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Incorporating self-assembled MXene to improve electrical conductivity of novel ZIF67 derivatives induced by NH4BF4 and NH4HF2 for energy storage

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Journal of Energy Storage 2024年 82卷

作者： Lee, Pin-Yan Chiou, Yu-Ren Cheng, Cheng-Siang Chen, Yu-Chun Kongvarhodom, Chutima Chen, Hung-Ming Yougbaré, Sibidou Husain, Sadang Ho, Kuo-Chuan Kuo, Tsung-Rong Lin, Lu-Yin Department of Chemical Engineering National Taiwan University Taipei Taiwan Graduate Institute of Nanomedicine and Medical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei Taiwan Department of Chemical Engineering King Mongkut's University of Technology Thonburi 126 Pracha-u-thit Toong-kru Bangkok10140 Thailand Gingen technology Co. LTD. Rm. 7 10F. No.189 Sec. 2 Keelung Rd. Xinyi Dist. Taipei11054 Taiwan /Nanoro 03 B.P 7192 Ouagadougou03 Burkina Faso Department of Physics Faculty of Mathematics and Natural Science Lambung Mangkurat University Banjarmasin70124 Indonesia International PhD Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan

Zeolitic imidazolate framework (ZIF-67) with high surface area and tunable pore size are considered as a promising active material for energy storage, but the low electrical conductivity restricts its performance. Developing ZIF67 derivatives with improved electrical conductivity is necessary to broaden its application in electrochemical fields. In this work, two strategies are applied to improve electrical conductivity and electrochemical performance of ZIF67. Novel structure directing agents of NH4BF4 and NH4HF2 are used to synthesize ZIF67 derivatives with higher theoretical capacitances and favorable layered structures. Self-assembled MXene with different amounts is further incorporated in ZIF67 derivatives to establish composites. The optimal composite electrode shows a high specific capacitance (CF) of 1410.4 F/g (775.6C/g) at 20 mV/s, while the ZIF67 derivative electrode without MXene only shows a CF value of 942.3 F/g (518.3C/g), due to the high surface area and better pore structure as well as the close combination of MXene and the layered ZIF67 derivative for the former case. An energy storage device with the optimal composite and carbon electrodes shows the maximum energy density of 32.40 Wh/kg at 375 W/kg. The Coulombic efficiency of 100% and the CF retention of 77.4% are also achieved after 10,000 cycles. © 2024 Elsevier Ltd

关键词： Energy storage

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Quantifying random variability in decision-making in pediatric cardiac surgery

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JTCVS Open 2025年 25卷 382-392页

作者： Dlugos, Kayla V. Mazwi, Mjaye Signorile, Marisa Steve Fan, Chun-Po Trbovich, Patricia Honjo, Osami Institute of Medical Science University of Toronto ON Canada Division of Cardiovascular Surgery The Labatt Family Heart Centre The Hospital for Sick Children Toronto ON Canada Department of Surgery University of Toronto ON Canada Division of Cardiac Critical Care Seattle Children's Hospital Seattle Wash United States Ted Rogers Computational Program Ted Rogers Centre for Heart Research Peter Munk Cardiac Centre UHN Toronto ON Canada Institute of Health Policy Management and Evaluation University of Toronto Toronto ON Canada North York General Hospital Toronto ON Canada Institute of Biomedical Engineering University of Toronto Toronto ON Canada

