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high-throughput calculations combining machine learning to investigate the corrosion properties of binary Mg alloys

Journal of Magnesium and Alloys 2024年第4期12卷 1406-1418页

作者： Yaowei Wang Tian Xie Qingli Tang Mingxu Wang Tao Ying Hong Zhu Xiaoqin Zeng University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University200240ShanghaiChina State Key Laboratory of Metal Matrix Composites Shanghai Jiao Tong UniversityShanghai200240China

Magnesium(Mg)alloys have shown great prospects as both structural and biomedical materials,while poor corrosion resistance limits their further application.In this work,to avoid the time-consuming and laborious experiment trial,a high-throughput computational strategy based on first-principles calculations is designed for screening corrosion-resistant binary Mg alloy with intermetallics,from both the thermodynamic and kinetic perspectives.The stable binary Mg intermetallics with low equilibrium potential difference with respect to the Mg matrix are firstly identified.Then,the hydrogen adsorption energies on the surfaces of these Mg intermetallics are calculated,and the corrosion exchange current density is further calculated by a hydrogen evolution reaction(HER)kinetic model.Several intermetallics,e.g.Y_(3)Mg,Y_(2)Mg and La_(5)Mg,are identified to be promising intermetallics which might effectively hinder the cathodic HER.Furthermore,machine learning(ML)models are developed to predict Mg intermetallics with proper hydrogen adsorption energy employing work function(W_(f))and weighted first ionization energy(WFIE).The generalization of the ML models is tested on five new binary Mg intermetallics with the average root mean square error(RMSE)of 0.11 eV.This study not only predicts some promising binary Mg intermetallics which may suppress the galvanic corrosion,but also provides a high-throughput screening strategy and ML models for the design of corrosion-resistant alloy,which can be extended to ternary Mg alloys or other alloy systems.

关键词： Mg intermetallics Corrosion property high-throughput Density functional theory Machine learning

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Base editor-mediated large-scale screening of functional mutations in bacteria for industrial phenotypes

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Science China(Life Sciences) 2024年第5期67卷 1051-1060页

作者： Yaomeng Yuan Xihao Liao Shuang Li Xin-Hui Xing Chong Zhang MOE Key Laboratory for Industrial Biocatalysis Institute of Biochemical EngineeringDepartment of Chemical EngineeringTsinghua UniversityBeijing 100084China Institute of Biopharmaceutical and Health Engineering Tsinghua Shenzhen International Graduate SchoolShenzhen 518055China Institute of Biomedical Health Technology and Engineering Shenzhen Bay LaboratoryShenzhen 440300China Center for Synthetic and Systems Biology Tsinghua UniversityBeijing 100084China

Base editing,the targeted introduction of point mutations into cellular DNA,holds promise for improving genome-scale functional genome screening to single-nucleotide resolution.Current efforts in prokaryotes,however,remain confined to loss-of-function screens using the premature stop codons-mediated gene inactivation library,which falls far short of fully releasing the potential of base editors.Here,we developed a base editor-mediated functional single nucleotide variant screening pipeline in Escherichia coli.We constructed a library with 31,123 sgRNAs targeting 462 stress response-related genes in E.coli,and screened for adaptive mutations under isobutanol and furfural selective conditions.Guided by the screening results,we successfully identified several known and novel functional mutations.Our pipeline might be expanded to the optimization of other phenotypes or the strain engineering in other microorganisms.

