Screen for stage-specific expression genes between tail bud stage and heartbeat beginning stage in embryogenesis of gynogenetic silver crucian carp

A systemic study was initiated to identify stage-specific expression genes in fish embryogenesis by using suppression subtractive hybridization (SSH) technique. In this study, we presented a preliminary result on screen for stage-specific expression genes between tail bud stage (TBS) and heartbeat beginning stage (HBS) in gynogenetic silver crucian carp (Carassius auratus gibelio). Two SSH plasmid libraries specific for TBS embryos and HBS embryos were constructed, and stage-specific expression genes were screened between the two stages. 1963 TBS positive clones and 2466 HBS positive clones were sampled to PCR amplification, and 1373 TBS and 1809 HBS PCR positive clones were selected to carry out dot blots. 169 TBS dot blot positive clones and 272 HBS dot blot positive clones were sequenced. Searching GenBank by using these nucleotide sequences indicated that most of the TBS dot blot positive clones could not be found homologous sequences in the database, while known genes were mainly detected from HBS dot blot positive clones. Of the 79 known genes, 20 were enzymes or kinases involved in important metabolism of embryonic development. Moreover, specific expressions of partial genes were further confirmed by virtual northern blots. This study is the first step for making a large attempt to study temporal and spatial control of gene expression in the gynogenetic fish embryogenesis.

Effects of antioxidant‑rich Lactiplantibacillus plantarum inoculated alfalfa silage on rumen fermentation, antioxidant and immunity status, and mammary gland gene expression in dairy goats

Background Milk synthesis in lactating animals demands high energy metabolism,which results in an increased production of reactive oxygen metabolites(ROM)causing an imbalance between oxidants and antioxidants thereby inducing oxidative stress(OS)on the animals.To mitigate OS and postpartum disorders in dairy goats and gain insight into the impact of dietary choices on redox status during lactation,a feeding trial was conducted using alfalfa silage inoculated with a high-antioxidant strain of Lactiplantibacillus plantarum.Methods Twenty-four Guanzhong dairy goats(38.1±1.20 kg)were randomly assigned to two dietary treatments:one containing silage inoculated with L.plantarum MTD/1(RSMTD-1),and the other containing silage inoculated with high antioxidant activity L.plantarum 24-7(ES24-7).Results ES24-7-inoculated silage exhibited better fermentation quality and antioxidant activity compared to RSMTD-1.The ES24-7 diet elevated the total antioxidant capacity(T-AOC),superoxide dismutase(SOD),glutathione peroxi-dase(GSH-Px),and catalase(CAT)activities in milk,serum,and feces of lactating goats(with the exception of T-AOC in milk).Additionally,the diet containing ES24-7 inoculated silage enhanced casein yield,milk free fatty acid(FFA)content,and vitamin A level in the goats’milk.Furthermore,an increase of immunoglobulin(Ig)A,IgG,IgM,inter-leukin(IL)-4,and IL-10 concentrations were observed,coupled with a reduction in IL-1β,IL-2,IL-6,interferon(IFN)-γ,and tumor necrosis factor(TNF)-αconcentrations in the serum of lactating goats fed ES24-7.Higher concentrations of total volatile fatty acid(VFA),acetate,and propionate were observed in the rumen fluid of dairy goats fed ES24-7 inoculated silage.Moreover,the diet containing ES24-7 inoculated silage significantly upregulated the expression of nuclear factor erythroid 2 like 2(NFE2L2),beta-carotene oxygenase 1(BCO1),SOD1,SOD2,SOD3,GPX2,CAT,glu-tathione-disulfide reductase(GSR),and heme oxygenase 1(HMOX1)genes in the mammary gland,while decreased the levels of NADPH oxidase 4(NOX4),TNF,and interferon gamma(IFNG).Conclusions These findings indicated that feeding L.plantarum 24-7 inoculated alfalfa silage not only improved rumen fermentation and milk quality in lactating dairy goats but also boosted their immunity and antioxidant status by modulating the expression of several genes related to antioxidant and inflammation in the mammary gland.

