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.

Screening of Postpartum Depression Diagnostic Markers Based on Immune-Related Genes and Immune Infiltration

Background:Postpartum depression(PPD)is a mild to severe non-psychotic depressive episode,one of the main factors leading to pregnancy-related morbidity and mortality,and a mental disorder that has not been fully diagnosed and treated.Compared with women without polycystic ovary syndrome,women with polycystic ovary syndrome are more likely to have a variety of pregnancy complications,including PPD.However,there is currently limited research on whether polycystic ovary syndrome is related to anxiety and depression during pregnancy,and whether this increases the risk of postpartum depression in women.Study design:The GSE10558 data set gene expression profile matrix was used for PPD expression profiles from Gene Expression Synthesis(GEO).The differentially expressed genes were selected and analyzed.Perform gene ontology(GO)enrichment and gene set variation analysis(GSVA)for annotation,visualization,and integrated discovery.At the same time,CIBERSORT and ESTIMATE were used to analyze the immune infiltration situation of the GSE10558 expression profile matrix,including the immune infiltration pattern of ovarian samples,and construct the immune cell infiltration(ICI)score.Then we screened the differentially expressed genes(DEGs)clustered with three groups of immune subtypes,and constructed a protein-protein interaction(PPI)and mRNA-miRNA-TF molecular interaction network.And further predicted the drug target of the hub gene and the target of small molecule compounds,and constructed a network.Based on the intersection of the phenotypic gene set,the pivot gene was identified.Finally,evaluate the expression differences of Hub genes between the data set groups,and generate receiver operating characteristic(ROC)curves to verify the diagnostic value of differentially expressed genes(DEG).Finally,genes with high area under the curve(AUC)values are validated.Results:We analyzed 222 DEGs with statistically significant differences in the GSE10558 data set by bioinformatics methods,of which 18 DEGs have significant differences.GO analysis showed that most of the 18 significantly differentially expressed genes were rich in receptor ligand activity and cytokine receptor binding.It is worth noting that these genes are also enriched in functional areas related to immune inflammatory response and immune cell regulation.The GSVA package was used for GSVA analysis,and the results showed that it was significantly enriched in growth factor binding and other aspects.And according to the ssGSEA analysis to obtain immune clustering groupings,the DEGs found in the high,medium,and low immune score groups are mainly enriched in immune inflammatory response and immune cell regulation through GO analysis.CIBERSORT analysis found that there are significant differences in memory B cells of 22 types of immune cells in ovarian samples.By mining the phenotypic gene set,the DEGs that are significantly related to PPD are intersected respectively,and four overlapping genes APOA1,PLN,PRKCZ,and TRPV2 are obtained as the most important pivot genes.We also use box plots to show the expression differences between tissue samples.The results show that there are significant differences in expression of these genes between groups,which may serve as new potential targets for the diagnosis and treatment of PPD.Subsequently,the ROC curve analysis of the four APOA1,PLN,PRKCZ,and TRPV2 that are significantly related to PPD showed significant prediction accuracy,and all AUCs were above 0.9,indicating that these new biomarkers can be further developed in PPD Research.Conclusion:The molecular markers APOA1,PLN,PRKCZ and TRPV2,which are closely related to immune cell function,can efficiently identify PPD.A diagnostic prediction model composed of these four immune function-related genes can distinguish PPD patients with different immune status.This discovery contributes to a more comprehensive understanding of the molecular mechanisms driving the occurrence and development of PPD,which is critical for improving the diagnosis,prognosis and treatment of this disease.

Construction of a Full-Length cDNA Library of Solen grandis Dunker and Identification of Defense- and Immune-Related Genes

