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New aspects of a small GTPase RAB35 in brain development and function

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Neural Regeneration Research 2025年第7期20卷 1971-1980页

作者： Ikuko Maejima Ken Sato Laboratory of Molecular Traffic Institute for Molecular and Cellular RegulationGunma UniversityMaebashiJapan

In eukaryotic cells,organelles in the secretory,lysosomal,and endocytic pathways actively exchange biological materials with each other through intracellular membrane trafficking,which is the process of transporting the cargo of proteins,lipids,and other molecules to appropriate compartments via transport vesicles or *** processes are strictly regulated by various small GTPases such as the RAS-like in rat brain(RAB)protein family,which is the largest subfamily of the RAS *** of membrane trafficking affects tissue homeostasis and leads to a wide range of diseases,including neurological disorders and neurodegenerative ***,it is important to understand the physiological and pathological roles of RAB proteins in brain ***35,a member of the RAB family,is an evolutionarily conserved protein in metazoans.A wide range of studies using cultured mammalian cells and model organisms have revealed that RAB35 mediates various processes such as cytokinesis,endocytic recycling,actin bundling,and cell ***35 is also involved in neurite outgrowth and turnover of synaptic *** generated brain-specific Rab35 knockout mice to study the physiological roles of RAB35 in brain development and *** mice exhibited defects in anxiety-related behaviors and spatial ***,RAB35 is required for the precise positioning of pyramidal neurons during hippocampal development,and thereby for normal hippocampal *** contrast,layer formation in the cerebral cortex occurred superficially,even in the absence of RAB35,suggesting a predominant role for RAB35 in hippocampal development rather than in cerebral cortex *** studies have suggested an association between RAB35 and neurodegenerative diseases,including Parkinson's disease and Alzheimer's *** this review,we provide an overview of the current understanding of subcellular functions of *** also provide insights into the phys

关键词： endocytosis endosomes hippocampal development neurodegenerative diseases RAB35

A new electric field mill array with each of the mill’s rotor controlled precisely by a GPS module:Equipment and initial results

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Earth and Planetary Physics 2024年第2期8卷 423-435页

作者： Kozo Yamashita Hironobu Fujisaka DaoHong Wang Hiroyuki Iwasaki Kazuo Yamamoto Koichiro Michimoto Masashi Hayakawa Department of Production Systems Engineering and Sciences Komatsu UniversityNu 1-3 Shicho-machiKomatsuIshikawa 923-8511Japan Fujisaka Technology Office 1058-5 Yoshizawa-choOhta-shiGunma 373-0019Japan Department of Electrical Electronic and Computer EngineeringGifu University1-1 YanagidoGifu CityGifu 501-1193Japan Cooperative Faculty of Education Gunma University4-2-Aramaki-machiMaebashiGunma 371-8510Japan Department of Electrical and Electronic Engineering Chubu University1200 Matsumoto-choKasugaiAichi 487-8501Japan Independent Researcher Kosenba Town 2-44-11-406Kawagoe CitySaitama350-0036Japan Advanced Wireless&Communications Research Center The University of Electro-Communications1-5-1 ChofugaokaChofuTokyo 182-8585Japan

We have newly designed an electrostatic sensor,called an electric field mill(EFM),to simplify the estimation of the charge position and charge amount transferred by lightning *** is necessary for this remote estimation of the transferred charge to measure electric field changes caused by charge loss at the time of a lightning strike at multiple *** multiple-station measurement of electric field changes,not only speed but also phase for exposure and shielding of the sensing plates inside each EFM of the array should be synchronized to maintain the sensitivities of the deployed ***,there is no such EFM with specified speed and phase control performance of the rotary ***,we developed a new EFM in which the rotary mechanism was controlled consistently to within 3%error by a GPS *** EFMs had been distributed in the Hokuriku area of Japan during the winter season of 2022-2023 for a test *** we describe the design and a simple calibration method for our new EFM *** analysis method based on the assumption of a simple monopole charge structure is also *** validation,locations of assumed point charges were compared with three-dimensional lightning mapping data estimated by radio observations in the MF-HF *** results indicated the validity to estimate transferred charge amounts and positions of winter cloud-to-ground lightning discharges with our new EFM array.

