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3D-Printable Photothermal and Temperature-Controlled Polycaprolactone Scaffolds Incorporating Gold Plasmonic Blackbodies for Bone Tissue Engineering

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ACS Applied Materials and Interfaces 2025年第20期17卷 29455-29468页

作者： Chen, Chieh-Ying Hope Gadia Moreno, Ruaina Lily Wang, Po-Yao Nguyen, Thanh Sang Wu, Jia-Lin Chen, Kuan-Hao Chen, Chih-Hwa Lin, Chia-Ying Wong, Pei-Chun Graduate Institute of Biomedical Optomechatronics College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan School of Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Graduate Institute of Biomedical Materials and Tissue Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Department of Orthopedics Taipei Medical University Hospital Taipei11031 Taiwan International Ph.D. Program in Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan Department of Trauma Hue Central Hospital Hue530000 Viet Nam Department of Orthopedics School of Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan Orthopedics Research Center Taipei Medical University Hospital Taipei11031 Taiwan Centers for Regional Anesthesia and Pain Medicine Wan Fang Hospital Taipei Medical University Taipei11096 Taiwan Department of Orthopedics Shuang Ho Hospital Taipei Medical University New Taipei23561 Taiwan Convergent Bioscience and Technology Institute Department of Biomedical Engineering and Informatics Indiana University IndianapolisIN46202 United States

Three-dimensional (3D) printing technology has revolutionized the design and fabrication of bone scaffolds, offering precise and customizable solutions for bone tissue engineering. In this study, we developed polycaprolactone (PCL) scaffolds that incorporated gold plasmonic blackbodies (AuPBs) to harness photothermal properties for temperature-controlled bone regeneration. The AuPB-PCL scaffolds demonstrated enhanced mechanical strength, a tunable thermal response under near-infrared (NIR) laser irradiation, and improved osteogenic potential. Photothermal stimulation effectively modulated cellular responses, promoting osteoblast proliferation, alkaline phosphatase (ALP) activity, and mineralization. Notably, mild hyperthermia (39-41 °C) induced by laser irradiation optimized osteogenesis, while excessive temperatures (≥42.5 °C) impaired cellular function due to mitochondrial stress and oxidative damage. These findings highlight the potential of AuPB-PCL scaffolds for controlled photothermal bone regeneration, offering a promising strategy for precise, completely noninvasive stimulation of bone repair. © 2025 The Authors. Published by American Chemical Society.

关键词： Fiber bonding

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Using a Recurrent Neural Network Model for Classification of Tweets Conveyed Influenza-related Information 1

Using a Recurrent Neural Network Model for Classification of...

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1st International Workshop on Digital Disease Detection using Social Media, DDDSM 2017, co-located with the 8th International Joint Conference on Natural Language Processing, IJCNLP 2017

作者： Wang, Chen-Kai Singh, Onkar Tang, Zhao-Li Dai, Hong-Jie Graduate Institute of Biomedical Informatics Taipei Medical University Taipei Taiwan Bioinformatics Program Taiwan International Graduate Program Institute of Information Science Academia Sinica Taipei Taiwan Institute of Biomedical Informatics National Yang-Ming University Taipei Taiwan Department of Computer Science and Information Engineering National Taitung University Taitung Taiwan Interdisciplinary Program of Green and Information Technology National Taitung University Taitung Taiwan

ISBN: (纸本)9781948087070

Traditional disease surveillance systems depend on outpatient reporting and virological test results released by hospitals. These data have valid and accurate information about emerging outbreaks but it's often not timely. In recent years the exponential growth of users getting connected to social media provides immense knowledge about epidemics by sharing related information. Social media can now flag more immediate concerns related to outbreaks in real time. In this paper we apply the long short-term memory recurrent neural network (RNN) architecture to classify tweets conveyed influenza-related information and compare its performance with baseline algorithms including support vector machine (SVM), decision tree, naive Bayes, simple logistics, and naive Bayes multinomial. The developed RNN model achieved an F-score of 0.845 on the MedWeb task test set, which outperforms the F-score of SVM without applying the synthetic minority oversampling technique by 0.08. The F-score of the RNN model is within 1% of the highest score achieved by SVM with oversampling technique. © 2017 AFNLP

关键词： Support vector machines

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Implementing globally unique identifier architecture in date collection for a health management study in taiwan aboriginal tribe 1

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9th FTRA International Conference on Future Information technology, FutureTech 2014

作者： Hung, Jui-Fu Rau, Hsiao-Hsien Hsu, Chien-Yeh Chen, Shih-Chang Tsai, Duu-Jian Fann, Yang Park, Joshua Eng, Joshua Graduate Institute of Biomedical Informatics Taipei Medical University Taipei Taiwan Graduate Institute of Patent National Taiwan University of Science and Technology Taipei Taiwan Intramural IT and Bioinformatics Program NINDS NIH HHS Bethesda United States