The basic genetic characteristics, important functional genes, and entire transcriptome of Solen grandis Dunker were investigated by constructing a full-length cDNA library with the ‘switching mechanism at the 5'-end of the RNA transcript'(SMART) technique. Total RNA was isolated from the immune-relevant tissues, gills and hemocytes, using the Trizol reagent, and cDNA fragments were digested with Sfi I before being ligated to the pBluescript II SK* vector. The cDNA library had a titer of 1048 cfu μL-1 and a storage capacity of 1.05×106 cfu. Approximately 98% of the clones in the library were recombinants, and the fragment lengths of insert cDNA ranged from 0.8 kb to 3.0 kb. A total of 2038 expressed sequence tags were successfully sequenced and clustered into 965 unigenes. BLASTN analysis showed that 240 sequences were highly similar to the known genes(E-value < 1e-5; percent identity >80%), accounting for 25% of the total unigenes. According to the Gene Ontology, these unigenes were related to several biological processes, including cell structure, signal transport, protein synthesis, transcription, energy metabolism, and immunity. Fifteen of the identified sequences were related to defense and immunity. The full-length cDNA sequence of HSC70 was obtained. The cDNA library of S. grandis provided a useful resource for future researches of functional genomics related to stress tolerance, immunity, and other physiological activities.

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.

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.

Identification of an immune-related gene signature for predicting prognosis and immunotherapy efficacy in liver cancer via cell-cell communication

BACKGROUND Liver cancer is one of the deadliest malignant tumors worldwide.Immunotherapy has provided hope to patients with advanced liver cancer,but only a small fraction of patients benefit from this treatment due to individual differences.Identifying immune-related gene signatures in liver cancer patients not only aids physicians in cancer diagnosis but also offers personalized treatment strategies,thereby improving patient survival rates.Although several methods have been developed to predict the prognosis and immunotherapeutic efficacy in patients with liver cancer,the impact of cell-cell interactions in the tumor microenvir-onment has not been adequately considered.AIM To identify immune-related gene signals for predicting liver cancer prognosis and immunotherapy efficacy.METHODS Cell grouping and cell-cell communication analysis were performed on single-cell RNA-sequencing data to identify highly active cell groups in immune-related pathways.Highly active immune cells were identified by intersecting the highly active cell groups with B cells and T cells.The significantly differentially expressed genes between highly active immune cells and other cells were subsequently selected as features,and a least absolute shrinkage and selection operator(LASSO)regression model was constructed to screen for diagnostic-related features.Fourteen genes that were selected more than 5 times in 10 LASSO regression experiments were included in a multivariable Cox regression model.Finally,3 genes(stathmin 1,cofilin 1,and C-C chemokine ligand 5)significantly associated with survival were identified and used to construct an immune-related gene signature.RESULTS The immune-related gene signature composed of stathmin 1,cofilin 1,and C-C chemokine ligand 5 was identified through cell-cell communication.The effectiveness of the identified gene signature was validated based on experi-mental results of predictive immunotherapy response,tumor mutation burden analysis,immune cell infiltration analysis,survival analysis,and expression analysis.CONCLUSION The findings suggest that the identified gene signature may contribute to a deeper understanding of the activity patterns of immune cells in the liver tumor microenvironment,providing insights for personalized treatment strategies.

Construction of an immune-related prognostic model to predict prognosis and immunotherapy in liver cancer patients with hepatitis B virus-infected

Background:Hepatocellular carcinoma(HCC)appears to be strongly associated with immune-related genes.However,immune-related genes are not well understood as a prognostic marker in HCC caused by the hepatitis B virus(HBV).The purpose of this study was to investigate the prognostic significance of immune-related genes in HBV-infected HCC.Methods:Gene expression data from 114 HBV-infected HCC and 50 normal tissues were integrated into The Cancer Genome Atlas.Differentially expressed immune-associated genes were analyzed to identify immune-associated differential genes associated with overall survival.Least Absolute Shrinkage and Selection Operator and multivariate Cox regressions were used to constructing immunoprognostic models.An independent prognostic factor analysis using multiple Cox regressions was also performed for HBV-infected HCCs.Immunocorrelation analysis markers and immune cell infiltration were also investigated.Results:We found 113 differentially expressed immune-associated genes.Immune-related differential genes were significantly correlated with the overall survival of HCC patients.We constructed an immune-based prognostic model using multivariate Cox regression analysis including seven immune-related genes.According to further analysis,immune-related prognostic factors may serve as independent prognostic indicators in the clinical setting.There is also evidence that the 7-gene prognostic model reflects the tumor immune microenvironment as a result of the risk score model and immune cell infiltration.Conclusions:As a result of our study,we screened immune-related genes for prognosis in HBV-infected HCC and developed a novel immune-based prognostic model.The research not only provides new prognostic biomarkers but also offers insight into the tumor immune microenvironment and lays the theoretical groundwork for immunotherapy.

