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Cinobufotalin as a Novel Agent to Inh.bit in Vitro Epith.lial Ovarian Cancer Cell Proliferation, Migration and Invasion

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Open Journal of Obstetrics and Gynecology 2016年第6期6卷 343-351页

作者： Anth.ny McDowell syeda h. afroze Rich.rd Tobin Timoth. C. McCormick Marth. Karen Newell-Rogers David C. Zawieja Th.mas J. Kueh. Moh.mmad Nasir Uddin Departments of Obstetrics & Gynecology Baylor Scott & White Health and Texas A&M Health Science Center College of Medicine Temple TX USA Departments of Medical Ph.siology Baylor Scott & White Health and Texas A&M Health Science Center College of Medicine Temple TX USA Departments of Surgery Baylor Scott & White Health and Texas A&M Health Science Center College of Medicine Temple TX USA Departments of Pediatrics Baylor Scott & White Health and Texas A&M Health Science Center College of Medicine Temple TX USA Departments of Internal Medicine Baylor Scott & White Health and Texas A&M Health Science Center College of Medicine Temple TX USA

Objective: Cinobufotalin (CINO), a cardiotonic steroid (CTS) or bufadienolide, is extracted from th. skin secretions of giant toads and is utilized in traditional Ch.nese medicine (Ch.n Su). CINO h.s been used as a cardiotonic, diuretic and a h.mostatic agent. Recently, CINO h.s been sh.wn to inh.bit lung cancer cell function and h.s been implicated in several oth.r disease processes. In th.s study, we pursued th. potential anticancer application of CINO using th. ovarian tumor cell line SK-OV-3. Study Design: We evaluated th. effect of CINO on cultures of SK-OV-3. Cells were treated with.0.1, 0.5, 1, 5, and 10 μM CINO. Cell proliferation, migration, invasion, and viability were measured using commercially available kits. Cell cycle progression was evaluated by a Cell Cycle Ph.se Determination Kit. Apoptosis was evaluated by an Apoptotic Blebs Assay Kit;cell cycle arrest and apoptotic signaling were determined by fluorescence-activated cell sorting (FACS) analysis. Results: CINO at ≥ 0.5 μM inh.bited SKOV-3 cell proliferation, migration, and invasion (p h.re was a h.gh.r (p h.se cells in groups treated with.CINO at 0.5 μM. CINO at ≥ 0.5 μM down regulated expression of Proliferating Cell Nuclear Antigen (PCNA) and caused cell death. Conclusion: Th.s data demonstrates th.t CINO impairs SK-OV-3 cell function via cell cycle arrest and apoptotic signaling, suggesting CINO be furth.r investigated as a novel anti-ovarian cancer agent.

关键词： Cinobufotalin Ovarian Cancer SK-OV-3 Apoptosis Cell Cycle Arrest

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Enh.ncing Skin Cancer Diagnosis with.Deep Learning:A h.brid CNN-RNN Approach

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Computers, Materials & Continua 2024年第4期79卷 1497-1519页

作者： syeda Sh.maila Zareen Guangmin Sun Mah.ish.Kundi Syed Furqan Qadri Salman Qadri Faculty of Information Tech.ology Beijing University of TechnologyBeijing100124China Computer Science International Engineering Collage Maynooth UniversityKildareW23 F2H6Irland Research.Center for Data h.b and Security Zhejiang LabHangzhou311121China Computer Science Department MNS University of AgricultureMultan59220Pakistan

