BACKGROUND Pyroptosis impacts the development of malignant tumors,yet its role in colorectal cancer(CRC)prognosis remains uncertain.AIM To assess the prognostic significance of pyroptosis-related genes and their assoc...BACKGROUND Pyroptosis impacts the development of malignant tumors,yet its role in colorectal cancer(CRC)prognosis remains uncertain.AIM To assess the prognostic significance of pyroptosis-related genes and their association with CRC immune infiltration.METHODS Gene expression data were obtained from The Cancer Genome Atlas(TCGA)and single-cell RNA sequencing dataset GSE178341 from the Gene Expression Omnibus(GEO).Pyroptosis-related gene expression in cell clusters was analyzed,and enrichment analysis was conducted.A pyroptosis-related risk model was developed using the LASSO regression algorithm,with prediction accuracy assessed through K-M and receiver operating characteristic analyses.A nomo-gram predicting survival was created,and the correlation between the risk model and immune infiltration was analyzed using CIBERSORTx calculations.Finally,the differential expression of the 8 prognostic genes between CRC and normal samples was verified by analyzing TCGA-COADREAD data from the UCSC database.RESULTS An effective pyroptosis-related risk model was constructed using 8 genes-CHMP2B,SDHB,BST2,UBE2D2,GJA1,AIM2,PDCD6IP,and SEZ6L2(P<0.05).Seven of these genes exhibited differential expression between CRC and normal samples based on TCGA database analysis(P<0.05).Patients with higher risk scores demonstrated increased death risk and reduced overall survival(P<0.05).Significant differences in immune infiltration were observed between low-and high-risk groups,correlating with pyroptosis-related gene expression.CONCLUSION We developed a pyroptosis-related prognostic model for CRC,affirming its correlation with immune infiltration.This model may prove useful for CRC prognostic evaluation.展开更多
Soil salinization may affect biodiversity and species composition,leading to changes in the plant community structure.However,few studies have explored the spatial pattern of soil salinization and its effects on shrub...Soil salinization may affect biodiversity and species composition,leading to changes in the plant community structure.However,few studies have explored the spatial pattern of soil salinization and its effects on shrub community structure at the ecosystem scale.Therefore,we conducted a transect sampling of desert shrublands in Northwest China during the growing season(June–September)in 2021.Soil salinization(both the degree and type),shrub community structure(e.g.,shrub density and height),and biodiversity parameters(e.g.,Simpson diversity,Margalf abundance,Shannon-Wiener diversity,and Pielou evenness indices)were used to assess the effects of soil salinization on shrub community structure.The results showed that the primary degree of soil salinization in the study area was light salinization,with the area proportion of 69.8%.Whereas the main type of soil salinization was characterized as sulfate saline soil,also accounting for 69.8%of the total area.Notably,there was a significant reduction in the degree of soil salinization and a shift in the type of soil salinization from chloride saline soil to sulfate saline soil,with an increase in longitude.Regional mean annual precipitation(MAP),mean annual evapotranspiration(MAE),elevation,and slope significantly contributed to soil salinization and its geochemical differentiation.As soil salinization intensified,shrub community structure displayed increased diversity and evenness,as indicated by the increases in the Simpson diversity,Shannon-Wiener diversity,and Pielou evenness indices.Moreover,the succulent stems and leaves of Chenopodiaceae and Tamaricaceae exhibited clear advantages under these conditions.Furthermore,regional climate and topography,such as MAP,MAE,and elevation,had greater effects on the distribution of shrub plants than soil salinization.These results provide a reference for the origin and pattern of soil salinization in drylands and their effects on the community structure of halophyte shrub species.展开更多
Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laborat...Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing.Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing.Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing.Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.展开更多
Achieving a balance between accuracy and efficiency in target detection applications is an important research topic.To detect abnormal targets on power transmission lines at the power edge,this paper proposes an effec...Achieving a balance between accuracy and efficiency in target detection applications is an important research topic.To detect abnormal targets on power transmission lines at the power edge,this paper proposes an effective method for reducing the data bit width of the network for floating-point quantization.By performing exponent prealignment and mantissa shifting operations,this method avoids the frequent alignment operations of standard floating-point data,thereby further reducing the exponent and mantissa bit width input into the training process.This enables training low-data-bit width models with low hardware-resource consumption while maintaining accuracy.Experimental tests were conducted on a dataset of real-world images of abnormal targets on transmission lines.The results indicate that while maintaining accuracy at a basic level,the proposed method can significantly reduce the data bit width compared with single-precision data.This suggests that the proposed method has a marked ability to enhance the real-time detection of abnormal targets in transmission circuits.Furthermore,a qualitative analysis indicated that the proposed quantization method is particularly suitable for hardware architectures that integrate storage and computation and exhibit good transferability.展开更多
研究旨在探讨丁酸甘油酯对断奶仔猪生长性能和腹泻率的影响,运用Meta分析方法进行系统评价。经检索万方、中国知网、维普、Pub Med和Web of Science数据库,搜索丁酸甘油酯对断奶仔猪生长性能影响的文献,按照纳入和排除标准筛选文献、提...研究旨在探讨丁酸甘油酯对断奶仔猪生长性能和腹泻率的影响,运用Meta分析方法进行系统评价。经检索万方、中国知网、维普、Pub Med和Web of Science数据库,搜索丁酸甘油酯对断奶仔猪生长性能影响的文献,按照纳入和排除标准筛选文献、提取资料,用Review Manager 5.4软件进行Meta分析。共纳入12个研究,样本838例。结果显示:丁酸甘油酯组的平均日增重显著高于空白组(P<0.0001,SMD=1.58,95%CI:0.80~2.36),平均日采食量与空白组差异不显著(P=0.30,SMD=-0.44,95%CI:-1.28~0.40),料重比显著低于空白组(P=0.0002,SMD=-0.85,95%CI:-1.29~-0.40),腹泻率显著低于空白组(P=0.0003,SMD=-2.78,95%CI:-4.27~-1.28)。说明饲料中添加丁酸甘油酯可显著提高断奶仔猪的平均日增重,降低料重比和腹泻率,建议丁酸甘油酯添加量为1%~2%。展开更多
