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Ultrasonic interfacial crosslinking of TiO2-based nanocomposite hydrogels through thiol-norbornene reactions for sonodynamic antibacterial treatment

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Biomaterials science 2023年第12期11卷 4184-4199页

作者： Yang, Su-Rung Wang, Reuben Yan, Chen-Jie Lin, Yi-Yun Yeh, Yu-Jia Yeh, Ying-Yu Yeh, Yi-Cheun Institute of Polymer Science and Engineering National Taiwan University Taipei Taiwan Institute of Food Safety and Health National Taiwan University Taipei Taiwan Master of Public Health Program National Taiwan University Taipei Taiwan GIP-TRIAD Master's Degree in Agro-Biomedical Science National Taiwan University Taipei Taiwan

Nanocomposite (NC) hydrogels used for sonodynamic therapy (SDT) face challenges such as lacking interfacial interactions between the polymers and nanomaterials as well as presenting uneven dispersion of nanomaterials in the hydrogel network, reducing their mechanical properties and treatment efficiency. Here, we demonstrate a promising approach of co-engineering nanomaterials and interfacial crosslinking to expand the materials construction and biomedical applications of NC hydrogels in SDT. In this work, mesoporous silica-coated titanium dioxide nanoparticles with thiolated surface functionalization (TiO2@MS-SH) are utilized as crosslinkers to react with norbornene-functionalized dextran (Nor-Dex) through ultrasound-triggered thiol-norbornene reactions, forming TiO2@MS-SH/Nor-Dex NC hydrogels. The TiO2@MS-SH nanoparticles act not only as multivalent crosslinkers to improve the mechanical properties of hydrogels under ultrasound irradiation but also as reactive oxygen species (ROS) generators to allow the use of TiO2@MS-SH/Nor-Dex NC hydrogels in SDT applications. Particularly, the TiO2@MS-SH/Nor-Dex NC hydrogels present tailorable microstructures, properties, and sonodynamic killing of bacteria through the modulation of the ultrasound frequency. Taken together, a versatile TiO2-based NC hydrogel platform prepared under ultrasonic interfacial crosslinking reactions is developed for advancing the applications in SDT. © 2023 The Royal Society of Chemistry.

关键词： Titanium dioxide

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An Evaluation Of Hospital Accreditation From The Survey With Text Vector Analysis Techniques 20

An Evaluation Of Hospital Accreditation From The Survey With...

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20th International Joint Conference on Computer science and Software Engineering, JCSSE 2023

作者： Prapunwattana, Dittaphong Imsombut, Aurawan Suwannahitatorn, Picha Saethang, Thammakorn Kasetsart University Biomedical Data Science Master's Program Faculty of Science Bangkok Thailand Kasetsart University Faculty of Science Department of Computer Science Bangkok Thailand Bangkok Thailand

ISBN: (纸本)9798350300505

The Healthcare Accreditation Institute has an assessment and certification process for hospitals applying for Healthcare Accreditation. The assessment process requires a large number of text-based reports. The purpose of this research was to study the text analysis of the self-assessment reports of healthcare facilities and surveyor reports on issues related to the pharmaceutical system to evaluate and rate the accreditation of medical facilities. The natural language text vector analysis technique, together with the Universal Sentence Encoder (USE) was compared to Learning Lightweight Language-agnostic Sentence Embeddings (LEALLA) for encoding data into a high-dimensional format. Next the sentence encoding feature was fed through a machine learning procedure, including artificial neural networks, logistic regression, and support vector machines to classify nursing facility accreditation ratings. The experimental results showed that the USE embedding yielded better performance than the LEALLA embedding across all models with a precision of 0.70 but took slightly longer to encode feature sentences. This research could improve the performance of the analysis and scoring. © 2023 IEEE.

关键词： Embeddings

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Analysis of the 5Rs in Thailand Medication Error Classification through Natural Language Processing 20

Analysis of the 5Rs in Thailand Medication Error Classificat...

