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Severe Congenital Neutropenia-Associated Mutations Reveal Stage-Specific Gfi1-Dependent Checkpoints in Myeloid Development

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BLOOD 2017年 130卷 544-544页

作者： Muench, David Kappes, Dietmar J. Salomonis, Nathan Myers, Kasiani C. Grimes, Lee Molecular and Developmental Biology Graduate Program Cincinnati Children's Hospital Medical Center Cincinnati OH Fox Chase Cancer Center Blood Cell Development and Function Program Philadelphia PA Bioinformatics Cincinnati Children's Hospital Medical Center Cincinnati OH Cincinnati Children's Hospital Cincinnati OH Division of Immunobiology Cincinnati Children's Hospital Medical Center Cincinnati OH

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Metformin escape in prostate cancer by activating the PTGR1 transcriptional program through a novel super-enhancer

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Signal Transduction and Targeted Therapy 2023年第9期8卷 4365-4379页

作者： Jianheng Ye Shanghua Cai Yuanfa Feng Jinchuang Li Zhiduan Cai Yulin Deng Ren Liu Xuejin Zhu Jianming Lu Yangjia Zhuo Yingke Liang Jianjiang Xie Yanqiong Zhang Huichan He Zhaodong Han Zhenyu Jia Weide Zhong Department of Urology Guangzhou First People’s HospitalSouth China University of Technology510180 GuangzhouGuangdongChina Urology Key Laboratory of Guangdong Province The First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou Medical University510230 GuangzhouGuangdongChina Guangzhou National Laboratory No.9 XingDaoHuanBei RoadGuangzhou International Bio Island510005 GuangzhouGuangdongChina Institute of Chinese Materia Medica China Academy of Chinese Medical Sciences100700 BeijingChina Department of Botany and Plant Sciences University of CaliforniaRiversideCA 92507USA Graduate Program in Genetics Genomics&BioinformaticsUniversity of CaliforniaRiversideCA 92507USA State Key Laboratory of Quality Research in Chinese Medicine Macao University of Science and TechnologyTaipa999078 MacaoChina

The therapeutic efficacy of metformin in prostate cancer(PCa)appears uncertain based on various clinical *** treatment failure may be attributed to the high frequency of transcriptional dysregulation,which leads to drug ***,the underlying mechanism is still *** this study,we found evidences that metformin resistance in PCa cells may be linked to cell cycle ***-enhancers(SEs),crucial regulatory elements,have been shown to be associated with drug resistance in various *** analysis of SEs in metformin-resistant(MetR)PCa cells revealed a correlation with Prostaglandin Reductase 1(PTGR1)expression,which was identified as significantly increased in a cluster of cells with metformin resistance through single-cell transcriptome *** functional experiments showed that PTGR1 overexpression accelerated cell cycle progression by promoting progression from the G0/G1 to the S and G2/M phases,resulting in reduced sensitivity to ***,we identified key transcription factors that significantly increase PTGR1 expression,such as SRF and RUNX3,providing potential new targets to address metformin resistance in *** conclusion,our study sheds new light on the cellular mechanism underlying metformin resistance and the regulation of the SE-TFs-PTGR1 axis,offering potential avenues to enhance metformin’s therapeutic efficacy in PCa.

关键词： RUNX3 cancer offering

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An Evaluation of Deep Neural Network Performance on Limited Protein Phosphorylation Site Prediction Data

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Procedia Computer Science 2019年 157卷 25-30页

作者： Favorisen Rosyking Lumbanraja Bharuno Mahesworo Tjeng Wawan Cenggoro Arif Budiarto Bens Pardamean Department of Computer Science Faculty of Mathematics and Natural Science University of Lampung Jalan Prof. Dr. Sumantri Brojonegoro No.17 35145 Bandar Lampung Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

One of the common and important post-translational modification (PTM) types is phosphorylation. Protein phosphorylation is used to regulate various enzyme and receptor activations which include signal pathways. There have been many significant studies conducted to predict phosphorylation sites using various machine learning methods. Recently, several researchers claimed deep learning based methods as the best methods for phosphorylation sited prediction. However, the performance of these methods were backed up with the massive training data used in the researches. In this paper, we study the performance of simple deep neural network on the limited data generally used prior to deep learning employment. The result shows that a deep neural network can still achieve comparable performance in the limited data settings.

