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GlycoPro:A High-Throughput Sample-Processing Platform for Multi-Glycosylation-Omics Analysis 认领 引用
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作者 Xuejiao Liu Yue Meng +4 位作者 Bin Fu Haoru Song Bing Gu Ying Zhang Haojie Lu 《Engineering》 SCIE EI CSCD 2026年第2期43-57,共15页
Glycosylation-omics has emerged as a prominent field for early detection and diagnosis by identifying alterations in glycosylation patterns linked to cancer.In the realm of clinical multi-glycosylation-omics applicati... Glycosylation-omics has emerged as a prominent field for early detection and diagnosis by identifying alterations in glycosylation patterns linked to cancer.In the realm of clinical multi-glycosylation-omics applications,there is a critical need for robust,efficient,and cost-effective preprocessing methodologies capable of handling large sample cohorts.To bridge this gap,we introduce the GlycoPro platform,an innovative solution designed to overcome the limitations of existing analysis methods.Tailored for multi-glycosylation-omics sample preprocessing,GlycoPro refines existing workflows by seamlessly integrating steps including protein extraction,desalting,digestion,derivatization,and enrichment.The GlycoPro platform employs a 96-well plate format,enabling the efficient enrichment or desalting of up to 384 samples in a single day.This capability represents a significant increase in throughput,meeting the demands of large-scale clinical sample preprocessing for mass spectrometry analysis.The GlycoPro platform was used to successfully enrich serum N-glycans from breast cancer patients,revealing unique glycomic signatures that distinguish malignant from benign conditions.We have developed a robust Nglycan biomarker panel,demonstrating a sensitivity of 88.24%and a specificity of 78.95%in diagnostics. 展开更多
关键词 Multi-glycosylation-omics High-throughput Sample preparation Biomarkers Breast cancer
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Deep learning advances high-throughput toxicity screening of chemicals at multi-biological levels 认领 引用
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作者 Xinyue Wu Ya Zhu +3 位作者 Jie Hou Jianying Zhang Jiang Xu Daohui Lin 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2026年第6期706-719,共14页
Deep learning(DL)has emerged as a powerful tool for modeling unstructured data,thereby improving prediction accuracy and expanding the application of machine learning(ML)in toxicity assessment.However,selecting suitab... Deep learning(DL)has emerged as a powerful tool for modeling unstructured data,thereby improving prediction accuracy and expanding the application of machine learning(ML)in toxicity assessment.However,selecting suitable DL architectures and training methods for toxicity prediction remains challenging due to the lack of systematic comparisons regarding data types and modeling tasks across biological levels,which hinders the development of optimal models.To address these challenges,we review the current DL applications for predicting toxic events at four stages within the adverse outcome pathway framework:toxicophore-induced effects at the chemical exposure stage,activation of toxic pathways at the macro-molecular level(molecular initiating events),toxicogenomic responses at the cellular level(key events),and observable toxic effects(adverse outcomes)at the tissue/organ/individual levels.We compare the technical aspects of various DL methods for toxicity prediction and discuss how interpretability analyses can reveal the underlying molecular mechanisms and modes of toxic action.We also summarize current solutions to the challenges of increased data requirements and reduced interpretability of DL compared to traditional ML,and propose the development of a general environmental toxicological model.We hope that the interdisciplinary insights provided in this review can accelerate the development and application of new DL models in high-throughput toxicity screening,thereby advancing risk management strategies based on modes of toxic action. 展开更多
关键词 Deep learning Toxicity prediction Adverse outcome pathway High-throughput screening
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High-throughput computational screening of functionalized MOFs for energy-efficient CO2capture:Balancing selective CO2adsorption performance and energy inputs 认领 引用
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作者 Sen Liu Zhe Sun +8 位作者 Bo Liao Huili Zhang Ling Zhang Yuchen Huang Lin Wan Maohuai Wang Shuxian Wei Baojun Wei Xiaoqing Lu 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2026年第3期136-145,共10页
The rational design of high-performance CO2adsorbents remains a critical challenge in addressing global carbon emissions,with metal-organic frameworks(MOFs)emerging as promising candidates due to their tunable pore... The rational design of high-performance CO2adsorbents remains a critical challenge in addressing global carbon emissions,with metal-organic frameworks(MOFs)emerging as promising candidates due to their tunable pore environments.However,the lack of systematic guidelines for functional group selection has hindered their practical implementation in carbon capture applications.Here,this gap was addressed by developing a comprehensive design framework through high-throughput computational screening.Through construction of a topology-directed database of 4797,integrating 10 metal centers with 144 functionalized ligands(18 ligands modified