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Diet,lipids,and antitumor immunity

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Cellular & Molecular Immunology 2022年第3期19卷 432-444页

作者： Hannah Prendeville lydia Lynch Trinity Biomedical Sciences Institute Trinity College DublinDublinIreland Brigham and Women’s Hospital Harvard Medical SchoolBostonMAUSA

Tumour growth and dissemination is largely dependent on nutrient *** has recently emerged that the tumour microenvironment is rich in a diverse array of lipids that increase in abundance with tumour progression and play a role in promoting tumour growth and ***,we describe the pro-tumorigenic roles of lipid uptake,metabolism and synthesis and detail the therapeutic potential of targeting lipid metabolism in ***,we highlight new insights into the distinct immunosuppressive effects of lipids in the tumour *** threaten an anti-tumour environment whereby metabolic adaptation to lipid metabolism is linked to immune ***,we describe the differential effects of commondietary lipids on cancer growth which may uncover a role for specific dietary regimens in association with traditional cancer *** the relationship between dietary lipids,tumour,and immune cells is important in the context of obesity which may reveal a possibility to harness the diet in the treatment of cancers.

关键词： Lipids cancer obesity β-oxidation anti-tumour immunity

Drugging IGF-1R in cancer: New insights and emerging opportunities

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Genes & Diseases 2023年第1期10卷 199-211页

作者： Panpan Wang Victor CY.Mak lydia WT.Cheung School of Biomedical Sciences Li Ka Shing Faculty of MedicineThe University of Hong KongHong Kong SARChina

The insulin-like growth factor(IGF)axis plays important roles in cancer development and *** type 1 IGF receptor(IGF-1R)is a key member in the IGF axis and has long been recognized for its oncogenic role in multiple cancer *** we review the occurrence of IGF-1R aberrations and activation mechanisms in cancers,which justify the development of anti-IGF-1R *** describe the therapeutic agents available for IGF-1R inhibition,with focuses on the recent or ongoing pre-clinical and clinical *** include antisense oligonucleotide,tyrosine kinase inhibitors and monoclonal antibodies which may be conjugated with cytotoxic ***,simultaneous targeting of IGF-1R and several other oncogenic vulnerabilities has shown early promise,highlighting the potential benefits of combination ***,we discuss the challenges in targeting IGF-1R so far and new concepts to improve therapeutic efficacy such as blockage of the nuclear translocationofIGF-1R.

关键词： Cancer IGF-1R Targeted therapy Metastasis Combination therapy

The role of LIN28B in tumor progression and metastasis in solid tumor entities

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Oncology Research 2023年第2期31卷 101-115页

作者： TABEA GEWALT KA-WON NOH lydia MEDER Department I of Internal Medicine Faculty of Medicine and University Hospital CologneUniversity of CologneCologneGermany Center for Molecular Medicine Cologne University of CologneCologneGermany Institute for Pathology Faculty of Medicine and University Hospital CologneUniversity of CologneCologneGermany Mildred Scheel School of Oncology Faculty of Medicine and University Hospital CologneUniversity of CologneCologneGermany

LIN28B is an RNA-binding protein that targets a broad range of microRNAs and modulates their maturation and *** normal conditions,LIN28B is exclusively expressed in embryogenic stem cells,blocking differentiation and promoting *** addition,it can play a role in epithelial-to-mesenchymal transition by repressing the biogenesis of let-7 *** malignancies,LIN28B is frequently overexpressed,which is associated with increased tumor aggressiveness and metastatic *** this review,we discuss the molecular mechanisms of LIN28B in promoting tumor progression and metastasis in solid tumor entities and its potential use as a clinical therapeutic target and biomarker.

关键词： Cancer Metastasis LIN28B Let-7 Stemness EMT Resistance

Blockchain state channels with compact states through the use of RSA accumulators

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Blockchain(Research and Applications) 2023年第1期4卷 71-89页

作者： lydia Negka Angeliki Katsika Georgios Spathoulas Vassilis Plagianakos Department of Computer Science and Biomedical Informatics University of Thessaly2-4 Papasiopoulou st.Lamia35131Greece Department of Information Security and Communication Technology Norwegian University of Science and Technology(NTNU)Mail Box 191GjøvikNO-2815Norway

One of the major concerns regarding currently proposed public blockchain systems relates to the feasible transaction processing *** is common for such systems to limit this rate to maintain the required levels of security and *** channels are an approach to overcome this limitation,as they aim to decrease the required on-chain transactions for a given application and thus indirectly increase the capacity(in terms of applications)of public blockchain *** the present paper,we propose a state channel design that,through the use of RSA accumulators,operates on a compact state *** scheme is optimal for applications whose state includes large sets of *** novel state channel design is presented by analysing all state channel operations and how they have to be *** security of the design is discussed,while a practical use case scenario regarding the use of the design for an on-chain asset(e.g.,non-fungible tokens)exchange application is also analysed.

