[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
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
RNA-sequencing(RNA-seq),based on next-generation sequencing technologies,has rapidly become a standard and popular technology for transcriptome analysis.However,serious challenges still exist in analyzing and interpre...RNA-sequencing(RNA-seq),based on next-generation sequencing technologies,has rapidly become a standard and popular technology for transcriptome analysis.However,serious challenges still exist in analyzing and interpreting the RNA-seq data.With the development of high-throughput sequencing technology,the sequencing depth of RNA-seq data increases explosively.The intricate biological process of transcriptome is more complicated and diversified beyond our imagination.Moreover,most of the remaining organisms still have no available reference genome or have only incomplete genome annotations.Therefore,a large number of bioinformatics methods for various transcriptomics studies are proposed to effectively settle these challenges.This review comprehensively summarizes the various studies in RNA-seq data analysis and their corresponding analysis methods,including genome annotation,quality control and pre-processing of reads,read alignment,transcriptome assembly,gene and isoform expression quantification,differential expression analysis,data visualization and other analyses.展开更多
A fundamental goal in cellular signaling is to understand allosteric communication, the process by which sig-nals originating at one site in a protein propagate reliably to affect distant functional sites. The general...A fundamental goal in cellular signaling is to understand allosteric communication, the process by which sig-nals originating at one site in a protein propagate reliably to affect distant functional sites. The general principles of protein structure that underlie this process remain unknown. Statistical coupling analysis （SCA） is a statistical technique that uses evolutionary data of a protein family to measure correlation between distant functional sites and suggests allosteric communication. In proteins, very distant and small interactions between collections of amino acids provide the communication which can be important for signaling process. In this paper, we present the SCA of protein alignment of the esterase family （pfam ID： PF00756） containing the sequence of antigen 85C secreted by Mycobacterium tuberculosis to identify a subset of interacting residues. Clustering analysis of the pairwise correlation highlighted seven important residue positions in the esterase family alignments. These resi-dues were then mapped on the crystal structure of antigen 85C （PDB ID： 1DQZ）. The mapping revealed corre-lation between 3 distant residues （Asp38, Leu123 and Met125） and suggests allosteric communication between them. This information can be used for a new drug against this fatal disease.展开更多
With continuous developments in biotechnology and information technology,we are entering the era of biological sequence big data.Extracting valuable insights from large-scale data to decipher life activities presents ...With continuous developments in biotechnology and information technology,we are entering the era of biological sequence big data.Extracting valuable insights from large-scale data to decipher life activities presents a major challenge.Artificial intelligence,particularly big data analysis and natural language processing technologies,has emerged as a crucial tool in biological sequence analysis.These technologies facilitate pattern detection,offering new perspectives on complex biological processes.Notably,AlphaFold and ESM models have achieved signifi-cant strides in protein structure prediction and functional annotation.These breakthroughs not only accelerate fundamental biological research but also provide innovative tools and strategies for disease diagnosis and drug discovery.In this perspective,we discuss the advancements in biological sequence analysis and focus on their extensive medical applications.Additionally,we highlight relevant challenges and propose further directions,emphasizing the need for ongoing innovation in sequence analysis to fully realize its potential in biomedical research.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
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
