Breast cancer is a malignant tumor originating from breast epithelial tissue.In essence,breast epithelial cells undergo gene mutation under the influence of carcinogenic factors,leading to abnormal cell proliferation ...Breast cancer is a malignant tumor originating from breast epithelial tissue.In essence,breast epithelial cells undergo gene mutation under the influence of carcinogenic factors,leading to abnormal cell proliferation and loss of organism regulation,ultimately leading to the formation of tumors with invasive and metastatic capabilities.Carcinogenic factors of breast cancer involve multiple cellular and molecular mechanisms.Among them,disseminated tumor cells(DTCs)are considered important for treating breast cancer.However,traditional bulk sequencing techniques have limitations,such as the inability to distinguish individual cell differences and dilution of information from key cell subpopulations(such as cancer stem cells and rare immune cells).Single-cell sequencing(scRNA-seq)overcomes the heterogeneity of tumors that traditional sequencing cannot capture by analysing the molecular characteristics of single cells,providing a highresolution perspective for precise typing of breast cancer,exploration of the mechanism of the microenvironment,and personalized treatment.Through this technology,researchers can identify specific gene expression profiles of different cell subpopulations,thus providing a new basis for the molecular typing and personalized treatment of breast cancer.This article explains how single-cell sequencing is used to describe the origin of disseminated tumor cells(DTCs),analyse tumor heterogeneity,metastasis,etc.,and review the current literature on the use of scRNA-seq in breast cancer treatment.In the future,cell separation and processing steps in single-cell sequencing will be further improved to ensure the accuracy of the results and broader application in clinical diagnosis and treatment.展开更多
As an important resource in data link,time slots should be strategically allocated to enhance transmission efficiency and resist eavesdropping,especially considering the tremendous increase in the number of nodes and ...As an important resource in data link,time slots should be strategically allocated to enhance transmission efficiency and resist eavesdropping,especially considering the tremendous increase in the number of nodes and diverse communication needs.It is crucial to design control sequences with robust randomness and conflict-freeness to properly address differentiated access control in data link.In this paper,we propose a hierarchical access control scheme based on control sequences to achieve high utilization of time slots and differentiated access control.A theoretical bound of the hierarchical control sequence set is derived to characterize the constraints on the parameters of the sequence set.Moreover,two classes of optimal hierarchical control sequence sets satisfying the theoretical bound are constructed,both of which enable the scheme to achieve maximum utilization of time slots.Compared with the fixed time slot allocation scheme,our scheme reduces the symbol error rate by up to 9%,which indicates a significant improvement in anti-interference and eavesdropping capabilities.展开更多
Orthopedic conditions have emerged as global health concerns,impacting approximately 1.7 billion individuals worldwide.However,the limited understanding of the underlying pathological processes at the cellular and mol...Orthopedic conditions have emerged as global health concerns,impacting approximately 1.7 billion individuals worldwide.However,the limited understanding of the underlying pathological processes at the cellular and molecular level has hindered the development of comprehensive treatment options for these disorders.The advent of single-cell RNA sequencing(scRNA-seq)technology has revolutionized biomedical research by enabling detailed examination of cellular and molecular diversity.Nevertheless,investigating mechanisms at the single-cell level in highly mineralized skeletal tissue poses technical challenges.In this comprehensive review,we present a streamlined approach to obtaining high-quality single cells from skeletal tissue and provide an overview of existing scRNA-seq technologies employed in skeletal studies along with practical bioinformatic analysis pipelines.By utilizing these methodologies,crucial insights into the developmental dynamics,maintenance of homeostasis,and pathological processes involved in spine,joint,bone,muscle,and tendon disorders have been uncovered.Specifically focusing on the joint diseases of degenerative disc disease,osteoarthritis,and rheumatoid arthritis using scRNA-seq has provided novel insights and a more nuanced comprehension.These findings have paved the way for discovering novel therapeutic targets that offer potential benefits to patients suffering from diverse skeletal disorders.展开更多
Tumor tissues contain both tumor and non-tumor cells,which include infiltrated immune cells and stromal cells,collectively called the tumor microenvironment(TME).Single-cell RNA sequencing(sc RNAseq)enables the examin...Tumor tissues contain both tumor and non-tumor cells,which include infiltrated immune cells and stromal cells,collectively called the tumor microenvironment(TME).Single-cell RNA sequencing(sc RNAseq)enables the examination of heterogeneity of tumor cells and TME.In this review,we examined sc RNAseq datasets for multiple cancer types and evaluated the heterogeneity of major cell type composition in different cancer types.We further showed that endothelial cells and fibroblasts/myofibroblasts in different cancer types can be classified into common subtypes,and the subtype composition is clearly associated with cancer characteristic and therapy response.展开更多
Gene sequencing is a great way to interpret life, and high-throughput sequencing technology is a revolutionary technological innovation in gene sequencing researches. This technology is characterized by low cost and h...Gene sequencing is a great way to interpret life, and high-throughput sequencing technology is a revolutionary technological innovation in gene sequencing researches. This technology is characterized by low cost and high-throughput data. Currently, high-throughput sequencing technology has been widely applied in multi-level researches on genomics, transcriptomics and epigenomics. And it has fundamentally changed the way we approach problems in basic and translational researches and created many new possibilities. This paper presented a general description of high-throughput sequencing technology and a comprehensive review of its application with plain, concisely and precisely. In order to help researchers finish their work faster and better, promote science amateurs and understand it easier and better.展开更多
Background Breed identification is useful in a variety of biological contexts.Breed identification usually involves two stages,i.e.,detection of breed-informative SNPs and breed assignment.For both stages,there are se...Background Breed identification is useful in a variety of biological contexts.Breed identification usually involves two stages,i.e.,detection of breed-informative SNPs and breed assignment.For both stages,there are several methods proposed.However,what is the optimal combination of these methods remain unclear.In this study,using the whole genome sequence data available for 13 cattle breeds from Run 8 of the 1,000 Bull Genomes Project,we compared the combinations of three methods(Delta,FST,and In)for breed-informative SNP detection and five machine learning methods(KNN,SVM,RF,NB,and ANN)for breed assignment with respect to different reference population sizes and difference numbers of most breed-informative SNPs.In addition,we evaluated the accuracy of breed identification using SNP chip data of different densities.Results We found that all combinations performed quite well with identification accuracies over 95%in all scenarios.However,there was no combination which performed the best and robust across all scenarios.We proposed to inte-grate the three breed-informative detection methods,named DFI,and integrate the three machine learning methods,KNN,SVM,and RF,named KSR.We found that the combination of these two integrated methods outperformed the other combinations with accuracies over 99%in most cases and was very robust in all scenarios.The accuracies from using SNP chip data were only slightly lower than that from using sequence data in most cases.Conclusions The current study showed that the combination of DFI and KSR was the optimal strategy.Using sequence data resulted in higher accuracies than using chip data in most cases.However,the differences were gener-ally small.In view of the cost of genotyping,using chip data is also a good option for breed identification.展开更多
