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Objective In this study, a strain of colistin and tigecycline-resistant bacteria isolated in 2009 was analyzed, and the structure of drug-resistant plasmid and genetic environment were discussed, so as to provide basis for the prevention and control of multidrug-resistant bacteria. Methods A strain (GZ12244) with positive mcr and tet(M) was obtained by screening colistin and tigecycline resistance genes. Vitek-2 was used for strain identification, and the drug sensitivity test was carried out by broth dilution method. The molecular typing, drug resistance genes, insertion sequences, plasmid structure and genetic background were analyzed by genome-wide sequencing and bioinformatics. Results Strain GZ12244 is Klebsiella pneumoniae, which is resistant to colistin B, tigecycline, cefuroxime and tetracycline, and carries a variety of drug-resistant related genes such as mcr-1 and tet(M), and some of the drug-resistant genes with antibiotic efflux and antibiotic target change have amino acid substitution mutations. Mcr-1 and tet(M) coexist in a plasmid, and mcr-1 flanked by two insertion sequences ISApl1. There are insertion sequences such as IS15, IS1D and ISEc63 in the upstream and downstream of tet(M) gene. Conclusion Klebsiella pneumoniae GZ12244 is a multidrug-resistant strain. The drug-resistant gene exists in plasmid, and the mobile elements in upstream and downstream may spread the drug-resistant gene.
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Optical genome mapping (OGM) is a novel non-sequencing genetic analysis technology that enables high-precision analysis of structural variations across the entire genome. It possesses unique technical advantages, and its procedural simplicity makes it easy to implement. In recent years, the application efficacy of OGM technology in the analysis of genomic structural variations in hematologic malignancies has been widely validated and recognized. Increasing evidence indicates that the application of OGM technology can help improve the genetic diagnosis, prognostic stratification and treatment guidance of hematologic malignancies. This article draws upon pertinent reports from the 65th American Society of Hematology Annual Meeting to provide an overview of the progress in applying OGM technology for the precise diagnosis and treatment of hematologic malignancies.
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Objective To compare the categorical agreement between drug susceptibility testing(DST)and whole genome sequencing(WGS)for the detection of drug resistance in Mycobacterium tuberculosis(MTB),and to explore the characteristics of WGS for MTB drug resistance detection.Methods A total of 71 MTB clinical isolates retained in West China Hospital of Sichuan University from 2018 to 2020 were included in this study.The MTB strains were tested for resistance to 14 anti-tuberculosis drugs,including Isoniazid(INH),Rifampicin(RIF),Rifabutin(RFB),Ethambutol(EMB),Streptomycin(SM),Moxifloxacin(MFX),Ofloxacin(OFX),Levofloxacin(LFX),Amikacin(AMK),Kanamycin(KAN),Capreomycin(CPM),Para-aminosalicylic acid(PAS),Ethionamide(ETH)and Clofazimine(CLO),using both DST(colorimetric redox indicator meth-od)and WGS methods.Kappa test was performed to analyze the results of drug resistance detection for both methods.Results Based on DST and WGS methods to detect anti-tuberculosis drug resistance in seventy-one MTB clinical isolates,the results showed that the agreement rate of RIF,RFB,SM,MFX,OFX and LFX ex-ceeded 90.00％,and the kappa values were all greater than 0.80,with near perfect agreement;The agreement rates of INH and EMB were 84.51％and 81.69％,and Kappa values were 0.68 and 0.54,respectively,with fair agreement.No more than two drug resistant MTB strains of AMK and KAN were detected by both meth-ods,and the resistance rate was less than 3.00％.The agreement rates of CPM,ETH,PAS,and CLO ranged from 61.97％to 91.55％,and the Kappa values were less than 0.40,with slight or fair agreement.Conclusion There are differences in the ability of WGS to detect resistance to various anti-tuberculosis drugs,and it is more effective in detecting resistance to six anti-tuberculosis drugs,including RIF,RFB,SM,MFX,OFX and LFX,while there are still certain differences in detecting resistance to other anti-tuberculosis drugs compared with DST.It is necessary to further clarify the detailed resistance mechanisms of relevant anti-tu-berculosis drugs and to explore the standardization of WGS for drug resistance detection.
