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Hypothyroidism affects astrocyte and microglial morphology in type 2 diabetes

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Neural Regeneration Research 2013年第26期8卷 2458-2467页

作者： Sung Min nam yo na kim Dae young yoo Sun Shin Yi Jung Hoon Choi In Koo Hwang Je Kyung Seong Yeo Sung yoon Department of Anatomy and Cell Biology College of Veterinary Medicine Research Institute for Veterinary Science Seoul National University Department of Biomedical Laboratory Science College of Biomedical Sciences Soonchunhyang University Department of Anatomy College of Veterinary Medicine Kangwon National University

In the present study, we investigated the effects of hypothyroidism on the morphology of astrocytes and microglia in the hippocampus of Zucker diabetic fatty rats and Zucker lean control rats. To induce hypothyroidism, Zucker lean control and Zucker diabetic fatty rats at 7 weeks of age orally received the vehicle or methimazole, an anti-thyroid drug, treatment for 5 weeks and were sacrificed at 12 weeks of age in all groups for blood chemistry and immunohistochemical staining. In the me- thimazole-treated Zucker lean control and Zucker diabetic fatty rats, the serum circulating triiodo- thyronine （T3） and thyroxine （＇I＂4） levels were significantly decreased compared to levels observed in the vehicle-treated Zucker lean control or Zucker diabetic fatty rats. This reduction was more prominent in the methimazole-treated Zucker diabetic fatty group. Glial fibrillary acidic protein im- munoreactive astrocytes and ionized calcium-binding adapter molecule 1 （Iba-1）-immunoreactive microglia in the Zucker lean control and Zucker diabetic fatty group were diffusely detected in the hippocampal CA1 region and dentate gyrus. There were no significant differences in the glial fibril- lary acidic protein and Iba-1 immunoreactivity in the CA1 region and dentate gyrus between Zucker lean control and Zucker diabetic fatty groups. However, in the methimazole-treated Zucker lean control and Zucker diabetic fatty groups, the processes of glial fibrillary acidic protein immunoreac- tive astrocytes and Iba-1 immunoreactive microglia, were significantly decreased in both the CA1 region and dentate gyrus compared to that in the vehicle-treated Zucker lean control and Zucker diabetic fatty groups. These results suggest that diabetes has no effect on the morphology of as- trocytes and microglia and that hypothyroidism during the onset of diabetes prominently reduces the processes of astrocytes and microglia.

关键词： neural regeneration astrocytes microglia diabetes hypothyroidism complications thyroid hormone obesity methimazole Zucker diabetic fatty rat grants-supported paper neuroregeneration

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Maximizing biomass utilization: An integrated strategy for coproducing multiple chemicals

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Journal of Energy Chemistry 2025年第1期100卷 180-191页

作者： Byeongchan Ahn Sua Jo Jonggeol na J.Jay Liu young-Ju kim Wangyun Won Department of Chemical and Biological Engineering Korea University Department of Chemical Engineering (Integrated process) Kyung Hee University Department of Chemical Engineering and Materials Science Ewha Womans University Department of Chemical Engineering Pukyong National University Resources Engineering Plant Research Department Korea Institute of Geoscience and Mineral Resources

Lignocellulosic biomass is one of the viable solutions to alleviate the global warming. However, the limited utilization of biomass majorly focused on cellulose and hemicellulose restricts the economic and environmental feasibilities. To cope with this issue, we proposed an integrated process of co-producing 1,6-hexanediol（1,6-HDO） with tetrahydrofuran and adipic acid from biomass, referred to as Strategy A. To compare the impacts of lignin upgrading and feedstock, Strategy B, which co-produces tetrahydrofuran alone, and Strategy C, which is the traditional route to produce 1,6-HDO from fossil fuels, were used. Heat networks are also designed to reduce operating costs and indirect carbon emissions due to energy consumption, saving 87% and 83% of the heat and cooling requirements, respectively, in Strategy A. The market competitiveness of Strategy A was evaluated by determining the minimum selling price through techno-economic analysis, and sustainability was thoroughly investigated by quantifying the environmental impacts through both midpoint and endpoint life-cycle assessments（LCAs）.Strategy A was found to be the most favorable both economically（USRDSCHARDOLLAR3,402/ton） and environmentally（-26.9 kg CO2eq.）. This indicates that lignin valorization is not only economically but also environmentally preferred. Finally, changes in economic and environmental feasibilities depending on economic, process, and environmental parameters were investigated using sensitivity and uncertainty analyses. The results of these analyses provide valuable insight into bio-based chemical production.