关键词： base editor high-throughput large-scale screening Escherichia coli functional mutation

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Automated and miniaturized screening of antibiotic combinations via robotic-printed combinatorial droplet platform

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Acta Pharmaceutica Sinica B 2024年第4期14卷 1801-1813页

作者： Fangchi Shao Hui Li Kuangwen Hsieh Pengfei Zhang Sixuan Li Tza-Huei Wang Department of Biomedical Engineering Johns Hopkins UniversityBaltimoreMD 21218USA Department of Mechanical Engineering Johns Hopkins UniversityBaltimoreMD 21218USA

Antimicrobial resistance(AMR)has become a global health crisis in need of novel solutions.To this end,antibiotic combination therapies,which combine multiple antibiotics for treatment,have at-tracted significant attention as a potential approach for combating AMR.To facilitate advances in anti-biotic combination therapies,most notably in investigating antibiotic interactions and identifying synergistic antibiotic combinations however,there remains a need for automated high-throughput plat-forms that can create and examine antibiotic combinations on-demand,at scale,and with minimal reagent consumption.To address these challenges,we have developed a Robotic-Printed Combinatorial Droplet(RoboDrop)platform by integrating a programmable droplet microfuidic device that generates antibiotic combinations in nanoliter droplets in automation,a robotic arm that arranges the droplets in an array,and a camera that images the array of thousands of droplets in parallel.We further implement a resazurin-based bacterial viability assay to accelerate our antibiotic combination testing.As a demonstration,we use RoboDrop to corroborate two pairs of antibiotics with known interactions and subsequently identify a new synergistic combination of cefsulodin,penicillin,and oxacillin against a model E.coli strain.We therefore envision RoboDrop becoming a useful tool to efficiently identify new synergistic antibiotic combinations toward combating AMR.

关键词： Droplet microfluidics Antimicrobial resistance Antibiotic combinatorial screening Contact printing Robotics Pharmaceutical analysis high-throughput Antibiotic interactions

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Flash‑Induced high‑throughput Porous Graphene via Synergistic Photo‑Effects for Electromagnetic Interference Shielding

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纳微快报:英文版 2023年第11期15卷 1-18页

作者： Jin Soo Lee Jeong‑Wook Kim Jae Hee Lee Yong Koo Son Young Bin Kim Kyoohee Woo Chanhee Lee Il‑Doo Kim Jae Young Seok Jong Won Yu Jung Hwan Park Keon Jae Lee Department of Materials Science and Engineering Korea Advanced Institute of Science and Technology(KAIST)291 Daehak‑roYuseong‑guDaejeon 34141Republic of Korea School of Electrical Engineering Korea Advanced Institute of Science and Technology(KAIST)291 Daehak‑roYuseong‑guDaejeon 34141Republic of Korea Department of Printed Electronics Nano‑Convergence Manufacturing Systems Research DivisionKorea Institute of Machinery and Materials(KIMM)156 Gajeongbuk‑RoYuseong‑GuDaejeon 34103Republic of Korea Department of Mechanical System Design Engineering Seoul National University of Science and Technology232 Gongneung‑roNowon‑guSeoul 01811Republic of Korea Department of Mechanical Engineering(Department of Aeronautics Mechanical and Electronic Convergence Engineering)Kumoh National Institute of Technology61 Daehak‑roGumiGyeongbuk 39177Republic of Korea

Porous 2D materials with high conductivity and large surface area have been proposed for potential electromagnetic interference(EMI)shielding materials in future mobility and wearable applications to prevent signal noise,transmission inaccuracy,system malfunction,and health hazards.Here,we report on the synthesis of lightweight and flexible flash-induced porous graphene(FPG)with excellent EMI shielding performance.The broad spectrum of pulsed flashlight induces photo-chemical and photo-thermal reactions in polyimide films,forming 5×10 cm^(2)-size porous graphene with a hollow pillar structure in a few milliseconds.The resulting material demonstrated low density(0.0354 g cm^(−3))and outstanding absolute EMI shielding effectiveness of 1.12×10^(5) dB cm^(2) g^(−1).The FPG was characterized via thorough material analyses,and its mechanical durability and flexibility were confirmed by a bending cycle test.Finally,the FPG was utilized in drone and wearable applications,showing effective EMI shielding performance for internal/external EMI in a drone radar system and reducing the specific absorption rate in the human body.