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Abstact:Objective To investigate the gene expression differences between left-sided colon cancer and right-sided colon cancer and the mechanism differences between the colorectal cancer core drug pairs of Sophorae Flavescentis Radix-Sargentodoxae Caulis-Scutellariae Barbatae Herba acting on left-sided and right-sided colon cancer.Methods The transcriptome data of 134 patients with left-sided colon cancer and 194 patients with right-sided colon cancer from The Cancer Genome Atlas(TCGA)were downloaded,and the R software was applied to realize the differential gene analysis of the two groups and the enrichment analysis of Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway;the BATMAN-TCM database was used to obtain the active ingredients and targets of the drug pair of Sophorae Flavescentis Radix-Sargentodoxae Caulis-Scutellariae Barbatae Herba,and based on the different genes of the left-and right-sided colon cancers,KEGG enrichment analysis of the drug pair-left/right-sided colon cancers was performed respectively,and the protein-protein-interaction(PPI)network was constructed to compare the differences of the biosignaling pathways enriched by the drug pairs for the treatment of left-and right-sided colon cancers,as well as the differences of the key target points.Results There were 6 051 differentially expressed genes common to left-and right-sided colon cancers relative to normal paracancerous tissues,1958 differentially expressed genes specific to left-sided colon cancer,and 1739 differentially expressed genes specific to right-sided colon cancer;14 KEGG-enriched pathways specific to left-sided colon cancer,and 23 KEGG-enriched pathways specific to right-sided colon cancer.There were 85 active compounds in the drug-pair of Sophorae Flavescentis Radix-Sargentodoxae Caulis-Scutellariae Barbatae Herba,corresponding to a total of 469 targets.The drug-pair-left-sided colon cancer targets were enriched in 10 KEGG signaling pathways,with the key targets being DRD2,CACNA1C,HTR3A,COMT,and TH;and the drug-pair-right-sided colon cancer targets were enriched in 1 KEGG signaling pathway,with the core targets being HTR3A,DRD2 TH,AGT,GRIN2B.Conclusion There are gene expression differences between left-and right-sided colon cancers:left-sided colon cancer is associated with abnormal immune function,abnormal AMPK signaling pathway and other mechanisms,and right-sided colon cancer is associated with neutrophil extracellular trap formation,alcoholism,abnormal Hippo signaling pathway and other mechanisms.In addition to regulating cell cycle and essential amino acid metabolism and other mechanisms,Sophorae Flavescentis Radix-Sargentodoxae Caulis-Scutellariae Barbatae Herba drug pairs have specific effects on regulating the intestinal endocrine function of the left-sided colon cancer,inhibiting inflammatory response of the right-sided colon cancer,and may also have mood-regulating effects on patients with colon cancer.
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Objective To investigate the genetic risk factors of deep vein thrombosis(DVT)after trauma.Methods In a nested case-control study,50 patients with DVT after traumatic lower extremity fractures and 50 patients without DVT were recruited.The two groups were matched with gender,age and fracture sites.Preoperative venography was performed to diagnose DVT in trauma patients.Genome wide association study(GWAS)was used to investigate the genetic risk factors for preoperative DVT after traumatic lower ex-tremity fractures.Genomic DNA in leukocytes from blood sample was extracted and used for GWAS.Results GWAS was conducted based on 2 662 single nucleotide variants(SNV)which were dispersed in 144 interested genes.Ten genes were found to have signifi-cant association with trauma-related DVT,including cofactors of hemostasis mechanism,i.e.,THBD,F5,SERPIND1 and ITGA2,the factors related to vitamin K-dependent(VKD)carboxylation,i.e.,GGCX and CALU,and the members of cytochrome P450 family,i.e.,CYP1A1,CYP3A4,CYP2C19 and CYP2B6.Conclusion DVT after trauma might be regulated by the cofactors of hemostasis mechanism,the factors related to VKD carboxylation and the members of cytochrome P450 family.The results of our study may provide reference and inspiration for genetic susceptibility of preoperative DVT after trauma.
