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RUFY4 deletion prevents pathological bone loss by blocking endo-lysosomal trafficking of osteoclasts

Bone research 2024年第2期12卷 407-420页

作者： Minhee Kim Jin Hee Park Miyeon Go Nawon Lee Jeongin Seo Hana Lee Doyong Kim Hyunil Ha Taesoo Kim Myeong Seon Jeong Suree Kim Taesoo Kim Han Sung Kim Dongmin Kang Hyunbo Shim Soo Young Lee Department of Life Science Ewha Womans UniversitySeoul 03760South Korea The Research Center for Cellular Homeostasis Ewha Womans UniversitySeoul 03760South Korea Department of Biomedical Engineering Yonsei UniversityWonju 26493South Korea KM Convergence Research Division Korea Institute of Oriental MedicineDaejeon 34054South Korea Chuncheon Center Korea Basic Science InstituteChuncheon 24341South Korea Fluorescence Core Imaging Center and Bioimaging Data Curation Center Ewha Womans UniversitySeoul 03760South Korea Multitasking Macrophage Research Center Ewha Womans UniversitySeoul 03760South Korea

Mature osteoclasts degrade bone matrix by exocytosis of active proteases from secretory lysosomes through a ruffled ***,the molecular mechanisms underlying lysosomal trafficking and secretion in osteoclasts remain largely ***,we show with GeneChip analysis that RUN and FYVE domain-containing protein 4(RUFY4)is strongly upregulated during *** lacking Rufy4 exhibited a high trabecular bone mass phenotype with abnormalities in osteoclast function in ***,deleting Rufy4 did not affect osteoclast differentiation,but inhibited bone-resorbing activity due to disruption in the acidic maturation of secondary lysosomes,their trafficking to the membrane,and their secretion of cathepsin K into the extracellular ***,RUFY4 promotes late endosome-lysosome fusion by acting as an adaptor protein between Rab7 on late endosomes and LAMP2 on primary ***,Rufy4-deficient mice were highly protected from lipopolysaccharide-and ovariectomy-induced bone ***,RUFY4 plays as a new regulator in osteoclast activity by mediating endo-lysosomal trafficking and have a potential to be specific target for therapies against bone-loss diseases such as osteoporosis.

关键词： osteoclast inhibited traffic

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Photo-responsive polypropylene/zinc oxide/polydopamine-TEMPO composite membranes with light-induced self-sterilization

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Nano Materials science 2025年第2期7卷 276-288页

作者： Huajie Wang Hao Peng Wenhao Ji Jiaxin Wang Xiaoyan Du Wen Song Wen Zhang Fazli Wahid Ali Raza Xinxiang Key Laboratory of 3D Bioprinting and Precision Medicine School of Chemistry and Chemical EngineeringHenan Institute of Science and TechnologyEastern HuaLan AvenueXinxiangHenan453003PR China School of Food Science Henan Institute of Science and TechnologyEastern HuaLan AvenueXinxiangHenan453003PR China School of Biomedical Sciences and Biotechnology Pak-Austria Fachhochshule:Institute of Applied Sciences and TechnologyMangKhanpur RoadHaripur22620Pakistan Drug Transport and Delivery Research Group Department of PharmacyUIT the Arctic University of NorwayTromsø9037Norway

Face masks play a pivotal role in preventing infection ***,the capture of infection-sourced particles in face masks poses challenges related to reuse,necessitating proper *** developed a self-sterilizable polypropylene-based membrane for face masks to address challenges associated with infection transmission *** membrane,created using 3D printing,underwent functionalization with zinc oxide(ZnO)and polydopamine(PDA)-TEMPO to achieve broad-spectrum light absorption and facilitate self-sterilization through photocatalytic and photothermal effects upon light *** hydrophobic surface(water contact angle:133±2°)minimized moisture accumulation,and the membrane exhibited robust mechanical properties,including shear strength(1.25±0.5kPa)and peel resistance strength(112.8±11.2kPa).The evaluation demonstrated stability in airflow(0-500cm^(3)/s)and excellent aerosol filtration efficiency(94.8±0.6%)for particles(PM 0.3,PM 2.5,PM 10),comparable to commercial *** membrane showed antibacterial efficacy over five uses in a simulated respiratory *** assessments confirmed biocompatibility through cytocompatibility and skin irritation *** conclusion,this membrane offers efficient filtration and photo-triggered sterilization,presenting a promising solution for next-generation face masks to address concerns related to reuse,disposal,and infection control.

