Labeled data is widely used in various classification tasks.However,there is a huge challenge that labels are often added artificially.Wrong labels added by malicious users will affect the training effect of the model...Labeled data is widely used in various classification tasks.However,there is a huge challenge that labels are often added artificially.Wrong labels added by malicious users will affect the training effect of the model.The unreliability of labeled data has hindered the research.In order to solve the above problems,we propose a framework of Label Noise Filtering and Missing Label Supplement(LNFS).And we take location labels in Location-Based Social Networks(LBSN)as an example to implement our framework.For the problem of label noise filtering,we first use FastText to transform the restaurant's labels into vectors,and then based on the assumption that the label most similar to all other labels in the location is most representative.We use cosine similarity to judge and select the most representative label.For the problem of label missing,we use simple common word similarity to judge the similarity of users'comments,and then use the label of the similar restaurant to supplement the missing labels.To optimize the performance of the model,we introduce game theory into our model to simulate the game between the malicious users and the model to improve the reliability of the model.Finally,a case study is given to illustrate the effectiveness and reliability of LNFS.展开更多
Edge-computing-enabled smart greenhouses are a representative application of the Internet of Things(IoT)technology,which can monitor the environmental information in real-time and employ the information to contribute ...Edge-computing-enabled smart greenhouses are a representative application of the Internet of Things(IoT)technology,which can monitor the environmental information in real-time and employ the information to contribute to intelligent decision-making.In the process,anomaly detection for wireless sensor data plays an important role.However,the traditional anomaly detection algorithms originally designed for anomaly detection in static data do not properly consider the inherent characteristics of the data stream produced by wireless sensors such as infiniteness,correlations,and concept drift,which may pose a considerable challenge to anomaly detection based on data stream and lead to low detection accuracy and efficiency.First,the data stream is usually generated quickly,which means that the data stream is infinite and enormous.Hence,any traditional off-line anomaly detection algorithm that attempts to store the whole dataset or to scan the dataset multiple times for anomaly detection will run out of memory space.Second,there exist correlations among different data streams,and traditional algorithms hardly consider these correlations.Third,the underlying data generation process or distribution may change over time.Thus,traditional anomaly detection algorithms with no model update will lose their effects.Considering these issues,a novel method(called DLSHiForest)based on Locality-Sensitive Hashing and the time window technique is proposed to solve these problems while achieving accurate and efficient detection.Comprehensive experiments are executed using a real-world agricultural greenhouse dataset to demonstrate the feasibility of our approach.Experimental results show that our proposal is practical for addressing the challenges of traditional anomaly detection while ensuring accuracy and efficiency.展开更多
Chikungunya virus(CHIKV)is a re-emerging mosquito-transmitted RNA virus causing joint and muscle pain.To better understand how CHIKV rewires the host cell and usurps host cell functions,we generated a systematic CHIKV...Chikungunya virus(CHIKV)is a re-emerging mosquito-transmitted RNA virus causing joint and muscle pain.To better understand how CHIKV rewires the host cell and usurps host cell functions,we generated a systematic CHIKV-human protein-protein interaction map and revealed several novel connections that will inform further mechanistic studies.One of these novel interactions,between the viral protein E1 and STIP1 homology and U-box containing protein 1(STUB1),was found to mediate ubiquitination of E1 and degrade E1 through the proteasome.Capsid associated with G3BP1,G3BP2 and AAAþATPase valosin-containing protein(VCP).Furthermore,VCP inhibitors blocked CHIKV infection,suggesting VCP could serve as a therapeutic target.Further work is required to fully understand the functional consequences of these interactions.Given that CHIKV proteins are conserved across alphaviruses,many virus-host protein-protein interactions identified in this study might also exist in other alphaviruses.Construction of interactome of CHIKV provides the basis for further studying the function of alphavirus biology.展开更多