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Objective To explore the role of retinol binding protein 7(RBP7)in breast cancer by bioinformatics.Methods R sofrware was used to explore the differential expression of the RBP7 gene in breast cancer by the cancer genome atlas(TCGA)dataset and the human protein atlas(HPA).Relationship between RBP7 and clinical data of breast cancer was evaluated by Kaplan-Meier survival analysis and receiver operating characteristic(ROC)curves.Correlation between high and low RBP7 expression groups and different tumor-infiltrating immune cells(TIICs)were analyzed based on the TCGA database.Gene set enrichment analysis(GSEA)was used to assess the distribute trends of RBP7 in gene tables sorted by phenotypic relatedness.Results RBP7 mRNA expression levels were down-regulated in breast cancer compared to paracancerous tissues,which were expressed in the nucleus.ROC curve analysis showed that the area under curve(AUC)of RBP7 for the diagnosis of breast cancer was 0.943(95%CI:0.926～0.960),and the best cut-off value of RBP7 was 6.29,with a sensitivity and specificity of 82.32%and 93.69%,respectively.Kaplan-Meier survival analysis showed that low expression of RBP7 was associated with overall survival rate in breast cancer patients(HR=0.68,95%CI:0.49～0.93,P=0.017),indicating that RBP7 was an independent risk factor for breast cancer.Spearman correlation showed that RBP7 was positively associated with pDC cells and NK cells(r=0.290,0.253,all P<0.05),and negatively associated with Th2 cells(r=-0.217,P<0.05)in breast cancer.GSEA showed that RBP7 was enriched in pathways such as adipogenesis,ribosome,peptiden ligand binding receptors,and calcium signaling pathway(all P<0.001).Conclusion RBP7 affects the occurrence and development of breast cancer,which may be a potential biomarker and therapeutic target for breast cancer.
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Objective To construct and evaluate a disulfidptosis-related genes(DRGs)prognostic risk model for hepatocellular carcinoma(HCC)based on the cancer genome atlas(TCGA)database.Methods The expression of 15 DRGs in 371 HCC samples and 50 adjacent cancer samples in the TCGA database was analyzed using bioinformatics methods,and then gene ontology(GO)functional annotation,Kyoto encyclopedia of genes and genomes(KEGG)enrichment analysis and Kaplan-Meier(KM)survival analysis were performed.Statistical significant DRGs were screened through univariate COX regression analysis,and key DRGs were selected through LASSO regression analysis and multivariate COX regression analysis to construct a prognostic risk model.HCC patients were divided into high-risk and low-risk groups based on risk scores,and the KM survival curves and time-dependent receiver operator characteristic(ROC)curves were created to validate and evaluate prognostic risk models.Results Compared with the adjacent cancer samples,FLNA,MYH9,TLN1,ACTB,MYL6,CAPZB,DSTN,ACTN4,SLC7A11,INF2,CD2AP,PDLIM1,and FLNB were all upregulated in the 15 DRGs of HCC samples,and the differences were significant(t=1 793～6 310,all P<0.001).According to GO functional annotation and KEGG enrichment analysis,DRGs were closely related to biological processes or pathways related to actin cytoskeleton and cell adhesion.The results of KM survival analysis showed that the survival rate of the high expression group of SLC7A11,INF2,CD2AP,MYL6,and ACTB were lower than that of the low expression group[HR=1.46(1.03～2.07)～1.93(1.36～2.75),all P<0.05].Univariate COX regression analysis,LASSO analysis,and multivariate COX regression analysis were used to construct a prognostic risk model,with risk score=(0.247×SLC7A11)+(0.289×INF2)+(0.076×CD2AP)+(0.06×MYL6).The risk score of the sample in this model was calculated,and the higher the risk score,the more HCC patients with poor prognosis.KM survival analysis showed that the overall survival rate of the high-risk group was lower than that of the low-risk group.The AUC values for 1,3,and 5 years were 0.709,0.661,and 0.648,respectively.Multivariate COX regression analysis showed that SLC7A11[HR=1.832(1.274～2.636),P=0.001]was an independent prognostic risk factor.Conclusion The prognostic risk model was constructed by four DRGs,which has a certain role in predicting the prognosis of HCC patients.