关键词： lightning electrostatic field electric field mill electric field change

Pickering emulsion transport in skeletal muscle tissue:A dissipative particle dynamics simulation approach

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Chinese Journal of Chemical Engineering 2024年第4期68卷 65-75页

作者： Xuwei Liu Wei Chen Yufei Xia Guanghui Ma Reiji Noda Wei Ge State Key Laboratory of Mesoscience and Engineering Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China Division of Environmental Engineering Science Graduate School of Science and TechnologyGunma University1-5-1 Tenjin-choKiryuGunma 376-8515Japan State Key Laboratory of Biochemical Engineering Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing 100049China Innovation Academy for Green Manufacture Chinese Academy of SciencesBeijing 100190China

Lymph node targeting is a commonly used strategy for particulate vaccines,particularly for Pickering ***,extensive research on the internal delivery mechanisms of these emulsions,especially the complex intercellular interactions of deformable Pickering emulsions,has been surprisingly *** gap in knowledge holds significant potential for enhancing vaccine *** study aims to address this by summarizing the process of lymph-node-targeting transport and introducing a dissipative particle dynamics simulation method to evaluate the dynamic processes within cell *** transport of Pickering emulsions in skeletal muscle tissue is specifically investigated as a case *** factors impacting the transport process are explored,including local cellular tissue environmental factors and the properties of the Pickering emulsion *** simulation results primarily demonstrate that an increase in radial repulsive interaction between emulsion particles can decrease the transport ***,larger intercellular gaps also diminish the transport efficiency of emulsion droplet particles due to the increased motion complexity within the intricate transport space compared to a single *** study sheds light on the nuanced interplay between engineered and biological systems influencing the transport dynamics of Pickering *** insights hold valuable potential for optimizing transport processes in practical biomedical applications such as drug ***,the desired transport efficiency varies depending on the specific *** instance,while a more rapid transport might be crucial for lymph-node-targeted drug delivery,certain applications requiring a slower release of active components could benefit from the reduced transport efficiency observed with increased particle repulsion or larger intercellular gaps.

关键词： Pickering emulsion Skeletal muscular cells Transport phenomena Dissipative particle dynamics Drug delivery

Performance Comparison of Vision Transformer- and CNN-Based Image Classification Using Cross Entropy: A Preliminary Application to Lung Cancer Discrimination from CT Images

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Journal of Biomedical Science and Engineering 2024年第9期17卷 157-170页

作者： Eri Matsuyama Haruyuki Watanabe Noriyuki Takahashi Faculty of Informatics The University of Fukuchiyama Kyoto Japan School of Radiological Technology Gunma Prefectural College of Health Sciences Gunma Japan School of Health Sciences Fukushima Medical University Fukushima Japan

This study evaluates the performance and reliability of a vision transformer (ViT) compared to convolutional neural networks (CNNs) using the ResNet50 model in classifying lung cancer from CT images into four categories: lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), large cell carcinoma (LULC), and normal. Although CNNs have made significant advancements in medical imaging, their limited capacity to capture long-range dependencies has led to the exploration of ViTs, which leverage self-attention mechanisms for a more comprehensive global understanding of images. The study utilized a dataset of 748 lung CT images to train both models with standardized input sizes, assessing their performance through conventional metrics—accuracy, precision, recall, F1 score, specificity, and AUC—as well as cross entropy, a novel metric for evaluating prediction uncertainty. Both models achieved similar accuracy rates (95%), with ViT demonstrating a slight edge over ResNet50 in precision and F1 scores for specific classes. However, ResNet50 exhibited higher recall for LULC, indicating fewer missed cases. Cross entropy analysis showed that the ViT model had lower average uncertainty, particularly in the LUAD, Normal, and LUSC classes, compared to ResNet50. This finding suggests that ViT predictions are generally more reliable, though ResNet50 performed better for LULC. The study underscores that accuracy alone is insufficient for model comparison, as cross entropy offers deeper insights into the reliability and confidence of model predictions. The results highlight the importance of incorporating cross entropy alongside traditional metrics for a more comprehensive evaluation of deep learning models in medical image classification, providing a nuanced understanding of their performance and reliability. While the ViT outperformed the CNN-based ResNet50 in lung cancer classification based on cross-entropy values, the performance differences were minor and may not hold c