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20th International Joint Conference on Computer science and Software Engineering, JCSSE 2023

作者： Udomnuchaisup, Peachyasitt Imsombut, Aurawan Suwannahitatorn, Picha Saethang, Thammakorn Kasetsart University Biomedical Data Science Master's Program Faculty of Science Bangkok Thailand Kasetsart University Faculty of Science Department of Computer Science Bangkok Thailand Bangkok Thailand

ISBN: (纸本)9798350300505

Medication errors threaten patient safety considerably, underscoring the necessity for enhanced detection and prevention techniques. A prevalent classification system in hospitals relies on the standard practice of medication administration known as the Five Rights (5R). This study seeks to develop an NLP-based tool designed to expand 5R error categorization coverage and alleviate the workload of medical professionals. The proposed method focuses on Thai medical text, incorporating Thai and English vocabulary. In this investigation, we developed a supervised learning classification framework using the Universal Sentence Encoder (USE) for sentence embedding, followed by an Artificial Neural Network (ANN) for model training. Additionally, we explored a zero-shot classification model employing pre-trained Large Language Models (PLMs). Our findings reveal that the supervised learning classification model provides the most favorable performance, albeit with the limitation of reliance on labeled datasets, which can be resource intensive. Conversely, the zero-shot classification framework's performance is less optimal. However, future advancements in Thai medical PLMs may improve efficacy and present a viable alternative for medical data analysis without dependence on labeled datasets. This initiative lays the groundwork for potential future applications and advantages within Thailand's medical domain. © 2023 IEEE.

关键词： Neural networks

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Entropy-Based Analysis of Electromyography Signal Complexity During Flexion of the Flexor Carpi Radialis Muscle Under Varied Load Conditions 4th

Entropy-Based Analysis of Electromyography Signal Complexity...

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4th International Conference on Electronics, biomedical Engineering, and Health Informatics, ICEBEHI 2023

作者： Katherine Putra, Alfian Pramudita Kurniawan, Angeline Shane Istiqomah, Dezy Zahrotul Sholihah, Nisa’ul Al-Salehi, Khalid Ali Salem Ain, Khusnul Sapuan, Imam Andarini, Esti Biomedical Engineering Master Program Department of Physics Faculty of Science and Technology Universitas Airlangga Surabaya60115 Indonesia Biomedical Engineering Study program Department of Physics Faculty of Science and Technology Universitas Airlangga Surabaya Indonesia Department of Physics Faculty of Science and Technology Universitas Airlangga Surabaya Indonesia School of Nursing Southern Medical University Guangdong Guangzhou510515 China

ISBN: (纸本)9789819714629

The motor impairments that stroke patients experience as a primary contributor to death and disability also impact their quality of life. Due to its characteristics as complex muscle signals, the Electromyograph (EMG) signal may be one of the markers in rehabilitation and a substitute that may be used to judge the success of rehabilitation. This study aims to analyze the complexity of EMG signals originating from the flexion of the flexor carpi radialis muscle with various weights indicating the rehabilitation state. It is important to monitor the progress of rehabilitation, and it can be done by using complexity analysis. The complexity of the EMG is examined in this work utilizing entropy measurement, namely Approximate Entropy (ApEn), Sample Entropy (SampEn), and Fuzzy Approximate Entropy (fApEn). We concentrated on the flexor carpi radialis muscle using flexion–extension exercises and varying the weight load. This study’s results indicate differences in the complexity of the EMG signal in the flexor carpi radialis when performing flexion–extension movements. Three differences showed a correlation based on the value of ApEN, SampEn, and fApEn. Complexity Analysis using fApEn showed the best correlation at R = 0.9966, which can be used to evaluate the rehabilitation process. The increase in weight was followed by the increase of the fApEn value, indicating that the value can be used to evaluate the rehabilitation process. The use of complexity analysis of EMG signal from flexion movement in flexor carpi radialis with various weights can be used to indicate the progress in the rehabilitation process. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Entropy

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Fabrication of versatile poly(xylitol sebacate)-co-poly(ethylene glycol) hydrogels through multifunctional crosslinkers and dynamic bonds for wound healing

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Acta Biomaterialia 2023年 170卷 344-359页

作者： Yeh, Ying-Yu Lin, Yi-Yun Wang, Ting-Teng Yeh, Yu-Jia Chiu, Ting-Hsiang Wang, Reuben Bai, Meng-Yi Yeh, Yi-Cheun Institute of Polymer Science and Engineering National Taiwan University Taipei Taiwan Institute of Biomedical Engineering National Taiwan University Taipei Taiwan Biomedical Engineering Program Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology Taipei Taiwan Institute of Food Safety and Health National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan Adjunct Appointment to the Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Program National Taiwan University Taipei Taiwan GIP-TRIAD Master's Degree in Agro-Biomedical Science National Taiwan University Taipei Taiwan

