Identification of differentially expressed mRNAs as novel predictive biomarkers for gastric cancer diagnosis and prognosis

BACKGROUND Gastric cancer(GC)has a high mortality rate worldwide.Despite significant progress in GC diagnosis and treatment,the prognosis for affected patients still remains unfavorable.AIM To identify important candidate genes related to the development of GC and iden-tify potential pathogenic mechanisms through comprehensive bioinformatics analysis.METHODS The Gene Expression Omnibus database was used to obtain the GSE183136 dataset,which includes a total of 135 GC samples.The limma package in R software was employed to identify differentially expressed genes(DEGs).Thereafter,enrichment analyses of Gene Ontology(GO)terms and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways were performed for the gene modules using the clusterProfile package in R software.The protein-protein interaction(PPI)networks of target genes were constructed using STRING and visualized by Cytoscape software.The common hub genes that emerged in the cohort of DEGs that was retrieved from the GEPIA database were then screened using a Venn Diagram.The expression levels of these overlapping genes in stomach adenocarcinoma samples and non-tumor samples and their association with prognosis in GC patients were also obtained from the GEPIA database and Kaplan-Meier curves.Moreover,real-time quantitative polymerase chain reaction(RT-qPCR)and western blotting were performed to determine the mRNA and protein levels of glutamic-pyruvic transaminase(GPT)in GC and normal immortalized cell lines.In addition,cell viability,cell cycle distribution,migration and invasion were evaluated by cell counting kit-8,flow cytometry and transwell assays.Furthermore,we also conducted a retrospective analysis on 70 GC patients diagnosed and surgically treated in Wenzhou Central Hospital,Dingli Clinical College of Wenzhou Medical University,The Second Affiliated Hospital of Shanghai University between January 2017 to December 2020.The tumor and adjacent normal samples were collected from the patients to determine the potential association between the expression level of GPT and the clinical as well as pathological features of GC patients.RESULTS We selected 19214 genes from the GSE183136 dataset,among which there were 250 downregulated genes and 401 upregulated genes in the tumor samples of stage III-IV in comparison to those in tumor samples of stage I-II with a P-value<0.05.In addition,GO and KEGG results revealed that the various upregulated DEGs were mainly enriched in plasma membrane and neuroactive ligand-receptor interaction,whereas the downregulated DEGs were primarily enriched in cytosol and pancreatic secretion,vascular smooth muscle contraction and biosynthesis of the different cofactors.Furthermore,PPI networks were constructed based on the various upregulated and downregulated genes,and there were a total 15 upregulated and 10 downregulated hub genes.After a comprehensive analysis,several hub genes,including runt-related transcription factor 2(RUNX2),salmonella pathogenicity island 1(SPI1),lysyl oxidase(LOX),fibrillin 1(FBN1)and GPT,displayed prognostic values.Interestingly,it was observed that GPT was downregulated in GC cells and its upregulation could suppress the malignant phenotypes of GC cells.Furthermore,the expression level of GPT was found to be associated with age,lymph node metastasis,pathological staging and distant metastasis(P<0.05).CONCLUSION RUNX2,SPI1,LOX,FBN1 and GPT were identified key hub genes in GC by bioinformatics analysis.GPT was significantly associated with the prognosis of GC,and its upregulation can effectively inhibit the proliferative,migrative and invasive capabilities of GC cells.

Decoding exercise-induced atomic components and prognostic shifts in endometrial carcinoma through differentially expressed genes

