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arXiv 2024年

作者： Zhao, Wenzhao Albert, Steffen Wichtmann, Barbara D. Maurer, Angelika Attenberger, Ulrike Zöllner, Frank G. Hesser, Jürgen School of Information Engineering Nanjing University of Finance and Economics Interdisciplinary Center for Scientific Computing Mannheim Institute for Intelligent Systems in Medicine Medical Faculty Mannheim Heidelberg University Germany Computer Assisted Clinical Medicine Mannheim Institute for Intelligent Systems in Medicine Medical Faculty Mannheim Heidelberg University Germany Clinic of Neuroradiology University Hospital Bonn Germany Department of Diagnostic and Interventional Radiology University Hospital Bonn Germany Department of Biomedical Imaging and Image-guided Therapy Medical University of Vienna Austria Interdisciplinary Center for Scientific Computing Central Institute for Computer Engineering CSZ Heidelberg Center for Model-Based AI Data Analysis and Modeling in Medicine Mannheim Institute for Intelligent Systems in Medicine Medical Faculty Mannheim Heidelberg University Germany

Filter-decomposition-based group equivariant convolutional neural networks (CNNs) have shown promising stability and data efficiency for 3D image feature extraction. However, these networks, which rely on parameter sharing and discrete transformation groups, often underperform in modern deep neural network architectures for processing volumetric images, such as the common 3D medical images. To address these limitations, this paper presents an efficient non-parameter-sharing continuous 3D affine group equivariant neural network for volumetric images. This network uses an adaptive aggregation of Monte Carlo augmented spherical Fourier-Bessel filter bases to improve the efficiency and flexibility of 3D group equivariant CNNs for volumetric data. Unlike existing methods that focus only on angular orthogonality in filter bases, the introduced spherical Bessel Fourier filter base incorporates both angular and radial orthogonality to improve feature extraction. Experiments on four medical image segmentation datasets show that the proposed methods achieve better affine group equivariance and superior segmentation accuracy than existing 3D group equivariant convolutional neural network layers, significantly improving the training stability and data efficiency of conventional CNN layers (at 0.05 significance level). The code is available at https://***/ZhaoWenzhao/WMCSFB. Copyright © 2024, The Authors. All rights reserved.

关键词： Spheres

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Harnessing Information Technology while Teaching in Distress: the Pandemic Toll vs. the Opportunity of Long-Awaited Paradigm Shift

Harnessing Information Technology while Teaching in Distress...

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E-Health and Bioengineering Conference (EHB)

作者： Diana Lungeanu Ioan Dragan Calin Muntean Bogdan Timar “Victor Babes” University of Medicine and Pharmacy Timisoara Romania Center for Modeling Biological Systems and Data Analysis UMF Timisoara Romania West University of Timisoara Romania

ISBN: (数字)9781728188034

ISBN: (纸本)9781728188041

Medical academic teaching has been under persistent scrutiny, while education in general underwent radical transformation in this century, when boundaries between teachers and learners are increasingly blurred and the very concept of reality is re-shaped. Based on a 2019 analysis of the two-year package comprising the biomedical informatics and biostatistics courses at a Romanian University of Medicine and Pharmacy, we conducted an ad-hoc analysis of the Covid-19 pandemic impact on our teaching. We profess that courses of information technology and data science in the medical curriculum should play a driving role in designing new educational approaches and instruments, subsequently contributing to shifting the vision of the future health professionals.

关键词： Education Bioinformatics Pandemics COVID-19 Depression Stress Standards

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The use of 3D-printed surgical guides and models for sinus lift surgery planning and education

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Journal of 3D Printing in Medicine 2019年第3期3卷 145-155页

作者： Tuce, Robert-Angelo Arjoca, Stelian Neagu, Monica Neagu, Adrian Department of Functional Sciences Center for Modeling Biological Systems and Data Analysis Victor Babeş University of Medicine and Pharmacy Timişoara Romania Department of Physics and Astronomy University of Missouri Columbia 65211 MO United States

Aim: To develop 3D printing and dentistry methods for building physical models that enable one to simulate a sinus lift surgery. Materials & methods: The Blue Sky Plan software was used to create a digital model from the cone beam computed tomography scan of the subject's maxilla and to design a surgical guide for sinus augmentation and implant placement. The anatomical model and surgical guide were 3D printed from dental resin. Results: Sinus augmentation and dental implant insertion were carried out on the model as examples of practical skills training for residents in maxillofacial surgery. Conclusion: The 3D-printed models and surgical guides are useful training materials. They could be helpful also in a dental practice for surgical planning and for illustrating the procedure to the patient. © 2019 Future Medicine Ltd.