Poly(polyol sebacate) (PPS) polymer family has been recognized as promising biomaterials for biomedical applications with their characteristics of easy production, elasticity, biodegradation, and cytocompatibility. Poly(xylitol sebacate)-co-poly(ethylene glycol) (PXS-co-PEG) has been developed to fabricate PPS-based hydrogels;however, current PXS-co-PEG hydrogels presented limited properties and functions due to the limitations of the crosslinkers and crosslinking chemistry used in the hydrogel formation. Here, we fabricate a new type of PXS-co-PEG hydrogels through the use of multifunctional crosslinkers as well as dynamic bonds. In our design, polyethyleneimine-polydopamine (PEI-PDA) macromers are utilized to crosslink aldehyde-functionalized PXS-co-PEG (APP) through imine bonds and hydrogen bonds. PEI-PDA/APP hydrogels present multiple functional properties (e.g., fluorescent, elastomeric, biodegradable, self-healing, bioadhesive, antioxidant, and antibacterial behaviors). These properties of PEI-PDA/APP hydrogels can be fine-tuned by changing the PDA grafting degrees in the PEI-PDA crosslinkers. Most importantly, PEI-PDA/APP hydrogels are considered promising wound dressings to promote tissue remodeling and prevent bacterial infection in vivo. Taken together, PEI-PDA/APP hydrogels have been demonstrated as versatile biomaterials to provide multiple tailorable properties and desirable functions to expand the utility of PPS-based hydrogels for advanced biomedical applications. Statement of significance: Various strategies have been developed to fabricate poly(polyol sebacate) (PPS)-based hydrogels. However, current PPS-based hydrogels present limited properties and functions due to the limitations of the crosslinkers and crosslinking chemistry used in the hydrogel formation. This work describes that co-engineering crosslinkers and interfacial crosslinking is a promising approach to synthesizing a new type of poly(xylitol sebacate)-co-poly(ethylene glycol) (PXS-co-

关键词： Polyols

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Beyond the Scroll: Eye-Tracking Evaluations on the National Gallery of Indonesia’s Instagram 26th

Beyond the Scroll: Eye-Tracking Evaluations on the National ...

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26th International Conference on Asia-Pacific Digital Libraries, ICADL 2024

作者： Sari, Desy Novita Prameswari, Clarissa Rahmi Anshori, Isa Master’s Program in Library Science Universitas Indonesia Kota Depok Indonesia Department of Library and Information Sciences Universitas Indonesia Kota Depok Indonesia Biomedical Engineering Department School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia National Gallery of Indonesia Central Jakarta Indonesia

ISBN: (纸本)9789819608676

Eye-tracking studies focused on art galleries and museums within the realm of Instagram, especially in the Indonesian context, are notably scant. This investigation elucidates the user interaction and experience of the art gallery’s Instagram account, @galerinasional. Employing a quantitative approach, we implemented eye-tracking experiments using the well-known online eye-tracking software RealEye. The study participants were followers of the National Gallery of Indonesia’s (Galnas) Instagram profile, seven women and three men, in two age brackets: 18–24 years (n = 5) and 25–34 years (n = 5). The experimental protocol required participants to execute five tasks centered on locating exhibition details and artwork on the Galnas Instagram platform, with a duration of 100 s allocated to each task. The Participant Quality Grade (PQG), examination duration, optimal browser dimensionality, K-factor mean, gaze and fixation frequencies, and heat maps were determined for the participants. The key findings are as follows. (1) The participants’ PQG scores were predominantly between 4 and 6. (2) Investigative browsing typically exceeded the 100-s limit. (3) The consensus on the ideal browser dimensions hovered around 1,368.6 × 814.8 px. (4) The K-factor mean across participants tended toward K > 0. (5) The average gaze occurrence was 27 items per second for most participants. (6) A noticeable disparity in fixation counts was observed between the two age groups, with individuals aged 25–34 demonstrating prolonged engagement with Galnas’ content. (7) Heat maps accentuated a pronounced concentration on visual content, encompassing photographs, videos, and their associated captions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Economic and social effects

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Overcoming the Blood-Brain Tumor Barrier with Docetaxel-Loaded Mesoporous Silica Nanoparticles for Treatment of Temozolomide-Resistant Glioblastoma

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ACS Applied Materials and Interfaces 2024年第17期16卷 21722-21735页

作者： Hsu, Tsung-I Chen, Yi-Ping Zhang, Rong-Lin Chen, Zih-An Wu, Cheng-Hsun Chang, Wen-Chang Mou, Chung-Yuan Chan, Hardy Wai-Hong Wu, Si-Han Ph.D. Program in Medical Neuroscience College of Medical Science and Technology Taipei Medical University and National Health Research Institutes Taipei110 Taiwan International Master Program in Medical Neuroscience College of Medical Science and Technology Taipei Medical University Taipei110 Taiwan Graduate Institute of Nanomedicine and Medical Engineering Taipei Medical University Taipei110 Taiwan International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei110 Taiwan Nano Targeting & Therapy Biopharma Inc. Taipei110 Taiwan Graduate Institute of Medical Sciences College of Medicine Taipei Medical University Taipei110 Taiwan Department of Chemistry National Taiwan University Taipei106 Taiwan

