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Prenatal exposure to parabens in relation to childhood obesity and the gut microbiome

Taiwan Journal of Public Health 2023年第1期42卷 62-74页

作者： Chen, Ying Kuo, Chin-Chi Chen, Ting-Wen Wang, Shu-Li Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Big Data Center China Medical University Hospital Taichung Taiwan Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu Taiwan National Institute of Environmental Health Sciences National Health Research Institutes No. 35 Keyan Rd Zhunan Town Miaoli Taiwan Department of Public Health National Defence Medical Centre Taipei Taiwan

Objectives: Parabens, which are common antimicrobial preservatives, are considered to be endocrine-disrupting chemicals. Previous studies regarding maternal exposure to paraben have shown that disturbances in physiological endocrine and metabolic signals during early childhood may lead to the long-term adverse health effects in children. We investigated the effects of maternal exposure to paraben on childhood obesity and gut microbiome diversity. Methods: We collected the data on 284 maternalinfant pairs from the central region of Taiwan Maternal- Infant Cohort Study. Liquid chromatography-tandem mass spectrometry was used to detect 4 common parabens, including methyl-paraben, ethyl-paraben, propyl-paraben, and butyl-paraben in maternal urinary samples. In addition, shotgun metagenomics sequencing was used to analyze 98 children’s fecal samples. Results: Greater maternal exposure to paraben was observed in boys who were significantly shorter and with wider chest circumferences and in girls with higher body mass index. Increased maternal exposure to paraben significantly reduced the abundance of several species, such as Barnesiella, Bacteroides uniformis, and Eubacterium rectale, but increased the abundance of several opportunistic pathogens, which interfered with the regulation of energy consumption. Conclusions: Maternal exposure to paraben promoted the development of obesity in girls and disrupted the diversity of gut microbial community. Maternal exposure to paraben may promote obesity in children at preschooler age. In addition, additional studies on the effects of the composition of the gut microbiome after puberty are required. © 2023, Taiwan Public Health Association. All rights reserved.

关键词： childhood obesity gut microbiome parabens prenatal exposure

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Saccharomyces cerevisiae I-3856 in irritable bowel syndrome with predominant constipation

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World Journal of Gastroenterology 2022年第22期28卷 2509-2522页

作者： Florian Mourey Amélie Decherf Jean-François Jeanne Mathieu Clément-Ziza Marie-Lise Grisoni François Machuron Sophie Legrain-Raspaud Arnaud Bourreille Pierre Desreumaux Research and Applications Department Gnosis by LesaffreLesaffre GroupMarcq-en-Baroeul 59700France Data Science and Bioinformatics Laboratory Research and Development DepartmentLesaffre InternationalLesaffre GroupMarcq-en-Baroeul 59700France Institut des Maladies de l'Appareil Digestif Centre Hospitalier Universitaire de NantesNantes 44093France Institute for Translational Research in Inflammation Centre Hospitalier Universitaire de LilleLille 59000France

BACKGROUND Probiotics are a promising solution for managing irritable bowel syndrome(IBS).Saccharomyces cerevisiae(***)I-3856 has already demonstrated beneficial effects in IBS subjects,particularly in IBS with predominant constipation(IBS-C).AIM To confirm the efficacy of *** I-3856 in the management of gastrointestinal symptoms in *** A randomized,double-blind,placebo-controlled clinical study was performed in a total of 456 *** a run-in period,subjects were randomly assigned to the group receiving *** I-3856(8×109 CFU daily)or the placebo for 8 wk,and they performed daily self-evaluations of gastrointestinal *** primary objective was to assess the effect of the probiotic on abdominal *** secondary objectives were the evaluation of other gastrointestinal symptoms,bowel movement frequency and consistency,and quality of life(QOL).RESULTS A significantly higher proportion of abdominal pain responders was reported in the Probiotic group(45.1%vs 33.9%,P=0.017).A nonsignificant difference in the area under the curve for abdominal pain over the second month of supplementation was observed in subjects receiving probiotic vs placebo[P=0.073,95%CI:-0.59(-1.23;0.05)].No statistically significant differences were reported in the evolution of bowel movement frequency and stool consistency between the *** 8 wk of supplementation,the overall QOL score was significantly higher in the Probiotic group than in the Placebo group[P=0.047,95%CI:3.86(0.52;7.20)].Furthermore,exploratory analyses showed statistically significant and clinically relevant improvements in QOL scores in abdominal pain responders vs *** The results of this clinical study confirmed the abdominal pain alleviation properties of *** I-3856 in *** pain relief was associated with improved *** identifier:NCT03150212.