关键词： 3D digital models biomodels dental education dental implant digital light processing lateral window osteotomy Schneiderian membrane sinus augmentation sinus floor elevation surgical templates

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A Game Theoretic Treatment of Contagion in Trade Networks

arXiv

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arXiv 2025年

作者： McAlister, John S. Brunner, Jesse L. Galvin, Danielle J. Fefferman, Nina H. University of Tennessee - Knoxville Department of Mathematics United States University of Tennessee - Knoxville Department of Ecology and Evolutionary Biology United States National Institute for Modeling Biological Systems NSF Center for the Analysis and Prediction of Pandemic Expansion Washington State University School of Biological Sciences United States University of Tennessee - Knoxville School of Natural Resources United States

Global trade of material goods involves the potential to create pathways for the spread of infectious pathogens. One trade sector in which this synergy is clearly critical is that of wildlife trade networks. This highly complex system involves important and understudied bidirectional coupling between the economic decision making of the stakeholders and the contagion dynamics on the emergent trade network. While each of these components are independently well studied, there is a meaningful gap in understanding the feedback dynamics that can arise between them. In the present study, we describe a general game theoretic model for trade networks of goods susceptible to contagion. The primary result relies on the acyclic nature of the trade network and shows that, through the course of trading with stochastic infections, the probability of infection converges to a directly computable fixed point. This allows us to compute best responses and thus identify equilibria in the game. We present ways to use this model to describe and evaluate trade networks in terms of global and individual risk of infection under a wide variety of structural or individual modifications to the trade network. In capturing the bidirectional coupling of the system, we provide critical insight into the global and individual drivers and consequences for risks of infection inherent in and arising from the global wildlife trade, and any economic trade network with associated contagion *** Codes 05C90, 39A05, 91A43 © 2025, CC BY.

关键词： Game theory

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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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Impact of Iron Deficiency on the Growth and Bioelectrical Profile of Different Gut Bacteria

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MicrobiologyOpen 2025年第3期14卷 e70015页

作者： Elisa Quarta Marwane Bourqqia-Ramzi David Muñoz-Rodriguez María Teresa García-Esteban Antonio Murciano-Cespedosa Álvaro Mateos González Francisco José Conejero-Meca Juan Lombardo-Hernandez Jesús Mansilla-Guardiola Simona Baroni Simonetta Geninatti Crich Stefano Geuna Luca Munaron Deborah Chiabrando Celia Herrera-Rincon Department of Biodiversity Ecology & Evolution and Modeling Data Analysis & Computational Tools for Biology Research Group Biomathematics Unit Faculty of Biological Sciences Complutense University of Madrid Madrid Spain. Department of Molecular Biotechnology and Health Sciences Molecular Biotechnology Center "Guido Tarone" University of Torino Turin Italy. Department of Genetic Physiology and Microbiology Unit of Microbiology Faculty of Biological Sciences Complutense University of Madrid Madrid Spain. Department of Clinical and Biological Sciences University of Torino Turin Italy. Department of Life Science and Systems Biology (DBIOS) University of Torino Turin Italy.

