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A virtual positioning system for external beam radiotherapy

Virtual Reality 2023年第3期27卷 2569-2582页

作者： Sung, Wen-Hsu Jiang, Ching-Fen Su, Tai-Sin Sun, Shuh-Ping Department of Physical Therapy and Assistive Technology National Yang Ming Chiao Tung University Taipei Taiwan Graduate Program of Smart Healthcare and Bioinformatics I-Shou University Kaohsiung Taiwan Department of Biomedical Engineering I-Shou University Kaohsiung Taiwan Department of Digital Media Design I-Shou University Kaohsiung Taiwan

In radiation therapy, positioning patients to ensure the accuracy of the setup of a procedure is a routine and labour-intensive process that substantially determines the efficacy of treatment. In this study, we propose a virtual positioning system that can simulate the positioning process with a visible beam path under the broad view of a life-like patient-positioning platform to obviate problems with excessively narrow view. This system integrates image processing, computer graphics, and virtual reality to encompass a 3D treatment target reconstructed from medical images of different modalities in a virtual scene. An innovative evaluation method is further proposed to verify the efficacy of the system using a full-scale 3D solid anthropometric model, and a treatment target showed an accuracy of 99% in calibration and a mean compatibility of 95% with an actual measurement. The proposed virtual positioning system provides a training and education platform for radiation therapy. The methodology through which the system was developed is also disclosed as a promising approach to improve the efficiency and safety of the position verification process for existing systems. © 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.

关键词： Radiotherapy

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Digital Twin (DT) Smart City for Air Quality Management 8

Digital Twin (DT) Smart City for Air Quality Management

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8th International Conference on Computer Science and Computational Intelligence, ICCSCI 2023

作者： Ariansyah, Dedy Isnan, Mahmud Rahutomo, Reza Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

Air pollution is a pressing issue in cities, and managing air quality poses a challenge for urban designers and decision-makers. This study proposes a Digital Twin (DT) Smart City integrated with Mixed Reality technology to enhance visualization and collaboration for addressing urban air pollution. The research adopts an applied research approach, with a focus on developing a DT framework. A use case of DT development for Jakarta, the capital of Indonesia, is presented. By integrating air quality data, meteorological information, traffic patterns, and urban infrastructure data, the DT provides a comprehensive understanding of air pollution dynamics. The visualization capabilities of the DT, utilizing Mixed Reality technology, facilitate effective decision-making and the identification of strategies for managing air quality. However, further research is needed to address data management challenges to build a DT for Smart City at scale. © 2023 The Authors. Published by Elsevier B.V.

关键词： Augmented Reality Digital Twin Mixed Reality Smart City

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Distinct gut microbiomes in Thai patients with colorectal polyps

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World Journal of Gastroenterology 2024年第27期30卷 3336-3355页

作者： Thoranin Intarajak Ahmad Nuruddin Khoiri Kanthida Kusonmano Weerayuth Kittichotirat Sawannee Sutheeworapong Supapon Cheevadhanarak Wandee Udomchaiprasertkul Chinae Thammarongtham Bioinformatics Unit Chulabhorn Royal AcademyLak Si 10210BangkokThailand Bioinformatics and Systems Biology Program School of Bioresources and Technologyand School of Information TechnologyKing Mongkut’s University of Technology ThonburiBang Khun Thian 10150BangkokThailand Bioinformatics and Systems Biology ProgramSchool of Bioresources and Technologyand School of Information TechnologyKing Mongkut’s University of Technology ThonburiBang Khun Thian 10150BangkokThailand Systems Biology and Bioinformatics Unit Pilot Plant Development and Training InstituteKing Mongkut’s University of Technology ThonburiBang Khun Thian 10150BangkokThailand Molecular Genomic Research Laboratory Chulabhorn Royal AcademyLak Si 10210BangkokThailand National Center for Genetic Engineering and Biotechnology King Mongkut's University of Technology ThonburiBang Khun Thian 10150BangkokThailand School of Bioresources and Technology King Mongkut’s University of Technology ThonburiBank Khun Thian 10150BangkokThailand Fungal Biotechnology Unit Pilot Plant Development and Training InstituteKing Mongkut’s University of Technology ThonburiBang Khun Thian 10150BangkokThailand

