The adenosine subfamily G protein-coupled receptors A_(2A)R and A_(2B)R have been identified as promising cancer immunotherapy candidates.One of the A_(2A)R/A_(2B)R dual antagonists,AB928,has progressed to a phaseⅡcl...The adenosine subfamily G protein-coupled receptors A_(2A)R and A_(2B)R have been identified as promising cancer immunotherapy candidates.One of the A_(2A)R/A_(2B)R dual antagonists,AB928,has progressed to a phaseⅡclinical trial to treat rectal cancer.However,the precise mechanism underlying its dual-antagonistic properties remains elusive.Herein,we report crystal structures of the A_(2A)R complexed with AB928 and a selective A_(2A)R antagonist 2-118.The structures revealed a common binding mode on A_(2A)R,wherein the ligands established extensive interactions with residues from the orthosteric and secondary pockets.In contrast,the cAMP assay and A_(2A)R and A_(2B)R molecular dynamics simulations indicated that the ligands adopted distinct binding modes on A_(2B)R.Detailed analysis of their chemical structures suggested that AB928 readily adapted to the A_(2B)R pocket,while 2-118 did not due to intrinsic differences.This disparity potentially accounted for the difference in inhibitory efficacy between A_(2B)R and A_(2A)R.This study serves as a valuable structural template for the future development of selective or dual inhibitors targeting A_(2A)R/A_(2B)R for cancer therapy.展开更多
Microbial communities in sediment are an important indicator linking to environmental pollution in urban river systems.However,how the diversity and structure of bacterial communities in sediments from an urban river ...Microbial communities in sediment are an important indicator linking to environmental pollution in urban river systems.However,how the diversity and structure of bacterial communities in sediments from an urban river network respond to different environmental factors has not been well studied.The goal of this study was to understand the patterns of bacterial communities in sediments from a highly dense urbanized river network in the lower Yangtze River Delta by Illumina MiSeq sequencing.The correlations between bacterial communities,the environmental gradient and geographical distance were analyzed by redundancy analysis(RDA)and network methods.The diversity and richness of bacterial community in sediments increased from upstream to downstream consistently with the accumulation of nutrient in the urban river network.Bacterial community composition and structure showed obvious spatial changes,leading to two distinct groups,which were significantly related to the characteristics of nutrient and heavy metal in sediments.Humic substance,available nitrogen,available phosphorus,Zn,Cu,Hg and As were selected as the key environmental factors shaping the bacterial community in sediments based on RDA.The co-occurrence patterns of bacterial networks showed that positive interaction between bacterial communities increased but the connectivity among bacterial genera and stability of sediment ecosystem reduced under a higher content of nutrient and heavy metal in average.The sensitive and ubiquitous taxa with an overproportional response to key environmental factors were detected as indicator species,which provided a novel method for the prediction of the pollution risk of sediment in an urban river network.展开更多
Application of aerogel fibers in thermal insulating garments have sparked a substantial interest.However,achieving a high porosity and low thermal conductivity for aerogel fibers remain challenging,despite the innovat...Application of aerogel fibers in thermal insulating garments have sparked a substantial interest.However,achieving a high porosity and low thermal conductivity for aerogel fibers remain challenging,despite the innovative designs of porous struc-ture.Herein,we fabricated lightweight and super-thermal insulating polyimide(PI)aerogel fibers via freeze-spinning by using polyvinyl alcohol(PVA)as a pore regulator.The high affinity of PVA with water enables it to accelerate the ice crystal nucleation,adjust pore formation,and construct a controllable porous structure of PI aerogel fiber.The as-fabricated PI aerogel fiber has a considerable reduced pore size,high porosity(95.6%),improved flexibility and mechanical strength,and can be woven into fabrics.The PI aerogel fabric exhibits low thermal conductivity and excellent thermal insulation in a wide range of temperature(from-196 to 300℃).Furthermore,the PI aerogel fabrics can be easily functionalized to expand their applications,such as in intelligent temperature regulation and photothermal conversion.These results demonstrate that the aerogel fibers/fabric are promising materials for next-generation textile materials for personal thermal management.展开更多
Transcriptional phenotypic drug discovery has achieved great success,and various compound perturbation-based data resources,such as connectivity map(CMap)and library of integrated network-based cellular signatures(LIN...Transcriptional phenotypic drug discovery has achieved great success,and various compound perturbation-based data resources,such as connectivity map(CMap)and library of integrated network-based cellular signatures(LINCS),have been presented.Computational strategies fully mining these resources for phenotypic drug discovery have been proposed.Among them,the fundamental issue is to define the proper similarity between transcriptional profiles.Traditionally,such similarity has been defined in an unsupervised way.However,due to the high dimensionality and the existence of high noise in high-throughput data,similarity defined in the traditional way lacks robustness and has limited performance.To this end,we present Dr Sim,which is a learning-based framework that automatically infers similarity rather than defining it.We evaluated Dr Sim on publicly available in vitro and in vivo datasets in drug annotation and repositioning.The results indicated that Dr Sim outperforms the existing methods.In conclusion,by learning transcriptional similarity,Dr Sim facilitates the broad utility of high-throughput transcriptional perturbation data for phenotypic drug discovery.The source code and manual of Dr Sim are available at https://github.com/bm2-lab/Dr Sim/.展开更多