Whole-genome genotyping methods are important for breeding.However,it has been challenging to develop a robust method for simultaneous foreground and background genotyping that can easily be adapted to different genes...Whole-genome genotyping methods are important for breeding.However,it has been challenging to develop a robust method for simultaneous foreground and background genotyping that can easily be adapted to different genes and species.In our study,we accidently discovered that in adapter ligation-mediated PCR,the amplification by primertemplate mismatched annealing(PTMA)along the genome could generate thousands of stable PCR products.Based on this observation,we consequently developed a novel method for simultaneous foreground and background integrated genotyping by sequencing(FBI-seq)using one specific primer,in which foreground genotyping is performed by primer-template perfect annealing(PTPA),while background genotyping employs PTMA.Unlike DNA arrays,multiple PCR,or genome target enrichments,FBI-seq requires little preliminary work for primer design and synthesis,and it is easily adaptable to different foreground genes and species.FBI-seq therefore provides a prolific,robust,and accurate method for simultaneous foreground and background genotyping to facilitate breeding in the postgenomics era.展开更多
We present a conceptual framework for understanding and formulating ion transport in concentrated solutions, which pictures the ion transport as an ion-vacancy coupled charge transfer reaction. A key element in this p...We present a conceptual framework for understanding and formulating ion transport in concentrated solutions, which pictures the ion transport as an ion-vacancy coupled charge transfer reaction. A key element in this picture is that the transport of an ion from an occupied to unoccupied site involves a transition state which exerts double volume exclusion. An ab initio random walk model is proposed to describe this process. Subsequent coarse-graining results in a continuum formula as a function of chemical potentials of the constituents, which are further derived from a lattice-gas model. The subtlety here is that what has been taken to be the chemical potential of the ion in the past is actually that of the ion-vacancy couple. By aid of this new concept, the driving force of ion transport is essentially the chemical affinity of the ion-vacancy coupled charge transfer reaction, which is a useful concept to unify transport and reaction, two fundamental processes in electrochemistry. This phenomenological model is parameterized for a specific material by the aid of first-principles calculations. Moreover, its extension to multiple-component systems is discussed.展开更多
B cell response plays a critical role against SARS-CoV-2 infection.However,little is known about the diversity and frequency of the paired SARS-CoV-2 antigen-specific BCR repertoire after SARS-CoV-2 infection.Here,we ...B cell response plays a critical role against SARS-CoV-2 infection.However,little is known about the diversity and frequency of the paired SARS-CoV-2 antigen-specific BCR repertoire after SARS-CoV-2 infection.Here,we performed single-cell RNA sequencing and VDJ sequencing using the memory and plasma B cells isolated from five convalescent COVID-19 patients,and analyzed the spectrum and transcriptional heterogeneity of antibody immune responses.Via linking BCR to antigen specificity through sequencing(LIBRA-seq),we identified a distinct activated memory B cell subgroup(CD11c^(high) CD95^(high))had a higher proportion of SARS-CoV-2 antigen-labeled cells compared with memory B cells.Our results revealed the diversity of paired BCR repertoire and the non-stochastic pairing of SARS-CoV-2 antigen-specific immunoglobulin heavy and light chains after SARS-CoV-2 infection.The public antibody clonotypes were shared by distinct convalescent individuals.Moreover,several antibodies isolated by LIBRA-seq showed high binding affinity against SARS-CoV-2 receptor-binding domain(RBD)or nucleoprotein(NP)via ELISA assay.Two RBD-reactive antibodies C14646P3S and C2767P3S isolated by LIBRA-seq exhibited high neutralizing activities against both pseudotyped and authentic SARS-CoV-2 viruses in vitro.Our study provides fundamental insights into B cell response following SARS-CoV-2 infection at the single-cell level.展开更多
The microRNAs (miRNAs) play an important role in regulating myogenesis by targeting mRNA. However, the understanding of miRNAs in skeletal muscle development and diseases is unclear. In this study, we firstly performe...The microRNAs (miRNAs) play an important role in regulating myogenesis by targeting mRNA. However, the understanding of miRNAs in skeletal muscle development and diseases is unclear. In this study, we firstly performed the transcriptome profiling in differentiating C2C12 myoblast cells. Totally, we identified 187 miRNAs and 4260 mRNAs significantly differentially expressed that were involved in myoblast differentiation. We carried out validation of microarray data based on 5 mRNAs and 5 miRNAs differentially expressed and got a consistent result. Then we constructed and validated the significantly up- and down-regulated mRNA-miRNA interaction networks. Four interaction pairs (miR-145a-5p-Fscn1, miR-200c-5p-Tmigd1, miR-27a-5p-Sln and miR-743a-5p-Mob1b) with targeted relationships in differentiated myoblast cells were demonstrated. They are all closely related to myoblast development. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated cell cycle signals important for exploring skeletal muscle development and disease. Functionally, we discovered that miR-743a targeting gene Mps One Binder Kinase Activator-Like 1B (Mob1b) gene in differentiated C2C12. The up-regulated miR-743a can promote the differentiation of C2C12 myoblast. While the down-regulated Mob1b plays a negative role in differentiation. In addition, the expression profile of miR-743a and Mob1b are consistent with skeletal muscle recovery after Cardiotoxin (CTX) injury. Our study revealed that miR-743a-5p regulates myoblast differentiation by targeting Mob1b involved in skeletal muscle development and regeneration. Our findings made a further exploration for mechanisms in myogenesis and might provide potential possible miRNA-based target therapies for skeletal muscle regeneration and disease in the near future.展开更多
