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M1-polarized macrophage-derived cellular nanovesicle-coated lipid nanoparticles for enhanced cancer treatment through hybridization of gene therapy and cancer immunotherapy

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Acta Pharmaceutica Sinica B 2024年第7期14卷 3169-3183页

作者： Ha Eun shin Jun-Hyeok Han seungyong shin Ga-Hyun Bae Boram Son Tae-Hyung Kim Hee Ho Park Chun Gwon Park Wooram Park Department of Integrative Biotechnology Sungkyunkwan University(SKKU)SuwonGyeonggi 16419Republic of Korea Deparment of Inteligent Precision Healthcare Convergence SKKUSuwonGyeonggi 16419Republic of Korea Department of MetaBioHealth SKKU Institute for ConvergenceSKKUSuwonGyeonggi 16419Republic of Korea Department of Bioengineering Hanyang UniversitySeoul 04763Republic of Korea Department of Integrative Engineering Chung-Ang UniversitySeoul 06974Republic of Korea Department of Biomedical Engineering SKKUSuwonGyeonggi 16419Republic of Korea Korea Institute of Science and Technology(KIST) Seoul 02792Republic of Korea

Optimum genetic delivery for modulating target genes to diseased tissue is a major obstacle for profitable gene *** nanoparticles(LNPs),considered a prospective vehicle for nucleic acid delivery,have demonstrated efficacy in human use during the COVID-19 *** study introduces a novel biomaterial-based platform,M1-polarized macrophage-derived cellular nanovesicle-coated LNPs(M1-C-LNPs),specifically engineered for a combined gene-immunotherapy approach against solid *** dual-function system of M1-C-LNPs encapsulates Bcl2-targeting siRNA within LNPs and immune-modulating cytokines within M1 macrophage-derived cellular nanovesicles(M1-NVs),effectively facilitating apoptosis in cancer cells without impacting T and NK cells,which activate the intratumoral immune response to promote granule-mediating killing for solid tumor *** retention within tumor was observed upon intratumoral administration of M1-C-LNPs,owing to the presence of adhesion molecules on M1-NVs,thereby contributing to superior tumor growth *** findings represent a promising strategy for the development of targeted and effective nanoparticle-based cancer genetic-immunotherapy,with significant implications for advancing biomaterial use in cancer therapeutics.

关键词： Genetic-immunotherapy M1 macrophage-derived cellular nanovesicles Lipid nanoparticles(LNPs) Gene therapy siRNA Cancer immunotherapy Solid tumor Tumor microenvironment(TME)

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Design and use of group-specific primers and probes for real-time quantitative PCR

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Frontiers of Environmental Science & Engineering 2011年第1期5卷 28-39页

作者： Juntaek LIM Seung Gu shin seungyong LEE Seokhwan HWANG School of Environmental Science and Engineering Pohang University of Science and TechnologyPohangGyungbuk 790-784The Republic of Korea

Real-time quantitative polymerase chain reaction(qPCR)has gained popularity as a technique to detect and quantify a specific group of target microorganisms from various environmental samples including soil,water,sediments,and *** qPCR is a very useful technique for nucleic acid quantification,accurately quantifying the target microbial group strongly depends on the quality of the primer and probe *** aspects of conducting qPCR assays have become increasingly routine and automated;however,one of the most important aspects,designing and selecting primer and probe sets,is often a somewhat arcane *** many cases,failed or non-specific amplification can be attributed to improperly designed primer-probe *** paper is intended to provide guidelines and general principles for designing group-specific primers and probes for qPCR *** demonstrate the effectiveness of these guidelines by reviewing the use of qPCR to study anaerobic processes and biologic nutrient removal *** assays using group-specific primers and probes designed with this method,have been used to successfully quantify 16S ribosomal Ribonucleic Acid(16S rRNA)gene copy numbers from target methanogenic and ammoniaoxidizing bacteria in various laboratory-and full-scale biologic *** with a good command of primer and probe design can use qPCR as a valuable tool to study biodiversity and to develop more efficient control strategies for biologic processes.

关键词： absolute quantification design guideline primer probe real-time quantitative polymerase chain reaction(qPCR)

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Epidermal piezoresistive structure with deep learning-assisted data translation

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npj Flexible Electronics 2022年第1期6卷 672-680页

作者： Changrok So Jong Uk Kim Haiwen Luan Sang Uk Park Hyochan Kim seungyong Han Doyoung Kim Changhwan shin Tae-il Kim Wi Hyoung Lee Yoonseok Park Keun Heo Hyoung Won Baac Jong Hwan Ko Sang Min Won Department of Electrical and Computer Engineering Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea School of Chemical Engineering Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea Querrey Simpson Institute for Bioelectronics Northwestern UniversityEvanstonIL 60208USA Department of Mechanical Engineering Ajou UniversitySuwon 16499Republic of Korea School of Electrical Engineering Korea UniversitySeoul 02841Republic of Korea Biomedical Institute for Convergence(BICS) Sungkyunkwan University(SKKU)Suwon 16419Korea Department of Organic and Nano System Engineering Konkuk UniversitySeoul 05029Republic of Korea Department of Advanced Materials Engineering for Information and Electronics Kyung Hee UniversityYongin 17104Republic of Korea School of Semiconductor and Chemical Engineering Jeonbuk National UniversityJeonju 54896Republic of Korea

Continued research on the epidermal electronic sensor aims to develop sophisticated platforms that reproduce key multimodal responses in human skin,with the ability to sense various external stimuli,such as pressure,shear,torsion,and *** development of such applications utilizes algorithmic interpretations to analyze the complex stimulus shape,magnitude,and various moduli of the epidermis,requiring multiple complex equations for the attached *** this experiment,we integrate silicon piezoresistors with a customized deep learning data process to facilitate in the precise evaluation and assessment of various stimuli without the need for such *** the ability to surpass conventional vanilla deep regression models,the customized regression and classification model is capable of predicting the magnitude of the external force,epidermal hardness and object shape with an average mean absolute percentage error and accuracy of<15 and 96.9%,*** technical ability of the deep learning-aided sensor and the consequent accurate data process provide important foundations for the future sensory electronic system.

关键词： utilize attached precise

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