by–NH2,–NO2,–CH3,–CF3,–SH2,–SO2,–OH,and–OLi)across 36 topologies,the fundamental structure–property relationships governing CO2capture performance was established.Multi-metric evaluation reveals that–NO2,–SO2,and–OLi dramatically enhance CO2selectivity over CH_4/N2via selectivity(Sads),working capacity(ΔN),adsorbent performance score(APS),sorbent selection parameter(Ssp),and renewability R.Specially,ΔN rises from 2.34(pristine)to 5.91–7.94 mmol g-1and Sadssurges from 24.94/40.36 to 121.11/176.87(–NO2),149.94/215.54(–SO2),and 58.64/267.44(–OLi).Besides,the critical trade-off between adsorption strength and renewability demonstrates that enhanced performance comes at the cost of reduced renewability,where stronger CO2affinity(isosteric heat of-29.15,-29.96,and-30.09 for–NO2,–SO2,and–OLi)compromises renewability(R reduced by -50%).To resolve this trade-off,a novel energy efficiency(η)metric was introduced,which holistically evaluates both adsorption performance(Sads,ΔN,APS,Ssp,and R)and energy inputs(desorption heat,pressure-swing energy,net loss).This leads to the identification of–SO2as the optimal functional group that balances exceptional CO2capture(η=6.17/12.78 for CO2over CH_4/N2),surpassing the second higher of 4.74/8.80 in–CF3and 0.99/2.18 in non-functionalized counterparts.Adopting high-throughput computational screening methods,this work provides both fundamental insights into host–guest interactions in functionalized MOFs and a practical framework for designing next-generation adsorbents,bridging the gap between materials discovery and process engineering considerations in carbon capture technologies. 展开更多
关键词 Metal-organic frameworks High-throughput computational screening Selective CO2adsorption Functional group engineering Energy efficiency
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Integrative combination of gas-liquid-phase plasma mutagenesis and high-throughput screening to enhance eicosapentaenoic acid production by Schizochytrium sp. 认领 引用
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作者 Chao YU Jialin ZHU +8 位作者 Jinyong WU Xiangsong CHEN Shuhuan LU Xiangyu LI Sa ZHAO Weiwei ZHU Min SHU Mianbin WU Jianming YAO 《Journal of Zhejiang University-SCIENCE B》 SCIE CAS CSCD 2026年第3期250-263,共14页
Dietary consumption of eicosapentaenoic acid(EPA)offers diverse health benefits,such as the regulation of blood triglycerides and the prevention of cardiovascular diseases.EPA is naturally synthesized by Schizochytriu... Dietary consumption of eicosapentaenoic acid(EPA)offers diverse health benefits,such as the regulation of blood triglycerides and the prevention of cardiovascular diseases.EPA is naturally synthesized by Schizochytrium sp.;however,its low production level limits its potential for industrial application.The goal of this study was to increase EPA productivity in Schizochytrium sp.by gas—liquid-phase plasma(GLPP)mutagenesis combined with a high-throughput screening method.First,a diverse array of mutants was generated through GLPP mutagenesis.Next,the mutants with elevated EPA productivity were identified through near-infrared spectroscopy(NIRS).Notably,the M7-25 mutant demonstrated the highest and most consistent EPA production.After the culture medium was optimized,the EPA titer increased from 0.45 to 1.70 g/L.Finally,a cofermentation strategy using ammonia and glucose feeding was employed,and the EPA titer reached 2.08 g/L in a 7-L fermenter.This study reports the highest EPA titer achieved in Schizochytrium sp.via mutagenesis to date,highlighting its great market potential for industrial production. 展开更多
关键词 Eicosapentaenoic acid(EPA) Schizochytrium sp. Mutagenesis High-throughput screening Near-infrared spectroscopy(NIRS)
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Decoding complex compositions in topologically close-packed nanoplates of magnesium alloys:A high-throughput route to stable precipitates 认领 引用
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作者 Junyuan Bai Xueyong Pang Gaowu Qin 《Journal of Magnesium and Alloys》 SCIE EI CAS CSCD 2026年第5期424-435,共12页
Coherent topologically close-packed(TCP)nanoplates play a crucial role in enhancing the strength and creep resistance of magnesium alloys.However,the thermodynamic formation mechanisms of several metastable TCP nanopl... Coherent topologically close-packed(TCP)nanoplates play a crucial role in enhancing the strength and creep resistance of magnesium alloys.However,the thermodynamic formation mechanisms of several metastable TCP nanoplates remain unclear,and the traditional trialand-error methods impede the rapid discovery of novel TCP precipitate-strengthened Mg alloys.In this study,using density functional theory calculations to construct convex hull diagrams and evaluate thermodynamic stability,our results clarify that the metastableβ2 nanoplates in Mg-Zn alloys adopt the Mg(Mg,Zn)2 composition with excess Mg in precipitates.This finding demonstrates the metastable nature of theβ2 phase and resolves the long-standing puzzle of its structural similarity to the equilibrium MgZn2 phase in the Mg-Zn binary phase diagram.Moreover,by integrating the thermodynamic and kinetic conditions for TCP precipitation,we developed a two-step highthroughput screening strategy to systematically identify Mg alloy systems capable of forming stable TCP nanoplates.Our screenings identify 43 previously unreported TCP nanoplates and indicate that the current development of TCP-strengthened Mg alloys should mainly focus on the Mg-RE(Ca)-Al systems.These findings reveal the atomic-scale compositional complexity in TCP nanoplates and establish a theoretical foundation for designing creep-resistant Mg alloys containing TCP nanoplates. 展开更多