关键词： Blockchain State channels Accumulators Layer 2 NFTs

Forecasting Future Trajectories with an Improved Transformer Network

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Computers, Materials & Continua 2023年第2期74卷 3811-3828页

作者： Wei Wu Weigong Zhang Dong Wang lydia Zhu Xiang Song School of Instrument Science and Engineering Southeast UniversityNanjing210000China Department of Mechanical Aerospace&Engineering North Carolina State UniversityRaleigh27695NCUSA School of Electronic Engineering Nanjing Xiaozhuang UniversityNanjing211171China

An increase in car ownership brings convenience to people’s ***,it also leads to frequent traffic *** forecasting surrounding agents’future trajectories could effectively decrease vehicle-vehicle and vehicle-pedestrian ***-short-term memory(LSTM)network is often used for vehicle trajectory prediction,but it has some shortages such as gradient explosion and low efficiency.A trajectory prediction method based on an improved Transformer network is proposed to forecast agents’future trajectories in a complex traffic *** realizes the transformation from sequential step processing of LSTM to parallel processing of Transformer based on *** performtrajectory predictionmore efficiently,a probabilistic sparse self-attention mechanism is introduced to reduce attention complexity by reducing the number of queried values in the attention *** or not(ACON)activation function is adopted to select whether to activate or not,hence improving model *** proposed method is evaluated on the publicly available benchmarks nextgeneration simulation(NGSIM)and ETH/*** experimental results indicate that the proposed method can accurately and efficiently predict agents’trajectories.

关键词： Trajectory prediction Transformer attention mechanism ACON activation intelligent perception

Leveraging Retinal Fundus Images with Deep Learning for Diabetic Retinopathy Grading and Classification

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Computer Systems Science & Engineering 2023年第8期46卷 1901-1916页

作者： Mohammad Yamin Sarah Basahel Saleh Bajaba Mona Abusurrah ELaxmi lydia Department of Management Information Systems Faculty of Economics and Administration King Abdulaziz UniversityP.O.Box 80201Jeddah21589Saudi Arabia Department of Business Administration King Abdulaziz UniversityP.O.Box 80201Jeddah21589Saudi Arabia Department of Management Information Systems College of Business AdministrationTaibah UniversityAl-MadinahSaudi Arabia Department of Computer Science and Engineering GMR Institute of TechnologyAndhra PradeshRajam 532127India

Recently,there has been a considerable rise in the number of diabetic patients suffering from diabetic retinopathy(DR).DR is one of the most chronic diseases and makes the key cause of vision loss in middle-aged people in the developed *** detection of DR becomes necessary for decreasing the disease severity by making use of retinal fundus *** article introduces a Deep Learning Enabled Large Scale Healthcare Decision Making for Diabetic Retinopathy(DLLSHDM-DR)on Retinal Fundus *** proposed DLLSHDM-DR technique intends to assist physicians with the DR decision-making *** the DLLSHDM-DR technique,image preprocessing is initially performed to improve the quality of the fundus ***,the DLLSHDM-DR applies HybridNet for producing a collection of feature *** retinal image classification,the DLLSHDM-DR technique exploits the Emperor Penguin Optimizer(EPO)with a Deep Recurrent Neural Network(DRNN).The application of the EPO algorithm assists in the optimal adjustment of the hyperparameters related to the DRNN model for DR detection showing the novelty of our *** assuring the improved performance of the DLLSHDMDR model,a wide range of experiments was tested on the EyePACS *** comparison outcomes assured the better performance of the DLLSHDM-DR approach over other DL models.

关键词： Decision making healthcare sector deep learning diabetic retinopathy emperor penguin optimizer

Task Offloading and Resource Allocation in IoT Based Mobile Edge Computing Using Deep Learning

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Computers, Materials & Continua 2023年第8期76卷 1463-1477页

作者： Ily s Abdullaev Natalia Prodanova KAruna Bhaskar ELaxmi lydia Seifedine Kadry Jungeun Kim Dean of the Faculty of Economics Department of Management and MarketingFaculty of EconomicsUrgench State UniversityUrganch220100Uzbekistan Basic Department Financial Control Analysis and Audit of Moscow Main Control DepartmentPlekhanov Russian University of EconomicsMoscow117997Russia Department of Computer Science and Engineering KL Deemed to UniversityVaddeswaramGunturAndhra PradeshIndia Department of Computer Science and Engineering GMR Institute of TechnologyAndhra PradeshRajamIndia Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjman346United Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea

Recently,computation offloading has become an effective method for overcoming the constraint of a mobile device(MD)using computationintensivemobile and offloading delay-sensitive application tasks to the remote cloud-based data *** city benefitted from offloading to edge *** a mobile edge computing(MEC)network in multiple *** comprise N MDs and many access points,in which everyMDhasM independent real-time *** study designs a new Task Offloading and Resource Allocation in IoT-based MEC using Deep Learning with Seagull Optimization(TORA-DLSGO)*** proposed TORA-DLSGO technique addresses the resource management issue in the MEC server,which enables an optimum offloading decision to minimize the system *** addition,an objective function is derived based on minimizing energy consumption subject to the latency requirements and restricted *** TORA-DLSGO technique uses the deep belief network(DBN)model for optimum offloading ***,the SGO algorithm is used for the parameter tuning of the DBN *** simulation results exemplify that the TORA-DLSGO technique outperformed the existing model in reducing client overhead in the MEC systems with a maximum reward of 0.8967.

关键词： Mobile edge computing seagull optimization deep belief network resource management parameter tuning

Early hemodynamic resuscitation of septic shock:what do the new Surviving Sepsis Campaign guidelines really provide?

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Journal of Intensive Medicine 2022年第1期2卷 1-2页

作者： Jean-Louis teboul Olfa Hamzaoui Service de Médecine Intensive-Réanimation Hôpital BicêtreAP-HPUniversitéParis-SaclayInserm S_999Le Kremlin-BicêtreFrance Service de Réanimation Polyvalente Hôpital Antoine BéclèreAP-HPUniversitéParis-SaclayClamartFrance

A new version of the Surviving Sepsis Campaign(SSC)guide-lines for sepsis and septic shock[1]has been published a few months *** this editorial,we aim to focus on similarities and differences between the 2021 and 2016 SSC guidelines,[2]in terms of hemodynamic *** first striking differ-ence concerns blood lactate *** is now suggested to guide resuscitation to decrease serum lactate but not normal-ize it as previously ***,as stated in an editorial by Hernandez and teboul,“since non-hypoperfusion-related causes of hyperlactatemia might predominate in an unknown number of patients,aiming at strictly normalizing lactate might lead to excessive resuscitation with inherent fluid and vasopressor over-load,and eventually to increased morbidity and mortality”.[3]In a recent multicenter randomized controlled trial in septic shock called ANDROMEDA-SHOCK,an early resuscitation strat-egy guided on capillary refill time(CRT)was shown to result in lesser organ dysfunction at 72 h than a strategy based on decrease in blood lactate.[4]In a subsequent Bayesian analysis of ANDROMEDA-SHOCK,the CRT-based strategy was shown to reduce mortality as compared to the lactate-based strategy.[5]These data support the new SSC recommendations stating that CRT can be used to guide resuscitation.[1]

关键词： resuscitation mortality shock

Enhanced Coyote Optimization with Deep Learning Based Cloud-Intrusion Detection System

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Computers, Materials & Continua 2023年第2期74卷 4319-4336页

作者： Abdullah M.Basahel Mohammad Yamin Sulafah M.Basahel E.Laxmi lydia Faculty of Economics and Administration King Abdulaziz UniversityJeddahSaudi Arabia E-commerce Department College of Administrative and Financial SciencesSaudi Electronic UniversityJeddahSaudi Arabia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India

Cloud Computing(CC)is the preference of all information technology(IT)organizations as it offers pay-per-use based and flexible services to its *** the privacy and security become the main hindrances in its achievement due to distributed and open architecture that is prone to *** Detection System(IDS)refers to one of the commonly utilized system for detecting attacks on *** proves to be an effective and promising technique,that identifies malicious activities and known threats by observing traffic data in computers,and warnings are given when such threatswere *** current mainstream IDS are assisted with machine learning(ML)but have issues of low detection rates and demanded wide feature *** article devises an Enhanced Coyote Optimization with Deep Learning based Intrusion Detection System for Cloud Security(ECODL-IDSCS)*** ECODL-IDSCS model initially addresses the class imbalance data problem by the use of Adaptive Synthetic(ADASYN)*** detecting and classification of intrusions,long short term memory(LSTM)model is *** addition,ECO algorithm is derived to optimally fine tune the hyperparameters related to the LSTM model to enhance its detection efficiency in the cloud *** the presented ECODL-IDSCS model is tested on benchmark dataset,the experimental results show the promising performance of the ECODL-IDSCS model over the existing IDS models.

关键词： Intrusion detection system cloud security coyote optimization algorithm class imbalance data deep learning