Effects of pyraclostrobin on growth,oxidative stress,and gene expression in relation to stress and ATP-binding cassette transporters in Tetrahymena thermophila

Pyraclostrobin(PYR),a widely used fungicide,has negative effects on fish and algae,but its toxicity in protozoa remains unclear.In this study,the effects of PYR on the growth,oxidative stress,and gene expression related to stress and ATP-binding cassette(ABC)transporters in Tetrahymena thermophila were investigated.The result showed that the 96-h IC_(50)of PYR against T.thermophila was 17.2 mg/L.Moreover,PYR inhibited the growth of T.thermophila in concentration-or time-dependent manner.A morphological study revealed that the shape and size of T.thermophila changed,and damage of cell membrane surface was observed by scanning electron microscopy after 96 h of PYR exposure.The activities of superoxide dismutase(SOD)and catalase(CAT)increased throughout the experiment.In contrast,the glutathione(GSH)content was increased at 24 h and 48 h of exposure and decreased at 96 h.Moreover,a significant increase in malondialdehyde(MDA)level was observed in T.thermophila after96 h of exposure.Furthermore,PYR upregulated the HSP703,HSP705,GPx2,and ABAC15 gene expression in the 0.1–5-mg/L groups and downregulated the HSP704,HSP90,TGR,and ABCC52 mRNA levels at 96 h of exposure.These results suggest that PYR may exert adverse effects on T.thermophila by inducing oxidative stress and changing the gene expression related to ABC transporters and stress,which may enrich the understanding of the toxicity mechanism of PYR in aquatic organisms and provide reference data for aquatic ecological risk assessments.

Genome-wide identification and expression profiling of photosystem II(PsbX)gene family in upland cotton(Gossypium hirsutum L.)

Background Photosystem II(PSII)constitutes an intricate assembly of protein pigments,featuring extrinsic and intrinsic polypeptides within the photosynthetic membrane.The low-molecular-weight transmembrane protein PsbX has been identified in PSII,which is associated with the oxygen-evolving complex.The expression of PsbX gene protein is regulated by light.PsbX’s central role involves the regulation of PSII,facilitating the binding of quinone molecules to the Qb(PsbA)site,and it additionally plays a crucial role in optimizing the efficiency of photosynthesis.Despite these insights,a comprehensive understanding of the PsbX gene’s functions has remained elusive.Results In this study,we identified ten PsbX genes in Gossypium hirsutum L.The phylogenetic analysis results showed that 40 genes from nine species were classified into one clade.The resulting sequence logos exhibited substantial conservation across the N and C terminals at multiple sites among all Gossypium species.Furthermore,the ortholo-gous/paralogous,Ka/Ks ratio revealed that cotton PsbX genes subjected to positive as well as purifying selection pressure might lead to limited divergence,which resulted in the whole genome and segmental duplication.The expression patterns of GhPsbX genes exhibited variations across specific tissues,as indicated by the analysis.Moreover,the expression of GhPsbX genes could potentially be regulated in response to salt,intense light,and drought stresses.Therefore,GhPsbX genes may play a significant role in the modulation of photosynthesis under adverse abiotic conditions.Conclusion We examined the structure and function of PsbX gene family very first by using comparative genom-ics and systems biology approaches in cotton.It seems that PsbX gene family plays a vital role during the growth and development of cotton under stress conditions.Collectively,the results of this study provide basic information to unveil the molecular and physiological function of PsbX genes of cotton plants.