Objective: Random variability in day-to-day decision-making referred to as “noise” is associated with variation that negatively affects both the reproducibility and quality of decision-making. Although well described in other fields, the prevalence and significance of noise in medical decision-making are understudied and largely unknown. The goal of this study was to quantify noise in medical decision-making using a noise audit. Methods: A noise audit was completed by 71 (n = 71) Heart Centre staff at the Hospital for Sick Children and Seattle Children's Hospital and involved a series of cases and questions surrounding decisions commonly encountered in the care for patients with transposition of the great arteries and critical aortic stenosis. Entropy was used to quantify total variation in responses. Because absolute entropy was not immediately comparable across audit questions with a different number of prespecified options, we reported a standardized version of entropy, which was calculated by dividing the absolute entropy by its theoretical maximum for each case. To compare responses in easy to hard questions across years of experience (<10 years and >10 years) and role, we reported aggregate entropy ratios. Aggregate entropy ratios were calculated by first stratifying by group of comparison and then calculating the standardized entropy for each question and taking the average of standardized entropies for easy questions and hard questions. Finally, to determine the ratio (easy to hard), we divided the average standardized entropy of the easy questions by the average standardized entropy of the hard questions. Results: The overall audit aggregate entropy ratio was 0.85 less than 1, indicating lower-complexity questions had less variation than higher-complexity questions. The aggregate entropy ratio for those with more than 10 years of experience was 0.8 and 0.87, respectively, for those with less than 10 years of experience. The aggregate entropy ratios for thos

关键词： congenital heart surgery entropy medical decision-making noise noise audit random variability

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How renal toxins respond to renal function deterioration and oral toxic adsorbent in pH-controlled releasing capsule

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Environmental Toxicology 2024年第7期39卷 3930-3943页

作者： Liu, Wen-Sheng Liang, Shih-Shin Cheng, Mei-Mei Wu, Ming-Tsan Li, Szu-Yuan Cheng, Tien-Tien Liu, Tsung-Yun Tsai, Ching-Yao Lai, Yen-Ting Lin, Chien-Hung Wang, Hsiang-Tsui Tsou, Han-Hsing Division of Nephrology Department of Medicine Taipei City Hospital Taipei Taiwan School of Medicine National Yang Ming Chiao Tung University Hsinchu Taiwan College of Science and Engineering Fu Jen Catholic University New Taipei City Taiwan Institute of Food Safety and Health Risk Assessment National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Special Education University of Taipei Taipei Taiwan Institute of Biomedical Science College of Medicine National Sun Yat-sen University Kaohsiung Taiwan Department of Biotechnology College of Life Science Kaohsiung Medical University Kaohsiung Taiwan Division of nephrology Department of internal medicine West Garden Hospital Taipei Taiwan Department of internal medicine Fu-Ling clinic New Taipei City Taiwan Division of Nephrology and Department of Medicine Taipei Veterans General Hospital Taipei Taiwan Institute of Public Health Department of Public Health College of Medicine National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Ophthalmology Taipei City Hospital Taipei Taiwan Department of Business Administration Fu Jen Catholic University New Taipei City Taiwan Department of Physical Medicine and Rehabilitation National Taiwan University College of Medicine Taipei Taiwan Department of Physical Medicine and Rehabilitation National Taiwan University Hospital Hsin-Chu Branch Hsinchu Taiwan Department of Nursing College of Medical Technology and Nursing Yuanpei University of Medical Technology Hsinchu Taiwan Division of Pediatric Immunology and Nephrology Department of Pediatrics Taipei Veterans General Hospital Taipei Taiwan Department of Pharmacology National Yang Ming Chiao Tung University Hsinchu Taiwan Kim Forest Enterprise Co. Ltd. New Taipei City Taiwan

The number of patients with chronic kidney disease (CKD) is increasing. Oral toxin adsorbents may provide some value. Several uremic toxins, including indoxyl sulfate (IS), p-cresol (PCS), acrolein, per- and poly-fluoroalkyl substances (PFAS), and inflammation markers (interleukin 6 [IL-6] and tumor necrosis factor [TNF]-alpha) have been shown to be related to CKD progression. A total of 81 patients taking oral activated charcoal toxin adsorbents (AC-134), which were embedded in capsules that dissolved in the terminal ileum, three times a day for 1 month, were recruited. The renal function, hemoglobulin (Hb), inflammation markers, three PFAS (PFOA, PFOS, and PFNA), and acrolein were quantified. Compared with the baseline, an improved glomerular filtration rate (GFR) and significantly lower acrolein were noted. Furthermore, the CKD stage 4 and 5 group had significantly higher concentrations of IS, PCS, IL-6, and TNF but lower levels of Hb and PFAS compared with the CKD Stage 3 group at baseline and after the intervention. Hb was increased only in the CKD Stage 3 group after the trial (p =.032). Acrolein did not differ between the different CKD stage groups. Patients with improved GFR (responders) (about 77%) and nonresponders had similar baseline GFR. Responders had higher acrolein and PFOA levels throughout the study and a more significant reduction in acrolein, indicating a better digestion function. Both the higher PFOA and lower acrolein may be related to improved eGFR (and possibly to improvements in proteinuria, which we did not measure. Proteinuria is associated with PFAS loss in the urine), AC-134 showed the potential to improve the GFR and decrease acrolein, which might better indicate renal function change. Future studies are needed with longer follow-ups. © 2024 The Authors. Environmental Toxicology published by Wiley Periodicals LLC.