关键词 High-throughput screening DFT calculations Coherent TCP precipitates Phase stability
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Optimized substrate selection for enhanced orchid growth based on high-throughput lysimetric arrays 认领 引用 被引量：3
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作者 Jia YAO Xubo KE +5 位作者 Xinyue GU Zhihan JIANG Zhengzheng YING Chenze LU Chongbo SUN Pei XU 《Journal of Zhejiang University-SCIENCE B》 SCIE CAS CSCD 2026年第5期437-449,I0002,共13页
Orchids are highly valued ornamental plants whose growth conditions directly impact the economic returns of the horticultural industry.The substrate,acting both as a physical support and a nutrient reservoir,is critic... Orchids are highly valued ornamental plants whose growth conditions directly impact the economic returns of the horticultural industry.The substrate,acting both as a physical support and a nutrient reservoir,is critical for orchid development.Therefore,the careful selection of an appropriate growth substrate is of paramount importance.However,existing research on the relationship between orchid growth and substrate properties relies mainly on manual measurements of physiological indicators,with limited application of high-throughput phenotyping(HTP)platforms.In this study,we evaluated three distinct substrate types,peat soil mixed with perlite,pine bark,and river sand,which were applied to two orchid species,Cymbidium goeringii and Cymbidium faberi.Using the high-throughput Plantarray lysimetric system,we continuously recorded environmental parameters(photosynthetically active radiation,humidity,and temperature)as well as key growth metrics(biomass accumulation,canopy conductance,and transpiration rate).This platform enabled precise and rapid quantification of orchid growth indicators.The results show that the type of substrate significantly affects orchid growth.Under controlled conditions,mixed substrates that provide balanced nutrition and excellent drainage enhanced orchid growth compared to other substrates.Additionally,when the data obtained from the HTP platform were compared with those from traditional manual measurements,the automated system showed higher reliability and accuracy.This study not only provides practical guidance for selecting cultivation substrates for orchids,but also establishes a robust scientific framework for integrating advanced phenotyping technologies into orchid cultivation practices. 展开更多
关键词 Orchid Cultivation substrate Phenotypic platform Plantarray High-throughput monitoring
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HTPRootSlides:A high-throughput phenotyping platform for crop root germination dynamic screening 认领 引用 被引量：1
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作者 Wenzhe Deng Jiafei Zhang +7 位作者 Jing Huang Hao Li Zhiguo Han Luyao Wang Xueying Guan Hongqing Ling Tingting Wu Weijuan Hu 《The Crop Journal》 SCIE CSCD 2026年第2期662-672,共11页
Root phenotyping is crucial for advancing our understanding of plant development and adaptation.However,existing platforms often face challenges in balancing high-throughput capacity with longterm,high-frequency monit... Root phenotyping is crucial for advancing our understanding of plant development and adaptation.However,existing platforms often face challenges in balancing high-throughput capacity with longterm,high-frequency monitoring.To overcome this limitation,we present HTPRootSlides,an integrated root phenotyping platform designed for dynamic and scalable trait analysis.Its design features a circulating zone that accommodates 141 specialized root boxes for high-throughput operation synchronously.Root boxes follow a continuous S-shaped trajectory step by step,facilitating repetitive imaging for high-throughput,time-series data acquisition.To address challenges such as water vapor condensation and fine root entanglement,we developed a dedicated segmentation algorithm,achieving 89.56%accuracy in root isolation.Combining morphological and skeleton-based feature extraction techniques,the platform ensures comprehensive and efficient phenotypic trait quantification.We validated HTPRootSlides by dynamically monitoring root development in four staple crops(soybean,maize,wheat,and rice)during early-stage germination(<14 d).The results demonstrate the capability of HTPRootSlides for high-frequency,high-precision and large-scale root phenotyping(<1 h with 141 root boxes per run),offering researchers a powerful tool to investigate root dynamics and optimize crop performance through trait selection. 展开更多
关键词 Root phenotyping High-throughput imaging Trait extraction Seedling development HTPRootSlides
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High-throughput Sequencing for Tuberculosis Diagnosis and Antimicrobial Resistance Detection:Progress,Challenges,and Future Perspectives 认领 引用 被引量：1
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作者 Lulu Zhang Junping Peng 《Biomedical and Environmental Sciences》 SCIE CAS CSCD 2026年第2期223-233,共11页