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Objective:To illustrate the characteristics of the distribution of prophages among the Group A Streptococcus(GAS) by mining the existing whole genome sequencing of the GAS, performing bioinformatic analyses, extracting data about prophages, and analyzing the state of prophages in the genome and genetic composition of some prophages. Methods:It was a retrospective study.Genome assembly sequences of GAS reported in GenBank till May 2020 were collected, and the important background information of these strains was sorted out to create a local genomic database.A phylogenetic tree of the whole genome of GAS was conducted using the bioinformatics software.The core genome was analyzed, and potential prophages and their integrity in the genome were predicted to obtain the characteristics of the distribution of prophages.Genotype types, number of core genes, and number, length and carrying rate of prophages in the database for GAS were analyzed.Results:A database containing the genome sequence of 2 529 GAS strains was established, involving 140 emm genotypes.These strains were isolated from 19 countries from East Asia, Europe, America and Oceania.Stratified by the disease background, these strains were mainly divided into invasive infection, non-invasive infection and immune sequelae.Prophage analysis of 1 798 genomes showed that at least one complete prophage was detected in 1 366 (76.0%) genomes.The number of complete prophages of each strain ranged from 0 to 6, and the length ranged from 32.8 to 62.6 kb, which was mainly 30-40 kb in length.The phiHKUssa, phiHKUvir and phiHKU488 were the most common prophages present in dominant clones circulated in China in recent years, which mainly carried virulence genes like the speC, spd1 and ssa. Conclusions:Prophages are widely distributed in the genome of GAS, which are of great significance in the evolution and expansion of dominating clones and thus reshape the population structure within the emm genotype.The establishment of a local genome database provides important baseline data for molecular epidemiological surveillance.
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BACKGROUND:Many clinical research observations have indicated a close association between rheumatoid arthritis and osteoporosis as well as bone mineral density(BMD).However,it remains unclear whether there is a causal genetic relationship between rheumatoid arthritis and the development of osteoporosis and alterations of BMD. OBJECTIVE:To assess the potential causal relationship between rheumatoid arthritis and osteoporosis as well as BMD using a two-sample Mendelian randomization approach,provide meaningful insights from a genetic perspective into the underlying mechanisms and offer a reference for early prevention of osteoporosis and improvement in the progression of the disease. METHODS:We conducted a study using data from publicly available genome-wide association studies databases to identify single nucleotide polymorphisms associated with rheumatoid arthritis as instrumental variables(P＜5×10-8).The main outcomes of the study included osteoporosis and BMD at five different sites,including total body BMD,lumbar spine BMD,femoral neck BMD,heel BMD,and forearm BMD.The inverse variance-weighted method was used as the primary analysis method to evaluate causal effects.Weighted median,simple median,weighted mode and MR-Egger regression were used as supplementary analyses.Causal relationships between rheumatoid arthritis and the risk of osteoporosis and BMD were assessed using odds ratios(OR)and 95%confidence intervals(CI).Heterogeneity was assessed using Cochran's Q test and horizontal pleiotropy was evaluated using MR-Egger intercept tests. RESULTS AND CONCLUSION:The inverse variance-weighted analysis demonstrated a positive association between genetically predicted rheumatoid arthritis and osteoporosis(OR=1.123,95%CI:1.077-1.171;P=4.02×10-8).Heterogeneity test(P=0.388)indicated no significant heterogeneity among the single nucleotide polymorphisms.MR-Egger intercept(P=0.571)tests did not detect horizontal pleiotropy,and sensitivity analysis showed no evidence of bias in the study results.There was no causal relationship between rheumatoid arthritis and BMD at the five different sites.The total body BMD(OR=1.000,95%CI:0.988-1.012;P=0.925),lumbar spine BMD(OR=0.999,95%CI:0.982-1.016;P=0.937),femoral neck BMD(OR=1.001,95%CI:0.986-1.016;P=0.866),heel BMD(OR=0.996,95%CI:0.989-1.004;P=0.419),and forearm BMD(OR=1.063,95%CI:0.970-1.031;P=0.996)indicated no significant association.MR-Egger intercept analysis did not detect potential horizontal pleiotropy(total body BMD:P=0.253;lumbar spine BMD:P=0.638;femoral neck BMD:P=0.553;heel BMD:P=0.444;forearm BMD:P=0.079).Rheumatoid arthritis may contribute to the development of osteoporosis through the interaction between chronic inflammation and bone formation,resorption,and absorption.Additionally,the use of glucocorticoids and the presence of autoantibodies(such as anti-citrullinated protein antibody)in patients with rheumatoid arthritis showed associations with osteoporosis.Future research should focus on monitoring systemic inflammatory markers,standardized use of glucocorticoids,and regular screening for osteoporosis risk in patients with rheumatoid arthritis.