The advent of single-cell RNA sequencing(scRNA-seq)has provided insight into the tumour immune microenvironment(TIME).This review focuses on the application of scRNA-seq in investigation of the TIME.Over time,scRNA-se...The advent of single-cell RNA sequencing(scRNA-seq)has provided insight into the tumour immune microenvironment(TIME).This review focuses on the application of scRNA-seq in investigation of the TIME.Over time,scRNA-seq methods have evolved,and components of the TIME have been deciphered with high resolution.In this review,we first introduced the principle of scRNA-seq and compared different sequencing approaches.Novel cell types in the TIME,a continuous transitional state,and mutual intercommunication among TIME components present potential targets for prognosis prediction and treatment in cancer.Thus,we concluded novel cell clusters of cancerassociated fibroblasts(CAFs),T cells,tumour-associated macrophages(TAMs)and dendritic cells(DCs)discovered after the application of scRNA-seq in TIME.We also proposed the development of TAMs and exhausted T cells,as well as the possible targets to interrupt the process.In addition,the therapeutic interventions based on cellular interactions in TIME were also summarized.For decades,quantification of the TIME components has been adopted in clinical practice to predict patient survival and response to therapy and is expected to play an important role in the precise treatment of cancer.Summarizing the current findings,we believe that advances in technology and wide application of single-cell analysis can lead to the discovery of novel perspectives on cancer therapy,which can subsequently be implemented in the clinic.Finally,we propose some future directions in the field of TIME studies that can be aided by scRNA-seq technology.展开更多
Single-step genomic best linear unbiased prediction(ss GBLUP) is now intensively investigated and widely used in livestock breeding due to its beneficial feature of combining information from both genotyped and ungeno...Single-step genomic best linear unbiased prediction(ss GBLUP) is now intensively investigated and widely used in livestock breeding due to its beneficial feature of combining information from both genotyped and ungenotyped individuals in the single model. With the increasing accessibility of whole-genome sequence(WGS) data at the population level, more attention is being paid to the usage of WGS data in ss GBLUP. The predictive ability of ss GBLUP using WGS data might be improved by incorporating biological knowledge from public databases. Thus, we extended ss GBLUP, incorporated genomic annotation information into the model, and evaluated them using a yellow-feathered chicken population as the examples. The chicken population consisted of 1 338 birds with 23 traits, where imputed WGS data including 5 127 612 single nucleotide polymorphisms(SNPs) are available for 895 birds. Considering different combinations of annotation information and models, original ss GBLUP, haplotype-based ss GHBLUP, and four extended ss GBLUP incorporating genomic annotation models were evaluated. Based on the genomic annotation(GRCg6a) of chickens, 3 155 524 and 94 837 SNPs were mapped to genic and exonic regions, respectively. Extended ss GBLUP using genic/exonic SNPs outperformed other models with respect to predictive ability in 15 out of 23 traits, and their advantages ranged from 2.5 to 6.1% compared with original ss GBLUP. In addition, to further enhance the performance of genomic prediction with imputed WGS data, we investigated the genotyping strategies of reference population on ss GBLUP in the chicken population. Comparing two strategies of individual selection for genotyping in the reference population, the strategy of evenly selection by family(SBF) performed slightly better than random selection in most situations. Overall, we extended genomic prediction models that can comprehensively utilize WGS data and genomic annotation information in the framework of ss GBLUP, and validated the idea that properly handling the genomic annotation information and WGS data increased the predictive ability of ss GBLUP. Moreover, while using WGS data, the genotyping strategy of maximizing the expected genetic relationship between the reference and candidate population could further improve the predictive ability of ss GBLUP. The results from this study shed light on the comprehensive usage of genomic annotation information in WGS-based single-step genomic prediction.展开更多
Single-cell RNA sequencing(scRNA-seq)has allowed for the profiling of host and virus transcripts and host-virus interactions at single-cell resolution.This review summarizes the existing scRNA-seq technologies togethe...Single-cell RNA sequencing(scRNA-seq)has allowed for the profiling of host and virus transcripts and host-virus interactions at single-cell resolution.This review summarizes the existing scRNA-seq technologies together with their strengths and weaknesses.The applications of scRNA-seq in various virological studies are discussed in depth,which broaden the understanding of the immune atlas,host-virus interactions,and immune repertoire.scRNA-seq can be widely used for virology in the near future to better understand the pathogenic mechanisms and discover more effective therapeutic strategies.展开更多
[Objective]The research aimed to study the influence of automatic station data on the sequence continuity of historical meteorological data.[Method]Based on the temperature data which were measured by the automatic me...[Objective]The research aimed to study the influence of automatic station data on the sequence continuity of historical meteorological data.[Method]Based on the temperature data which were measured by the automatic meteorological station and the corresponding artificial observation data during January-December in 2001,the monthly average,maximum and minimum temperatures in the automatic station were compared with the corresponding artificial observation temperature data in the parallel observation period by using the contrast difference and the standard deviation of difference value.The difference between the automatic station and the artificial data,the variation characteristics were understood.Meanwhile,the significance test and analysis of annual average value were carried out by the data sequence during 1990-2009.The influence of automatic station replacing the artificial observation on the sequence continuity of historical temperature data was discussed.[Result]Although the two temperature data in the parallel observation period had the certain difference,the difference was in the permitted range of automatic station difference value on average.The difference of individual month surpassed the permitted range of automatic station difference value.The significance test showed that the annual average temperature and the annual average minimum temperature which were observed in the automatic station had the difference with the historical data.It had the certain influence on the annual temperature sequence,but the difference wasn’t significant as a whole.When the automatic observation combined with the artificial observation to use,the sequence needed carry out the homogeneous test and correction.[Conclusion]The research played the important role on guaranteeing the monorail running of automatic station,optimizing the meteorological surface observation system,improving the climate sequence continuity of meteorological element and the reliability of climate statistics.展开更多