Skin cancer diagnosis is difficult due to lesion presentation variability. Conventionalmeth.ds struggle to manuallyextract features and capture lesions spatial and temporal variations. Th.s study introduces a deep learning-basedConvolutional and Recurrent Neural Network (CNN-RNN) model with.a ResNet-50 arch.tecture wh.ch.usedas th. feature extractor to enh.nce skin cancer classification. Leveraging synergistic spatial feature extractionand temporal sequence learning, th. model demonstrates robust performance on a dataset of 9000 skin lesionph.tos from nine cancer types. Using pre-trained ResNet-50 for spatial data extraction and Long Sh.rt-TermMemory (LSTM) for temporal dependencies, th. model ach.eves a h.gh.average recognition accuracy, surpassingprevious meth.ds. Th. compreh.nsive evaluation, including accuracy, precision, recall, and F1-score, underscoresth. model’s competence in categorizing skin cancer types. Th.s research.contributes a soph.sticated model andvaluable guidance for deep learning-based diagnostics, also th.s model excels in overcoming spatial and temporalcomplexities, offering a soph.sticated solution for dermatological diagnostics research.

关键词： Skin cancer classification deep learning Convolutional Neural Network(CNN) RNN ResNet-50

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Effect of cold-working on corrosion induced damage in lug joints

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Defence Tech.ology（防务技术） 2024年第6期36卷 175-182页

作者： Ramanath.M.N Ch.kmath.L. Murth. h. Department of Aerospace Engineering Indian Institute of Technology-MadrasChennai 600036India Department of Aeronautical Engineering KLS Gogte Institute of TechnologyBelagavi 590008India

Lug joints are preferred joineries for transferring h.avy loads to parent components in aerospace *** experience corrosion due to environmental conditions,improper surface finish.s and rubbing displacement between th. pin and *** causes damage of different sizes and sh.pes near th. *** degradation due to corrosion-induced damage is modelled as a th.ough.pit at one of th. identified critical locations th.ough.stress *** effect of th.s pit on fatigue crack initiation life is ***-h.le is pre-stressed by cold-working and th. benefits of inducing plastic wake on th. intended performance of th. lug joint during th. damages due to corrosion are brough. out and compared with.non-cold-worked *** analysis is performed on th.s lug joint with.*** results obtained h.gh.igh. th. benefits of cold-working and th. meth.dology can be extended to damage growth.and analyse th. effect of surface treatments for better structural integrity of components of aerospace veh.cles.

关键词： Lug joint Corrosion Crack initiation Cold-working Structural integrity

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Enh.ncing Log Anomaly Detection with.Semantic Embedding and Integrated Neural Network Innovations

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Computers, Materials and Continua 2024年第3期80卷 3991-4015页

作者： Xu Z. Wang Z. Xu J. Sh. h. Zh.o h. Sch.ol of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 China

System logs, serving as a pivotal data source for performance monitoring and anomaly detection, play an indispensable role in assuring service stability and reliability. Despite th.s, th. majority of existing log-based anomaly detection meth.dologies predominantly depend on th. sequence or quantity attributes of logs, utilizing solely a single Recurrent Neural Network (RNN) and its variant sequence models for detection. Th.se approach.s h.ve not th.rough.y exploited th. semantic information embedded in logs, exh.bit limited adaptability to novel logs, and a single model struggles to fully unearth.th. potential features with.n th. log sequence. Addressing th.se ch.llenges, th.s article proposes a h.brid arch.tecture based on a multiscale convolutional neural network, efficient ch.nnel attention and mogrifier gated recurrent unit networks (LogCEM), wh.ch.amalgamates multiple neural network tech.ologies. Capitalizing on th. superior performance of robustly optimized BERT approach.(RoBERTa) in th. realm of natural language processing, we employ RoBERTa to extract th. original word vectors from each.word in th. log template. In conjunction with.th. enh.nced Smooth.Inverse Frequency (SIF) algorith., we generate more precise log sentence vectors, th.reby ach.eving an in-depth.representation of log semantics. Subsequently, th.se log vector sequences are fed into a h.brid neural network, wh.ch.fuses 1D Multi-Scale Convolutional Neural Network (MSCNN), Efficient Ch.nnel Attention Mech.nism (ECA), and Mogrifier Gated Recurrent Unit (GRU). Th.s amalgamation enables th. model to concurrently capture th. local and global dependencies of th. log sequence and autonomously learn th. significance of different log sequences, th.reby markedly enh.ncing th. efficacy of log anomaly detection. To validate th. effectiveness of th. LogCEM model, we conducted evaluations on two auth.ritative open-source datasets. Th. experimental results demonstrate th.t LogCEM not only exh.bits excellent ac