Background:Evidence has suggested that cytokine storms may be associated with T cell exhaustion(TEX)in COVID-19.However,the interaction mechanism between cytokine storms and TEX remains unclear.Methods:With the aim of...Background:Evidence has suggested that cytokine storms may be associated with T cell exhaustion(TEX)in COVID-19.However,the interaction mechanism between cytokine storms and TEX remains unclear.Methods:With the aim of dissecting the molecular relationship of cytokine storms and TEX through single-cell RNA sequencing data analysis,we identified 14 cell types from bronchoalveolar lavage fluid of COVID-19 patients and healthy people.We observed a novel subset of severely exhausted CD8 T cells(Exh T_CD8)that co-expressed multiple inhibitory receptors,and two macrophage subclasses that were the main source of cytokine storms in bronchoalveolar.Results:Correlation analysis between cytokine storm level and TEX level suggested that cytokine storms likely promoted TEX in severe COVID-19.Cell–cell communication analysis indicated that cytokines(e.g.CXCL10,CXCL11,CXCL2,CCL2,and CCL3)released by macrophages acted as ligands and significantly interacted with inhibitory receptors(e.g.CXCR3,DPP4,CCR1,CCR2,and CCR5)expressed by Exh T_CD8.These interactions formed the cytokine–receptor axes,which were also verified to be significantly correlated with cytokine storms and TEX in lung squamous cell carcinoma.Conclusions:Cytokine storms may promote TEX through cytokine-receptor axes and be associated with poor prognosis in COVID19.Blocking cytokine-receptor axes may reverse TEX.Our finding provides novel insights into TEX in COVID-19 and new clues for cytokine-targeted immunotherapy development.展开更多
Open earthen pond-based larviculture is the main method for rearing Chinese mitten crab(Eriocheir sinensis)larvae in China.Bacterioplankton play a vital role in aquaculture ecosystems,but their community succession th...Open earthen pond-based larviculture is the main method for rearing Chinese mitten crab(Eriocheir sinensis)larvae in China.Bacterioplankton play a vital role in aquaculture ecosystems,but their community succession throughout the larval nursery stages of E.sinensis in such systems is still poorly understood.Using 16S rRNA gene amplicon sequencing,this study characterized the dynamics of bacterioplankton communities during a complete E.sinensis larval rearing cycle in open earthen ponds.Results presented a distinct,unidirectional succession in bacterioplankton composition,characterized by a decrease in Alphaproteobacteria and an increase in Actinobacteria.Live feeds(Brachionus plicatilis and Artemia salina)significantly affected bacterioplankton communities directly through their biological activities and indirectly by modifying the structure of phytoplankton composition.In addition to live feeds,water temperature and dissolved oxygen were key environmental factors affecting the structure of bacterioplankton communities.Biotic interactions,specifically with phytoplankton and copepods,were key drivers of bacterioplankton succession.Routine feeding practices during larval cultivation decreased bacterioplankton network complexity and strengthened community stability.Keystone taxa,specifically OTU783(Rhodobacteraceae)and OTU1235(Microbacteriaceae),played an essential role in maintaining the community stability through recruiting more rare species during the later stages despite their low abundances.These outcomes advance our understanding of the mechanisms central to bacterioplankton community succession and stability in E.sinensis larviculture systems,offering critical insights for developing sustainable aquaculture management strategies.展开更多
With the rapid development of genetic analysis techniques and crop population size,phenotyping has become the bottleneck restricting crop breeding.Breaking through this bottleneck will require phenomics,defined as the...With the rapid development of genetic analysis techniques and crop population size,phenotyping has become the bottleneck restricting crop breeding.Breaking through this bottleneck will require phenomics,defined as the accurate,high-throughput acquisition and analysis of multi-dimensional phenotypes during crop growth at organism-wide levels,ranging from cells to organs,individual plants,plots,and fields.Here we offer an overview of crop phenomics research from technological and platform viewpoints at various scales,including microscopic,ground-based,and aerial phenotyping and phenotypic data analysis.We describe recent applications of high-throughput phenotyping platforms for abiotic/biotic stress and yield assessment.Finally,we discuss current challenges and offer perspectives on future phenomics research.展开更多
Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have rev...Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.展开更多