Background:This study aimed to portray the atomic intelligence and prognostic implications of differentially expressed genes and their involvement in biological pathways in endometrial carcinoma,with a specific focus on the impacts of exercise on cancer.Methods:We utilized a multi-faceted approach,including volcano plots,Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses,Venn diagrams,protein-protein interaction networks,Kaplan-Meier survival analysis,Gene Set Variety Analysis,and single-cell transcriptomic analysis.Furthermore,we profiled tumor mutational scenes,assessed the prognostic value of immune-related features,and conducted a comprehensive examination of genetic variations and their impact on tumor mutational burden across different cancer types.Multidimensional genomic interactions and methylation elements were also investigated.Using real-time quantitative PCR and immunofluorescence staining,the effects of B-cell lymphoma 2(BCL2)silencing on TNF-αand caspase-3 gene expression were evaluated.Results:Our study identified a noteworthy number of differentially expressed genes in endometrial carcinoma with potential links to athletic performance traits.BCL2 expression levels were found to be associated with survival outcomes,and its changeability across cancers was related to immune cell infiltration and immune checkpoint gene expression.Single-cell investigations uncovered cellular complexity within tumor microenvironments and critical biological pathways in BCL2-overexpressing cells.The expression flow and mutational effect of BCL2 in endometrial carcinoma were characterized,and the prognostic implications of immune-related features were assessed.Hereditary variations,including copy number variations and their relationship with gene expression and tumor mutational burden,were investigated.Multidimensional genomic transaction highlighted the essential role of regulatory genes in cancer pathogenesis.Silencing of the BCL2 gene significantly inhibited the proliferation of HEC-108 cells and promoted apoptosis,as evidenced by decreased TNF-αgene expression and increased caspase-3 gene expression.Immunofluorescence staining further confirmed these results.Conclusion:This study gives a point-by-point understanding of the atomic intelligence and prognostic implications in endometrial carcinoma and across various other cancers.BCL2’s role as a modulatory factor within the tumor-resistant environment and its potential impact on disease prognosis and response to immunotherapy were underscored.The multidimensional genomic analysis provides insights into the complex interaction between genetic and epigenetic variables in cancer,which may shed light on future therapeutic strategies.This study indicates that silencing the BCL2 gene can significantly inhibit tumor cell proliferation and promote apoptosis through the regulation of the TNF-αand caspase-3 pathways.

Differentially Private Support Vector Machines with Knowledge Aggregation

With the widespread data collection and processing,privacy-preserving machine learning has become increasingly important in addressing privacy risks related to individuals.Support vector machine(SVM)is one of the most elementary learning models of machine learning.Privacy issues surrounding SVM classifier training have attracted increasing attention.In this paper,we investigate Differential Privacy-compliant Federated Machine Learning with Dimensionality Reduction,called FedDPDR-DPML,which greatly improves data utility while providing strong privacy guarantees.Considering in distributed learning scenarios,multiple participants usually hold unbalanced or small amounts of data.Therefore,FedDPDR-DPML enables multiple participants to collaboratively learn a global model based on weighted model averaging and knowledge aggregation and then the server distributes the global model to each participant to improve local data utility.Aiming at high-dimensional data,we adopt differential privacy in both the principal component analysis(PCA)-based dimensionality reduction phase and SVM classifiers training phase,which improves model accuracy while achieving strict differential privacy protection.Besides,we train Differential privacy(DP)-compliant SVM classifiers by adding noise to the objective function itself,thus leading to better data utility.Extensive experiments on three high-dimensional datasets demonstrate that FedDPDR-DPML can achieve high accuracy while ensuring strong privacy protection.

Differentially private SGD with random features

In the realm of large-scale machine learning,it is crucial to explore methods for reducing computational complexity and memory demands while maintaining generalization performance.Additionally,since the collected data may contain some sensitive information,it is also of great significance to study privacy-preserving machine learning algorithms.This paper focuses on the performance of the differentially private stochastic gradient descent(SGD)algorithm based on random features.To begin,the algorithm maps the original data into a lowdimensional space,thereby avoiding the traditional kernel method for large-scale data storage requirement.Subsequently,the algorithm iteratively optimizes parameters using the stochastic gradient descent approach.Lastly,the output perturbation mechanism is employed to introduce random noise,ensuring algorithmic privacy.We prove that the proposed algorithm satisfies the differential privacy while achieving fast convergence rates under some mild conditions.