关键词： Deterioration

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Invited: Drug Discovery Approaches Using Quantum Machine Learning 21

Invited: Drug Discovery Approaches Using Quantum Machine Lea...

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Proceedings of the 58th Annual ACM/IEEE Design Automation Conference

作者： Junde Li Mahabubul Alam Congzhou M Sha Jian Wang Nikolay V. Dokholyan Swaroop Ghosh Department of Computer Science and Engineering Penn State University University Park Department of Electrical Engineering Penn State University University Park Department of Engineering Science and Mechanics Penn State University University Park and Department of Pharmacology Penn State College of Medicine Hershey Department of Pharmacology Penn State College of Medicine Hershey Department of Pharmacology Penn State College of Medicine Hershey and Department of Biochemistry & Molecular Biology Penn State College of Medicine Hershey and Departments of Chemistry and Biomedical Engineering Penn State University University Park Department of Computer Science and Engineering Penn State University University Park and Department of Electrical Engineering Penn State University University Park

ISBN: (纸本)9781665432740

Traditional drug discovery pipelines can require multiple years and billions of dollars of investment. Deep generative and discriminative models are widely adopted to assist in drug development. Classical machines cannot efficiently reproduce the atypical patterns of quantum computers, which may improve the quality of learned tasks. We propose a suite of quantum machine learning techniques: incorporating generative adversarial networks (GAN), convolutional neural networks (CNN) and variational auto-encoders (VAE) to generate small drug molecules, classify binding pockets in proteins, and generate large drug molecules, respectively.

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Pulmonary Disease Pattern Recognition on X-Ray Radiography Image Using Artificial Neural Network (ANN) Method 3

Pulmonary Disease Pattern Recognition on X-Ray Radiography I...

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3rd Annual Scientific Meeting on Medical Physics and Biophysics, PIT-FMB in conjunction with the 17th South-East Asia Congress of Medical Physics, SEACOMP 2019

作者： Fitriyah, N. Kurniawati, L.D. Purwanti, E. Astuti, S.D. Department of Physics Faculty of Science and Technology Universitas Airlangga Surabaya60115 Indonesia Biomedical Engineering Study Program Faculty of Science and Technology Universitas Airlangga Surabaya60115 Indonesia Department of Biomedical Engineering Post-Graduate Program Faculty of Science and Technology Universitas Airlangga Surabaya60115 Indonesia

This research aims to recognize the pattern of pulmonary disease on x-ray radiography image using artificial neural network (ANN) method. The images, which were used such as images of healthy pulmonary, pulmonary tuberculosis, and pulmonary tumour. Pattern recognition was using an extraction feature of GLCM (Gray Level Co-occurrence Matrix) and back propagation method. Before being identified, the images were processed by median filter and adaptive histogram equalization. The GLCM features that used were homogeneity, energy, contrast, variance and correlation. The parameters were learning rate and hidden layer. Learning rate was 0.3 and hidden layer was 25. Back propagation training showed 100% accuracy, which all of 44 images were used had been successfully identified. From the result, the healthy pulmonary showed 60% accuracy, 83.3% for pulmonary tuberculosis and 100% for pulmonary tumor. Hence, the overall result showed 81.25% accuracy, which 13 of 16 images had been successfully identified. From these result, extraction feature of GLCM using back propagation method was capable to recognize the pattern of pulmonary disease. However, due to narrow range of the feature, this application may not be used optimally for comparing features in every category of images. Therefore, the further research is needed to determine the best features and parameters of training back propagation. © Published under licence by IOP Publishing Ltd.