基金Supported by the National Natural Science Foundation of China,No.81960100Applied Basic Foundation of Yunnan Province,No.202001AY070001-192+2 种基金Young and Middle-aged Academic and Technical Leaders Reserve Talents Program in Yunnan Province,No.202305AC160018Yunnan Revitalization Talent Support Program,No.RLQB20200004 and No.RLMY20220013and Yunnan Health Training Project of High-Level Talents,No.H-2017002。
文摘BACKGROUND Pyroptosis impacts the development of malignant tumors,yet its role in colorectal cancer(CRC)prognosis remains uncertain.AIM To assess the prognostic significance of pyroptosis-related genes and their association with CRC immune infiltration.METHODS Gene expression data were obtained from The Cancer Genome Atlas(TCGA)and single-cell RNA sequencing dataset GSE178341 from the Gene Expression Omnibus(GEO).Pyroptosis-related gene expression in cell clusters was analyzed,and enrichment analysis was conducted.A pyroptosis-related risk model was developed using the LASSO regression algorithm,with prediction accuracy assessed through K-M and receiver operating characteristic analyses.A nomo-gram predicting survival was created,and the correlation between the risk model and immune infiltration was analyzed using CIBERSORTx calculations.Finally,the differential expression of the 8 prognostic genes between CRC and normal samples was verified by analyzing TCGA-COADREAD data from the UCSC database.RESULTS An effective pyroptosis-related risk model was constructed using 8 genes-CHMP2B,SDHB,BST2,UBE2D2,GJA1,AIM2,PDCD6IP,and SEZ6L2(P<0.05).Seven of these genes exhibited differential expression between CRC and normal samples based on TCGA database analysis(P<0.05).Patients with higher risk scores demonstrated increased death risk and reduced overall survival(P<0.05).Significant differences in immune infiltration were observed between low-and high-risk groups,correlating with pyroptosis-related gene expression.CONCLUSION We developed a pyroptosis-related prognostic model for CRC,affirming its correlation with immune infiltration.This model may prove useful for CRC prognostic evaluation.
基金financially supported by the National Natural Sciences Foundation of China(42330503,42171068)the Third Xinjiang Scientific Expedition Program(2022xjkk0901)the Tianshan Talent Training Program(2023TSYCLJ0048).
文摘Soil salinization may affect biodiversity and species composition,leading to changes in the plant community structure.However,few studies have explored the spatial pattern of soil salinization and its effects on shrub community structure at the ecosystem scale.Therefore,we conducted a transect sampling of desert shrublands in Northwest China during the growing season(June–September)in 2021.Soil salinization(both the degree and type),shrub community structure(e.g.,shrub density and height),and biodiversity parameters(e.g.,Simpson diversity,Margalf abundance,Shannon-Wiener diversity,and Pielou evenness indices)were used to assess the effects of soil salinization on shrub community structure.The results showed that the primary degree of soil salinization in the study area was light salinization,with the area proportion of 69.8%.Whereas the main type of soil salinization was characterized as sulfate saline soil,also accounting for 69.8%of the total area.Notably,there was a significant reduction in the degree of soil salinization and a shift in the type of soil salinization from chloride saline soil to sulfate saline soil,with an increase in longitude.Regional mean annual precipitation(MAP),mean annual evapotranspiration(MAE),elevation,and slope significantly contributed to soil salinization and its geochemical differentiation.As soil salinization intensified,shrub community structure displayed increased diversity and evenness,as indicated by the increases in the Simpson diversity,Shannon-Wiener diversity,and Pielou evenness indices.Moreover,the succulent stems and leaves of Chenopodiaceae and Tamaricaceae exhibited clear advantages under these conditions.Furthermore,regional climate and topography,such as MAP,MAE,and elevation,had greater effects on the distribution of shrub plants than soil salinization.These results provide a reference for the origin and pattern of soil salinization in drylands and their effects on the community structure of halophyte shrub species.
基金supported by the National Key Research and Development Program(grant number:2022YFC2305304).
文摘Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing.Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing.Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing.Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.
基金supported by State Grid Corporation Basic Foresight Project(5700-202255308A-2-0-QZ).
文摘Achieving a balance between accuracy and efficiency in target detection applications is an important research topic.To detect abnormal targets on power transmission lines at the power edge,this paper proposes an effective method for reducing the data bit width of the network for floating-point quantization.By performing exponent prealignment and mantissa shifting operations,this method avoids the frequent alignment operations of standard floating-point data,thereby further reducing the exponent and mantissa bit width input into the training process.This enables training low-data-bit width models with low hardware-resource consumption while maintaining accuracy.Experimental tests were conducted on a dataset of real-world images of abnormal targets on transmission lines.The results indicate that while maintaining accuracy at a basic level,the proposed method can significantly reduce the data bit width compared with single-precision data.This suggests that the proposed method has a marked ability to enhance the real-time detection of abnormal targets in transmission circuits.Furthermore,a qualitative analysis indicated that the proposed quantization method is particularly suitable for hardware architectures that integrate storage and computation and exhibit good transferability.