SCOPE:Iron deficiency (ID) is the most common nutritional deficiency worldwide, impacting gut bacteria's metabolism and cellular biochemistry, but its effects on the microbiota-gut-brain axis (MGB) are poorly understood. Early-life ID-related dysbiosis is linked to neurodevelopmental impairments like autism and attention deficit hyperactivity disorder. Studying ID's impact on bacterial signaling can guide interventions to target MGB in iron-deficient populations. This study examined the responses of Escherichia coli (E. coli) and Limosilactobacillus reuteri (L. reuteri) to in-vitro ID conditions using the iron chelator 2,2'-Bipyridyl (BP). METHODS AND RESULTS:We assessed and modeled their growth and cultivability and explored their bioelectric profiles using the voltage-sensitive dye DiBAC4(3). Results showed differential responses: L. reuteri's growth and cultivability were unaffected by BP, while E. coli's growth rate and cultivability decreased under ID. Additionally, we created a deterministic mathematical model that demonstrated a decrease in the population's average reproduction rate in E. coli under ID. Only E. coli exhibited an altered bioelectric profile, marked by increased cell depolarization in ID conditions, which was largely rescued upon the addition of a saturating concentration of iron. CONCLUSION:These findings highlight specific bioelectrical responses in gut bacteria to ID. Understanding this variability is crucial for deciphering the microbiota's role in health and disease, particularly concerning nutritional iron imbalance and bacterial signaling in the MGB.

关键词： bioelectricity membrane potential microbiota‐gut‐brain axis nutritional deficiency

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Anthropogenic emission is the main contributor to the rise of atmospheric methane during 1993-2017

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National Science Review 2022年第5期9卷 154-166页

作者：张臻 Benjamin Poulter Sara Knox Ann Stavert Gavin McNicol Etienne Fluet-Chouinard Aryeh Feinberg 赵园红 Philippe Bousquet Josep G.Canadell Anita Ganesan Gustaf Hugelius George Hurtt Robert B.Jackson Prabir K.Patra Marielle Saunois Lena H?glund-Isaksson 黄春林 Abhishek Chatterjee 李新 Department of Geographical Sciences University of Maryland Biospheric Sciences Laboratory NASA Goddard Space Flight Center Department of Geography University of British Columbia Global Carbon Project CSIRO Oceans and Atmosphere Department of Earth and Environmental Sciences University of Illinois Chicago Department of Earth System Science Stanford University Institute for Data Systems and Society Massachusetts Institute of Technology College of Oceanic and Atmospheric Sciences Ocean University of China Laboratoire des Sciences du Climat et de l’Environment LSCE-IPSL (CEA-CNRS-UVSQ)Université Paris-Saclay School of Geographical Sciences University of Bristol Department of Physical Geography and Bolin Centre for Climate Research Stockholm University Woods Institute for the Environment and Precourt Institute for Energy Stanford University Research Institute for Global Change JAMSTEC International Institute for Applied Systems Analysis (IIASA) Northwest Institute of Eco-Environment and Resources Chinese Academy of Sciences Global Modeling and Assimilation Office NASA Goddard Space Flight Center Universities Space Research Association Institute of Tibetan Plateau Research Chinese Academy of Sciences

Atmospheric methane（CH4） concentrations have shown a puzzling resumption in growth since 2007 following a period of stabilization from 2000 to *** hypotheses have been proposed to explain the temporal variations in CH4growth,and attribute the rise of atmospheric CH4either to increases in emissions from fossil fuel activities,agriculture and natural wetlands,or to a decrease in the atmospheric chemical ***,we use a comprehensive ensemble of CH4source estimates and isotopic δ13C-CH4source signature data to show that the resumption of CH4growth is most likely due to increased anthropogenic *** emission scenarios that have the fewest biases with respect to isotopic composition suggest that the agriculture,landfill and waste sectors were responsible for 53±13% of the renewed growth over the period 2007-2017 compared to 2000-2006;industrial fossil fuel sources explained an additional 34 ±24%,and wetland sources contributed the least at 13 ±9%.The hypothesis that a large increase in emissions from natural wetlands drove the decrease in atmospheric δ13C-CH4values cannot be reconciled with current process-based wetland *** finding suggests the need for increased wetland measurements to better understand the contemporary and future role of wetlands in the rise of atmospheric methane and climate *** findings highlight the predominant role of anthropogenic activities in driving the growth of atmospheric CH4concentrations.