关键词： Probiotic Yeast Saccharomyces cerevisiae Irritable bowel syndrome Abdominal pain Quality of life

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Drone Application Model for Image Acquisition of Plantation Areas and Oil Palm Trees Counting 7

Drone Application Model for Image Acquisition of Plantation ...

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7th International Conference on Information Management and Technology, ICIMTech 2022

作者： Sastrohartono, Hermantoro Suryotomo, Andiko Putro Saifullah, Shoffan Suparyanto, Teddy Perbangsa, Anzaludin Samsinga Pardamean, Bens Instiper Yogyakarta Faculty of Agricultural Technology Department of Agricultural Engineering Yogyakarta55281 Indonesia Universitas Pembangunan Nasional Veteran Yogyakarta Department of Informatics Yogyakarta55283 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia BINUS Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

The area of oil palm plantations in Indonesia increased by 7% from 14 million ha in 2017 to 15 million ha in 2021. The vast land requires the support of effective and efficient management techniques to maintain sustainable productivity. The high-performance computing technologies, Internet of Things (IoT), Big data, Artificial Intelligence, spatial modeling, and drones are the answers to these needs. This study aims to design an application that can obtain plantation image data and analyze the calculation of the number of oil palm trees. The image of oil palm plantations is obtained from processing photo data from drones through a mosaic and composite process. This study also employed Scrum and UML as a system model development method. The image of the oil palm plantation area is used to build a tree counting model using the Viola-Jones algorithm. The oil palm tree count information generated by this system can then be used by management for fertilizing, harvesting, and monitoring the condition of oil palm trees. © 2022 IEEE.

关键词： Drones

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MotifBench: A standardized protein design benchmark for motif-scaffolding problems

arXiv

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arXiv 2025年

作者： Zheng, Zhuoqi Zhang, Bo Didi, Kieran Yang, Kevin K. Yim, Jason Watson, Joseph L. Chen, Hai-Feng Trippe, Brian L. Department of Bioinformatics and Biostatistics Shanghai Jiao Tong University China School of Life Sciences Tsinghua University China Department of Computer Science Oxford University United Kingdom NVIDIA United States Microsoft Research Department of Computer Science Massachusetts Institute of Technology United States Department of Biochemistry University of Washington United States Department of Statistics Stanford University United States Stanford Data Science Stanford University United States

The motif-scaffolding problem is a central task in computational protein design: Given the coordinates of atoms in a geometry chosen to confer a desired biochemical function (a motif), the task is to identify diverse protein structures (scaffolds) that include the motif and maintain its geometry. Significant recent progress on motif-scaffolding has been made due to computational evaluation with reliable protein structure prediction and fixed-backbone sequence design methods [1–17]. However, significant variability in evaluation strategies across publications has hindered comparability of results, challenged reproducibility, and impeded robust progress. In response we introduce MotifBench, comprising (1) a precisely specified pipeline and evaluation metrics, (2) a collection of 30 benchmark problems, and (3) an implementation of this benchmark and leaderboard at ***/blt2114/MotifBench. The MotifBench test cases are more difficult compared to earlier benchmarks (e.g. [4]), and include protein design problems for which solutions are known but on which, to the best of our knowledge, state-of-the-art methods fail to identify any solution. © 2025, CC BY.

关键词： Computational geometry

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Implementation of Face Patterns and Smile Recognition for Intelligent Class Attendance Systems

Implementation of Face Patterns and Smile Recognition for In...

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International Conference of Computer and Informatics Engineering (IC2IE)

作者： Miftakhurrokhmat Teddy Suparyanto Gregorius Natanael Elwirehardja Shofiyati Nur Karimah Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Department of Informatics Faculty of Computer Science Universitas Amikom Yogyakarta Yogyakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