Objective:To surveill emerging variants by nanopore technology-based genome sequencing in different COVID-19 waves in Sri Lanka and to examine the association with the sample characteristics,and vaccination status.Met...Objective:To surveill emerging variants by nanopore technology-based genome sequencing in different COVID-19 waves in Sri Lanka and to examine the association with the sample characteristics,and vaccination status.Methods:The study analyzed 207 RNA positive swab samples received to sequence laboratory during different waves.The N gene cut-off threshold of less than 30 was considered as the major inclusion criteria.Viral RNA was extracted,and elutes were subjected to nanopore sequencing.All the sequencing data were uploaded in the publicly accessible database,GISAID.Results:The Omicron,Delta and Alpha variants accounted for 58%,22%and 4%of the variants throughout the period.Less than 1%were Kappa variant and 16%of the study samples remained unassigned.Omicron variant was circulated among all age groups and in all the provinces.Ct value and variants assigned percentage was 100%in Ct values of 10-15 while only 45%assigned Ct value over 25.Conclusions:The present study examined the emergence,prevalence,and distribution of SARS-CoV-2 variants locally and has shown that nanopore technology-based genome sequencing enables whole genome sequencing in a low resource setting country.展开更多
This Paper presents a data fusion method with distributed sequence detection for on hypothasis testingtheory including the data fusion algorithm of sequence detection based on least error probability rule, the decisio...This Paper presents a data fusion method with distributed sequence detection for on hypothasis testingtheory including the data fusion algorithm of sequence detection based on least error probability rule, the decision ruleand the calcation formula of the detction times and the simulation result of system performance as well.展开更多
The recognition and contrast of bed sets in parasequence is difficult in terrestrial basin high-resolution sequence stratigraphy. This study puts forward new methods for the boundary identification and contrast of bed...The recognition and contrast of bed sets in parasequence is difficult in terrestrial basin high-resolution sequence stratigraphy. This study puts forward new methods for the boundary identification and contrast of bed sets on the basis of manifold logging data. The formation of calcareous interbeds, shale resistivity differences and the relation of reservoir resistivity to altitude are considered on the basis of log curve morphological characteristics, core observation, cast thin section, X-ray diffraction and scanning electron microscopy. The results show that the thickness of calcareous interbeds is between 0.5 m and 2 m, increasing on weathering crusts and faults. Calcareous interbeds occur at the bottom of a distributary channel and the top of a distributary mouth bar. Lower resistivity shale （4-5 Ω · m） and higher resistivity shale （〉 10Ω·m） reflect differences in sediment fountain or sediment microfacies. Reservoir resistivity increases with altitude. Calcareous interbeds may be a symbol of recognition for the boundary of bed sets and isochronous contrast bed sets, and shale resistivity differences may confirm the stack relation and connectivity of bed sets. Based on this, a high-resolution chronostratigraphic frame- work of Xi-1 segment in Shinan area, Junggar basin is presented, and the connectivity of bed sets and oil-water contact is confirmed. In this chronostratigraphic framework, the growth order, stack mode and space shape of bed sets are qualitatively and quantitatively described.展开更多
Spermatogenic cell heterogeneity is determined by the complex process of spermatogenesis differentiation.However,effectively revealing the regulatory mechanisms underlying mammalian spermatogenic cell development and ...Spermatogenic cell heterogeneity is determined by the complex process of spermatogenesis differentiation.However,effectively revealing the regulatory mechanisms underlying mammalian spermatogenic cell development and differentiation via traditional methods is difficult.Advances in technology have led to the emergence of many single-cell transcriptome sequencing protocols,which have partially addressed these challenges.In this review,we detail the principles of 10x Genomics technology and summarize the methods for downstream analysis of single-cell transcriptome sequencing data.Furthermore,we explore the role of single-cell transcriptome sequencing in revealing the heterogeneity of testicular ecological niche cells,delineating the establishment and disruption of testicular immune homeostasis during human spermatogenesis,investigating abnormal spermatogenesis in humans,and,ultimately,elucidating the molecular evolution of mammalian spermatogenesis.展开更多
Massively parallel sequencing(MPS), alias next-generation sequencing, is making its way from research laboratories into applied sciences and clinics. MPS is a framework of experimental procedures which offer possibili...Massively parallel sequencing(MPS), alias next-generation sequencing, is making its way from research laboratories into applied sciences and clinics. MPS is a framework of experimental procedures which offer possibilities for genome research and genetics which could only be dreamed of until around 2005 when these technologies became available. Sequencing of a transcriptome, exome, even entire genomes is now possible within a time frame and precision that we could only hope for 10 years ago. Linking other experimental procedures with MPS enables researchers to study secondary DNA modifications across the entire genome, and protein binding sites, to name a few applications. How the advancements of sequencing technologies can contribute to transplantation science is subject of this discussion: immediate applications are in graft matching via human leukocyte antigen sequencing, as part of systems biology approaches which shed light on gene expression processes during immune response, as biomarkers of graft rejection, and to explore changes of microbiomes as a result of transplantation. Of considerable importance is the socio-ethical aspect of data ownership, privacy, informed consent, and result report to the study participant. While the technology is advancing rapidly, legislation is lagging behind due to the globalisation of data requisition, banking and sharing.展开更多
miRNAs are non-coding RNAs that play a regulatory role in expression of genes and are associated with diseases. Quantitatively measuring expression levels of miRNAs can help understanding the mechanisms of human disea...miRNAs are non-coding RNAs that play a regulatory role in expression of genes and are associated with diseases. Quantitatively measuring expression levels of miRNAs can help understanding the mechanisms of human diseases and discovering new drug targets. There are three major methods that have been used to measure the expression levels of miRNAs: real-time reverse transcription PCR (qRT-PCR), microarray, and the newly introduced next-generation sequencing (NGS). NGS is not only suitable for profiling of known miRNAs that qRT-PCR and microarray can do too but also able to detect unknown miRNAs that the other two methods are incapable. Profiling of miRNAs by NGS has been progressed rapidly and is a promising field for applications in drug development. This paper will review the technical advancement of NGS for profiling miRNAs, including comparative analyses between different platforms and software packages for analyzing NGS data. Examples and future perspectives of applications of NGS profiling miRNAs in drug development will be discussed.展开更多