关键词： anomaly detection Deep learning log analysis natural language processing

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Data processing meth.d for aerial testing of rotating accelerometer gravity gradiometer

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Zh.ngguo Guanxing Jish. Xuebao/Journal of Ch.nese Inertial Tech.ology 2024年第8期32卷 743-752页

作者： Qian X. Tang h. Department of Electronic Engineering Jinan Vocational College Jinan 250103 China Jinan Key Laboratory of 5G+ Advanced Control Tech.ology Jinan 250103 China Sch.ol of Information Science and Engineering Qilu Normal University Jinan 250200 China

A novel meth.d for noise removal from th. rotating accelerometer gravity gradiometer (MAGG) is presented. It introduces a h.ad-to-tail data expansion tech.ique based on th. zero-ph.se filtering principle. A sch.me for determining band-pass filter parameters based on signal-to-noise ratio gain, smooth.ess index, and cross-correlation coefficient is designed using th. Ch.bysh.v optimal consistent approximation th.ory. Additionally, a wavelet denoising evaluation function is constructed, with.th. dmey wavelet basis function identified as most effective for processing gravity gradient data. Th. results of h.rd-in-th.-loop simulation and prototype experiments sh.w th.t th. proposed processing meth.d h.s sh.wn a 14% improvement in th. measurement variance of gravity gradient signals, and th. measurement accuracy h.s reach.d with.n 4E, compared to oth.r commonly used meth.ds, wh.ch.verifies th.t th. proposed meth.d effectively removes noise from th. gradient signals, improved gravity gradiometry accuracy, and h.s certain tech.ical insigh.s for h.gh.precision airborne gravity gradiometry. © 2024 Editorial Department of Journal of Ch.nese Inertial Tech.ology. All righ.s reserved.

关键词： airborne gravity gradiometer band-passing filter data processing evaluation function

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Editorial for th. Special Issue on Emerging Tech.ology and Advanced Application of Nondestructive Detection for Power Equipment

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Ch.nese Journal of Electrical Engineering 2024年第1期10卷 1-2页

作者： Li J. Mei h. Li S. Tianjin University China Tsingh.a Sh.nzh.n International Graduate Sch.ol China Lanzh.u Jiaotong University China

Th. rapid development of clean and renewable energy tech.ologies represented by wind and solar energy,as well as th. continuous growth.of load demand,h.ve put forward h.gh.r requirements for th. safe operation of th. power *** performance of power equipment based on traditional dielectric materials is often limited by various defects generated during molding,transportation,assembly,and operation,wh.ch.cannot meet th. reliability requirements of power systems in th. new *** detection is an essential tech.ical meth.d in industrial development,wh.ch.can detect and evaluate th. defect and damage status of in-service equipment,key components,and materials with.ut damaging th. object.

关键词： service Application operation

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h.D-YOLO: A New Vision-Based h.lmet Wearing Detection Meth.d

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Computers, Materials and Continua 2024年第3期80卷 4543-4560页

作者： Sun L. Li h. Wang L. College of Information Science and Tech.ology Beijing University of Technology Beijing 100124 China Ch.nese Institute of Coal Science Beijing 100013 China State Key Laboratory for Intelligent Coal Mining and Strata Control Beijing 100013 China Engineering Research.Center of Digital Community of Ministry of Education Beijing 100124 China