关键词： Phosphorylation Site Prediction Protein Phosphorylation Deep Learning Deep Neural Network

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K-Means Clustering Model to Discriminate Copper-Resistant Bacteria as Bioremediation Agents

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Procedia Computer Science 2021年 179卷 804-812页

作者： Ika Nurlaila Wahyu Irawati Kartika Purwandari Bens Pardamean Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Department of Biology Education Faculty of Education Pelita Harapan University Tangerang Indonesia 15811 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Copper (Cu) has been excessively used for some valuable commodities and this creates environmental problems. The inorganic element becomes toxic when presents beyond the recommended tolerated concentration. Bacterial-based remediation is seen to be an excellent tool to overcome it as it reduces the copper contamination without yielding any other forms of contamination. There are some pivotal properties in the bacteria render them being considered as bioremediation agents against coppers contamination, namely bioaccumulation and biosorption. In the present study, we question if these bacteria could be clustered into a strong and representative proximity according to their functional properties. Mostly, bacteria are grouped based on their genetic profiles derived from the 16S rRNA sequencing. We propose that our K-Means clustering model can be employed to identify genetically-unlabelled bacteria. But first, a prominent reference should be developed and we are in this phase. We figured out the K-Means clustering model do not pull the same-genus bacteria into the same cluster. Instead, the model gathers into a proximity those isolates with similarity on a functional characteristic termed minimum inhibitory concentration (MIC), regardless their origins and their hierarchy in taxonomy.

关键词： Copper-Resistant Bacteria K-Means Minimum Inhibitory Concentration

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Web-based healthcare Hand Drawing Management System

Web-based healthcare Hand Drawing Management System

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Sheau-Ling Hsieh Yung-Ching Weng Chi-Huang Chen Kai-Ping Hsu Jeng-Wei Lin Feipei Lai EECS International Graduate Program Institute IT Center National Chiao Tung University Hsinchu Taiwan Taiwan University Taipei Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Computer and Information Networking Center National Taiwan University Taipei Taiwan Department of Information Management Tunghai University Taichung Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan

The paper addresses Medical Hand Drawing Management System architecture and implementation. In the system, we developed four modules: hand drawing management module; patient medical records query module; hand drawing editing and upload module; hand drawing query module. The system adapts windows-based applications and encompasses web pages by *** hosting mechanism under web services platforms. The hand drawings implemented as files are stored in a FTP server. The file names with associated data, e.g. patient identification, drawing physician, access rights, etc. are reposited in a database. The modules can be conveniently embedded, integrated into any system. Therefore, the system possesses the hand drawing features to support daily medical operations, effectively improve healthcare qualities as well. Moreover, the system includes the printing capability to achieve a complete, computerized medical document process. In summary, the system allows web-based applications to facilitate the graphic processes for healthcare operations.

关键词： Medical services Biomedical imaging Printing Conferences Web services Graphics Databases

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Clustering Analysis of a Spatiotemporal Dataset with a Novel Kernel Density Estimator

Clustering Analysis of a Spatiotemporal Dataset with a Novel...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jen-Chien Yu Chun-Chieh Yang John Reuben Gilbert Rou-Jun Liu Yen-Jen Oyang Meng-Han Yang Department of Computer Science and Information Engineering National Kaohsiung University of Science and Technology Kaohsiung City Taiwan ROC Master Program in Statistics National Taiwan University Taipei Taiwan ROC Department of Computer Science & Information Engineering National Taiwan University Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University

A vast number of spatiotemporal datasets collected from a wide range of sources has motivated scientists to develop effective approaches to identify interesting patterns hidden in these datasets. In this respect, kernel density estimators, which belong to a class of non-parametric estimators in statistics, have been widely exploited in recent years. With this background, we have developed a novel kernel density estimator aiming to provide accurate analysis results. According to the evaluation with a real spatiotemporal dataset, which collected emergency medical service records in a county in the United States, the proposed kernel density estimator can approximate the probability density function significantly more accurately than a conventional kernel density estimator. Furthermore, we have exploited the proposed kernel density estimator to identify interesting patterns hidden in the real spatiotemporal dataset.

