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SSRN 2023年

作者： Soares, Stephanie Dias dos Santos, Orquídea Vasconcelos da Conceição, Leyvison Rafael Vieira Costi, Hilton Túlio Júnior, José Otávio Carrera Silva do Nascimento, Francisco das Chagas Alves Pena, Rosinelson da Silva Graduate Program in Food Science and Technology Federal University of Pará Belém Brazil Faculty of Nutrition Institute of Health Sciences Federal University of Pará Belém Brazil Faculty of Chemistry Institute of Exact and Natural Sciences Federal University of Pará Belém Brazil Emílio Goeldi Museum Coordination of Earth Sciences and Ecology Belém Brazil Faculty of Pharmacy Institute of Health Sciences Federal University of Pará Belém Brazil Faculty of Food Engineering Institute of Technology Federal University of Pará Belém Brazil

This study aimed to submit the albino peach palm to the cooking and drying processes, and characterize the raw pulp (RP), cooked pulp (CP), raw pulp flour (RPF), and cooked pulp flour (CPF). The product's chemical composition, bioactive compounds, and physical-chemical, color, thermal, morphological, and functional-technological properties were evaluated. The proximate composition showed that carbohydrates were the main constituents of all products. The cooking process increased the moisture content of the pulp but decreased its other contents. The colorimetric parameters indicated a significant browning. After cooking, the total phenolic compounds and ascorbic acid content decreased in the pulp. The RPF and CPF presented different thermogravimetric behaviors. The spectral patterns in the infrared region showed characteristic bands of organic compounds which are present in the structure of starches. Scanning electron microscopy showed amyloplast and fiber bundles with starches in the RP and gelatinized starch granules in the CP and CPF. The RPF presented small and heterogeneous starch granules with isolated amyloplast. The RPF and CPF showed different granulometric patterns and technological indices. The results indicated that pulp and flour from the pulp of albino peach palms can be exploited by the food, pharmaceutical, and biotechnological industries. © 2023, The Authors. All rights reserved.

关键词： Fruits

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NTRK3 exhibits a pro-oncogenic function in upper tract urothelial carcinomas

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Kaohsiung Journal of Medical Sciences 2024年第5期40卷 445-455页

作者： Lim, Lee-Moay Lee, Yi-Chen Lin, Ting-Wei Hong, Zi-Xuan Hsu, Wei-Chi Ke, Hung-Lung Hwang, Daw-Yang Chung, Wen-Yu Li, Wei-Ming Lin, Hui-Hui Kuo, Hung-Tien Huang, A-Mei Graduate Institute of Clinical Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Division of Nephrology Department of Internal Medicine Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Graduate Institute of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Department of Anatomy School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Department of Urology School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Department of Urology Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan Department of Urology Kaohsiung Municipal Ta-Tung Hospital Kaohsiung Medical University Kaohsiung Taiwan National Institute of Cancer Research National Health Research Institute Tainan Taiwan Department of Computer Science and Information Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Urology Ministry of Health and Welfare Pingtung Hospital Pingtung Taiwan Department of Medical Research Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan Doctoral Degree Program in Toxicology College of Pharmacy Kaohsiung Medical University Kaohsiung Taiwan Department of Biochemistry School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Research Center for Environmental Medicine Kaohsiung Medical University Kaohsiung Taiwan

Neurotrophic receptor tyrosine kinase 3 (NTRK3) has pleiotropic functions: it acts not only as an oncogene in breast and gastric cancers but also as a dependence receptor in tumor suppressor genes in colon cancer and neuroblastomas. However, the role of NTRK3 in upper tract urothelial carcinoma (UTUC) is not well documented. This study investigated the association between NTRK3 expression and outcomes in UTUC patients and validated the results in tests on UTUC cell lines. A total of 118 UTUC cancer tissue samples were examined to evaluate the expression of NTRK3. Survival curves were generated using Kaplan–Meier estimates, and Cox regression models were used for investigating survival outcomes. Higher NTRK3 expression was correlated with worse progression-free survival, cancer-specific survival, and overall survival. Moreover, the results of an Ingenuity Pathway Analysis suggested that NTRK3 may interact with the PI3K-AKT-mTOR signaling pathway to promote cancer. NTRK3 downregulation in BFTC909 cells through shRNA reduced cellular migration, invasion, and activity in the AKT-mTOR pathway. Furthermore, the overexpression of NTRK3 in UM-UC-14 cells promoted AKT-mTOR pathway activity, cellular migration, and cell invasion. From these observations, we concluded that NTRK3 may contribute to aggressive behaviors in UTUC by facilitating cell migration and invasion through its interaction with the AKT-mTOR pathway and the expression of NTRK3 is a potential predictor of clinical outcomes in cases of UTUC. © 2024 The Authors. The Kaohsiung Journal of Medical Sciences published by John Wiley & Sons Australia, Ltd on behalf of Kaohsiung Medical University.