关键词： Biorefinery Carbon mitigation Climate change Global warming Lignin utilization Bioeconomy

Effective Denoising Architecture for Handling Multiple Noises

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Computer Systems Science & Engineering 2023年第3期44卷 2667-2682页

作者： na Hyoun kim namgyu kim The Graduate School of Business IT of Kookmin University Seoul02707Korea

Object detection,one of the core research topics in computer vision,is extensively used in various industrial *** there have been many studies of daytime images where objects can be easily detected,there is relatively little research on nighttime *** the case of nighttime,various types of noises,such as darkness,haze,and light blur,deteriorate image ***,an appropriate process for removing noise must precede to improve object detection *** there are many studies on removing individual noise,only a few studies handle multiple noises *** this paper,we pro-pose a convolutional denoising autoencoder(CDAE)-based architecture trained on various types of *** also present various composing modules for each noise to improve object detection performance for night *** the exclusively dark(ExDark)Image dataset,experimental results show that the Sequentialfiltering architecture showed superior mean average precision(mAP)compared to other architectures.

关键词： Object detection computer vision nighttime multiple noises convolutional denoising autoencoder

Potential Alzheimer’s disease therapeutic nano-platform: Discovery of amyloid-beta plaque disaggregating agent and brain-targeted delivery system using porous silicon nanoparticles

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Bioactive Materials 2023年第6期24卷 497-506页

作者： Jaehoon kim Hyeji Um na Hee kim Dokyoung kim Department of Biomedical Science Graduate SchoolKyung Hee UniversitySeoul02447Republic of Korea Medical Research Center for Bioreaction to Reactive Oxygen Species and Biomedical Science Institute Kyung Hee UniversitySeoul02447Republic of Korea Department of Anatomy and Neurobiology College of MedicineKyung Hee UniversitySeoul02447Republic of Korea Center for Converging Humanities Kyung Hee UniversitySeoul02447Republic of Korea KHU-KIST Department of Converging Science and Technology Kyung Hee UniversitySeoul02447Republic of Korea UC San Diego Materials Research Science and Engineering Center 9500 Gilman Drive La JollaCA92093USA

There has been a lot of basic and clinical research on Alzheimer’s disease(AD)over the last 100 years,but its mechanisms and treatments have not been fully *** some controversies,the amyloid-beta hypothesis is one of the most widely accepted causes of *** this study,we disclose a new amyloid-beta plaque disaggregating agent and an AD brain-targeted delivery system using porous silicon nanoparticles(pSiNPs)as a therapeutic nano-platform to overcome *** hypothesized that the negatively charged sulfonic acid functional group could disaggregate plaques and construct a chemical *** a result of the in vitro assay of amyloid plaques and library screening,we confirmed that 6-amino-2-naphthalenesulfonic acid(Ana)showed the highest efficacy for plaque disaggregation as a hit *** confirm the targeted delivery of Ana to the AD brain,a nano-platform was created using porous silicon nanoparticles(pSiNPs)with Ana loaded into the pore of pSiNPs and biotin-polyethylene glycol(PEG)surface *** resulting nano-formulation,named Biotin-CaCl2-Ana-pSiNPs(BCAP),delivered a large amount of Ana to the AD brain and ameliorated memory impairment of the AD mouse model through the disaggregation of amyloid plaques in the *** study presents a new bioactive small molecule for amyloid plaque disaggregation and its promising therapeutic nano-platform for AD brain-targeted delivery.