BACKGROUND Colorectal polyps that develop via the conventional adenoma-carcinoma sequence[e.g.,tubular adenoma(TA)]often progress to malignancy and are closely associated with changes in the composition of the gut *** is limited research concerning the microbial functions and gut microbiomes associated with colorectal polyps that arise through the serrated polyp pathway,such as hyperplastic polyps(HP).Exploration of microbiome alterations asso-ciated with HP and TA would improve the understanding of mechanisms by which specific microbes and their metabolic pathways contribute to colorectal *** To investigate gut microbiome signatures,microbial associations,and microbial functions in HP and TA *** Full-length 16S rRNA sequencing was used to characterize the gut microbiome in stool samples from control participants without polyps[control group(CT),n=40],patients with HP(n=52),and patients with TA(n=60).Significant differences in gut microbiome composition and functional mechanisms were identified between the CT group and patients with HP or *** techniques in this study included differential abundance analysis,co-occurrence network analysis,and differential pathway *** Colorectal cancer(CRC)-associated bacteria,including Streptococcus gallolyticus(***),Bacteroides fragilis,and Clostridium symbiosum,were identified as characteristic microbial species in TA *** gnavus,associated with dysbiosis and gastrointestinal diseases,was significantly differentially abundant in the HP and TA *** pathway analysis revealed that HP patients exhibited enrichment in the sulfur oxidation pathway exclusively,whereas TA patients showed dominance in pathways related to secondary metabolite biosynthesis(e.g.,mevalonate);*** was a major ***-occurrence network and dynamic network analyses revealed co-occurrence of dysbiosis-associated bacteria in HP patients,wh

关键词： Gut microbiome Colorectal adenoma Hyperplastic polyp Full-length 16s rRNA Microbial correlation networks Predicted functional mechanisms

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Throughput and accuracy of microbial community analysis using full-length 16S rDNA amplicon sequences generated from SMRT sequencers

Throughput and accuracy of microbial community analysis usin...

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第七届全国微生物资源学术暨国际微生物系统与分类学研讨会

作者： YoungJae Hur Kihyun Lee Jongsik Chun Interdisciplinary Program in Bioinformatics Seoul National University School of Biological SciencesSeoul National University

Universally conserved 16S rRNA gene sequences generated using high-throughput sequencing technique has become powerful tool to analysis the robust diversity and characterizing microbial ***,even full-length 16S rRNA sequence can be obtained from PacBio(R)SMRT sequencer with high yield and *** partial region sequences have been used as sequence tags in microbial community analysis with sequencing bias and absence of taxonomic classification below genus level,the analysis using full-length 16S rRNA is expected to improve the result *** this study,soil metagenome,fecal metagenome and a synthetic mock community DNA were profiled for bacterial 16S with SMRT sequencing using P6/*** 16S rDNA PCR and its representing SMRT sequencing were performed five times *** SMRT cell of full-length 16S rDNA reads analyzed using three different CCS filtering condition,CCS with minimum 6 full passes,minimum 90%,and 99%predicted *** sorting and 12~18kbp length filtering was followed by primer trimming *** checked as error correction and UCHIME from USEARCH program used for detect ***-chimeric CCS reads analyzed for community profiling through in house *** reads accuracy evaluated by number of mismatches and insertion/deletion *** community profile evaluated in classification rate at taxonomic levels and its accuracy,taxon *** soil and fecal data,we were able to sort out non-chimeric sequences based on the reproduction of highly similar sequences from multiple PCR ***,we demonstrate the usefulness of full-length 16S rRNA gene amplicon sequencing in microbial ecology,and suggest the optimal method for generation and analysis of barcoded full-length 16S rDNA sequence data.

关键词： PacBio 16S rDNA Microbial Communities Metagenomes

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Machine Learning Approaches in Detecting Autism Spectrum Disorder 8

Machine Learning Approaches in Detecting Autism Spectrum Dis...

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8th International Conference on Computer Science and Computational Intelligence, ICCSCI 2023

作者： Daniel Dominic, Nicholas Cenggoro, Tjeng Wawan Pardamean, Bens Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia

Early detection of Autism Spectrum Disorder (ASD) needs to be increased to prevent further adverse impacts. Thus, the classification between ASD and Typically Development (TD) individuals is an intriguing task. This review study has collected 26 related papers to answer four research questions, i.e., what are the most used data inputs, brain atlases, and machine learning models for ASD classification, as also to discover the significant parts of the brain correlated with the ASD. It was eventually found that functional connectivity matrix, Support Vector Machine, and CC200 are the most frequently used data input, model, and brain atlas, respectively. Researchers also concluded that the posterior temporal fusiform cortex, intracalcarine cortex, cuneal cortex, subcallosal cortex, occipital pole, and lateral occipital cortex are the brain regions highly correlated with ASD. © 2023 The Authors. Published by Elsevier B.V.

