ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently， the gene family members were subject to analysis， including gene structure， chromosomal localization， cis-acting elements， gene synteny， and phylogeny. Combined with transcriptome data and quantitative Real-time PCR， the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally， correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca， unevenly distributed across 17 chromosomes and clustered into 16 subfamilies， with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes， 12 bHLH genes （such as bHLH62-3 and bHLH74） were associated with the bright yellow color of G elata f. elata stem， while 9 bHLH genes （such as PIL13， UNE12， and bHLH130） were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca， the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata， and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes， 21 bHLH genes participate in the coloration metabolic pathway regulation of stems， flowers， and fruits. Specifically， bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata， thus relevant to the color formation of stem. Additionally， GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.

ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently， the gene family members were subject to analysis， including gene structure， chromosomal localization， cis-acting elements， gene synteny， and phylogeny. Combined with transcriptome data and quantitative Real-time PCR， the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally， correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca， unevenly distributed across 17 chromosomes and clustered into 16 subfamilies， with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes， 12 bHLH genes （such as bHLH62-3 and bHLH74） were associated with the bright yellow color of G elata f. elata stem， while 9 bHLH genes （such as PIL13， UNE12， and bHLH130） were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca， the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata， and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes， 21 bHLH genes participate in the coloration metabolic pathway regulation of stems， flowers， and fruits. Specifically， bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata， thus relevant to the color formation of stem. Additionally， GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.

With the continuous development of society, a large number of new chemicals are continuously emerging, which presents a challenge to current risk assessment and safety management of chemicals. Traditional toxicology research methods have certain limitations in quickly, efficiently, and accurately assessing the toxicity of many chemicals, and cannot meet the actual needs. In response to this challenge, computational toxicology that use mathematical and computer models to achieve the prediction of chemical toxicity has emerged. In the meantime, as researchers increasingly pay attention to understanding the interaction mechanisms between exogenous chemical substances and the body from the system level, and multiomics technologies develop rapidly such as genomics, transcriptomics, proteomics, and metabolomics, huge amounts of data have been generated, providing rich information resources for studying the interactions between chemical substances and biological molecules. System toxicology and network toxicology have also developed accordingly. Of these, network toxicology can integrate these multiomics data to construct biomolecular networks, and then quickly predict the key toxicological targets and pathways of chemicals at the molecular level. This paper outlined the concept and development of network toxicology, summarized the main methods and supporting tools of network toxicology research, expounded the application status of network toxicology in studying potential toxicity of exogenous chemicals such as agricultural chemicals, environmental pollutants, industrial chemicals, and foodborne chemicals, and analyzed the development prospects and limitations of network toxicology research. This paper aimed to provide a reference for the application of network toxicology in other fields.

OBJECTIVE: To explore the potential role of mRNA m7G modification in the pathogenesis of human adenocarcinoma of esophagogastric junction (AEG). METHODS: Pathological tissue specimens from four AEG patients who underwent surgical treatment at the People's Hospital Affiliated to Jiangsu University between 2018 and 2019 were selected. Tumor tissues and adjacent normal tissues were collected from these patients. RNA was extracted from both tissue types and subjected to m7G methylated RNA immunoprecipitation sequencing (m7G-MeRIP-seq) to analyze the patterns of m7G modification, the characteristics of differential m7G modification sites, the differentially expressed mRNA, and the correlation between m7G modification and mRNA expression levels. Differential m7G-modified genes (MSH6, BRCA1, and SOX9) were further validated using methylated RNA immunoprecipitation quantitative PCR (MeRIP-qPCR), while the expression of METTL1 and WDR4 genes was examined by real-time quantitative PCR (RT-qPCR). This study was approved by the Medical Ethics Committee of the People's Hospital Affiliated to Jiangsu University (Ethics No. 20150083). RESULTS: m7G-MeRIP-seq analysis revealed that m7G modifications in both AEG and adjacent normal tissues were predominantly located in the GC-rich region surrounding the internal start codon of mRNA. Differential m7G modification sites between the two groups were closely associated with cancer-related genes. mRNA library analysis showed that differentially expressed mRNA were predominantly upregulated in AEG tissues and downregulated in adjacent normal tissues. Cross-analysis indicated that genes with hypermethylation tended to exhibit upregulated expression, while genes with hypomethylation were typically downregulated in AEG tissues. MeRIP-qPCR validation confirmed that the mRNA expression of MSH6, BRCA1, and SOX9 were significantly upregulated in AEG tissues compared to adjacent normal tissues (AEG vs. normal, P < 0.05). RT-qPCR results demonstrated that the mRNA expression levels of METTL1 and WDR4 were also upregulated in AEG tissues (AEG vs. normal, P < 0.000 5). CONCLUSION These findings suggest that mRNA m7G modification plays a significant role in the development of AEG. Furthermore, proteins as METTL1 and WDR4 may facilitate AEG progression by regulating mRNA m7G modification. These results provide valuable insights into the molecular mechanisms underlying AEG and may inform future therapeutic strategies for this malignancy.