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.

Mining elite loci and candidate genes for root morphology-related traits at the seedling stage by genome-wide association studies in upland cotton(Gossypium hirsutum L.)

Root system architecture plays an essential role in water and nutrient acquisition in plants,and it is significantly involved in plant adaptations to various environmental stresses.In this study,a panel of 242 cotton accessions was collected to investigate six root morphological traits at the seedling stage,including main root length(MRL),root fresh weight(RFW),total root length(TRL),root surface area(RSA),root volume(RV),and root average diameter(AvgD).The correlation analysis of the six root morphological traits revealed strong positive correlations of TRL with RSA,as well as RV with RSA and AvgD,whereas a significant negative correlation was found between TRL and AvgD.Subsequently,a genome-wide association study(GWAS)was performed using the root phenotypic and genotypic data reported previously for the 242 accessions using 56,010 single nucleotide polymorphisms(SNPs)from the CottonSNP80K array.A total of 41 quantitative trait loci(QTLs)were identified,including nine for MRL,six for RFW,nine for TRL,12 for RSA,12 for RV and two for AvgD.Among them,eight QTLs were repeatedly detected in two or more traits.Integrating these results with a transcriptome analysis,we identified 17 candidate genes with high transcript values of transcripts per million(TPM)≥30 in the roots.Furthermore,we functionally verified the candidate gene GH_D05G2106,which encodes a WPP domain protein 2in root development.A virus-induced gene silencing(VIGS)assay showed that knocking down GH_D05G2106significantly inhibited root development in cotton,indicating its positive role in root system architecture formation.Collectively,these results provide a theoretical basis and candidate genes for future studies on cotton root developmental biology and root-related cotton breeding.

Knockdown of the atypical protein kinase genes GhABC1K2-A05 and GhABC1K12-A07 make cotton more sensitive to salt and PEG stress

Activity of bc1 complex kinase(ABC1K)is an atypical protein kinase(aPK)that plays a crucial role in plant mitochondrial and plastid stress responses,but little is known about the responses of ABC1Ks to stress in cotton(Gossypium spp.).Here,we identified 40 ABC1Ks in upland cotton(Gossypium hirsutum L.)and found that the Gh ABC1Ks were unevenly distributed across 17 chromosomes.The GhABC1K family members included 35 paralogous gene pairs and were expanded by segmental duplication.The GhABC1K promoter sequences contained diverse cis-acting regulatory elements relevant to hormone or stress responses.The qRT-PCR results revealed that most Gh ABC1Ks were upregulated by exposure to different stresses.Gh ABC1K2-A05 and Gh ABC1K12-A07 expression levels were upregulated by at least three stress treatments.These genes were further functionally characterized by virus-induced gene silencing(VIGS).Compared with the controls,the Gh ABC1K2-A05-and Gh ABC1K12-A07-silenced cotton lines exhibited higher malondialdehyde(MDA)contents,lower catalase(CAT),peroxidase(POD)and superoxide dismutase(SOD)activities and reduced chlorophyll and soluble sugar contents under NaCl and PEG stress.In addition,the expression levels of six stress marker genes(Gh DREB2A,Gh SOS1,Gh CIPK6,Gh SOS2,Gh WRKY33,and Gh RD29A)were significantly downregulated after stress in the Gh ABC1K2-A05-and Gh ABC1K12-A07-silenced lines.The results indicate that knockdown of Gh ABC1K2-A05 and Gh ABC1K12-A07 make cotton more sensitive to salt and PEG stress.These findings can provide valuable information for intensive studies of Gh ABC1Ks in the responses and resistance of cotton to abiotic stresses.