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Automatic Smart Crawling on Twitter for Weather Information in Indonesia

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Procedia Computer Science 2023年 227卷 795-804页

作者： Kartika Purwandari Reza Bayu Perdana Join W.C. Sigalingging Reza Rahutomo Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Database Center Division of BMKG Meteorological Climatological and Geophysical Agency Jakarta 10720 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

Although Twitter is a popular platform for social interaction analysis and text data mining, it faces challenges with geolocation automation. To address this problem, the researchers propose the utilization of a Support Vector Machine (SVM) model to develop an automated Twitter crawling system. The system aims to collect data related to weather in Indonesia by employing Twin, a Python-based Twitter scraping software. To overcome null geolocations, the study incorporates aliases created based on the common practice of Indonesian users mentioning the country's location in tweets. The results demonstrate that the SVM model, combined with automated smart crawling, achieves an 85% accuracy rate.

关键词： Social media Twitter SVM smart crawling weather

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Metagenomic analysis reveals the roles of Actinobacteria in plasticizer-contaminated landfills and aids in identifying key degraders

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Scientific reports 2025年第1期15卷 18157页

作者： Adisan Rungsihiranrut Chanokporn Muangchinda Onruthai Pinyakong International Postgraduate Programs in Hazardous Substance and Environmental Management Graduate School Chulalongkorn University Bangkok 10330 Thailand. Center of Excellence in Microbial Technology for Marine Pollution Treatment (MiTMaPT) Department of Microbiology Faculty of Science Chulalongkorn University Bangkok 10330 Thailand. Center of Excellence in Microbial Technology for Marine Pollution Treatment (MiTMaPT) Department of Microbiology Faculty of Science Chulalongkorn University Bangkok 10330 Thailand. onruthai.p@chula.ac.th. Research Program on Remediation Technologies for Petroleum Contamination Center of Excellence on Hazardous Substance Management (HSM) Bangkok 10330 Thailand. onruthai.p@chula.ac.th. Omics Sciences and Bioinformatics Center Faculty of Science Chulalongkorn University Bangkok 10330 Thailand. onruthai.p@chula.ac.th. Department of Microbiology Faculty of Science Chulalongkorn University Bangkok 10330 Thailand. onruthai.p@chula.ac.th.

Phthalate ester (PAE) contamination, particularly from dibutyl phthalate (DBP) and di-2-ethylhexyl phthalate (DEHP), originating from landfills and released into the environment, poses a significant concern. Understanding PAE biodegradation is crucial for developing bioremediation strategies. This study used cover material from a 1-month-old landfill for soil microcosms. Indigenous microbes effectively removed 300 mg kg of DBP and DEHP as individual and mixed substrates, achieving complete DBP removal and 70% DEHP removal at room temperature (27-30 °C) and 37 °C. Actinobacteria were dominant, indicating potential active PAE-degraders. Shotgun metagenomic analysis revealed an increased abundance of potential PAE catabolic genes, such as those encoding esterase, lipase, and dioxygenase, under all conditions, mainly associated with Streptomyces, Saccharopolyspora, Nocardia, Nocardioides, and Amycolatopsis. The genes associated with Saccharopolyspora were abundant at 37 °C, while those related to Nocardia and Actinomadura were prevalent at room temperature, suggesting temperature preferences. The genera Saccharopolyspora and Actinomadura have not been linked to PAE degradation, indicating potential novel PAE degraders. Furthermore, PAE-degrading bacteria were isolated using media designed from metagenomic data and were categorized into Streptomyces, Amycolatopsis, and Nocardia. This work highlights the roles of rare taxa and provides insights into potential novel PAE degraders, emphasizing the need for further research into these organisms.

