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BAF45D regulates spinal cord neural stem/progenitor cell fate through the SMAD-PAX6 axis

Genes & Diseases 2023年第2期10卷 366-369页

作者： Xueying Chen Xiujuan Hu Jing Jiang Jie Tao Lihua Liu Shengyun Fang Yuxian Shen Qingsong Hu Chao Liu School of Basic Medical Sciences Anhui Medical UniversityHefeiAnhui 230032China Department of Histology and Embryology Institute of Stem Cell and Tissue EngineeringAnhui Medical UniversityHefeiAnhui 230032China Division of Life Sciences and Medicine University of Science and Technology of ChinaThe First Affiliated Hospital of USTCHefeiAnhui 230001China Institute of Clinical Pharmacology Anhui Medical UniversityHefeiAnhui 230032China Center for Biomedical Engineering and Technology University of MarylandBaltimoreMD 21201USA

Mutations in BRG1-associated factor 45D (BAF45D, also known as double PHD fingers 2 (DPF2)) are linked to Coffin-Siris syndrome (CSS).1 However, the underlying molecular mechanisms remain ill-defined. Here, we identified that wild-type but not CSS-associated BAF45D mutants increased the expression of PAX6,2 a neural stem cell marker, and phosphorylated SMAD3 (p-SMAD3) in spinal cord neural stem cells (NSCs) derived from H9 human embryonic stem cells. Both BAF45D and SMAD3 are required for the induction of p-SMAD3 and PAX6 together with STAT3 and SMAD7 by retinoic acid (RA). In the presence of RA, BAF45D knockdown decreased the expression of genes that regulate stem cell pluripotency. Moreover, the same genes in the spinal cord NSCs had more binding sites with BAF45D than those in H9 cells. Furthermore, Gene Ontology (GO) assay results indicated that BAF45D targets more pathways responsible for stem cell maintenance in NSCs. Finally, BAF45D is associated with BRG1, p-SMAD3, and PAX6. Together, these findings suggest a role for BAF45D in modulating PAX6 expression through SMAD signaling, highlighting the importance of BAF45D in neural stem/progenitor cell fate commitment.

关键词： PAX6 progenitor SMAD

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Advances in transcription factor delivery: Target selection, engineering strategies, and delivery platforms

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Journal of Controlled Release 2025年 384卷 113885页

作者： Lee, Yeji Yoo, Seongkyeong Cho, Seongeon Kim, Iljin Kim, In-San KU-KIST Graduate School of Converging Science and Technology Korea University Seoul02841 Korea Republic of Chemical and Biological Integrative Research Center Biomedical Research Institute Korea Institute Science and Technology Seoul02792 Korea Republic of Department of Pharmacology and Program in Biomedical Science and Engineering Inha University College of Medicine Incheon22212 Korea Republic of Research Center for Controlling Intercellular Communication Inha University College of Medicine Incheon22212 Korea Republic of

Recent advances in delivery systems for transcription factors (TFs) have opened new therapeutic opportunities in regenerative medicine, cancer therapy, and genetic disorders. However, effective TF delivery still faces substantial obstacles, including limited cellular uptake, inefficient nuclear translocation, low cargo stability, and insufficient target specificity. Furthermore, artificial TFs have enabled targeted modulation of gene expression, further expanding their therapeutic potential. This review comprehensively discusses current progress in TF delivery methodologies, including direct TF protein delivery using cell-penetrating peptides, and extracellular vesicles, as well as TF gene delivery approaches utilizing both lipid-based nanoparticles and viral strategies. Notably, engineered nanoparticles have emerged as promising platforms due to their precise control over TF delivery, improved specificity, and minimized off-target effects. Despite these significant advancements, major hurdles in delivery efficiency, cargo stability, and overall safety persist. Overcoming these obstacles will be essential to accelerate the clinical translation of TF-based therapeutics for a broad spectrum of diseases. © 2024

关键词： Transcription factors

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Constructing a Segmentation Model for Patients with Leukoaraiosis Using Deep Learning Algorithms 24

Constructing a Segmentation Model for Patients with Leukoara...