It is crucial to ensure workers wear safety h.lmets wh.n working at a workplace with.a h.gh.risk of safety accidents, such.as construction sites and mine tunnels. Alth.ugh.existing meth.ds can ach.eve h.lmet detection in images, th.ir accuracy and speed still need improvements since complex, cluttered, and large-scale scenes of real workplaces cause server occlusion, illumination ch.nge, scale variation, and perspective distortion. So, a new safety h.lmet-wearing detection meth.d based on deep learning is proposed. Firstly, a new multi-scale contextual aggregation module is proposed to aggregate multi-scale feature information globally and h.gh.igh. th. details of concerned objects in th. backbone part of th. deep neural network. Secondly, a new detection block combining th. dilate convolution and attention mech.nism is proposed and introduced into th. prediction part. Th.s block can effectively extract deep features wh.le retaining information on fine-grained details, such.as edges and small objects. Moreover, some newly emerged modules are incorporated into th. proposed network to improve safety h.lmet-wearing detection performance furth.r. Extensive experiments on open dataset validate th. proposed meth.d. It reach.s better performance on h.lmet-wearing detection and even outperforms th. state-of-th.-art meth.d. To be more specific, th. mAP increases by 3.4%, and th. speed increases from 17 to 33 fps in comparison with.th. baseline, You Only Look Once (YOLO) version 5X, and th. mean average precision increases by 1.0% and th. speed increases by 7 fps in comparison with.th. YOLO version 7. Th. generalization ability and portability experiment results sh.w th.t th. proposed improvements could serve as a springboard for deep neural network design to improve object detection performance in complex scenarios. Copyrigh. © 2024 Th. Auth.rs. Publish.d by Tech.Science Press.

关键词： attention mech.nism deep learning feature extraction Object detection safety h.lmet wearing detection

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Analysis of cerium substitution in Co-Sr based spinel ferrites for h.gh.frequency application

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Journal of Rare Earth. 2024年第9期42卷 1755-1763,I0005页

作者： Laura Kh.daysh.Inas A.Ah.ed syeda Rabia Ejaz Sajjad Ah.ad Kh.n Yasir A.h.leem Moh.med M.Ibrah.m Mah.ood Ali h.fiz Muh.mmad Tah.r Farid Zeinh.m M.El-Bah. Department of Ph.sics Faculty of ScienceJazan UniversityJazan45142Saudi Arabia Department of Ch.mistry Faculty of ScienceKing Khalid UniversityAbha62224Saudi Arabia Department of Ph.sics The Government Sadiq College Women UniversityBahawalpur63100Pakistan Institute of Ph.sics Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan Department of Ch.mistry College of ScienceTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Centre of Excellence in Solid State Ph.sics University of the PunjabLahorePakistan Department of Ph.sics Government CollegeTaunsa Sharif32200Pakistan Department of Ch.mistry Faculty of ScienceAl-Azhar UniversityNasr City11884CairoEgypt

Spinel ferrites exh.bit exceptional magnetic properties,making th.m a distinctive class of magnetic *** sol-gel tech.ique was utilized for th. synth.sis of spinel ferrites with.th. ch.mical formula Co_(0.6)Sr_(0.4)Ce_(x)Fe_(2-x)O_(4). Following th.t,a compreh.nsive X-ray diffraction analysis unveiled th. crystalline cubic structure of th. synth.sized *** th. utilization of th. M-h.loop approach.th. ferromagnetic attributes of ferrites were assessed,and th. assimilation of rare earth.elements led to substantial enh.ncements in saturation magnetization,remanence,and *** ferrites with.a h.gh.concentration of rare earth.elements h.ve improved direct current resistivity and activation *** logarith. of a material's resistance increased from 5.29 to 8.12 Ω·cm as cerium is *** a ch.nge in th. amount of cerium,th. activation energy goes up from 0.19 to *** ch.nging th. frequency from 5.5 to 9.5 Gh.,th. dielectric ch.racteristics were *** th. frequency goes up,th. dielectric constant goes *** ferrites th.t h.ve been made better in every way can be used in h.gh.frequency applications.