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BACKGROUND:Observational studies have suggested that statins may have a protective effect against osteoarthritis,including knee osteoarthritis and hip osteoarthritis.However,the association between statins and the risk of osteoarthritis remains unclear. OBJECTIVE:To investigate the association between statins and the risk of osteoarthritis through Mendelian randomization analysis using summary data from large-scale population-based genome-wide association studies(GWAS). METHODS:Firstly,single nucleotide polymorphism data related to statins were obtained from the latest 9th edition of the FinnGen database,while data of osteoarthritis,knee osteoarthritis and hip osteoarthritis were obtained from the IEU Open GWAS,UK Biobank,and ArcOGEN(Genetics of Osteoarthritis)databases,respectively.The inverse variance weighted method was used as the primary analysis approach to evaluate the causal effects.The weighted median method,simple median method,weighted mode-based method,and MR-Egger regression were used as supplementary analyses.The causal relationship between statins and the risk of osteoarthritis,knee osteoarthritis and hip osteoarthritis was assessed using odds ratios(OR)with 95%confidence intervals(CI).Sensitivity analyses were conducted to validate the reliability of the results,including the Cochran's Q test for heterogeneity and the MR-Egger-intercept test for horizontal pleiotropy,as well as leave-one-out analysis to identify potentially influential single nucleotide polymorphisms. RESULTS AND CONCLUSION:The inverse variance weighted analysis demonstrated a negative causal relationship between genetically predicted statins and the risk of osteoarthritis(OR=0.998,95%CI:0.996-0.999,P=0.01),knee osteoarthritis(OR=0.964,95%CI:0.940-0.989,P=0.005),and hip osteoarthritis(OR=0.928,95%CI:0.901-0.955,P=4.28×10-7).MR-Egger intercept analysis did not detect potential horizontal pleiotropy(osteoarthritis:P=0.658;knee osteoarthritis:P=0.600;hip osteoarthritis:P=0.141).The results of this study provide evidence that statins reduce the risks of osteoarthritis,knee osteoarthritis and hip osteoarthritis as described in observational studies.Further research is needed to explore the specific mechanisms of statin treatment for osteoarthritis.
