT dataset.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Yunan Liu, Shanshan Zhang, Chunpeng Wang, Jie Xu
Summary: This paper proposes a hybrid resolution NSST prediction method, which better represents the global topology information and local texture details of HR images. By using a deep hybrid resolution network with a residual-in-residual style, features from multiple resolutions are aggregated to achieve more appealing results.
COMPUTER VISION AND IMAGE UNDERSTANDING
(2021)
Article
Computer Science, Artificial Intelligence
Veronica Corona, Angelica Aviles-Rivero, Noemie Debroux, Carole Le Guyader, Carola-Bibiane Schonlieb
Summary: The study introduces a variational multi-task framework that combines reconstruction, registration, and super-resolution tasks in MRI to achieve high-quality, motion-free image reconstructions with fine details and improved texture compared to state-of-the-art methods.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Multidisciplinary Sciences
Jiahua He, Peicong Lin, Ji Chen, Hong Cao, Sheng-You Huang
Summary: In this study, the authors propose an automatic model building method, named EMBuild, which can build high-quality complex structures from intermediate-resolution cryo-EM maps. By integrating multiple techniques and algorithms, EMBuild is able to accurately construct complex structures comparable to manually built ones.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Sami I. Alzarea
Summary: This study identified vaccine candidates for Klebsiella aerogene using reverse vaccinology, and confirmed the stable binding between the vaccine and receptors through molecular docking and molecular dynamics simulations. The binding energies of the complex were also calculated.
SCIENTIFIC REPORTS
(2022)
Article
Mathematics, Applied
Lin Fu, Tian Liang
Summary: Adaptive mesh refinement (AMR) and wavelet-based multi-resolution technique are widely used in scientific computing for higher computational efficiency. This paper proposes a new adaptation strategy for AMR and the multi-resolution method, which examines the solution smoothness based on the high-order TENO reconstruction. The new strategy eliminates the complexity of empirical gradient computing or wavelet analysis and is weakly problem-dependent.
JOURNAL OF SCIENTIFIC COMPUTING
(2022)
Article
Mechanics
Shasha Qiu, Qinglin Duan, Yulong Shao, Songtao Chen, Weian Yao
Summary: This paper presents a combination technique to address the computational cost and high crack resolution requirements in three-dimensional phase-field modeling of cracks. The technique utilizes a simple and robust one-pass staggered solution scheme to implement a hybrid phase-field model, and incorporates adaptive mesh refinement using the predictor-corrector algorithm to minimize the number of nodes. The results show a significant reduction in computational cost and efficient modeling of complex crack events.
ENGINEERING FRACTURE MECHANICS
(2022)
Article
Chemistry, Medicinal
Shide Liang, Chi Zhang, Mingfu Zhu
Summary: In protein backbone refinements, calculating residue-atom interaction energy can improve the accuracy of protein loop modeling. The developed novel method shows good performance in crystal and model environments.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Computer Science, Interdisciplinary Applications
I. M. Bulai, M. C. De Bonis, C. Laurita, V. Sagaria
Summary: This paper discusses a generalized metastatic tumor growth model, which uses an Ordinary Differential Equation (ODE) to describe the primary tumor growth and a transport Partial Differential Equation (PDE) to describe the evolution of metastatic density. The numerical method solves a linear Volterra integral equation (VIE) of the second kind, derived from the reformulation of the ODE-PDE model. Convergence of the method is proven and error estimates are provided. The study focuses on lung and breast cancer, considering different tumor growth laws, metastatic emission rates, and the formation of newborn metastases by clusters of cells.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2023)
Article
Computer Science, Interdisciplinary Applications
Jianjing Zhang, Peng Wang, Robert X. Gao
Summary: This paper presents a hybrid approach to context-aware human action recognition and prediction based on the integration of a convolutional neural network (CNN) and variable-length Markov modeling (VMM) to improve operational flexibility and productivity in human-robot collaboration.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2021)
Article
Public, Environmental & Occupational Health
Weiping Zhao, Yunpeng Sun, Ying Li, Weimin Guan
Summary: The study focuses on the dissemination of COVID-19 in different regions and provinces of China, proposing a hybrid model architecture for analyzing and optimizing COVID-19 data nationwide. Various models such as logistic regression, ARIMA, SVR, MLP, RNN, GRU, and LSTM are used to address the limitations of individual models. The findings provide insights into new cases, quarantines, mortality rates, and the implementation of self-protection measures, enabling government officials to make more informed decisions in disease prevention and control.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Engineering, Electrical & Electronic
H. Yu, H. D. Tuan, E. Dutkiewicz, H. V. Poor, L. Hanzo
Summary: A new hybrid amalgam of analog and baseband digital beamforming is proposed for mmWave multi-user networks. The base station uses a large-scale antenna array with a limited number of RF chains to mitigate path-loss. Each user has a multi-antenna array. The hybrid beamformer design maximizes the geometric means of users' rates, resulting in fair rate distributions without minimum rate constraints. Computationally efficient algorithms based on closed-form low-complexity expressions are developed for large-scale mmWave arrays. Numerical examples demonstrate their efficiency.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Environmental Sciences
Eleanor A. Bash, Lakin Wecker, Mir Mustafizur Rahman, Christine F. Dow, Greg McDermid, Faramarz F. Samavati, Ken Whitehead, Brian J. Moorman, Dorota Medrzycka, Luke Copland
Summary: Terrestrial photographic imagery combined with structure-from-motion (SfM) provides an easy-to-implement method for monitoring environmental systems. However, in-situ positioning data collection and identification of control points are primary roadblocks for using SfM in difficult-to-access locations and time series. A novel approach is proposed for georeferencing point clouds from terrestrial overlapping photos to a reference dataset using a Discrete Global Grid System (DGGS) and a modified iterative closest point algorithm. Results from case studies demonstrate the promise of the approach for georeferencing point clouds with acceptable accuracy, enabling remote monitoring for change-detection.
