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Juvenile hormone membrane signaling phosphorylates USP and thus potentiates 20-hydroxyecdysone action in drosophila

Science Bulletin 2022年第2期67卷 186-197,M0004页

作者： Yue Gao Suning Liu Qiangqiang Jia Lixian Wu dongwei Yuan Emma Y.Li Qili Feng Guirong Wang Subba r.Palli Jian Wang Sheng Li Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology Institute of Insect Science and Technology&School of Life SciencesSouth China Normal UniversityGuangzhou 510631China Guangmeiyuan R&D Center Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied TechnologySouth China Normal UniversityMeizhou 514779China International Department The Afﬁliated High School of South China Normal UniversityGuangzhou 510631China Lingnan Guangdong Laboratory of Modern Agriculture Genome Analysis Laboratory of the Ministry of AgricultureAgricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhen 518120China Department of Entomology College of AgricultureFood and EnvironmentUniversity of KentuckyLexington 40546USA Department of Entomology University of MarylandCollege Park 20742USA

Juvenile hormone(JH) and 20-hydroxyecdysone(20 E) coordinately regulate development and metamorphosis in insects. Two JH intracellular receptors, methoprene-tolerant(Met) and germ-cell expressed(Gce), have been identified in the fruit fly drosophila melanogaster. To investigate JH membrane signaling pathway without the interference from JH intracellular signaling, we characterized phosphoproteome profiles of the Met gce double mutant in the absence or presence of JH in both chronic and acute *** through a potential receptor tyrosine kinase and phospholipase C pathway, JH membrane signaling activated protein kinase C(PKC) which phosphorylated ultraspiracle(USP) at Ser35, the PKC phosphorylation site required for the maximal action of 20 E through its nuclear receptor complex Ec rUSP. The usp;mutant, in which Ser was replaced with Ala at position 35 by genome editing, showed decreased expression of Halloween genes that are responsible for ecdysone biosynthesis and thus attenuated 20 E signaling that delayed developmental timing. The usp;mutant also showed lower Yorkie activity that reduced body size. Altogether, JH membrane signaling phosphorylates USP at Ser35 and thus potentiates 20 E action that regulates the normal fly development. This study helps better understand the complex JH signaling network.

关键词： Juvenile hormone receptor tyrosine kinase Phosphoproteomics USP 20-Hydroxyecdysone action Yorkie activity

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deep Learning for Predictive Forecasts and Brain Imaging in Memory Loss diseases

Deep Learning for Predictive Forecasts and Brain Imaging in ...

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Communication, Computing and Energy Efficient Technologies (I3CEET), International Conference on

作者： P Arunachalam Vaibhav C. Gandhi Jalpa Bhatt Tushar desai S. Surendran Nandhini T J Department of Biomedical Engineering VelTech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Department of Computer Engineering Madhuben and Bhanubhai Patel Institute of Technology (MBIT) Constitute College of CVM University Anand Gujarat India Krishna School of Emerging Technology and Applied Research Drs. Kiran & Pallavi Patel Global University Vadodara Gujarat India Department of Computer Science and Engineering Tagore Engineering College Chennai Tamil Nadu India Department of Computer Science and Engineering Saveetha School of Enginnering Saveetha Institute of Medical and Technical Science – SIMATS Saveetha University Chennai India

ISBN: (数字)9798331541583

ISBN: (纸本)9798331541590

Because deep learning is so adept at finding patterns in complex, high-dimensional data, it has revolutionized computer vision, beating traditional machine learning models. The development of brain imaging technology led to extensive multim…OrIZATIONS: deep learning algorithms, Alzheimer's illness, and classification This chapter presents a review of recent neuroimaging studies that used deep learning techniques to enhance Ad classification and evaluation. Articles Published between January 2013 and July 2018 (searched on Pubmed and Google Scholar) Alzheimer's disease deep Learning Following a review of the articles, the findings were rated based on the classification technique and the kind of neuroimaging data utilized in each research. Twelve of the sixteen included research exclusively used deep learning models (CNN for eleven [5] – [14] and Bidirectional Long Short-Term Memory networks—Bi-LSTM for one study); the other four studies mixed classical machine learning with deep learning techniques [1] - [4]. The best accurate diagnosis result was obtained when these multimodal techniques were combined with biomarkers found in cerebrospinal fluid (used for further investigations). deep learning algorithms have a lot of promise for the diagnostic criteria used to classify Ad since they are getting more efficient. Understanding Ad is still in its early stages, but deep learning and explainable technologies like these may help shed more light on the symptoms of the illness.