Tuberculosis(TB)continues to pose a significant threat to global public health,necessitating rapid and precise diagnostic methods and comprehensive detection of antimicrobial resistance(AMR)to facilitate timely clinic... Tuberculosis(TB)continues to pose a significant threat to global public health,necessitating rapid and precise diagnostic methods and comprehensive detection of antimicrobial resistance(AMR)to facilitate timely clinical management.Traditional diagnostic techniques suffer from extended turnaround times and limited ability to comprehensively profile AMR,often resulting in delayed therapeutic interventions.Highthroughput sequencing(HTS)technologies have revolutionized pathogen research by significantly improving diagnostic speed and accuracy.In the context of TB,diverse sequencing strategies and platforms are being employed to fulfill specific research goals,ranging from elucidating the molecular mechanisms underlying AMR to characterizing the genomic diversity among clinical isolates.This review systematically examines current progress in the application of HTS for rapid pathogen identification,comprehensive AMR profiling,epidemiological studies,advances in novel drugs,and vaccine development.Furthermore,we address existing technological limitations and bioinformatics challenges and explore the future directions necessary for effectively integrating HTS-based methodologies into global TB control efforts. 展开更多
关键词 Tuberculosis Antimicrobial resistance High-throughput sequencing
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High-Throughput Sequencing Analyzed the Effects of Three Antibiotics on the Bacterial Community in the Phycosphere of Typical Harmful Algae During Laboratory Culturing 认领 引用
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作者 JIANG Fan LI Xiaodong +12 位作者 REN Kunlei WANG Ziyang CHEN Ziqin WU Tong NONG Yanhong LIU Qionglin LI Jing LIU Yang CHU Yaoyao HUANG Xiongwei WANG Weicheng YAN Tian CHEN Xinhua 《Journal of Ocean University of China》 SCIE CAS CSCD 2026年第2期743-754,I0042-I0047,共12页
The long-term laboratory preservation of algae serves as the foundation for research on harmful algal blooms(HABs).Purification by antibiotics during the preservation may inhibit algal growth and alter the phycosphere... The long-term laboratory preservation of algae serves as the foundation for research on harmful algal blooms(HABs).Purification by antibiotics during the preservation may inhibit algal growth and alter the phycosphere bacterial community.However,related research remains relatively rare.In this study,16S rDNA V3-V4 region-based high-throughput sequencing was used to analyze the impact of three antibiotics(penicillin-streptomycin-amphotericin)on the algal-associated microbiome of three common HAB-forming species Akashiwo sanguinea,Karenia mikimotoi,and Alexandrium tamarense.Results showed that the antibiotics significantly inhibited the growth of A.sanguinea and A.tamarense.Although algal species exerted a primary effect on these bacterial communities,with antibiotics also exerting a significant impact.In antibiotic-treated A.sanguinea cultures,relative aboundance of Enterobacterales species like Alteromonas mediterranea were suppressed,whereas Pseudomonas stutzeri were elevated.Antibiotics also suppressed the growth of Yoonia vestfoldensis in the K.mikimotoi cultures and Dinoroseobacter shibae in A.tamarense cultures.Functional predictions based on 16S rDNA data showed that antibiotic addition significantly upregulated the expression of transportrelated systems,such as ABC transporters associated with efflux pumps,while downregulating metabolism-related functions in algalassociated bacteria.Collectively,our results indicated that phycosphere bacterial communities primarily differed by algal species,followed by antibiotic addition;bacteria with broad-spectrum antibiotic resistance mechanisms,such as efflux pump,may benefit from antibiotic pressure;and algal-bacteria relations might be involved in growth inhibition of antibiotics. 展开更多
关键词 harmful algae species phycosphere bacterial community high-throughput sequencing antibiotics antibiotics resistance
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Strengthening effect of laser shock peening on fatigue performance and life extension of high-throughput laser-directed energy deposition high-strength steel components 认领 引用
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作者 Rong-Da Wu Yong-Xiang Geng +2 位作者 Hai-Zhong Zheng Yi-Xin Xiao Xin Wang 《Journal of Iron and Steel Research International》 SCIE EI CSCD 2026年第6期308-324,共17页
The fatigue life degradation in remanufactured high-strength steels was addressed by implementing an integrated strategy that combined high-throughput laser-directed energy deposition,homogenization heat treatment(HHT... The fatigue life degradation in remanufactured high-strength steels was addressed by implementing an integrated strategy that combined high-throughput laser-directed energy deposition,homogenization heat treatment(HHT),and laser shock peening(LSP).This sequential processing route significantly mitigated the inherent drawbacks of additive remanufacturing while preserving ultrahigh strength.HHT-LSP processed specimens demonstrated a remarkable 74.4%increase in fatigue life(68,000 cycles compared to 11,000 cycles in as-deposited specimens)under a high applied stress of 1100 MPa,while maintaining ultrahigh tensile strength(1675 MPa).Mechanistic analysis revealed that laser shock peening created a beneficial gradient microstructure.Fine surface grains suppressed crack initiation,while subsurface structures impeded crack propagation.HHT step further enhanced performance by homogenizing the tempered martensite matrix and eliminating brittle phases. 展开更多
