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Hypoglycemic activity of curcuma mangga val. Extract via modulation of GLUT4 and ppar-γ mrna expression in 3T3-L1 adipocytes

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Journal of Experimental Pharmacology 2020年 12卷 363-369页

作者： Pujimulyani, Dwiyati Yulianto, Wisnu Adi Setyowati, Astuti Arumwardana, Seila Kusuma, Hanna Sari Widya Sholihah, Ika Adhani Rizal, Rizal Widowati, Wahyu Maruf, Ali Faculty of Agroindustry University of Mercu Buana Yogyakarta Yogyakarta 55753 Indonesia Biomolecular and Biomedical Research Center Aretha Medika Utama Bandung 40163 Indonesia Biomedical Engineering Study Program Department of Electrical Engineering Faculty of Engineering University of Indonesia Jakarta 16424 Indonesia Medical Research Center Faculty of Medicine Maranatha Christian University Bandung 40164 Indonesia Key Laboratory for Biorheological Science and Technology of Ministry of Education State and Local Joint Engineering Laboratory for Vascular Implants Bioengineering College Faculty of Medicine Chongqing University Chongqing 400030 China

Background: There would be over 600 million people living with diabetes by 2040 as predicted by the World Health Organization. Diabetes is characterized by raised blood sugar and insulin resistance. Insulin regulates the influx of glucose into the cell by upregulating the glucose transporter type 4 (GLUT4) expression on the plasma membrane. Besides, PPAR-γ also controls the metabolism of glucose in adipose tissues. Curcuma mangga Val., denoted as C. mangga, is a native Indonesian medicinal plant that has many beneficial effects, including an antidiabetic potential. Purpose: In this research, we aimed to disclose the hypoglycemic activity of ethanol extract of C. mangga (EECM) in 3T3-L1 fibroblasts-derived adipocyte cells in regulating glucose uptake as confirmed by the GLUT4 and PPAR-γ gene expression. Methods: The uptake of glucose was determined using radioactive glucose, while the gene expression of GLUT4, PPAR-γ, and β-actin was quantified using mRNA segregation and real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR). Results: We discovered that EECM interventions (200 and 50 μg/mL) increased glucose uptake in lipid-laden 3T3-L1 cells by 14.75 and 8.86 fold compared to the control noninsulin, respectively (p < 0.05). At the same doses, they also increased GLUT4 mRNA expression by 8.41 and 11.18 fold compared to the control non-insulin, respectively (p < 0.05). In contrast, EECM interventions (200 and 50 μg/mL) showed lower levels of PPAR-γ mRNA expression compared to the control metformin, indicating the anti-adipogenic potentials of EECM. Conclusion: EECM showed hypoglycemic activity in lipid-laden 3T3-L1 cells by improving glucose ingestion into the cells, which was mediated by increased GLUT4 expression and downregulated PPAR-γ expression. © 2020 Pujimulyani et al.

关键词： 3T3-L1 adipocytes Curcuma mangga Val Glucose uptake GLUT4 PPAR-γ

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Polyvinyl chloride microplastics and drought co-exposure alter rice growth by affecting metabolomics and proteomics

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Science of the Total Environment 2024年 955卷 177002页

作者： Khan, Kiran Yasmin Ali, Barkat Ghani, Hafiz Usman Cui, Xiaoqiang Luo, Xiaohan Ali, Zeshan Ahmed, Waqar Tan, Jinglu Lysenko, Vladimir Guo, Ya Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi214122 China Food Science Research Institute National Agricultural Research Centre Islamabad44000 Pakistan Hebei Medical University Shijiazhuang050000 China School of Environmental Science and Engineering/Tianjin Key Lab of Biomass Waste Utilization Tianjin University Tianjin300072 China Ecotoxicology Research Program Institute of Plant and Environmental Protection National Agriculture Research Center Islamabad44000 Pakistan Department of Biomedical Biological & Chemical Engineering University of Missouri ColumbiaMO65211 United States Southern Federal University Academy of Biology and Biotechnology Rostov-on-Don344041 Russia International Joint Research Center for Intelligent Optical Sensing and Applications at Jiangnan University Wuxi214122 China