关键词： Lung Cancer Classification Vision Transformers Convolutional Neural Networks Cross Entropy Deep Learning

Using Cross Entropy as a Performance Metric for Quantifying Uncertainty in DNN Image Classifiers: An Application to Classification of Lung Cancer on CT Images

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Journal of Biomedical Science and Engineering 2024年第1期17卷 1-12页

作者： Eri Matsuyama Masayuki Nishiki Noriyuki Takahashi Haruyuki Watanabe Faculty of Informatics University of Fukuchiyama Kyoto Japan Graduate School of Radiological Sciences International University of Health and Welfare Tochigi Japan School of Health Sciences Fukushima Medical University Fukushima Japan School of Radiological Technology Gunma Prefectural College of Health Sciences Gunma Japan

Cross entropy is a measure in machine learning and deep learning that assesses the difference between predicted and actual probability distributions. In this study, we propose cross entropy as a performance evaluation metric for image classifier models and apply it to the CT image classification of lung cancer. A convolutional neural network is employed as the deep neural network (DNN) image classifier, with the residual network (ResNet) 50 chosen as the DNN archi-tecture. The image data used comprise a lung CT image set. Two classification models are built from datasets with varying amounts of data, and lung cancer is categorized into four classes using 10-fold cross-validation. Furthermore, we employ t-distributed stochastic neighbor embedding to visually explain the data distribution after classification. Experimental results demonstrate that cross en-tropy is a highly useful metric for evaluating the reliability of image classifier models. It is noted that for a more comprehensive evaluation of model perfor-mance, combining with other evaluation metrics is considered essential. .

关键词： Cross Entropy Performance Metrics DNN Image Classifiers Lung Cancer Prediction Uncertainty

Engineering W/O/W pickering emulsion for the enhanced antigen delivery and immune responses

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Particuology 2024年第9期92卷 224-233页

作者： Sihua Wu Xiaonan Huang Yin Ma Naoki Asakawa Yufei Xia State Key Laboratory of Biochemical Engineering Institute of Process EngineeringChinese Academy of SciencesBeijing100081China Key Laboratory of Biopharmaceutical Preparation and Delivery Chinese Academy of SciencesBeijing100190China Division of Molecular Science Graduate School of Science and TechnologyGunma University1-5-1Tenjin-choKiryu376-8515Japan Sinovac Biotech Ltd. Beijing100085China School of Chemical Engineering Nanjing Tech UniversityNanjing211816China School of Chemical Engineering University of Chinese Academy of SciencesBeijing100049China

Tumor immunotherapy,particularly cancer vaccines,holds promise for combating cancer by harnessing tailored immune responses against malignant ***,conventional approaches face challenges in efficiently delivering antigens for optimal immune *** adjuvants,like MF59,enhance cellular uptake but struggle to induce robust CD8^(+)T cell ***,we introduce a novel strategy employing a water-in-oil-in-water(W/O/W)multiple Pickering emulsion(mPE)for antigen *** mPE,utilizing biocompatible,pH-sensitive particles,encapsulates antigens within the inner water phase,ensuring enhanced intracellular processing and dictating the intracellular fate of antigens for improved *** vitro and in vivo studies demonstrated that mPEs induced robust dendritic cells activation and antigen cross-presentation,leading to a significantly enhanced immune ***,calcium phosphate-stabilized mPE(CaP-mPE)illustrated the more robust IFN-γ^(+)T cell *** comparison with traditional surfactant-stabilized multiple emulsions,CaP-mPE significantly inhibit tumor growth and effectively prolong the survival of tumor-bearing *** innovative approach offers a promising avenue for the development of effective cancer vaccines with potent cellular immune responses.