关键词 30CrMnSiA steel Additive manufacturing High-throughput laser-directed energy deposition Laser shock peening Grain boundary Fatigue life
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A Low-Cost RGB-Based Image Processing Method for High-Throughput Assessment of Rice Grain Chalkiness 认领 引用
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作者 Jardel da SILVA SOUZA Sandra Helena UNEDA-TREVISOLI +1 位作者 Felipe DALLA LANA Roberto FRITSCHE-NETO 《Rice science》 SCIE CAS CSCD 2026年第3期381-391,共11页
Although numerous rice genotypes have been developed worldwide,post-harvest evaluation of chalkiness,a key grain trait,remains a significant challenge in breeding programs.Conventional phenotyping methods rely on manu... Although numerous rice genotypes have been developed worldwide,post-harvest evaluation of chalkiness,a key grain trait,remains a significant challenge in breeding programs.Conventional phenotyping methods rely on manual grain separation and analysis,which limit the speed and performance of decision-making.This study aimed to assess the efficiency of a low-cost,image-based phenotyping method for characterizing rice grain chalkiness and morphological traits(grain length and width)in comparison with traditional evaluation methods.Grains from 270 rice samples were imaged using a hyperspectral camera(visible to near-infrared,400-1000 nm)and a Nikon digital single-lens reflex(DSLR)camera.Only RGB information was used for analysis,including RGB channels extracted from hyperspectral imagery to simulate low-cost setups.Python scripts were used to segment grains,estimate morphological parameters,and calculate chalkiness degree.Results from both imaging systems were compared with reference data obtained from the SeedCount platform.Strong correlations with SeedCount reference data were observed for chalkiness degree,reaching r=0.93 when using hyperspectral-derived RGB data and r=0.98 when using DSLR-acquired RGB images.Binary classification metrics showed high discriminative performance,with area under the curve(AUC)values above 0.90 for most traits.The proposed method enabled image acquisition and processing in approximately 21 s per sample,compared to 1.5 min required by the conventional platform.The findings demonstrate the feasibility of a rapid and low-cost image-based phenotyping strategy to support rice breeding programs,particularly for chalkiness quantification and grain morphology assessment.The complete image-processing pipeline is provided as supplementary material,reinforcing the transparency and reproducibility of the method. 展开更多
关键词 Oryza sativa grain trait chalkiness degree hyperspectral high-throughput phenotyping
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From Stability to Hardness: High-Throughput First-Principles Screening Reveals Promising MAB Phases for Advanced Engineering Applications 认领 引用
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作者 Jiamin Xue Jiexi Song Diwei Shi 《Computers, Materials & Continua》 SCIE EI 2026年第6期825-838,共14页
MAB phases are a class of layered ternary transition-metal borides,characterized by hard M-B slabs interleaved with softer A-element layers,and thus hold promise for wear-resistant and high-temperature structural appl... MAB phases are a class of layered ternary transition-metal borides,characterized by hard M-B slabs interleaved with softer A-element layers,and thus hold promise for wear-resistant and high-temperature structural applications.However,their compositional space and structural diversity remain insufficiently explored,limiting guidance for synthesis and property optimization.In this work,we perform a comprehensive exploration and screening of the MAB family using high-throughput first-principles calculations.We systematically identify 855 candidate MAB compounds with orthorhombic and hexagonal structures across multiple transition-metal families,which form the starting pool for subsequent stability and property evaluation.The workflow evaluates viability using three criteria:quantifying thermodynamic stability through formation energy and energy above the convex hull,confirming dynamical stability using phonon spectra,and evaluating mechanical stability via the Born criteria.We identify 336 MAB candidates that satisfy all three stability requirements,and further conduct a comprehensive evaluation and statistical analysis of their elastic constants and derived mechanical properties,including bulk,shear,and Young’s modulus as well as Vickers hardness,thereby elucidating how stoichiometry and composition influence hardness and brittle-ductile behavior.This study not only provides a curated set of experimentally viable MAB materials spanning diverse stoichiometries but also establishes a robust and transferable computational workflow for accelerating the discovery of layered ternary borides. 展开更多
关键词 MAB phases high-throughput first-principles calculations
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Decoding DNA metabolism and its clinical relevance through the lens of high-throughput sequencing assays 认领 引用
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作者 Jingzhi Luo Fanyu Zhao +1 位作者 Shuyan Lin Yang Liu 《Medical Review》 2026年第3期219-242,共24页