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BACKGROUND:Rheumatoid arthritis is a chronic systemic autoimmune disease.It is important to study the immunological changes involved in it for diagnosis and treatment. OBJECTIVE:To identify immune-related biomarkers associated with rheumatoid arthritis utilizing bioinformatics techniques and examine alterations in immune cell infiltration as well as the relationship between immune cells and biomarkers. METHODS:Differential expression analysis was used to identify the immune-related genes that were up-regulated in rheumatoid arthritis based on the GEO and Immport databases.Kyoto encyclopedia of genes and genomes(KEGG)and gene ontology(GO)enrichment analyses were used to investigate the possible function of these elevated genes.The immunological characteristic genes associated with rheumatoid arthritis were screened using least absolute shrinkage and selection operator(Lasso)and support vector machine recursive feature elimination(SVM-RFE).Independent datasets were used for difference validation,and the diagnostic performance was evaluated by plotting receiver operating characteristic curves for feature genes.Immune cell infiltration was used to analyze the differential profile of immune cells in rheumatoid arthritis and the correlation between the characterized genes and immune cells.In order to ascertain the causal relationship between monocytes and rheumatoid arthritis in immune cells,Mendelian randomization analysis was ultimately employed. RESULTS AND CONCLUSION:There were 39 upregulated differentially expressed genes in rheumatoid arthritis.The genes were primarily enriched in chemotaxis,cytokine activity,and immune receptor activity,according to GO enrichment analysis,while kEGG enrichment analysis revealed that the genes were considerably enriched in the tumor necrosis factor signaling pathway and peripheral leukocyte migration.Lasso and SVM-RFE identified five feature genes:CXCL13,SDC1,IGLC1,PLXNC1,and SLC29A3.Independent dataset validation of the feature genes found them to be similarly highly expressed in rheumatoid arthritis samples,with area under the curve values greater than 0.8 for all five feature genes in both datasets.Immune cell infiltration indicated that most immune cells,including natural killer cells and monocytes,exhibited increased levels of infiltration in rheumatoid arthritis samples.The correlation analysis revealed a significant positive correlation between memory B cells and immature B cells and these five feature genes.Correlation analysis showed that the five feature genes were positively correlated with memory B cells and immature B cells.The inverse variance weighting method revealed that monocytes were associated with the risk of developing rheumatoid arthritis.
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BACKGROUND:Osteonecrosis due to drugs is a serious adverse reaction occurring after the application of such drugs.Increasing evidence suggests that the gut microbiota composition is associated with osteonecrosis due to drugs.However,the causal relationship of the gut microbiota to osteonecrosis due to drugs is still unclear. OBJECTIVE:To evaluate the potential causal relationship between the gut microbiota and the risk of osteonecrosis due to drugs using the Mendelian randomization method. METHODS:A two-sample Mendelian randomization study was performed using the summary statistics of gut microbiota from the largest available genome-wide association study meta-analysis(n=13 266)conducted by the MiBioGen consortium as well as the summary statistics of osteonecrosis due to drugs obtained from the FinnGen consortium R9 release data(264 cases and 377 013 controls).Inverse variance weighted,MR-Egger,weighted median,weighted model and simple model were used to examine the causal association between gut microbiota and osteonecrosis due to drugs.Sensitivity analysis was used to test whether the results of the Mendelian randomization analysis were reliable.Reverse Mendelian randomization analysis was performed on all the bacteria as an outcome for effect analysis and sensitivity analysis. RESULTS AND CONCLUSION:Inverse variance weighted estimates suggested that Lentisphaerae(phylum),Lentisphaeria(class),Melainabacteria(class),Gastranaerophilales(order),Rhodospirillales(order),Victivallales(order)and Bifidobacterium(genus)had protective causal effects on osteonecrosis due to drugs.Methanobacteria(class),Bacillales(order),Methanobacteriaceae(family),Lachnospiraceae(family),Methanobacteriales(order),Holdemania(genus),Holdemania(UCG010 group)(genus),Odoribacter(genus)and Tyzzerella3(genus)had negative causal effects on osteonecrosis due to drugs.According to the results of reverse Mendelian randomization analysis,Clostridiaceae1(family),Peptostreptococcaceae(family),Streptococcaceae(family),Clostridiumsensustricto1(genus)and Streptococcus(genus)showed negative causal effects on osteonecrosis due to drugs.However,Eisenbergiella(genus)showed protective causal effects on osteonecrosis due to drugs.None of the bidirectional sensitivity analysis revealed heterogeneity or horizontal pleiotropy.When gut microbiota were used as exposure and osteonecrosis due to drugs as the outcome,Mendelian randomization analysis found that seven bacterial traits were positively correlated to osteonecrosis due to drugs,nine bacterial traits were negatively related to osteonecrosis due to drugs.When osteonecrosis due to drugs were used as exposure and gut microbiota as the outcome,reverse Mendelian randomization analysis found a negative correlated relationship with five bacterial traits and a positive causal relationship with one bacterial trait.By changing the diversity and composition of gut microbiota,it is expected to improve the incidence and prognosis of osteonecrosis due to drugs,providing new ideas for the study of orthopedic diseases.