Students “attendance in class is one important success parameter in face-to-face learning processes. Conventional attendance systems, such as paper-based attendance sheets or identity card systems, require a long time in the manual recapitulation process. Without additional verifications, even computer vision-based methods are prone to fraudulent practices by the students instead of gaining their excitement and attention in a class. To stimulate students” attention in a class, this work designs an intelligent class attendance system, in which facial pattern and smile recognition are implemented by using the latter as an additional task-based verification to reduce the risks of fake attendance. For the face recognition module, this pilot study used FaceNet as a feature extractor combined with SVM for classification, whereas the Haar cascade algorithm is used for recognizing smiles. This face recognition pipeline was implemented as a service installed on minicomputers or Internet of Things (IoT) devices in each classroom and connected to an IP camera. Every recorded attendance will be sent as a notification to a mobile application for students that requires their active participation to confirm it with a smiling self-photo. The proposed pipeline obtained 92.86% accuracy on the test data, and 66.67% accuracy when evaluated in a real-life simulation setting through the implemented system. The lower accuracy in the simulation indicated that further improvements are indispensable, especially since the model obtained 28.57% False Negative Rate. Future studies will need to acquire more data and experiment with more efficient methods of attendance verification.

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The Impact of Different Modes of Augmented Reality Information in Assisted Aircraft Cable Assembly 1

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International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Ariansyah, Dedy Xi, Khaizuo Erkoyuncu, John Ahmet Pardamean, Bens Bioinformatics and Data Science Research Centre Bina Nusantara University Jakarta11480 Indonesia School of Aerospace Transport and Manufacturing Cranfield University BedfordMK43 0AL United Kingdom Centre of Digital Engineering and Manufacturing School of Aerospace Transport and Manufacturing Cranfield University BedfordMK43 0AL United Kingdom Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Aircraft avionics systems are complicated systems which involves high number of components and complex cable assembly procedure. To deal with this challenge, Augmented Reality (AR) has been proposed to be an effective method to improve assembly efficiency and to reduce error rates. In this paper, the authors developed AR-based guidance cable assembly and compare the impact of different modes of AR information. The results show that although AR outperformed the paper document assembly guidance, the design of AR information has distinct influence on the successful completion of the cables assembly process. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Augmented reality

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A Diversity Inventory Monitoring System of Riparian Vegetation 4

A Diversity Inventory Monitoring System of Riparian Vegetati...

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4th International Conference on Cybernetics and Intelligent System, ICORIS 2022

作者： Putra, Dian Pratama Nugraha, Nanda Satya Suparyanto, Teddy Hidayat, Alam Ahmad Sudigyo, Digdo Pardamean, Bens STIPER Agricultural Institute Faculty of Agricultural Technology Yogyakarta55282 Indonesia STIPER Agricultural Institute Yogyakarta Faculty of Agricultural Technology Faculty of Forestry Yogyakarta55282 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665453950

To strengthen conservation efforts for preserving biodiversity in a conservation area, forest inventory is important to understand the natural succession process in the area and to establish a monitoring strategy. Further, tree inventory aims to monitor the output yielded in the area. More specifically, the tree inventory in the watershed area plays a key role to achieve Sustainable Development Goals (SDG), especially in riparian zones which are also vital parts of green zones in forests. However, the traditional inventory approach is time-consuming and laborious therefore the development of an expert system to assist in inventory monitoring is required. In this study, we develop a monitoring system via a mobile application to collect, analyze and visualize tree inventory data. The application includes algorithms required to compute tree biodiversity, distribution, and richness for the given input of the data of all tree species in a conservation area. For the model validation stage, we compare the traditional inventory approach with our proposed application-based approach to compute diversity inventory in two riparian locations: Klaten Conservation Park and Wonosobo Conservation Park. After the three-day data collection in the areas, we obtain that the accuracy of reading data of our proposed system can achieve more than 90% in comparison with the manual approach. This demonstrates that the system can assist forestry workers to perform more efficient tree inventories in different locations. © 2022 IEEE.

关键词： Biodiversity

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BraceNet: Graph-Embedded Neural Network For Brain Network Analysis

BraceNet: Graph-Embedded Neural Network For Brain Network An...

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IEEE International Conference on Big data

作者： Xuan Kan Yunchuan Kong Tianwei Yu Ying Guo Department of Computer Science Emory University GA USA Department of Biostatistics and Bioinformatics Emory University GA USA School of Data Science The Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781665480468

Multimodal brain networks extracted from functional magnetic resonance imaging (fMRI) characterize complex connectivities among brain regions from both structural and functional, showing great potential for mental health analysis. Deep neural network models have led a tremendous success in various downstream tasks. However, common property in brain network data, the small number of samples compared with the huge amount of features, hinders the application of deep learning techniques for brain network analysis. This work presents a graph-embedding method by leveraging the unique characteristics of brain networks to unleash the power of deep neural networks and achieve outstanding prediction performance with proper explainability. Experiment results show clear advancements in our proposed braceNet on both real and synthetic datasets.