关键词： autism spectrum disorder brain atlas brain region machine learning

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Modeling the breakage-fusion-bridge mechanism: Combinatorics and cancer genomics

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16th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2012

作者： Kinsella, Marcus Bafna, Vineet Bioinformatics and Systems Biology Program University of California San Diego San Diego CA 92093 United States Department of Computer Science and Engineering University of California San Diego San Diego CA 92093 United States

ISBN: (纸本)9783642296260

The breakage-fusion-bridge (BFB) mechanism was proposed over seven decades ago and is a source of genomic variability and gene amplification in cancer. Here we formally model and analyze the BFB mechanism, to our knowledge this first time this has been undertaken. We show that BFB can be modeled as successive inverted prefix duplications of a string. Using this model, we show that BFB can achieve a surprisingly broad range of amplification patterns. We find that a sequence of BFB operations can be found that nearly fits most patterns of copy number increases along a chromosome. We conclude that this limits the usefulness of methods like array CGH for detecting BFB and discuss other implications for understanding mechanisms of genomic instability. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Pattern matching

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Data mining for epidemiology: The correlation of typhoid fever occurrence and environmental factors 7

Data mining for epidemiology: The correlation of typhoid fev...

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7th International Conference on Computer Science and Computational Intelligence, CSCI 2022

作者： Asadi, Faisal Trinugroho, Joko Pebrianto Hidayat, Alam Ahmad Rahutomo, Reza Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Information System Department School of Information System Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia

Typhoid fever is an endemic disease that burdens Indonesia and has a potentially fatal infection multisystem. Salmonella typhi bacterium is responsible for typhoid fever disease. Poor sanitation, crowding, and slums are the main factors of increasing typhoid fever incidences. Environmental factors directly connected to meteorological factors are the main factor in breeding the Salmonella typhi bacterium. This study aims to identify the correlation between meteorological parameters and typhoid fever disease occurrence. The study was carried out in Jakarta, Indonesia, and the Bureau of Meteorological, Climatology, and Geophysics (BMKG) provided the meteorological parameter data. In addition, the Jakarta health surveillance office provided information on typhoid fever hospitalizations from 2019 to 2021. Pearson's concept was utilized d to investigate the correlation between typhoid fever incidences and the meteorological parameters. Humidity, precipitation, and wind speed are the meteorological parameters that significantly affect in contribute to the occurrence of typhoid fever disease. These findings might be used as a reference for Indonesia's government in making public policy to prevent typhoid fever in Indonesia. © 2022 Elsevier B.V.. All rights reserved.

关键词： Data mining

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Enhanced expression of β3-galactosyltransferase 5 activity is sufficient to induce in vivo synthesis of extended type 1 chains on lactosylceramides of selected human colonic carcinoma cell lines

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Glycobiology 2009年第4期19卷 418-427页

作者： Lin, Chi-Hung Fan, Yao-Yun Chen, Yen-Ying Wang, Shih-Hsin Chen, Chun-I Yu, Lung-Chih Khoo, Kay-Hooi Chemical Biology and Molecular Biophysics Program Taiwan International Graduate Program Academia Sinica Taipei 115 Taiwan Institute of Bioinformatics and Structural Biology National Tsing-Hua University Hsinchu 300 Taiwan Institute of Biological Chemistry Academia Sinica Nankang Taipei 115 Taiwan Taiwan and Institute of Biochemical Science National Taiwan University Taipei 106 Taiwan

In general, an elevated expression of β3-galactosyltrans-ferase (β3GalT) activity contributed by β3GalT5 correlates well with increased biosynthesis and expression of type 1 chain (Galβ1-3GlcNAcβ1-) derivatives such as Lewis A and sialyl Lewis A, which are mostly recognized as terminal epitopes and not further extended. Most known β3-N-acetylglucosaminyltransferases show a higher activity toward extending type 2 chain (Galβ1-4GlcNAcβ1-), and an over-expression of β3GalT5 could suppress the formation of the type 2 chain poly-N- acetyllactosaminoglycans. The potential of extending instead the predominant type 1 chain termini synthesized under such circumstances was, however, not investigated, partly due to technical difficulty in unambiguous identification of extended type 1 chains. Using an advanced mass spectrometry-based glycomic mapping and glycan sequencing approach, we show here that type 1 chains carried on the lacto-series glycosphingolipids of colonic carcinoma cells can be extended when the endogenous β3GalT activity relative to competing β4GalT activity, as defined against a common GlcNAcβ1-3Galβ1-4Glc acceptor, is sufficiently high, as found in Colo205 and SW1116, but not in DLD-1 cells. In support of this positive correlation, the lacto-series glycosphingolipids isolated from stably transfected DLD-1 clones over-expressing β3GalT5 were shown to comprise fucosylated dimeric type 1 chains, whereas a mock transfectant and the DLD-1 parent carried only fucosylated dimeric type 2 chains on their lactosylceramides. It suggests that while the natural expression of extended type 1 chain is likely to be determined by many contributing factors including the relative amounts of competing glycosyltransferases and the UDP-Gal level, the enhanced expression of β3GalT5 is sufficient to promote in vivo extension of type 1 chains by furnishing a significantly higher amount of type 1 chain precursors relative to competing type 2 chains. © The Author 2009. Published by Oxfo

