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Effect of MSTN Propeptide and shRNA Co-expression Vector on Proliferation of Skeletal Muscle Satellite Cells
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作者 Feng Lin-he Wang Xin +3 位作者 Lu Ming Tong Hui-li Li Shu-feng Yan Yun-qin 《Journal of Northeast Agricultural University(English Edition)》 CAS 2014年第1期31-38,共8页
Myostatin (MSTN) is a negative regulator of skeletal muscle growth, in order to study the effect of inhibition MSTN expression on the proliferation of bovine skeletal muscle satellite cells, we constructed co-expres... Myostatin (MSTN) is a negative regulator of skeletal muscle growth, in order to study the effect of inhibition MSTN expression on the proliferation of bovine skeletal muscle satellite cells, we constructed co-expression vector pcDNA3.1-Pro- MSTNshRNA, transfected it into muscle satellite cells by Liposome 2000, and detected cell proliferation changes by CCK-8 method and flow cytometry after 48 h. The expressions of P21 and CDK2 were detected by Western blot and real-time PCR. The results showed that the cell vitality of experimental groups significantly increased than that of the negative control, and cells in S phase also increased significantly (P〈0.05). After knocked down MSTN gene, P21 expression decreased (P〈0.05), but CDK2 gene expression increased (P〈0.05). These results indicated that MSTN gene expression was associated with P21 and CDK2, the proliferation of skeletal muscle satellite cells could be promoted while MSTN was inhibited, which provided a theoretical basis for the study on transgenic cattle. 展开更多
关键词 MYOSTATIN cell proliferation flow cytometry expression vector
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Co-expression of cancer stem cell markers CD24 and CD133 in gastric cancer tissues:Clinicopathological and prognostic significance
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作者 Cheng-Xian Ma Jie Chen +4 位作者 Jian-Lin Wang Shuai Pei Zhao-Jun Zhang Yu-Si Xie Xia He 《World Journal of Stem Cells》 2026年第1期25-35,共11页
BACKGROUND Gastric cancer(GC)is one of the most common malignant tumors of the digestive system worldwide,the prognosis of patients with advanced GC remains poor.AIM To evaluate the combined expression characteristics... BACKGROUND Gastric cancer(GC)is one of the most common malignant tumors of the digestive system worldwide,the prognosis of patients with advanced GC remains poor.AIM To evaluate the combined expression characteristics of cancer stem cell markers CD24 and CD133 in GC pathological tissues,and to explore their association with patients’clinicopathological parameters and postoperative survival outcomes.METHODS A total of 304 GC patients who underwent surgical treatment in our hospital from January 2018 to January 2020 were retrospectively included.Immunohistochemistry was used to detect the protein expression of CD24 and CD133 in tumor tissues,adjacent tissues,and normal gastric mucosa tissues.Based on staining intensity and the proportion of positive cells,expression levels were classified into low and high expression,while clinicopathological parameters were recorded.χ2 test was used to evaluate the correlation between expression and categorical variables,Spearman rank correlation analysis was performed to assess the correlation between the expression intensities of the two markers,and multivariate regression models were applied to identify independent risk factors influencing co-expression.Kaplan-Meier survival curves and Log-rank test were used to compare survival differences among groups with different expression patterns.RESULTS Among the 304 patients,155 cases(50.99%)were CD24 positive,including 91 low-expression and 64 highexpression;133 cases(43.75%)were CD133 positive,including 81 low-expression and 52 high-expression.There were 74 cases(24.34%)with double positivity and 81 cases(26.64%)with double negativity.Compared with tumor tissues,the positive rates of CD24 and CD133 in normal gastric tissues and adjacent tissues were significantly lower(P<0.05).Univariate analysis showed that co-expression of CD24 and CD133 in GC tissues was significantly correlated with tumor size,Lauren classification,T stage,N stage,and vascular invasion(P<0.05),but not with patient age,gender,tumor site,World Health Organization histological classification,or M stage(P>0.05).Further multivariate regression analysis suggested that tumor size,T stage,N stage,and vascular invasion were independent risk factors promoting CD24 and CD133 double positivity.Spearman rank correlation analysis indicated a moderate positive correlation between their expression intensities(r=0.420,P<0.001).During follow-up,29 of 304 patients were lost(loss rate 9.54%);146 deaths