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Protein Arginine Methyltransferase 1 Ablation in Motor Neurons Causes Mitochondrial Dysfunction Leading to Age-related Motor Neuron Degeneration with Muscle Loss

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Research 2024年第1期2023卷 637-649页

作者： Hyun-Kyung So Hyebeen Kim Jinwoo Lee Chang-Lim You Chae-Eun Yun Hyeon-Ju Jeong Eun-Ju Jin Yunju Jo dongryeol ryu Gyu-Un Bae Jong-Sun Kang Department of Molecular Cell Biology Sungkyunkwan University School of MedicineSuwonKorea Single Cell Network Research Center Sungkyunkwan University School of MedicineSuwonKorea Research Institute of Aging-Related Diseases AniMusCureInc.SuwonKorea Drug Information Research Institute Muscle Physiome Research CenterCollege of PharmacySookmyung Women’s UniversitySeoulKorea

Neuromuscular dysfunction is tightly associated with muscle wasting that occurs with age or due to degenerative diseases.However,the molecular mechanisms underlying neuromuscular dysfunction are currently unclear.Recent studies have proposed important roles of Protein arginine methyltransferase 1(Prmt1)in muscle stem cell function and muscle maintenance.In the current study,we set out to determine the role of Prmt1 in neuromuscular function by generating mice with motor neuron-specific ablation of Prmt1(mnKO)using Hb9-Cre.mnKO exhibited age-related motor neuron degeneration and neuromuscular dysfunction leading to premature muscle loss and lethality.Prmt1 deficiency also impaired motor function recovery and muscle reinnervation after sciatic nerve injury.The transcriptome analysis of aged mnKO lumbar spinal cords revealed alterations in genes related to inflammation,cell death,oxidative stress,and mitochondria.Consistently,mnKO lumbar spinal cords of sciatic nerve injury model or aged mice exhibited elevated cellular stress response in motor neurons.Furthermore,Prmt1 inhibition in motor neurons elicited mitochondrial dysfunction.Our findings demonstrate that Prmt1 ablation in motor neurons causes agerelated motor neuron degeneration attributing to muscle loss.Thus,Prmt1 is a potential target for the prevention or intervention of sarcopenia and neuromuscular dysfunction related to aging.

关键词： degeneration impaired prevention

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Bio-printing of aligned GelMa-based cell-laden structure for muscle tissue regeneration

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Bioactive Materials 2022年第2期7卷 57-70页

作者： Hanjun Hwangbo Hyeongjin Lee Eun-Ju Jin JaeYoon Lee Yunju Jo dongryeol ryu GeunHyung Kim Department of Biomechatronics Engineering College of Biotechnology and BioengineeringSungkyunkwan University(SKKU)Suwon16419Republic of Korea Department of Molecular Cell Biology Sungkyunkwan University School of Medicine(SKKU-SOM)Suwon16419Republic of Korea Biomedical Institute for Convergence at SKKU(BICS) Sungkyunkwan UniversitySuwon16419Republic of Korea

Volumetric muscle loss(VML)is associated with a severe loss of muscle tissue that overwhelms the regenerative potential of skeletal muscles.Tissue engineering has shown promise for the treatment of VML injuries,as evidenced by various preclinical trials.The present study describes the fabrication of a cell-laden GelMa muscle construct using an in situ crosslinking(ISC)strategy to improve muscle functionality.To obtain optimal biophysical properties of the muscle construct,two UV exposure sources,UV exposure dose,and wall shear stress were evaluated using C2C12 myoblasts.Additionally,the ISC system showed a significantly higher degree of uniaxial alignment and myogenesis compared to the conventional crosslinking strategy(post-crosslinking).To evaluate the in vivo regenerative potential,muscle constructs laden with human adipose stem cells were used.The VML defect group implanted with the bio-printed muscle construct showed significant restoration of functionality and muscular volume.The data presented in this study suggest that stem cell-based therapies combined with the modified bioprinting process could potentially be effective against VML injuries.