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

作者： Lo, Li-Ting Tsai, Yi-Chia Chang, Yi-Jou Ting, Hsien-Wei Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Department of Neurosurgery Taipei Hospital Ministry of Health and Welfare New Taipei City242 Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Many patients with leukoaraiosis (LA) exhibit mild and difficult-to-detect symptoms in the early stages, and due to the lack of effective detection methods, the optimal timing for treatment is often missed. This not only makes later treatment more difficult but, in severe cases, can even lead to mild to severe dementia. Therefore, in addition to relying on radiologists to manually interpret magnetic resonance imaging (MRI) scans, finding more effective detection methods has become extremely urgent. This study aimed to combine image processing and deep learning technologies to develop a model capable of accurately identifying and segmenting white matter hyperintensities (WMHs) to assist doctors in the early diagnosis of LA. We first performed efficient preprocessing on MR image slices from two different series and used the ResNet18 model to identify key slices containing WMHs, ultimately achieving precise segmentation of WMH areas with the U-Net model. This research focused on developing innovative preprocessing techniques, improving the accuracy by 12.3% with a limited dataset through preprocessing. Ultimately, the ResNet18 model achieved an F1 score of 0.829, while the U-Net model’s intersection over union (IoU) and Dice coefficient reached 0.750 and 0.857, respectively, showing the potential of this architecture. We propose improvements in the final chapter to construct a more comprehensive model. © 2024 Copyright ACM.

关键词： Deep learning

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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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Microenvironmental regulation of stem cells injected in the area at risk of neurodegenerative diseases

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BIOCELL 2022年第10期46卷 2231-2234页

作者： JU HYUNG LEE IL-KWON KIM SANG WOO KIM SOYEON LIM SEAHYOUNG LEE KI-CHUL HWANG BYEONG-WOOK SONG Graduate Program of Biomedical Engineering Yonsei UniversitySeoul03722Korea Institute for Bio-Medical Convergence College of MedicineCatholic Kwandong UniversityGangwon-do25601Korea Department for Medical Science College of MedicineCatholic Kwandong UniversityGangwon-do25601Korea

The complex mechanism of degenerative diseases and the non-specific modulation of regenerative targets aretopics that need to be elucidated in order to advance the use of stem cells in improvement of neurodegenerative *** pre-transplantation through post-transplantation, there are many changes in the conditions, both inside andoutside of the stem cells that have not been carefully considered. This has hindered development in the field of celltherapy and regeneration. This viewpoint highlights the potential implications of intracellular and extracellularalterations of stem cells in transplanted areas at risk of neurodegenerative disease.

关键词： Cell therapy Microenvironment Neurodegenerative disease Stem cells

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Constructing an Automated Method for Interpreting Alzheimer’s Disease Based on Deep Learning Models and Image Processing 24

Constructing an Automated Method for Interpreting Alzheimer...

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

作者： Yi, Chia-Pin Ting, Hsien-Wei Yang, Tzu-Fang Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Department of Neurosurgery Taipei Hospital Ministry of Health and Welfare New Taipei City242 Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan TaiwanInnovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Alzheimer’s disease (AD) often presents only mild symptoms in its early stages, and as there is no direct diagnostic method currently available, many patients are diagnosed only after the condition has worsened. Considering that magnetic resonance imaging (MRI) can provide key information in the diagnosis of AD, but the condition may go undiagnosed under manual interpretation due to the subtleness of symptoms and the reliance on radiologists to interpret MRI images, this study aimed to develop an automated method for interpreting brain MR images, hoping to screen for potential AD patients. By combining image processing, the U-Net model, YOLOv8 model, various CNN model architectures, and ensemble data statistics, our method was able to identify features related to AD and predict whether a patient has the disease. Our method can process a complete set of MR images and automatically extract important slices for prediction, making it practical for medical applications. Furthermore, we tested the accuracy and reliability of the method with additional datasets. © 2024 Copyright ACM.