Microplastics, interacting with drought stress, have become threat to crops by altering soil environment. Currently, the effect of combined microplastic and drought stress on crop growth remain poorly understood. In this work, the mechanism of multi-stress responses was investigated under the exposure of polvinylchloride microplastic (PV) and drought (D) individually and in combination (DPV) on rice varieties Hanyou73 and Q280 through proteomics and metabolomic analysis. All treatments negatively affect chlorophyll content, antioxidant enzyme activities, rice grain composition, metabolome and proteomic profiling of both rice varieties. Full rice grain yield was decreased under all treatments except PV treatment in which it was increased in both rice varieties. DPV treatment shows the lowest grain yield and more adverse effects on metabolome by affecting glycerophospholipid metabolism, tryptophan metabolism and alanine, aspartate and glutamate metabolism. Soluble sugar contents were decreased in H73 but in Q280 increased by 159 % under DPV and 123 % in PV treatment, compared to their control group. The results from metabolomics illustrate that glycerophospholipid metabolism is commonly altered in both rice types under all treatments. PV and drought alone and in combination induce extensive alterations in proteomics of rice leaves especially impacting proteins related to binding, translation and photosynthetic process. The results reveal that PV and DPV treatments highly distort the abundance of metabolites and proteins in both rice types, demonstrating that microplastic toxicity effects on rice plants become more severe when combined with drought stress. © 2024 Elsevier B.V.

关键词： Drought Metabolite Polyvinyl chloride microplastic Protein Rice

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Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time

arXiv

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arXiv 2021年

作者： Zhu, Feng Sedler, Andrew R. Grier, Harrison A. Ahad, Nauman Davenport, Mark A. Kaufman, Matthew T. Giovannucci, Andrea Pandarinath, Chethan Neuroscience Graduate Program Emory University Center for Machine Learning Georgia Tech Computational Neuroscience Graduate Program The University of Chicago School of Electrical and Computer Engineering Georgia Tech Dept. of Organismal Biology and Anatomy The University of Chicago Neuroscience Institute The University of Chicago Joint Dept. of Biomedical Engineering UNC Chapel Hill NC State University UNC Chapel Hill Neuroscience Center Coulter Dept. of Biomedical Engineering Emory University Georgia Tech Dept. of Neurosurgery Emory University

Modern neural interfaces allow access to the activity of up to a million neurons within brain circuits. However, bandwidth limits often create a trade-off between greater spatial sampling (more channels or pixels) and the temporal frequency of sampling. Here we demonstrate that it is possible to obtain spatio-temporal super-resolution in neuronal time series by exploiting relationships among neurons, embedded in latent low-dimensional population dynamics. Our novel neural network training strategy, selective backpropagation through time (SBTT), enables learning of deep generative models of latent dynamics from data in which the set of observed variables changes at each time step. The resulting models are able to infer activity for missing samples by combining observations with learned latent dynamics. We test SBTT applied to sequential autoencoders and demonstrate more efficient and higher-fidelity characterization of neural population dynamics in electrophysiological and calcium imaging data. In electrophysiology, SBTT enables accurate inference of neuronal population dynamics with lower interface bandwidths, providing an avenue to significant power savings for implanted neuroelectronic interfaces. In applications to two-photon calcium imaging, SBTT accurately uncovers high-frequency temporal structure underlying neural population activity, substantially outperforming the current state-of-the-art. Finally, we demonstrate that performance could be further improved by using limited, high-bandwidth sampling to pretrain dynamics models, and then using SBTT to adapt these models for sparsely-sampled data. © 2021, CC BY-NC-SA.

关键词： Neurons

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Large animal models of cardiac ischemia-reperfusion injury:Where are we now?