Metal-organic frameworks(MOFs)hold great promises as membrane candidates for highly efficient separation applications,benefiting from the diversified structures,high surface areas and adjustable chemical functionaliti...Metal-organic frameworks(MOFs)hold great promises as membrane candidates for highly efficient separation applications,benefiting from the diversified structures,high surface areas and adjustable chemical functionalities.However,non-selective defects and framework flexibility are two main concerns which would attenuate the ultimate separation performance and stability.Modification helps to orientationally optimize the gas adsorption and diffusion behaviors via manipulation towards framework chemical components,aperture sizes,nanocages,and intercrystalline/intracrystalline defects,consequently promoting membrane separation performance and membrane stability.In view of recent progresses of modification on MOF-based membranes,two categories of modification strategies were summarized,namely post-synthetic modification and in situ modification.And the merits and demerits are elucidated.Furthermore,challenges and opportunities for the current modification strategies were discussed from our perspectives,with an expectation to provide guidelines to the future development of MOF-based membranes which were aspired to reach the commercially attractive performance region.展开更多
Base editing technology is being increasingly applied in genome engineering,but the current strategy for designing guide RNAs(gRNAs)relies substantially on empirical experience rather than a dependable and efficient i...Base editing technology is being increasingly applied in genome engineering,but the current strategy for designing guide RNAs(gRNAs)relies substantially on empirical experience rather than a dependable and efficient in silico design.Furthermore,the pleiotropic effect of base editing on disease treatment remains unexplored,which prevents its further clinical usage.Here,we presented BExplorer,an integrated and comprehensive computational pipeline to optimize the design of gRNAs for 26 existing types of base editors in silico.Using BExplorer,we described its results for two types of mainstream base editors,BE3 and ABE7.10,and evaluated the pleiotropic effects of the corresponding base editing loci.BExplorer revealed 524 and 900 editable pathogenic single nucleotide polymorphism(SNP)loci in the human genome together with the selected optimized gRNAs for BE3 and ABE7.10,respectively.In addition,the impact of 707 edited pathogenic SNP loci following base editing on 131 diseases was systematically explored by revealing their pleiotropic effects,indicating that base editing should be carefully utilized given the potential pleiotropic effects.Collectively,the systematic exploration of optimized base editing gRNA design and the corresponding pleiotropic effects with BExplorer provides a computational basis for applying base editing in disease treatment.展开更多
The rapid accumulation of large-scale single-cell RNA-seq datasets from multiple institutions presents remarkable opportunities for automatically cell annotations through integrative analyses.However,the privacy issue...The rapid accumulation of large-scale single-cell RNA-seq datasets from multiple institutions presents remarkable opportunities for automatically cell annotations through integrative analyses.However,the privacy issue has existed but being ignored,since we are limited to access and utilize all the reference datasets distributed in different institutions globally due to the prohibited data transmission across institutions by data regulation laws.To this end,we present scPrivacy,which is the first and generalized automatically single-cell type identification prototype to facilitate single cell annotations in a data privacy-preserving collaboration manner.We evaluated scPrivacy on a comprehensive set of publicly available benchmark datasets for single-cell type identification to stimulate the scenario that the reference datasets are rapidly generated and distributed in multiple institutions,while they are prohibited to be integrated directly or exposed to each other due to the data privacy regulations,demonstrating its effectiveness,time efficiency and robustness for privacy-preserving integration of multiple institutional datasets in single cell annotations.展开更多
基金supported by the National Key Research and Development Program of China(2018YFA0507001)the Basic Research Program of Science and Technology Commission of Shanghai Municipality(21JC1402400)+1 种基金the National Natural Science Foundation of China(32171215,81972828,82172644,82273857 and 81830083)the National Key Scientific Infrastructure for Translational Medicine(Shanghai)(TMSK-2021-120)。
文摘The adenosine subfamily G protein-coupled receptors A_(2A)R and A_(2B)R have been identified as promising cancer immunotherapy candidates.One of the A_(2A)R/A_(2B)R dual antagonists,AB928,has progressed to a phaseⅡclinical trial to treat rectal cancer.However,the precise mechanism underlying its dual-antagonistic properties remains elusive.Herein,we report crystal structures of the A_(2A)R complexed with AB928 and a selective A_(2A)R antagonist 2-118.The structures revealed a common binding mode on A_(2A)R,wherein the ligands established extensive interactions with residues from the orthosteric and secondary pockets.In contrast,the cAMP assay and A_(2A)R and A_(2B)R molecular dynamics simulations indicated that the ligands adopted distinct binding modes on A_(2B)R.Detailed analysis of their chemical structures suggested that AB928 readily adapted to the A_(2B)R pocket,while 2-118 did not due to intrinsic differences.This disparity potentially accounted for the difference in inhibitory efficacy between A_(2B)R and A_(2A)R.This study serves as a valuable structural template for the future development of selective or dual inhibitors targeting A_(2A)R/A_(2B)R for cancer therapy.