Predictive model using four ferroptosis-related genes accurately predicts gastric cancer prognosis

BACKGROUND Gastric cancer(GC)is a common malignancy of the digestive system.According to global 2018 cancer data,GC has the fifth-highest incidence and the thirdhighest fatality rate among malignant tumors.More than 60%of GC are linked to infection with Helicobacter pylori(H.pylori),a gram-negative,active,microaerophilic,and helical bacterium.This parasite induces GC by producing toxic factors,such as cytotoxin-related gene A,vacuolar cytotoxin A,and outer membrane proteins.Ferroptosis,or iron-dependent programmed cell death,has been linked to GC,although there has been little research on the link between H.pylori infection-related GC and ferroptosis.AIM To identify coregulated differentially expressed genes among ferroptosis-related genes(FRGs)in GC patients and develop a ferroptosis-related prognostic model with discrimination ability.METHODS Gene expression profiles of GC patients and those with H.pylori-associated GC were obtained from The Cancer Genome Atlas and Gene Expression Omnibus(GEO)databases.The FRGs were acquired from the FerrDb database.A ferroptosis-related gene prognostic index(FRGPI)was created using least absolute shrinkage and selection operator–Cox regression.The predictive ability of the FRGPI was validated in the GEO cohort.Finally,we verified the expression of the hub genes and the activity of the ferroptosis inducer FIN56 in GC cell lines and tissues.RESULTS Four hub genes were identified(NOX4,MTCH1,GABARAPL2,and SLC2A3)and shown to accurately predict GC and H.pylori-associated GC.The FRGPI based on the hub genes could independently predict GC patient survival;GC patients in the high-risk group had considerably worse overall survival than did those in the low-risk group.The FRGPI was a significant predictor of GC prognosis and was strongly correlated with disease progression.Moreover,the gene expression levels of common immune checkpoint proteins dramatically increased in the highrisk subgroup of the FRGPI cohort.The hub genes were also confirmed to be highly overexpressed in GC cell lines and tissues and were found to be primarily localized at the cell membrane.The ferroptosis inducer FIN56 inhibited GC cell proliferation in a dose-dependent manner.CONCLUSION In this study,we developed a predictive model based on four FRGs that can accurately predict the prognosis of GC patients and the efficacy of immunotherapy in this population.

Progress on immuno-microenvironment and immune-related therapies in patients with pseudomyxoma peritonei

Pseudomyxoma peritonei(PMP) is an indolent malignant syndrome. The standard treatment for PMP is cytoreductive surgery combined with intraperitoneal hyperthermic chemotherapy(CRS + HIPEC). However, the high recurrence rate and latent clinical symptoms and signs are major obstacles to further improving clinical outcomes. Moreover, patients in advanced stages receive little benefit from CRS + HIPEC due to widespread intraperitoneal metastases. Another challenge in PMP treatment involves the progressive sclerosis of PMP cell-secreted mucus, which is often increased due to activating mutations in the gene coding for guanine nucleotide-binding protein alpha subunit(GNAS). Consequently, the development of other PMP therapies is urgently needed. Several immune-related therapies have shown promise, including the use of bacterium-derived non-specific immunogenic agents, radioimmunotherapeutic agents, and tumor cell-derived neoantigens, but a well-recognized immunotherapy has not been established. In this review the roles of GNAS mutations in the promotion of mucin secretion and disease development are discussed. In addition, the immunologic features of the PMP microenvironment and immune-associated treatments are discussed to summarize the current understanding of key features of the disease and to facilitate the development of immunotherapies.

Key genes and regulatory networks for diabetic retinopathy based on hypoxia-related genes:a bioinformatics analysis

AIM:To prevent neovascularization in diabetic retinopathy(DR)patients and partially control disease progression.METHODS:Hypoxia-related differentially expressed genes(DEGs)were identified from the GSE60436 and GSE102485 datasets,followed by gene ontology(GO)functional annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis.Potential candidate drugs were screened using the CMap database.Subsequently,a protein-protein interaction(PPI)network was constructed to identify hypoxia-related hub genes.A nomogram was generated using the rms R package,and the correlation of hub genes was analyzed using the Hmisc R package.The clinical significance of hub genes was validated by comparing their expression levels between disease and normal groups and constructing receiver operating characteristic curve(ROC)curves.Finally,a hypoxia-related miRNA-transcription factor(TF)-Hub gene network was constructed using the NetworkAnalyst online tool.RESULTS:Totally 48 hypoxia-related DEGs and screened 10 potential candidate drugs with interaction relationships to upregulated hypoxia-related genes were identified,such as ruxolitinib,meprylcaine,and deferiprone.In addition,8 hub genes were also identified:glycogen phosphorylase muscle associated(PYGM),glyceraldehyde-3-phosphate dehydrogenase spermatogenic(GAPDHS),enolase 3(ENO3),aldolase fructose-bisphosphate C(ALDOC),phosphoglucomutase 2(PGM2),enolase 2(ENO2),phosphoglycerate mutase 2(PGAM2),and 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3(PFKFB3).Based on hub gene predictions,the miRNA-TF-Hub gene network revealed complex interactions between 163 miRNAs,77 TFs,and hub genes.The results of ROC showed that the except for GAPDHS,the area under curve(AUC)values of the other 7 hub genes were greater than 0.758,indicating their favorable diagnostic performance.CONCLUSION:PYGM,GAPDHS,ENO3,ALDOC,PGM2,ENO2,PGAM2,and PFKFB3 are hub genes in DR,and hypoxia-related hub genes exhibited favorable diagnostic performance.

Neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio:Markers predicting immune-checkpoint inhibitor efficacy and immune-related adverse events

We conducted a comprehensive review of existing prediction models pertaining to the efficacy of immune-checkpoint inhibitor(ICI)and the occurrence of immune-related adverse events(irAEs).The predictive potential of neutrophil-to-lymphocyte ratio(NLR)and platelet-to-lymphocyte ratio(PLR)in determining ICI effectiveness has been extensively investigated,while limited research has been conducted on predicting irAEs.Furthermore,the combined model incor-porating NLR and PLR,either with each other or in conjunction with additional markers such as carcinoembryonic antigen,exhibits superior predictive capabilities compared to individual markers alone.NLR and PLR are promising markers for clinical applications.Forthcoming models ought to incorporate established efficacious models and newly identified ones,thereby constituting a multifactor composite model.Furthermore,efforts should be made to explore effective clinical application approaches that enhance the predictive accuracy and efficiency.

RPLP0/TBP are the most stable reference genes for human dental pulp stem cells under osteogenic differentiation

BACKGROUND Validation of the reference gene(RG)stability during experimental analyses is essential for correct quantitative real-time polymerase chain reaction(RT-qPCR)data normalisation.Commonly,in an unreliable way,several studies use genes involved in essential cellular functions[glyceraldehyde-3-phosphate dehydro-genase(GAPDH),18S rRNA,andβ-actin]without paying attention to whether they are suitable for such experimental conditions or the reason for choosing such genes.Furthermore,such studies use only one gene when Minimum Information for Publication of Quantitative Real-Time PCR Experiments guidelines recom-mend two or more genes.It impacts the credibility of these studies and causes dis-tortions in the gene expression findings.For tissue engineering,the accuracy of gene expression drives the best experimental or therapeutical approaches.We cultivated DPSCs under two conditions:Undifferentiated and osteogenic dif-ferentiation,both for 35 d.We evaluated the gene expression of 10 candidates for RGs[ribosomal protein,large,P0(RPLP0),TATA-binding protein(TBP),GAPDH,actin beta(ACTB),tubulin(TUB),aminolevulinic acid synthase 1(ALAS1),tyro-sine 3-monooxygenase/tryptophan 5-monooxygenase activation protein,zeta(YWHAZ),eukaryotic translational elongation factor 1 alpha(EF1a),succinate dehydrogenase complex,subunit A,flavoprotein(SDHA),and beta-2-micro-globulin(B2M)]every 7 d(1,7,14,21,28,and 35 d)by RT-qPCR.The data were analysed by the four main algorithms,ΔCt method,geNorm,NormFinder,and BestKeeper and ranked by the RefFinder method.We subdivided the samples into eight subgroups.RESULTS All of the data sets from clonogenic and osteogenic samples were analysed using the RefFinder algorithm.The final ranking showed RPLP0/TBP as the two most stable RGs and TUB/B2M as the two least stable RGs.Either theΔCt method or NormFinder analysis showed TBP/RPLP0 as the two most stable genes.However,geNorm analysis showed RPLP0/EF1αin the first place.These algorithms’two least stable RGs were B2M/GAPDH.For BestKeeper,ALAS1 was ranked as the most stable RG,and SDHA as the least stable RG.The pair RPLP0/TBP was detected in most subgroups as the most stable RGs,following the RefFinfer ranking.CONCLUSION For the first time,we show that RPLP0/TBP are the most stable RGs,whereas TUB/B2M are unstable RGs for long-term osteogenic differentiation of human DPSCs in traditional monolayers.