Improving the utility of locally differentially private protocols for longitudinal and multidimensional frequency estimates

This paper investigates the problem of collecting multidimensional data throughout time(i.e.,longitudinal studies)for the fundamental task of frequency estimation under Local Differential Privacy(LDP)guarantees.Contrary to frequency estimation of a single attribute,the multidimensional aspect demands particular attention to the privacy budget.Besides,when collecting user statistics longitudinally,privacy progressively degrades.Indeed,the“multiple”settings in combination(i.e.,many attributes and several collections throughout time)impose several challenges,for which this paper proposes the first solution for frequency estimates under LDP.To tackle these issues,we extend the analysis of three state-of-the-art LDP protocols(Generalized Randomized Response–GRR,Optimized Unary Encoding–OUE,and Symmetric Unary Encoding–SUE)for both longitudinal and multidimensional data collections.While the known literature uses OUE and SUE for two rounds of sanitization(a.k.a.memoization),i.e.,L-OUE and L-SUE,respectively,we analytically and experimentally show that starting with OUE and then with SUE provides higher data utility(i.e.,L-OSUE).Also,for attributes with small domain sizes,we propose Longitudinal GRR(L-GRR),which provides higher utility than the other protocols based on unary encoding.Last,we also propose a new solution named Adaptive LDP for LOngitudinal and Multidimensional FREquency Estimates(ALLOMFREE),which randomly samples a single attribute to be sent with the whole privacy budget and adaptively selects the optimal protocol,i.e.,either L-GRR or L-OSUE.As shown in the results,ALLOMFREE consistently and considerably outperforms the state-of-the-art L-SUE and L-OUE protocols in the quality of the frequency estimates.

Analysis of differentially expressed genes in Verruca vulgaris vs.adjacent normal skin by RNA-sequencing

Introduction:Verruca vulgaris is one of the most common low-risk HPV infections and is characterized by excessive proliferation of keratinocytes.Currently,very little genetic information is available regarding verruca vulgaris in the Chinese population.This study aimed to obtain comprehensive transcript information of verruca vulgaris by RNA sequencing.Methods:High-throughput sequencing was performed on three fresh verruca vulgaris samples and adjacent normal skin on the Illumina sequencing platform.The transcriptomes were analyzed using bioinformatics and the differentially expressed genes(DEGs)were verified by immunohistochemistry.Verruca vulgaris exhibited a unique molecular signature.Results:In total,1,643 DEGs were identified in verruca vulgaris compared to normal skin.The functions of the DEGs were studies by Gene Ontology(GO)enrichment,Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis,DEGs Reactome analysis,disease annotation function,and STRING protein-protein interaction(PPI)network analysis.The results revealed 595 GO terms associated with the cell cycle,signal transduction,immune system,signaling molecules,and interaction.The Reactome analysis revealed enrichment in reversible hydration of carbon dioxide and BMP signaling,while the disease annotation function revealed that the enriched DEGs are involved in keratosis disorders.The STRING PPI network showed that the edges with the highest density mainly included the 2′-5′oligoadenylate synthase(OAS)family-related proteins.Furthermore,the M-code analysis found ISG15,IRF7,and OASL were scored as significant modules and their high expression compared to the control was verified by immunohistochemistry.Conclusion:These findings contribute to the genetic information of verruca vulgaris in the Chinese population,revealing that interferon-stimulated genes may play essential roles in verruca vulgaris.

Analysis of differentially expressed genes related to cerebral ischaemia in young rats based on the Gene Expression Omnibus database