occurred.According to expression combination,there were 89 cases of CD24 single positivity(39 deaths),68 cases of CD133 single positivity(31 deaths),81 cases of double negativity(25 deaths),and 66 cases of double positivity(51 deaths).Log-rank test showed significant differences in overall survival among the four groups(χ2=20.89,P<0.001),with CD24+/CD133+group showing the worst prognosis.CONCLUSION CD24 and CD133 exhibit high positive detection rates in GC tissues,and their co-positivity is closely associated with tumor stage progression and significantly indicates unfavorable survival outcomes.The co-expression of CD24/CD133 may reflect higher aggressiveness and metastatic potential of GC,serving as a potential prognostic marker and a direction for targeted therapeutic strategies.However,as this is a single-center retrospective study with limitations such as patient loss to follow-up and sample size,further prospective,multicenter,and mechanistic studies are required to validate its clinical applicability and biological role. 展开更多
关键词 Gastric cancer CD24 CD133 Cancer stem cell co-expression Prognosis IMMUNOHISTOCHEMISTRY
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Genome-wide association and co-expression uncovered ZmMYB71 controls kernel starch content in maize
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作者 Jienan Han Ran Li +14 位作者 Ze Zhang Shiyuan Liu Qianqian Liu Zhennan Xu Zhiqiang Zhou Xin Lu Xiaochuan Shangguan Tingfang Zhou Jianfeng Weng Zhuanfang Hao Degui Zhang Hongjun Yong Jingyu Xu Mingshun Li Xinhai Li 《Journal of Integrative Agriculture》 2025年第12期4496-4514,共19页
Starch serves as a critical storage component,significantly influencing the grain yield and quality of maize(Zea mays L.).Understanding the genetic basis of natural variation in kernel starch content(SC)is essential f... Starch serves as a critical storage component,significantly influencing the grain yield and quality of maize(Zea mays L.).Understanding the genetic basis of natural variation in kernel starch content(SC)is essential for maize breeding to meet future demands.A genome-wide association study(GWAS)identified 84 and 96 loci associated with kernel SC across two years,overlapping with 185 candidate genes.The candidate gene Zm MYB71,encoding a MYB-related transcription factor,demonstrated the highest co-expression frequency with starch synthesis genes.Analysis revealed that Zm MYB71 functions as a nuclear located transcription repressor,and mutants exhibited increased kernel SC by over 2.32%,with minimal impact on amylose content or 100-grain weight.Sh1,Sh2,and GBSSI exhibited up-regulation in mutants by 1.56-,1.45-and 1.32-fold,respectively,aligning with RNA sequencing results;their promoter activities appear directly repressed by Zm MYB71 through the GATATC and TTAGGG motifs.Additionally,the Zm MYB71 elite haplotype Hap1 occurred in over 55%of the high-starch maize sub-populations Iowa Stiff Stalk Synthetic(BSSS)and Partner B(PB),but only in 7.14%of the low-starch sub-population Partner A(PA).Analysis of Hap1 haplotype frequencies across breeding stages revealed a significant increase to 40.28%in inbred groups released after 2010,compared to 28.57 and 27.94%in 1980 and 1990,and 2000,respectively.These findings enhance understanding of natural variation in maize kernel SC and establish Zm MYB71 as a negative regulator with potential applications in SC improvement. 展开更多
关键词 MAIZE kernel starch content co-expression analysis ZmMYB71 negative regulator
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Support Vector-Guided Class-Incremental Learning:Discriminative Replay with Dual-Alignment Distillation
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作者 Moyi Zhang Yixin Wang Yu Cheng 《Computers, Materials & Continua》 2026年第3期2040-2061,共22页
Modern intelligent systems,such as autonomous vehicles and face recognition,must continuously adapt to new scenarios while preserving their ability to handle previously encountered situations.However,when neural netwo... Modern intelligent systems,such as autonomous vehicles and face recognition,must continuously adapt to new scenarios while preserving their ability to handle previously encountered situations.However,when neural networks learn new classes sequentially,they suffer from catastrophic forgetting—the tendency to lose knowledge of earlier classes.This challenge,which lies at the core of class-incremental learning,severely limits the deployment of continual learning systems in real-world applications with streaming data.Existing approaches,including rehearsalbased methods and knowledge distillation techniques,have attempted to address this issue but often struggle to effectively preserve decision boundaries and discriminative features under