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| http://dx.doi.org/10.1111/acer.13990 | DOI Listing |
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Development and validation of a new nomogram for self-reported OA based on machine learning: a cross-sectional study.
Sci Rep
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Department of Rheumatology and Immunology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Developing a new diagnostic prediction model for osteoarthritis (OA) to assess the likelihood of individuals developing OA is crucial for the timely identification of potential populations of OA. This allows for further diagnosis and intervention, which is significant for improving patient prognosis. Based on the NHANES for the periods of 2011-2012, 2013-2014, and 2015-2016, the study involved 11,366 participants, of whom 1,434 reported a diagnosis of OA.
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Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, P.R. China, 210029; The Affiliated Suqian First People's Hospital of Nanjing Medical University, Suqian, Jiangsu Province, China. Electronic address:
Preoperative detection of muscle-invasive bladder cancer (MIBC) remains a great challenge in practice. We aimed to develop and validate a deep Vesical Imaging Network (ViNet) model for the detection of MIBC using high-resolution Tweighted MR imaging (hrTWI) in a multicenter cohort. ViNet was designed using a modified 3D ResNet, in which, the encoder layers were pretrained using a self-supervised foundation model on over 40,000 cross-modal imaging datasets for transfer learning, and the classification modules were weakly supervised by an experiential knowledge-domain mask indicated by a nnUNet segmentation model.
View Article and Find Full Text PDFDeciphering the mechanisms of action underlying probiotic properties of Shouchella clausii by a functional genomics approach.
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Université Paris-Saclay, 27057INRAE, AgroParisTech, Micalis Institute, 78350, Jouy-en-Josas, France.
Probiotics are widely used for their health promoting effects, though a lot remain to be discovered, particularly on their mechanisms of action at the molecular level. The functional genomic approach is an appropriate method to decipher how probiotics may influence human cell fate and therefore contribute to their health benefit. In the present work, we focused on Shouchella clausii (formerly named Bacillus then Alkalihalobacillus clausii), a spore-forming bacterium that is commercially available as a probiotic for the prevention and the treatment of intestinal dysbiosis and related gastrointestinal disorders, such as diarrhoea.
View Article and Find Full Text PDFElectrochemical destruction of PFAS at low oxidation potential enabled by CeO electrodes utilizing adsorption and activation strategies.
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School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, PR China; Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, Southern University of Science and Technology, Shenzhen 518055, PR China. Electronic address:
The persistence and ecological impact of per- and poly-fluoroalkyl substances (PFAS) in water sources necessitate effective and energy-efficient treatment solutions. This study introduces a novel approach using cerium dioxide (CeO) electrodes enhanced with oxygen vacancy (O) to catalyze the defluorination of PFAS. By leveraging the unique affinity between cerium and fluorine-containing species, our approach enables adsorptive preconcentration and catalytic degradation at low oxidation potentials (1.
View Article and Find Full Text PDFMPIC: Exploring alternative approach to standard convolution in deep neural networks.
Neural Netw
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Institute of Automation, Chinese Academy of Sciences, MAIS, Beijing, 100190, China; University of Chinese Academy of Sciences, Beijing, 101408, China.
In the rapidly evolving field of deep learning, Convolutional Neural Networks (CNNs) retain their unique strengths and applicability in processing grid-structured data such as images, despite the surge of Transformer architectures. This paper explores alternatives to the standard convolution, with the objective of augmenting its feature extraction prowess while maintaining a similar parameter count. We propose innovative solutions targeting depthwise separable convolution and standard convolution, culminating in our Multi-scale Progressive Inference Convolution (MPIC).
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