BACKGROUND The incidence rate of cerebral infarction in young people is increasing day by day,the age of onset tends to be younger,and its internal pathogenesis and mechanism are very complicated,which leads to greater difficulties in treatment.Therefore,it is essential to analyze the key pathway that affects the onset of cerebral infarction in young people from the perspective of genetics.AIM To compare the differentially expressed genes in the brain tissue of young and aged rats with middle cerebral artery occlusion and to analyse their effect on the key signalling pathway involved in the development of cerebral ischaemia in young rats.METHODS The Gene Expression Omnibus 2R online analysis tool was used to analyse the differentially expressed genes in the GSE166162 dataset regarding the development of cerebral ischaemia in young and aged groups of rats.DAVID 6.8 software was further used to filter the differentially expressed genes.These genes were subjected to Gene Ontology(GO)function analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis to determine the key gene pathway that affects the occurrence of cerebral ischaemia in young rats.RESULTS Thirty-five differentially expressed genes(such as Igf2,Col1a2,and Sfrp1)were obtained;73 GO enrichment analysis pathways are mainly involved in biological processes such as drug response,amino acid stimulation response,blood vessel development,various signalling pathways,and enzyme regulation.They are involved in molecular functions such as drug binding,protein binding,dopamine binding,metal ion binding,and dopamine neurotransmitter receptor activity.KEGG pathway enrichment analysis showed a significantly enriched pathway:The cyclic adenosine monophosphate(c-AMP)signalling pathway.CONCLUSION The c-AMP signalling pathway might be the key pathway in the intervention of cerebral infarction in young people.

Analysis of Growth Characteristics and Differentially Expressed Homologous Genes in Rhodobacter sphaeroides under Normal and Simulated Microgravity Conditions

The term “microgravity” is used to describe the “weightlessness” or “zero-g” circumstances that can only be found in space beyond earth’s atmosphere. Rhodobacter sphaeroides is a gram-negative purple phototroph, used as a model organism for this study due to its genomic complexity and metabolic versatility. Its genome has been completely sequenced, and profiles of the differential gene expression under aerobic, semi-aerobic, and photosynthetic conditions were examined. In this study, we hypothesized that R. sphaeroides will show altered growth characteristics, morphological properties, and gene expression patterns when grown under simulated microgravity. To test that, we measured the optical density and colony-forming units of cell cultures grown under both microgravity and normal gravity conditions. Differences in the cell morphology were observed using scanning electron microscopy (SEM) images by measuring the length and the surface area of the cells under both conditions. Furthermore, we also identified homologous genes of R. spheroides using the differential gene expression study of Acidovorax under microgravity in our laboratory. Growth kinetics results showed that R. sphaeroides cells grown under microgravity experience a shorter log phase and early stationary phase compared to the cells growing under normal gravity conditions. The length and surface area of the cells under microgravity were significantly higher confirming that bacterial cells experience altered morphological features when grown under microgravity conditions. Differentially expressed homologous gene analysis indicated that genes coding for several COG and GO functions, such as metabolism, signal-transduction, transcription, translation, chemotaxis, and cell motility are differentially expressed to adapt and survive microgravity.

A 2GHz Low Power Differentially Tuned CMOS Monolithic LC-VCO

A 2GHz differentially tuned CMOS monolithic LC-VCO is designed and fabricated in a 0.18μm CMOS process. The VCO has a 16.15% tuning range （from 1. 8998 to 2. 2335GHz） through a combination of analog and digital tuning techniques （4-bit binary switch-capacitor array）. The measured phase noise is - 118.17dBc/Hz at a 1MHz offset from a 2. 158GHz carrier. With the presented improved switch,the phase noise varies no more than 3dB at different digital control bits. The phase noise changes only by about 2dB in the tuning range because of the pn-junctions as the varactors. The VCO draws a current of about 2. lmA from a 1.8V power supply and works normally with a 1.5V power supply.

Separation and Identification of Differentially Expressed Proteins in Pistillate Flowers between Different Mulberry Cultivars

[Objective] This study aimed to explore the proteins related to pistillate flower development in different mulberry cultivars. [Method] The total proteins of the pistillate flowers of two mulberry cultivars Dal0 （Morus atropurpurea Roxb.） and SG01 （Morus muIticaulis Perr.） were extracted, separated and detected through two- dimensional electrophoresis （2-DE） and mass spectrometry. [Result] There was sig- nificant difference in the expression of proteins from the pistillate flowers of different mulberry cultivars. From the 2-DE images of Dal0 and SG01, 445_＋17 and 425_＋12 protein spots were respectively detected. The expression levels of 75 protein spots differed significantly. Thirteen spots those were expressed at high levels and well separated were analyzed by mass spectrometry, and nine of them were identified successfully. The nine proteins are involved in the glycometabolism, protein and amino acid metabolism and defense responses during the development of mulberry pistillate flower after they were pollinated. [Conclusion] The findings will provide reference for further study on the molecular mechanism of mulberry pistillate flower de- velopment.