As the main parent and guardian, mothers are often concerned with the study performance of their children.More specifically, most mothers are eager to know the concrete examination scores of their children. However,wi...As the main parent and guardian, mothers are often concerned with the study performance of their children.More specifically, most mothers are eager to know the concrete examination scores of their children. However,with the continuous progress of modern education systems, most schools or teachers have now been forbidden to release sensitive student examination scores to the public due to privacy concerns, which has made it infeasible for mothers to know the real study level or examination performance of their children. Therefore, a conflict has come to exist between teachers and mothers, which harms the general growing up of students in their study. In view of this challenge, we propose a Privacy-aware Examination Results Ranking(PERR) method to attempt at balancing teachers’ privacy disclosure concerns and the mothers’ concerns over their children’s examination performance.By drawing on a relevant case study, we prove the effectiveness of the proposed PERR method in evaluating and ranking students according to their examination scores while at the same time securing sensitive student information.展开更多
基金supported by the National Natural Science Foundation of China(No.61872219)the Natural Science Foundation of Shandong Province(ZR2019MF001).
文摘Labeled data is widely used in various classification tasks.However,there is a huge challenge that labels are often added artificially.Wrong labels added by malicious users will affect the training effect of the model.The unreliability of labeled data has hindered the research.In order to solve the above problems,we propose a framework of Label Noise Filtering and Missing Label Supplement(LNFS).And we take location labels in Location-Based Social Networks(LBSN)as an example to implement our framework.For the problem of label noise filtering,we first use FastText to transform the restaurant's labels into vectors,and then based on the assumption that the label most similar to all other labels in the location is most representative.We use cosine similarity to judge and select the most representative label.For the problem of label missing,we use simple common word similarity to judge the similarity of users'comments,and then use the label of the similar restaurant to supplement the missing labels.To optimize the performance of the model,we introduce game theory into our model to simulate the game between the malicious users and the model to improve the reliability of the model.Finally,a case study is given to illustrate the effectiveness and reliability of LNFS.
基金supported in part by the Fundamental Research Funds for the Central Universities under Grant No.30919011282.
文摘Edge-computing-enabled smart greenhouses are a representative application of the Internet of Things(IoT)technology,which can monitor the environmental information in real-time and employ the information to contribute to intelligent decision-making.In the process,anomaly detection for wireless sensor data plays an important role.However,the traditional anomaly detection algorithms originally designed for anomaly detection in static data do not properly consider the inherent characteristics of the data stream produced by wireless sensors such as infiniteness,correlations,and concept drift,which may pose a considerable challenge to anomaly detection based on data stream and lead to low detection accuracy and efficiency.First,the data stream is usually generated quickly,which means that the data stream is infinite and enormous.Hence,any traditional off-line anomaly detection algorithm that attempts to store the whole dataset or to scan the dataset multiple times for anomaly detection will run out of memory space.Second,there exist correlations among different data streams,and traditional algorithms hardly consider these correlations.Third,the underlying data generation process or distribution may change over time.Thus,traditional anomaly detection algorithms with no model update will lose their effects.Considering these issues,a novel method(called DLSHiForest)based on Locality-Sensitive Hashing and the time window technique is proposed to solve these problems while achieving accurate and efficient detection.Comprehensive experiments are executed using a real-world agricultural greenhouse dataset to demonstrate the feasibility of our approach.Experimental results show that our proposal is practical for addressing the challenges of traditional anomaly detection while ensuring accuracy and efficiency.