基金the National Water Pollution Control and Treatment Science and Technology Major Project of China(No.2017ZX07205)the China Postdoctoral Science Foundation(No.2017M620801)+1 种基金National Natural Science Foundation of China(Grant No.41702262)Zhejiang Provincial Natural Science Foundation of China(No.LY17D060004).
文摘Microbial communities in sediment are an important indicator linking to environmental pollution in urban river systems.However,how the diversity and structure of bacterial communities in sediments from an urban river network respond to different environmental factors has not been well studied.The goal of this study was to understand the patterns of bacterial communities in sediments from a highly dense urbanized river network in the lower Yangtze River Delta by Illumina MiSeq sequencing.The correlations between bacterial communities,the environmental gradient and geographical distance were analyzed by redundancy analysis(RDA)and network methods.The diversity and richness of bacterial community in sediments increased from upstream to downstream consistently with the accumulation of nutrient in the urban river network.Bacterial community composition and structure showed obvious spatial changes,leading to two distinct groups,which were significantly related to the characteristics of nutrient and heavy metal in sediments.Humic substance,available nitrogen,available phosphorus,Zn,Cu,Hg and As were selected as the key environmental factors shaping the bacterial community in sediments based on RDA.The co-occurrence patterns of bacterial networks showed that positive interaction between bacterial communities increased but the connectivity among bacterial genera and stability of sediment ecosystem reduced under a higher content of nutrient and heavy metal in average.The sensitive and ubiquitous taxa with an overproportional response to key environmental factors were detected as indicator species,which provided a novel method for the prediction of the pollution risk of sediment in an urban river network.
基金supported by the National Natural Science Foundation of China(52073053)Shanghai Rising-Star Program(21QA1400300)+2 种基金Innovation Program of Shanghai Municipal Education Commission(2021-01-07-00-03-E00108)Science and Technology Commission of Shanghai Municipality(20520741100)China Postdoctoral Science Foundation(2021M690596).
文摘Application of aerogel fibers in thermal insulating garments have sparked a substantial interest.However,achieving a high porosity and low thermal conductivity for aerogel fibers remain challenging,despite the innovative designs of porous struc-ture.Herein,we fabricated lightweight and super-thermal insulating polyimide(PI)aerogel fibers via freeze-spinning by using polyvinyl alcohol(PVA)as a pore regulator.The high affinity of PVA with water enables it to accelerate the ice crystal nucleation,adjust pore formation,and construct a controllable porous structure of PI aerogel fiber.The as-fabricated PI aerogel fiber has a considerable reduced pore size,high porosity(95.6%),improved flexibility and mechanical strength,and can be woven into fabrics.The PI aerogel fabric exhibits low thermal conductivity and excellent thermal insulation in a wide range of temperature(from-196 to 300℃).Furthermore,the PI aerogel fabrics can be easily functionalized to expand their applications,such as in intelligent temperature regulation and photothermal conversion.These results demonstrate that the aerogel fibers/fabric are promising materials for next-generation textile materials for personal thermal management.
基金supported by the National Key R&D Program of China(Grant Nos.2021YFF1201200 and 2021YFF1200900)the National Natural Science Foundation of China(Grant Nos.31970638 and 61572361)+5 种基金the Shanghai Natural Science Foundation Program(Grant No.17ZR1449400)the Shanghai Artificial Intelligence Technology Standard Project(Grant No.19DZ2200900)the Shanghai Shuguang scholars projectthe We Bank scholars projectthe Shanghai outstanding academic leaders projectthe Fundamental Research Funds for the Central Universities,China。
文摘Transcriptional phenotypic drug discovery has achieved great success,and various compound perturbation-based data resources,such as connectivity map(CMap)and library of integrated network-based cellular signatures(LINCS),have been presented.Computational strategies fully mining these resources for phenotypic drug discovery have been proposed.Among them,the fundamental issue is to define the proper similarity between transcriptional profiles.Traditionally,such similarity has been defined in an unsupervised way.However,due to the high dimensionality and the existence of high noise in high-throughput data,similarity defined in the traditional way lacks robustness and has limited performance.To this end,we present Dr Sim,which is a learning-based framework that automatically infers similarity rather than defining it.We evaluated Dr Sim on publicly available in vitro and in vivo datasets in drug annotation and repositioning.The results indicated that Dr Sim outperforms the existing methods.In conclusion,by learning transcriptional similarity,Dr Sim facilitates the broad utility of high-throughput transcriptional perturbation data for phenotypic drug discovery.The source code and manual of Dr Sim are available at https://github.com/bm2-lab/Dr Sim/.
