Marek’s disease virus challenge induced immune-related gene expression and chicken repeat 1 (CR1) methylation alterations in chickens

Marek’s disease virus (MDV) challenge induces lymphoma in susceptible chickens. Host genes, especially immune related genes, are activated by the virus. DNA methylation is an epigenetic mechanism that governs gene transcription. In the present study, we found that expression of signal transducer and activator of transcription 1 (STAT1) was upregulated at 10 days post infection (dpi) in MD susceptible chickens, whereas interleukin 12A (IL12A) was elevated in both resistant and susceptible chickens. However, we did not observe MDV-induced DNA methylation variations at the promoter CpG islands (CGIs) in STAT1 and IL12A. Interestingly, the methylation levels at Chicken Repeat 1 (CR1), the transposable elements (TEs) located upstream of two genes, were different between resistant and susceptible chickens. Furthermore, a mutation was identified in the CR1 element near IL12A. The impact of the point mutation in transcriptional factor binding is to be examined in the near future.

Identification of potential immune-related prognostic biomarkers of lung cancer using gene co-expression network analysis

Objective The objective of this study was to identify new carcinogenetic hub genes and develop the integration of differentially expressed genes to predict the prognosis of lung cancer.Methods GSE139032 microarray data packages were downloaded from the Gene Expression Omnibus for planning,testing,and review of data.We identified KRT6C,LAMC2,LAMB3,KRT6A,and MYEOV from a key module for validation.Results We found that the five genes were related to a poor prognosis,and the expression levels of these genes were associated with tumor stage.Furthermore,Kaplan-Meier plotter showed that the five hub genes had better prognostic values.The mean levels of methylation in lung adenocarcinoma(LUAD)were significantly lower than those in healthy lung tissues for the hub genes.However,gene set enrichment analysis(GSEA)for single hub genes showed that all of them were immune-related.Conclusion Our findings demonstrated that KRT6C,LAMC2,LAMB3,KRT6A,and MYEOV are all candidate diagnostic and prognostic biomarkers for LUAD.They may have clinical implications in LUAD patients not only for the improvement of risk stratification but also for therapeutic decisions and prognosis prediction.

Weighted gene co-expression network analysis identifies a novel immune-related gene signature and nomogram to predict the survival and immune infiltration status of breast cancer

Breast cancer is one of the most common cancers in the world and seriously threatens the health of women worldwide.Prognostic models based on immune-related genes help to improve the prognosis prediction and clinical treatment of breast cancer patients.In the study,we used weighted gene co-expression network analysis to construct a co-expression network to screen out highly prognostic immune-related genes.Subsequently,the prognostic immunerelated gene signature was successfully constructed from highly immune-related genes through COX regression and LASSO COX analysis.Survival analysis and time receiver operating characteristic curves indicate that the prognostic signature has strong predictive performance.And we developed a nomogram by combing the risk score with multiple clinical characteristics.CIBERSORT and TIMER algorithms confirmed that there are significant differences in tumorinfiltrating immune cells in different risk groups.In addition,gene set enrichment analysis shows 6 pathways that differ between high-and low-risk group.The immune-related gene signature effectively predicts the survival and immune infiltration of breast cancer patients and is expected to provide more effective immunotherapy targets for the prognosis prediction of breast cancer.

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 investigation of Hsf gene family in Phoebe bournei:identification,evolution,and expression after abiotic stresses

Heat shock transcription factors(Hsfs)have important roles during plant growth and development and responses to abiotic stresses.The identification and func-tion of Hsf genes have been thoroughly studied in various herbaceous plant species,but not woody species,especially Phoebe bournei,an endangered,unique species in China.In this study,17 members of the Hsf gene family were identi-fied from P.bournei using bioinformatic methods.Phyloge-netic analysis indicated that PbHsf genes were grouped into three subfamilies:A,B,and C.Conserved motifs,three-dimensional structure,and physicochemical properties of the PbHsf proteins were also analyzed.The structure of the PbHsf genes varied in the number of exons and introns.Pre-diction of cis-acting elements in the promoter region indi-cated that PbHsf genes are likely involved in responses to plant hormones and stresses.A collinearity analysis dem-onstrated that expansions of the PbHsf gene family mainly take place via segmental duplication.The expression levels of PbHsf genes varied across different plant tissues.On the basis of the expression profiles of five representative PbHsf genes during heat,cold,salt,and drought stress,PbHsf pro-teins seem to have multiple functions depending on the type of abiotic stress.This systematic,genome-wide investigation of PbHsf genes in P.bournei and their expression patterns provides valuable insights and information for further func-tional dissection of Hsf proteins in this endangered,unique species.