Decoding Retinoblastoma: Differential Gene Expression

Background: Retinoblastoma, the most common intraocular pediatric cancer, presents complexities in its genetic landscape that necessitate a deeper understanding for improved therapeutic interventions. This study leverages computational tools to dissect the differential gene expression profiles in retinoblastoma. Methods: Employing an in silico approach, we analyzed gene expression data from public repositories by applying rigorous statistical models, including limma and de seq 2, for identifying differentially expressed genes DEGs. Our findings were validated through cross-referencing with independent datasets and existing literature. We further employed functional annotation and pathway analysis to elucidate the biological significance of these DEGs. Results: Our computational analysis confirmed the dysregulation of key retinoblastoma-associated genes. In comparison to normal retinal tissue, RB1 exhibited a 2.5-fold increase in expression (adjusted p Conclusions: Our analysis reinforces the critical genetic alterations known in retinoblastoma and unveils new avenues for research into the disease’s molecular basis. The discovery of chemoresistance markers and immune-related genes opens potential pathways for personalized treatment strategies. The study’s outcomes emphasize the power of in silico analyses in unraveling complex cancer genomics.

A Novel Deep Learning-Based Model for Classification of Wheat Gene Expression

Deep learning(DL)plays a critical role in processing and converting data into knowledge and decisions.DL technologies have been applied in a variety of applications,including image,video,and genome sequence analysis.In deep learning the most widely utilized architecture is Convolutional Neural Networks(CNN)are taught discriminatory traits in a supervised environment.In comparison to other classic neural networks,CNN makes use of a limited number of artificial neurons,therefore it is ideal for the recognition and processing of wheat gene sequences.Wheat is an essential crop of cereals for people around the world.Wheat Genotypes identification has an impact on the possible development of many countries in the agricultural sector.In quantitative genetics prediction of genetic values is a central issue.Wheat is an allohexaploid(AABBDD)with three distinct genomes.The sizes of the wheat genome are quite large compared to many other kinds and the availability of a diversity of genetic knowledge and normal structure at breeding lines of wheat,Therefore,genome sequence approaches based on techniques of Artificial Intelligence(AI)are necessary.This paper focuses on using the Wheat genome sequence will assist wheat producers in making better use of their genetic resources and managing genetic variation in their breeding program,as well as propose a novel model based on deep learning for offering a fundamental overview of genomic prediction theory and current constraints.In this paper,the hyperparameters of the network are optimized in the CNN to decrease the requirement for manual search and enhance network performance using a new proposed model built on an optimization algorithm and Convolutional Neural Networks(CNN).

Effect of Chuanzhifang component (ZGC) on macrophage inflammatory injury based on whole gene expression profile

Objective: The effect of Chuanzhi Fang (ZGC) on the whole genome expression profile of RAW264.7 cells activated by lipopolysaccharide (LPS) was analyzed, and to explore the possible mechanism of action and core target of this formula on macrophage inflammatory injury at the overall level. Methods: A model of LPS-induced inflammation in RAW264.7 cells was constructed, and the effect of ZGC intervention on the genome-wide expression of inflammatory macrophages 3was examined by gene microarray technology, GO/KEGG enrichment analysis was performed for significantly differentially expressed genes among each group. Results: The results of genome-wide expression profiling microarray analysis showed that the ZGC intervention group upregulated the expression of 5 genes including C4bp and inhibited the expression of 22 genes including Mgat3, Psma6, and Siglecg relative to the LPS model group. KEGG signaling pathway analysis results showed that ZGC mainly acted through cytokine receptor interaction and the C-type lectin receptor signaling pathway. Conclusion: ZGC can interfere with the abnormal expression of 27 genes in inflammatory macrophages, and the related genes may exert corresponding anti-inflammatory effects by affecting cytokine receptor interactions, C-type lectin receptor signaling pathway, and TLR4/ NF-κB signaling pathway.

Establishment of a prognosis predictive model for liver cancer based on expression of genes involved in the ubiquitin-proteasome pathway