Results from optical CCD photometric observations of 13 pre-main-sequence stars collected during the period from February 2007 to November 2020 are presented.These stars are located in the association Cepheus OB3,in t...Results from optical CCD photometric observations of 13 pre-main-sequence stars collected during the period from February 2007 to November 2020 are presented.These stars are located in the association Cepheus OB3,in the field of the young star V733 Cephei.Photometric observations,especially concerning the long-term variability of the stars,are missing in the literature.We present the first longterm V(RI)c monitoring for them,that cover 13 years.Results from our study indicate that all of the investigated stars manifest strong photometric variability.The presented paper is a part of our program for the photometric study of pre-main-sequence stars located in active star-forming regions.展开更多
This study employed Mendelian randomization(MR)analysis to confirm the association between breast cancer and the risk of anxiety and depression,and to explore the molecular mechanisms by which lipid nanoparticles of k...This study employed Mendelian randomization(MR)analysis to confirm the association between breast cancer and the risk of anxiety and depression,and to explore the molecular mechanisms by which lipid nanoparticles of ketamine(LNP@Ket)modulate these behaviors in a mouse model of breast cancer.Through single-cell transcriptomic analysis,the study aimed to clarify nuclear factor erythroid 2-related factor 2(Nrf2)’s role in the development of anxiety and depression in these mice.Analysis of patient data from genome-wide association study(GWAS)databases supported the link between breast cancer,anxiety,and depression.In vivo experiments demonstrated that treating breast cancer mice with LNP@Ket significantly reduced anxiety and depression behaviors.The synthesis of LNP@Ket and its subsequent analysis highlighted its inhibitory effects on these behaviors.Single-cell transcriptomic sequencing identified key cells and genes affected by LNP@Ket treatment,particularly emphasizing Nrf2.Upregulation of Nrf2 in astrocytes increased the expression of antioxidant enzymes and reduced pro-inflammatory cytokines,alleviating anxiety and depression symptoms by inhibiting neuroinflammation and neurodegeneration.This comprehensive study highlights the pivotal role of Nrf2 in the therapeutic efficacy of LNP@Ket for treating anxiety and depression in breast cancer mice.展开更多
The varying degrees of browning due to the Maillard reaction result in distinct characteristics across different parts within the cross-section of Houhuo low-temperature Daqu(LTD).However,the microbial community struc...The varying degrees of browning due to the Maillard reaction result in distinct characteristics across different parts within the cross-section of Houhuo low-temperature Daqu(LTD).However,the microbial community structure of the peel and core of Daqu is still poorly understood.In this study,using a combination of high-throughput sequencing and pure culture techniques,the microbial communities present in the peel and core of Houhuo LTD were compared and analyzed.Bacillus(58.84%)and Saccharomycopsis(87.61%)were the main bacterial and fungal genera present in Houhuo LTD.The abundance and diversity of fungi were significantly lower in peel samples(P<0.01).At the bacterial genus level,Sphingobium,Staphylococcus,and Streptomyces were significantly enriched in peel samples,while Saccharopolyspora was significantly enriched in core samples(P<0.05).At the fungal genus level,Saccharomycopsis and Clavispora were significantly enriched in peel samples,while Monascus and Aspergillus were significantly enriched in core samples(P<0.05).Differences in the layers of LTD block had a greater effect on the correlation between bacterial genera,and the microbial networks in the peel samples were more compact.Some microbial groups were common to the two groups,including the main bacterial genera Bacillus,Saccharopolyspora,Streptomyces,and Staphylococcus and the main fungal genera Saccharomycopsis and Monascus.Pure culture techniques revealed that B.paralicheniformis,Pediococcus pentosaceus,and S.fibuligera were the most abundant strains of Bacillus,lactic acid bacteria,and yeast in all samples,respectively.The findings could support the optimization of the Daqu-making processes and the screening of microbial strains for brewing.展开更多