Transcriptome analysis reveals key differentially expressed genes involved in wheat grain development

Wheat seed development is an important physiological process of seed maturation and directly affects wheat yield and quality. In this study, we performed dynamic transcriptome microarray analysis of an elite Chinese bread wheat cultivar(Jimai 20) during grain development using the Gene Chip Wheat Genome Array. Grain morphology and scanning electron microscope observations showed that the period of 11–15 days post-anthesis(DPA) was a key stage for the synthesis and accumulation of seed starch. Genome-wide transcriptional profiling and significance analysis of microarrays revealed that the period from 11 to 15 DPA was more important than the 15–20 DPA stage for the synthesis and accumulation of nutritive reserves.Series test of cluster analysis of differential genes revealed five statistically significant gene expression profiles. Gene ontology annotation and enrichment analysis gave further information about differentially expressed genes, and Map Man analysis revealed expression changes within functional groups during seed development. Metabolic pathway network analysis showed that major and minor metabolic pathways regulate one another to ensure regular seed development and nutritive reserve accumulation. We performed gene co-expression network analysis to identify genes that play vital roles in seed development and identified several key genes involved in important metabolic pathways. The transcriptional expression of eight key genes involved in starch and protein synthesis and stress defense was further validated by q RT-PCR. Our results provide new insight into the molecular mechanisms of wheat seed development and the determinants of yield and quality.

Identification of differentially expressed genes regulated by methylation in colon cancer based on bioinformatics analysis

BACKGROUND DNA methylation, acknowledged as a key modification in the field of epigenetics, regulates gene expression at the transcriptional level. Aberrant methylation in DNA regulatory regions could upregulate oncogenes and downregulate tumor suppressor genes without changing the sequences.However, studies of methylation in the control of gene expression are still inadequate. In the present research, we performed bioinformatics analysis to clarify the function of methylation and supply candidate methylation-related biomarkers and drivers for colon cancer.AIM To identify and analyze methylation-regulated differentially expressed genes(MeDEGs) in colon cancer by bioinformatics analysis.METHODS We downloaded RNA expression profiles, Illumina Human Methylation 450 K BeadChip data, and clinical data of colon cancer from The Cancer Genome Atlas project. MeDEGs were identified by analyzing the gene expression and methylation levels using the edgeR and limma package in R software. Gene ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses were performed in the DAVID database and KEGG Orthology-Based Annotation System 3.0, respectively. We then conducted Kaplan–Meier survival analysis to explore the relationship between methylation and expression and prognosis. Gene set enrichment analysis(GSEA) and investigation of protein-protein interactions(PPI) were performed to clarify the function of prognosis-related genes.RESULTS A total of 5 up-regulated and 81 down-regulated genes were identified asMeDEGs. GO and KEGG pathway analyses indicated that MeDEGs were enriched in multiple cancer-related terms. Furthermore, Kaplan–Meier survival analysis showed that the prognosis was negatively associated with the methylation status of glial cell-derived neurotrophic factor(GDNF) and reelin(RELN). In PPI networks, GDNF and RELN interact with neural cell adhesion molecule 1. Besides, GDNF can interact with GDNF family receptor alpha(GFRA1), GFRA2, GFRA3, and RET. RELN can interact with RAFAH1 B1,disabled homolog 1, very low-density lipoprotein receptor, lipoprotein receptorrelated protein 8, and NMDA 2 B. Based on GSEA, hypermethylation of GDNF and RELN were both significantly associated with pathways including "RNA degradation," "ribosome," "mismatch repair," "cell cycle" and "base excision repair."CONCLUSION Aberrant DNA methylation plays an important role in colon cancer progression.MeDEGs that are associated with the overall survival of patients may be potential targets in tumor diagnosis and treatment.