limited memory constraints.To overcome these limitations,we propose a support vector-guided framework for class-incremental learning.The framework integrates an enhanced feature extractor with a Support Vector Machine classifier,which generates boundary-critical support vectors to guide both replay and distillation.Building on this architecture,we design a joint feature retention strategy that combines boundary proximity with feature diversity,and a Support Vector Distillation Loss that enforces dual alignment in decision and semantic spaces.In addition,triple attention modules are incorporated into the feature extractor to enhance representation power.Extensive experiments on CIFAR-100 and Tiny-ImageNet demonstrate effective improvements.On CIFAR-100 and Tiny-ImageNet with 5 tasks,our method achieves 71.68%and 58.61%average accuracy,outperforming strong baselines by 3.34%and 2.05%.These advantages are consistently observed across different task splits,highlighting the robustness and generalization of the proposed approach.Beyond benchmark evaluations,the framework also shows potential in few-shot and resource-constrained applications such as edge computing and mobile robotics. 展开更多
关键词 Class-incremental learning catastrophic forgetting support vector machine knowledge distillation
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Adeno-associated viral vectors for modeling Parkinson's disease in non-human primates
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作者 Julia Chocarro José L.Lanciego 《Neural Regeneration Research》 2026年第1期224-232,共9页
The development of clinical candidates that modify the natural progression of sporadic Parkinson's disease and related synucleinopathies is a praiseworthy endeavor,but extremely challenging.Therapeutic candidates ... The development of clinical candidates that modify the natural progression of sporadic Parkinson's disease and related synucleinopathies is a praiseworthy endeavor,but extremely challenging.Therapeutic candidates that were successful in preclinical Parkinson's disease animal models have repeatedly failed when tested in clinical trials.While these failures have many possible explanations,it is perhaps time to recognize that the problem lies with the animal models rather than the putative candidate.In other words,the lack of adequate animal models of Parkinson's disease currently represents the main barrier to preclinical identification of potential disease-modifying therapies likely to succeed in clinical trials.However,this barrier may be overcome by the recent introduction of novel generations of viral vectors coding for different forms of alpha-synuclein species and related genes.Although still facing several limitations,these models have managed to mimic the known neuropathological hallmarks of Parkinson's disease with unprecedented accuracy,delineating a more optimistic scenario for the near future. 展开更多
关键词 adeno-associated viral vectors ALPHA-SYNUCLEIN DOPAMINE Lewy bodies NEURODEGENERATION NEUROMELANIN NEUROPATHOLOGY substantia nigra
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Yaw stabilization and maneuvering control of tailless flying wing by co-directional fluidic thrust vectoring
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作者 Liu ZHANG Meng HE 《Chinese Journal of Aeronautics》 2026年第1期66-77,共12页
Fluidic Thrust Vectoring(FTV)is used for the yaw attitude control of tailless flying wing,which can significantly improve stealth performance,maneuverability and lateral/heading maneuverability.The FTV control scheme ... Fluidic Thrust Vectoring(FTV)is used for the yaw attitude control of tailless flying wing,which can significantly improve stealth performance,maneuverability and lateral/heading maneuverability.The FTV control scheme of co-directional secondary flow was designed based on a 30 kgf thrust turbojet engine,an equivalent rudder deflection control variable of Mass Flow Combination(MFC)was proposed,and a control model was established to form a FTV control system scheme,which was integrated with the flight control system of a 100 kg tailless flying wing with medium aspect ratio to achieve closed-loop control of the yaw attitude based on FTV.The heading stability augmentation and maneuvering control characteristics and time response characteristics of tailless flying wing by FTV were quantitatively studied through virtual flight test in a wind tunnel at a wind speed of 35 m/s.The results show that the control strategy based on MFC achieves bidirectional continuous and stable control of thrust vector angle in a range of±11°,and the thrust vector angle varies monotonically with MFC;the co-directional FTV realizes bidirectional continuous and stable control of the yaw attitude of tailless flying wing,without longitudinal/lateral coupling moment.The increment of the maximum yawing moment coefficient is 0.0029,the maximum yaw rate is 7.55(°)/s,and the response time of the yaw rate of the vectoring nozzle actuated by the secondary flow is about 0.06 s,which satisfies the heading stability augmentation and maneuvering control response requirements of the aircraft with statically unstable heading,and provides new control means for the heading rudderless attitude control of tailless flying wing. 展开更多