关键词： Magnetic resonance imaging

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MOF-Derived Bimetal-Embedded Carbon with Etched Morphologies as an Efficient Activator of Peroxymonosulfate for Eliminate Emerging Contaminants

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Korean Journal of Chemical engineering 2024年第6期41卷 1815-1831页

作者： Chen, Yi-Chun Jiang, Xin-Yu Lin, Jia-Yin Thanh, Bui Xuan Wang, Haitao Huang, Chao-Wei Ghotekar, Suresh Huang, Chih-Feng Lin, Kun-Yi Andrew Department of Biotechnology National Formosa University Yunlin63208 Taiwan Department of Environmental Engineering & amp Innovation and Development Center of Sustainable Agriculture National Chung Hsing University Taichung Taiwan Semiconductor and Green Technology Program National Chung Hsing University 250 Kuo-Kuang Road Taichung Taiwan Ho Chi Minh City Viet Nam Ho Chi Minh City700000 Viet Nam Key Laboratory of Pollution Processes and Environmental Criteria College of Environmental Science and Engineering Nankai University Tianjin300071 China Department of Engineering Science National Cheng Kung University Tainan70101 Taiwan Centre for Herbal Pharmacology and Environmental Sustainability Chettinad Hospital and Research Institute Chettinad Academy of Research and Education Kelambakkam Tamil Nadu Chennai603103 India Department of Chemical Engineering National Chung Hsing University Taichung Taiwan Institute of Analytical and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Civil Engineering National Taipei University of Technology Taipei City Taiwan

As bis(4-hydroxyphenyl)methanone (BHP) is one of the most common UV light stabilizers (UVLS), but exhibits endocrine disrupting toxicity, this study aims to develop useful sulfate radical-based techniques to eliminate BHP from water by activating peroxymonosulfate (PMS). Hence, while cobalt (Co) exhibits efficacy as a transition metal for the activation of PMS, the utilization of manganese/cobalt (Mn/Co) bimetallic oxides presents an even more encouraging prospect as heterogeneous catalysts for PMS activation. In this study, we have successfully produced N-doped carbon-supported Mn/Co nanoparticles (NCMC) with a distinctive hollow-engineered nanostructure. The synthesis involved the utilization of Co-MOF as a precursor, followed by easy etching and Mn doping to achieve the desired composition of Mn/Co bimetallic oxide nanoparticles. The inclusion of Mn dopant facilitates the integration of Mn/Co nanoparticles into the hollow-structured N-doped carbon matrix. NCMC demonstrates much higher activity compared to NCC and the benchmark catalyst, Co3O4 NP, in terms of PMS activation for the degradation of BHP. The findings of the eco-toxicity study indicate that the degradation of BHP by NCMC + PMS does not yield hazardous or extremely toxic byproducts, so establishing NCMC as a potentially effective heterogeneous catalyst for activating PMS in the degradation of BHP. © The Author(s), under exclusive licence to Korean Institute of Chemical Engineers, Seoul, Korea 2024.

关键词： Transition metals

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Automatic image registration of optoacoustic tomography and magnetic resonance imaging based on deep learning 1

Automatic image registration of optoacoustic tomography and ...

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1st Conference on biomedical Photonics and Cross-Fusion, BPC 2022

作者： Hu, Yexing Lafci, Berkan Luzgin, Artur Wang, Hao Klohs, Jan Deán-Ben, Xose Luis Ni, Ruiqing Razansky, Daniel Ren, Wuwei School of Information Science and Technology ShanghaiTech University Shanghai201210 China Institute of Pharmacology and Toxicology Institute for Biomedical Engineering Faculty of Medicine University of Zurich Zurich8052 Switzerland Institute for Biomedical Engineering Department of Information Technology and Electrical Engineering ETH Zurich Zurich8093 Switzerland Institute for Regenerative Medicine University of Zurich Zurich8952 Switzerland