Eukaryotic DNA metabolism,involving DNA replication and damage repair,ensures the faithful trans-mission of genetic information and is essential for main-taining genome integrity.Consequently,its dysregulation contrib... Eukaryotic DNA metabolism,involving DNA replication and damage repair,ensures the faithful trans-mission of genetic information and is essential for main-taining genome integrity.Consequently,its dysregulation contributes to a broad spectrum of human diseases,including cancer and pregnancy loss.Recent advances in high-throughput sequencing(HTS)assays have enabled genome-wide,single-cell,and even single-molecule analyses of DNA metabolism dynamics within their native chromatin context,profoundly expanding our capacity to dissect these processes in vivo and to evaluate their clinical significance.In this review,we summarize HTS-based technologies that profile the entire DNA replication program,spanning initi-ation,elongation,termination,and replication timing,as well as the diverse pathways involved in DNA damage detection and repair.We further highlight how these ap-proaches have been leveraged to investigate fundamental biological processes and translational applications,with particular emphasis on early embryonic development,can-cer,and genome editing.Collectively,these advances illus-trate how HTS has bridged molecular mechanisms with physiological and clinical insights,while pointing toward future directions including telomere-to-telomere genome analysis,single-cell multi-omics integration,and precision genomic medicine. 展开更多
关键词 DNA replication DNA damage repair high-throughput sequencing early embryonic development cancer genome editing
Engineering of l-threonine and l-proline biosensors by directed evolution of transcriptional regulator SerR and application for high-throughput screening 认领 引用 被引量：2
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作者 Wei Pu Jinhui Feng +9 位作者 Jiuzhou Chen Jiao Liu Xuan Guo Lixian Wang Xiaojia Zhao Ningyun Cai Wenjuan Zhou Yu Wang Ping Zheng Jibin Sun 《Bioresources and Bioprocessing》 SCIE EI CSCD 2025年第1期48-61,共14页
Amino acids are important bio-based products with a multi-billion-dollar market.The development of efficient high-throughput screening technologies utilizing biosensors is essential for the rapid identification of hig... Amino acids are important bio-based products with a multi-billion-dollar market.The development of efficient high-throughput screening technologies utilizing biosensors is essential for the rapid identification of high-performance amino acid producers.However,there remains a pressing need for biosensors that specifically target certain critical amino acids,such as l-threonine and l-proline.In this study,a novel transcriptional regulator-based biosensor for l-threonine and l-proline was successfully developed,inspired by our new finding that SerE can export l-proline in addition to the previously known l-threonine and l-serine.Through directed evolution of SerR(the corresponding transcriptional regulator of SerE),the mutant SerRF104I which can recognize both l-threonine and l-proline as effectors and effectively distinguish strains with varying production levels was identified.Subsequently,the SerRF104I-based biosensor was employed for high-throughput screening of the superior enzyme mutants of l-homoserine dehydrogenase and γ-glutamyl kinase,which are critical enzymes in the biosynthesis of l-threonine and l-proline,respectively.A total of 25 and 13 novel mutants that increased the titers of l-threonine and l-proline by over 10%were successfully identified.Notably,six of the newly identified mutants exhibited similarities to the most effective mutants reported to date,indicating the promising application potential of the SerRF104I-based biosensor.This study illustrates an effective strategy for the development of transcriptional regulator-based biosensors for amino acids and other chemical compounds. 展开更多
关键词 L-Threonine and l-proline biosensor Transcriptional regulator SerR Directed evolution High-throughput screening l-Homoserine dehydrogenase γ-Glutamyl kinase
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Rapid optimization of laser powder bed fusion process:a high-throughput integrated multi-task robust modeling approach 认领 引用 被引量：1
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作者 Han Zhang Bingke Song +6 位作者 Keyu Shi Yusheng Chen Biqi Yang Miao Chang Longhai Hu Jinming Xing Dongdong Gu 《International Journal of Extreme Manufacturing》 SCIE EI CAS CSCD 2025年第4期312-332,共21页
Transpiration cooling is crucial for the performance of aerospace engine components,relying heavily on the processing quality and accuracy of microchannels.Laser powder bed fusion(LPBF)offers the potential for integra... Transpiration cooling is crucial for the performance of aerospace engine components,relying heavily on the processing quality and accuracy of microchannels.Laser powder bed fusion(LPBF)offers the potential for integrated manufacturing of complex parts and precise microchannel fabrication,essential for engine cooling applications.However,optimizing LPBF’s extensive process parameters to control processing quality and microchannel accuracy effectively remains a significant challenge,especially given the time-consuming and labor-intensive nature of handling numerous variables and the need for thorough data analysis and correlation discovery.This study introduced a combined methodology of high-throughput experiments and Gaussian process algorithms to optimize the processing quality and accuracy of nickel-based high-temperature alloy with microchannel structures.250 parameter combinations,including laser power,scanning speed,channel diameter,and spot compensation,were designed across ten high-throughput specimens.This setup allowed for rapid and efficient evaluation of processing quality and microchannel accuracy.Employing Bayesian optimization,the Gaussian process model accurately predicted processing outcomes over a broad parameter range.The correlation between various processing parameters,processing quality and accuracy was revealed,and various optimized process combinations were summarized.Verification through computed Tomography testing of the specimens confirmed the effectiveness and precision of this approach.The approach introduced in this research provides a way for quickly and efficiently optimizing the process parameters and establishing process-property relationships for LPBF,which has broad application value. 展开更多