关键词 Thrust vectoring Flow control Coanda effect Flying-wing aircraft Flight tests Yaw control
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Using mixed kernel support vector machine to improve the predictive accuracy of genome selection
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作者 Jinbu Wang Wencheng Zong +6 位作者 Liangyu Shi Mianyan Li Jia Li Deming Ren Fuping Zhao Lixian Wang Ligang Wang 《Journal of Integrative Agriculture》 2026年第2期775-787,共13页
The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects acc... The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects accurately.Machine learning models have demonstrated remarkable potential in addressing these challenges.In this study,we introduced the concept of mixed kernel functions to explore the performance of support vector machine regression(SVR) in GS.Six single kernel functions(SVR_L,SVR_C,SVR_G,SVR_P,SVR_S,SVR_L) and four mixed kernel functions(SVR_GS,SVR_GP,SVR_LS,SVR_LP) were used to predict genome breeding values.The prediction accuracy,mean squared error(MSE) and mean absolute error(MAE) were used as evaluation indicators to compare with two traditional parametric models(GBLUP,BayesB) and two popular machine learning models(RF,KcRR).The results indicate that in most cases,the performance of the mixed kernel function model significantly outperforms that of GBLUP,BayesB and single kernel function.For instance,for T1 in the pig dataset,the predictive accuracy of SVR_GS is improved by 10% compared to GBLUP,and by approximately 4.4 and 18.6% compared to SVR_G and SVR_S respectively.For E1 in the wheat dataset,SVR_GS achieves 13.3% higher prediction accuracy than GBLUP.Among single kernel functions,the Laplacian and Gaussian kernel functions yield similar results,with the Gaussian kernel function performing better.The mixed kernel function notably reduces the MSE and MAE when compared to all single kernel functions.Furthermore,regarding runtime,SVR_GS and SVR_GP mixed kernel functions run approximately three times faster than GBLUP in the pig dataset,with only a slight increase in runtime compared to the single kernel function model.In summary,the mixed kernel function model of SVR demonstrates speed and accuracy competitiveness,and the model such as SVR_GS has important application potential for GS. 展开更多
关键词 genome selection machine learning support vector machine kernel function mixed kernel function
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A viral masterstroke:Geminivirus C4 protein reprograms auxin transport to attract its insect vector
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作者 Mingjun Li Lyuxin Wang +1 位作者 Gentu Wu Ling Qing 《Molecular Plant》 2026年第2期239-241,共3页
Disruption of host physiological processes,leading to symptom expression,is a common hallmark during plant virus infections.The concept of“symptoms as strategy”is rapidly reshaping our understanding of plant virolog... Disruption of host physiological processes,leading to symptom expression,is a common hallmark during plant virus infections.The concept of“symptoms as strategy”is rapidly reshaping our understanding of plant virology.An emerging theme is that symptom expressions—such as stunting,curling,and yellowing,which devastate yield—may themselves be evolved viral adaptation strategies rather than collateral damage. 展开更多
关键词 symptom expressions such viral masterstroke insect vector disruption host physiological processesleading geminivirus C protein host physiological processes auxin transport symptom expressionis
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A Convolutional Neural Network-Based Deep Support Vector Machine for Parkinson’s Disease Detection with Small-Scale and Imbalanced Datasets
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作者 Kwok Tai Chui Varsha Arya +2 位作者 Brij B.Gupta Miguel Torres-Ruiz Razaz Waheeb Attar 《Computers, Materials & Continua》 2026年第1期1410-1432,共23页
Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using d... Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using deep learning algorithms further enhances performance;nevertheless,it is challenging due to the nature of small-scale and imbalanced PD datasets.This paper proposed a convolutional neural network-based deep support vector machine(CNN-DSVM)to automate the feature extraction process using CNN and extend the conventional SVM to a DSVM for better classification performance in small-scale PD datasets.A customized kernel function reduces the impact of biased classification towards the majority class(healthy candidates in our consideration).An improved generative adversarial network(IGAN)was designed to generate additional training data to enhance the model’s performance.For performance evaluation,the proposed algorithm achieves a sensitivity of 97.6%and a specificity of 97.3%.The performance comparison is evaluated from five perspectives,including comparisons with different data generation algorithms,feature extraction techniques,kernel functions,and existing works.Results reveal the effectiveness of the IGAN algorithm,which improves the sensitivity and specificity by 4.05%–4.72%and 4.96%–5.86%,respectively;and the effectiveness of the CNN-DSVM algorithm,which improves the sensitivity by 1.24%–57.4%and specificity by 1.04%–163%and reduces biased detection towards the majority class.The ablation experiments confirm the effectiveness of individual components.Two future research directions have also been suggested. 展开更多
关键词 Convolutional neural network data generation deep support vector machine feature extraction generative artificial intelligence imbalanced dataset medical diagnosis Parkinson’s disease small-scale dataset
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Predicting Arabidopsis thaliana Gene Function by Transitiving Co-expression in Shortest-path 被引量:1
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作者 史锋莉 黄继风 +1 位作者 Feng-li Ji-feng 《Agricultural Science & Technology》 CAS 2010年第5期1-4,21,共5页
The present paper predicted the function of unknow genes by analyzing the co-expression data of Arabidopsis thaliana from biological pathway based on the shortest-path algorithm. This paper proposed that transitive co... The present paper predicted the function of unknow genes by analyzing the co-expression data of Arabidopsis thaliana from biological pathway based on the shortest-path algorithm. This paper proposed that transitive co-expression among genes can be used as an important attribute to link genes of the same biological pathway. The genes from the same biological pathway with similar functions are strongly correlated in expression. Moreover,the function of unknown genes can be predicted by the known genes where they are strongly correlated in expression lying on the same shortest-path from the biological pathway. Analyzing the Arabidopsis thaliana from the biological pathway,this study showed that this method can reliably reveal function of the unknown Arabidopsis thaliana genes and the approach of predicting gene function by transitiving co-expression in shortest-path is feasible and effective. 展开更多
关键词 Shortest-path Pathway co-expression Gene function Arabidopsis thaliana
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Identification of Differentially Expressed Genes in Grape Skin at Veraison and Maturity and Construction of Co-expression Network 被引量:4
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作者 Pengfei WANG Xilong JIANG +5 位作者 Xinying WU Ling SU Lei GONG Hongmei SHI Fengshan REN Yongmei WANG 《Agricultural Science & Technology》 CAS 2017年第11期1993-2000,共8页
The ripening process of grape is an important stage during grape growth and development. During this process, color of grape skin is the most obvious change. The molecular mechanism for the ripening of grape(a non-cli... The ripening process of grape is an important stage during grape growth and development. During this process, color of grape skin is the most obvious change. The molecular mechanism for the ripening of grape(a non-climacteric fruit, which ripens without ethylene and respiration bursts) is still unclear. Although numerous studies have been done on the changes in the contents of metabolites during grape ripening, the differentially expressed genes at veraison and maturity stages have not been systematically analyzed. In this study, 1 524 genes that are significantly differentially expressed in grape(Pinot Noir) skin at veraison and maturity stages were identified, and a co-expression network of these genes was built. Some of the eight co-expression modules we identified may be closely related to the synthesis or metabolism of anthocyanins, sugar acids, and other flavor substances. The transcription factor families WRKY, b ZIP, HSF and WOX may play an important role in the regulation of anthocyanin synthesis or metabolism. The results provide a foundation for further study of the molecular mechanism of grape ripening. 展开更多
关键词 GRAPE Fruit ripening co-expression network co-expression module ANTHOCYANIN Transcription factor