Humans ; RNA, Messenger/metabolism* ; Adenocarcinoma/pathology* ; Esophagogastric Junction/metabolism* ; Esophageal Neoplasms/metabolism* ; Gene Expression Regulation, Neoplastic ; Female ; Male ; Middle Aged ; DNA Methylation ; Methyltransferases/metabolism* ; Stomach Neoplasms/genetics*

OBJECTIVE: To explore the association between single nucleotide polymorphism (SNP) rs2073618 and rs3102735 of the TNFRSF11B gene and the susceptibility to gastric cancer. METHODS: A case-control study was conducted. A total of 577 patients with primary gastric cancer treated at Zhenjiang First People's Hospital from May 2013 to June 2017 were selected as the case group, and 678 healthy individuals who underwent physical examinations at the same hospital during the same period were enrolled as the control group. Blood samples were collected from both groups, and genomic DNA was extracted. The target gene fragments were amplified using PCR, and genotyping was performed using the Snapshot technique. Statistical analysis was conducted using SPSS v2.0 software. This study was approved by the Medical Ethics Committee of the Zhenjiang First People's Hospital (Ethics No. 20150083). RESULTS: The smoking rate was significantly higher in the case group than in the control group (P = 0.006). The T>C polymorphism at the rs3102735 locus of the TNFRSF11B gene was significantly associated with an increased risk of gastric cancer (CC vs. TT: OR = 2.164, 95%CI = 1.063~4.406, P = 0.030). In contrast, the rs2073618 polymorphism did not show a significant association with gastric cancer susceptibility (P > 0.05). Stratified analysis by age, gender, smoking status, and drinking status revealed no significant association between the rs2073618 polymorphism and gastric cancer susceptibility (P > 0.05). However, the rs3102735 polymorphism showed a significant association with gastric cancer risk in individuals over 62 years of age (CC vs. TT: OR = 5.44, 95%CI = 1.54~19.21, P = 0.003). CONCLUSION The rs3102735 polymorphism of the TNFRSF11B gene may be associated with susceptibility to gastric cancer, particularly in older populations. This polymorphism could serve as a potential indicator for identifying high-risk groups for gastric cancer.
Humans ; Stomach Neoplasms/genetics* ; Polymorphism, Single Nucleotide ; Male ; Female ; Genetic Predisposition to Disease ; Middle Aged ; Case-Control Studies ; Osteoprotegerin/genetics* ; Aged ; Adult ; Genotype

Objective:To analyze risk factors for early trauma-induced coagulopathy (TIC) in pediatric patients with moderate-to-severe traumatic brain injury (msTBI), develop a predictive model and evaluate its predictive performance.Methods:A retrospective cohort study was conducted to analyze the clinical data of 290 pediatric patients with msTBI who were admitted to Children′s Hospital of Soochow University between January 2016 and December 2024, including 188 boys and 102 girls, aged 0.2-15.7 years [5.2(2.8, 9.3)years]. Based on the coagulation test results at admission, the patients were divided into TIC group ( n=162) and non-TIC group ( n=128). The patients were randomly allocated into training set ( n=203) and validation set ( n=87) at a ratio of 7∶3. Demographic characteristics, clinical data, vital signs, imaging findings, arterial blood gas analysis results, and coagulation profiles of the patients were collected. Univariate analysis and Lasso regression analysis were used to identify risk factors associated with early TIC in children with msTBI and multivariate Logistic regression analysis was performed to determine independent risk factors and construct a predictive model. The model′s discrimination and calibration were evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), Hosmer-Lemeshow (H-L) test, and calibration curve. Its clinical utility was assessed through decision curve analysis (DCA). Results:Significant differences were observed between the TIC group and non-TIC group in terms of age, weight, time from injury to admission, child′s Glasgow coma scale (CGCS) score, pediatric trauma score (PTS), shock index, heart rate, respiratory rate, systolic blood pressure, Rotterdam CT score, intraventricular hemorrhage, cerebral contusion, brain herniation, long bone fracture, pelvic fracture, hemopneumothorax, pulmonary contusion, intra-abdominal organ injury, actual bicarbonate, base excess, base excess in the extracellular fluid, blood glucose, hemoglobin (Hb), osmolarity, blood calcium, anion gap, blood lactate, prothrombin time, activated partial thromboplastin time, international normalized ratio, and platelet count ( P<0.05). With coagulation-related variables excluded, the following features were identified with Lasso regression including CGCS score, PTS, heart rate, systolic blood pressure, long bone fracture, blood glucose, and Hb. Multivariate Logistic regression analysis revealed that CGCS score≤8 points ( OR=3.05, 95% CI 1.65, 5.63), PTS>5 points ( OR=0.45, 95% CI 0.23, 0.89), systolic blood pressure ( OR=0.98, 95% CI 0.97, 0.99), blood glucose ( OR=1.09, 95% CI 1.01, 1.17), and long bone fracture ( OR=2.47, 95% CI 1.13, 5.42) were influencing factors for early TIC in children with msTBI ( P<0.05). The regression equation of the predictive model was established as follows: Logit[ P/(1- P)]=1.01×"CGCS score≤8 points"-0.69×"PTS>5 points"- 0.02×"systolic blood pressure"+0.89×"long bone fracture"+0.08×"blood glucose"+1.32. The ROC curve analysis showed that the training set had an AUC of 0.86 (95% CI 0.78, 0.94), with sensitivity and specificity of 76.6% and 92.5%, while the AUC was 0.80 (95% CI 0.74, 0.86), with sensitivity and specificity of 75.7% and 79.6% in the validation set. H-L test results showed a χ2 value of 8.18 ( P=0.416) in the training set and 5.30 ( P=0.216) in the validation set. The calibration curves for both sets demonstrated good agreement with the actual curves, indicating that the predicted probabilities closely matched the observed probabilities. The DCA results indicated that both the training set and validation set demonstrated positive net benefits within threshold probabilities ranges of 10%-100% and 15%-96%. Conclusions:Independent risk factors for early TIC in pediatric msTBI patients include CGCS score≤ 8 points, PTS≤5 points, low systolic blood pressure, long bone fracture, and high blood glucose. The predictive model constructed based on these factors demonstrates favorable predictive performance and clinical application value.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Objective: To investigate the expressions of GPR15 and FOXP3 in colorectal carcinoma(CRC) tissues and their clinical prognostic values. Methods : A total of 132 patients with CRC underwent radical surgery were collected. The control group selected the normal mucosal tissues more than 5 cm away from the edge of the cancer focus. Immunohistochemistry(Envision two-step method) was used to detect the expression levels of GPR15 and FOXP3 in CRC and adjacent tissues, and analyze their relationships with clinicopathological factors of colorectal cancer. Kaplan-Meier method was used to draw the survival curve to analyze the correlation between the expressions of GPR15 and FOXP3 and the survival prognosis of patients with CRC. The factors influencing prognosis of patients with colorectal cancer were analyzed by Cox regression. Results : The immunohistochemistry showed that the expression levels of GPR15 and FOXP3 in CRC were significantly higher than those in normal colorectal mucosal tissues(P<0.05). The expression of GPR15 in CRC tissues was correlated with location, nerve invasion and TNM stage; FOXP3 expression was correlated with sex(P<0.05).Both expressions were not significantly correlated with the clinicopathologic features of age, tumor size, differentiation degree, tissue type, depth of invasion, tumor budding, vascular invasion and lymph node metastasis. Correlation analysis showed that there was no significant correlation between GPR15 and FOXP3 expression(Kappa=-0.019,P>0.05). The survival prognosis of GPR15 positive group was significantly worse than that of negative group(log-rank: χ2=4.3,P=0.039);while the survival prognosis of FOXP3 positive group was significantly better than that of negative group(log-rank: χ2=7.3,P=0.007).Age ≤55 years, positive GPR15 and negative FOXP3 were independent risk factors for poor prognosis in patients with CRC(P<0.05). Conclusion The expression levels of GPR15 and FOXP3 in CRC are significantly higher than those in paracancer tissues, GPR15 and FOXP3 are expected to become new tumor markers for early screening, accurate treatment and prognosis assessment of CRC.