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Zoological Research 2023年第3期44卷 591-603页

作者： Attaur Rahman Yuhao Li To-Kiu Chan Hui Zhao Yaozu Xiang Xing Chang Hao Zhou Dachun Xu Sang-Bing Ong Department of Medicine and Therapeutics Faculty of MedicineThe Chinese University of Hong Kong(CUHK)Hong Kong SARChina Centre for Cardiovascular Genomics and Medicine(CCGM) Lui Che Woo Institute Innovative MedicineThe Chinese University of Hong Kong(CUHK)Hong Kong SARChina College of Veterinary Sciences and Animal Husbandry Abdul Wali Khan University MardanMardanKhyber Pakhtunkhwa 23200Pakistan School of Biomedical Sciences CUHK-GIBH CAS Joint Laboratory on Stem Cell and Regenerative MedicineThe Chinese University of Hong Kong(CUHK)Hong Kong SARChina Institute for Tissue Engineering and Regenerative Medicine(iTERM) The Chinese University of Hong Kong(CUHK)Hong Kong SARChina SBS Core Laboratory CUHK Shenzhen Research InstituteShenzhenGuangdong 518172China Kunming Institute of Zoology–The Chinese University of Hong Kong(KIZ-CUHK)Joint Laboratory of Bioresources and Molecular Research of Common Diseases Hong Kong SARChina Shanghai East Hospital Key Laboratory of Arrhythmias of the Ministry of Education of ChinaSchool of Life Sciences and TechnologyTongji UniversityShanghai 200092China Guang’anmen Hospital China Academy of Chinese Medical SciencesBeijing 100053China Department of Cardiology Chinese People’s Liberation Army General HospitalBeijing 100853China Center for Cardiovascular Research and Alternative Medicine University of Wyoming College of Health SciencesLaramieWY 82071USA Department of Cardiology Shanghai Tenth People’s HospitalTongji University School of MedicineShanghai 200072China Hong Kong Hub of Paediatric Excellence(HK HOPE) Hong Kong Children’s Hospital(HKCH)Kowloon BayHong Kong SARChina CUHK Shenzhen Research Institute(SZRI) ShenzhenGuangdong 518172China Neural Vascularand Metabolic Biology Thematic Research ProgramSchool of Biomedical SciencesThe Chinese University of Hong Kong(CUHK)Hong Kong SARChina

Large animal models of cardiac ischemia-reperfusion are critical for evaluation of the efficacy of cardioprotective interventions prior to clinical ***,current cardioprotective strategies/interventions formulated in preclinical cardiovascular research are often limited to small animal models,which are not transferable or reproducible in large animal models due to different factors such as:(i)complex and varied features of human ischemic cardiac disease(ICD),which are challenging to mimic in animal models,(ii)significant differences in surgical techniques applied,and(iii)differences in cardiovascular anatomy and physiology between small versus large *** article highlights the advantages and disadvantages of different large animal models of preclinical cardiac ischemic reperfusion injury(IRI),as well as the different methods used to induce and assess IRI,and the obstacles faced in using large animals for translational research in the settings of cardiac IR.

关键词： Cardiovascular disorder Ischemic cardiac disease Ischemic-reperfusion injury Large animal model Myocardial infarction Translational gap

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Ti-6al-4v Intervertebral Fusion Cage with Compatible Stiffness, Enhanced Fatigue Life, and Osteogenic Differentiation

SSRN

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SSRN 2023年

作者： Wu, Yu-Jie Wang, Chi-Yun Feng, Kuei-Chih Chien, R.R. Mana-Ay, Haidee Kung, Shyang-Yih Hou, Kuang-Hua Tu, Chi-Shun Chen, Pin-Yi Lai, Po-Liang International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City24301 Taiwan Research Center for Intelligent Medical Devices Ming Chi University of Technology New Taipei City24301 Taiwan Department of Mechanical Engineering Ming Chi University of Technology New Taipei City24301 Taiwan Department of Physics Fu Jen Catholic University New Taipei City24205 Taiwan Bone and Joint Research Center Chang Gung Memorial Hospital Taoyuan City33305 Taiwan Department of Physics Silliman University Dumaguete City6200 Philippines Department of Mechanical Engineering Chang Gung University Taoyuan City33302 Taiwan