An unequal time interval sequence or a sequence with blanks is usually completed with average generation in grey system theory. This paper discovers that there exists obvious errors when using average generation to ge...An unequal time interval sequence or a sequence with blanks is usually completed with average generation in grey system theory. This paper discovers that there exists obvious errors when using average generation to generate internal points of non-consecutive neighbours. The average generation and the preference generation of the sequence are discussed, the concave and convex properties show the status of local sequence and propose a new idea for using the status to build up the criteria of choosing generation coefficient. Compared with the general average method of the one-dimensional data sequence, the two-dimensional data sequence is defined and its average generation is discussed, and the coefficient decision method for the preference generation is presented.展开更多
Genital herpes(GH)is a common sexually transmitted disease,which is primarily caused by herpes simplex virus type 2(HSV-2),and continues to be a global health concern.Although our understanding of the alterations in i...Genital herpes(GH)is a common sexually transmitted disease,which is primarily caused by herpes simplex virus type 2(HSV-2),and continues to be a global health concern.Although our understanding of the alterations in immune cell populations and immunomodulation in GH patients is still limited,it is evident that systemic intrinsic immunity,innate immunity,and adaptive immunity play crucial roles during HSV-2 infection and GH reactivation.To investigate the mechanisms underlying HSV-2 infection and recurrence,single-cell RNA sequencing(scRNA-seq)was performed on immune cells isolated from the peripheral blood of both healthy individuals and patients with recurrent GH.Furthermore,the systemic immune response in patients with recurrent GH showed activation of classical monocytes,CD4þT cells,natural killer cells(NK cells),and plasmacytoid dendritic cells(pDCs),especially of genes associated with the Toll-like receptor signaling pathway and T cell activation.Circulating immune cells in GH patients show higher expression of genes associated with inflammation and antiviral responses both in the scRNA-Seq data set and in independent quantitative real-time polymerase chain reaction(qRT-PCR)analysis and ELISA experiments.This study demonstrated that localized genital herpes,resulting from HSV reactivation,may influence the functionality of circulating immune cells,suggesting a potential avenue for future research into the role of systemic immunity during HSV infection and recurrence.展开更多
Autoimmune uveitis is one of the most common inflammatory eye diseases leading to blindness globally.Its etiology is primarily associated with autoimmune responses.Patients with this condition often exhibit complex an...Autoimmune uveitis is one of the most common inflammatory eye diseases leading to blindness globally.Its etiology is primarily associated with autoimmune responses.Patients with this condition often exhibit complex and chronic disease courses,with a high propensity for recurrence.Current treatments mainly involve corticosteroids and immunosuppressive agents,which,despite their effectiveness,entail significant side effects that severely impact patients'vision and quality of life.There are still unresolved questions regarding the etiology and immunopathogenesis of autoimmune uveitis,and traditional high-throughput sequencing techniques fall short of adequately elucidating its pathogenic mechanisms at the cellular level.With the continuous advancement of single-cell sequencing technology,an increasing number of studies are leveraging this approach to deeply investigate the pathogenesis of autoimmune uveitis,thereby offering new insights for identifying novel diagnostic and therapeutic targets.This paper reviews the latest applications of single-cell sequencing technology in exploring the pathogenesis of autoimmune uveitis.Through the utilization of this technology,researchers can gain a more comprehensive understanding of cellular-level changes in patients,providing robust support for the search for new therapeutic avenues.These studies offer new directions for the diagnosis and treatment of autoimmune uveitis and provide valuable information for the development of future therapeutic strategies and approaches.展开更多
Online sensing can provide useful information in monitoring applications,for example,machine health monitoring,structural condition monitoring,environmental monitoring,and many more.Missing data is generally a signifi...Online sensing can provide useful information in monitoring applications,for example,machine health monitoring,structural condition monitoring,environmental monitoring,and many more.Missing data is generally a significant issue in the sensory data that is collected online by sensing systems,which may affect the goals of monitoring programs.In this paper,a sequence-to-sequence learning model based on a recurrent neural network(RNN)architecture is presented.In the proposed method,multivariate time series of the monitored parameters is embedded into the neural network through layer-by-layer encoders where the hidden features of the inputs are adaptively extracted.Afterwards,predictions of the missing data are generated by network decoders,which are one-step-ahead predictive data sequences of the monitored parameters.The prediction performance of the proposed model is validated based on a real-world sensory dataset.The experimental results demonstrate the performance of the proposed RNN-encoder-decoder model with its capability in sequence-to-sequence learning for online imputation of sensory data.展开更多
文摘Breast cancer is a malignant tumor originating from breast epithelial tissue.In essence,breast epithelial cells undergo gene mutation under the influence of carcinogenic factors,leading to abnormal cell proliferation and loss of organism regulation,ultimately leading to the formation of tumors with invasive and metastatic capabilities.Carcinogenic factors of breast cancer involve multiple cellular and molecular mechanisms.Among them,disseminated tumor cells(DTCs)are considered important for treating breast cancer.However,traditional bulk sequencing techniques have limitations,such as the inability to distinguish individual cell differences and dilution of information from key cell subpopulations(such as cancer stem cells and rare immune cells).Single-cell sequencing(scRNA-seq)overcomes the heterogeneity of tumors that traditional sequencing cannot capture by analysing the molecular characteristics of single cells,providing a highresolution perspective for precise typing of breast cancer,exploration of the mechanism of the microenvironment,and personalized treatment.Through this technology,researchers can identify specific gene expression profiles of different cell subpopulations,thus providing a new basis for the molecular typing and personalized treatment of breast cancer.This article explains how single-cell sequencing is used to describe the origin of disseminated tumor cells(DTCs),analyse tumor heterogeneity,metastasis,etc.,and review the current literature on the use of scRNA-seq in breast cancer treatment.In the future,cell separation and processing steps in single-cell sequencing will be further improved to ensure the accuracy of the results and broader application in clinical diagnosis and treatment.