关键词： Bioremediation PAE biodegradation pathway Plasticizer Shotgun sequencing Soil microcosm

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Effects of intracerebroventricular lipopolysaccharide administration on behavioral, neurochemical, and neurogenomic responses in adult zebrafish

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Behavioural Brain Research 2025年

作者： Nikita P. Ilyin David S. Galstyan Anastasia E. Zolotova Nikita I. Golushko Varvara N. Tolkunova Saklakova Daryna Daniil Martynov Kirill V. Apukhtin Adam M. Stewart Murilo S. de Abreu Allan V. Kalueff Institute of Translational Biomedicine St. Petersburg State University St. Petersburg Russia Institute of Experimental Medicine Almazov National Medical Research Centre Ministry of Healthcare of Russian Federation St. Petersburg Russia World Class Research Center for Personalized Medicine Almazov National Medical Research Centre Ministry of Healthcare of Russian Federation St. Petersburg Russia Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia Herzen State Pedagogical University St. Petersburg Russia International Zebrafish Neuroscience Research Consortium (ZNRC) New Orleans USA Graduate Program in Health Sciences Federal University of Health Sciences of Porto Alegre Porto Alegre Brazil Western Caspian University Baku Azerbaijan Department of Biosciences and Bioinformatics School of Science Xi'an Jiaotong-Liverpool University Suzhou China Suzhou Municipal Key Laboratory of Neurobiology and Cell Signaling School of Science Xi'an Jiaotong-Liverpool University Suzhou China

Neuroinflammation is a common trigger of multiple neuropsychiatric disorders. Lipopolysaccharide (LPS) administration in widely used to induce systemic and neural inflammation in various in vivo animal models. Complementing rodent studies, the zebrafish emerges as a powerful model organism for studying complex neurobehavioral consequences of neuroinflammation. Here, adult fish received intracerebroventricularly administered LPS and were assessed behaviorally in the novel tank, zebrafish tail immobilization (ZTI) and Y-maze tests for locomotor, affective and cognitive responses. We also performed neurochemical and neurogenomic profiling of zebrafish to assess their brain monoamine levels and the expression of selected cytokine-related genes. Overall, LPS-treated zebrafish showed hypolocomotion in the novel tank test, reduced spontaneous alternation in the Y-maze and higher ZTI test immobility, suggesting affective and cognitive deficits, accompanied by elevated serotonin turnover and upregulated pro-inflammatory ( Il1b, tnf ) and anti-inflammatory ( il10 ) cytokine genes. Collectively, these findings parallel rich rodent evidence of central LPS effects, and support zebrafish as a valuable model system for probing the interplay between neuroinflammation and psychiatric disorders, with a specific focus on evolutionarily conserved, shared mechanisms of CNS pathogenesis.

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Web Development of Direct-to-consumer Genetics Testing

Web Development of Direct-to-consumer Genetics Testing

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Kians Azizatikarna Deby Erina Parung Dian Amirullah Alam Ahmad Hidayat Tjeng Wawan Cenggoro Arif Budiarto Simon Bens Pardamean Genetics Indonesia Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665453967

As the cost of genetic testing becomes more affordable each year, direct-to-customer (DTC) genetic testing services witness rapid market growth. This has encouraged the development of an easy-to-use website application to optimize potential customers to obtain informed choice regarding the offered DTC genetic testing as well as purchasing information. We present a wireframing process as a part of the agile software development process to build a web portal prototype for an Indonesia-based genetic testing service called DNAku. The approach in building the prototype used in this case is a part of the Agile Software Development Method. In brief, the wireframing stage resulted in this work consists of three main important outcomes. The first one is the use case diagram as a blueprint of this web-based system. A site map is then proposed as an extended version of the use case diagram which visualizes the whole pages with the links. Finally, based on this site map a series of page mock-ups are designed using Hyper Text Marking Language (HTML) and Cascading Style Sheets (CSS). The result of the prototype can be used as the basis for the next development stage, which is the coding stage based on the collected feedback from users. Considering the continuous application development via the wireframing method by taking into account the cycle of feedbacks from involved parties, this approach can strengthen the infrastructure to sustain DTC genetic business model, which has a niche market in Indonesia.

关键词： Visualization Costs Buildings Prototypes Agile software development Genetics Encoding

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