The 3D-printed Ti-6Al-4V intervertebral fusion cage is fabricated to be biocompatible with improved stiffness, fatigue life, and osteogenic differentiation, which are greatly enhanced by heat treatment and surface modification. The flexible cage’s life, which exceeds the standard dynamic fatigue requirement of 5x106 cycles based on the ASTM F2077 and F2267 test methods, is achieved by heat treatment at 800 ℃ in argon atmosphere, shot peening, and adjusting the α to β phase ratio to increase mechanical toughness. Surface modification via sandblasting and chemical etching removes the surface oxide layer and forms submicron pores on the surface of the cage, which significantly boosts cell proliferation, differentiation, and osteoblast mineralization. This work exhibits a novel design of Ti-6Al-4V intervertebral fusion cage with biocompatible stiffness, enhanced fatigue life, and improved osteogenic differentiation achieved by reducing residual stress, modifying surface micro-pores, and optimizing microstructure. © 2023, The Authors. All rights reserved.

关键词： Aluminum alloys

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Machine Learning for Improved Current Density Reconstruction from 2D Vector Magnetic Images

arXiv

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arXiv 2024年

作者： Reed, Niko R. Bhutto, Danyal Turner, Matthew J. Daly, Declan M. Oliver, Sean M. Tang, Jiashen Olsson, Kevin S. Langellier, Nicholas Ku, Mark J.H. Rosen, Matthew S. Walsworth, Ronald L. Department of Physics University of Maryland College ParkMD United States Quantum Technology Center University of Maryland College ParkMD United States Joint Quantum Institute University of Maryland College ParkMD United States Department of Biomedical Engineering Boston University BostonMA United States A. A. Martinos Center for Biomedical Imaging Massachusetts General Hospital CharlestownMA United States Department of Electrical and Computer Engineering University of Maryland College ParkMD United States The MITRE Corporation McLeanVA22102 United States Intelligence Community Postdoctoral Research Fellowship Program University of Maryland College ParkMD20742 United States Department of Physics Harvard University CambridgeMA United States Department of Materials Science and Engineering University of Delaware NewarkDE19716 United States Department of Physics and Astronomy University of Delaware NewarkDE19716 United States Harvard Medical School 25 Shattuck St. BostonMA United States

The reconstruction of electrical current densities from magnetic field measurements is an important technique with applications in materials science, circuit design, quality control, plasma physics, and biology. Analytic reconstruction methods exist for planar currents, but break down in the presence of high spatial frequency noise or large standoff distance, restricting the types of systems that can be studied. Here, we demonstrate the use of a deep convolutional neural network for current density reconstruction from two-dimensional (2D) images of vector magnetic fields acquired by a quantum diamond microscope (QDM). Trained network performance significantly exceeds analytic reconstruction for data with high noise or large standoff distances. This machine learning technique can perform quality inversions on lower SNR data, significantly reducing the data collection time and permitting reconstructions of weaker and three-dimensional current sources. © 2024, CC BY.

关键词： Magnetic fields

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Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time 21

Deep inference of latent dynamics with spatio-temporal super...