关键词： Alzheimer’s disease Plaques disaggregation nanotherapeutics Brain-targeted drug delivery Porous silicon nanoparticles

The Fitzpatrick-Neville-Type Algorithm for Multivariate Vector-Valued Osculatory Rational Interpolation

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Journal of Systems Science & Complexity 2015年第1期28卷 222-242页

作者： XIA Peng ZHANG Shugong LEI na kim Zhangyong School of Mathematics Liaoning University Automated Reasoning and Cognition Key Laboratory of Chongqing School of Mathematics Key Laboratory of Symbolic Computation and Knowledge Engineering(Ministry of Education)Jilin University

In this paper,the authors first apply the Fitzpatrick algorithm to multivariate vectorvalued osculatory rational *** based on the Fitzpatrick algorithm and the properties of an Hermite interpolation basis,the authors present a Fitzpatrick-Neville-type algorithm for multivariate vector-valued osculatory rational *** may be used to compute the values of multivariate vector-valued osculatory rational interpolants at some points directly without computing the interpolation function explicitly.

关键词： Fitzpatrick algorithm GrSbner basis module vector-valued osculatory rational interpolation.

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Fruit Ripeness Prediction Based on DNN Feature Induction from Sparse Dataset

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Computers, Materials & Continua 2021年第12期69卷 4003-4024页

作者： Wan Hyun Cho Sang Kyoon kim Myung Hwan na In Seop na Department of Statistics Chonnam National UniversityGwangju61186Korea Department of Electronics Eng. Mokpo National UniversityMuan58557Korea national Program of Excellence in Software Centre Chosun UniversityGwangju61452Korea

Fruit processing devices,that automatically detect the freshness and ripening stages of fruits are very important in precision ***,based on deep learning,many attempts have been made in computer image processing,to monitor the ripening stage of ***,it is timeconsuming to acquire images of the various ripening stages to be used for training,and it is difficult to measure the ripening stages of fruits accurately with a small number of *** this paper,we propose a prediction system that can automatically determine the ripening stage of fruit by a combination of deep neural networks(DNNs)and machine learning(ML)that focus on optimizing them in combination on several image ***,we used eight DNN algorithms to extract the color feature vectors most suitable for classifying them from the observed images representing each ripening ***,we applied seven ML methods to determine the ripening stage of fruits based on the extracted color ***,we propose an automatic prediction system that can accurately determine the ripeness in images of various fruits such as strawberries and tomatoes by a combination of the DNN and ML ***,we used the transfer learning method to train the proposed system on few image datasets to increase the training ***,we experimented to find out which of the various combinations of DNN and ML methods demonstrated excellent classification *** the experimental results,a combination of DNNs and multilayer perceptron,or a combination of DNNs and support vector machine or kernel support vector machine generally exhibited excellent classification ***,the combination of various DNNs and statistical classification models shows that the overall classification rate is ***,in the case of using tomato images,it was found that the classification rate for the combination of various DNNs and ML methods was generally similar to the results obtained

关键词： Ripening stage prediction deep neural network machine learning tomato strawberry small dataset

Voxelated opto-physically unclonable functions via irreplicable wrinkles

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Light(Science & Applications) 2023年第11期12卷 2378-2390页

作者： Kitae kim Se-Um kim Moon-young Choi Mohsin Hassan Saeed youngmin kim Jun-Hee na Department of Convergence System Engineering Chungnam National University99 Daehak-roYuseong-guDaejeon 34134Republic of Korea Department of Electrical and Information Engineering Seoul National University of Science&Technology232 Gongneung-roNowon-guSeoul 01811Republic of Korea Department of Electrical Electronicsand Communication Engineering EducationChungnam National University99 Daehak-roYuseong-guDaejeon 34134Republic of Korea Hologram Research Center Korea Electronics Technology InstituteWorld Cup buk-ro 54-gilMapo-guSeoul 03924Republic of Korea