ISBN: (数字)9789401795586

ISBN: (纸本)9789401795579

In present, more and more attention has been put on the effort of protection of personal data and also new encryption technologies are derived. In this article, we introduce a personal information protection technology, global unique identifier (GUID), which is developed by National Institutes of Health U.S. and used for personal health information protection. The GUID is an identifier that allows researchers to associate and share data specific to a study participant without using or exposing personally identifiable information (PII). The GUID is made up of random alphanumeric characters and is not directly generated from PII/Protected Health Information (PHI). It has been approved by the NIH/USA office General Counsel for secure sharing of anonymized database. In our study, we used GUID as key identifier for health data collection from aboriginal tribe in a health promotion project. © Springer Science+Business Media Dordrecht 2015.

关键词： Cryptography

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Impact of DNA-binding position variants on yeast gene expression

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Nucleic Acids Research 2009年第21期37卷 6991-7001页

作者： Swamy, Krishna B.S. Cho, Chung-Yi Chiang, Sufeng Tsai, Zing Tsung-Yeh Tsai, Huai-Kuang Institute of Information Science National Yang-Ming University Taiwan Bioinformatics Program Taiwan International Graduate Program National Yang-Ming University Taiwan Institute of Biomedical Informatics National Yang-Ming University Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei 115 Taiwan

Transcription factors (TFs) regulate gene expression by binding to specific binding sites (TFBSs) in gene promoters. TFBS motifs may contain one or more variable positions. Although the prevailing assumption is that nucleotide variants at such positions are functionally equivalent, there is increasing evidence that such variants play a role in regulation of gene expression. In this article, we propose a method for studying the relationship between the expression of target genes and nucleotide variants in TFBS motifs at a genome-wide scale in Saccharomyces cerevisiae, especially the combinatorial effects of variants at two positions. Our analysis shows that nucleotide variations in more than one-third of variable positions and in 20% of dependent position pairs are highly correlated to gene expression. We define such positions as 'functional'. However, some positions are only functional as dependent pairs, but not individually. In addition, a significant proportion of the functional positions have been well conserved across all yeast-related species studied. We also find that some positions require the presence of co-occurring TFs, while others maintain their functionality in the absence of a co-occurring TF. Our analysis supports the importance of nucleotide variants at variable positions of TFBSs in gene regulation. © The Author(s) 2009. Published by Oxford University Press.

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Meteorological influences on dengue transmission in Pakistan

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Asian Pacific Journal of Tropical Medicine 2016年第10期9卷 932-938页

作者： Suleman Atique Shabbir Syed Abdul Chien-Yeh Hsu Ting-Wu Chuang Graduate Institute of Biomedical Informatics College of Medical Science and TechnologyTaipei Medical University Master Program in Global Health and Development Taipei Medical University Department of Information Management National Taipei University of Nursing and Health Sciences Department of Molecular Parasitology and Tropical Diseases School of MedicineCollege of MedicineTaipei Medical University

Objective: To identify the influences of local and regional climate phenomena on dengue transmission in Lahore District of Pakistan, from 2006 to 2014. Methods: Time-series models were applied to analyze associations between reported cases of dengue and climatic parameters. The coherence trend of regional climate phenomena(IOD and ENSO) was evaluated with wavelet analysis. Results: The minimum temperature 4 months before the dengue outbreak played the most important role in the Lahore District(P=0.03). A NINO 3.4 index 9 months before the outbreaks exhibited a significant negative effect on dengue transmission(P=0.02). The IOD exhibited a synchronized pattern with dengue outbreak from 2010 to 2012. The ENSO effect(NINO 3.4 index) might have played a more important role after 2012. Conclusions: This study provides preliminary results of climate influences on dengue transmission in the Lahore District of Pakistan. An increasing dengue transmission risk accompanied by frequent climate changes should be noted. Integrating the influences of climate variability into disease prevention strategies should be considered by public health authorities.