BACKGROUND The ubiquitin-proteasome pathway(UPP)has been proven to play important roles in cancer.AIM To investigate the prognostic significance of genes involved in the UPP and develop a predictive model for liver cancer based on the expression of these genes.METHODS In this study,UPP-related E1,E2,E3,deubiquitylating enzyme,and proteasome gene sets were obtained from the Kyoto Encyclopedia of Genes and Genomes(KEGG)database,aiming to screen the prognostic genes using univariate and multivariate regression analysis and develop a prognosis predictive model based RESULTS Five genes(including autophagy related 10,proteasome 20S subunit alpha 8,proteasome 20S subunit beta 2,ubiquitin specific peptidase 17 like family member 2,and ubiquitin specific peptidase 8)were proven significantly correlated with prognosis and used to develop a prognosis predictive model for liver cancer.Among training,validation,and Gene Expression Omnibus sets,the overall survival differed significantly between the high-risk and low-risk groups.The expression of the five genes was significantly associated with immunocyte infiltration,tumor stage,and postoperative recurrence.A total of 111 differentially expressed genes(DEGs)were identified between the high-risk and low-risk groups and they were enriched in 20 and 5 gene ontology and KEGG pathways.Cell division cycle 20,Kelch repeat and BTB domain containing 11,and DDB1 and CUL4 associated factor 4 like 2 were the DEGs in the E3 gene set that correlated with survival.CONCLUSION We have constructed a prognosis predictive model in patients with liver cancer,which contains five genes that associate with immunocyte infiltration,tumor stage,and postoperative recurrence.

Prediction of Lung Cancer Stage Using Tumor Gene Expression Data

Lung cancer remains a significant global health challenge and identifying lung cancer at an early stage is essential for enhancing patient outcomes. The study focuses on developing and optimizing gene expression-based models for classifying cancer types using machine learning techniques. By applying Log2 normalization to gene expression data and conducting Wilcoxon rank sum tests, the researchers employed various classifiers and Incremental Feature Selection (IFS) strategies. The study culminated in two optimized models using the XGBoost classifier, comprising 10 and 74 genes respectively. The 10-gene model, due to its simplicity, is proposed for easier clinical implementation, whereas the 74-gene model exhibited superior performance in terms of Specificity, AUC (Area Under the Curve), and Precision. These models were evaluated based on their sensitivity, AUC, and specificity, aiming to achieve high sensitivity and AUC while maintaining reasonable specificity.

The Influence of Aerial Exposure on Sea Anemones Aulactinia veratra Mucin Genes Expression Using the RNA Sequencing

Mucin genes are the main component of mucus. The sea anemone species, Aulactinia veratra (Phylum Cnidaria) contains different types of mucin genes. In the intertidal zone, A. veratra is found to be exposed to air during the low tide and produces large quantities of mucus as an external covering. The relation between low tide and mucus secretion is still unclear, and what is the role of mucin during arial exposure is not yet investigated. This study hypothesised that the mucin genes in A. veratra would have significantly high expression in response to aerial exposure. Therefore, the aim of current study was to examine and analyses the response of A. veratra mucins in response to an experiment involving three hours of aerial exposure. To achieve this, aim the RNA-sequencing and bioinformatics analyses were used to examine the expression profile of A. veratra mucin genes in response to aerial exposure. The generated results have shown that, Mucin4-like and mucin5B-like were up-regulated in response to the three hours of aerial exposure in A. veratra. This finding shows a significant role of mucin5B-like and mucin4-like genes in response to air stress at low tide. The data generated from this study could be used in conjunction with future mucin gene studies of sea anemones and other cnidarians to compare A. veratra mucin gene expression results across time, and to extend our understanding of mucin stress response in this phylum.

In Vivo Improvements in Facial Appearance and in Vitro Changes in Gene Expression Using a Topical Formulation Designed to Repair Environmentally Induced DNA Damage