Ovarian endometrioma(OE),also known as“chocolate cysts,”is a cystic mass that develops in the ovaries due to endometriosis and is a common gynecological condition characterized by the growth of endometrial tissue ou...Ovarian endometrioma(OE),also known as“chocolate cysts,”is a cystic mass that develops in the ovaries due to endometriosis and is a common gynecological condition characterized by the growth of endometrial tissue outside the uterus,leading to symptoms such as dysmenorrhea,pelvic pain,and infertility.However,the precise molecular and cellular mechanisms driving this pathophysiology remain largely unknown,posing challenges for diagnosis and treatment.Here,we employed integrated single-cell transcriptomic profiling of over 52,000 individual cells from endometrial tissues of OE patients and healthy donors and identified twelve major cell populations.We identified notable alterations in cell type-specific proportions and molecular signatures associated with OE.Notably,the activation of IGFBP5^(+) macrophages with pro-inflammatory properties,NK cell exhaustion,and aberrant proliferation of IQCG^(+) and KLF2^(+) epithelium are key features and may be the potential mechanisms underlying the pathogenesis of OE.Collectively,our data contribute to a better understanding of OE at the single cell level and may pave the way for the development of novel therapeutic strategies.展开更多
Realizing personalized medicine requires integrating diverse data types with bioinformatics.The most vital data are genomic information for individuals that are from advanced next-generation sequencing(NGS) technologi...Realizing personalized medicine requires integrating diverse data types with bioinformatics.The most vital data are genomic information for individuals that are from advanced next-generation sequencing(NGS) technologies at present.The technologies continue to advance in terms of both decreasing cost and sequencing speed with concomitant increase in the amount and complexity of the data.The prodigious data together with the requisite computational pipelines for data analysis and interpretation are stressors to IT infrastructure and the scientists conducting the work alike.Bioinformatics is increasingly becoming the rate-limiting step with numerous challenges to be overcome for translating NGS data for personalized medicine.We review some key bioinformatics tasks,issues,and challenges in contexts of IT requirements,data quality,analysis tools and pipelines,and validation of biomarkers.展开更多
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.
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.
文摘RNA-sequencing(RNA-seq),based on next-generation sequencing technologies,has rapidly become a standard and popular technology for transcriptome analysis.However,serious challenges still exist in analyzing and interpreting the RNA-seq data.With the development of high-throughput sequencing technology,the sequencing depth of RNA-seq data increases explosively.The intricate biological process of transcriptome is more complicated and diversified beyond our imagination.Moreover,most of the remaining organisms still have no available reference genome or have only incomplete genome annotations.Therefore,a large number of bioinformatics methods for various transcriptomics studies are proposed to effectively settle these challenges.This review comprehensively summarizes the various studies in RNA-seq data analysis and their corresponding analysis methods,including genome annotation,quality control and pre-processing of reads,read alignment,transcriptome assembly,gene and isoform expression quantification,differential expression analysis,data visualization and other analyses.
文摘A fundamental goal in cellular signaling is to understand allosteric communication, the process by which sig-nals originating at one site in a protein propagate reliably to affect distant functional sites. The general principles of protein structure that underlie this process remain unknown. Statistical coupling analysis （SCA） is a statistical technique that uses evolutionary data of a protein family to measure correlation between distant functional sites and suggests allosteric communication. In proteins, very distant and small interactions between collections of amino acids provide the communication which can be important for signaling process. In this paper, we present the SCA of protein alignment of the esterase family （pfam ID： PF00756） containing the sequence of antigen 85C secreted by Mycobacterium tuberculosis to identify a subset of interacting residues. Clustering analysis of the pairwise correlation highlighted seven important residue positions in the esterase family alignments. These resi-dues were then mapped on the crystal structure of antigen 85C （PDB ID： 1DQZ）. The mapping revealed corre-lation between 3 distant residues （Asp38, Leu123 and Met125） and suggests allosteric communication between them. This information can be used for a new drug against this fatal disease.
基金supported by the National Natural Science Foundation of China ( 62325202 , 62372041 and U22A2039 ).