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MCENet: A database for maize conditional co-expression network and network characterization collaborated with multi-dimensional omics levels 被引量:5
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作者 Tian Tian Qi You +2 位作者 Hengyu Yan Wenying Xu Zhen Su 《Journal of Genetics and Genomics》 SCIE CAS CSCD 2018年第7期351-360,共10页
Maize (Zea mays) is the most widely grown grain crop in the world, playing important roles in agriculture and industry. However, the functions of maize genes remain largely unknown. High-quality genome- wide transcr... Maize (Zea mays) is the most widely grown grain crop in the world, playing important roles in agriculture and industry. However, the functions of maize genes remain largely unknown. High-quality genome- wide transcriptome datasets provide important biological knowledge which has been widely and suc- cessfully used in plants not only by measuring gene expression levels but also by enabling co-expression analysis for predicting gene functions and modules related to agronomic traits. Recently, thousands of maize transcriptomic data are available across different inbred lines, development stages, tissues, and treatments, or even across different tissue sections and cell lines. Here, we integrated 701 transcriptomic and 108 epigenomic data and studied the different conditional networks with multi-dimensional omics levels. We constructed a searchable, integrative, one-stop online platform, the maize conditional co- expression network (MCENet) platform. MCENet provides 10 global/conditional co-expression net- works, 5 network accessional analysis toolkits (i.e., Network Search, Network Remodel, Module Finder, Network Comparison, and Dynamic Expression View) and multiple network functional support toolkits (e.g., motif and module enrichment analysis). We hope that our database might help plant research communities to identify maize functional genes or modules that regulate important agronomic traits. 展开更多
关键词 Conditional co-expression network Module finder Transcriptomic datasets Epigenomic datasets MAIZE
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Identify the signature genes for diagnose of uveal melanoma by weight gene co-expression network analysis 被引量:10
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作者 Kai Shi Zhi-Tong Bing +4 位作者 Gui-Qun Cao Ling Guo Ya-Na Cao Hai-Ou Jiang Mei-Xia Zhang 《International Journal of Ophthalmology(English edition)》 SCIE CAS 2015年第2期269-274,共6页
AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression lev... AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.METHODS: Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus(GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes.The function of the genes were annotated by gene ontology(GO).RESULTS: In this study, we identified four co-expression modules significantly correlated with clinictraits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location(sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter(LTD). Additionally, we identified the hug gene(top connectivity with other genes) in each module. The hub gene RPS15 A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.CONCLUSION: From WGCNA analysis and hub gene calculation, we identified RPS15 A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma. 展开更多
关键词 weighted gene co-expression network analysis microarray data gene ontology
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Weighted Gene Co-expression Network Analysis of Gene Modules for the Prognosis of Esophageal Cancer 被引量:2
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作者 张丛 孙茜 《Journal of Huazhong University of Science and Technology(Medical Sciences)》 SCIE CAS 2017年第3期319-325,共7页
Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict t... Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas(TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival(PFS) or overall survival(OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that 'glycoprotein binding' was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor(PTAFR) and feline Gardner-Rasheed(FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer. 展开更多
关键词 esophageal cancer The Cancer Genome Atlas co-expression network analysis weighted gene co-expression network analysis enrichment analysis
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Enhanced production of shikimic acid using a multi-gene co-expression system in Escherichia coli 被引量:3
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作者 LIU Xiang-Lei LIN Jun +2 位作者 HU Hai-Feng ZHOU Bin ZHU Bao-Quan 《Chinese Journal of Natural Medicines》 SCIE CAS CSCD 2016年第4期286-293,共8页