Immune-related gene characteristics:A new chapter in precision treatment of gastric cancer

Gastric cancer ranks as the sixth most prevalent cancer worldwide.In recent research within the realm of gastric cancer treatment,the identification and application of immune-related genetic features have emerged as groundbreaking advancements.The study by Ma et al,which developed a prognostic model based on 10 genes,categorizes patients into high and low-risk groups to predict their responsiveness to immune checkpoint inhibitor therapy.This research underscores the potential of immune-related genes as biomarkers for personalized treatment,offering insights into tumor mutation burden and immune phenotype scores.We advocate for further validation,understanding of biological mechanisms,and integration of diverse datasets to enhance the model's predictive accuracy and clinical application,marking a significant step towards personalized and precise treatment for gastric cancer.

Dietary manganese supplementation inhibits abdominal fat deposition possibly by regulating gene expression and enzyme activity involved in lipid metabolism in the abdominal fat of broilers

Excessive abdominal fat deposition seriously restricts the production efficiency of broilers.Several studies found that dietary supplemental manganese(Mn)could effectively reduce the abdominal fat deposition of broilers,but the underlying mechanisms remain unclear.The present study aimed to investigate the effect of dietary supplementation with the inorganic or organic Mn on abdominal fat deposition,and enzyme activity and gene expression involved in lipid metabolism in the abdominal fat of male or female broilers.A total of 4201-d-old AA broilers(half males and half females)were randomly allotted by body weight and gender to 1 of 6 treatments with 10 replicates cages of 7 chicks per cage in a completely randomized design involving a 3(dietary Mn addition)×2(gender)factorial arrangement.Male or female broilers were fed with the Mn-unsupplemented basal diets containing 17.52 mg Mn kg^(-1)(d 1-21)and 15.62 mg Mn kg^(-1)(d 22-42)by analysis or the basal diets supplemented with 110 mg Mn kg^(-1)(d 1-21)and 80 mg Mn kg^(-1)(d 22-42)as either the Mn sulfate or the Mn proteinate with moderate chelation strength(Mn-Prot M)for 42 d.The results showed that the interaction between dietary Mn addition and gender had no impact(P>0.05)on any of the measured parameters;abdominal fat percentage of broilers was decreased(P<0.003)by Mn addition;Mn addition increased(P<0.004)adipose triglyceride lipase(ATGL)activity,while Mn-Prot M decreased(P<0.002)the fatty acid synthase(FAS)activity in the abdominal fat of broilers compared to the control;Mn addition decreased(P<0.009)diacylglycerol acyltransferase 2(DGAT2)mRNA expression level and peroxisome proliferator-activated receptor γ(PPARγ)mRNA and protein expression levels,but up-regulated(P<0.05)the ATGL mRNA and protein expression levels in the abdominal fat of broilers.It was concluded that dietary supplementation with Mn inhibited the abdominal fat deposition of broilers possibly via decreasing the expression of PPARγand DGAT2 as well as increasing the expression and activity of ATGL in the abdominal fat of broilers,and Mn-Prot M was more effective in inhibiting the FAS acitivity.

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.

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.

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.

