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支气管或肺动脉化学栓塞治疗不能切除和不能消融的肺转移瘤：一项一期临床研究

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国际医学放射学杂志 2022年第1期 108-109页

作者： F.E.Boas N.E.Kemeny C.T.Sofocleous r.yeh V.r.Thompson M.Hsu 曹秋婷

摘要肺化学栓塞术是一种新兴的治疗肺肿瘤的方法，但最佳的栓塞剂、药物及技术尚不明确。目的探讨用乙碘化油、丝裂霉素和微球进行支气管或肺动脉化学栓塞肺转移瘤

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18F-FDGPET、CT和MrI对头颈部恶性肿瘤沿神经扩散的诊断和预后价值

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国际医学放射学杂志 2018年第3期 374-374页

作者： L.Dercle D.Hartl L.rozenblum-Beddok F.Z.Mokrane r.D.Seban r.yeh 于清扬 Département d'imagerie médicale Institut Gustave-Roussy

摘要目的评估是否可以从头颈部恶性肿瘤(HNM)的沿神经扩散(PNS)中提取来源于18F-FDG PET的定量成像生物标志物,从而改善病人的风险分层。方法收集81例摄取

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4D CT和SPECT/CT锝显像对原发性甲状旁腺功能亢进症病人甲状旁腺腺瘤定位的诊断性能

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国际医学放射学杂志 2019年第4期 483-483页

作者：吴酥 r.yeh Y.K.D.Tay G.Tabacco L.Dercle J.H.Kuo L.Bandeira Department of radiology New York-Presbyterian Hospital/Columbia University Medical Center

摘要目前对甲状旁腺腺瘤的最佳定位方法和成像方案尚未确定。甲状旁腺四维（4D）CT是一种很有前景的术前定位方法。目的评估甲状旁腺4D CT以及;Tc;-司他比锝(以

关键词：甲状旁腺腺瘤敏感度 AUC SPECT/CT CT 原发性甲状旁腺功能亢进症

Coarse to Fine: The role of Severe Plastic Deformation in Advancing Titanium-Based Medical Implants - A Comprehensive review

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 295-306页

作者： Dragana r Mihajlović Bojan I Međo Ivana Lj Cvijović-Alagić Veljko r Djokić Faculty of Technology and Metallurgy University of BelgradeKarnegijeva 411120 BelgradeSerbia Vinča Institute of Nuclear Sci-ences-National Institute of the republic of Serbia University of Belgrade11001BeogradSerbia Innovation Centre of the Faculty of Technology and Metallurgy Karnegijeva 411120 BelgradeSerbia

This paper describes severe plastic deformation(SPD)procedures,which are utilized to form an ultrafine-grained structure in metallic *** the SPD process,a solid material sample is subjected to very high loads without a significant change in sample *** the present work,the high-pressure torsion(HPT)process,as one of the SPD techniques,which achieves a high degree of deformation and ensures refinement of the microstructure,will be discussed in more *** that grain size control is accepted as a method to obtain materials with desired characteristics,an overview of the properties of ultrafine-grained titanium-based biomaterials to be used in medicine is ***,particular attention is dedicated to the influences of HPT process parameters,primarily hydrostatic pressure,and number of revolutions during torsion,on the grain size and physical and mechanical characteristics(modulus of elasticity,microhardness,and tensile properties),corrosion resistance,and biocompatibility of the titanium-based biomaterials.A review of the literature indicates that titanium-based materials obtained by the SPD process show improved mechanical and physical properties without losing biocompatibility and corrosion resistance,which suggests that these methods of obtaining implants are something that should be further developed in the future.

关键词： high-pressure torsion process ultrafine-grained titanium-based materials electrochemical anodization physical properties mechanical properties

Emerging potential of progranulin-dependent SorCS2 signaling in healthy and diseased nervous systems

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Neural regeneration research 2025年第9期20卷 2591-2593页

作者： Alena Salasova Anders Nykjær Danish research Institute of Translational Neuroscience DANDrITE-Nordic EMBL Partnership for Molecular Medicine and Centre of Excellence PROMEMODepartment of BiomedicineAarhus UniversityAarhusDenmark

The formation of the mammalian nervous system and its maturation into sensory,motor,cognitive,and behavioral circuits is a complex process that begins during early embryogenesis and lasts until young *** neurodevelopm... 详细信息

关键词： progr jointly CS2

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Security Strategy of Digital Medical Contents Based on Blockchain in Generative AI Model

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Computers, Materials & Continua 2025年第1期82卷 259-278页

作者： Hoon Ko Marek r.Ogiela Division of Computer Science and Engineering Sunmoon UniversityAsan31460Republic of Korea AGH University of Krakow Cryptography and Cognitive Informatics LaboratoryKrakow30-059Poland

