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CHITOSAN-COLLAGEN COMPOSITE SCAFFOLDS FOR GROWTH DIRECTION GUIDANCE OF PC12 AXONS

CHITOSAN-COLLAGEN COMPOSITE SCAFFOLDS FOR GROWTH DIRECTION G...

ASME 2024 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2024

作者： Tsai, Po-Yu Lin, Ying-Ting Wang, Gou-Jen Graduate Institute of Biomedical Engineering National Chung-Hsing University Taichung Taiwan PhD Program in Tissue Engineering and Regenerative Medicine National Chung-Hsing University Taichung Taiwan Department of Mechanical Engineering Graduate Institute of Biomedical Engineering National Chung-Hsing University Taichung Taiwan

ISBN: (纸本)9780791888421

In this study, nerve conduits of chitosan and collagen composites with biocompatibility and biodegradability were fabricated. The effects of material composition and surface morphology on the axonal growth and directionality of rat epinephric pheochromocytoma PC12 were investigated. The cells were separated by a PDMS structure to simulate nerve injury, and the growth of axons of PC12 cells was observed under the separation of large gaps. At the same time, mitochondria extracted from osteosarcoma cybrid cells (C2-GFP) were added to the culture to investigate the effect of healthy mitochondria on axon differentiation and growth. The experimental results showed that the chitosan-collagen composite film can promote the growth of PC12 axons more effectively than the pure chitosan film. Cell culture results at different groove widths also showed that smaller grooves resulted in more axon numbers and longer axon lengths. Nerve injury simulation experiments showed that the nerve repair could be almost completed after 12 days of culture. Copyright © 2024 by ASME.

关键词： Mitochondria

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A keratinocyte-adipocyte signaling loop is reprogrammed by loss of BTG3 to augment skin carcinogenesis

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Cell Death and Differentiation 2024年第8期31卷 970-982页

作者： Cheng, Yu-Che Acedera, Jack Dalit Li, Yi-Ju Shieh, Sheau-Yann Institute of Biomedical Sciences Academia Sinica Taipei Taiwan Taiwan International Graduate Program in Molecular Medicine National Yang Ming Chiao Tung University and Academia Sinica Taipei Taiwan

Obesity is endemic to many developed countries. Overweight or obesity is associated with an increased risk of developing cancer. Dysfunctional adipose tissue alters cancer cell proliferation and migration;however, whether and how neoplastic epithelial cells communicate with adipose tissue and the underlying mechanism are less clear. BTG3 is a member of the anti-proliferative BTG/Tob family and functions as a tumor suppressor. Here, we demonstrated that BTG3 levels are downregulated in basal cell carcinoma and squamous cell carcinoma compared to normal skin tissue, and Btg3 knockout in mice augmented the development of papilloma in a mouse model of DMBA/TPA-induced skin carcinogenesis. Mechanistically, BTG3-knockout keratinocytes promoted adipocyte differentiation mainly through the release of IL1α, IL10, and CCL4, as a result of elevated NF-κB activity. These adipocytes produced CCL20 and FGF7 in a feedback loop to promote keratinocyte migration. Thus, our findings showcased the role of BTG3 in guarding the interplay between keratinocytes and adjacent adipocytes, and identified the underlying neoplastic molecular mediators that may serve as possible targets in the treatment of skin cancer. (Figure presented.). © The Author(s) 2024.