Objective:To investigate the expression of protein kinase D2(PRKD2)in bladder cancer(BLCA)tissue using bioinformatics analysis method and its effect on the prognosis of BLCA patients,and to clarify the role of PRKD2 in the occurrence and development of BLCA.Methods:The data from 9 normal bladder samples,19 BLCA paracancerous samples,and 407 BLCA tumor samples were downloaded from the UCSC Cancer Genome Database.The Mann-Whitney U test was applied to analyze the difference in expression of PRKD2 mRNA in BLCA tumor and normal bladder tissues,and the Human Protein Atlas(HPA)database was used for proteomic validation.DESeq2 package in R software was applied to screen the differentially expressed genes(DEGs)in BLCA tissue in PRKD2 low-and high-expression groups.The co-expression heatmaps of PRKD2 were plotted using the ggplot2 package,Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)were used for functional annotation analysis and pathway enrichment analysis of DEGs,and Gene Set Enrichment Analysis(GSEA)was used to obtain the gene sets that were significantly enriched for DEGs.The BLCA samples were divided into low-and high-expression groups according to the expression level of PRKD2,and the correlations between PRKD2 expression and immune cell infiltration in the BLCA patients were analyzed with GSVA package.The relationship between PRKD2 and prognosis of BLCA patients was further analyzed using the survival package and the survminer package.The PRKD2 gene mutations in BLCA tissue were analyzed using the cBioPortal database.The cystitis,bladder polyp and BLCA tissues were collected,and the expression levels of interleukin-17F(IL-17F)protein in BLCA and control tissues were detected using immunohistochemical staining technique.Results:PRKD2 was highly expressed in a variety of malignant tumors,and the expression levels of PRKD2 mRNA and protein in BLCA tissue were significantly increased compared with those in normal bladder tissue(P＜0.05).Single gene differential analysis of PRKD2 yielded a total of 1 058 DEGs,of which a total of 29 genes were up-regulated and 1 029 were down-regulated.The results of GO functional enrichment analysis showed that DEGs were mainly enriched in the biological process(BP),such as chemical stimuli involved in sensory perception,Cajal body,and endopeptidase inhibitor activity.The results of KEGG pathway analysis showed that DEGs were mainly enriched in the pathway of Staphylococcus aureus infection and the pathway of maturity onset diabetes of the young.GSEA analysis showed that DEGs were mainly enriched in the Notch signaling pathway,the retinoic acid-inducible gene-Ⅰ(RIG-Ⅰ)-like receptor signaling pathway,the cytoplasmic DNA screening pathway,the base excision repair signaling pathway,natural killer(NK)cell-mediated cytotoxicity signaling pathway and T cell receptor signaling pathway.The results of immune infiltration analysis indicated that the expression of PRKD2 was positively correlated with five types of cells,such as activated dendritic cells(aDC),NK CD56dim cells and central memory T cells(Tcm)(P＜0.05),and negatively correlated with three types of immune cells,including macrophages,effector memory T cells(Tem)and plasmacytoid dendritic cells(pDC)(P＜0.05).The clinical characteristic subgroup analysis results showed that the expression levels of PRKD2 mRNA in BLCA patients who were over 70 years old and developed lymphovascular invasion were decreased(P＜0.05);the overall survival(OS),disease-specific survival(DSS)and progression-free interval(PFI)in the BLCA patients with PRKD2 high expression were significantly longer than those with PRKD2 low expression(P＜0.05).The univariate and multivariate Cox analyses indicated that distant metastasis,primary therapy outcome and clinicopathologic stage were the important factors affecting BLCA prognosis.About 9％patients had PRKD2 gene mutations,including missense mutation,gene amplification,mRNA low or high expression,and multi-motif mutation.The immunohistochemistry results showed that the expression level of IL-17F protein in BLCA tissue was significantly higher than that in cystitis tissue(P＜0.05).Conclusion:The expression level of PRKD2 in BLCA tissue is obviously increased,which could up-regulate the expression of IL-17F protein,and the decrease of PRKD2 protein expression may be a potential factor for the poor prognosis of BLCA patients.