关键词 laser powder bed fusion process parameter high-throughput Gaussian process microchannel accuracy
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Microfluidic Barcode Biochips for High-Throughput Real-Time Biomolecule and Single-Cell Screening 认领 引用 被引量：1
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作者 Jiaoyan Qiu Yanbo Liang +4 位作者 Chao Wang Yang Yu Yu Zhang Hong Liu Lin Han 《Engineering》 SCIE EI CSCD 2025年第3期130-146,共17页
The real-time screening of biomolecules and single cells in biochips is extremely important for disease prediction and diagnosis,cellular analysis,and life science research.Barcode biochip technology,which is integrat... The real-time screening of biomolecules and single cells in biochips is extremely important for disease prediction and diagnosis,cellular analysis,and life science research.Barcode biochip technology,which is integrated with microfluidics,typically comprises barcode array,sample loading,and reaction unit array chips.Here,we present a review of microfluidics barcode biochip analytical approaches for the high-throughput screening of biomolecules and single cells,including protein biomarkers,microRNA(miRNA),circulating tumor DNA(ctDNA),single-cell secreted proteins,single-cell exosomes,and cell interactions.We begin with an overview of current high-throughput detection and analysis approaches.Following this,we outline recent improvements in microfluidic devices for biomolecule and single-cell detection,highlighting the benefits and limitations of these devices.This paper focuses on the research and development of microfluidic barcode biochips,covering their self-assembly substrate materials and their specific applications with biomolecules and single cells.Looking forward,we explore the prospects and challenges of this technology,with the aim of contributing toward the use of microfluidic barcode detection biochips in medical diagnostics and therapies,and their large-scale commercialization. 展开更多
关键词 High-throughput Microfluidic barcode biochip Single-cell analysis Biomolecules
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High-throughput screening of CO2 cycloaddition MOF catalyst with an explainable machine learning model 认领 引用 被引量：1
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作者 Xuefeng Bai Yi Li +3 位作者 Yabo Xie Qiancheng Chen Xin Zhang Jian-Rong Li 《Green Energy & Environment》 SCIE EI CAS CSCD 2025年第1期132-138,共7页
The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF str... The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF structure database is available.In this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO2 cycloaddition reaction.The descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification criterion.The feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were discovered.Among them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction. 展开更多
关键词 Metal-organic frameworks High-throughput screening Machine learning Explainable model CO2cycloaddition
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High-throughput sequencing unveils microbial succession patterns in restored Hulun Buir Sandy Land,northern China 认领 引用 被引量：1
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作者 PENG Tiantian HAO Haojing +5 位作者 GUAN Xiao LI Junsheng DIAO Zhaoyan BU He WO Qiang SONG Ni 《Journal of Arid Land》 SCIE CSCD 2025年第9期1297-1313,共17页
In recent years,intensive human activities have increased the intensity of desertification,driving continual desertification process of peripheral meadows.To investigate the effects of restoration on soil microbial co... In recent years,intensive human activities have increased the intensity of desertification,driving continual desertification process of peripheral meadows.To investigate the effects of restoration on soil microbial communities,we analyzed vegetation-soil relationships in the Hulun Buir Sandy Land,northern China.Through the use of high-throughput sequencing,we examined the structure and diversity in the bacterial and fungal communities within the 0-20 cm soil layer after 9-15 a of restoration.Different slope positions were analyzed and spatial heterogeneity was assessed.The results showed progressive improvements in soil properties and vegetation with the increase of restoration duration,and the following order was as follows:bottom slope>middle slope>crest slope.During the restoration in the Hulun Buir Sandy Land,the bacterial communities were dominated by Proteobacteria,Actinobacteria,and Acidobacteria,whereas the fungal communities were dominated by Ascomycota and Basidiomycota.Eutrophic bacterial abundance increased with the restoration duration,whereas oligotrophic bacterial and fungal abundance levels decreased.The soil bacterial abundance significantly increased with the increasing restoration duration,whereas the fungal diversity