关键词： Porous graphene Flash lamp Photo-pyrolysis high-throughput Electromagnetic interference shielding

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high-throughput genome editing in rice with a virus-based surrogate system

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Journal of Integrative Plant Biology 2023年第3期65卷 646-655页

作者： Yifu Tian Dating Zhong Xinbo Li Rundong Shen Han Han Yuqin Dai Qi Yao Xuening Zhang Qi Deng Xuesong Cao Jian-Kang Zhu Yuming Lu Shanghai Center for Plant Stress Biology Center for Excellence in Molecular Plant SciencesChinese Academy of SciencesShanghai 201602China Center for Advanced Bioindustry Technologies Institute of Crop SciencesChinese Academy of Agricultural SciencesBeiing 100081China Hainan Yazhou Bay Seed Lab Sanya 572024China Shanghai Collaborative Innovation Center of Agri Seeds Joint Center for Single Cell BiologySchool of Agriculture and BiologyShanghai Jiao Tong UniversityShanghai 200240China Institute of Advanced Biotechnology School of Life SciencesSouthern University of Science and TechnologyShenzhen 518055China

With the widespread use of clustered regularly interspaced palindromic repeats(CRISPR)/CRISPR-associated nuclease(Cas) technologies in plants, large-scale genome editing is increasingly needed. Here, we developed a geminivirus-mediated surrogate system, called Wheat Dwarf Virus-Gate(WDV-surrogate), to facilitate high-throughput genome editing.WDV-Gate has two parts: one is the recipient callus from a transgenic rice line expressing Cas9 and a mutated hygromycin-resistant gene(HygM) for surrogate selection;the other is a WDV-based construct expressing two single guide RNAs(sgRNAs) targeting HygM and a gene of interest, respectively. We evaluated WDV-Gate on six rice loci by producing a total of 874 T_0 plants. Compared with the conventional method, the WDV-Gate system, which was characterized by a transient and high level of sgRNA expression, significantly increased editing frequency(66.8% vs. 90.1%), plantlet regeneration efficiency(2.31-fold increase), and numbers of homozygous-edited plants(36.3%vs. 70.7%). Large-scale editing using pooled sg RNAs targeting the SLR1 gene resulted in a high editing frequency of 94.4%, further demonstrating its feasibility. We also tested WDVGate on sequence knock-in for protein tagging.By co-delivering a chemically modified donor DNA with the WDV-Gate plasmid, 3xFLAG peptides were successfully fused to three loci with an efficiency of up to 13%. Thus, by combining transiently expressed sgRNAs and a surrogate selection system, WDV-Gate could be useful for high-throughput gene knock-out and sequence knock-in.

关键词： genome editing high-throughput protein tagging rice

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A deep-learning-based workflow to deal with the defocusing problem in high-throughput experiments

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Bioactive Materials 2022年第5期7卷 218-229页

作者： Yunfan Xue Honglin Qian Xu Li Jing Wang Kefeng Ren Jian Ji MOE Key Laboratory of Macromolecule Synthesis and Functionalization Department of Polymer Science and EngineeringZhejiang UniversityHangzhou310027PR China

The increasing throughput of experiments in biomaterials research makes automatic techniques more and more necessary.Among all the characterization methods,microscopy makes fundamental contributions to biomaterials science where precisely focused images are the basis of related research.Although automatic focusing has been widely applied in all kinds of microscopes,defocused images can still be acquired now and then due to factors including background noises of materials and mechanical errors.Herein,we present a deep-learning-based method for the automatic sorting and reconstruction of defocused cell images.First,the defocusing problem is illustrated on a high-throughput cell microarray.Then,a comprehensive dataset of phase-contrast images captured from varied conditions containing multiple cell types,magnifications,and substrate materials is prepared to establish and test our method.We obtain high accuracy of over 0.993 on the dataset using a simple network architecture that requires less than half of the training time compared with the classical ResNetV2 architecture.Moreover,the subcellular-level reconstruction of heavily defocused cell images is achieved with another architecture.The applicability of the established workflow in practice is finally demonstrated on the high-throughput cell microarray.The intelligent workflow does not require a priori knowledge of focusing algorithms,possessing widespread application value in cell experiments concerning high-throughput or time-lapse imaging.