基金supported by National Natural Science Foundation of China (82072270 and 82272306)Taishan Scholars Program (tstp20221142)+1 种基金Shandong Provincial Natural Science Foundation (ZR2021QC095)Academic Promotion Programme of Shandong First Medical University (2019LJ001).
文摘Chikungunya virus(CHIKV)is a re-emerging mosquito-transmitted RNA virus causing joint and muscle pain.To better understand how CHIKV rewires the host cell and usurps host cell functions,we generated a systematic CHIKV-human protein-protein interaction map and revealed several novel connections that will inform further mechanistic studies.One of these novel interactions,between the viral protein E1 and STIP1 homology and U-box containing protein 1(STUB1),was found to mediate ubiquitination of E1 and degrade E1 through the proteasome.Capsid associated with G3BP1,G3BP2 and AAAþATPase valosin-containing protein(VCP).Furthermore,VCP inhibitors blocked CHIKV infection,suggesting VCP could serve as a therapeutic target.Further work is required to fully understand the functional consequences of these interactions.Given that CHIKV proteins are conserved across alphaviruses,many virus-host protein-protein interactions identified in this study might also exist in other alphaviruses.Construction of interactome of CHIKV provides the basis for further studying the function of alphavirus biology.
基金supported by the National Natural Science Foundation of China(31970379 and 32172086)the Jiangsu Collaborative Innovation Center for Modern Crop Production (JCIC-MCP)+3 种基金the National Key R&D Program of China (ZZ202001)the R&D program of Shenzhen (KCXFZ20211020164207012)the R&D program in key areas of Guangdong Province (2021B0707010006)the Science and Technology Planning Project of Guangdong Province (2022B0202060002)。
文摘Whole-genome genotyping methods are important for breeding.However,it has been challenging to develop a robust method for simultaneous foreground and background genotyping that can easily be adapted to different genes and species.In our study,we accidently discovered that in adapter ligation-mediated PCR,the amplification by primertemplate mismatched annealing(PTMA)along the genome could generate thousands of stable PCR products.Based on this observation,we consequently developed a novel method for simultaneous foreground and background integrated genotyping by sequencing(FBI-seq)using one specific primer,in which foreground genotyping is performed by primer-template perfect annealing(PTPA),while background genotyping employs PTMA.Unlike DNA arrays,multiple PCR,or genome target enrichments,FBI-seq requires little preliminary work for primer design and synthesis,and it is easily adaptable to different foreground genes and species.FBI-seq therefore provides a prolific,robust,and accurate method for simultaneous foreground and background genotyping to facilitate breeding in the postgenomics era.
基金supported by the National Natural Science Foundation of China (21673163, 21832004, 21802170)financial support from Central South University (502045001, 20180020050002)
文摘We present a conceptual framework for understanding and formulating ion transport in concentrated solutions, which pictures the ion transport as an ion-vacancy coupled charge transfer reaction. A key element in this picture is that the transport of an ion from an occupied to unoccupied site involves a transition state which exerts double volume exclusion. An ab initio random walk model is proposed to describe this process. Subsequent coarse-graining results in a continuum formula as a function of chemical potentials of the constituents, which are further derived from a lattice-gas model. The subtlety here is that what has been taken to be the chemical potential of the ion in the past is actually that of the ion-vacancy couple. By aid of this new concept, the driving force of ion transport is essentially the chemical affinity of the ion-vacancy coupled charge transfer reaction, which is a useful concept to unify transport and reaction, two fundamental processes in electrochemistry. This phenomenological model is parameterized for a specific material by the aid of first-principles calculations. Moreover, its extension to multiple-component systems is discussed.
基金supported by National Natural Science Foundation of China(31970881)and(82041046)to Y.Q.C.Shenzhen Science and Technology Program under Grant(JCYJ20190807154603596 and JCYJ20200109142438111)+2 种基金the National Key Research and Development Project(2020YFC0841700)to M.W.the National Natural Science Foundation of China(32041002)to D.Y.G.the Special Fund for COVID-19 Epidemic Prevention&Control of Zhuhai City of China granted to S.D.C.