Shikimic acid(SA) is the key synthetic material for the chemical synthesis of Oseltamivir, which is prescribed as the front-line treatment for serious cases of influenza. Multi-gene expression vector can be used for e... Shikimic acid(SA) is the key synthetic material for the chemical synthesis of Oseltamivir, which is prescribed as the front-line treatment for serious cases of influenza. Multi-gene expression vector can be used for expressing the plurality of the genes in one plasmid, so it is widely applied to increase the yield of metabolites. In the present study, on the basis of a shikimate kinase genetic defect strain Escherichia coli BL21(?aro L/aro K, DE3), the key enzyme genes aro G, aro B, tkt A and aro E of SA pathway were co-expressed and compared systematically by constructing a series of multi-gene expression vectors. The results showed that different gene co-expression combinations(two, three or four genes) or gene orders had different effects on the production of SA. SA production of the recombinant BL21-GBAE reached to 886.38 mg·L^(-1), which was 17-fold(P < 0.05) of the parent strain BL21(?aro L/aro K, DE3). 展开更多
关键词 Shikimic acid Escherichia coli Multi-gene co-expression
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CO-EXPRESSION OF MACROPHAGE COLONY-STIMULATING FACTOR WITH ITS RECEPTOR IN HUMAN HEPATOMA CELLS AND ITS POTENTIAL ROLES 被引量:4
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作者 杨文清 吴克复 +4 位作者 宋玉华 赵明河 张陆松 宋乃国 张丽娜 《Chinese Journal of Cancer Research》 SCIE CAS CSCD 1999年第2期79-84,共6页
Objective: To investigate the potential role of macrophage colony-stimulating factor (M-CSF) and macrophage colony-stimulating factor receptor (M-CSF-R) on the growth of human hepatoma cells. Methods: Specimens of dif... Objective: To investigate the potential role of macrophage colony-stimulating factor (M-CSF) and macrophage colony-stimulating factor receptor (M-CSF-R) on the growth of human hepatoma cells. Methods: Specimens of different origin, including tissues of human hepatocellular carcinoma (HCC), human fetal liver (FL) and normal liver (NL), the hepatoma cell lines, as well as the peripheral blood mononuclear cells (PBMC) from patients with HCC or liver metastatic tumor (LMT), were used to detect the expression levels of M-CSF and M-CSF-R by ABC immunohistochemistry staining and reverse transcription polymerase chain reaction methods the expression levels of M-CSF and M-CSF-R. Influence of monoclonal antibody against M-CSF (B5) or M-CSF-R (RE2) on proliferation ability of hepatoma cell linesin vitro was also studied. Results: The results showed that hepatoma tissues produced elevated levels of both M-CSF and M-CSF-R compared with those of fetal liver (P<0.001). The M-CSF/M-CSF-R expression levels of PBMC from hepatoma patients were higher than those of LMT patients (P<0.01,P<0.05) and the normal people (P<0.001). The hepatoma cell lines showed strong positive for M-CSF and M-CSF-R production. Both B5 and RE2 displayed a dose-dependent inhibitory effect on the growth and proliferation of hepatoma cells. Conclusion: The study indicates a co-expression model for M-CSF-R in hepatoma cells, suggesting an involvement of M-CSF/M-CSF-R in growth signaling of those malignant cells. The M-CSF/M-CSF-R seems to function through an autonomy mechanism in human hepatoma. 展开更多
关键词 Macrophage colony-stimulating factor (M-CSF) Macrophage colony-stimulating factor receptor (M-CSF-R) HEPATOMA co-expression AUTOCRINE
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Combinatorial co-expression of xanthine dehydrogenase and chaperone XdhC from Acinetobacter baumannii and Rhodobacter capsulatus and their applications in decreasing purine content in food 被引量:2
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作者 Chenghua Wang Ran Zhang +3 位作者 Yu Sun You Wen Xiaoling Liu Xinhui Xing 《Food Science and Human Wellness》 SCIE CSCD 2023年第4期1343-1350,共8页
This study investigated the combinatorial expression of xanthine dehydrogenase(XDH)and chaperone XdhC from Acinetobacter baumannii and Rhodobacter capsulatus and their applications in decreasing purine content in the ... This study investigated the combinatorial expression of xanthine dehydrogenase(XDH)and chaperone XdhC from Acinetobacter baumannii and Rhodobacter capsulatus and their applications in decreasing purine content in the beer,beef and yeast.Naturally occurring xdhABC gene clusters of A.baumannii CICC 10254 and R.capsulatus CGMCC 1.3366 as well as two refactored clusters constructed by exchanging their xdhC genes were overexpressed in Escherichia coli and purified to near homogeneity.RcXDH chaperoned by AbXdhC showed nearly the same catalytic performance as that by RcXdhC,except for the decreased substrate affinity.While the AbXDH co-expressed with RcXdhC displayed enhanced acidic adaptation but weakened catalytic activity.All the XDHs degraded purines in beer,beef and yeast extract effectively,indicating potential applications in low-purine foods to prevent hyperuricemia and gout.The study also presents a method for exploiting the better chaperone XdhC and novel XDHs by functional complement activity using existing XdhCs such as RcXdhC. 展开更多