基金supported by the National Science Foundation of China(No.62171387)the Science and Technology Program of Sichuan Province(No.2024NSFSC0468)the China Postdoctoral Science Foundation(No.2019M663475).
文摘As an important resource in data link,time slots should be strategically allocated to enhance transmission efficiency and resist eavesdropping,especially considering the tremendous increase in the number of nodes and diverse communication needs.It is crucial to design control sequences with robust randomness and conflict-freeness to properly address differentiated access control in data link.In this paper,we propose a hierarchical access control scheme based on control sequences to achieve high utilization of time slots and differentiated access control.A theoretical bound of the hierarchical control sequence set is derived to characterize the constraints on the parameters of the sequence set.Moreover,two classes of optimal hierarchical control sequence sets satisfying the theoretical bound are constructed,both of which enable the scheme to achieve maximum utilization of time slots.Compared with the fixed time slot allocation scheme,our scheme reduces the symbol error rate by up to 9%,which indicates a significant improvement in anti-interference and eavesdropping capabilities.
基金National Key Research and Development Program of China(2022YFA1103202)National Natural Science Foundation of China(82272507,32270887,and 32200654)+6 种基金Natural Science Foundation of Chongqing(CSTB2023NSCQ-ZDJO008)Postdoctoral Innovative Talent Support Program(BX20220397)Independent Research Project of State Key Laboratory of Trauma and Chemical Poisoning(SFLKF202201)Project for Enhancing Innovation of Army Medical University(2023X1839)Talent Innovation Training Program at the Army Medical Center(ZXZYTSYS09)General Hospital of Western Theater Command Research Project(2021-XZYG-B10)University Grants Committee,Research Grants Council of Hong Kong,China(14113723,N_CUHK472/22,C7030-18G,T13-402/17-N,and AoE/M-402/20)。
文摘Orthopedic conditions have emerged as global health concerns,impacting approximately 1.7 billion individuals worldwide.However,the limited understanding of the underlying pathological processes at the cellular and molecular level has hindered the development of comprehensive treatment options for these disorders.The advent of single-cell RNA sequencing(scRNA-seq)technology has revolutionized biomedical research by enabling detailed examination of cellular and molecular diversity.Nevertheless,investigating mechanisms at the single-cell level in highly mineralized skeletal tissue poses technical challenges.In this comprehensive review,we present a streamlined approach to obtaining high-quality single cells from skeletal tissue and provide an overview of existing scRNA-seq technologies employed in skeletal studies along with practical bioinformatic analysis pipelines.By utilizing these methodologies,crucial insights into the developmental dynamics,maintenance of homeostasis,and pathological processes involved in spine,joint,bone,muscle,and tendon disorders have been uncovered.Specifically focusing on the joint diseases of degenerative disc disease,osteoarthritis,and rheumatoid arthritis using scRNA-seq has provided novel insights and a more nuanced comprehension.These findings have paved the way for discovering novel therapeutic targets that offer potential benefits to patients suffering from diverse skeletal disorders.
基金partially supported by NIH grants(Grant Nos.R01CA249175 and U19AI118610)。
文摘Tumor tissues contain both tumor and non-tumor cells,which include infiltrated immune cells and stromal cells,collectively called the tumor microenvironment(TME).Single-cell RNA sequencing(sc RNAseq)enables the examination of heterogeneity of tumor cells and TME.In this review,we examined sc RNAseq datasets for multiple cancer types and evaluated the heterogeneity of major cell type composition in different cancer types.We further showed that endothelial cells and fibroblasts/myofibroblasts in different cancer types can be classified into common subtypes,and the subtype composition is clearly associated with cancer characteristic and therapy response.
基金Supported by the National Natural Science Foundations of China(3127218631301791)
文摘Gene sequencing is a great way to interpret life, and high-throughput sequencing technology is a revolutionary technological innovation in gene sequencing researches. This technology is characterized by low cost and high-throughput data. Currently, high-throughput sequencing technology has been widely applied in multi-level researches on genomics, transcriptomics and epigenomics. And it has fundamentally changed the way we approach problems in basic and translational researches and created many new possibilities. This paper presented a general description of high-throughput sequencing technology and a comprehensive review of its application with plain, concisely and precisely. In order to help researchers finish their work faster and better, promote science amateurs and understand it easier and better.
基金funded by National Key Research and Development Program of China(2021YFD1200404)the Yangzhou University Interdisciplinary Research Foundation for Animal Science Discipline of Targeted Support(yzuxk202016)the Project of Genetic Improvement for Agricultural Species(Dairy Cattle)of Shandong Province(2019LZGC011).