文摘B cell response plays a critical role against SARS-CoV-2 infection.However,little is known about the diversity and frequency of the paired SARS-CoV-2 antigen-specific BCR repertoire after SARS-CoV-2 infection.Here,we performed single-cell RNA sequencing and VDJ sequencing using the memory and plasma B cells isolated from five convalescent COVID-19 patients,and analyzed the spectrum and transcriptional heterogeneity of antibody immune responses.Via linking BCR to antigen specificity through sequencing(LIBRA-seq),we identified a distinct activated memory B cell subgroup(CD11c^(high) CD95^(high))had a higher proportion of SARS-CoV-2 antigen-labeled cells compared with memory B cells.Our results revealed the diversity of paired BCR repertoire and the non-stochastic pairing of SARS-CoV-2 antigen-specific immunoglobulin heavy and light chains after SARS-CoV-2 infection.The public antibody clonotypes were shared by distinct convalescent individuals.Moreover,several antibodies isolated by LIBRA-seq showed high binding affinity against SARS-CoV-2 receptor-binding domain(RBD)or nucleoprotein(NP)via ELISA assay.Two RBD-reactive antibodies C14646P3S and C2767P3S isolated by LIBRA-seq exhibited high neutralizing activities against both pseudotyped and authentic SARS-CoV-2 viruses in vitro.Our study provides fundamental insights into B cell response following SARS-CoV-2 infection at the single-cell level.
基金This work was supported by the Basic and Applied Basic Research Foundation of Guangdong province (2019B1515120059), the National Natural Science Foundation of China (No. 31830090), Shenzhen Key Technology Projects (JSGG20180507182028625), the National Key Project (No. 2016ZX08009-003-006), and Major Tasks of Science and Technology Innovation Project of the Chinese Academy of Agricultural Sciences (No. CAAS-ZDRW202006).
文摘The microRNAs (miRNAs) play an important role in regulating myogenesis by targeting mRNA. However, the understanding of miRNAs in skeletal muscle development and diseases is unclear. In this study, we firstly performed the transcriptome profiling in differentiating C2C12 myoblast cells. Totally, we identified 187 miRNAs and 4260 mRNAs significantly differentially expressed that were involved in myoblast differentiation. We carried out validation of microarray data based on 5 mRNAs and 5 miRNAs differentially expressed and got a consistent result. Then we constructed and validated the significantly up- and down-regulated mRNA-miRNA interaction networks. Four interaction pairs (miR-145a-5p-Fscn1, miR-200c-5p-Tmigd1, miR-27a-5p-Sln and miR-743a-5p-Mob1b) with targeted relationships in differentiated myoblast cells were demonstrated. They are all closely related to myoblast development. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated cell cycle signals important for exploring skeletal muscle development and disease. Functionally, we discovered that miR-743a targeting gene Mps One Binder Kinase Activator-Like 1B (Mob1b) gene in differentiated C2C12. The up-regulated miR-743a can promote the differentiation of C2C12 myoblast. While the down-regulated Mob1b plays a negative role in differentiation. In addition, the expression profile of miR-743a and Mob1b are consistent with skeletal muscle recovery after Cardiotoxin (CTX) injury. Our study revealed that miR-743a-5p regulates myoblast differentiation by targeting Mob1b involved in skeletal muscle development and regeneration. Our findings made a further exploration for mechanisms in myogenesis and might provide potential possible miRNA-based target therapies for skeletal muscle regeneration and disease in the near future.
基金supported by the Ministry of Education in China Project of Humanities and Social Sciences (No. 20YJC880077)。
文摘As the main parent and guardian, mothers are often concerned with the study performance of their children.More specifically, most mothers are eager to know the concrete examination scores of their children. However,with the continuous progress of modern education systems, most schools or teachers have now been forbidden to release sensitive student examination scores to the public due to privacy concerns, which has made it infeasible for mothers to know the real study level or examination performance of their children. Therefore, a conflict has come to exist between teachers and mothers, which harms the general growing up of students in their study. In view of this challenge, we propose a Privacy-aware Examination Results Ranking(PERR) method to attempt at balancing teachers’ privacy disclosure concerns and the mothers’ concerns over their children’s examination performance.By drawing on a relevant case study, we prove the effectiveness of the proposed PERR method in evaluating and ranking students according to their examination scores while at the same time securing sensitive student information.