关键词： Deep learning Network analyzers Mental health Functional magnetic resonance imaging Big data Brain modeling Mathematical models

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Encoding biological metaverse: Advancements and challenges in neural fields from macroscopic to microscopic

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The Innovation 2024年第3期5卷 30-32页

作者： Yantong Cai Wenbo Hu Yao Pei Hao Zhao Guangchuang Yu Dermatology Hospital Southern Medical UniversityGuangzhou 266003China Department of Bioinformatics School of Basic Medical SciencesSouthern Medical UniversityGuangzhou 510515China Tencent AI Lab Shenzhen 518071China State Key Laboratory of Emerging Infectious Diseases School of Public HealthThe University of Hong KongHong Kong SARChina Laboratory of Data Discovery for Health(D24H) Hong Kong Science ParkHong Kong SARChina Institute for AI Industry Research Tsinghua UniversityBeijing 100000China

Neural fields can efficiently encode three-dimensional(3D)scenes,providing a bridge between two-dimensional(2D)images and virtual *** method becomes a trendsetter in bringing the metaverse into vivo *** has initially captured the attention of macroscopic biology,as demonstrated by computed tomography and magnetic resonance imaging,which provide a 3D field of view for diagnostic biological ***,it has also opened up new research opportunities in microscopic imaging,such as achieving clearer de novo protein structure *** this method to the field of biology is particularly significant,as it is refining the approach to studying biological ***,many biologists have yet to fully appreciate the distinctive meaning of neural fields in transforming 2D images into 3D *** article discusses the application of neural fields in both microscopic and macroscopic biological images and their practical uses in biomedicine,highlighting the broad prospects of neural fields in the future biological *** stand at the threshold of an exciting new era,where the advancements in neural field technology herald the dawn of exploring the mysteries of life in innovative ways.

关键词： neural bringing innovative

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The prognosis of clinical stage IIIa non-small cell lung cancer in Taiwan

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Cancer Medicine 2023年第16期12卷 17087-17097页

作者： Cheng, Ya-Fu Huang, Jing-Yang Lin, Ching-Hsiung Wang, Bing-Yen Division of Thoracic Surgery Department of Surgery Changhua Christian Hospital Changhua Taiwan Institute of Medicine Chung Shan Medical University Taichung Taiwan Center for Health Data Science Chung Shan Medical University Hospital Taichung Taiwan Department of Recreation and Holistic Wellness MingDao University Changhua Taiwan Department of Internal Medicine Division of Chest Medicine Changhua Christian Hospital Changhua Taiwan Institute of Genomics and Bioinformatics National Chung Hsing University Taichung Taiwan Department of Post-Baccalaureate Medicine College of Medicine National Chung Hsing University Taichung Taiwan

Lung cancer is the leading cause of cancer death. The treatment of stage IIIa remained the most controversial of all stages of non-small cell lung cancer (NSCLC). We reported on the heterogenicity and current treatment strategies of stage IIIa NSCLC in Taiwan. This study is a retrospective analysis using data from the Taiwan Society of Cancer Registry between January 2010 and December 2018. 4232 patients with stage IIIa NSCLC were included. Based on cell type, the best 5-year OS (40.40%) occurred among adenocarcinoma victims. The heterogenicity of T1N2 had the best 5-year OS (47.62%), followed by T4N0 (39.82%), and the others. Patients who underwent operations had better 5-year OS (over 50%) than those who did not (less than 30%). Segmentectomy (75.28%) and lobectomy (54.06%) showed better 5-year OS than other surgical methods (less than 50%). In multivariable analysis, young age, female, lower Charlson Comorbidity Index score, adenocarcinoma cell type, well differentiated, T1N2/T4N0 heterogenicity, treatment with operation, and segmentectomy/lobectomy/bilobectomy were significant factors. In conclusions, the heterogenicity of T1N2 had the best outcomes followed by T4N0. Patients received surgical treatment revealed much better outcomes than those did not. As always, multimodal therapies with individualized treatment tend to provide better survival outcomes. © 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

关键词： heterogenicity non-small cell lung cancer outcomes stage IIIa Taiwan

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