文摘With continuous developments in biotechnology and information technology,we are entering the era of biological sequence big data.Extracting valuable insights from large-scale data to decipher life activities presents a major challenge.Artificial intelligence,particularly big data analysis and natural language processing technologies,has emerged as a crucial tool in biological sequence analysis.These technologies facilitate pattern detection,offering new perspectives on complex biological processes.Notably,AlphaFold and ESM models have achieved signifi-cant strides in protein structure prediction and functional annotation.These breakthroughs not only accelerate fundamental biological research but also provide innovative tools and strategies for disease diagnosis and drug discovery.In this perspective,we discuss the advancements in biological sequence analysis and focus on their extensive medical applications.Additionally,we highlight relevant challenges and propose further directions,emphasizing the need for ongoing innovation in sequence analysis to fully realize its potential in biomedical research.
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.
基金supported by the National Key R&D Program of China(Grants No.2021YFF1200900,2021YFF1200903,2016YFC0901604&2018YFC091040)the Natural Science Foundation of Guangdong Province(Grant No.2021A1515012108)+1 种基金the Guangdong Project(Grant No.2017GC010608)the Support Scheme of Guangzhou for Leading Talents in Innovation and Entrepreneurship(Grant No.2020007).
文摘Background:Evidence has suggested that cytokine storms may be associated with T cell exhaustion(TEX)in COVID-19.However,the interaction mechanism between cytokine storms and TEX remains unclear.Methods:With the aim of dissecting the molecular relationship of cytokine storms and TEX through single-cell RNA sequencing data analysis,we identified 14 cell types from bronchoalveolar lavage fluid of COVID-19 patients and healthy people.We observed a novel subset of severely exhausted CD8 T cells(Exh T_CD8)that co-expressed multiple inhibitory receptors,and two macrophage subclasses that were the main source of cytokine storms in bronchoalveolar.Results:Correlation analysis between cytokine storm level and TEX level suggested that cytokine storms likely promoted TEX in severe COVID-19.Cell–cell communication analysis indicated that cytokines(e.g.CXCL10,CXCL11,CXCL2,CCL2,and CCL3)released by macrophages acted as ligands and significantly interacted with inhibitory receptors(e.g.CXCR3,DPP4,CCR1,CCR2,and CCR5)expressed by Exh T_CD8.These interactions formed the cytokine–receptor axes,which were also verified to be significantly correlated with cytokine storms and TEX in lung squamous cell carcinoma.Conclusions:Cytokine storms may promote TEX through cytokine-receptor axes and be associated with poor prognosis in COVID19.Blocking cytokine-receptor axes may reverse TEX.Our finding provides novel insights into TEX in COVID-19 and new clues for cytokine-targeted immunotherapy development.
基金supported by the National Key R&D Program(No.2022YFD2400700)from the Ministry of Science and Technology of Chinathe Open Competition Project(No.JBGS[2021]127)from the Department of Agriculture and Rural Affairs of Jiangsu Provincepartially supported by the platform project of Shanghai Collaborative Innovation Center for Cultivating Elite Breeds and Green-culture of Aquaculture Animals(No.2021-KJ-02-12)。
文摘Open earthen pond-based larviculture is the main method for rearing Chinese mitten crab(Eriocheir sinensis)larvae in China.Bacterioplankton play a vital role in aquaculture ecosystems,but their community succession throughout the larval nursery stages of E.sinensis in such systems is still poorly understood.Using 16S rRNA gene amplicon sequencing,this study characterized the dynamics of bacterioplankton communities during a complete E.sinensis larval rearing cycle in open earthen ponds.Results presented a distinct,unidirectional succession in bacterioplankton composition,characterized by a decrease in Alphaproteobacteria and an increase in Actinobacteria.Live feeds(Brachionus plicatilis and Artemia salina)significantly affected bacterioplankton communities directly through their biological activities and indirectly by modifying the structure of phytoplankton composition.In addition to live feeds,water temperature and dissolved oxygen were key environmental factors affecting the structure of bacterioplankton communities.Biotic interactions,specifically with phytoplankton and copepods,were key drivers of bacterioplankton succession.Routine feeding practices during larval cultivation decreased bacterioplankton network complexity and strengthened community stability.Keystone taxa,specifically OTU783(Rhodobacteraceae)and OTU1235(Microbacteriaceae),played an essential role in maintaining the community stability through recruiting more rare species during the later stages despite their low abundances.These outcomes advance our understanding of the mechanisms central to bacterioplankton community succession and stability in E.sinensis larviculture systems,offering critical insights for developing sustainable aquaculture management strategies.