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Proceedings of the 35th International Conference on Neural Information Processing Systems

作者： Feng Zhu Andrew R. Sedler Harrison A. Grier Nauman Ahad Mark A. Davenport Matthew T. Kaufman Andrea Giovannucci Chethan Pandarinath Neuroscience Graduate Program Emory University Center for Machine Learning Georgia Tech Computational Neuroscience Graduate Program The University of Chicago School of Electrical and Computer Engineering Georgia Tech Dept. of Organismal Biology and Anatomy The University of Chicago and Neuroscience Institute The University of Chicago Joint Dept. of Biomedical Engineering UNC Chapel Hill and NC State University and UNC Chapel Hill Neuroscience Center and NC State/UNC Closed-Loop Engineering for Advanced Rehabilitation (CLEAR) Coulter Dept. of Biomedical Engineering Emory University and Georgia Tech and Dept. of Neurosurgery Emory University

ISBN: (纸本)9781713845393

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How Microbes Shape Their Communities? A Microbial Community Model Based on Functional Genes

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Genomics, Proteomics & Bioinformatics 2019年第1期17卷 91-105页

作者： Xiaoqing Jiang Xin Li Longshu Yang Chunhong Liu Qi Wang Weilai Chi Huaiqiu Zhu State Key Laboratory for Turbulence and Complex Systems Department of Biomedical Engineering College of Engineering Peking University Center for Quantitative Biology Peking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Biological (PTN) PhD Program and College of Life Sciences Peking University Center for Protein Science Peking University

Exploring the mechanisms of maintaining microbial community structure is important to understand biofilm development or microbiota dysbiosis. In this paper, we propose a functional gene-based composition prediction(FCP) model to predict the population structure composition within a microbial community. The model predicts the community composition well in both a low-complexity community as acid mine drainage(AMD) microbiota, and a complex community as human gut microbiota. Furthermore, we define community structure shaping(CSS) genes as functional genes crucial for shaping the microbial community. We have identified CSS genes in AMD and human gut microbiota samples with FCP model and find that CSS genes change with the conditions. Compared to essential genes for microbes, CSS genes are significantly enriched in the genes involved in mobile genetic elements, cell motility, and defense mechanisms, indicating that the functions of CSS genes are focused on communication and strategies in response to the environment factors. We further find that it is the minority, rather than the majority, which contributes to maintaining community structure. Compared to health control samples, we find that some functional genes associated with metabolism of amino acids, nucleotides, and lipopolysaccharide are more likely to be CSS genes in the disease group. CSS genes may help us to understand critical cellular processes and be useful in seeking addable gene circuitries to maintain artificial self-sustainable communities. Our study suggests that functional genes are important to the assembly of microbial communities.

关键词： Metagenomics Dynamics model Community structure Acid mine drainage Human gut microbiota

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SSD-KD: A Self-supervised Diverse Knowledge Distillation Method for Lightweight Skin Lesion Classification Using Dermoscopic Images

arXiv

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arXiv 2022年

作者： Wang, Yongwei Wang, Yuheng Lee, Tim K. Miao, Chunyan Wang, Z. Jane Joint NTU-WeBank Research Center on Fintech Nanyang Technological University Singapore Singapore Department of Electrical and Computer Engineering University of British Columbia VancouverBC Canada School of Biomedical Engineering University of British Columbia VancouverBC Canada Department of Dermatology and Skin Science University of British Columbia VancouverBC Canada Photomedicine Institute Vancouver Coast Health Research Institute VancouverBC Canada Cancer Control Research Program Bc Cancer VancouverBC Canada School of Computer Science and Engineering Nanyang Technological University Singapore Singapore

Skin cancer is one of the most common types of malignancy, affecting a large population and causing a heavy economic burdenworldwide. Over the last fewyears, computer-aided diagnosis has been rapidly developed and make great progress in healthcare and medical practices due to the advances in artificial intelligence, particularly with the adoption of convolutional neural networks. However, most studies in skin cancer detection keep pursuing high prediction accuracies without considering the limitation of computing resources on portable devices. In this case, the knowledge distillation (KD) method has been proven as an efficient tool to help improve the adaptability of lightweight models under limited resources, meanwhile keeping a high-level representation capability. To bridge the gap, this study specifically proposes a novel method, termed SSD-KD, that unifies diverse knowledge into a generic KD framework for skin diseases classification. Our method models an intra-instance relational feature representation and integrates it with existing KD research. A dual relational knowledge distillation architecture is self-supervisedly trained while the weighted softened outputs are also exploited to enable the student model to capture richer knowledge from the teacher model. To demonstrate the effectiveness of our method, we conduct experiments on ISIC 2019, a large-scale open-accessed benchmark of skin diseases dermoscopic images. Experiments show that our distilled lightweight model can achieve an accuracy as high as 85% for the classification tasks of 8 different skin diseases with minimal parameters and computing requirements. Ablation studies confirm the effectiveness of our intra- and inter-instance relational knowledge integration strategy. Compared with state-of-the-art knowledge distillation techniques, the proposed method demonstrates improved performances. To the best of our knowledge, this is the first deep knowledge distillation application for multi-diseases cl