文摘Background Breed identification is useful in a variety of biological contexts.Breed identification usually involves two stages,i.e.,detection of breed-informative SNPs and breed assignment.For both stages,there are several methods proposed.However,what is the optimal combination of these methods remain unclear.In this study,using the whole genome sequence data available for 13 cattle breeds from Run 8 of the 1,000 Bull Genomes Project,we compared the combinations of three methods(Delta,FST,and In)for breed-informative SNP detection and five machine learning methods(KNN,SVM,RF,NB,and ANN)for breed assignment with respect to different reference population sizes and difference numbers of most breed-informative SNPs.In addition,we evaluated the accuracy of breed identification using SNP chip data of different densities.Results We found that all combinations performed quite well with identification accuracies over 95%in all scenarios.However,there was no combination which performed the best and robust across all scenarios.We proposed to inte-grate the three breed-informative detection methods,named DFI,and integrate the three machine learning methods,KNN,SVM,and RF,named KSR.We found that the combination of these two integrated methods outperformed the other combinations with accuracies over 99%in most cases and was very robust in all scenarios.The accuracies from using SNP chip data were only slightly lower than that from using sequence data in most cases.Conclusions The current study showed that the combination of DFI and KSR was the optimal strategy.Using sequence data resulted in higher accuracies than using chip data in most cases.However,the differences were gener-ally small.In view of the cost of genotyping,using chip data is also a good option for breed identification.
基金supported by the National Key Research Development Program of China(2021YFA1301203)the National Natural Science Foundation of China(82103031,82103918,81973408)+6 种基金the Clinical Research Incubation Project,West China Hospital,Sichuan University(22HXFH019)the China Postdoctoral Science Foundation(2019 M653416)the International Cooperation Project of Chengdu Municipal Science and Technology Bureau(2020-GH02-00017-HZ)the“1.3.5 Project for Disciplines of Excellence,West China Hospital,Sichuan University”(ZYJC18035,ZYJC18025,ZYYC20003,ZYJC18003)the GIST Research Institute(GRI)IIBR grants funded by the GISTthe National Research Foundation of Korea funded by the Korean government(MSIP)(2019R1C1C1005403,2019R1A4A1028802 and2021M3H9A2097520)the Post-Doctor Research Project,West China Hospital,Sichuan University(2021HXBH054)。
文摘The advent of single-cell RNA sequencing(scRNA-seq)has provided insight into the tumour immune microenvironment(TIME).This review focuses on the application of scRNA-seq in investigation of the TIME.Over time,scRNA-seq methods have evolved,and components of the TIME have been deciphered with high resolution.In this review,we first introduced the principle of scRNA-seq and compared different sequencing approaches.Novel cell types in the TIME,a continuous transitional state,and mutual intercommunication among TIME components present potential targets for prognosis prediction and treatment in cancer.Thus,we concluded novel cell clusters of cancerassociated fibroblasts(CAFs),T cells,tumour-associated macrophages(TAMs)and dendritic cells(DCs)discovered after the application of scRNA-seq in TIME.We also proposed the development of TAMs and exhausted T cells,as well as the possible targets to interrupt the process.In addition,the therapeutic interventions based on cellular interactions in TIME were also summarized.For decades,quantification of the TIME components has been adopted in clinical practice to predict patient survival and response to therapy and is expected to play an important role in the precise treatment of cancer.Summarizing the current findings,we believe that advances in technology and wide application of single-cell analysis can lead to the discovery of novel perspectives on cancer therapy,which can subsequently be implemented in the clinic.Finally,we propose some future directions in the field of TIME studies that can be aided by scRNA-seq technology.
基金supported by the National Natural Science Foundation of China(32022078)the Local Innovative and Research Teams Project of Guangdong Province,China(2019BT02N630)the support from the National Supercomputer Center in Guangzhou,China。
文摘Single-step genomic best linear unbiased prediction(ss GBLUP) is now intensively investigated and widely used in livestock breeding due to its beneficial feature of combining information from both genotyped and ungenotyped individuals in the single model. With the increasing accessibility of whole-genome sequence(WGS) data at the population level, more attention is being paid to the usage of WGS data in ss GBLUP. The predictive ability of ss GBLUP using WGS data might be improved by incorporating biological knowledge from public databases. Thus, we extended ss GBLUP, incorporated genomic annotation information into the model, and evaluated them using a yellow-feathered chicken population as the examples. The chicken population consisted of 1 338 birds with 23 traits, where imputed WGS data including 5 127 612 single nucleotide polymorphisms(SNPs) are available for 895 birds. Considering different combinations of annotation information and models, original ss GBLUP, haplotype-based ss GHBLUP, and four extended ss GBLUP incorporating genomic annotation models were evaluated. Based on the genomic annotation(GRCg6a) of chickens, 3 155 524 and 94 837 SNPs were mapped to genic and exonic regions, respectively. Extended ss GBLUP using genic/exonic SNPs outperformed other models with respect to predictive ability in 15 out of 23 traits, and their advantages ranged from 2.5 to 6.1% compared with original ss GBLUP. In addition, to further enhance the performance of genomic prediction with imputed WGS data, we investigated the genotyping strategies of reference population on ss GBLUP in the chicken population. Comparing two strategies of individual selection for genotyping in the reference population, the strategy of evenly selection by family(SBF) performed slightly better than random selection in most situations. Overall, we extended genomic prediction models that can comprehensively utilize WGS data and genomic annotation information in the framework of ss GBLUP, and validated the idea that properly handling the genomic annotation information and WGS data increased the predictive ability of ss GBLUP. Moreover, while using WGS data, the genotyping strategy of maximizing the expected genetic relationship between the reference and candidate population could further improve the predictive ability of ss GBLUP. The results from this study shed light on the comprehensive usage of genomic annotation information in WGS-based single-step genomic prediction.
基金supported by the National Key Research and Devel-opment Program of China(2021YFC2300202)the National Natural Science Foundation of China(U1902210,81871641,81972979,82172266,82241071,and 81902048)+1 种基金the Support Project of High-level Teachers in Beijing Municipal Universities in the Period of 13th Five-year Plan(IDHT20190510)the Beijing Key Laboratory of Emerging In-fectious Diseases(DTKF202103).