关键词： Dengue Fever Pakistan Climate IOD NINO 3.4

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Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains

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Computational and Structural Biotechnology Journal 2024年 23卷 1864-1876页

作者： Do, Duyen Thi Yang, Ming-Ren Vo, Tran Nam Son Le, Nguyen Quoc Khanh Wu, Yu-Wei Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University Taipei Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Business Administration College of Management Lunghwa University of Science and Technology Taoyuan City Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei Taiwan TMU Research Center for Digestive Medicine Taipei Medical University Taipei Taiwan

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these limitations, we propose a pan-genome-based machine learning approach to advance our understanding of AMR gene repertoires and uncover possible feature sets for precise AMR classification. By building compacted de Brujin graphs (cDBGs) from thousands of genomes and collecting the presence/absence patterns of unique sequences (unitigs) for Pseudomonas aeruginosa, we determined that using machine learning models on unitig-centered pan-genomes showed significant promise for accurately predicting the antibiotic resistance or susceptibility of microbial strains. Applying a feature-selection-based machine learning algorithm led to satisfactory predictive performance for the training dataset (with an area under the receiver operating characteristic curve (AUC) of > 0.929) and an independent validation dataset (AUC, approximately 0.77). Furthermore, the selected unitigs revealed previously unidentified resistance genes, allowing for the expansion of the resistance gene repertoire to those that have not previously been described in the literature on antibiotic resistance. These results demonstrate that our proposed unitig-based pan-genome feature set was effective in constructing machine learning predictors that could accurately identify AMR pathogens. Gene sets extracted using this approach may offer valuable insights into expanding known AMR genes and forming new hypotheses to uncover the underlying mechanisms of bacterial AMR. © 2024 The Authors

关键词： Genes

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Derivatives (halogen, nitro and amino) of 8-hydroxyquinoline with highly potent antimicrobial and antioxidant activities

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Biochemistry and Biophysics Reports 2016年 6卷 135-141页

作者： Cherdtrakulkiat, Rungrot Boonpangrak, Somchai Sinthupoom, Nujarin Prachayasittikul, Supaluk Ruchirawat, Somsak Prachayasittikul, Virapong Department of Clinical Microbiology and Applied Technology Faculty of Medical Technology Mahidol University Bangkok 10700 Thailand Center for Innovation Development and Technology Transfer Faculty of Medical Technology Mahidol University Bangkok 10700 Thailand Center of Data Mining and Biomedical Informatics Faculty of Medical Technology Mahidol University Bangkok 10700 Thailand Laboratory of Medicinal Chemistry Chulabhorn Research Institute and Program in Chemical Biology Chulabhorn Graduate Institute Bangkok 10210 Thailand Center of Excellence on Environmental Health and Toxicology Commission on Higher Education (CHE) Ministry of Education Thailand

8-Hydroxyquinoline (8HQ) compounds have been reported to possess diverse bioactivities. In recent years, drug repositioning has gained considerable attention in drug discovery and development. Herein, 8HQ (1) and its derivatives (2-9) bearing various substituents (amino, nitro, cyano and halogen) were investigated for their antimicrobial against 27 microorganisms (agar dilution method) and antioxidant (DPPH method) activities. The parent 8HQ (1) exerted a highly potent antimicrobial activity against Gram-positive bacteria including diploid fungi and yeast with MIC values in the range of 3.44-13.78 μM. Moreover, the halogenated 8HQ, especially 7-bromo-8HQ (4) and clioquinol (6), displayed a high antigrowth activity against Gram-negative bacteria compared with the parent compound (1). Apparently, the derivatives with a relatively high safely index, e.g., nitroxoline (2), exhibited strong antibacterial activity against Aeromonas hydrophila (MIC=5.26 μM) and selectively inhibited the growth of P. aeruginosa with the MIC value of 84.14 μM;cloxyquin (3) showed a strong activity against L. monocytogenes and P. shigelloides with MIC values of 5.57 and 11.14 μM, respectively. Most compounds displayed an antioxidant activity. Specifically, 5-amino-8HQ (8) was shown to be the most potent antioxidant (IC₅₀=8.70 μM) compared with the positive control (α-tocopherol) with IC₅₀ of 13.47 μM. The findings reveal that 8HQ derivatives are potential candidates to be further developed as antimicrobial and antioxidant agents. © 2016 The Authors.

关键词： 8-Hydroxyquinoline Antimicrobial Antioxidant Clioquinol Cloxyquin Nitroxoline

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Simultaneous identification for synergistic transcription factors and their transcription factor binding sites

Simultaneous identification for synergistic transcription fa...