Transcriptome analysis reveals immune-related genes in tissues of Vibrio anguillarum-infected turbot Scophthalmus maximus

Turbot Scophthalmus maximus is an important mariculture fish species with high economic value.However,the bacterial diseases caused by Vibrio anguillarum infection bring huge economic losses to the turbot aquaculture industry.To understand the immune response of the turbot against V.anguillarum infection and to explore novel immune-related genes,the transcriptome analysis of turbot spleen and gills were conducted after V.anguillarum infection.Differentially expressed genes(DEGs)were identified in spleen and gill of the turbot amounted to 17261 and 16436,respectively.A large number of immunerelated DEGs were enriched in cytokine-cytokine receptor interaction signaling pathway,and the others by the kyoto encyclopedia of genes and genomes(KEGG)enrichment.The gene ontology(GO)classification analysis revealed that V.anguillarum infection had the greatest effect on biological processes and cellular components.Twelve immune-related DEGs were identified in the spleen(cstl.1,egfl6,lamb21,v2rx4,calcr,and gpr78a)and gills(ghra,sh3gl2a,cst12,inhbaa,cxcl8,and il-1b)by heat map.The proteinprotein interaction(PPI)networks were constructed to analyze the immune mechanism.The results demonstrate that the maturation and antigen processing of major histocompatibility complex(MHC)class II molecule,and calcitonin-or adrenomedullin-regulated physiological activity were important events in the immunity of turbot against V.anguillarum infection.In the gills,the protein interactions in TGF-βsignaling pathway,production of inflammatory factors,and endocytosis regulation were most significant.Our research laid a foundation for discovering novel immune-related genes and enriching the knowledge of immune mechanisms of turbot against V.anguillarum infection.

Genome-Wide Identification of the GST Gene Family in Loquat (Eriobotrya japonica Lindl.) and Their Expression under Cold Stress with ALA Pretreatment

Loquat(Eriobotrya japonica Lindl.),a rare fruit native to China,has a long history of cultivation in China.Low temperature is the key factor restricting loquat growth and severely affects yield.Low temperature induces the regeneration and metabolism of reduced glutathione(GSH)to alleviate stress damage via the participation of glu-tathione S-transferases(GSTs)in plants.In this study,16 GSTs were identified from the loquat genome according to their protein sequence similarity with Arabidopsis GSTs.On the basis of domain characteristics and phyloge-netic analysis of AtGSTs,these EjGSTs can be divided into 4 subclasses:Phi,Theta,Tau and Zeta.The basic prop-erties,subcellular localization,structures,motifs,chromosomal distribution and collinearity of the EjGST proteins or genes were further analyzed.Tandem and segmental gene duplications play pivotal roles in EjGST expansion.Cis-elements that respond to various hormones and stresses,especially those associated with low-temperature responsiveness,were predicted to be present in the promoters of EjGSTs.Moreover,analysis of gene expression profiles revealed that 9 of 16 EjGSTs may be involved in the low-temperature responsiveness of loquat leaves.In agriculture,5-aminolevulinic acid(ALA),a potential multifunctional plant growth regulator,can improve the stress response of plants.Among the 9 low-temperature-responsive EjGSTs,the expression of EjGSTU1 and EjGSTF1 significantly differed under cold stress in response to exogenous 5-aminolevulinic acid(ALA)pretreat-ment.The remarkable increase in GST activity and GSH/GSSG ratio reflected the increase in the cold response ability of loquat plants caused by exogenous ALA,thereby alleviating H2O2 accumulation and membrane lipid preoxidation.Overall,this study provides an initial exploration of the cold tolerance function of GSTs in loquat,offering a theoretical foundation for the development of cold-resistant loquat cultivars and new antifreeze agents.

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.

Genome-Wide Identification of Tomato (Solanum lycopersicum L.) CKX Gene Family and Expression Analysis in the Callus Tissue under Zeatin Treatment

