Viruses evade detection by the host immune system through the suppression of antiviral pathways. These pathways are thus obscured when measuring the host response to viral infection and cannot be inferred by current network reconstruction methodology. Here we aim to close this gap by providing a novel computational framework for the inference of such inhibited pathways as well as the proteins targeted by the virus to achieve this inhibition. We demonstrate the power of our method by testing it on the response to influenza infection in humans, with and without the viral inhibitory protein NS1, revealing its direct targets and their inhibitory effects.
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http://dx.doi.org/10.1089/cmb.2013.0147 | DOI Listing |
Eur Heart J Digit Health
January 2025
Department of Cardiovascular Surgery of Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Aims: Accurate heart function estimation is vital for detecting and monitoring cardiovascular diseases. While two-dimensional echocardiography (2DE) is widely accessible and used, it requires specialized training, is prone to inter-observer variability, and lacks comprehensive three-dimensional (3D) information. We introduce CardiacField, a computational echocardiography system using a 2DE probe for precise, automated left ventricular (LV) and right ventricular (RV) ejection fraction (EF) estimations, which is especially easy to use for non-cardiovascular healthcare practitioners.
View Article and Find Full Text PDFMed Image Comput Comput Assist Interv
September 2022
Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus.
Quantitative evaluation of pediatric craniofacial anomalies relies on the accurate identification of anatomical landmarks and structures. While segmentation and landmark detection methods in standard clinical images are available in the literature, image-based methods are not directly applicable to 3D photogrammetry because of its unstructured nature consisting in variable numbers of vertices and polygons. In this work, we propose a graph-based convolutional neural network based on Chebyshev polynomials that exploits vertex coordinates, polygonal connectivity, and surface normal vectors to extract multi-resolution spatial features from the 3D photographs.
View Article and Find Full Text PDFSci Technol Adv Mater
December 2024
JST-CREST, Saitama, Japan.
In this review, we present a new set of machine learning-based materials research methodologies for polycrystalline materials developed through the Core Research for Evolutionary Science and Technology project of the Japan Science and Technology Agency. We focus on the constituents of polycrystalline materials (i.e.
View Article and Find Full Text PDFFront Comput Neurosci
January 2025
Interdisciplinary Research Center for Finance and Digital Economy, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
Marketing plays a vital role in the success of a business, driving customer engagement, brand recognition, and revenue growth. Neuromarketing adds depth to this by employing insights into consumer behavior through brain activity and emotional responses to create more effective marketing strategies. Electroencephalogram (EEG) has typically been utilized by researchers for neuromarketing, whereas Eye Tracking (ET) has remained unexplored.
View Article and Find Full Text PDFHeliyon
January 2025
Center for Plastic & Reconstructive Surgery, Department of Orthopedics, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, 310014, China.
Background: The present study aims to explore the metastasis-related signatures in connection with tumor microenvironment (TME), revealing new molecular targets promising in improving osteosarcoma (OS) patients' outcomes.
Methods: The high-throughput sequencing data was downloaded from the TARGET database and performed the ESTIMATE algorithm. Metastasis-related information was obtained from the GSE21257 dataset.
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