关键词： Cancer microenvironment Tumour-suppressor proteins

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Picrasidine I Regulates Apoptosis in Melanoma Cell Lines by Activating ERK and JNK Pathways and Suppressing AKT Signaling

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Environmental Toxicology 2024年第12期39卷 5309-5320页

作者： Shieu, Mu-Kuei Lin, Chia-Chieh Ho, Hsin-Yu Lo, Yu-Sheng Chuang, Yi-Ching Hsieh, Ming-Ju Department of Dermatology Changhua Christian Hospital Changhua Taiwan Oral Cancer Research Center Changhua Christian Hospital Changhua Taiwan Graduate Institute of Clinical Medicine College of Medicine National Chung Hsing University Taichung Taiwan Doctoral Program in Tissue Engineering and Regenerative Medicine College of Medicine National Chung Hsing University Taichung Taiwan Graduate Institute of Biomedical Sciences China Medical University Taichung Taiwan

World Health Organization data indicate a continuous increase in melanoma incidence, with metastatic melanoma characterized by poor prognosis and drug resistance. The exploration of therapeutics derived from natural products remains an active area of in vitro research. The aim of this study was to determine the antitumor effects of picrasidine I, a natural compound extracted from Picrasma quassioides, against two melanoma cell lines. We selected two metastatic melanoma cell lines, HMY-1 and A2058, for molecular studies, including Western blotting, 4′,6-diamidino-2-phenylindole staining, and flow cytometry. Picrasidine I demonstrated cytotoxic effects against the HMY-1 and A2058 melanoma cell lines. It induced cell cycle arrest in the sub-G1 phase and downregulated cell cycle–related proteins (e.g., cyclin A2, D1, cyclin-dependent kinases 4, and 6). In the intrinsic apoptosis pathway, picrasidine I activated proapoptotic proteins (e.g., Bax, Bak, t-Bid, BimL/S) and suppressed the expression of antiapoptotic proteins (e.g., Bcl-2, Bcl-xL), with an observed increase in the quantity of depolarized cells. In addition, the apoptotic effects of picrasidine I were linked to the activation of the c-Jun N-terminal kinase and extracellular signal-regulated kinase pathways and the inhibition of the protein kinase B signaling pathway. A human apoptosis array indicated claspin inhibition upon picrasidine I treatment, suggesting the potential involvement of picrasidine I in apoptosis and cell cycle regulation. Our findings suggest that picrasidine I has potential as a candidate for treating advanced melanoma, and thus these findings warrant further investigation. The modulation of claspin expression by picrasidine I could be investigated further as a potential biomarker to predict its efficacy in related to advanced stages of melanoma. © 2024 The Author(s). Environmental Toxicology published by Wiley Periodicals LLC.

关键词： Dermatology

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A Novel SERS Substrate Containing Silver Nanoparticle-Deposited Photoresist Microcone Array for Sensitive Biosensing

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IEEE Sensors Journal 2024年第2期24卷 1398-1404页

作者： Lin, Ying-Ting Wang, Sheng-Hsiang Tseng, Yu-Hsin Lin, Ze-Cheng Chen, Jyun-Tu Chang, Cheng-Chung Wang, Gou-Jen National Chung Hsing University Program in Tissue Engineering and Regenerative Medicine Taichung40227 Taiwan National Chung Hsing University Department of Mechanical Engineering Taichung40227 Taiwan Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung40227 Taiwan

In this study, we developed a novel surface-enhanced Raman scattering (SERS) substrate formed by depositing silver nanoparticles (AgNPs) on a silver thin film-coated photoresist (PR) microcone array. The semiconductor photolithographic process was adopted for fabricating the PR microcone array. The hotspot enhancement effect of the SERS substrates was optimized by adjusting the concentration of the trisodium citrate, which was used as a reducing agent and a stabilizing agent for the synthesis of AgNPs. Experimental results showed that the proposed SERS substrate could detect the indicating peaks of Rhodamine 6G (R6G) at a relatively low concentration of 10-12 M. A standard detection curve for HbA1c detection with a linear detection range of 5000-20000 ng/mL with good linearity of 0.994 and a limit of detection (LOD) of 850.2 ng/mL was further established by adding HbA1c agent to artificial blood to simulate a real environmental condition. Recovery rate detection experiments confirmed the reproducibility of the established standard detection curve. © 2001-2012 IEEE.

关键词： Silver nanoparticles

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Lung Nodule Analysis in CT Images: Deep Learning for Segmentation and Measurement 24

Lung Nodule Analysis in CT Images: Deep Learning for Segment...