GST family genes in jujube actively respond to phytoplasma infection

Jujube witches’broom(JWB)caused by phytoplasma has a severely negative effect on multiple metabolisms in jujube.The GST gene family in plants participates in the regulation of a variety of biotic and abiotic stresses.This study aims to identify and reveal the changes in the jujube GST gene family in response to phytoplasma infection.Here,70 ZjGSTs were identified in the jujube genome and divided into 8 classes.Among them,the Tau-class,including 44 genes,was the largest.Phylogenetic analysis indicated that Tau-class genes were highly conserved among species,such as Arabidopsis,cotton,chickpea,and rice.Through chromosome location analysis,37.1%of genes were clustered,and 8 of 9 gene clusters were composed of Tau class members.Through RT-PCR,qRT-PCR and enzyme activity detection,the results showed that the expression of half(20/40)of the tested ZjGSTs was inhibited by phytoplasma infection in field and tissue culture conditions,and GST activity was also significantly reduced.In the resistant and susceptible varieties under phytoplasma infection,ZjGSTU49-ZjGSTU54 in the cluster IV showed opposite expression patterns,which may be due to functional divergence during evolution.Some upregulated genes(ZjGSTU45,ZjGSTU49,ZjGSTU59,and ZjGSTU70)might be involved in the process of jujube against JWB.The yeast two-hybrid results showed that all 6 Tauclass proteins tested could form homodimers or heterodimers.Overall,the comprehensive analysis of the jujube GST gene family revealed that ZjGSTs responded actively to phytoplasma infection.Furthermore,some screened genes(ZjGSTU24,ZjGSTU49-52,ZjGSTU70,and ZjDHAR10)will contribute to further functional studies of jujube-phytoplasma interactions.

Fate and Behavior of Tetracycline Resistance Genes in Activated Carbon Adsorption

The accessibility of tetracycline resistance gene (tetG) into the pores of activated carbon (AC), as well as the impact of the pore size distribution (PSD) of AC on the uptake capacity of tetG, were investigated using eight types of AC (four coal-based and four wood-based). AC showed the capability to admit tetG and the average reduction of tetG for coal-based and wood-based ACs at the AC dose of 1 g·L-1 was 3.12 log and 3.65 log, respectively. The uptake kinetic analysis showed that the uptake of the gene followed the pseudo-second-order kinetics reaction, and the uptake rate constant for the coal-based and wood-based ACs was in the range of 5.97 × 10-12 - 4.64 × 10-9 and 7.02 × 10-11 - 1.59 × 10-8 copies·mg-1·min-1, respectively. The uptake capacity analysis by fitting the obtained experiment data with the Freundlich isotherm model indicated that the uptake constant (KF) values were 1.71 × 103 - 8.00 × 109 (copies·g-1)1-1/n for coal-based ACs and 7.00 × 108 - 3.00 × 1010 (copies·g-1)1-1/n for wood-based ones. In addition, the correlation analysis between KF values and pore volume as well as pore surface at different pore size regions of ACs showed that relatively higher positive correlation was found for pores of 50 - 100 Å, suggesting ACs with more pores in this size region can uptake more tetG. The findings of this study are valuable as reference for optimizing the adsorption process regarding antibiotic resistance-related concerns in drinking water treatment.

Comprehensive analysis of the potential pathogenesis of COVID-19 infection and liver cancer