关键词： AKT-mTOR pathway neurotrophic receptor tyrosine kinase 3 (NTRK3) prognosis tropomyosin-related kinase (TrK) upper tract urothelial carcinoma (UTUC)

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Contour Detection from Ultrasound Kidney Images with A Coarse-to-Fine Approach

Contour Detection from Ultrasound Kidney Images with A Coars...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Peng, Tao Gu, Yidong Xu, Yanqing Wang, Caishan Zhang, Lei Cai, Jing School of Future Science and Engineering Soochow University Suzhou China UT Southwestern Medical Center Department of Radiation Oncology DallasTX United States The Affiliated Suzhou Hospital of Nanjing Medical University Department of Medical Ultrasound Suzhou Municipal Hospital Jiangsu Suzhou China University of Texas Southwestern Medical Center McDermott Center for Human Growth and Development DallasTX United States The Second Affiliated Hospital of Soochow University Department of Ultrasound Suzhou China Duke Kunshan University Graduate Program of Medical Physics and Data Science Research Center Jiangsu Kunshan China The Hong Kong Polytechnic University Department of Health Technology and Informatics Hong Kong Hong Kong

ISBN: (纸本)9798350337020

Ultrasound kidney image segmentation presents significant challenges due to missing or ambiguous boundaries. In this study, we introduce a coarse-to-refinement approach incorporating four novel aspects. Firstly, we leverage the properties of a principal curve (PC) to automatically fine-tune the curve shape and employ a neural network's learning ability to reduce model error. Secondly, a deep fusion learning network is utilized for the coarse segmentation step, incorporating a parallel architecture to enhance deep-learning performance. Thirdly, addressing the limitation of standard PC-based methods in determining the number of vertices automatically, we propose an automatic searching polygon tracking method using a mean shift clustering-based approach to replace the projection and vertex extension step in standard PC-based methods. Lastly, we develop an explainable mathematical map function for the kidney contour, as denoted by the neural network output (i.e., optimized vertices), which aligns well with the ground truth contour. We conducted various experiments to evaluate our method's performance, demonstrating its effectiveness in ultrasound kidney image segmentation. © 2023 IEEE.

关键词： Artificial intelligence Explainable mathematical model Ultrasound kidney segmentation

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Effects of Mobile health Care App "Asmile" on Physical Activity of 80,689 Users in Osaka Prefecture, Japan: Longitudinal Observational Study

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Journal of medical Internet research 2025年 27卷 e65943页

作者： Asuka Oyama Kenshiro Taguchi Hiroe Seto Reiko Kanaya Jun'ichi Kotoku Miyae Yamakawa Hiroshi Toki Ryohei Yamamoto Health and Counseling Center The University of Osaka Toyonaka Japan. Graduate Degree Program of Health Data Science Teikyo University Tokyo Japan. Graduate School of Human Sciences The University of Osaka Suita Japan. Division of Health Sciences Graduate School of Medicine The University of Osaka Suita Japan. Graduate School of Medical Care and Technology Teikyo University Tokyo Japan. Department of Nephrology Graduate School of Medicine The University of Osaka Suita Japan. Laboratory of Behavioral Health Promotion Department of Health Promotion Graduate School of Medicine The University of Osaka Suita Japan. Institute for Sports and Global Health The University of Osaka Suita Japan.