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8th International Conference on Medical and Health informatics, ICMHI 2024

作者： Li, Ai-Hsien Adams Aruperes, Cristian Daniel Lai, Yen-Jun Chien, Ting-Ying Chiu, Yen-Ling Chan, Chien-Lung Division of Cardiology Far Eastern Memorial Hospital New Taipei TaiwanGraduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan TaiwanDepartment of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan TaiwanInnovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan Taiwan Department of Information Management Yuan Ze University Taoyuan Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan TaiwanGraduate Institute of Medicine Yuan Ze University Taoyuan Taiwan TaiwanDepartment of Medical Research Far Eastern Memorial Hospital New Taipei Taiwan Department of Radiology Far Eastern Memorial Hospital New Taipei Taiwan Department of Information Management Yuan Ze University Taoyuan Taiwan

ISBN: (纸本)9798400716874

In the realm of research, the global health challenge posed by lung cancer remains pronounced, contributing substantially to annual cancer-related fatalities. The critical imperative lies in the early identification of pulmonary nodules, frequently indicative of impending lung cancer, to enhance patient outcomes and diminish mortality rates. Computed Tomography (CT) imaging stands out as a pivotal diagnostic instrument for the timely detection of these nodules. The swift proliferation of medical imaging data has underscored the pressing necessity for precise and efficient methodologies dedicated to nodule segmentation and measurement. These approaches are crucial in assisting radiologists in their diagnostic and clinical decision-making endeavors. In this study, we introduced a thorough method for analyzing lung nodules, leveraging dataset from Far Eastern Memorial Hospital (FEMH) comprising original CT images and manually annotated ground truth masks obtained with the assistance of radiologists at FEMH. This dataset is utilized for the segmentation of nodules. We employed advanced deep learning models, specifically the U-Net architecture, identified as the optimal model through our training process. We made substantial progress in nodule segmentation, attaining an Intersection over Union (IoU) score of 0.824 and a Dice Coefficient of 0.903 for the FEMH dataset. Furthermore, our performance improved when utilizing the merged dataset comprising FEMH and Luna16, yielding an IoU score of 0.862 and a Dice Coefficient of 0.926. Luna16 has been extensively utilized in numerous studies related to nodule detection and segmentation. In the next phase of the study, the best-performing model from our segmentation phase was utilized to predict nodule masks on the merged dataset. Subsequently, we measured the size of each predicted nodule by comparing it with the size ground truth mask in millimeters. In detail, this study achieved the Pearson Correlation Coefficient (PCC) at 0.

关键词： Computerized tomography

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Brain age estimation:premise,promise,and problems

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Neural Regeneration Research 2025年第8期20卷 2313-2314页

作者： Jarrad Perron Ji Hyun Ko Graduate Program in Biomedical Engineering Price Faculty of EngineeringUniversity of ManitobaWinnipegMBCanada PrairieNeuro Research Centre Kleysen Institute for Advanced MedicineHealth Sciences CentreWinnipegMBCanada Department of Human Anatomy and Cell Science Rady Faculty of Health SciencesUniversity of ManitobaWinnipegMBCanada

Premise:The com bined effects of modern healthcare practices which prolong lifespan and declining birthrates have created unprecedented changes in age demographics worldwide that are especially pronounced in Japan,South Korea,Europe,and North *** old age is the most significant predictor of dementia,global healthcare systems must rise to the challenge of providing care for those with neurodegenerative disorders.

关键词： estimation providing birth

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Predicting Types of Urinary Crystals and Diameter Using Image Processing Techniques and Deep Learning Models 24

Predicting Types of Urinary Crystals and Diameter Using Imag...