BACKGROUND A growing number of clinical examples suggest that coronavirus disease 2019(COVID-19)appears to have an impact on the treatment of patients with liver cancer compared to the normal population,and the prevalence of COVID-19 is significantly higher in patients with liver cancer.However,this mechanism of action has not been clarified.Gene sets for COVID-19(GSE180226)and liver cancer(GSE87630)were obtained from the Gene Expression Omnibus database.After identifying the common differentially expressed genes(DEGs)of COVID-19 and liver cancer,functional enrichment analysis,protein-protein interaction network construction and scree-ning and analysis of hub genes were performed.Subsequently,the validation of the differential expression of hub genes in the disease was performed and the regulatory network of transcription factors and hub genes was constructed.RESULTS Of 518 common DEGs were obtained by screening for functional analysis.Fifteen hub genes including aurora kinase B,cyclin B2,cell division cycle 20,cell division cycle associated 8,nucleolar and spindle associated protein 1,etc.,were further identified from DEGs using the“cytoHubba”plugin.Functional enrichment analysis of hub genes showed that these hub genes are associated with P53 signalling pathway regulation,cell cycle and other functions,and they may serve as potential molecular markers for COVID-19 and liver cancer.Finally,we selected 10 of the hub genes for in vitro expression validation in liver cancer cells.CONCLUSION Our study reveals a common pathogenesis of liver cancer and COVID-19.These common pathways and key genes may provide new ideas for further mechanistic studies.

Biomarkers associated with immune-related adverse events induced by immune checkpoint inhibitors

Immune checkpoint inhibitors(ICIs)constitute a pivotal class of immunotherapeutic drugs in cancer treatment.However,their widespread clinical application has led to a notable surge in immune-related adverse events(irAEs),significantly affecting the efficacy and survival rates of patients undergoing ICI therapy.While conventional hematological and imaging tests are adept at detecting organ-specific toxicities,distinguishing adverse reactions from those induced by viruses,bacteria,or immune diseases remains a formidable challenge.Consequently,there exists an urgent imperative for reliable biomarkers capable of accurately predicting or diagnosing irAEs.Thus,a thorough review of existing studies on irAEs biomarkers is indispensable.Our review commences by providing a succinct over-view of major irAEs,followed by a comprehensive summary of irAEs biomarkers across various dimensions.Furthermore,we delve into innovative methodologies such as machine learning,single-cell RNA sequencing,multiomics analysis,and gut microbiota profiling to identify novel,robust biomarkers that can facilitate precise irAEs diagnosis or prediction.Lastly,this review furnishes a concise exposition of irAEs mechanisms to augment understanding of irAEs prediction,diagnosis,and treatment strategies.

Effects of Heterologously Overexpressing PIP5K-Family Genes in Arabidopsis on Inflorescence Development

Castor is one of the top 10 oil crops in the world and has extremely valuable uses.Castor inflorescences directly affect yield,so the study of inflorescence development is very important in increasing castor yield.Our previous studies have shown that the PIP5K gene family(PIP5Ks)is associated with inflorescence development.In this study,to determine the function of each PIP5K gene in castor,a female Lm-type castor line,aLmAB2,was used to determine the relative expression levels of the PIP5Ks in castor inflorescences.Six PIP5K genes were heterologously overexpressed in Arabidopsis thaliana,the relative expression of each gene and the effect on plants was determined in A.thaliana,and the relationships among the PIP5Ks in castor were inferred.The expression levels of the PIP5Ks in the female Lm-type castor line aLmAB2 were analyzed.The relative expression levels of the PIP5K9 and PIP5K11 genes were high(p<0.05)in isofemale inflorescences,and those of PIP5K1,PIP5K2,PIP5K6,and PIP5K8 were high(p<0.05)in female inflorescences but low(p<0.05)in bisexual inflorescences.The PIP5Ks were heterologously overexpressed in A.thaliana,and T3-generation plants with stable genetic resistance,i.e.,AT-PIP5K^(+)plants(AT-PIP5K1^(+),AT-PIP5K2^(+),AT-PIP5K6^(+),AT-PIP5K8^(+),AT-PIP5K9^(+),and ATPIP5K11^(+) plants),were obtained.Biological tests of the AT-PIP5K+plants showed that the growth of the main stem was significantly delayed in AT-PIP5K+plants compared with Columbia wild-type(WT)A.thaliana plants;the PIP5K1 and PIP5K2 genes promoted lateral stem growth and flower and silique development;and the PIP5K6,PIP5K8,PIP5K9 and PIP5K11 genes inhibited lateral stem growth and flower and silique development.The correlations among PIP5Ks in castor suggest that there may be a synergistic relationship among PIP5K1,PIP5K2,and PIP5K6 in castor inflorescences,and PIP5K8,PIP5K9,and PIP5K11 are complementary to the other three genes.