Background: While sunscreen has been accepted as a mainline defence against photodamage from ultraviolet, visible light and near-infrared radiation, there appears to be a lack of research into photorepair. The concept of protecting the skin during the day and repairing cellular damage at night is intuitive, yet specific strategies revolving around combinations of proven reparative active ingredients remain unelucidated. Purpose: To investigate the efficacy of a solar repair Formulation following ultraviolet and environmental exposure in order to improve overall skin health and appearance through three hypotheses: The Formulation increases expression of DNA repair mechanisms markers;The Formulation enhances overall skin appearance through reducing signs of inflammation, elevating hydration, reinforcing skin firmness and amplifying radiance;In-Vivo efficacy test results are aligned with measured gene expression changes. Methods: The Formulation (#6NIC1.V1.1-1) was tested for: In-vitro LDH cytotoxicity activity, In-vitro qPCR gene expression with and without ultraviolet exposure on a reconstructed 3-dimensional skin model, and In-Vivo efficacy study on a panel of 22 participants objectively and subjectively. Results: Skin radiance, firmness, hydration, redness, and inflammation are significantly improved after In-Vivo skin exposure to the Formulation and environmental challenges such as ultraviolet radiation. These outcomes were confirmed by in-vitro genetic testing on a reconstructed human skin model. Conclusion: The studies allowed us to identify and group results in four main skin functions that were significantly enhanced following the application of the Formulation: firmness, hydration, radiance and soothing.

Genome-wide identification of TPS genes in sesame and analysis of their expression in response to abiotic stresses

Trehalose and its precursor,trehalose-6-phosphate,play critical roles in plant metabolism and response to abiotic stresses.Trehalose-6-phosphate synthase(TPS)is a key enzyme in the trehalose synthesis pathway.Hence this study identified TPS genes in sesame(SiTPSs)and examined their expression patterns under various abiotic stresses.Totally,ten SiTPSs were identified and comprehensively characterized.SiTPSs were found to be unevenly distributed on five out of 13 sesame chromosomes and were predicted to be localized in chloroplasts and vacuoles of cells.Phylogenetic analysis classified SiTPS proteins into two groups(I and II),which was supported by gene structure and conserved motif analyses.Analysis of cis-acting elements in promoter regions of SiTPSs revealed that they might primarily involve developmental and environmental responses.SiTPSs exhibited different expression patterns in different tissues and under different abiotic stresses.Most group II SiTPS genes(SiTPS4-SiTPS10)were strongly induced by drought,salt,waterlogging,and osmotic stress.Particularly,SiTPS10 was the most significantly up-regulated under various abiotic stresses,indicating it is a candidate gene for improving sesame tolerance to multiple abiotic stresses.Our results provide insight into the TPS gene family in sesame and fundamental resources for genomics studies towards dissecting SiTPS genes’functions.

Metabolomics and gene expression levels reveal the positive effects of teaseed oil on lifespan and aging process in Caenorhabditis elegans

As an irreplaceable dietary constituent,lipids play a vital important role in health,but their effects on aging process and longevity are still not well known yet.In this paper,the metabolic profiling and gene expression levels of Caenorhabditis elegans were investigated to explore the effects of different edible oils on senescence and lifespan.The results showed that teaseed oil(TO)could prolong the life expectancy and slow down the aging process of C.elegans.Compared to the control group,the intake of lard oil(LO)and TO increased the expression levels of genes related to inhibition of protein aggregation(akt-1,daf-16,hsf-1,hsp-16.2)and lipid metabolism(daf-7,daf-1,mdt-15,lipl-4,fat-5,fat-6,fat-7),with a more significant alteration in TO group.Metabolomics revealed that palm oil can upregulated plenty of fatty acids(palmitic acid,stearic acid,tetracosanoic acid),together with some amino acids(tryptophan,L-aspartate,L-valine)and carbohydrate(D-glucose),while the trend was opposite in TO group.Besides,moderate-to-strong correlations were found between differential metabolites and changed genes.In general,this paper claimed that TO could prolong lifespan and slow down aging process via regulating the lipids,amino acids and carbohydrates metabolism.