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5th International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2011

作者： Tsai, Zing Tsung-Yeh Huang, Grace Tzu-Wei Tsai, Huai-Kuang Institute of Information Science Academia Sinica Taipei 115 Taiwan Bioinformatics Program Taiwan International Graduate Program Taiwan Institute of Biomedical Informatics National Yang-Ming University Taiwan Joint CMU-Pitt PhD Program in Computational Biology University of Pittsburgh Carnegie Mellon University Pittsburgh PA United States Research Center for Information Technology Innovation Taipei 115 Taiwan Computer Science and Engineering National Taiwan Ocean University Keelung 202 Taiwan

ISBN: (纸本)9780769543734

Identifying transcription factor binding sites (TFBSs) is crucial for understanding the mechanism of transcriptional regulation. It is known that transcription factors (TFs) often cooperate to regulate genes. While traditional approaches can be used to discover binding motifs of a group of co-regulated genes, they often fail to accurately assign motifs to the corresponding TFs. Here, we consider two TFs together to infer their TFBSs and their synergistic relationship simultaneously. The basic idea is that if two TFs interact, their TFBSs, if distinct, would be conserved across species and coincided in the promoter regions of the genes they co-regulated. Applying our method to Saccharomyces cerevisiae chromatin immunoprecipitation data, we predicted 110 TF pairs with statistically significant motif assignments. A majority of these TF pairs have literature support to be synergistic, and the designated motifs to TFs match well with their known consensus. We further examined the synergism of predicted TF pairs in seven experimental conditions using ANOVA, and identified significant interactions. © 2011 IEEE.

关键词： Yeast

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SeqCP: A sequence-based algorithm for searching circularly permuted proteins

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Computational and Structural Biotechnology Journal 2023年 21卷 185-201页

作者： Chen, Chi-Chun Huang, Yu-Wei Huang, Hsuan-Cheng Lo, Wei-Cheng Lyu, Ping-Chiang Bioinformatics Program Institute of Information Science Taiwan International Graduate Program Academia Sinica Taipei115 Taiwan Institute of Bioinformatics and Structural Biology National Tsing Hua University Hsinchu300 Taiwan Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu300 Taiwan Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taipei112 Taiwan Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu300 Taiwan The Center for Bioinformatics Research National Yang Ming Chiao Tung University Hsinchu Taiwan

Circular permutation (CP) is a protein sequence rearrangement in which the amino- and carboxyl-termini of a protein can be created in different positions along the imaginary circularized sequence. Circularly permutated proteins usually exhibit conserved three-dimensional structures and functions. By comparing the structures of circular permutants (CPMs), protein research and bioengineering applications can be approached in ways that are difficult to achieve by traditional mutagenesis. Most current CP detection algorithms depend on structural information. Because there is a vast number of proteins with unknown structures, many CP pairs may remain unidentified. An efficient sequence-based CP detector will help identify more CP pairs and advance many protein studies. For instance, some hypothetical proteins may have CPMs with known functions and structures that are informative for functional annotation, but existing structure-based CP search methods cannot be applied when those hypothetical proteins lack structural information. Despite the considerable potential for applications, sequence-based CP search methods have not been well developed. We present a sequence-based method, SeqCP, which analyzes normal and duplicated sequence alignments to identify CPMs and determine candidate CP sites for proteins. SeqCP was trained by data obtained from the Circular Permutation Database and tested with nonredundant datasets from the Protein Data Bank. It shows high reliability in CP identification and achieves an AUC of 0.9. SeqCP has been implemented into a web server available at: http://***/SeqCP/. © 2022 The Authors

关键词： Proteins

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Modeling of solitary pulmonary nodules in PET/CT images using Monte Carlo methods

Modeling of solitary pulmonary nodules in PET/CT images usin...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： George Tzanoukos Anastasios Gaitanis Alexandros Georgakopoulos Achilleas Chatziioannou Sofia Chatziioannou George Spyrou post-graduate Program: “Information Technologies in Medicine and Biology” (ITMB) National Center for Scientific Research (NCSR) “Demokritos” Athens CO Greece Department of Biomedical Technology Biomedical Research Foundation of the Academy of Athens (BRFAA) Athens Greece Nuclear Medicine Department Biomedical Research Foundation of the Academy of Athens (BRFAA) Athens Greece First Radiology Department University of Athens Athens Greece Biomedical Informatics Unit Biomedical Research Foundation of the Academy of Athens (BRFAA) Athens Greece

The assessment of solitary pulmonary nodules (SPN) is a very difficult task in PET imaging due to adjacent normal structures. Physicians and computational systems as well, would gain benefit if trained to a large number of SPN cases with controlled topological and morphological characteristics. Our objective was to develop a method for the modeling of the solitary pulmonary nodules in CT and PET images. The modeling of SPN was implemented by Monte Carlo methods taking into consideration morphological characteristics, internal features and Standardized Uptake Value (SUV) activity distribution. For the validation of the model, an observer study from three independent medical experts was performed. The reviewers characterized the lesions as simulated or real and finally they classified them as benign or malignant. According to the results of the human observer study a significant percentage of simulated images could not be differentiated from real ones and the simulated class (benign or malignant) was consistent with the observers' classification.

关键词： Positron emission tomography Lesions Computed tomography Cancer Observers Computational modeling Monte Carlo methods

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