This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain *** combining the strengths of blockchain and generative AI,the research team aimed to address the timely challenge of safeguarding visual medical *** participating researchers conducted a comprehensive analysis,examining the vulnerabilities of medical AI services,personal information protection issues,and overall security *** multi faceted exploration led to an indepth evaluation of the model’s performance and ***,the correlation between accuracy,detection rate,and error rate was *** analysis revealed insights into the model’s strengths and limitations,while the consideration of standard deviation shed light on the model’s stability and performance *** study proposed practical improvements,emphasizing the reduction of false negatives to enhance detection rate and leveraging blockchain technology to ensure visual data integrity in medical *** blockchain to generative AI-created medical content addresses key personal information protection *** utilizing the distributed ledger system of blockchain,the research team aimed to protect the privacy and integrity of medical data especially medical *** approach not only enhances security but also enables transparent and tamperproof ***,the use of generative AI models ensures the creation of novel medical content without compromising personal information,further safeguarding patient *** conclusion,this study showcases the potential of blockchain-based solutions in the medical field,particularly in securing sensitive medical data and protecting patient *** proposed approach,combining blockchain and generative AI,offers a promising direction toward more robust and secure medical content *** research and advancements

关键词： Digitalmedical content medical diagnostic visualization security analysis generativeAI blockchain vulnerability pattern recognition

A comprehensive investigation on nonlinear vibration and bending characteristics of bio-inspired helicoidal laminated composite structures

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 81-100页

作者： S.SAUrABH r.KIrAN D.SINGH r.VAISH V.S.CHAUHAN School of Mechanical and Materials Engineering Indian Institute of Technology Mandi

Bio-inspired helicoidal composite laminates, inspired by the intricate helical structures found in nature, present a promising frontier for enhancing the mechanical properties of structural designs. Hence, this study provides a comprehensive investigation into the nonlinear free vibration and nonlinear bending behavior of bio-inspired composite plates. The inverse hyperbolic shear deformation theory(IHSDT) of plates is employed to characterize the displacement field, with the incorporation of Green-Lagrange nonlinearity. The problem is modeled using the C0finite element method(FEM), and an in-house code is developed in the MATLAB environment to solve it numerically. Various helicoidal layup configurations including helicoidal recursive(Hr), helicoidal exponential(HE), helicoidal semi-circular(HS), linear helicoidal(LH), and Fibonacci helicoidal(FH)with different layup sequences and quasi-isotropic configurations are studied. The model is validated, and parametric studies are conducted. These studies investigate the effects of layup configurations, side-to-thickness ratio, modulus ratios, boundary conditions, and loading conditions at different load amplitudes on the nonlinear vibration and nonlinear bending behaviors of bio-inspired composite plates. The results show that the laminate sequence exerts a substantial impact on both nonlinear natural frequencies and nonlinear bending behaviors. Moreover, this influence varies across different side-to-thickness ratios and boundary conditions of the bio-inspired composite plate.

关键词： Inverse problems

Machine Learning Techniques in Predicting Hot Deformation Behavior of Metallic Materials

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 713-732页

作者： Petr Opela Josef Walek Jaromír Kopecek Department of Metallurgical Technologies Faculty of Materials Science and TechnologyVSB–Technical University of OstravaOstrava70800Czech Republic FZU—Institute of Physics of the Czech Academy of Sciences Prague18200Czech Republic

In engineering practice,it is often necessary to determine functional relationships between dependent and independent *** relationships can be highly nonlinear,and classical regression approaches cannot always provide sufficiently reliable ***,Machine Learning(ML)techniques,which offer advanced regression tools to address complicated engineering issues,have been developed and widely *** study investigates the selected ML techniques to evaluate their suitability for application in the hot deformation behavior of metallic *** ML-based regression methods of Artificial Neural Networks(ANNs),Support Vector Machine(SVM),Decision Tree regression(DTr),and Gaussian Process regression(GPr)are applied to mathematically describe hot flow stress curve datasets acquired experimentally for a medium-carbon *** the GPr method has not been used for such a regression task before,the results showed that its performance is the most favorable and practically unrivaled;neither the ANN method nor the other studied ML techniques provide such precise results of the solved regression analysis.

关键词： Machine learning Gaussian process regression artificial neural networks support vector machine hot deformation behavior

Antisense oligonucleotides provide optimism to the therapeutic landscape for tauopathies

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Neural regeneration research 2025年第3期20卷 803-804页

作者： Glenn A.Harris Lauren r.Hirschfeld rainwater Charitable Foundation Fort WorthTXUSA

Tauopathies are a group of neurodegenerative diseases characterized by abnormal metabolism of the misfolded tau protein. Tau is encoded by the microtubule-associated protein tau gene(MAPT) and can be classified as either 3-repeat(3r) or 4-repeat(4r) based on the number of repeat domains from alternative splicing of exon 10 of the MAPT gene.

关键词： tau metabolism diseases

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