关键词： deep learning Neuroimaging Training Machine learning algorithms reviews Prediction algorithms Brain modeling Classification algorithms Alzheimer's disease Unsupervised learning

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Investigation of Thermal Characteristics of Turbulent Non-Premixed Flames in a Conical Bluff Body Using ridge and Support Vector regressor Algorithms

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Journal of Thermal Science and Engineering Applications 2025年第4期17卷 041002页

作者： Quadros, Jaimon dennis Mogul, Ibtisam Ata, Alper Bedii Ozdemir, I. Mohin, Ma Department of Mechanical Engineering University of Bolton RAK Academic Center Ras Al Khaimah 16038 UAE Centre for Applied Computer Science School of Creative Technologies University of Bolton Deane Road Bolton BL3 5AB UK R&D Heating Alarko-Carrier San. ve Tic. A.S. Sahabettin Bilgisu Cad Gebze Organize Sanayi Bolgesi (GOSB) Gebze Kocaeli 41480 Turkey Fluids Group Faculty of Mechanical Engineering Istanbul Technical University Gumussuyu Istanbul 34437 Turkey Department of Mechanical Engineering School of Engineering University of Bolton Deane Road Bolton BL3 5AB UK

The current work aims to develop computational models for the thermal characteristics of turbulent CH4flames for varying burner dimensions. This study develops a platform for data-driven analysis of temperature prediction of turbulent non-premixed flames, in which the influence of flow and geometric parameters, including burner head diameter (d), half cone angles (α), and co-flow air velocity (Ucf), have been considered. The algorithms used were ridge regressor (rr), linear regressor (Lr), and three variations of support vector regression (SVr): SVr with a linear kernel (SVr-Lr), SVr with a radial basis function (SVr-rBF), and SVr with a polynomial kernel (SVr-Poly). The performance of each computational model was evaluated and contrasted based on several metrics: mean absolute error, regression coefficient (r2), mean absolute percentage error, and mean Poisson deviance. From the modeling of the output data, it was observed that the SVr-rBF predictions were more accurate compared to those from the other algorithms, as it achieved the highest training value of 0.955. The testing predictions of rr, SVr-Lr, SVr-rBF, and SVr-Poly algorithms were also robust, withr2values ranging between 0.91 and 0.94. It is, therefore, established that these computational models are effectively suited for predicting sensitive turbulent CH4flame characteristics based on varying input factors.

关键词： Support vector machines combustion and reactive flows Turbulence Flames Testing energy systems support vector regression Errors velocity Modeling temperature Temperature non-premixed flames Algorithms

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Enhanced tumor targeting with near-infrared light-activated indocyanine green encapsulated in covalent organic framework for combined photodynamic therapy (PdT) and photothermal therapy (PTT)

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dyes and Pigments 2024年 221卷

作者： Thankachan, darieo Anbazhagan, rajeshkumar Tsai, Hsieh Chih dinh, Van Thi Thuy Gebrie, Hailemichael Tegenu Kitaw, Sintayehu Leshe Ahmed, Yohannis Wondwosen Anley, Beyadgalem Endawoke Liao, Yu-Shu Chen, Wei-Liang Chen, Jem-Kun Department of Materials Science and Engineering National Taiwan University of Science and Technology 43 Sec. 4 Keelung Road Taipei106 Taiwan Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology Taipei106 Taiwan R&D Centre for Membrane Technology Chung Yuan University Taoyuan320 Taiwan Division of Gastroenterology and Hepatology Department of Internal Medicine Chung Shan Medical University Hospital Taichung402 Taiwan Department of Chemistry College of Natural and Computational Sciences University of Gondar P.O. Box 196 Gondar Ethiopia