BACKGROUND:Lifestyle-related diseases can be controlled by improving individuals' lifestyles; however, improving and maintaining a healthy lifestyle is difficult. Mobile health (mhealth) applications have recently attracted attention as tools for maintaining and improving health, and their use may also increase physical activity. OBJECTIVE:This study aimed to verify the effect of registration in Asmile, an mhealth application provided by the Osaka Prefectural Government, on step counts using a Causal Impact approach based on the step count data recorded in the Asmile application. METHODS:This observational study included Osaka residents aged 20-79 years, newly registered to Asmile, between the fiscal years 2020 and 2023. Of these, 80,689 participants with step count records for 4 weeks before and after the day they registered to Asmile were included in the analysis. We used daily step counts that were automatically transferred from a standard smartphone health care app into Asmile. We used a Causal Impact model to estimate the increase in step count after registration to Asmile. RESULTS:Of the 80,689 participants analyzed, 38.5% (31,082/80,689) were men, and the mean age was 51.6 (SD 13.2) years. The mean step count before registration was 5923 (SD 4860) steps per day, with the highest proportion of new users registered in spring (38,389/80,689, 47.6%) and in fiscal year 2020 (34,491/80,689, 42.7%). The analysis revealed that the effect of Asmile registration on step counts was 360 steps (95% CI 331-389) per day and 10,041 steps (95% CI 9632-10,450) over 4 weeks. Stratified analysis showed that the impact of increased step count was more pronounced in younger groups and groups with fewer step counts before registration. Conversely, the effect of registration on step count was relatively minor in the groups registered in summer or winter. CONCLUSIONS:This study demonstrates increased physical activity among users registered with the Asmile app. These findings suggest

关键词： Causal Impact Causal Inference Japan Osaka app apps exercise healthy lifestyle lifestyle-related disease mhealth mobile health mobile phone observational study physical activity smartphone step counts

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Hybrid Intelligent-Annotation Organ Segmentation on Medical Datasets

Hybrid Intelligent-Annotation Organ Segmentation on Medical ...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Peng, Tao Zhao, Jing Gu, Yidong Di, Gongye Zhang, Lei Cai, Jing School of Future Science and Engineering Soochow University Suzhou China Ut Southwestern Medical Center Department of Radiation Oncology DallasTX United States Tsinghua University Affiliated Beijing Tsinghua Changgung Hospital Department of Ultrasound Beijing China The Affiliated Suzhou Hospital of Nanjing Medical University Suzhou Municipal Hospital Department of Medical Ultrasound Jiangsu Suzhou China The Affiliated Taizhou People's Hospital of Nanjing Medical University Department of Ultrasonic Taizhou China Duke Kunshan University Graduate Program of Medical Physics Data Science Research Center Jiangsu Kunshan China The Hong Kong Polytechnic University Department of Health Technology and Informatics Hong Kong

ISBN: (纸本)9798350337020

Ultrasound image segmentation is crucial for early disease detection and treatment planning but remains a challenging task due to the low contrast of organ boundaries and varying image quality. Current methods often require manual intervention or have limited accuracy. In this paper, we propose a novel hybrid framework that combines an automatic option polygon segment (AOPS) algorithm and a distributed- and memory-based evolution (DME) algorithm for precise ultrasound organ segmentation. Our pipeline consists of two cascaded stages: (1) a coarse segmentation step using the AOPS algorithm, which determines the number of vertices/clusters without human intervention, and (2) a refinement step using the DME algorithm to hunt for the optimal neural network, which is then used to represent a smooth, explainable mathematical expression of the organ boundary. We employ the fractional backpropagation learning network with L2 regularization (FBLN) for training and use the scaled exponential linear unit (SELU) activation function to address the vanishing gradient problem. This is a new attempt such a hybrid framework is applied to ultrasound organ segmentation tasks, and it demonstrates significant contributions in terms of accuracy, smoothness, and computational efficiency. © 2023 IEEE.

关键词： distributed-evolution learning network Multi-organs segmentation principal curve SEL U-based explainable mathematical model ultrasound

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Revisiting some overlooked registered Thai traditional medicine preparations: an alert to a regulatory affair

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Bulletin of the National Research Centre 2022年第1期46卷 1-9页

作者： Vimolmangkang, Sornkanok Rani, Dolly Prestwong, Naruemon Sutcharitchan, Chayanis Pakdeesattayapong, Duangkamol Department of Pharmacognosy and Pharmaceutical Botany Faculty of Pharmaceutical Sciences Chulalongkorn University Bangkok Thailand Center of Excellence in Plant Produced Pharmaceuticals Faculty of Pharmaceutical Sciences Chulalongkorn University Bangkok Thailand Graduate Program in Pharmaceutical Science and Technology Faculty of Pharmaceutical Sciences Chulalongkorn University Bangkok Thailand Herbal Products Division Food and Drug Administration Thailand Ministry of Public Health Nonthaburi Thailand