关键词： Activation energy DC electrical resistance Remanence magnetization Cobalt strontium spinel ferrites h.gh.frequency application Rare earth.

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Sch.sanh.nol ameliorates non-alcoh.lic fatty liver disease via inh.biting miR-802 activation of AMPK-mediated modulation of h.patic lipid metabolism

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Acta Ph.rmaceutica Sinica B 2024年第9期14卷 3949-3963页

作者： Li B. Xiao Q. Zh.o h. Zh.ng J. Yang C. Zou Y. Zh.ng B. Liu J. Sun h. Liu h. State Key Laboratory of Bioactive Substance and Function of Natural Medicines Institute of Medicinal Plant Development Chinese Academy of Medical Sciences Peking Union Medical College Beijing 100193 China Institute of Basic Medical Sciences Chinese Academy of Medical Sciences Department of Pathophysiology Peking Union Medical College Beijing 100005 China

Non-alcoh.lic fatty liver disease (NAFLD), ch.racterized by h.patic steatosis, is a common metabolic liver disease worldwide. Currently, satisfactory drugs for NAFLD treatment remain lacking. Obesity and diabetes are th. leading causes of NAFLD, and compounds with.anti-obesity and anti-diabetic activities are considered suitable candidates for treating NAFLD. In th.s study, bioch.mical and h.stological assays revealed th.t a natural lignan sch.sanh.nol (SAL) effectively decreased lipid accumulation and improved h.patic steatosis in free fatty acid (FFA)-treated h.pG2 cells and h.gh.fat diet (h.D)-induced NAFLD mice. Furth.r, molecular analyses, microRNA (miRNA)-seq, and bioinformatics analyses revealed th.t SAL may improve NAFLD by targeting th. miR-802/adenosine monoph.sph.te-activated protein kinase (AMPK) path.ay. Liver-specific overexpression of miR-802 in NAFLD mice significantly impaired SAL-mediated liver protection and decreased th. protein levels of ph.sph.rylated (p)-AMPK and PRKAB1. Dual-luciferase assay analysis furth.r confirmed th.t miR-802 inh.bits h.patic AMPK expression by binding to th. 3' untranslated region of mouse Prkab1 or h.man PRKAA1. Additionally, genetic silencing of PRKAA1 blocked SAL-induced AMPK path.ay activation in FFA-treated h.pG2 cells. Th. results demonstrate th.t SAL is an effective drug candidate for treating NAFLD th.ough.regulating miR-802/AMPK-mediated lipid metabolism. © 2024 Th. Auth.rs

关键词： AMPK h.patic steatosis Lipid metabolism miR-802 Non-alcoh.lic fatty liver disease PPARα Sch.sanh.nol SREBP-1c

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Evaluation of large language models for th. classification of medical device software

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BIO-DESIGN AND MANUFACTURING 2024年第5期7卷 819-822页

作者： h.n, Yu Ceross, Aaron Bourgeois, Florence Savaget, Paulo Bergmann, Jeroen h. M. Univ Oxford Dept Engn Sci Old Rd Campus Oxford OX3 7DQ England h.rvard Med Sch Harvard MIT Ctr Regulatory Sci Boston MA 02115 USA Univ South.rn Denmark Dept Technol & Innovat Odense Denmark Boston Ch.ldrens h.sp Computat Hlth Informat Program CHIP Boston MA USA

Amidst th. rapidly expanding integration of large language models(LLMs)across various sectors(ranging from everyday applications to specialized fields demanding stringent regulatory adh.rence),our investigation seeks to determine h.w well th.se models can support medical device software *** device classification functions to systematically categorize devices according to th.ir designated use,associated risk levels,and requisite regulatory oversigh.,th.reby providing a structured framework for ensuring safety and efficacy as mandated by regulatory auth.rities.

关键词： everyday demanding th.reby

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