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QUANTITATIVE ULTRASOUND METHODS FOR THE ASSESSMENT OF LIVER STEATOSIS USING CONTROLLED ATTENUATION PARAMETER AS REFERENCE METHOD

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Ultrasound in Medicine & Biology 2022年 48卷 S23-S23页

作者： Popescu, Alina Foncea, Camelia Lupusoru, Raluca Cotrau, Radu Bende, Felix Sirli, Roxana Sporea, Ioan Department of Internal Medicine II Division of Gastroenterology and Hepatology Center for Advanced Research in Gastroenterology and Hepatology "Victor Babes" University of Medicine and Pharmacy Timisoara Romania Center for Advanced Hepatology Research of the Academy of Medical Sciences Timișoara Romania “Victor Babes” University of Medicine and Pharmacy Center for Modeling Biological Systems and Data Analysis Department of Functional Sciences Timisoara Romania

ObjectivesLiver steatosis can progress to nonalcoholic steatohepatitis and liver cirrhosis, becoming one of the leading indications for liver transplantation. Therefore, early detection and staging of steatosis is very important. In addition to Transient Elastography (TE) with Controlled Attenuation Parameter (CAP), several methods were developed for steatosis assessment. The aim of our study was to evaluate the feasibility of two new quantitative ultrasound (QUS) parameters, TSI (tissue scatter-distribution imaging) and TAI (tissue attenuation imaging) for steatosis diagnosis considering CAP as reference. MaterialsA prospective study was conducted in which liver steatosis was assessed in 67 patients (65.7% men, mean age 55.6 ± 13.2 years), evaluated in the same session by QUS and CAP implemented on the following systems: Samsung Medison RS85 (CA1-7A probe) and FibroScan Compact M 530 (M and XL probes), respectively. For CAP, reliable measurements were defined as the median value of 10 measurements with IQR/M<0.3. For QUS, five consecutive measurements of TAI and TSI were acquired by a color-coded map overlaid on B-mode ultrasound. Attenuation coefficient and scatter-distribution coefficient were automatically calculated and reliable measurements were defined as an reliability index, R2 over 0.6. The cut-off value by CAP for identifying the presence of at least mild steatosis was 248 dB/m [1]. ResultsReliable measurements by CAP and TAI/TSI were obtained in 100% of cases. Moderate correlations between steatosis assessment methods were observed: TAI vs. CAP r=0.67, TSI vs. CAP r=0.53, TSI vs. TAI, r=0.63. The best cut-off value for TAI to identify at least mild steatosis was > 0.66 (AUROC=0.87, p<0.0001, Se=81.2%, Sp=84.2%, PPV=92.9%, NPV=64%). The best cut-off value for TSI for identifying at least mild steatosis was > 96.2 (AUROC=0.81, p<0.0001, Se=81.2%, Sp=84.2%, PPV=88.6%, NPV=64%). ConclusionsTAI and TSI are feasible methods for assessing liver steatosis, whic

关键词： liver steatosis elastography quantitative ultrasound

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FATTY LIVER QUANTIFICATION USING ULTRASOUND DERIVED FAT FRACTION (UDFF) AS COMPARED TO CONTROLLED ATTENUATION PARAMETER (CAP) IN A MIXED COHORT OF PATIENTS

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Ultrasound in Medicine & Biology 2022年 48卷 S16-S16页

作者： Sporea, Ioan Lupusoru, Raluca Sirli, Roxana Bende, Felix Cotrau, Radu Foncea, Camelia Popescu, Alina Department of Internal Medicine II Division of Gastroenterology and Hepatology Center for Advanced Research in Gastroenterology and Hepatology "Victor Babes" University of Medicine and Pharmacy Timisoara Romania Center for Advanced Hepatology Research of the Academy of Medical Sciences Timișoara Romania Center for Modeling Biological Systems and Data Analysis Department of Functional Sciences “Victor Babes” University of Medicine and Pharmacy Timisoara Romania