基金supported by the National Key Research and Development Program of China(2016YFD0100101-18,2020YFD1000904-1-3)the National Natural Science Foundation of China(31601216,31770397)Fundamental Research Funds for the Central Universities(2662019QD053,2662020ZKPY017)。
文摘With the rapid development of genetic analysis techniques and crop population size,phenotyping has become the bottleneck restricting crop breeding.Breaking through this bottleneck will require phenomics,defined as the accurate,high-throughput acquisition and analysis of multi-dimensional phenotypes during crop growth at organism-wide levels,ranging from cells to organs,individual plants,plots,and fields.Here we offer an overview of crop phenomics research from technological and platform viewpoints at various scales,including microscopic,ground-based,and aerial phenotyping and phenotypic data analysis.We describe recent applications of high-throughput phenotyping platforms for abiotic/biotic stress and yield assessment.Finally,we discuss current challenges and offer perspectives on future phenomics research.
基金supported by a grant from the Standardization and Integration of Resources Information for Seed-cluster in Hub-Spoke Material Bank Program,Rural Development Administration,Republic of Korea(PJ01587004).
文摘Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.
基金partly supported by the National Science Fund of the Ministry of Education and Science of Bulgaria under grant DN 18-10/2017funds of the project RD-08-125/2021 of the University of Shumen。
文摘Results from optical CCD photometric observations of 13 pre-main-sequence stars collected during the period from February 2007 to November 2020 are presented.These stars are located in the association Cepheus OB3,in the field of the young star V733 Cephei.Photometric observations,especially concerning the long-term variability of the stars,are missing in the literature.We present the first longterm V(RI)c monitoring for them,that cover 13 years.Results from our study indicate that all of the investigated stars manifest strong photometric variability.The presented paper is a part of our program for the photometric study of pre-main-sequence stars located in active star-forming regions.
文摘This study employed Mendelian randomization(MR)analysis to confirm the association between breast cancer and the risk of anxiety and depression,and to explore the molecular mechanisms by which lipid nanoparticles of ketamine(LNP@Ket)modulate these behaviors in a mouse model of breast cancer.Through single-cell transcriptomic analysis,the study aimed to clarify nuclear factor erythroid 2-related factor 2(Nrf2)’s role in the development of anxiety and depression in these mice.Analysis of patient data from genome-wide association study(GWAS)databases supported the link between breast cancer,anxiety,and depression.In vivo experiments demonstrated that treating breast cancer mice with LNP@Ket significantly reduced anxiety and depression behaviors.The synthesis of LNP@Ket and its subsequent analysis highlighted its inhibitory effects on these behaviors.Single-cell transcriptomic sequencing identified key cells and genes affected by LNP@Ket treatment,particularly emphasizing Nrf2.Upregulation of Nrf2 in astrocytes increased the expression of antioxidant enzymes and reduced pro-inflammatory cytokines,alleviating anxiety and depression symptoms by inhibiting neuroinflammation and neurodegeneration.This comprehensive study highlights the pivotal role of Nrf2 in the therapeutic efficacy of LNP@Ket for treating anxiety and depression in breast cancer mice.
基金supported by the Projects of Innovation and Development Pillar Program for Key Industries in Southern Xinjiang of Xinjiang Production and Construction Corps(2022DB007)Hubei University of Arts and Science Cultivation Fund for Teachers’Scientific Research Ability:Technological Innovation Team(2020kypytd009).