Identification of potential diagnostic and prognostic biomarkers for breast cancer based on gene expression omnibus

BACKGROUND Breast cancer is regarded as a highly malignant neoplasm in the female population,posing a significant risk to women’s overall well-being.The prevalence of breast cancer has been observed to rise in China,accompanied by an earlier age of onset when compared to Western countries.Breast cancer continues to be a prominent contributor to cancer-related mortality and morbidity among women,primarily due to its limited responsiveness to conventional treatment modalities.The diagnostic process is challenging due to the presence of non-specific clinical manifestations and the suboptimal precision of conventional diagnostic tests.There is a prevailing uncertainty regarding the most effective screening method and target populations,as well as the specificities and execution of screening programs.AIM To identify diagnostic and prognostic biomarkers for breast cancer.METHODS Overlapping differentially expressed genes were screened based on Gene Expression Omnibus(GSE36765,GSE10810,and GSE20086)and The Cancer Genome Atlas datasets.A protein-protein interaction network was applied to excavate the hub genes among these differentially expressed genes.Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses,as well as gene set enrichment analyses,were conducted to examine the functions of these genes and their potential mechanisms in the development of breast cancer.For clarification of the diagnostic and prognostic roles of these genes,Kaplan–Mei-er and Cox proportional hazards analyses were conducted.RESULTS This study demonstrated that calreticulin,heat shock protein family B member 1,insulin-like growth Factor 1,interleukin-1 receptor 1,Krüppel-like factor 4,suppressor of cytokine signaling 3,and triosephosphate isomerase 1 are potential diagnostic biomarkers of breast cancer as well as potential treatment targets with clinical implications.CONCLUSION The screening of biomarkers is of guiding significance for the diagnosis and prognosis of the diseases.

Insecticidal Potential of α-Pinene and β-Caryophyllene against Myzus persicae and Their Impacts on Gene Expression

Myzus persicae(M.persicae)is now considered a threat to agricultural crops due to economic losses.Numerous synthetic insecticides applied every year against M.persicae,are reported to be unsafe for environment,humans,and beneficial insects.Furthermore,several species of Myzus have been found to develop resistance due to over application of these insecticides.Therefore,it is required to find some novel insecticide that would be safe for the environment as well as for humans.In the current study,two major pure constituentsα-pinene andβ-caryophyllene were evaluated for their insecticidal potential against M.persicae using a fumigant toxicity assay.Furthermore,impact ofα-pinene andβ-caryophyllene on expression of five different genes,e.g.,HSP 60,FPPS I,OSD,TOL and ANT responsible for reproduction,dispersion,and growth of M.persicae has also been investigated.To perform fumigant toxicity assay,five different concentrations(3.5,4,4.5,5 and 6μL L−1)ofα-pinene andβ-caryophyllene were prepared.Lethal concentration(LC)was calculated,and gene expression studies were executed through qRT PCR at LC30 ofα-pinene andβ-caryophyllene.Both constituents demonstrated excellent fumigant toxicity effects against M.persicae at all five concentrations.However,α-pinene shows significantly better results(98%)as compared toβ-caryophyllene(80%)after 72 h at 6μL L−1 of dose.The highest upregulation in expression was demonstrated at LC30 dose ofα-pinene in five in three out of five genes understudy(TOL,ANT,and FPPS I).Conversely,two genes HSP 60 and OSD demonstrated downregulation at LC30 dose ofβ-caryophyllene.Conclusively,our results highlighted the promising insecticidal potential of both compoundsα-pinene andβ-caryophylleneby interfering with the reproduction and development related processes in M.persicae,allowing us to recommend the phytoconstituents under investigation as an ecofriendly alternative to synthetic insecticides.

A true triaxial strength criterion for rocks by gene expression programming

Rock strength is a crucial factor to consider when designing and constructing underground projects.This study utilizes a gene expression programming(GEP)algorithm-based model to predict the true triaxial strength of rocks,taking into account the influence of rock genesis on their mechanical behavior during the model building process.A true triaxial strength criterion based on the GEP model for igneous,metamorphic and magmatic rocks was obtained by training the model using collected data.Compared to the modified Weibols-Cook criterion,the modified Mohr-Coulomb criterion,and the modified Lade criterion,the strength criterion based on the GEP model exhibits superior prediction accuracy performance.The strength criterion based on the GEP model has better performance in R2,RMSE and MAPE for the data set used in this study.Furthermore,the strength criterion based on the GEP model shows greater stability in predicting the true triaxial strength of rocks across different types.Compared to the existing strength criterion based on the genetic programming(GP)model,the proposed criterion based on GEP model achieves more accurate predictions of the variation of true triaxial strength(s1)with intermediate principal stress(s2).Finally,based on the Sobol sensitivity analysis technique,the effects of the parameters of the three obtained strength criteria on the true triaxial strength of the rock are analysed.In general,the proposed strength criterion exhibits superior performance in terms of both accuracy and stability of prediction results.