关键词： Face masks 3D printing Nanocomposites Polydopamine Photo-responsive Self-sterilization

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Robotic Cognitive Behavioural Therapy: rCBT 16th

Robotic Cognitive Behavioural Therapy: rCBT

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16th International Conference on Social Robotics, ICSR + BioMed 2024

作者： Samani, Hooman Zaraki, Abolfazl Davies, Daisy-Rose Fernando, Owen Noel Newton Creative Computing Institute University of the Arts London London United Kingdom and Robotics Research Group University of Hertfordshire Hatfield United Kingdom School of Engineering Computing and Mathematics University of Plymouth Plymouth United Kingdom College of Computing and Data Science Nanyang Technological University Singapore Singapore

ISBN: (纸本)9789819789627

This paper introduces Robotic Cognitive Behavioural Therapy (rCBT) as a novel approach to overcoming the limitations of traditional Cognitive Behavioural Therapy (CBT) in treating emotional and psychological issues. After a brief overview of CBT and its inherent challenges, this paper explores the innovative application of physical robots in therapy, building on the success of technology-based CBT methods that have effectively treated various mental health conditions. The proposed rCBT solution is a compact, portable, and cost-effective 3D-printed robot designed to aid individuals with anxiety or depression. This robot includes interactive features such as a diary, health questionnaires, daily mood monitoring, to-do lists, mindfulness exercises, and a crisis helpline, enabling users to track their emotional states and activities. These functions support healthcare professionals and users in identifying emotional patterns and triggers. The robot can monitor physiological signals like heart rate. This research aims to enhance the accessibility and effectiveness of CBT, suggesting that rCBT could significantly broaden the therapy’s reach and improve mental health outcomes for a larger population. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Social robots

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Anticipating Fainting: Real-Time Prediction of Vasovagal Syncope During Head-Up Tilt Table Testing 38

Anticipating Fainting: Real-Time Prediction of Vasovagal Syn...

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38th IEEE Region 10 Conference, TENCON 2023

作者： Ferdowsi, Mahbuba Gan, Ming-Hong Kwan, Ban-Hoe Tan, Maw Pin Goh, Choon-Hian Centre for Healthcare Science and Technology Universiti Tunku Abdul Rahman Department of Mechatronics and BioMedical Engineering Kajang Malaysia Universiti Tunku Abdul Rahman Department of Mechatronics and BioMedical Engineering Kajang Malaysia Universiti Malaya Ageing and Age-Associated Disorders Research Group Faculty of Medicine Department of Medicine Kuala Lumpur Malaysia

ISBN: (纸本)9798350302196

Vasovagal syncope (VVS) is the commonest cause of short-term loss of consciousness, which negatively impacts quality of life. To gather diagnostic information, medical professions often perform a head-up tilt test (HUTT) during direct observation. During this test, subjects may experience common symptoms such as nausea, pallor, sweating, palpitations, near faint and syncope. The purpose of the study was to develop an algorithm that uses electrocardiography (ECG) and blood pressure (BP) recordings from HUTT to predict VVS before its onset. In this study, the calculated cumulative risk based on the analysis of the three specific sets of features was compared to a pre-established VVS risk threshold. The purpose of this comparison was to determine if the cumulative risk was above or below the threshold and whether an alert should be generated. An alert would only be triggered when the cumulative risk exceeded the threshold. The prediction time was defined as the duration between the first alert and the actual syncope episode. A total of 137 subjects were recruited in this study. Our proposed model accurately predicted syncope onset in 87 out of 120 subjects. The model's sensitivity was 81.6% while its specificity was 66.2%. The precision was determined to be 62.5%, the F1 score was 70.8%. Additionally, the model was able to predict syncope before its onset with a median prediction time of 221.45 seconds (Interquartile range: 180.0 - 294.0 s). In conclusion, while predicting VVS can be challenging due to its complex nature, recognizing, and treating the underlying causes as well as implementing appropriate treatment methods, can significantly improve outcomes for individuals at risk. The proposed algorithm shows promise in reducing discomfort associated with symptom reproduction with HUTT. © 2023 IEEE.