ISBN: (纸本)9781510660274

Multi-spectral optoacoustic tomography (MSOT) combines rich contrast of optical imaging and high resolution of ultrasound, and becomes an attractive biomedical research tool in the last decade. Aligning MSOT images with anatomical map provided by magnetic resonance imaging (MRI) can potentially enhance the interpretation of optoacoustic signal which mainly reflects molecular and functional information. Therefore, developing an automated algorithm of image registration between MSOT and MRI is crucial. Existing MSOT-MRI registration algorithms mostly relied on manual segmentation, which requires user-dependent experience. Herein, we developed a fully automated algorithm for MSOT-MRI registration based on deep learning (DL). This workflow consists of DL-based segmentation and image transformation. We have experimentally demonstrated the accuracy and computational efficiency of the method, paving the way towards high-throughput MSOT data analysis in close future. © 2022 SPIE. All rights reserved.

关键词： Magnetic resonance imaging

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Optimized Photonic Integrated Circuit Components for Optical Coherence Tomography at 1060 nm

Optimized Photonic Integrated Circuit Components for Optical...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Senyue Hao Aaron J Adkins Yitian Zhang Chao Zhou Department of Electrical & Systems Engineering Washington University in Saint Louis USA Imaging Science PhD Program Washington University in Saint Louis USA Department of Biomedical Engineering Washington University in Saint Louis USA

To implement optical coherence tomography on photonic chips, we developed optimized and experimentally validated silicon nitride-based components for photonic integrated circuits in order to achieve high sensitivity a... 详细信息

ISBN: (纸本)9798350369311

关键词： Sensitivity Optical coherence tomography Photonic integrated circuits Silicon Electro-optical waveguides Photonics

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Undulating Seal Whiskers Evolved Optimal Wavelength-to-Diameter Ratio for Efficient Reduction in Vortex-Induced Vibrations (Adv. Sci. 2/2024)

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ADVANCED science 2024年第2期11卷 e2304304页

作者： Kamat, Amar M. Zheng, Xingwen Bos, Julian Cao, Ming Triantafyllou, Michael S. Kottapalli, Ajay Giri Prakash Bioinspired MEMS and Biomedical Devices Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Groningen The Netherlands Discrete Technology and Production Automation Group Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Groningen The Netherlands Department of Mechanical Engineering Massachusetts Institute of Technology (MIT) Cambridge MA USA MIT Sea Grant College Program Massachusetts Institute of Technology (MIT) Cambridge MA USA Bioinspired MEMS and Biomedical Devices Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Groningen The Netherlands MIT Sea Grant College Program Massachusetts Institute of Technology (MIT) Cambridge MA USA

Seals are well-known for their remarkable hydrodynamic trail-following capabilities made possible by undulating flow-sensing whiskers that enable the seals to detect fish swimming as far as 180 m away. In this work, the form-function relationship in the undulating whiskers of two different phocid seal species, viz. harbor and gray seals, is studied. The geometry and material properties of excised harbor and grey seal whiskers are systematically characterized using blue light 3D scanning, optical and scanning electron microscopy, and nanoindentation. The effect of the undulating geometry on the whiskers’ vibration in uniform water flow is studied using both experimental (piezoelectric MEMS and 3D-printed piezoresistive sensors developed in-house) and numerical (finite element method) techniques. The results indicate that the dimensionless ratio of undulation wavelength to mean whisker diameter (λ/Dm) in phocid seals may have evolved to be in the optimal range of 4.4–4.6, enabling an order-of-magnitude reduction in vortex-induced vibrations (compared to a similarly-shaped circular cylinder) and, consequently, an enhanced flow sensing capability with minimal self-induced noise. The results highlight the importance of the dimensionless λ/Dm ratio in the biomimetic design of seal whisker-inspired vibration-resistant structures, such as marine risers and wake detection sensors for submarines.

关键词： 3D printing biological fluid dynamics biomimetics microelectromechanical systems (MEMS) seal whiskers vortex-induced vibrations

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