The cytokinin oxidase/dehydrogenase(CKX)enzyme is essential for controlling thefluctuating levels of endogen-ous cytokinin(CK)and has a significant impact on different aspects of plant growth and development.Nonethe-less,there is limited knowledge about CKX genes in tomato(Solanum lycopersicum L.).Here we performed genome-wide identification and analysis of nine SlCKX family members in tomatoes using bioinformatics tools.The results revealed that nine SlCKX genes were unevenly distributed onfive chromosomes(Chr.1,Chr.4,Chr.8,Chr.10,and Chr.12).The amino acid length,isoelectric points,and molecular weight of the nine SlCKX proteins ranged from 453 to 553,5.77 to 8.59,and 51.661 to 62.494 kD,respectively.Subcellular localization analysis indi-cated that SlCKX2 proteins were located in both the vacuole and cytoplasmic matrix;SlCKX3 and SlCKX5 pro-teins were located in the vacuole;and SlCKX1,4,6,7,8,and 9 proteins were located in the cytoplasmic matrix.Furthermore,we observed differences in the gene structures and phylogenetic relationships of SlCKX proteins among different members.SlCKX1-9 were positioned on two out of the three branches of the CKX phylogenetic tree in the multispecies phylogenetic tree construction,revealing their strong conservation within phylogenetic subgroups.Unique patterns of expression of CKX genes were noticed in callus cultures exposed to varying con-centrations of exogenous ZT,suggesting their roles in specific developmental and physiological functions in the regeneration system.These results may facilitate subsequent functional analysis of SlCKX genes and provide valu-able insights for establishing an efficient regeneration system for tomatoes.

Genome-Wide Discovery and Expression Profiling of the SWEET Sugar Transporter Gene Family in Woodland Strawberry (Fragaria vesca) under Developmental and Stress Conditions: Structural and Evolutionary Analysis

The SWEET(sugar will eventually be exported transporter)family proteins are a recently identified class of sugar transporters that are essential for various physiological processes.Although the functions of the SWEET proteins have been identified in a number of species,to date,there have been no reports of the functions of the SWEET genes in woodland strawberries(Fragaria vesca).In this study,we identified 15 genes that were highly homolo-gous to the A.thaliana AtSWEET genes and designated them as FvSWEET1–FvSWEET15.We then conducted a structural and evolutionary analysis of these 15 FvSWEET genes.The phylogenetic analysis enabled us to categor-ize the predicted 15 SWEET proteins into four distinct groups.We observed slight variations in the exon‒intron structures of these genes,while the motifs and domain structures remained highly conserved.Additionally,the developmental and biological stress expression profiles of the 15 FvSWEET genes were extracted and analyzed.Finally,WGCNA coexpression network analysis was run to search for possible interacting genes of FvSWEET genes.The results showed that the FvSWEET10 genes interacted with 20 other genes,playing roles in response to bacterial and fungal infections.The outcomes of this study provide insights into the further study of FvSWEET genes and may also aid in the functional characterization of the FvSWEET genes in woodland strawberries.

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).

Gene expression analysis of cytokines and MMPs in melatonin and rhBMP-2 enhanced bone remodeling

BACKGROUND In the medical and dental fields,there is a need for studies of new therapeutic approaches for the treatment of bone defects that cause extensive bone loss.Melatonin may be an important endogenous biological factor for bone remodeling,and growth factors may enhance the repair process.AIM To evaluate the gene expression of cytokines(IL-1β,IL-6,IL-10 and TNF-α),markers of osteoclastogenesis(RANK,RANKL and OPG)and MMPs(MMP-1,MMP-2,MMP-8 and MMP-13)from the treatment of melatonin associated with an osteogenic membrane and rhBMP-2 on the recovery of a bone injury.METHODS Sixty-four rats were used and divided into 9 experimental groups and were formed according to the treatment carried out in the region of the bone lesion,which varied between the combination of 1,10 and 100μmol/L of melatonin.Gene Expression analysis was performed using real time-PCR by reading the concentration of total RNA and reverse transcription.RESULTS There were differences between groups when compared with clot or scaffold control,and improvement with a higher concentration of melatonin or rhBMP-2.The combination melatonin(1μg)with 5μg of rhBMP-2,using the guided bone regeneration technique,demonstrated some effects,albeit mild,on bone repair of critical bone defects.CONCLUSION This indicates that the approach for administering these substances needs to be reassessed,with the goal of ensuring their direct application to the affected area.Therefore,future research must be carried out,seeking to produce materials with these ideal characteristics.

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.

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.

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.