Article
Engineering, Biomedical
Lianli Liu, Adam Johansson, Yue Cao, Theodore S. Lawrence, James M. Balter
Summary: This study investigates a multi-temporal resolution 3D motion prediction scheme for abdominal organs during radiotherapy. It uses high temporal resolution radial k-space samples for fast breathing motion modeling and lower temporal resolution image time series for slow drifting motion modeling. The results show that the scheme is capable of accurately predicting breathing and slow drifting motion, supporting the potential of MRI-guided abdominal radiotherapy.
PHYSICS IN MEDICINE AND BIOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Indrani Bhattacharya, Arun Seetharaman, Christian Kunder, Wei Shao, Leo C. Chen, Simon J. C. Soerensen, Jeffrey B. Wang, Nikola C. Teslovich, Richard E. Fan, Pejman Ghanouni, James D. Brooks, Geoffrey A. Sonn, Mirabela Rusu
Summary: CorrSigNIA is a radiology-pathology fusion approach that selectively identifies and localizes indolent and aggressive prostate cancer on MRI. It uses registered MRI and whole-mount histopathology images to derive accurate ground truth labels and learn correlated features between radiology and pathology images, achieving high accuracy in detecting and localizing different types of prostate cancer.
MEDICAL IMAGE ANALYSIS
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Heying Duan, Lucia Baratto, Richard E. Fan, Simon John Christoph Soerensen, Tie Liang, Benjamin Inbeh Chung, Alan Eih Chih Thong, Harcharan Gill, Christian Kunder, Tanya Stoyanova, Mirabela Rusu, Andreas M. Loening, Pejman Ghanouni, Guido A. Davidzon, Farshad Moradi, Geoffrey A. Sonn, Andrei Iagaru
Summary: In this study, the authors compared the accuracy of 68Ga-RM2 PET with histopathology in patients with intermediate or high-risk prostate cancer. The results showed that 68Ga-RM2 PET accurately detected intraprostatic lesions and lymph node metastases, with higher specificity and accuracy than mpMRI and similar performance to 68Ga-PSMA11 PET.
JOURNAL OF NUCLEAR MEDICINE
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Indrani Bhattacharya, David S. Lim, Han Lin Aung, Xingchen Liu, Arun Seetharaman, Christian A. Kunder, Wei Shao, Simon J. C. Soerensen, Richard E. Fan, Pejman Ghanouni, Katherine J. To'o, James D. Brooks, Geoffrey A. Sonn, Mirabela Rusu
Summary: This study compares different labeling strategies for training machine learning models to detect and localize prostate cancer on MRI. The results show that models trained with digital pathologist labels perform better than those trained with radiologist labels, and they have higher or comparable performance with pathologist label-trained models. This suggests that digital pathologist labels can improve the accuracy of prostate cancer detection on MRI.
