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particle elasticity influences polymeric artificial antigen presenting cell effectiveness in vivo via CD8+T cell activation,macrophage uptake,and the protein corona

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Nano Research 2024年第10期17卷 9052-9064页

作者： Savannah E.Est-Witte Sydney R.Shannon Dennis H.Gong Kaitlyn G.Calabresi Jawaun J.Harris Kaitlyn Storm Edwin J.Yoo Ariel Isser Vivek p.Jani Natalie K.Livingston Mary O.Omotoso Kelly Rhodes Elana Ben-Akiva Randall A.Meyer Zoe T.hsieh Simone Sidoli Stephany Y.Tzeng jonathan p.Schneck Jordan J.Green Translational Tissue Engineering Center Institute for NanobiotechnologyDepartment of Biomedical EngineeringJohns Hopkins School of Medicine400 N BroadwayBaltimoreMD 21231USA Institute for Cell Engineering Department of PathologyJohns Hopkins School of Medicine733 N BroadwayBaltimoreMD 21205USA Department of Biochemistry Albert Einstein College of MedicineThe BronxNew York CityNY 10461USA

Adoptive cell therapy(ACT)is an immunotherapy strategy for cancer that has seen widespread clinical *** ACT,patient-derived lymphocytes are stimulated with the antigen of interest ex vivo,proliferated,then returned to the patient to initiate an antigen-specific antitumor *** effective,this process is resource-intensive and logistically impossible for many *** artificial antigen presenting cells(aApCs)offer a potential“off-the-shelf”alternative to ex vivo *** particulate aApCs perform well in vitro,they have had limited success in vivo due to poor bioavailability after *** to bioavailability include rapid clearance,unfavorable biodistribution,and inadequate interactions with CD8+T cells at sites of *** properties such as elasticity have been shown to vastly impact the bioavailability and particle-cell interactions,but this has yet to be investigated in the context of aApCs for in vivo T-cell *** literature likewise indicates that biomaterial properties,especially elasticity,can modulate T-cell activation in *** the goal of creating a more biomimetic,next-generation particulate aApC,we developed a poly(ethylene)glycol hydrogel particle platform with tunable elasticity to investigate the impact of elasticity on antigen-specific T cell activation for in vivo adoptive *** this knowledge,we were able to gain more precise control over in vivo T cell activation and investigate possible mechanisms including the effects of aApC elasticity on T cell binding,macrophage uptake,and the protein corona.

关键词： adoptive cell therapy artificial antigen presenting cells particle drug delivery elasticity protein corona poly(ethylene glycol)

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Machine learning accelerated carbon neutrality research using big data-from predictive models to interatomic potentials

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Science China(Technological Sciences) 2022年第10期65卷 2274-2296页

作者： WU LingJun XU ZhenMing WANG ZiXuan CHEN ZiJian HUANG ZhiChao pENG Chao pEI XiangDong LI XiangGuo mailoa jonathan p.hsieh chang-yu WU Tao yu Xue-Feng ZHAO HaiTao Materials Interfaces Center Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China College of Materials Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 210016China Multiscale Crystal Materials Research Center Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China College of Computer National University of Defense TechnologyChangsha 410073China School of Materials Shenzhen Campus of Sun Yat-sen UniversityShenzhen 518107China Quantum Laboratory TencentShenzhen 518057China China Beacons Institute The University of Nottingham Ningbo ChinaNingbo 315100China

Carbon neutrality has been proposed as a solution for the current severe energy and climate crisis caused by the overuse of fossil fuels, and machine learning(ML) has exhibited excellent performance in accelerating related research owing to its powerful capacity for big data processing. This review presents a detailed overview of ML accelerated carbon neutrality research with a focus on energy management, screening of novel energy materials, and ML interatomic potentials(MLIps), with illustrations of two selected MLIp algorithms: moment tensor potential(MTp) and neural equivariant interatomic potential(NequIp). We conclude by outlining the important role of ML in accelerating the achievement of carbon neutrality from global-scale energy management, unprecedented screening of advanced energy materials in massive chemical space, to the revolution of atomicscale simulations of MLIps, which has the bright prospect of applications.

关键词： carbon neutrality machine learning big data molecular dynamics interatomic potentials

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Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture

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npj Computational Materials 2021年第1期7卷 650-658页

作者： Cheol Woo park Mordechai Kornbluth jonathan Vandermause Chris Wolverton Boris Kozinsky jonathan p.mailoa Robert Bosch Research and Technology Center CambridgeMA 02139USA Northwestern University EvanstonIL 60208USA Harvard School of Engineering and Applied Sciences CambridgeMA 02138USA

Recently,machine learning(ML)has been used to address the computational cost that has been limiting ab initio molecular dynamics(AIMD).Here,we present GNNFF,a graph neural network framework to directly predict atomic forces from automatically extracted features of the local atomic environment that are translationally-invariant,but rotationally-covariant to the coordinate of the *** demonstrate that GNNFF not only achieves high performance in terms of force prediction accuracy and computational speed on various materials systems,but also accurately predicts the forces of a large MD system after being trained on forces obtained from a smaller ***,we use our framework to perform an MD simulation of Li7p3S11,a superionic conductor,and show that resulting Li diffusion coefficient is within 14%of that obtained directly from *** high performance exhibited by GNNFF can be easily generalized to study atomistic level dynamics of other material systems.

关键词： neural AIMD dynamics

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Interferon-mediated reprogramming of membrane cholesterol to evade bacterial toxins

Interferon-mediated reprogramming of membrane cholesterol to...

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第四届中国生物物理学会代谢生物学分会学术研讨会

作者： Quan D.Zhou Xun Chi Min Sub Lee Wei yuan hsieh jonathan J.Mkrtchyan An-Chieh Feng Cuiwen He Autumn G York Viet L.Bui Eliza B.Kronenberger Alessandra Ferrari Xu Xiao Allison E.Daly Elizabeth J.Tarling Robert Damoiseaux philip O.Scumpia Stephen T.Smale Kevin J.Williams peter Tontonoz Steven J.Bensinger Zhejiang University School of Medicine

＜正＞Cholesterol is an important determinant of the biochemical and biophysical properties of animal cell membranes. Given the requirement for cholesterol in membranes, it is not surprising that microorganisms and viruses have evolved strategies that take advantage of cholesterol availability in membranes to facilitate pathogenesis. Cholesterol-dependent cytolysins （CDCs） are a group of secreted toxins produced mainly by Gram-positive bacteria that depend on membrane cholesterol for their function.

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