关键词： Dermatology

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Bone changes in early inflammatory arthritis assessed with High-Resolution peripheral Quantitative Computed Tomography (HR-pQCT): A 12-month cohort study

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Revue du Rhumatisme (Edition Francaise) 2021年第6期88卷 450-458页

作者： Brunet, Scott C. Finzel, Stephanie Engelke, Klaus Boyd, Steven K. Barnabe, Cheryl Manske, Sarah L. McCaig Institute for Bone and Joint Health Cumming School of Medicine University of Calgary Calgary AB Canada Biomedical Engineering Graduate Program and Department of Radiology Cumming School of Medicine University of Calgary Calgary AB Canada Department of Rheumatology and Clinical Immunology Medical Center University of Freiburg Faculty of Medicine University of Freiburg Freiburg Germany Department of Medicine FAU University Erlangen-Nürnberg and Universitätsklinikum Erlangen Erlangen Germany Department of Medicine Cumming School of Medicine University of Calgary Calgary AB Canada Department of Community Health Sciences Cumming School of Medicine University of Calgary Calgary AB Canada

Objectifs: L'apparition d’érosions dans les arthropathies inflammatoires revêt une importance majeure car elles ont une incidence sur le pronostic et les décisions thérapeutiques. Notre étude visait à déterminer la sensibilité de la tomodensitométrie quantitative périphérique haute résolution (HR-pQCT) pour détecter des changements de la surface osseuse au cours du temps et identifier l'apparition d’érosions chez les patients présentant une arthrite inflammatoire précoce (AIP). Nous avons également exploré la contribution de facteurs de pronostic aux dommages osseux périarticulaires évalués par HR-pQCT dans l'année suivant le diagnostic. Méthodes: Quarante-six patients présentant des symptômes d'arthrites depuis moins d'un an et ayant reçu un diagnostic clinique d'arthrite inflammatoire ont passé un examen d'imagerie prospectif à l'inclusion et à 12 mois. Une HR-pQCT de la deuxième et de la troisième articulation MCP et des radiographies conventionnelles (RC) des mains et des pieds ont été réalisées. La largeur de l'interligne articulaire, la densité minérale osseuse totale (DMOt), la présence d’érosions et leur volume ont été évalués par HR-pQCT. La précision des analyses scan–rescan a été évaluée afin de définir un critère de plus petite variation significative (PPVS) au niveau individuel. Des analyses de régression ont exploré les facteurs de pronostic de progression des dommages osseux. Résultats: Nous n'avons pas constaté de changements significatifs au niveau du groupe concernant la largeur de l'interligne, la DMOt ou le volume des érosions. Jusqu’à 20 % d'articulations ont présenté des changements individuels supérieurs au critère PPVS pour la largeur d'interligne moyenne, la DMOt et le volume des érosions. L'HR-pQCT a détecté davantage d’érosions que la RC dans la 2e et la 3e MCP. Une durée des symptômes plus longue au moment du diagnostic a été faiblement associée (p < 0,10) à une largeur d'interligne minimale plus faible et à un écart-type d'interligne plu

关键词： Arthrite inflammatoire précoce Densité minérale osseuse Polyarthrite rhumatoïde Tomodensitométrie quantitative périphérique haute résolution (HR-pQCT) Érosions osseuses

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