文摘Single-cell RNA sequencing(scRNA-seq)has allowed for the profiling of host and virus transcripts and host-virus interactions at single-cell resolution.This review summarizes the existing scRNA-seq technologies together with their strengths and weaknesses.The applications of scRNA-seq in various virological studies are discussed in depth,which broaden the understanding of the immune atlas,host-virus interactions,and immune repertoire.scRNA-seq can be widely used for virology in the near future to better understand the pathogenic mechanisms and discover more effective therapeutic strategies.
文摘[Objective]The research aimed to study the influence of automatic station data on the sequence continuity of historical meteorological data.[Method]Based on the temperature data which were measured by the automatic meteorological station and the corresponding artificial observation data during January-December in 2001,the monthly average,maximum and minimum temperatures in the automatic station were compared with the corresponding artificial observation temperature data in the parallel observation period by using the contrast difference and the standard deviation of difference value.The difference between the automatic station and the artificial data,the variation characteristics were understood.Meanwhile,the significance test and analysis of annual average value were carried out by the data sequence during 1990-2009.The influence of automatic station replacing the artificial observation on the sequence continuity of historical temperature data was discussed.[Result]Although the two temperature data in the parallel observation period had the certain difference,the difference was in the permitted range of automatic station difference value on average.The difference of individual month surpassed the permitted range of automatic station difference value.The significance test showed that the annual average temperature and the annual average minimum temperature which were observed in the automatic station had the difference with the historical data.It had the certain influence on the annual temperature sequence,but the difference wasn’t significant as a whole.When the automatic observation combined with the artificial observation to use,the sequence needed carry out the homogeneous test and correction.[Conclusion]The research played the important role on guaranteeing the monorail running of automatic station,optimizing the meteorological surface observation system,improving the climate sequence continuity of meteorological element and the reliability of climate statistics.
文摘Objective:To surveill emerging variants by nanopore technology-based genome sequencing in different COVID-19 waves in Sri Lanka and to examine the association with the sample characteristics,and vaccination status.Methods:The study analyzed 207 RNA positive swab samples received to sequence laboratory during different waves.The N gene cut-off threshold of less than 30 was considered as the major inclusion criteria.Viral RNA was extracted,and elutes were subjected to nanopore sequencing.All the sequencing data were uploaded in the publicly accessible database,GISAID.Results:The Omicron,Delta and Alpha variants accounted for 58%,22%and 4%of the variants throughout the period.Less than 1%were Kappa variant and 16%of the study samples remained unassigned.Omicron variant was circulated among all age groups and in all the provinces.Ct value and variants assigned percentage was 100%in Ct values of 10-15 while only 45%assigned Ct value over 25.Conclusions:The present study examined the emergence,prevalence,and distribution of SARS-CoV-2 variants locally and has shown that nanopore technology-based genome sequencing enables whole genome sequencing in a low resource setting country.
文摘This Paper presents a data fusion method with distributed sequence detection for on hypothasis testingtheory including the data fusion algorithm of sequence detection based on least error probability rule, the decision ruleand the calcation formula of the detction times and the simulation result of system performance as well.
基金This paper is supported by the Main Project of the National Tenth Five-Year Plan .
文摘The recognition and contrast of bed sets in parasequence is difficult in terrestrial basin high-resolution sequence stratigraphy. This study puts forward new methods for the boundary identification and contrast of bed sets on the basis of manifold logging data. The formation of calcareous interbeds, shale resistivity differences and the relation of reservoir resistivity to altitude are considered on the basis of log curve morphological characteristics, core observation, cast thin section, X-ray diffraction and scanning electron microscopy. The results show that the thickness of calcareous interbeds is between 0.5 m and 2 m, increasing on weathering crusts and faults. Calcareous interbeds occur at the bottom of a distributary channel and the top of a distributary mouth bar. Lower resistivity shale （4-5 Ω · m） and higher resistivity shale （〉 10Ω·m） reflect differences in sediment fountain or sediment microfacies. Reservoir resistivity increases with altitude. Calcareous interbeds may be a symbol of recognition for the boundary of bed sets and isochronous contrast bed sets, and shale resistivity differences may confirm the stack relation and connectivity of bed sets. Based on this, a high-resolution chronostratigraphic frame- work of Xi-1 segment in Shinan area, Junggar basin is presented, and the connectivity of bed sets and oil-water contact is confirmed. In this chronostratigraphic framework, the growth order, stack mode and space shape of bed sets are qualitatively and quantitatively described.
基金supported by National Key Research and Development Program of China(2022YFD1302201,2023YFF1000904)the National Natural Science Foundation of China(32072806,32372970)+2 种基金Key Technologies Demonstration of Animal Husbandry in Shaanxi Province(20221086,20230978)Inner Mongolia Autonomous Region Competition Leaders(2022JBGS0025)Xinjian Ugur Autonouous Region Scientific Research and Innovation Platform Construction Project“State Key Laboratory of Genetic Improvement and Germplasm”。
文摘Spermatogenic cell heterogeneity is determined by the complex process of spermatogenesis differentiation.However,effectively revealing the regulatory mechanisms underlying mammalian spermatogenic cell development and differentiation via traditional methods is difficult.Advances in technology have led to the emergence of many single-cell transcriptome sequencing protocols,which have partially addressed these challenges.In this review,we detail the principles of 10x Genomics technology and summarize the methods for downstream analysis of single-cell transcriptome sequencing data.Furthermore,we explore the role of single-cell transcriptome sequencing in revealing the heterogeneity of testicular ecological niche cells,delineating the establishment and disruption of testicular immune homeostasis during human spermatogenesis,investigating abnormal spermatogenesis in humans,and,ultimately,elucidating the molecular evolution of mammalian spermatogenesis.