This study evaluated the heavy metal identity and content of registered Thai Traditional medicine (TTM) preparations in Thailand to ensure consumer safety. Both qualitative and quantitative information about the elemental composition of the heavy metal content in each TTM crude drug and the heavy metal content in some registered TTM preparations in Thailand was performed. Seven kinds of mineral-based TTM crude drugs, namely realgar, orpiment, Chinese powder, Sen, vermilion, natural vermilion, and cinnabar, were analyzed with X-ray diffraction and scanning electron microscopy and energy-dispersive spectroscopy techniques to determine the type of metal and elemental composition to confirm their chemical formulas. Furthermore, the number of heavy metals, such as arsenic (As), lead (Pb), and mercury (Hg), was in three samples of realgar-containing preparations; one sample of Sen-containing preparation, and eight samples of cinnabar-containing preparations. Heavy metals were determined with inductively coupled plasma-optical emission spectrometry. It was observed that realgar and orpiment consisted of arsenic sulfide (AsS) and arsenic trisulfide (As2S3), respectively. Both crude drugs contained approximately 50% of As. Vermilion, natural vermilion, and cinnabar consisted of mercuric sulfide (HgS), with Hg accounting for approximately 66%. Sen consisted of Pb (II, IV) oxide (Pb3O4) with an approximate Pb percentage of 80%. However, Pb was absent in Chinese powder and consisted mainly of calcium carbonate (CaCO3). A traditional detoxification procedure can reduce the amount of As and Hg in processed crude drugs by at least 20%. Pb was higher in some TTM preparations, and no CaCO3 was detected in Chinese powder. Our results raise concerns on both safety and efficacy to consumers and alert public health policymakers that they should implement regulations so that the quality (authenticity) and quantity of elemental medicine used in traditional medicine are correctly labeled a

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Extreme temperature increases the risk of COPD morbimortality: A systematic review and meta-analysis

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Science of the Total Environment 2025年 958卷 178087页

作者： Tran, Huan Minh Tsai, Feng-Jen Lee, Kang-Yun Wang, Yuan-Hung Yang, Feng-Ming Ho, Shu-Chuan Bui, Hanh Thi My Hoang, Linh Nhat Nguyen Bui, Linh Thi My Ho, Kin-Fai Chung, Kian Fan Chuang, Kai-Jen Chuang, Hsiao-Chi Ph.D. Program in Global Health and Health Security College of Public Health Taipei Medical University Taipei Taiwan Faculty of Public Health Da Nang University of Medical Technology and Pharmacy Da Nang Viet Nam Division of Pulmonary Medicine Department of Internal Medicine Shuang Ho Hospital Taipei Medical University New Taipei City Taiwan Division of Pulmonary Medicine Department of Internal Medicine School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Graduate Institute of Clinical Medicine College of Medicine Taipei Medical University Taipei Taiwan Department of Medical Research Shuang Ho Hospital Taipei Medical University New Taipei City Taiwan School of Respiratory Therapy College of Medicine Taipei Medical University Taipei Taiwan Da Nang Center for Disease Control Da Nang Viet Nam The Jockey Club School of Public Health and Primary Care The Chinese University of Hong Kong N.T. Shatin Hong Kong National Heart and Lung Institute Imperial College London London United Kingdom School of Public Health College of Public Health Taipei Medical University Taipei Taiwan Department of Public Health School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Cell Physiology and Molecular Image Research Center Wan Fang Hospital Taipei Medical University Taipei Taiwan

Introduction: This systematic review examines how extreme temperatures impact chronic obstructive pulmonary disease (COPD) morbidity and mortality, focusing on identifying vulnerable subpopulations. Methods: We conducted a systematic literature search from January 1, 2000, to November 6, 2024, across databases like PubMed, MEDLINE and EMBASE, Web of Science, and Scopus, focusing on observational studies that quantitatively defined extreme temperatures and their impacts on COPD morbidity and mortality. Out of 3140 records, 25 studies met the inclusion criteria. We extracted data on study characteristics, effect estimates, and confounders, employing methods to assess the risk of bias and synthesize results. Results: We observed that extreme heat increased the relative risk (RR) for COPD morbimortality by 1.16-fold (95 % CI: 1.08–1.26;p © 2024 Elsevier B.V.