基金the National Natural Science Foundation of China,China(21808215)the Dalian Institute of Chemical Physics,CAS,China(ZZBS201815)+1 种基金the DNL Cooperation Fund,Chinese Academy of Sciences,China(DNL201917)the Liaoning Revitalization Talents Program,China(XLYC1801004).
文摘Metal-organic frameworks(MOFs)hold great promises as membrane candidates for highly efficient separation applications,benefiting from the diversified structures,high surface areas and adjustable chemical functionalities.However,non-selective defects and framework flexibility are two main concerns which would attenuate the ultimate separation performance and stability.Modification helps to orientationally optimize the gas adsorption and diffusion behaviors via manipulation towards framework chemical components,aperture sizes,nanocages,and intercrystalline/intracrystalline defects,consequently promoting membrane separation performance and membrane stability.In view of recent progresses of modification on MOF-based membranes,two categories of modification strategies were summarized,namely post-synthetic modification and in situ modification.And the merits and demerits are elucidated.Furthermore,challenges and opportunities for the current modification strategies were discussed from our perspectives,with an expectation to provide guidelines to the future development of MOF-based membranes which were aspired to reach the commercially attractive performance region.
基金supported by the National Key R&D Program of China(Grant No.2021YFF1201200)the National Natural Science Foundation of China(Grant Nos.31970638 and 61572361)+2 种基金the Shanghai Natural Science Foundation Program(Grant No.17ZR1449400)the Shanghai Artificial Intelligence Technology Standard Project(Grant No.19DZ2200900)the Shanghai Shuguang scholars project,the WeBank scholars project,and the Fundamental Research Funds for the Central Universities.
文摘Base editing technology is being increasingly applied in genome engineering,but the current strategy for designing guide RNAs(gRNAs)relies substantially on empirical experience rather than a dependable and efficient in silico design.Furthermore,the pleiotropic effect of base editing on disease treatment remains unexplored,which prevents its further clinical usage.Here,we presented BExplorer,an integrated and comprehensive computational pipeline to optimize the design of gRNAs for 26 existing types of base editors in silico.Using BExplorer,we described its results for two types of mainstream base editors,BE3 and ABE7.10,and evaluated the pleiotropic effects of the corresponding base editing loci.BExplorer revealed 524 and 900 editable pathogenic single nucleotide polymorphism(SNP)loci in the human genome together with the selected optimized gRNAs for BE3 and ABE7.10,respectively.In addition,the impact of 707 edited pathogenic SNP loci following base editing on 131 diseases was systematically explored by revealing their pleiotropic effects,indicating that base editing should be carefully utilized given the potential pleiotropic effects.Collectively,the systematic exploration of optimized base editing gRNA design and the corresponding pleiotropic effects with BExplorer provides a computational basis for applying base editing in disease treatment.
基金supported by the National Key Research and Development Program of China(2021YFF1200900,2021YFF1201200)the National Natural Science Foundation of China(31970638,61572361)+3 种基金the Shanghai Artificial Intelligence Technology Standard Project(19DZ2200900)the Shanghai Shuguang Scholars ProjectWeBank Scholars Projectthe Fundamental Research Funds for the Central Universities。
文摘The rapid accumulation of large-scale single-cell RNA-seq datasets from multiple institutions presents remarkable opportunities for automatically cell annotations through integrative analyses.However,the privacy issue has existed but being ignored,since we are limited to access and utilize all the reference datasets distributed in different institutions globally due to the prohibited data transmission across institutions by data regulation laws.To this end,we present scPrivacy,which is the first and generalized automatically single-cell type identification prototype to facilitate single cell annotations in a data privacy-preserving collaboration manner.We evaluated scPrivacy on a comprehensive set of publicly available benchmark datasets for single-cell type identification to stimulate the scenario that the reference datasets are rapidly generated and distributed in multiple institutions,while they are prohibited to be integrated directly or exposed to each other due to the data privacy regulations,demonstrating its effectiveness,time efficiency and robustness for privacy-preserving integration of multiple institutional datasets in single cell annotations.