Article
Biochemical Research Methods
Xiaotao Shen, Wei Shao, Chuchu Wang, Liang Liang, Songjie Chen, Sai Zhang, Mirabela Rusu, Michael P. Snyder
Summary: Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics provides systematic profiling of metabolic. However, its applications in precision medicine encounter challenges such as metabolite identification, information loss, and low reproducibility. In this study, a deep-learning-based Pseudo-Mass Spectrometry Imaging (deeppseudoMSI) project is proposed to convert LC-MS raw data to pseudo-MS images and utilize deep learning for disease diagnosis in precision medicine. Extensive tests based on real data demonstrate the superiority and accuracy of deepPseudoMSI over traditional approaches. This framework lays the foundation for future metabolic-based precision medicine.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Multidisciplinary Sciences
Cherrelle Dacon, Courtney Tucker, Linghang Peng, Chang-Chun D. Lee, Ting-Hui Lin, Meng Yuan, Yu Cong, Lingshu Wang, Lauren Purser, Jazmean K. Williams, Chul-Woo Pyo, Ivan Kosik, Zhe Hu, Ming Zhao, Divya Mohan, Andrew J. R. Cooper, Mary Peterson, Jeff Skinner, Saurabh Dixit, Erin Kollins, Louis Huzella, Donna Perry, Russell Byrum, Sanae Lembirik, David Drawbaugh, Brett Eaton, Yi Zhang, Eun Sung Yang, Man Chen, Kwanyee Leung, Rona S. Weinberg, Amarendra Pegu, Daniel E. Geraghty, Edgar Davidson, Iyadh Douagi, Susan Moir, Jonathan W. Yewdell, Connie Schmaljohn, Peter D. Crompton, Michael R. Holbrook, David Nemazee, John R. Mascola, Ian A. Wilson, Joshua Tan
Summary: This study identified six monoclonal antibodies that bind to spike proteins from all seven human-infecting coronaviruses. Two of these antibodies, COV44-62 and COV44-79, showed broad neutralizing activity against alpha- and betacoronaviruses, including the Omicron subvariants of SARS-CoV-2. The fusion peptide region in the spike protein was found to be a potential candidate epitope for next-generation coronavirus vaccine development.
Article
Oncology
Stefania L. Moroianu, Indrani Bhattacharya, Arun Seetharaman, Wei Shao, Christian A. Kunder, Avishkar Sharma, Pejman Ghanouni, Richard E. Fan, Geoffrey A. Sonn, Mirabela Rusu
Summary: This study proposes a computational method for the detection of extraprostatic extension (EPE) on multiparametric MRI using deep learning. The method achieves high sensitivity and specificity, providing a potential independent diagnostic aid for radiologists and facilitating treatment planning.
Article
Immunology
Brian P. Epling, Joseph M. Rocco, Kristin L. Boswell, Elizabeth Laidlaw, Frances Galindo, Anela Kellogg, Sanchita Das, Allison Roder, Elodie Ghedin, Allie Kreitman, Robin L. Dewar, Sophie E. M. Kelly, Heather Kalish, Tauseef Rehman, Jeroen Highbarger, Adam Rupert, Gregory Kocher, Michael R. Holbrook, Andrea Lisco, Maura Manion, Richard A. Koup, Irini Sereti
Summary: Treatment with Nirmatrelvir/ritonavir does not hinder immune responses to SARS-CoV-2. Clinical rebound is associated with the development of a robust antibody and T-cell immune response, indicating a low risk of disease progression. The presence of infectious virus supports the need for isolation and assessment of longer treatment courses.
CLINICAL INFECTIOUS DISEASES
(2023)
Article
Cell Biology
Zhaochun Chen, Peng Zhang, Yumiko Matsuoka, Yaroslav Tsybovsky, Kamille West, Celia Santos, Lisa F. Boyd, Hanh Nguyen, Anna Pomerenke, Tyler Stephens, Adam S. Olia, Baoshan Zhang, Valeria De Giorgi, Michael R. Holbrook, Robin Gross, Elena Postnikova, Nicole L. Garza, Reed F. Johnson, David H. Margulies, Peter D. Kwong, Harvey J. Alter, Ursula J. Buchholz, Paolo Lusso, Patrizia Farci
Summary: This study reports the generation and characterization of two potent human monoclonal antibodies against the SARS-CoV-2 spike protein. The antibodies show broad and potent neutralizing activity against the major SARS-CoV-2 variants of concern and demonstrate in vivo protective and therapeutic efficacy in a hamster model.
Article
Virology
Kassandra L. Carpio, Jill K. Thompson, Steven G. Widen, Jennifer K. Smith, Terry L. Juelich, David E. Clements, Alexander N. Freiberg, Alan D. T. Barrett
Summary: The genetic diversities of mammalian tick-borne flaviviruses were examined using next-generation sequencing. Among the viruses studied, Deer Tick virus, Alkhurma hemorrhagic fever virus, and Kyasanur Forest Disease virus showed low genetic diversity, while Powassan virus exhibited high genetic diversity. The level of genetic diversity could be attributed to the number of tick vector species and amplification hosts each virus can occupy.