关键词： Pattern recognition

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The Utilization of Padding Scheme on Convolutional Neural Network for Cervical Cell Images Classification

The Utilization of Padding Scheme on Convolutional Neural Ne...

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2020 International Conference on Computer engineering, Network, and Intelligent Multimedia, CENIM 2020

作者： Haryanto, Toto Sitanggang, Imas Sukaesih Agmalaro, Muhammad Ashyar Rulaningtyas, Riries IPB University Computer Science Department Bogor Indonesia Universitas Airlangga Biomedical Engineering Program Department of Physics Surabaya Indonesia

ISBN: (纸本)9781728182834

Cervical cancer identification through pap-smear images analysis is a challenge for medicians, especially in distinguishing cells, between the normal and abnormal one. This study aims to create the classification model of Cervical Cell Images using the Convolutional Neural Network (CNN) algorithm. The dataset used is the image dataset SIPaKMeD. The CNN algorithm was implemented using the AlexNet architecture with and non-padding scheme. Padding is included in the experiments by adding the pixel 0 on the original images to improve the accuracy of the model. The experimental results show that using the utilization padding scheme on the AlexNet architecture can increase the accuracy of the model slightly significantly from 84.88% to 87.32%. © 2020 IEEE.

关键词： Convolutional neural networks

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A digital microfluidic device integrated with electrochemical sensor and 3D matrix for detecting soluble PD-L1

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Biosensors and Bioelectronics: X 2024年 19卷 100490页

作者： Zhang, Yuqian Liu, Jing Lo, Ting-Wen Kim, Yohan Lucien, Fabrice Dong, Haidong Liu, Yuguang Department of Physiology & Biomedical Engineering Mayo Clinic RochesterMN55905 United States Microbiomics Program Center for Individualized Medicine Mayo Clinic RochesterMN55905 United States Department of Urology Mayo Clinic College of Medicine and Science RochesterMN55905 United States Department of Immunology Mayo Clinic RochesterMN55905 United States Department of Surgery Mayo Clinic RochesterMN55905 United States

PD1/PD-L1 checkpoint inhibitors are at the forefront of cancer immunotherapies. However, the overall response rate remains only 10–30%. Even among initial responders, drug resistance often occurs, which can lead to prolonged use of a futile therapy in the race with the fatal disease. It would be ideal to closely monitor key indicators of patients’ immune responsiveness, such as circulating PD-L1 levels. Traditional PD-L1 detection methods, such as ELISA, are limited in sensitivity and rely on core lab facilities, preventing their use for the regular monitoring. Electrochemical sensors exist as an attractive candidate for point-of-care tool, yet, streamlining multiple processes in a single platform remains a challenge. To overcome this challenge, this work integrated electrochemical sensor arrays into a digital microfluidic device to combine their distinct merits, so that soluble PD-L1 (sPD-L1) molecules can be rapidly detected in a programmed and automated manner. This new platform featured microscale electrochemical sensor arrays modified with electrically conductive 3D matrix, and can detect as low as 1 pg/mL sPD-L1 with high specificity. The sensors also have desired repeatability and can obtain reproducible results on different days. To demonstrate the functionality of the device to process more complex biofluids, we used the device to detect sPD-L1 molecules secreted by human breast cancer cell line in culture media directly and observed 2X increase in signal compared with control experiment. This novel platform holds promise for the close monitoring of sPD-L1 level in human physiological fluids to evaluate the efficacy of PD-1/PD-L1 immunotherapy. © 2024 The Author(s)

关键词： Digital microfluidics

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Pan-cancer analysis of CDC7 in human tumors: Integrative multi-omics insights and discovery of novel marine-based inhibitors through machine learning and computational approaches