文摘The varying degrees of browning due to the Maillard reaction result in distinct characteristics across different parts within the cross-section of Houhuo low-temperature Daqu(LTD).However,the microbial community structure of the peel and core of Daqu is still poorly understood.In this study,using a combination of high-throughput sequencing and pure culture techniques,the microbial communities present in the peel and core of Houhuo LTD were compared and analyzed.Bacillus(58.84%)and Saccharomycopsis(87.61%)were the main bacterial and fungal genera present in Houhuo LTD.The abundance and diversity of fungi were significantly lower in peel samples(P<0.01).At the bacterial genus level,Sphingobium,Staphylococcus,and Streptomyces were significantly enriched in peel samples,while Saccharopolyspora was significantly enriched in core samples(P<0.05).At the fungal genus level,Saccharomycopsis and Clavispora were significantly enriched in peel samples,while Monascus and Aspergillus were significantly enriched in core samples(P<0.05).Differences in the layers of LTD block had a greater effect on the correlation between bacterial genera,and the microbial networks in the peel samples were more compact.Some microbial groups were common to the two groups,including the main bacterial genera Bacillus,Saccharopolyspora,Streptomyces,and Staphylococcus and the main fungal genera Saccharomycopsis and Monascus.Pure culture techniques revealed that B.paralicheniformis,Pediococcus pentosaceus,and S.fibuligera were the most abundant strains of Bacillus,lactic acid bacteria,and yeast in all samples,respectively.The findings could support the optimization of the Daqu-making processes and the screening of microbial strains for brewing.
基金supported from Scientific and Technological Innovation Project of China Academy of Chinese Medical Sciences(CI2023D003,CI2021B014)the National Key Research and Development Program of China(2022YFC2303600,2020YFA0908000)+8 种基金the Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine(ZYYCXTD-C-202002)the CACMS Innovation Fund(CI2023E002,CI2021A05101,CI2021A05104)the Science and Technology Foundation o f Shenzhen(JCYJ20210324115800001)the Science and Technology Foundation of Shenzhen(Shenzhen Clinical Medical Research Center for Geriatric Diseases)the Shenzhen Medical Research Fund(B2302051)the National Natural Science Foundation of China(82201786)Guangdong Basic and Applied Basic Research Foundation(2021A1515110646)Guangdong-Dongguan Joint Fund Regional Cultivation Project(2021B1515140033)Dongguan Science and Technology of Social Development Program(20211800904742,20221800905732,20221800904462).
文摘Ovarian endometrioma(OE),also known as“chocolate cysts,”is a cystic mass that develops in the ovaries due to endometriosis and is a common gynecological condition characterized by the growth of endometrial tissue outside the uterus,leading to symptoms such as dysmenorrhea,pelvic pain,and infertility.However,the precise molecular and cellular mechanisms driving this pathophysiology remain largely unknown,posing challenges for diagnosis and treatment.Here,we employed integrated single-cell transcriptomic profiling of over 52,000 individual cells from endometrial tissues of OE patients and healthy donors and identified twelve major cell populations.We identified notable alterations in cell type-specific proportions and molecular signatures associated with OE.Notably,the activation of IGFBP5^(+) macrophages with pro-inflammatory properties,NK cell exhaustion,and aberrant proliferation of IQCG^(+) and KLF2^(+) epithelium are key features and may be the potential mechanisms underlying the pathogenesis of OE.Collectively,our data contribute to a better understanding of OE at the single cell level and may pave the way for the development of novel therapeutic strategies.
文摘Realizing personalized medicine requires integrating diverse data types with bioinformatics.The most vital data are genomic information for individuals that are from advanced next-generation sequencing(NGS) technologies at present.The technologies continue to advance in terms of both decreasing cost and sequencing speed with concomitant increase in the amount and complexity of the data.The prodigious data together with the requisite computational pipelines for data analysis and interpretation are stressors to IT infrastructure and the scientists conducting the work alike.Bioinformatics is increasingly becoming the rate-limiting step with numerous challenges to be overcome for translating NGS data for personalized medicine.We review some key bioinformatics tasks,issues,and challenges in contexts of IT requirements,data quality,analysis tools and pipelines,and validation of biomarkers.