ObjectivesThe aim of this study was to assess the performance and optimal cut-off points of UDFF for the non-invasive assessment of liver steatosis, using transient elastography (TE) with CAP as a reference method. MaterialsWe included 271 consecutive patients, with or without chronic liver disease (43.7% female, mean age 53.3 ± 13.05 years). Liver steatosis was evaluated in the same session by two techniques: UDFF - using a Siemens ACUSON Sequoia system (Deep Abdominal Transducer-DAX) and by CAP – using a FibroScan Compact M 530 device (M and XL probes). The following CAP cut-off values were used to differentiate among different grades of steatosis: 248dB/m for mild steatosis (S1), 268 dB/m for moderate steatosis (S2) and 280 dB/m for severe steatosis (S3). ResultsAccording to BMI, from the 271 patients 41% were obese, 34% were overweight and 25% normal weight. The correlation between UDFF and CAP was good, r=0.75, p<0.0001. We calculated the following UDFF optimal cut-off values to differentiate among steatosis grades: for S1->5% [(with 88.4% Se, 77.5% Sp,73.8% NPV, 90.3% PPV and an AUC of 0.92 (0.89-0.95), p< 0.0001];for S2 >10% [(with 69.3% Se, 99% Sp, 99.1% NPV, 67.9% PPV and an AUC of 0.95 (0.92-0.97), p< 0.0001]; and for S3 >15% [(with46.9% Se, 100% Sp, 100% NPV, 60.5% PPV and an AUC of 0.93 (0.89-0.96), p<0.0001]. ConclusionsUDFF is a good method for classifying steatosis severity with the following cut-offs:> 5% for mild steatosis,> 10% for moderate steatosis and > 15% for severe steatosis,the specificity increasing with steatosis severity.

关键词： UDFF- ultrasound derived fat fraction Liver steatosis assessment

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POINT SHEARWAVE ELASTOGRAPHY TECHNIQUES FOR THE ASSESSMENT OF LIVER STIFFNESS

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Ultrasound in Medicine & Biology 2022年 48卷 S30-S31页

ObjectivesNon-invasive ultrasound-based techniques for liver stiffness assessment (LS) were developed as an alternative to liver biopsy. Transient Elastography (TE) is the first method validated by several guidelines and other new methods were developed recently. The aim of this study was to evaluate the performance of two point Shear Waves Elastography (pSWE) techniques implemented in the same ultrasound system for liver stiffness assessment, using TE as reference. MaterialsA prospective study was conducted, in which 271 consecutive patients with or without previously diagnosed liver disease were included. LS was evaluated by point Shear Wave Elastography (pSWE and Auto pSWE) implemented on Siemens ACUSON Sequoia system (Deep Abdominal Transducer-DAX) and by TE using FibroScan Compact M 530 system (M and XL probes).For Auto pSWE, 15 measurements/values are automatically obtained in a single evaluation and the median and IQR are calculated. For p-SWE and TE, reliable measurements were defined as the median value of 10 measurements with IQR/M<0.3 for all probes. For significant fibrosis, a cut-off value by TE of 7 kPa was used, and for liver cirrhosis 12 kPa [1]. ResultsValid LSM were obtained in all 271 (100%) patients using both elastographic methods. A very good positive correlation was found between the LS values obtained by TE and both Auto pSWE and pSWE: r=0.78, p< 0.0001; and between Auto pSWE and p-SWE: r=0.92, p<0.0001. The best pSWE and Auto pSWE cut-off value for significant fibrosis (F≥2) was 5.1 kPa (p-SWE: AUC- 0.81; Se-58.3%; Sp-94.6%; PPV-83.1%; NPV-83.5%; Auto pSWE: AUC- 0.82; Se-63.1%; Sp-90.4%; PPV-76.8%; NPV-84.4%) and for liver cirrhosis (F4) was 6.7 kPa (p-SWE: AUC- 0.92; Se-73.8%; Sp-94.3%; PPV-83.8%; NPV-95.3%; Auto pSWE: AUC- 0.93; Se-78.5%; Sp-97.8%; PPV-86.8%; NPV-96.1%). ConclusionsThe two techniques, pSWE and Auto pSWE have very good correlations with TE and similar performance for predicting significant fibrosis and liver cirrhosis in a

关键词： liver fibrosis elastography point shearwave

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