The increased prevalence of the Internet of Things(IoT)and the integration of digital technology into our daily lives have given rise to heightened security risks and the need for more robust security *** response to these challenges,physical unclonable functions(PUFs)have emerged as promising solution,offering a highly secure method to generate unpredictable and unique random digital values by leveraging inherent physical ***,traditional PUFs implementations often require complex hardware and circuitry,which can add to the cost and complexity of the *** present a novel approach using a random wrinkles PUF(rw-PUF)based on an optically anisotropic,facile,simple,and cost-effective *** wrinkles contain randomly oriented liquid crystal molecules,resulting in a two-dimensional retardation map corresponding to a complex birefringence ***,our proposed technique allows for customization based on specific requirements using a spatial light modulator,enabling fast *** random wrinkles PUF has the capability to store multiple data sets within a single PUF without the need for physical ***,we introduce a concept called‘polyhedron authentication,’which utilizes three-dimensional information storage in a voxelated random wrinkles *** approach demonstrates the feasibility of implementing high-level security technology by leveraging the unique properties of the rw-PUF.

关键词： hardware functions utilize

A BPR-CNN Based Hand Motion Classifier Using Electric Field Sensors

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Computers, Materials & Continua 2022年第6期71卷 5413-5425页

作者： Hunmin Lee Inseop na Kamoliddin Bultakov youngchul kim Department of Computer Science Georgia State UniversityAtlanta30302USA nat’l Program of Excellence in Software Centre Chosun UniversityGwangju61452Korea Department of Computer Inf.&Communication Eng. Chonnam Nat’l Univ.Gwangju61186Korea

In this paper,we propose a BPR-CNN(Biometric Pattern Recognition-Convolution Neural Network)classifier for hand motion classification as well as a dynamic threshold algorithm for motion signal detection and extraction by EF(Electric Field)***,an EF sensor or EPS(Electric Potential Sensor)system is attracting attention as a next-generationmotion sensing technology due to low computation and price,high sensitivity and recognition speed compared to other sensor ***,it remains as a challenging problem to accurately detect and locate the authentic motion signal frame automatically in real-time when sensing body-motions such as hand motion,due to the variance of the electric-charge state by heterogeneous surroundings and operational *** hinders the further utilization of the EF sensing;thus,it is critical to design the robust and credible methodology for detecting and extracting signals derived from the motion movement in order to make use and apply the EF sensor technology to electric consumer products such as mobile *** this study,we propose a motion detection algorithm using a dynamic offset-threshold method to overcome uncertainty in the initial electrostatic charge state of the sensor affected by a user and the surrounding environment of the *** method is designed to detect hand motions and extract its genuine motion signal frame successfully with high *** setting motion frames,we normalize the signals and then apply them to our proposed BPR-CNN motion classifier to recognize their motion *** experiment and analysis show that our proposed dynamic threshold method combined with a BPR-CNN classifier can detect the hand motions and extract the actual frames effectively with 97.1%accuracy,99.25%detection rate,98.4%motion frame matching rate and 97.7%detection&extraction success rate.

关键词： BPR-CNN dynamic offset-threshold method electric potential sensor electric field sensor multiple convolution neural network motion classification

Suppression of DRR1 results in the accumulation of insoluble ubiquitinated proteins,which impairs drought stress tolerance

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Journal of Integrative Plant Biology 2021年第3期63卷 431-437页

作者： Seong Gwan Yu na Hyun Cho Jong Hum kim Tae Rin Oh Woo Taek kim Department of Systems Biology and Division of Life Science Yonsei UniversitySeoul 03722Korea Institute of Life Science and Biotechnology Yonsei UniversitySeoul 03722Korea

Drought stress has detrimental effects on *** the abscisic acid(ABA)-mediated drought response is well established,defensive mechanisms to cope with dehydration-induced proteotoxicity have been rarely ***1 was identified as an Arabidopsis drought-induced gene encoding an ER-localized RING-type E3 Ub *** of DRR1 markedly reduced tolerance to drought and proteotoxic stress without altering ABA-mediated germination and stomatal *** dehydration-induced insoluble ubiquitinated protein accumulation was more obvious in DRR1 loss-of-function plants than in wild-type *** results suggest that DRR1 is involved in an ABA-independent drought stress response possibly through the mitigation of dehydration-induced proteotoxic stress.

关键词： Arabidopsis drought stress E3 ligase proteotoxicity ubiquitination

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