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8th International Conference on Medical and Health informatics, ICMHI 2024

作者： Huang, Yu-Ju Tseng, Yi-Shiou Chen, Tzu-Jung Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Department of Surgery Far Eastern Memorial Hospital Graduate Institute of Medicine Yuan Ze University Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Kidney stones are primarily crystals formed from ion oversaturation in urine. Currently, the diagnosis of kidney stones involves experienced professionals manually interpreting images of urinary crystals under a microscope. In recent years, with the rapid development of artificial intelligence (AI), many researchers have proposed various methods to assist in diagnosis, hoping to improve medical quality. This study explored the application of AI in the medical field, aiming to automate the interpretation of urinary crystal images, such as red blood corpuscles (RBCs), calcium oxalate monohydrate (COM), calcium oxalate dihydrate octahedron (COD-OCT), calcium oxalate dihydrate dodecahedron (COD-DOD), debris, and others, and to use image processing techniques to classify urinary crystal types. This research is expected to assist medical personnel in quickly determining the categories of urinary crystals. Ultimately, our model achieved an F1-score of 0.93, indicating that this architecture has significant potential. © 2024 Copyright ACM.

关键词： Deep learning

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Enhanced Performance and Data Privacy in Lung Nodule Classification via Federated Deep Learning Approach 24

Enhanced Performance and Data Privacy in Lung Nodule Classif...

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2024 7th International Conference on Healthcare Service Management, ICHSM 2024

作者： Nguyen, Duc-Khanh Li, Ai-Hsien Adam Lai, Yen-Jun Chiu, Yen-Ling Phan, Dinh-Van Chien, Ting-Ying Chan, Chien-Lung Department of Information Management Yuan Ze University Taoyuan Taiwan Department of Statistics and Informatics University of Economics The University of Danang Danang Viet Nam Division of Cardiology Far Eastern Memorial Hospital New Taipei Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Radiology Far Eastern Memorial Hospital New Taipei Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Medical Research Far Eastern Memorial Hospital New Taipei Taiwan Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan ZDT Group- YZU Joint Research and Development Center for Big Data Taoyuan Taiwan Yuan Ze University Taoyuan Taiwan

ISBN: (纸本)9798400710162

This study explores the feasibility of deep learning for classifying nodule neoplasms, analyzing their performance on two openly available datasets, LUNGx SPIE, and LIDC-IDRI. These datasets offer valuable diversity in image quantity, quality, and malignancy annotation methodologies, posing a real-world challenge for effective model development. To handle the disparities in these diverse datasets, we aim to develop a robust classification model trained using federated learning. This decentralized approach allows model training across datasets without sharing patient data, preserving privacy and overcoming data fragmentation. Our experiments demonstrate that federated learning enables the development of a robust and superior deep learning model compared to individual models trained on limited data. This combination of deep learning, and federated learning holds immense promise for nodule neoplasm classification and can significantly improve patient care and outcomes. © 2024 Copyright held by the owner/author(s).

关键词： Federated learning

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Toward a Patient-Centered Care Supporting System: Integration of Multidisciplinary Health Records in Breast Cancer Care

Toward a Patient-Centered Care Supporting System: Integratio...

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34th Medical informatics Europe Conference, MIE 2024

作者： Sugiyama, Atsuko Utsunomiya, Kazuki Okumiya, Hayato Fujimoto, Katsuhiko Shimomura, Yuka Sanuki, Masaru Kume, Keitaro Yano, Takahiro Kagawa, Rina Bando, Hiroko Canon Medical Systems Corporation Tochigi Otawara Japan Graduate School of Biomedical Engineering Tohoku University Miyagi Sendai Japan Laboratory of Mathematical Informatics in Medicine University of Tsukuba Ibaraki Tsukuba Japan Department of Biomedical Informatics and Management University of Tsukuba Hospital Ibaraki Tsukuba Japan Department of Breast-Thyroid-Endocrine Surgery Institute of Medicine University of Tsukuba Ibaraki Tsukuba Japan