AFF1 and AFF4 differentially regulate the osteogenic differentiation of human MSCs

AFF1 and AFF4 belong to the AFF （AF4/FMR2） family of proteins, which function as scaffolding proteins linking two different transcription elongation factors, positive elongation factor b （P-TEFb） and ELL1/2, in super elongation complexes （SECs）. Both AFF1 and AFF4 regulate gene transcription through elongation and chromatln remodeling. However, their function in the osteogenic differentiation of mesenchymal stem cells （MSCs） is unknown. In this study, we show that small interfering RNA （siRNA）-mediated depletion of AFF1 in human MSCs leads to increased alkaline phosphatase （ALP） activity, enhanced mineralization and upregulated expression of osteogenic-related genes. On the contrary, depletion of AFF4 significantly inhibits the osteogenic potential of MSCs. In addition, we confirm that overexpression of AFF1 and AFF4 differentially affects osteogenic differentiation in vitro and MSC-mediated bone formation in vivo. Mechanistically, we find that AFFI regulates the expression of DKK1 via binding to its promoter region. Depletion of DKK1 in HA-AFFl-overexpressing MSCs abrogates the impairment of osteogenic differentiation. Moreover, we detect that AFF4 is enriched in the promoter region of ID1. AFF4 knockdown blunts the BRE luciferase activity, SP7 expression and ALP activity induced by BMP2 treatment. In conclusion, our data indicate that AFF1 and AFF4 differentially regulate the osteogenic differentiation of human MSCs.AFF1 and AFF4 belong to the AFF （AF4/FMR2） family of proteins, which function as scaffolding proteins linking two different transcription elongation factors, positive elongation factor b （P-TEFb） and ELL1/2, in super elongation complexes （SECs）. Both AFFI and AFF4 regulate gene transcription through elongation and chromatln remodeling. However, their function in the osteogenic differentiation of mesenchymal stem cells （MSCs） is unknown. In this study, we show that small interfering RNA （siRNA）-mediated depletion of AFF1 in human MSCs leads to increased alkaline phosphatase （ALP） activity, enhanced mineralization and upregulated expression of osteogenic-related genes. On the contrary, depletion of AFF4 significantly inhibits the osteogenic potential of MSCs. In addition, we confirm that overexpression of AFF1 and AFF4 differentially affects osteogenic differentiation in vitro and MSC-mediated bone formation in vivo. Mechanistically, we find that AFFI regulates the expression of DKK1 via binding to its promoter region. Depletion of DKK1 in HA-AFFl-overexpressing MSCs abrogates the impairment of osteogenic differentiation. Moreover, we detect that AFF4 is enriched in the promoter region of ID1. AFF4 knockdown blunts the BRE luciferase activity, SP7 expression and ALP activity induced by BMP2 treatment. In conclusion, our data indicate that AFF1 and AFF4 differentially regulate the osteogenic differentiation of human MSCs.

Effects of Mycobacterium vaccae vaccine in a mouse model of tuberculosis: protective action and differentially expressed genes

Background:Tuberculosis is a leading cause of death worldwide.BCG is an effective vaccine,but not widely used in many parts of the world due to a variety of issues.Mycobacterium vaccae(M.vaccae)is another vaccine used in human subjects to prevent tuberculosis.In the current study,we investigated the potential mechanisms of M.vaccae vaccination by determining differentially expressed genes in mice infected with M.tuberculosis before and after M.vaccae vaccination.Methods:Three days after exposure to M.tuberculosis H37 Rv strain(5×10~5 CFU),adult BALB/c mice randomly received either M.vaccae vaccine(22.5μg)or vehicle via intramuscular injection(n=8).Booster immunization was conducted 14 and 28 days after the primary immunization.Differentially expressed genes were identified by microarray followed by standard bioinformatics analysis.Results:M.vaccae vaccination provided protection against M.tuberculosis infection(most prominent in the lungs).We identified 2,326 upregulated and 2,221 downregulated genes in vaccinated mice.These changes could be mapped to a total of 123 signaling pathways(68 upregulated and 55 downregulated).Further analysis pinpointed to the MyD88-dependent TLR signaling pathway and PI3 K-Akt signaling pathway as most likely to be functional.Conclusions:M.vaccae vaccine provided good protection in mice against M.tuberculosis infection,via a highly complex set of molecular changes.Our findings may provide clue to guide development of more effective vaccine against tuberculosis.