Article
Urology & Nephrology
Yash S. Khandwala, Simon John Christoph Soerensen, Shravan Morisetty, Pejman Ghanouni, Richard E. Fan, Sulaiman Vesal, Mirabela Rusu, Geoffrey A. Sonn
Summary: This study aimed to evaluate the association between intraoperative tissue change monitoring (TCM) during HIFU focal therapy for localized prostate cancer and oncological outcomes 12 months afterward. The results showed that greater tissue change during HIFU was associated with less residual cancer after treatment.
EUROPEAN UROLOGY FOCUS
(2023)
Article
Biology
Gabriella Worwa, Timothy K. Cooper, Steven Yeh, Jessica G. Shantha, Amanda M. W. Hischak, Sarah E. Klim, Russell Byrum, Jonathan R. Kurtz, Scott M. Anthony, Nina M. Aiosa, Danny Ragland, Ji Hyun Lee, Marisa St Claire, Carl Davis, Rafi Ahmed, Michael R. Holbrook, Jens H. Kuhn, Erica Ollmann Saphire, Ian Crozier
Summary: Deep characterization of uveitis in a rhesus monkey confirms the association between persistence of Ebola virus RNA and severe immunopathology in the eye, which has broader implications for the prevention and treatment of sight-threatening uveitis in human Ebola virus survivors.
COMMUNICATIONS BIOLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Alessa Hering, Lasse Hansen, Tony C. W. Mok, Albert C. S. Chung, Hanna Siebert, Stephanie Hager, Annkristin Lange, Sven Kuckertz, Stefan Heldmann, Wei Shao, Sulaiman Vesal, Mirabela Rusu, Geoffrey Sonn, Theo Estienne, Maria Vakalopoulou, Luyi Han, Yunzhi Huang, Pew-Thian Yap, Mikael Brudfors, Yael Balbastre, Samuel Joutard, Marc Modat, Gal Lifshitz, Dan Raviv, Jinxin Lv, Qiang Li, Vincent Jaouen, Dimitris Visvikis, Constance Fourcade, Mathieu Rubeaux, Wentao Pan, Zhe Xu, Bailiang Jian, Francesca De Benetti, Marek Wodzinski, Niklas Gunnarsson, Jens Sjolund, Daniel Grzech, Huaqi Qiu, Zeju Li, Alexander Thorley, Jinming Duan, Christoph Grossbroehmer, Andrew Hoopes, Ingerid Reinertsen, Yiming Xiao, Bennett Landman, Yuankai Huo, Keelin Murphy, Nikolas Lessmann, Bram van Ginneken, Adrian V. Dalca, Mattias P. Heinrich
Summary: Image registration is a fundamental task in medical image analysis, but comprehensive comparisons of registration approaches on clinically relevant tasks are lacking. The Learn2Reg challenge addresses these limitations by providing a multi-task medical image registration dataset and evaluation framework. Over 65 individual method submissions were collected from more than 20 unique teams, and a set of metrics was used to evaluate the performance of different approaches. The challenge results demonstrate the potential of pushing the state-of-the-art in medical image registration and challenge the common belief about the speed of conventional registration methods compared to deep-learning-based methods.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2023)
Article
Clinical Neurology
Paymon G. Rezaii, Daniel Herrick, John K. Ratliff, Mirabela Rusu, David Scheinker, Atman M. Desai
Summary: This retrospective cohort study aimed to identify factors associated with readmissions after posterior lumbar fusion (PLF) using machine learning and logistic regression (LR) models. The results showed that discharge status, prior admission, and geographic division were most influential for the LR model, while discharge status, length of stay, and prior admissions were most relevant for the GBM model. GBM outperformed LR in predicting unplanned 30-day readmission and achieved a projected 80% decrease in readmission-associated costs compared to the LACE index model.
Article
Cell Biology
Thayne H. Dickey, Rui Ma, Sachy Orr-Gonzalez, Tarik Ouahes, Palak Patel, Holly McAleese, Brandi Butler, Elizabeth Eudy, Brett Eaton, Michael Murphy, Jennifer L. Kwan, Nichole D. Salinas, Michael R. Holbrook, Lynn E. Lambert, Niraj H. Tolia
Summary: Continued vaccination against SARS-CoV-2 is necessary due to waning immunity and emerging variants. A nanoparticle vaccine displaying the spike receptor-binding domain (RBD) has been developed, with improvements in stability, immune response, and manufacturing ease. The engineered RBD nanoparticles elicit potent neutralizing antibodies that surpass monomeric RBDs, providing protection against emerging variants.
Article
Virology
Sarah van Tol, Adam Hage, Ricardo Rajsbaum, Alexander N. Freiberg
Summary: The expression of TRIM40 in bat cells during Nipah virus infection helps control the infection by reducing viral titers, while its expression is suppressed in human cells. These findings suggest that bats may achieve tolerance to viral infections by regulating the expression of TRIM40.