关键词： Blood pressure

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ICH-SCNet: Intracerebral Hemorrhage Segmentation and Prognosis Classification Network Using CLIP-guided SAM mechanism

ICH-SCNet: Intracerebral Hemorrhage Segmentation and Prognos...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Yu, Xinlei Elazab, Ahmed Ge, Ruiquan Jin, Hui Jiang, Xinchen Jia, Gangyong Wu, Qing Shi, Qinglei Wang, Changmiao Hangzhou Dianzi University School of Computer Science Hangzhou China Shenzhen University School of Biomedical Engineering Shenzhen China Chinese University of Hong Kong Shenzhen School of Management and Economics Shenzhen China Chinese University of Hong Kong Shenzhen School of Medicine Shenzhen China Shenzhen Research Institute of Big Data Medical Big Data Lab Shenzhen China

ISBN: (纸本)9798350386226

Intracerebral hemorrhage (ICH) is the most fatal subtype of stroke and is characterized by a high incidence of disability. Accurate segmentation of the ICH region and prognosis prediction are critically important for developing and refining treatment plans for post-ICH patients. However, existing approaches address these two tasks independently and predominantly focus on imaging data alone, thereby neglecting the intrinsic correlation between the tasks and modalities. This paper introduces a multi-task network, ICH-SCNet, designed for both ICH segmentation and prognosis classification. Specifically, we integrate a SAM-CLIP cross-modal interaction mechanism that combines medical text and segmentation auxiliary information with neuroimaging data to enhance cross-modal feature recognition. Additionally, we develop an effective feature fusion module and a multi-task loss function to improve performance further. Extensive experiments on an ICH dataset reveal that our approach surpasses other state-of-the-art methods. It excels in the overall performance of classification tasks and outperforms competing models in all segmentation task metrics. © 2024 IEEE.

关键词： Diagnosis

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Out-of-Distribution Detection for Learning-Based Chest X-Ray Diagnosis

Out-of-Distribution Detection for Learning-Based Chest X-Ray...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Wenlong Chen Chuanwen Feng Ao Ke Xike Xie S. Kevin Zhou School of Biomedical Engineering University of Science and Technology of China Data Darkness Lab Miracle Center Suzhou Institute for Advanced Research USTC

Deep learning has shown prominence in chest radiography interpretation, which is critical in evaluating various lung and chest diseases, such as pneumonia, emphysema, and tuberculosis. Deploying machine learning model, it is important to detect out-of-distribution (OOD) inputs, which are distinct from the training data. For example, a model trained on conventional pneumonia data may not be able to diagnose COVID-19 accurately, letting alone the vast body of possible abnormalities and variation in medical imaging. Thus, a trustworthy diagnosing model should be alerted with such OOD inputs to avoid the overconfidence with samples and therefore the risk of misdiagnosis and severe medical consequences. In this paper, we study the problem of OOD detection for deep learning-based chest X-ray imaging by proposing a distance-based OOD detection method. We show that our method (1) inherits the merits of distance-based methods in being applicable to different models and training losses; and (2) adopts probabilistic score functions with fewer statistics to mitigate the potential distribution assumption on training data. We conduct extensive experiments on benchmarks to demonstrate the superiority of our method. In particular, on challenging tasks, such as Chest X-ray 14 vs. COVID-19, our method achieves 12.62% lower FPR than the state-of-the-art solutions.