关键词： high-throughput Deep learning Cell imaging Refocusing Microscopy

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Transfer learning aided high-throughput computational design of oxygen evolution reaction catalysts in acid conditions

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Journal of Energy Chemistry 2023年第5期80卷 744-757,I0015页

作者： Siwen Wang Honghong Lin Yui Wakabayashi Li Qin Zhou Charles A.Roberts Debasish Banerjee Hongfei Jia Chen Ling Toyota Research Institute of North America Ann ArborMI 48105USA

Sluggish oxygen evolution reaction(OER)in acid conditions is one of the bottlenecks that prevent the wide adoption of proton exchange membrane water electrolyzer for green hydrogen production.Despite recent advancements in developing high-performance catalysts for acid OER,the current electrocatalysts still rely on iridium-and ruthenium-based materials,urging continuous efforts to discover better performance catalysts as well as reduce the usage of noble metals.Pyrochlore structured oxide is a family of potential high-performance acid OER catalysts with a flexible compositional space to tune the electrochemical capabilities.However,exploring the large composition space of pyrochlore compounds demands an imperative approach to enable efficient screening.Here we present a highthroughput screening pipeline that integrates density functional theory calculations and a transfer learning approach to predict the critical properties of pyrochlore compounds.The high-throughput screening recommends three sets of candidates for potential acid OER applications,totaling 61 candidates from 6912 pyrochlore compounds.In addition to 3d-transition metals,p-block metals are identified as promising dopants to improve the catalytic activity of pyrochlore oxides.This work demonstrates not only an efficient approach for finding suitable pyrochlores towards acid OER but also suggests the great compositional flexibility of pyrochlore compounds to be considered as a new materials platform for a variety of applications.

关键词： Pyrochlore Acid OER high-throughput Machine learning

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A direct,sensitive and high-throughput genus and species-specific molecular assay for large-scale malaria screening

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Infectious Diseases of Poverty 2022年第2期11卷 11-22页

作者： Yaling Zhao Ye Zhao Yu Sun Lihua Fan Duoquan Wang Heng Wang Xiaodong Sun Zhi Zheng Institute of Basic Medical Sciences Chinese Academy of Medical SciencesSchool of Basic MedicinePeking Union Medical CollegeBeijingChina Yunnan Institute of Parasitic Diseases Yunnan Center for Malaria ResearchInstitute of Vector and Pathogen BiologyDali UniversityPuerYunnanChina National Institute of Parasitic Diseases Chinese Center for Disease Control and PreventionWHO Collaborating Center for MalariaSchistosomiasisand FilariasisKey Laboratory of Parasite and Vector BiologyMinistry of HealthShanghaiChina Blood Transfusion Department Peking Union Medical College HospitalChinese Academy of Medical SciencesBeijingChina

Background:Infectious disease diagnostics often requires sensitive molecular assays that identify at both genus and species levels.For large scale screening,such as malaria screening for elimination,diagnostic assay can be a challenge,as both the throughput and cost of the assay must be considered.The requirement of nucleic acid extraction hampers the throughput of most molecular assays.Co-amplification of multiple species or multiplex identification either can result in missed diagnosis or are too costly for large-scale screening.A genus-and species-specific diagnostic assay with simplified procedure,high sensitivity and throughput is still needed.This study aimed to develop a sensitive and high-throughput approach for large-scale infectious disease screening.Methods:We developed multi-section Capture and Ligation Probe PCR(mCLIP-PCR)for the direct detection of RNA without extraction and reverse transcription.Multiple tailed sandwich hybridization probes were used to bind at genus-and species-specific sections of the target RNA to cooperatively capture the target onto a 96-well plate.After enzymatic ligation of the bound probes,a single-stranded DNA formed at each section with distinct tail sequence at the ends.They were separately PCR-amplified with primers corresponding to tail sequences for genus or species identification.We applied the method to the active screening ofPlasmodium infections of 4,580 asymptomatic dried blood spot samples collected in malaria endemic areas and compared the results with standard qPCR using linear regression.Results:With multi-section cooperative capture but separate amplification strategy,we accurately identified genusPlasmodium and speciesP.falciparum andP.vivax without RNA extraction,with favorable sensitivities among the published reports.In the active screening,our method identified all 53 positive infections including two mixed infections,and twoP.vivax infections that were missed by standard qPCR.Conclusions:mCLIP-PCR provides a sensitive and high-throughput approach to la