ISBN: (纸本)9781643685335

An important paradigm shift within healthcare is the shift toward patient-centered care (PCC). Multidisciplinary team meetings (MDTM) are considered essential for PCC, despite being considered time-consuming and expensive. Patient-centered information (PCI) is known to improve the quality of care. This study investigated where and how the PCI of multidisciplinary professionals' health records exists, and to explore the possibility of a sustainable PCC-supporting healthcare system. We performed an exploratory pilot study of the patient records of three patients with breast cancer. We observed that PCI was documented throughout the care pathway in the cases examined. However, we also found that these data were fragmented and scattered across various medical records, and they were also from different point of views and patient care perspectives. PCI was founded to be less accessible than traditional medical records and was even hard to find using a manual search. We therefore propose that preparing PCI for MDTM may be one of the obvious burdens for healthcare professionals (HPs). We do however believe that integrating PCI from multiple professionals' records likely plays an important function in a shift towards PCC and serves to improve not only the quality of care but also the HPs' experiences without additional burden and could contribute to a more sustainable health care system. © 2024 The Authors.

关键词： Electronic health record

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Peripheral pulse harmonic analysis and its clinical application: A systematic review

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Journal of Traditional and Complementary medicine 2024年第2期14卷 223-236页

作者： Hsiao, Kun-Yuan Kang, Jiunn-Horng Wu, Yeong-Shing Chang, Hen-Hong Yang, Cheng-Ta Institute of Allied Health Sciences National Cheng Kung University Tainan Taiwan Department of Chinese Medicine Cishan Hospital Ministry of Health and Welfare Kaohsiung Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Graduate Institute of Nanomedicine and Medical Engineering College of Biomedical Engineering Taipei Medical University Taipei Taiwan Department of Physical Medicine and Rehabilitation Taipei Medical University Hospital Taipei Taiwan Graduate Institute of Integrated Medicine College of Chinese Medicine and Chinese Medicine Research Center China Medical University Taichung Taiwan Department of Chinese Medicine China Medical University Hospital Taichung Taiwan Department of Psychology National Cheng Kung University Tainan Taiwan Graduate Institute of Mind Brain and Consciousness Taipei Medical University Taipei Taiwan Graduate Institute of Health and Biotechnology Law Taipei Medical University Taipei City Taiwan

Introduction: Pulse harmonic analysis is a quantitative and objective methodology within traditional Chinese medicine (TCM) used to evaluate pulse characteristics. However, interpreting pulse wave data is challenging due to its inherent complexity. This study aims to provide a comprehensive review and comparison of existing human pulse wave harmonic analysis methods to elucidate their patterns and characteristics. Methods: A systematic review of clinical research reports published from 1990 to 2021 was conducted, focusing on variations in harmonic characteristics across different medical conditions and physiological states. Keyword searches included terms related to analysis methods (e.g., “Pulse Spectrum,” "harmonic analysis," “harmonic index”) and measured indicators (e.g., “vascular response,” "PPG," “Photoplethysmography,” "aortic," “arterial,” "blood pressure"). Supplementary research using PubMed's Mesh terms specifically targeted “Pulse wave analysis” within the methods and statistical analysis domain. Articles were filtered based on predefined criteria, including human participants and research related to pulse pressure or vascular volume changes. Conference papers, animal studies, and irrelevant research were excluded, with literature evaluation scales selected based on the retrieved research reports. Results: Initially, 6487 research reports were identified, and after screening, 50 reports were included in the review. The analysis revealed that low-frequency harmonics increase following vigorous activity or sympathetic excitation but decrease during rest or parasympathetic excitation. Cardiovascular patients exhibited elevated first harmonics associated with the liver meridian, while diabetes patients displayed weakened third harmonics related to the spleen meridian. Liver dysfunction was linked to changes in the first harmonic, and cancer patients showed signs of liver and kidney yin deficiency in the first and second harmonics. These findings underscore

关键词： Diagnostic tools Harmonic characteristics Pulse diagnosis Pulse harmonic analysis Traditional Chinese medicine

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