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Comparison of extruded cell nanovesicles and exosomes in their molecular cargos and regenerative potentials

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Nano research 2023年第5期16卷 7248-7259页

作者： Xianyun Wang Shiqi Hu Dashuai Zhu Junlang Li Ke Cheng Gang Liu Department of Cardiology The First Hospital of Hebei Medical UniversityShijiazhuang 050000China Scientific Research Data Center The First Hospital of Hebei Medical UniversityShijiazhuang 050000China Hebei Key Laboratory of Cardiac Injury Repair Mechanism Study Shijiazhuang 050000China Hebei International Joint Research Center for Structural Heart Disease Shijiazhuang 050000China Department of Molecular Biomedical Science North Carolina State UniversityRaleigh 27607North CarolinaUSA Department of Biomedical Engineering University of North CarolinaChapel Hill and North Carolina State UniversityRaleigh 27607North CarolinaUSA

Extracellular vesicles(EVs)generated from mesenchymal stem cells(MSCs)play an essential role in modulating cell–cell communication and tissue *** clinical translation of EVs is constrained by the poor yield of *** has recently become an effective technique for producing a large scale of nanovesicles(NVs).In this study,we systematically compared MSC NVs(from extrusion)and EVs(from natural secretion).Proteomics and RNA sequencing data revealed that NVs resemble MSCs more closely than ***,microRNAs in NVs are related to cardiac repair,fibrosis repression,***,intravenous delivery of MSC NVs improved heart repair and cardiac function in a mouse model of myocardial infarction.

关键词： nanovesicles(NVs) exosomes,cardiac repair mesenchymal stem cells(MSCs) extracellular vesicles(EVs) myocardial infarction(MI)

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Graded porous scaffold mediates internal fluidic environment for 3D in vitro mechanobiology

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Computers in Biology and Medicine 2025年 186卷 109674-109674页

作者： De Rosa, Chiara Angela Wright, Christopher J. Xiong, Yi Del Giudice, Francesco Zhao, Feihu Department of Biomedical Engineering Faculty of Science and Engineering Swansea University Swansea United Kingdom Zienkiewicz Institute for Modelling Data and AI Swansea University Swansea United Kingdom School of System Design and Intelligent Manufacturing Southern University of Science and Technology Guangdong Province Shenzhen China Complex Fluid Research Group Department of Chemical Engineering Faculty of Science and Engineering Swansea University Swansea United Kingdom

Most cell types are mechanosensitive, their activities such as differentiation, proliferation and apoptosis, can be influenced by the mechanical environment through mechanical stimulation. In three dimensional (3D) mechanobiological in vitro studies, the porous structure of scaffold controls the local mechanical environment that applied to cells. Many previous studies have focused on the topological design of homogeneous scaffold struts. However, the impact of scaffold inhomogeneity on the mechanical environment, which is essential in mechanobiological application (e.g. for multi-cells co-culture), remains elusive. In this study, we use a computational fluid dynamics (CFD) approach together with data analysis to study the influence of a porosity gradient (10 %–30 % porosity difference) on the local and global mechanical environment (wall shear stress - WSS) within the commonly used structures of triple periodic minimal surfaces (TPMS). In addition, the anisotropy of internal WSS and scaffold permeability caused by the porosity gradient is investigated. It is found that the influence of anisotropy on the average WSS and permeability is up to 11 % and 31 %, respectively. These results, as theoretical references will be useful to tissue engineers and mechanobiologists for scaffold design and in vitro experiment planning such as integrated use of graded scaffold and bioreactors for specific cell types. © 2025 The Authors

关键词： Shear stress

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DVasMesh: Deep Structured Mesh Reconstruction from Vascular Images for Dynamics Modeling of Vessels 6th

DVasMesh: Deep Structured Mesh Reconstruction from Vascular...