关键词： β3-galactosyltransferase β3GalT5 Extended type 1 chain Glycomics Mass spectrometry

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Predicting outcomes of steady-state ¹³C isotope tracing experiments using Monte Carlo sampling

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BMC Systems Biology 2012年第1期6卷 1-14页

作者： Schellenberger, Jan Zielinski, Daniel C. Choi, Wing Madireddi, Sunthosh Portnoy, Vasiliy Scott, David A. Reed, Jennifer L. Osterman, Andrei L. Palsson, Bernhard T. Bioinformatics and Systems Biology Program University of California La Jolla CA 92093-0419 9500 Gilman Drive - San Diego United States Department of Bioengineering University of California La Jolla CA 92093-0412 9500 Gilman Drive - San Diego United States Bioinformatics and Systems Biology Program Sanford-Burnham Institute La Jolla CA 92037 10901 North Torrey Pines Road United States Department of Chemical and Biological Engineering University of Wisconsin Madison WI 53706-1607 1415 Engineering Drive Madison United States

Background: Carbon-13 ( 13C) analysis is a commonly used method for estimating reaction rates in biochemical networks. The choice of carbon labeling pattern is an important consideration when designing these experimen...

Background: Carbon-13 ( ¹³C) analysis is a commonly used method for estimating reaction rates in biochemical networks. The choice of carbon labeling pattern is an important consideration when designing these experiments. We present a novel Monte Carlo algorithm for finding the optimal substrate input label for a particular experimental objective (flux or flux ratio). Unlike previous work, this method does not require assumption of the flux distribution ***: Using a large E. coli isotopomer model, different commercially available substrate labeling patterns were tested computationally for their ability to determine reaction fluxes. The choice of optimal labeled substrate was found to be dependent upon the desired experimental objective. Many commercially available labels are predicted to be outperformed by complex labeling patterns. Based on Monte Carlo Sampling, the dimensionality of experimental data was found to be considerably less than anticipated, suggesting that effectiveness of ¹³C experiments for determining reaction fluxes across a large-scale metabolic network is less than previously ***: While ¹³C analysis is a useful tool in systems biology, high redundancy in measurements limits the information that can be obtained from each experiment. It is however possible to compute potential limitations before an experiment is run and predict whether, and to what degree, the rate of each reaction can be resolved. © 2012 Schellenberger et al.;licensee BioMed Central Ltd.

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Pixelsteganalysis: Destroying hidden information with a low degree of visual degradation

arXiv

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arXiv 2019年

作者： Jung, Dahuin Bae, Ho Choi, Hyun-Soo Yoon, Sungroh Electrical and Computer Engineering Seoul National University Interdisciplinary Program in Bioinformatics Seoul National University

Steganography is the science of unnoticeably concealing a secret message within a certain image, called a cover image. The cover image with the secret message is called a stego image. Steganography is commonly used for illegal purposes such as terrorist activities and pornography. To thwart covert communications and transactions, attacking algorithms against steganography, called steganalysis, exist. Currently, there are many studies implementing deep learning to the steganography algorithm. However, conventional steganalysis is no longer effective for deep learning based steganography algorithms. Our framework is the first one to disturb covert communications and transactions via the recent deep learning-based steganography algorithms. We first extract a sophisticated pixel distribution of the potential stego image from the auto-regressive model induced by deep learning. Using the extracted pixel distributions, we detect whether an image is the stego or not at the pixel level. Each pixel value is adjusted as required and the adjustment induces an effective removal of the secret image. Because the decoding method of deep learning-based steganography algorithms is approximate (lossy), which is different from the conventional steganography, we propose a new quantitative metric that is more suitable for measuring the accurate effect. We evaluate our method using three public benchmarks in comparison with a conventional steganalysis method and show up to a 20% improvement in terms of decoding rate. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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