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Computers in Biology and Medicine 2025年 190卷 110044-110044页

作者： Saif, Ahmed Islam, Md. Tarikul Raihan, Md. Obayed Yousefi, Niloofar Rahman, Md. Ajijur Faridi, Hafeez Hasan, Al Riyad Hossain, Mirza Mahfuj Saleem, Rasha Mohammed Albadrani, Ghadeer M. Al-Ghadi, Muath Q. Ahasan Setu, Md. Ali Kamel, Mohamed Abdel-Daim, Mohamed M. Aktaruzzaman, Md. Department of Pharmacy Faculty of Science University of Rajshahi Rajshahi6205 Bangladesh Department of Genetic Engineering and Biotechnology Faculty of Biological Science and Technology Jashore University of Science and Technology Jashore7408 Bangladesh Jashore7408 Bangladesh Department of Pharmaceutical Sciences College of Health Sciences and Pharmacy Chicago State University ChicagoIL United States Department of Industrial Engineering and Management Systems University of Central Florida USA OrlandoFL United States Department of Pharmacy Faculty of Biological Science and Technology Jashore University of Science and Technology Jashore7408 Bangladesh Department of Computer Science and Engineering Faculty of Engineering and Technology Jashore University of Science and Technology Jashore7408 Bangladesh Department of Laboratory Medicine Faculty of Applied Medical Sciences Al-Baha University Al-Baha65431 Saudi Arabia Department of Biology College of Science Princess Nourah bint Abdulrahman University 84428 Riyadh11671 Saudi Arabia Department of Zoology College of Science King Saud University P.O. Box 2455 Riyadh11451 Saudi Arabia Department of Microbiology Faculty of Biological Science and Technology Jashore University of Science and Technology Jashore7408 Bangladesh Department of Medicine and Infectious Diseases Faculty of Veterinary Medicine Cairo University Giza12211 Egypt Department of Pharmaceutical Sciences Pharmacy Program Batterjee Medical College P.O. Box 6231 Jeddah21442 Saudi Arabia Pharmacology Department Faculty of Veterinary Medicine Suez Canal University Ismailia41522 Egypt

Cancer remains a significant global health challenge, with the Cell Division Cycle 7 (CDC7) protein emerging as a potential therapeutic target due to its critical role in tumor proliferation, survival, and resistance. However, a comprehensive analysis of CDC7 across multiple cancers is lacking, and existing therapeutic options have come with limited clinical success. The aim of this is to integrate a comprehensive pan-cancer analysis of CDC7 with the identification of novel marine-derived inhibitors, bridging the understanding of CDC7's role as a prognostic biomarker and therapeutic target across diverse cancer types. In this study, we conducted a pan-cancer analysis of CDC7 across 33 tumor types using publicly available datasets to evaluate its expression, genetic alterations, immune interactions, survival, and prognostic significance. Additionally, a marine-derived compound library of 31,492 molecules was screened to identify potential CDC7 inhibitors using chemoinformatics and machine learning. The top candidates underwent rigorous evaluations, including molecular docking, pharmacokinetics, toxicity, Density Functional Theory (DFT) calculations, and Molecular Dynamics (MD) simulations. The findings revealed that CDC7 is overexpressed in several cancers and is associated with poor survival outcomes and unfavorable prognosis. Enrichment analysis linked CDC7 to critical DNA replication pathways, while its role in modulating tumor-immune interactions highlighted its potential as a target for immunotherapy. Among all tested compounds, Tetrahydroaltersolanol D (CMNPD21999) exhibited the strongest binding affinity and stability, along with better drug-likeness and zero toxicity. These attributes highlight its potential as a promising drug candidate for CDC7 inhibition and future cancer treatment development. Furthermore, additional in vitro and in vivo studies are required to confirm the effectiveness of this drug candidate against the CDC7 protein. © 2025

关键词： Gene expression

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Generative adversarial networks applied to gene expression analysis: An interdisciplinary perspective

Computational and Systems Oncology

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Computational and Systems Oncology 2023年第3期3卷