While temozolomide (TMZ) has been a cornerstone in the treatment of newly diagnosed glioblastoma (GBM), a significant challenge has been the emergence of resistance to TMZ, which compromises its clinical benefits. Additionally, the nonspecificity of TMZ can lead to detrimental side effects. Although TMZ is capable of penetrating the blood-brain barrier (BBB), our research addresses the need for targeted therapy to circumvent resistance mechanisms and reduce off-target effects. This study introduces the use of PEGylated mesoporous silica nanoparticles (MSN) with octyl group modifications (C8-MSN) as a nanocarrier system for the delivery of docetaxel (DTX), providing a novel approach for treating TMZ-resistant GBM. Our findings reveal that C8-MSN is biocompatible in vitro, and DTX@C8-MSN shows no hemolytic activity at therapeutic concentrations, maintaining efficacy against GBM cells. Crucially, in vivo imaging demonstrates preferential accumulation of C8-MSN within the tumor region, suggesting enhanced permeability across the blood-brain tumor barrier (BBTB). When administered to orthotopic glioma mouse models, DTX@C8-MSN notably prolongs survival by over 50%, significantly reduces tumor volume, and decreases side effects compared to free DTX, indicating a targeted and effective approach to treatment. The apoptotic pathways activated by DTX@C8-MSN, evidenced by the increased levels of cleaved caspase-3 and PARP, point to a potent therapeutic mechanism. Collectively, the results advocate DTX@C8-MSN as a promising candidate for targeted therapy in TMZ-resistant GBM, optimizing drug delivery and bioavailability to overcome current therapeutic limitations. © 2024 The Authors. Published by American Chemical Society.

关键词： Tumors

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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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2023 International Conference on Machine Learning and Cybernetics, ICMLC 2023

作者： Yu, Jen-Chien Yang, Chun-Chieh Gilbert, John Reuben Liu, Rou-Jun Oyang, Yen-Jen Yang, Meng-Han National Kaohsiung University of Science and Technology Department of Computer Science and Information Engineering Kaohsiung City807618 Taiwan National Taiwan University Master Program in Statistics Taipei106216 Taiwan National Taiwan University Department of Computer Science & Information Engineering Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taiwan

ISBN: (纸本)9798350303780

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. © 2023 IEEE.

关键词： Probability density function

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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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Foot hemodynamics using optical tomography: A potential biomarker of peripheral arterial disease

Foot hemodynamics using optical tomography: A potential biom...

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2023 Advances in science and Engineering Technology International Conferences, ASET 2023

作者： Al Abdi, Rabah M. Zakaria, Amer Al Nashash, Hasan Zalak, Tasnim Goswami, Nandu Jeet, Vishwa Jordan Univ. of Science and Tech. Dept. of Biomedical Engineering Irbid Jordan American University of Sharjah Dept. of Electrical Engineering Sharjah United Arab Emirates American University of Sharjah Master of Science in Biomedical Engineering Program Sharjah United Arab Emirates College of Medicine Mohammed Bin Rashed University of Medicine and Health Sciences Dubai United Arab Emirates

ISBN: (纸本)9781665454742

Peripheral arterial disease (PAD) is the narrowing of the arteries within the lower extremities, which inhibits blood flow to the foot. We present the use of dynamic diffuse optical tomography (DDOT) system to measure blood flow in the foot during venous and arterial occlusions. DDOT is a non-ionizing, contrast-free, and fast imaging modality. The DDOT system consists of 4 sensors, each containing four laser diodes (at wavelengths of 670, 780, 808, and 850 nm) and two silicon photodiodes. We examined 11 healthy subjects with a protocol consisting of five consecutive measurements. Biomarkers were extracted from changes in hemoglobin concentrations during the measurements. The results from a pilot study are presented in this report. The average increase in total hemoglobin was 17.2 ±5.8 μ M during a measurement with 60 mmHg occlusion and 10.4 ± 6.7 μ M during a measurement with 180 mmHg occlusion. The biomarkers can quantify blood perfusion and oxygen consumption in the foot, and they have the potential to detect and monitor PAD. © 2023 IEEE.

关键词： Hemodynamics

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