关键词： GelMa bio-ink in-situ crosslinking 3D bioprinting Myogenesis

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Longwave infrared multispectral image sensor system using aluminum-germanium plasmonic filter arrays Noor E

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Nano Research 2023年第7期16卷 10018-10025页

作者： Karishma Shaik Bryce Widdicombe Dechuan Sun Sam E John dongryeol ryu Ampalavanapillai Nirmalathas Ranjith R Unnithan Department of Electrical and Electronic Engineering University of MelbourneParkvilleVIC 3010Australia Department of Biomedical Engineering University of MelbourneParkvilleVIC 3010Australia Department of Infrastructure Engineering University of MelbourneParkvilleVIC 3010Australia

A multispectral camera records image data in various wavelengths across the electromagnetic spectrum to acquire additional information that a conventional camera fails to capture.With the advent of high-resolution image sensors and color filter technologies,multispectral imagers in the visible wavelengths have become popular with increasing commercial viability in the last decade.However,multispectral imaging in longwave infrared(LWIR,8-14μm)is still an emerging area due to the limited availability of optical materials,filter technologies,and high-resolution sensors.Images from LWIR multispectral cameras can capture emission spectra of objects to extract additional information that a human eye fails to capture and thus have important applications in precision agriculture,forestry,medicine,and object identification.In this work,we experimentally demonstrate an LWIR multispectral image sensor with three wavelength bands using optical elements made of an aluminum(Al)-based plasmonic filter array sandwiched in germanium(Ge).To realize the multispectral sensor,the filter arrays are then integrated into a three-dimensional(3D)printed wheel stacked on a low-resolution monochrome thermal sensor.Our prototype device is calibrated using a blackbody and its thermal output has been enhanced with computer vision methods.By applying a state-of-theart deep learning method,we have also reconstructed multispectral images to a better spatial resolution.Scientifically,our work demonstrates a versatile spectral thermography technique for detecting target signatures in the LWIR range and other advanced spectral analyses.

关键词： infrared plasmonics germanium(Ge) aluminum(Al) thermal optics longwave infrared(LWIR)multispectral system

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Estimation of Organic Matter Content in Coastal Soil Using Reflectance Spectroscopy

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Pedosphere 2016年第1期26卷 130-136页

作者： ZHENG Guanghui dongryeol ryu JIAO Caixia HONG Changqiao School of Geography and Remote Sensing Nanjing University of Information Science & Technology Department of Infrastructure Engineering University of Melbourne

Rapid determination of soil organic matter(SOM) using regression models based on soil reflectance spectral data serves an important function in precision agriculture. "Deviation of arch"(DOA)-based regression and partial least squares regression(PLSR)are two modeling approaches to predict SOM.However,few studies have explored the accuracy of the DOA-based regression and PLSR models.Therefore,the DOA-based regression and PLSR were applied to the visible near-infrared(VNIR) spectra to estimate SOM content in the case of various dataset divisions.A two-fold cross-validation scheme was adopted and repeated 10 000 times for rigorous evaluation of the DOA-based models in comparison with the widely used PLSR model.Soil samples were collected for SOM analysis in the coastal area of northern Jiangsu Province,China.The results indicated that both modelling methods provided reasonable estimation of SOM,with PLSR outperforming DOA-based regression in general.However,the performance of PLSR for the validation dataset decreased more noticeably.Among the four DOA-based regression models,a linear model provided the best estimation of SOM and a cutoff of SOM content(19.76 g kg^(-1)),and the performance for calibration and validation datasets was consistent.As the SOM content exceeded 19.76 g kg^(-1),SOM became more effective in masking the spectral features of other soil properties to a certain extent.This work confirmed that reflectance spectroscopy combined with PLSR could serve as a non-destructive and cost-efficient way for rapid determination of SOM when hyperspectral data were available.The DOA-based model,which requires only 3 bands in the visible spectra,also provided SOM estimation with acceptable accuracy.

关键词：土壤有机质含量滨海土壤反射光谱偏最小二乘回归回归模型高光谱数据估算精度估计

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