文摘Massively parallel sequencing(MPS), alias next-generation sequencing, is making its way from research laboratories into applied sciences and clinics. MPS is a framework of experimental procedures which offer possibilities for genome research and genetics which could only be dreamed of until around 2005 when these technologies became available. Sequencing of a transcriptome, exome, even entire genomes is now possible within a time frame and precision that we could only hope for 10 years ago. Linking other experimental procedures with MPS enables researchers to study secondary DNA modifications across the entire genome, and protein binding sites, to name a few applications. How the advancements of sequencing technologies can contribute to transplantation science is subject of this discussion: immediate applications are in graft matching via human leukocyte antigen sequencing, as part of systems biology approaches which shed light on gene expression processes during immune response, as biomarkers of graft rejection, and to explore changes of microbiomes as a result of transplantation. Of considerable importance is the socio-ethical aspect of data ownership, privacy, informed consent, and result report to the study participant. While the technology is advancing rapidly, legislation is lagging behind due to the globalisation of data requisition, banking and sharing.
文摘miRNAs are non-coding RNAs that play a regulatory role in expression of genes and are associated with diseases. Quantitatively measuring expression levels of miRNAs can help understanding the mechanisms of human diseases and discovering new drug targets. There are three major methods that have been used to measure the expression levels of miRNAs: real-time reverse transcription PCR (qRT-PCR), microarray, and the newly introduced next-generation sequencing (NGS). NGS is not only suitable for profiling of known miRNAs that qRT-PCR and microarray can do too but also able to detect unknown miRNAs that the other two methods are incapable. Profiling of miRNAs by NGS has been progressed rapidly and is a promising field for applications in drug development. This paper will review the technical advancement of NGS for profiling miRNAs, including comparative analyses between different platforms and software packages for analyzing NGS data. Examples and future perspectives of applications of NGS profiling miRNAs in drug development will be discussed.
文摘An unequal time interval sequence or a sequence with blanks is usually completed with average generation in grey system theory. This paper discovers that there exists obvious errors when using average generation to generate internal points of non-consecutive neighbours. The average generation and the preference generation of the sequence are discussed, the concave and convex properties show the status of local sequence and propose a new idea for using the status to build up the criteria of choosing generation coefficient. Compared with the general average method of the one-dimensional data sequence, the two-dimensional data sequence is defined and its average generation is discussed, and the coefficient decision method for the preference generation is presented.
基金supported by grants from the National Natural Science Foundation of China[grant number 82471846,82103740 and 82103743]Medical Science and Technology Project of Zhejiang Province[grant number 2022RC198].
文摘Genital herpes(GH)is a common sexually transmitted disease,which is primarily caused by herpes simplex virus type 2(HSV-2),and continues to be a global health concern.Although our understanding of the alterations in immune cell populations and immunomodulation in GH patients is still limited,it is evident that systemic intrinsic immunity,innate immunity,and adaptive immunity play crucial roles during HSV-2 infection and GH reactivation.To investigate the mechanisms underlying HSV-2 infection and recurrence,single-cell RNA sequencing(scRNA-seq)was performed on immune cells isolated from the peripheral blood of both healthy individuals and patients with recurrent GH.Furthermore,the systemic immune response in patients with recurrent GH showed activation of classical monocytes,CD4þT cells,natural killer cells(NK cells),and plasmacytoid dendritic cells(pDCs),especially of genes associated with the Toll-like receptor signaling pathway and T cell activation.Circulating immune cells in GH patients show higher expression of genes associated with inflammation and antiviral responses both in the scRNA-Seq data set and in independent quantitative real-time polymerase chain reaction(qRT-PCR)analysis and ELISA experiments.This study demonstrated that localized genital herpes,resulting from HSV reactivation,may influence the functionality of circulating immune cells,suggesting a potential avenue for future research into the role of systemic immunity during HSV infection and recurrence.
基金supported by the CAMS Innovation Fund for Medical Sciences(2019-I2M-5-005)the State Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University.
文摘Autoimmune uveitis is one of the most common inflammatory eye diseases leading to blindness globally.Its etiology is primarily associated with autoimmune responses.Patients with this condition often exhibit complex and chronic disease courses,with a high propensity for recurrence.Current treatments mainly involve corticosteroids and immunosuppressive agents,which,despite their effectiveness,entail significant side effects that severely impact patients'vision and quality of life.There are still unresolved questions regarding the etiology and immunopathogenesis of autoimmune uveitis,and traditional high-throughput sequencing techniques fall short of adequately elucidating its pathogenic mechanisms at the cellular level.With the continuous advancement of single-cell sequencing technology,an increasing number of studies are leveraging this approach to deeply investigate the pathogenesis of autoimmune uveitis,thereby offering new insights for identifying novel diagnostic and therapeutic targets.This paper reviews the latest applications of single-cell sequencing technology in exploring the pathogenesis of autoimmune uveitis.Through the utilization of this technology,researchers can gain a more comprehensive understanding of cellular-level changes in patients,providing robust support for the search for new therapeutic avenues.These studies offer new directions for the diagnosis and treatment of autoimmune uveitis and provide valuable information for the development of future therapeutic strategies and approaches.
文摘Online sensing can provide useful information in monitoring applications,for example,machine health monitoring,structural condition monitoring,environmental monitoring,and many more.Missing data is generally a significant issue in the sensory data that is collected online by sensing systems,which may affect the goals of monitoring programs.In this paper,a sequence-to-sequence learning model based on a recurrent neural network(RNN)architecture is presented.In the proposed method,multivariate time series of the monitored parameters is embedded into the neural network through layer-by-layer encoders where the hidden features of the inputs are adaptively extracted.Afterwards,predictions of the missing data are generated by network decoders,which are one-step-ahead predictive data sequences of the monitored parameters.The prediction performance of the proposed model is validated based on a real-world sensory dataset.The experimental results demonstrate the performance of the proposed RNN-encoder-decoder model with its capability in sequence-to-sequence learning for online imputation of sensory data.