关键词 co-expression Low purine food Uric acid Xanthine dehydrogenase XdhC
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Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning 被引量:6
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作者 Xiaolu Li Ye Yang +3 位作者 Senming Xu Yuchang Gui Jianmin Chen Jianwen Xu 《Neural Regeneration Research》 SCIE CAS CSCD 2024年第12期2723-2734,共12页
Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is s... Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022). 展开更多
关键词 bioinformatics analysis BIOMARKER CIBERSORT GEO dataset LASSO miRNA-mRNA network RNA sequencing spinal cord injury SVM-RFE weighted gene co-expression network analysis
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Identification of a TSPY co-expression network associated with DNA hypomethylation and tumor gene expression in somatic cancers 被引量:2
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作者 Tatsuo Kido Yun-Fai Chris Lau 《Journal of Genetics and Genomics》 SCIE CAS CSCD 2016年第10期577-585,共9页
Testis specific protein Y-encoded(TSPY) is a Y-located proto-oncogene predominantly expressed in normal male germ cells and various types of germ cell tumor. Significantly, TSPY is frequently expressed in somatic ca... Testis specific protein Y-encoded(TSPY) is a Y-located proto-oncogene predominantly expressed in normal male germ cells and various types of germ cell tumor. Significantly, TSPY is frequently expressed in somatic cancers including liver cancer but not in adjacent normal tissues, suggesting that ectopic TSPY expression could be associated with oncogenesis in non-germ cell cancers. Various studies demonstrated that TSPY expression promotes growth and proliferation in cancer cells; however, its relationship to other oncogenic events in TSPY-positive cancers remains unknown. The present study seeks to correlate TSPY expression with other molecular features in clinical cancer samples, by analyses of RNA-seq transcriptome and DNA methylation data in the Cancer Genome Atlas(TCGA) database. A total of 53 genes,including oncogenic lineage protein 28 homolog B(LIN28B) gene and RNA-binding motif protein Y-linked(RBMY) gene, are identified to be consistently co-expressed with TSPY, and have been collectively designated as the TSPY co-expression network(TCN). TCN genes were simultaneously activated in subsets of liver hepatocellular carcinoma(30%) and lung adenocarcinoma(10%) regardless of pathological stage, but only minimally in other cancer types. Further analysis revealed that the DNA methylation level was globally lower in the TCN-active than TCN-silent cancers. The specific expression and methylation patterns of TCN genes suggest that they could be useful as biomarkers for the diagnosis,prognosis and clinical management of cancers, especially those for liver and lung cancers, associated with TSPY co-expression network genes. 展开更多
关键词 co-expression network DNA methylation Gene expression signature Cancer subclassification Y chromosome genes TSPY Cancer/testis antigens
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Predictive value of co-expression patterns of immune checkpoint molecules for clinical outcomes of hematological malignancies 被引量:1
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作者 Cunte Chen Yangqiu Li 《Chinese Journal of Cancer Research》 SCIE CAS CSCD 2023年第3期245-251,共7页
Co-expression of immune checkpoint(IC)molecules can exacerbate T cell exhaustion in patients with hematological malignancies(HMs)and contribute to the immune escape of tumor cells,which is related to poor clinical out... Co-expression of immune checkpoint(IC)molecules can exacerbate T cell exhaustion in patients with hematological malignancies(HMs)and contribute to the immune escape of tumor cells,which is related to poor clinical outcome.It is worth establishing and optimizing an ideal prediction model based on the co-expression patterns of IC molecules to evaluate the immune status of HM patients and predict their clinical outcome.In this perspective,we summarize the co-expression patterns of IC molecules and their importance as biomarkers that predict the prognosis of patients with different HMs,providing new insights for designing dual IC blockades(ICBs). 展开更多
关键词 Immune checkpoint T cell exhaustion co-expression pattern PROGNOSIS hematological malignancy
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