decreased after 11 a of restoration,except that at the crest slope.Redundancy analysis showed that pH,soil moisture content,total nitrogen,and vegetation-related factors affected the bacterial community structure(45.43%of the total variance explained).Canonical correspondence analysis indicated that pH,total phosphorus,and vegetation-related factors shaped the bacterial community structure(31.82%of the total variance explained).Structural equation modeling highlighted greater bacterial responses(R2=0.49-0.79)to changes in environmental factors than those of fungi(R2=0.20-0.48).The soil bacterial community was driven mainly by pH,soil moisture content,electrical conductivity,plant coverage,and litter dry weight.The abundance and diversity of the soil fungal community were mainly driven by plant coverage,litter dry weight,and herbaceous aboveground biomass,while there was no significant correlation between the soil fungal community structure and environmental factors.These findings highlighted divergent microbial succession patterns and environmental sensitivities during sandy grassland restoration. 展开更多
关键词 revegetation soil microbes high-throughput sequencing sandy grassland dunes
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Design strategies for fast-charging multiphase Na-ion layered cathodes:Dopant selection via computational high-throughput screening 认领 引用 被引量：1
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作者 Taehyun Park Juo Kim +2 位作者 Yerim Jung Jiwon Sun Kyoungmin Min 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2025年第8期103-113,共11页
For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered tr... For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered transition metal oxides(LTMOs),which leverage the synergistic properties of two distinct monophasic LTMOs,have garnered significant attention;however,their efficacy under fast-charging conditions remains underexplored.In this study,we developed a high-throughput computational screening framework to identify optimal dopants that maximize the electrochemical performance of LTMOs.Specifically,we evaluated the efficacy of 32 dopants based on P2/O3-type Mn/Fe-based NaxMn0.5Fe0.5O2(NMFO)cathode material.Multiphase LTMOs satisfying criteria for thermodynamic and structural stability,minimized phase transitions,and enhanced Na+diffusion were systematically screened for their suitability in fast-charging applications.The analysis identified two dopants,Ti and Zr,which met all predefined screening criteria.Furthermore,we ranked and scored dopants based on their alignment with these criteria,establishing a comprehensive dopant performance database.These findings provide a robust foundation for experimental exploration and offer detailed guidelines for tailoring dopants to optimize fast-charging SIBs. 展开更多
关键词 Sodium-ion battery cathode Multiphase layered transition metal oxide Fast-charging High-throughput computational screening Doping strategy
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Computer Vision-Assisted High-Throughput Screening of Crystallization Additives for Crystal Size,Shape,and Agglomeration Regulation 认领 引用 被引量：1
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作者 Jian Liu Tuo Yao +4 位作者 Muyang Li Sohrab Rohani Jingkang Wang Zhenguo Gao Junbo Gong 《Engineering》 SCIE EI CSCD 2025年第11期308-319,共12页
Additives are widely employed to regulate the morphology,size,and agglomeration degree of crystalline materials during crystallization to enhance their functional,physical,and powder properties.However,the existing me... Additives are widely employed to regulate the morphology,size,and agglomeration degree of crystalline materials during crystallization to enhance their functional,physical,and powder properties.However,the existing methods for screening and validating target additives require a large quantity of materials and involve tedious molecular simulation/crystallization experiments,making them time-consuming,resource-intensive,and reliant on the operator’s experience level.To overcome these challenges,we proposed a computer vision-assisted high-throughput additive screening system(CV-HTPASS)which comprises a high-throughput additive screening device,in situ imaging equipment,and an artificial intelligence(AI)-assisted image-analysis algorithm.Using the CV-HTPASS,we performed high-throughput screening experiments on additives to regulate the succinic acid crystal properties,generating thousands of crystal images with diverse crystal morphologies.To extract valuable crystal information from the massive data and improve the analysis accuracy and efficiency,the AI-based image-analysis algorithm was implemented innovatively for the segmentation,classification,and data mining of crystals with four morphologies to further screen the target additive.Subsequently,scale-up crystallization experiments conducted under optimized conditions demonstrated that succinic acid products exhibited a preferred cubic morphology,reduced agglomeration degree,narrowed crystal size distribution,and improved powder properties.The proposed CV-HTPASS offers a highly efficient approach for scale-up experiments.Further,it provides a platform for the screening of additives and the optimization of the powder properties of crystal products in industrial-scale crystallization processes. 展开更多
关键词 High-throughput screening Computer visionImage analysis Solution crystallization Powder property optimization
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