Covalent organic framework (COF), a new emerging class of crystalline porous polymeric networks with reversible covalent bonds are a better smart material in Nano medicine in this regard. 1,3,5-Triformylbenzene (TFB) and 2,5-Bis(methylsulfonyl)-1,4-diaminobenzene (BMSdAB) are used to develop a uniform shaped covalent organic framework at room temperature (rT-USCOF). In order to achieve the PTT and PdT effect in rT-USCOF, near infrared photosensitizer, photothermal and fluorescence agent, indocyanine green (ICG) was encapsulated. Moreover, enhanced loading content of ICG in I rT-USCOF to produce II rT-USCOF followed by stabilize with hyaluronic acid designed in order to reduce drug leakage and increase carrier stability. The II rT-USCOF-HA exhibits an increased encapsulation efficiency of 57.75% and a drug loading capacity of 53.59%. The developed system shows an 80% ICG release upon exposure to NIr 808-laser in acidic pH relative to the one without light irradiation proved the effective structural changes under light cause drug release. The newly developed II rT-USCOF-HA shows excellent biocompatibility against NIH 3T3 cell lines and CT2A cell lines under dark. Whereas, upon irradiation with NIr 808 nm laser, the system kills more than 70% of the cells and cellular uptake studies also proved the same. Finally, flow cytometry analysis confirmed, the II-rT-USCOF-HA treated with CT2A cell lines shows an early apoptosis cell population of 1.95%, a late apoptosis rate of 1.24% and a necrotic cell death of 4.77%, which are significantly greater than the free ICG treated groups. The singlet oxygen production followed by thermal ablation of tumor cells by the developed system further demonstrates its efficacy as a PdT/PTT probe. © 2023 Elsevier Ltd

关键词： Photodynamic therapy

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Therapeutic potential of fucoidan derived from Sargassum wightii greville in diabetic encephalopathy – behavioural, biochemical, histopathological and histochemical evidences

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Phytomedicine Plus 2021年第1期1卷 100011-100011页

作者： ramu, Sathiya Anbu, Jayaraman Krishnaraj, Kaliaperumal Department of Pharmacology Faculty of Pharmacy Ramaiah University of Applied Sciences Karnataka Bengaluru 560054 India Formulation R&D Himalaya Drug Company Karnataka Bengaluru India

Background: Brown seaweeds are the most intensely studied type of seaweeds being composed of potentially bioactive polysaccharides such as fucoidan. Fucoidan from Sargassum wightii Greville (S. wightii) has been reported to possess α-d-glucosidase inhibitory activity. However, there are no scientific data available regarding the evaluation of fucoidan derived from S. wightii in diabetes mellitus induced cognitive dysfunction. Purpose: The present work studies the protective effect of fucoidan isolated from S. wightii against diabetic encephalopathy. Methodology: Streptozotocin (65 mg/kg, i.p.) was used to induce diabetic encephalopathy and animals were subjected to behavioural analysis including Morris water maze, open field and light dark discrimination test. Biochemical, histopathology and histochemical studies were carried out to validate the therapeutic potential of fucoidan in diabetic encephalopathy. results: Streptozotocin (65 mg/kg, i.p) treated diabetic animals showed significant cognitive deficits with a poor performance in behavioural analysis. There was also a significant increase in hippocampal MdA, nitrite, AGEs, AChE activity and a decrease in GSH, SOd in disease control which is correlated to cognitive deficits. Elevated level of Aβ protein and Tau protein indicated the neuronal damage in hippocampus by streptozotocin. Treatment with fucoidan 100 and 200 mg/kg significantly combated behavioural deficits, oxidative stress and amyloid burden. Histopathology of pancreas revealed the protective effect of fucoidan against streptozotocin induced diabetes mellitus. Congo red staining of cerebral cortex and hippocampus further strengthened the neuroprotective role of fucoidan. Conclusion: Thus, it may be suggested that fucoidan showed protective effect against diabetes induced cognitive dysfunction. © 2020 The Author(s)

关键词： diabetic encephalopathy Fucoidan Sargassum wightii

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reactive seeding growth of cobalt-doped MIL-88B(Fe) on Al2O3 membrane for phenol removal in a photocatalytic membrane reactor

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Journal of Membrane Science 2023年第1期680卷

作者： Hou, Long-Bin Catherine, Hepsiba Niruba Harada, Kazuki Yoshida, Masaaki Chen, Yu-Lin Hu, Chechia Department of Chemical Engineering National Taiwan University of Science and Technology Daan Dist. Taipei City106 Taiwan Applied Chemistry Graduate School of Sciences and Technology for Innovation Yamaguchi University Ube Yamaguchi755-8611 Japan Yamaguchi University Ube Yamaguchi755-8611 Japan R&D Center for Membrane Technology Chung Yuan Christian University Chungli Dist. Taoyuan City320 Taiwan