Comparative transcriptome analysis identifies differentially expressed genes between normal and late-blooming Siberian apricot

Blooming date is an important trait in fruit tree species.Although several quantitative trait loci confirming blooming date were identified in Prunus spp.,the molecular mechanism underlying it remains unclear.Arising from this,the transcriptomes of normal blooming and lateblooming Siberian apricot(P.sibirica L.)flower buds were analyzed using RNA-seq technology.A total of 68,855 unigenes were de novo assembled,among which 1204 were differentially expressed between normal and late blooming.Gene ontology enrichment analysis revealed that biological processes were enriched with metabolic processes.The catalytic-related gene transcripts between the two types of blooming were significantly changed in the molecular function.Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that 156 genes were successfully annotated and 75 pathways enriched.Genes for gibberellin biosynthesis were up-regulated in normal blooming,whereas abscisic acid degradation-related genes were also up-regulated in normal blooming.Moreover,circadian rhythms related genes including EARLY FLOWERING 4,LATE ELONGATED HYPOCOTYL and CIRCANDIAN CLOCK ASSOCIATED1 were all up-regulated in normal blooming,indicating that circadian rhythms have a very important role in controlling blooming date.Furthermore,zinc finger protein CONSTANS-LIKE 12 was blasted onto the quantitative trait loci region on linkage group 4 in peach.However,changes in the abundance of key flowering genes such as SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1,FLOWERING LOCU T,LEAFY and FLOWERING LOCUS C were not significantly different,indicating that further investigation should explore the function of these genes on blooming date.The outcomes of this study will provide a valuable platform for further research on the molecular mechanism of blooming date in Prunus.

Event-Triggered Differentially Private Average Consensus for Multi-agent Network

This paper investigates the differentially private problem of the average consensus for a class of discrete-time multi-agent network systems(MANSs). Based on the MANSs,a new distributed differentially private consensus algorithm(DPCA) is developed. To avoid continuous communication between neighboring agents, a kind of intermittent communication strategy depending on an event-triggered function is established in our DPCA. Based on our algorithm, we carry out the detailed analysis including its convergence, its accuracy, its privacy and the trade-off between the accuracy and the privacy level, respectively. It is found that our algorithm preserves the privacy of initial states of all agents in the whole process of consensus computation. The trade-off motivates us to find the best achievable accuracy of our algorithm under the free parameters and the fixed privacy level. Finally, numerical experiment results testify the validity of our theoretical analysis.

Bioinformatics analyses of differentially expressed genes associated with spinal cord injury:a microarray-based analysis in a mouse model

Gene spectrum analysis has shown that gene expression and signaling pathways change dramatically after spinal cord injury,which may affect the microenvironment of the damaged site.Microarray analysis provides a new opportunity for investigating diagnosis,treatment,and prognosis of spinal cord injury.However,differentially expressed genes are not consistent among studies,and many key genes and signaling pathways have not yet been accurately studied.GSE5296 was retrieved from the Gene Expression Omnibus DataSet.Differentially expressed genes were obtained using R/Bioconductor software(expression changed at least two-fold;P < 0.05).Database for Annotation,Visualization and Integrated Discovery was used for functional annotation of differentially expressed genes and Animal Transcription Factor Database for predicting potential transcription factors.The resulting transcription regulatory protein interaction network was mapped to screen representative genes and investigate their diagnostic and therapeutic value for disease.In total,this study identified 109 genes that were upregulated and 30 that were downregulated at 0.5,4,and 24 hours,and 3,7,and 28 days after spinal cord injury.The number of downregulated genes was smaller than the number of upregulated genes at each time point.Database for Annotation,Visualization and Integrated Discovery analysis found that many inflammation-related pathways were upregulated in injured spinal cord.Additionally,expression levels of these inflammation-related genes were maintained for at least 28 days.Moreover,399 regulation modes and 77 nodes were shown in the protein-protein interaction network of upregulated differentially expressed genes.Among the 10 upregulated differentially expressed genes with the highest degrees of distribution,six genes were transcription factors.Among these transcription factors,ATF3 showed the greatest change.ATF3 was upregulated within 30 minutes,and its expression levels remained high at28 days after spinal cord injury.These key genes screened by bioinformatics tools can be used as biological markers to diagnose diseases and provide a reference for identifying therapeutic targets.