Identification of hub genes associated with Helicobacter pylori infection and type 2 diabetes mellitus:A pilot bioinformatics study

BACKGROUND Helicobacter pylori(H.pylori)infection is related to various extragastric diseases including type 2 diabetes mellitus(T2DM).However,the possible mechanisms connecting H.pylori infection and T2DM remain unknown.AIM To explore potential molecular connections between H.pylori infection and T2DM.METHODS We extracted gene expression arrays from three online datasets(GSE60427,GSE27411 and GSE115601).Differentially expressed genes(DEGs)commonly present in patients with H.pylori infection and T2DM were identified.Hub genes were validated using human gastric biopsy samples.Correlations between hub genes and immune cell infiltration,miRNAs,and transcription factors(TFs)were further analyzed.RESULTS A total of 67 DEGs were commonly presented in patients with H.pylori infection and T2DM.Five significantly upregulated hub genes,including TLR4,ITGAM,C5AR1,FCER1G,and FCGR2A,were finally identified,all of which are closely related to immune cell infiltration.The gene-miRNA analysis detected 13 miRNAs with at least two gene cross-links.TF-gene interaction networks showed that TLR4 was coregulated by 26 TFs,the largest number of TFs among the 5 hub genes.CONCLUSION We identified five hub genes that may have molecular connections between H.pylori infection and T2DM.This study provides new insights into the pathogenesis of H.pylori-induced onset of T2DM.

Construction of an immune-related gene signature for overall survival prediction and immune infiltration in gastric cancer

BACKGROUND Treatment options for patients with gastric cancer(GC)continue to improve,but the overall prognosis is poor.The use of PD-1 inhibitors has also brought benefits to patients with advanced GC and has gradually become the new standard treatment option at present,and there is an urgent need to identify valuable biomarkers to classify patients with different characteristics into subgroups.AIM To determined the effects of differentially expressed immune-related genes(DEIRGs)on the development,prognosis,tumor microenvironment(TME),and treatment response among GC patients with the expectation of providing new biomarkers for personalized treatment of GC populations.METHODS Gene expression data and clinical pathologic information were downloaded from The Cancer Genome Atlas(TCGA),and immune-related genes(IRGs)were searched from ImmPort.DEIRGs were extracted from the intersection of the differentially-expressed genes(DEGs)and IRGs lists.The enrichment pathways of key genes were obtained by analyzing the Kyoto Encyclopedia of Genes and Genomes(KEGGs)and Gene Ontology(GO)databases.To identify genes associated with prognosis,a tumor risk score model based on DEIRGs was constructed using Least Absolute Shrinkage and Selection Operator and multivariate Cox regression.The tumor risk score was divided into high-and lowrisk groups.The entire cohort was randomly divided into a 2:1 training cohort and a test cohort for internal validation to assess the feasibility of the risk model.The infiltration of immune cells was obtained using‘CIBERSORT,’and the infiltration of immune subgroups in high-and low-risk groups was analyzed.The GC immune score data were obtained and the difference in immune scores between the two groups was analyzed.RESULTS We collected 412 GC and 36 adjacent tissue samples,and identified 3627 DEGs and 1311 IRGs.A total of 482 DEIRGs were obtained.GO analysis showed that DEIRGs were mainly distributed in immunoglobulin complexes,receptor ligand activity,and signaling receptor activators.KEGG pathway analysis showed that the top three DEIRGs enrichment types were cytokine-cytokine receptors,neuroactive ligand receptor interactions,and viral protein interactions.We ultimately obtained an immune-related signature based on 10 genes,including 9 risk genes(LCN1,LEAP2,TMSB15A mRNA,DEFB126,PI15,IGHD3-16,IGLV3-22,CGB5,and GLP2R)and 1 protective gene(LGR6).Kaplan-Meier survival analysis,receiver operating characteristic curve analysis,and risk curves confirmed that the risk model had good predictive ability.Multivariate COX analysis showed that age,stage,and risk score were independent prognostic factors for patients with GC.Meanwhile,patients in the low-risk group had higher tumor mutation burden and immunophenotype,which can be used to predict the immune checkpoint inhibitor response.Both cytotoxic T lymphocyte antigen4+and programmed death 1+patients with lower risk scores were more sensitive to immunotherapy.CONCLUSION In this study a new prognostic model consisting of 10 DEIRGs was constructed based on the TME.By providing risk factor analysis and prognostic information,our risk model can provide new directions for immunotherapy in GC patients.