In this study, cobalt-doped MIL-88B(Fe) (xCoMIL-88B(Fe)) was successfully synthesized and grown on an Al2O3 support. The cobalt doping of MIL-88(Fe) not only enhanced its visible-light absorption but also improved free electron–hole pair separation. On adding peroxymonosulfate (PMS), 5CoMIL-88B(Fe) powder demonstrated superior photocatalytic phenol removal than that without the PMS or catalyst. The reactive seeding growth of cobalt-doped MIL-88B(Fe) was employed to prepare a 5CoMIL-88B(Fe) membrane coupled with a filtration module to produce a photocatalytic membrane reactor (PMr). The permeate flux of the photocatalytic membrane reactor (PMr) was approximately 2900–4000 L m−2 h−1 bar−1 (LMH), which demonstrated over 90% phenol removal efficiency and exhibited high stability, reusability, recyclability, and high photocatalytic activity for phenol degradation over 10 cycles utilizing 5CoMIL-88B(Fe)@Al2O3 membrane with PMS. This is the first study to demonstrate a cobalt-doped MIL-88B(Fe) membrane through the reactive seeding method for a PMr system, which is an effective and sustainable process for wastewater treatment. © 2023 Elsevier B.V.

关键词： Phenols

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Smart Soft Sensor for Froth flotation quality monitoring using pre-trained feature extractor and Vision Transformer ViT

Smart Soft Sensor for Froth flotation quality monitoring usi...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Oussama Hasidi Ahmed Bendaouia El Hassan Abdelwahed El Alaoui-Chrifi Moulay Abdellah Abdelmalek Boussetta Intissar Benzakour François Bourzeix Kaotar Oubouhss LISI Laboratory Computer Science Departement UCA Analytics Lab Mohammed VI Polytechnic University Marrakech Morocco LISI Laboratory Computer Science Departement Cadi Ayyad University Marrakech Morocco R&D and Engineering center Reminex Managem Group Marrakech Morocco Analytics Lab Mohammed VI Polytechnic University Rabat Morocco Department of Electrical and Industrial Engineering National School of Applied Science UAE Tangier Morocco

Smart sensor technologies have gained prominence in the field of machine vision-based applications. Within this context, the utilization of machine vision systems for monitoring and controlling flotation plants has become increasingly prevalent. This paper addresses the critical need for accurate froth image classification in the development of an online machine vision-based control system. This paper explores the recent advancements in machine learning, with a focus on deep learning techniques. Specifically, it introduces the application of a Vision Transformer (VIT) model as an alternative to the traditional Convolutional Neural Network (CNN) for classifying froth images collected from an industrial lead flotation circuit. The results of this research demonstrate the remarkable performance of the ViT model, achieving an impressive overall accuracy rate of 96% when combined with pre-trained feature extractor models. This achievement surpasses the capabilities of conventional artificial neural network (CNN) classifiers of the state of art in terms of both accuracy and computational efficiency. These findings underscore the promising potential of deep learning neural networks in froth image analysis, highlighting their significance in the advancement of smart sensor-based machine vision systems within the field of flotation plant control.

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Position based in-motion alignment method for an auv

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Journal of Institute of Control, robotics and Systems 2020年第8期26卷 649-659页

作者： Choo, Jinwoo Lee, Gwonsoo Lee, Phil-Yeob Kim, Ho Sung Lee, Hansol Park, daegil Lee, Jihong Department of Mechatronics Engineering of Chungnam National University Korea Republic of Naval R&D Center Hanwha Systems Co. Ltd Korea Republic of Autonomous System R&D Center Korea Institute of Robot and Technology Convergence Korea Republic of

This paper describes a position based in-motion alignment method for underwater navigation of an AUV(Autonomous Underwater Vehicle). For proper estimation of the position and orientation of the AUV the navigation algorithm requires accurate initial values of its position and attitude. However, it is difficult to obtain exact attitude of the AUV in the marine environment, because of the AUV’s body drift caused by flow of the water. To avoid this, in general, the initial alignment is performed on shore using gravitational acceleration, with further launching of AUV into the water. In this paper, we propose the in-motion alignment algorithm that is able to accurately estimate azimuth in the marine environment. Additionally, the proposed method allows to correct velocity of the AUV. © ICrOS 2020.