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6th International Workshop on Graphs in biomedical Image Analysis, GRAIL 2024

作者： Jia, Dengqiang Yang, Xinnian Xiong, Xiaosong Huang, Shijie Hou, Feiyu Qin, Li Sun, Kaicong Chan, Kannie Wai Yan Shen, Dinggang Hong Kong Centre for Cerebro-Cardiovascular Health Engineering China School of Data Science City University of Hong Kong China School of Biomedical Engineering and State Key Laboratory of Advanced Medical Materials and Devices ShanghaiTech University Shanghai201210 China School of Mechanical and Automotive Engineering Shanghai University of Engineering Science Shanghai201620 China JinFeng Laboratory Chongqing401329 China Department of Biomedical Engineering City University of Hong Kong China Shanghai United Imaging Intelligence Co. Ltd. Shanghai200230 China Shanghai Clinical Research and Trial Center Shanghai201210 China

ISBN: (纸本)9783031832420

Vessel dynamics simulation is vital in studying the relationship between geometry and vascular disease progression. Reliable dynamics simulation relies on high-quality vascular meshes. Most of the existing mesh generation methods highly depend on manual annotation, which is time-consuming and laborious, usually facing challenges such as branch merging and vessel disconnection. This will hinder vessel dynamics simulation, especially for the population study. To address this issue, we propose a deep learning-based method, dubbed as DVasMesh to directly generate structured hexahedral vascular meshes from vascular images. Our contributions are threefold. First, we propose to formally formulate each vertex of the vascular graph by a four-element vector, including coordinates of the centerline point and the radius. Second, a vectorized graph template is employed to guide DVasMesh to estimate the vascular graph. Specifically, we introduce a sampling operator, which samples the extracted features of the vascular image (by a segmentation network) according to the vertices in the template graph. Third, we employ a graph convolution network (GCN) and take the sampled features as nodes to estimate the deformation between vertices of the template graph and target graph, and the deformed graph template is used to build the mesh. Taking advantage of end-to-end learning and discarding direct dependency on annotated labels, our DVasMesh demonstrates outstanding performance in generating structured vascular meshes on cardiac and cerebral vascular images. It shows great potential for clinical applications by reducing mesh generation time from 2 h (manual) to 30 s (automatic). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Mesh generation

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GCN2 inhibition reduces mutant SOD1 clustering and toxicity and delays disease progression in an amyotrophic lateral sclerosis mouse model

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Translational Neurodegeneration 2024年第1期13卷 351-355页

作者： Didio Alberto Ortiz Nuria Peregrín Miguel Valencia Rodrigo Vinueza-Gavilanes Elisa Marín-Ordovas Roberto Ferrero María Jesús Nicolás Gloria González-Aseguinolaza Montserrat Arrasate Tomás Aragón DNA and RNA Medicine Program Center for Applied Medical Research(CIMA)University of NavarraPamplonaSpain Biomedical Engineering Program Center for Applied Medical Research(CIMA)University of NavarraPamplonaSpain Institute of Data Science and Artificial Intelligence(DATAI) University of NavarraPamplonaSpain Navarra Institute for Health Research(IdiSNA) PamplonaSpain Neuroimmunology Department Multiple Sclerosis Center of Catalonia(Cemcat)Vall d’Hebron Research Institute(VHIR)BarcelonaSpain School of Medicine University of NavarraPamplonaSpain Brain Lab Biobizkaia Health Research InstituteBarakaldoSpain Present Address:Ikerbasque Basque Foundation for ScienceBilbaoSpain

Main text The disruption of protein folding homeostasis in motoneurons(MNs)and the accumulation of protein aggregates are some of the main molecular hallmarks of amyotrophic lateral sclerosis(ALS).Evidence from sporadic and familial ALS(fALS)patients and from ALS models suggests that protein aggregation directly participates in *** turn,the loss of MN homeostasis triggers a coping mechanism,the integrated stress response(ISR)[1].The ISR is initiated by four independent stress-sensing kinases,each of them activated by distinct stresses:protein kinase R(PKR)by double-strand RNA,protein kinase RNA-like endoplasmic reticulum kinase(PERK)by protein misfolding at the endoplasmic reticulum(ER),general control nonderepressible 2(GCN2)by nutrient starvation,and heme-regulated inhibitor(HRI)by heme deprivation.

关键词： homeostasis amyotrophic sclerosis

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