关键词： Extreme weather

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Computer-Aided System of the Mandibular Cortical Bone Porosity Assessment on Digital Panoramic Radiographs

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European Journal of Dentistry 2022年第2期17卷 464-471页

作者： Eha R. Astuti Agus Z. Arifin Rarasmaya Indraswari Ramadhan H. Putra Nastiti F. Ramadhani Berty Pramatika Department of Dentomaxillofacial Radiology Faculty of Dental Medicine Airlangga University Surabaya Indonesia Department of Informatics Faculty of Intelligent Electrical and Information Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Information Systems Faculty of Intelligent Electrical and Information Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia Graduate Student of Dental Health Sciene Program Faculty of Dental Medicine Airlangga University Surabaya Indonesia Universitas Brawijaya Hospital Brawijaya University Malang Indonesia

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Filtering motion signals from Microsoft Kinect® in the context of stroke rehabilitation

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Research on Biomedical Engineering 2019年第3-4期35卷 265-270页

作者： Moreira, Gabrielly M. Giovanini, Luiz H. F. de Castro, Marcos P. R. Nogueira, Guilherme N. Boumer, Tatiane C. Manffra, Elisangela F. Graduate Program in Health Technology Pontifícia Universidade Católica do Paraná Curitiba Brazil Graduate Program in Computer Science Pontifícia Universidade Católica do Paraná Curitiba Brazil Undegraduate Program on Digital Games of Pontifícia Universidade Católica do Paraná Curitiba Brazil

Purpose: The Microsoft Kinect® sensor has been employed for developing serious games and for biomechanics analysis. Both applications, when combined in the context of motor rehabilitation, might provide relevant data for therapists. However, the reliability of clinical data obtained with Kinect® is affected by filtering parameters which should be chosen according to spectral characteristics of the signals. In this paper we aim at determining the spectral characteristics of kinematics data collected with Kinect® during a serious game and to suggest adequate filtering. Methods: The motor tasks of lateral trunk inclination, trunk rotation, and shoulder abduction performed with heading, ski, and goalkeeper games originated 45 time series derived from 5 healthy people and 87 time series of 4 people with stroke. Time series were analyzed using the Fourier analysis and empirical mode decomposition (EMD). A residual analysis was performed to determine the optimal cutoff frequencies of the fourth-order low-pass Butterworth filters. Results: Fourier and EMD analyses evidenced that the highest spectral power for header and goalkeeper tasks is below 3 Hz and for skiing, it is below 0.8 Hz. The ideal cutoff frequencies were around 3 Hz and 5 Hz and differed between healthy and stroke groups. The range of motion was affected by the cutoff frequencies. Conclusion: The signals captured by Kinect® have the main spectral components at lower frequencies and should be filtered at cutoff frequencies below 6 Hz. We recommend including the determination the impact of signal processing on clinical indicators in the workflow when developing a serious game for rehabilitation. © 2019, Sociedade Brasileira de Engenharia Biomedica.

关键词： Cutoff frequency

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COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2

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Briefings in Bioinformatics 2023年第5期24卷 bbad280-bbad280页

作者： Lim, Hendrick Gao-Min Fann, Yang C Lee, Yuan-Chii Gladys Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University Taipei 11031 Taiwan Department of Medical Research Tzu Chi Hospital Indonesia Pantai Indah Kapuk Greater Jakarta 14470 Indonesia It and Bioinformatics Program Division of Intramural National Institute of Neurological Disorders and Stroke National Institutes of Health Bethesda 20892 MD United States

Implementing a specific cloud resource to analyze extensive genomic data on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a challenge when resources are limited. To overcome this, we repurposed a cloud platform initially designed for use in research on cancer genomics (https://***) to enable its use in research on SARS-CoV-2 to build Cloud Workflow for Viral and Variant Identification (COWID). COWID is a workflow based on the Common Workflow Language that realizes the full potential of sequencing technology for use in reliable SARS-CoV-2 identification and leverages cloud computing to achieve efficient parallelization. COWID outperformed other contemporary methods for identification by offering scalable identification and reliable variant findings with no false-positive results. COWID typically processed each sample of raw sequencing data within 5 min at a cost of only US$0.01. The COWID source code is publicly available (https://***/hendrick0403/COWID) and can be accessed on any computer with Internet access. COWID is designed to be user-friendly;it can be implemented without prior programming knowledge. Therefore, COWID is a time-efficient tool that can be used during a pandemic. © 2023 Published by Oxford University Press.

关键词： cloud repurposing cloud workflow COVID-19 Illumina sequencing parallel computation SARS-CoV-2

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