关键词： Cancer vaccine Multiple pickeringemulsion Adjuvant Antigen delivery Anti-tumor response

Flow Rate Measurement of Gravity Infusion Set and Functional Evaluation of Drop Counter: A Pilot Study

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Journal of Biomedical Science and Engineering 2024年第7期17卷 129-135页

作者： Rina Sakai Shuichi Tanaka Kaya Murakami Tomomi Mizuhashi Kazuhiro Yoshida Masanobu Ujihira Department of Medical Engineering and Technology Kitasato University School of Allied Health Sciences Sagamihara Japan Faculty of Medical Engineering Gunma University of Health and Welfare Maebashi Japan Kitasato university Graduate School of Medical Sciences Sagamihara Japan

Developing a novel drop counter by introducing the Internet of Things concept has been vigorously conducted in recent years. Understanding the newly introduced drop counter’s flow rate control accuracy and flow rate count feature is essential for improving safety in infusion management. This study aimed to verify if the new drop counters could secure accurate flow rate and drip count by conducting actual flow rate measurements using gravimetry and functional evaluation. A drop counter was attached to each drip chamber of the infusion set, and an IV drip was conducted at the 100 ml/h flow rate. The weight of discharged physiological saline was measured to plot trumpet curves. Next, three different types of drop counters were evaluated to determine if they maintained drip count accuracy according to the changes in their position angles. The flow rate errors in all conditions indicated trumpet-like curves, exhibiting an overall error range within ±10% in all observation windows. Although every drop counter successfully detected and measured dripping, it was challenging in some counters to detect dripping when the drip chamber was tilted. In comparing adult and pediatric IV sets, the adult IV set was found to be less likely to detect dripping in the angled position. No significant differences in results were confirmed between high and low flow rates, suggesting that the drop count function would not be affected by the flow rate in the ranges of typical infusion practices. Doppler sensors have a wide range of measurements and high sensitivity;the dripping was detected successfully even when the drip chamber was tilted, probably due to the advantages of these sensors. In contrast, miscounts occurred in those equipped with infrared sensors, which could not detect light intensity changes in tilted positions. Understanding the tendencies in flow rate errors in infusion can be valuable information for infusion management.

关键词： Gravity Infusion Set Drop Counter IV Fluids Flow Rate Trumpet Curves

Entanglement quantification via weak measurements assisted by deep learning

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Photonics Research 2024年第4期12卷 712-719页

作者： MU YANG YA XIAO ZE-YAN HAO YU-WEI LIAO JIA-HE CAO KAI SUN EN-HUI WANG ZHENG-HAO LIU YUTAKA SHIKANO JIN-SHI XU CHUAN-FENG LI GUANG-CAN GUO CAS Key Laboratory of Quantum Information University of Science and Technology of ChinaHefei 230026China College of Physics and Optoelectronic Engineering Ocean University of ChinaQingdao 266100China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of ChinaHefei 230026China Hefei National Laboratory University of Science and Technology of ChinaHefei 230088China Electric Power Research Institute State Grid Anhui Electric Power Co.Ltd.Hefei 230601China Institute of Systems and Information Engineering University of TsukubaIbaraki 305-8573Japan Center for Artificial Intelligence Research University of TsukubaIbaraki 305-8577Japan Graduate School of Science and Technology Gunma UniversityGunma 371-8510Japan Institute for Quantum Studies Chapman UniversityOrangeCalifornia 92866USA JST PRESTO Saitama 332-0012Japan

Entanglement has been recognized as being crucial when implementing various quantum information ***, quantifying entanglement for an unknown quantum state requires nonphysical operations or post-processing measurement data. For example, evaluation methods via quantum state tomography require vast amounts of measurement data and likely estimation.

关键词： estimation quantum angle

Epidemic threshold influenced by non-pharmaceutical interventions in residential university environments

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Chinese Physics B 2024年第2期33卷 551-556页

作者：卢泽超赵生妹束华中巩龙延 Institute of Signal Processing and Transmission Nanjing University of Posts and TelecommunicationsNanjing 210003China College of Science Nanjing University of Posts and TelecommunicationsNanjing 210003China

The control of highly contagious disease spreading in campuses is a critical *** residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining halls and *** move from one place to *** simulate such environments,we propose an agent-based susceptible–infected–recovered model with time-varying heterogeneous contact *** close environments,maintaining physical distancing is the most widely recommended and encouraged non-pharmaceutical *** can be easily realized by using larger classrooms,adopting staggered dining hours,decreasing the number of students per dorm and so *** real-world influence remains *** numerical simulations,we obtain epidemic *** effect of such countermeasures on reducing the number of disease cases is also quantitatively evaluated.

关键词： epidemic threshold susceptible-infected-recovered model non-pharmaceutical interventions time-varying heterogeneous contact networks