关键词： Autonomous underwater vehicles

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Investigation of space group effects of High-Voltage spinel LiNi0.5Mn1.5O4: Unveiling the influences of fluorinate benzimidazole salt additive

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Chemical Engineering Journal 2024年 494卷

作者： Khotimah, Chusnul Yuwono, rio Akbar Wang, Fu-Ming Yang, Chun-Chen Wu, Nae-Lih dewi Sundari, Citra deliana Imawan, Arif Cahyo Chang, Ching-Kai Hsu, Ping-Hsuan Huang, Pin-Cheng Liu, Guan-Yi Tsai, Yi-de Haw, Shu-Chih Iskandar, Ferry Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology Taipei Taiwan Graduate Institute of Energy and Sustainability Technology National Taiwan University of Science and Technology Taipei Taiwan Department of Chemical Engineering Chung Yuan Christian University Taoyuan Taiwan R&D Center for Membrane Technology Chung Yuan Christian University Taoyuan Taiwan Department of Chemical Engineering Ming-Chi University of Technology New Taipei City Taiwan Department of Chemical Engineering National Taiwan University Taipei Taiwan Department of Chemistry Education UIN Sunan Gunung Djati Bandung Bandung Indonesia National Synchrotron Radiation Research Center Hsinchu Taiwan Research Center of Nanoscience and Nanotechnology Institut Teknologi Bandung Jl. Ganesha 10 Bandung40132 Indonesia

Spinel LiNi0.5Mn1.5O4 (LNMO) is one of the attractive cathodes due to several advantages such as Co-free for low cost and high operating voltage (∼5 V). Normally, there are Fd3¯m and P4332 space group types of LNMOs. However, both LNMOs suffer phase segregation at intragranular side which affects the lithium diffusion pathway and structural degradation during cycles. On the other hand, Jahn-Teller distortion on Mn3+ as well as HF effects from electrolyte oxidation at high voltage window triggered lead Mn dissolution from LNMO that causes performance fade. In this work, a new salt is developed, lithium 1-fluoro benzimidazole (Li-1FB) for LNMO with two different space groups. Ex-situ Xrd results show the Li-1FB postpones the formation of intermediate phase transition on both LNMOs at different states of charge. In addition, 1H NMr analysis reveals the Li-1FB salt can prevent HF formation by the N-Li functional group of imidazole ring thus inhibits Mn dissolution on both LNMOs after cycling. Furthermore, the Li-1FB salt is suitable to improve cycle performance of both LNMOs in half-cell (Li metal as anode) and full cell (graphite as anode) applications. This new salt provides dramatic improvements, and it is suitable for further high-energy applications. © 2024

关键词： Lithium

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Enhancing air treatment through controlled fabrication of transition metal-doped titanium dioxide nanocomposites for photocatalytic toluene degradation

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Chemosphere 2024年 351卷 141261页

作者： Ly, Huyen Ngoc Parasuraman, Vijayarohini Lee, Hojae Sheraz, Mahshab Anus, Ali Lee, Woo ram Kim, Seungdo Department of Chemistry Hallym University Chuncheon 24252 South Korea Research Center for Climate Change and Energy Hallym University Chuncheon 24252 South Korea Nano-InnoTek Corporation 123 Digital-ro 26-gil Guro-gu Seoul South Korea Department of Chemistry and Institute of Applied Chemistry Hallym University Chuncheon 24252 South Korea Advanced Textile R&D Department Republic of Korea Institute of Industrial Technology (KITECH) Ansan-si 15588 South Korea Department of Chemistry Inha University Incheon 22212 South Korea

rapid industrial growth and urbanization have resulted in a significant rise in environmental pollution issues, particularly indoor air pollutants. As a result, it is crucial to design and develop technologies and/or catalysts that are not only cost-effective but also promising high performance and practical applicability. However, achieving this goal has been so far remained a challenging task. Herein, a series of transition metal M − TiO₂ (M = W, Fe, Mn) nanocrystals was prepared for photocatalytic degradation of volatile organic compounds (VOCs), i.e., toluene. Of the nanocomposites tested, W–TiO₂ showed significantly improved photocatalytic activity for VOC degradation under UV irradiation compared to the others. In particular, the optimized W dopant amount of 0.5 wt% resulted in the outstanding degradation performance of toluene (96%) for the obtained W–TiO₂(0.5%) nanocomposite. Moreover, W–TiO₂(0.5%) nanocomposite exhibited good stability for 32 h working under high toluene concentration (10 ppm) compared to the pristine TiO₂. The current work demonstrates the potential usage of M − TiO₂ nanocrystals, particularly W–TiO₂(0.5%), as a promising photocatalyst for efficient VOCs degradation. © 2024

关键词： Air pollutant treatment Photocatalyst regeneration Photochemical durability Toluene degradation Transition metal doped TiO2

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