作者： Ai, Xusheng Smith, Melissa C Feltus, Frank Alex Electrical and Computer Engineering Department Clemson University Clemson SC United States Department of Genetics and Biochemistry Biomedical Data Science & Informatics Program Clemson Center for Human Genetics Clemson University Clemson SC United States

The remarkable flexibility and adaptability of generative adversarial networks (GANs) have led to the proliferation of its models in bioinformatics research. Proteomic and transcriptomic profiles have been shown to be promising methods for discovering and identifying disease biomarkers. However, those analyses were performed by trained human examiners making the process tedious, time consuming, and hard to standardize. With the development of GANs, it is now possible to reduce computational costs and human time for bioinformatics analysis to produce effective biomarkers. Moreover, GANs help address the lack of phenotypic state transitional gene expression data as well as avoid protected human data constraints by generating RNA sequencing (RNA-seq) data from random vectors. The purpose of this review is to summarize the use of GAN approaches and techniques to augment RNA-seq expression data and identify clinically useful biomarkers. We compare different studies that use different types of GAN models to examine the biomarkers. Also, we identify research gaps and challenges that apply GANs to bio-informatics. Finally, we propose potential directions for future research. © 2023 The Authors. Computational and Systems Oncology published by Wiley Periodicals LLC.

关键词： biomarkers data augmentation generative adversarial network RNA sequencing

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Quantification of transient evoked otoacoustic emissions by sample entropy to assess cochlear symptoms (Hearing and Tinnitus) in Meniere's disease

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Applied Acoustics 2023年第1期212卷

作者： Fang, Jui Liu, Yi-Wen Chen, Yi-Wen Shih, Tzu-Ching Yao, Chun-Hsu Tsai, Chon-Haw Tyler, Richard S. Hsu, Alan Wang, Tang-Chuan x-Dimension Center for Medical Research and Translation China Medical University Hospital Taichung City Taiwan Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan Graduate Institute of Biomedical Sciences China Medical University Taichung City Taiwan Department of Biomedical Imaging and Radiological Science China Medical University Taichung City Taiwan School of Medicine College of Medicine China Medical University Taichung City Taiwan Department of Otolaryngology University of Iowa Iowa CityIA United States Department of Otorhinolaryngology - Head and Neck Surgery China Medical University Hsinchu Hospital Zhubei City Taiwan Master Program for Biomedical Engineering College of Biomedical Engineering China Medical University Taichung City Taiwan

The deteriorations of Meniere's disease (MD) cochlear symptoms (i.e., hearing loss and tinnitus) are progressive. We proposed sample entropy (SampEn) of transiently evoked otoacoustic emission (TEOAE) for quantitative assessment of MD cochlear symptoms without subject-dependent variations and system-dependent differences to prevent impacts of MD cochlear symptoms on life qualities of patients. This cross-sectional study based in a single center investigated 1) the preferred parameters for estimation of TEOAE SampEn and 2) resulting performances in diagnosing of MD cochlear symptoms. Nineteen normal (38 ears) and 29 (29 ears) unilateral definitive MD were recruited between June 2021 and March 2022. Hearing loss and tinnitus of MD were measured by pure-tone audiometry and described by chief complaint, respectively. TEOAE SampEn were estimated using different parameters of data size N = 772, template length m from 1 to 9 and similarity tolerance r from 0.1 to 1. Areas under receiver operating characteristic curves (AUROCs) were used to evaluate the performances of TEOAE SampEn in diagnosing MD cochlear symptoms. In terms of result, TEOAE SampEn based on the parameters of (N = 772, m = 2, r = 0.2) resulted in the maximum AUROCs = 0.7732 and 0.8421 in diagnosing MD hearing loss and tinnitus, respectively. In conclusion, TEOAE SampEn provides good performances and demonstrates great potential of assessment for MD cochlear symptoms. In future, recruitment of more participants, especially MD with tinnitus only without hearing loss, and other OHC-related disease, is necessary to further support the findings of this study. © 2023 The Author(s)

关键词： Audition

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