Genome-wide identification and spatiotemporal expression profiling of zinc finger SWIM domain-containing protein family genes

The biological function of the novel zinc-finger SWIM domain-containing protein family(ZSWIM)during embryonic development remains elusive.Here,we conducted a genome-wide analysis to explore the evolutionary processes of the ZSWIM gene family members in mice,Xenopus tropicalis,zebrafish,and humans.We identified nine putative ZSWIM genes in the human and mouse genome,eight in the Xenopus genome,and five in the zebrafish genome.Based on multiple sequence alignment,three members,ZSWIM5,ZSWIM6,and ZSWIM8,demonstrated the highest homology across all four species.Using available RNA sequencing(RNAseq)data,ZSWIM genes were found to be widely expressed across different tissues,with distinct tissuespecific properties.To identify the functions of the ZSWIM protein family during embryogenesis,we examined temporal and spatial expression patterns of zswim family genes in Xenopus embryos.Quantitative real-time polymerase chain reaction(qRT-PCR)revealed that each member had a distinct expression profile.Whole-mount in situ hybridization showed that both zswim1 and zswim3 were maternally expressed genes;zswim5 and zswim6were expressed throughout embryogenesis and displayed dynamic expression in the brain,eyes,somite,and bronchial arch at the late tailbud stages;zswim7 was detected in the eye area;zswim8 showed a dynamic expression pattern during the tailbud stages,with expression detected in the brain,eyes,and somite;zswim9 was faintly expressed throughout embryonic development.This study provides a foundation for future research to delineate the functions of ZSWIM gene members.

Identification and expression analysis of sugar transporter family genes reveal the role of ZmSTP2 and ZmSTP20 in maize disease resistance

Sugar is an indispensable source of energy for plant growth and development, and it requires the participation of sugar transporter proteins(STPs) for crossing the hydrophobic barrier in plants. Here, we systematically identified the genes encoding sugar transporters in the genome of maize(Zea mays L.), analyzed their expression patterns under different conditions, and determined their functions in disease resistance. The results showed that the mazie sugar transporter family contained 24 members, all of which were predicted to be distributed on the cell membrane and had a highly conserved transmembrane transport domain. The tissue-specific expression of the maize sugar transporter genes was analyzed, and the expression level of these genes was found to be significantly different in different tissues. The analysis of biotic and abiotic stress data showed that the expression levels of the sugar transporter genes changed significantly under different stress factors. The expression levels of Zm STP2 and Zm STP20 continued to increase following Fusarium graminearum infection. By performing disease resistance analysis of zmstp2 and zmstp20 mutants, we found that after inoculation with Cochliobolus carbonum, Setosphaeria turcica, Cochliobolus heterostrophus, and F. graminearum, the lesion area of the mutants was significantly higher than that of the wild-type B73 plant. In this study, the genes encoding sugar transporters in maize were systematically identified and analyzed at the whole genome level. The expression patterns of the sugar transporter-encoding genes in different tissues of maize and under biotic and abiotic stresses were revealed, which laid an important theoretical foundation for further elucidation of their functions.