关键词： Infectious disease Malaria Molecular screening CLIP-PCR Genus Species high-throughput

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high-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis

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National Science Review 2023年第1期10卷 214-225页

作者： Zhenyu Sun Bin Fu Guoli Wang Lei Zhang Ruofan Xu Ying Zhang Haojie Lu Shanghai Cancer Center and Institutes of Biomedical Sciences Fudan University Department of Chemistry and NHC Key Laboratory of Glycoconjugates Research Fudan University Eleanor Roosevelt College University of California San Diego

The glycoproteome has emerged as a prominent target for screening biomarkers,as altered glycosylation is a hallmark of cancer cells.In this work,we incorporated tandem mass tag labeling into quantitative glycoproteomics by developing a chemical labeling-assisted complementary dissociation method for the multiplexed analysis of intact N-glycopeptides.Benefiting from the complementary nature of two different mass spectrometry dissociation methods for identification and multiplex labeling for quantification of intact N-glycopeptides,we conducted the most comprehensive site-specific and subclass-specific N-glycosylation profiling of human serum immunoglobulin G(IgG) to date.By analysing the serum of 90 human patients with varying severities of liver diseases,as well as healthy controls,we identified that the combination of IgG1-H3N5F1 and IgG4-H4N3 can be used for distinguishing between different stages of liver diseases.Finally,we used targeted parallel reaction monitoring to successfully validate the expression changes of glycosylation in liver diseases in a different sample cohort that included 45 serum samples.

关键词： glycoproteomics high-throughput quantification N-glycopeptides liver disease

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Porous-structure engineered spacer for high-throughput and rapidgrowth of high-quality graphene films

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Nano Research 2022年第11期15卷 9741-9746页

作者： Ziteng Ma Heng Chen Xiaofeng Song Buhang Chen Qin Li Yanglizhi Li Haiyang Liu Kaicheng Jia Shenghong Huang Luzhao Sun Zhongfan Liu Center for Nanochemistry Beijing Science and Engineering Center for NanocarbonsBeijing National Laboratory for Molecular SciencesCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China Beijing Graphene Institute Beijing 100095China College of Materials Science and Technology Beijing University of Chemical TechnologyBeijing 100029China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijing 100871China College of Energy Soochow Institute for Energy and Materials InnovationS(SIEMIS)Key Laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu ProvinceSoochow UniversitySuzhou 215006China CAS Key Laboratory of Mechanical Behavior and Design of Materials Department of Modern MechanicsUniversity of Science and Technology of ChinaHefei 230027China

Chemical vapor deposition(CVD)in conjunction with batch-to-batch manufacturing process is considered as the most promising technical route for mass-production of high-quality graphene films.To improve the space utilization of the CVD chamber and increase the throughput per batch,stacking of the Cu foil substrates is efficient,but suffers from the problems of adjacent fusion and the poor mass-transfer.Here,we demonstrate an efficient strategy for high-throughput and rapid growth of high-quality graphene by alternate stacking of Cu foils and porous carbon fiber paper(CFP).Relying on the unhindered mass-transfer through the pores of CFPs,full-covered high-quality graphene films on compact-stacked Cu foils were achieved within 2 min.Computational fluid dynamics(CFD)simulation and isotope labeling technique were performed to explore the gas diffusion and graphene growth process in the confined space of the Cu-CFP stacks.This work provides a feasible method for industrial production of graphene films,which may also be used for batch production of other two-dimensional materials.

关键词： graphene chemical vapor deposition fast growth high-throughput batch-to-batch production

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