Identification of Differentially Expressed Genes Associated with Cotton Fiber Development in a Chromosomal Substitution Line(CS-B22sh)

One of the impediments in the genetic improvement of cotton fiber is the paucity of information about genes associated with fiber development.Availability of chromosome arm substitution line CS-

Identification of Differentially Expressed Genes in Sweetpotato Storage Roots Between Kokei No.14 and Its Mutant Nongdafu 14 Using PCR-Based cDNA Subtraction

The contents of earotenoids in the storage root of sweetpotato, Ipomoea batatas （L.） Lam. vary dramatically among different cultivars. However, so far little is known about the regulation of carotenoids synthesis in sweetpotato. In our laboratory, we identified a novel sweetpotato mutant, Nongdafu 14, which is a homogenous mutant derived from the wild type Kokei No. 14. The contents of carotenoids in the storage root of Nongdafu 14 were analyzed using high performance liquid chromatography （HPLC）, and it was found that the amount of carotenoids, [3-carotene, lutein and zeaxantion, three major types of earotenoids in sweetpotato storage roots, increased 2-26 folds in Nongdafu 14 compared to Kokei No. 14. Suppression subtractive hybridization （SSH） was used to identify genes that were differentially expressed in Nongdafu 14, and a differentially expressed eDNA library was constructed using the eDNA of Nongdafu 14 storage roots as tester and that of Kokei No. 14 storage roots as driver. Out of the 1 530 clones sequenced, we identified 292 nonredundant ESTs. GO and KEGG analyses of these differentially expressed ESTs indicated that diverse metabolism pathways were affected and candidate genes involved in regulation of carotenoids synthesis are suggested.

Differentially Expressed Proteins in Rat Hippocampus after Chronic Immobilization Stress and Intervention Using Xiao Yao San Decoction

Objective To identify differentially expressed proteins in the hippocampus of rats after chronic immobilization stress(CIS)using a proteomics approach,and to study the effect of the Xiao Yao San(XYS)decoction on differentially expressed proteins.Methods Twenty-four Sprague Dawley rats were randomly assigned to one of four groups of equal body weight:control(non-stress),7-day stress,21-day stress and21-day stress+XYS treatment groups.Two-dimensional gel electrophoresis(2-DE)was used to detect differences in protein expression in rat hippocampus.One differentially expressed protein was measured and verified by western blotting.Results Seventeen proteins showed differential expression.Among these,eight could be identified:glial fibrillary acidic protein-2(GFAP-2),tubulin alpha-1c,cytoplasmic muscle actin2,14-3-3protein,β-2a tubulin,phosphatidylethanolamine binding protein,synucleinαsyn3,and a low molecular weight(18kD)protein.Six of these proteins exhibited increased expression,one showed decreased expression,and the other protein,which comprised five subtypes,were either increased or decreased.These proteins are known to be involved in immunity,signal transduction,cell cycle control,apoptosis,regulation of enzyme activity,cytoskeleton structure,and synaptic plasticity.GFAP-2was further analyzed,and its differential expression confirmed by western blotting.Conclusion Some proteins are differentially expressed in the hippocampus of rats under chronic stress.The biological functions of these differentially expressed proteins are varied.Finally,the XYS decoction can significantly up-or down-regulate these protein expression levels.