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BACKGROUND:Observational studies have suggested that statin drugs may have a protective effect on bone density,making them a potential treatment option for osteoporosis. OBJECTIVE:To evaluate the causal relationship between drug target-mediated lipid phenotypes and bone mineral density(BMD)using Mendelian randomization methods. METHODS:We obtained single nucleotide polymorphismsrelated to statin drugs and BMD data from the IEU Open GWAS database.The primary analysis method was the inverse variance weighted method,and we also used weighted median,simple median,weighted mode,and MR-Egger regression.We usedβ values and 95%confidence intervals(CI)to assess the causal relationship between statin drugs and BMD.Additionally,we conducted sensitivity analyses to validate the results,assessed heterogeneity using Cochran's Q test,examined for horizontal pleiotropy using the MR-Egger intercept test,and performed leave-one-out analyses to determine if individual or multiplesingle nucleotide polymorphism influenced the results. RESULTS AND CONCLUSION:There was a significant association between the statin target of action,3-hydroxy-3-methyl glutaryl coenzyme A reductase-mediated low-density lipoprotein cholesterol,and heel bone BMD(β=-0.086,95%CI:-0.117 to-0.055,P=5.42×10-8)and whole-body BMD(β=-0.193,95%CI:-0.288 to-0.098,P=7.35×10-5).The findings of this study support the protective effect of statin drugs on BMD.These findings not only deepen our understanding of the relationship between cholesterol-related genes and bone health but also reveal potential therapeutic targets for improving BMD.
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BACKGROUND:With the continuous improvement and progress of artificial intelligence technology in the treatment of spinal deformity,a large number of studies have been invested in this field,but the main research status,hot spots and development trends are still unclear. OBJECTIVE:To visually analyze the literature related to artificial intelligence in the field of spinal deformities by using bibliometrics,identify the research hotspots and shortcomings in this field,and provide references for future research. METHODS:The core database of Web of Science was used to search the articles related to artificial intelligence in the field of spinal deformities published from inception to 2023.The data were visually analyzed by Citespace 5.6.R5 and VOSviewer 1.6.19. RESULTS AND CONCLUSION:(1)A total of 165 papers were included,and the number of papers published in this field showed a fluctuating upward trend.The author with the largest number of articles is Lafage V,and the country with the largest number of articles is China.(2)Keyword analysis results show that adolescent scoliosis,deep learning,classification,precision and robot are the main keywords.(3)The in-depth analysis results of co-cited and highly cited articles show that artificial intelligence has three hotspots in the field of spinal deformities,including the use of U-shaped architecture(a mature mode of deep learning convolutional neural networks)to automatically measure imaging parameters(Cobb angle and accurate segmentation of paraspinal muscles),multi-view correlation network architecture(i.e.,spine curvature assessment framework),and robot-guided spinal surgery.(4)In the field of artificial intelligence treatment of spinal malformations,the mechanism research such as genomics is very weak.In the future,unsupervised hierarchical clustering and other machine learning techniques can be used to study the basic mechanism of susceptibility genes in the field of spinal deformities by genome-wide association analysis and other genomics research methods.
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BACKGROUND:Osteonecrosis is a common refractory disease in clinical practice,and observational studies have suggested that micronutrients may have a prognostic role in osteonecrosis.However,the specific causal association between micronutrients and osteonecrosis is not known. OBJECTIVE:To explore the causal association between micronutrients and osteonecrosis by Mendelian randomization using summary data from a large population-based genome-wide association study(GWAS)for clinical diagnosis and treatment. METHODS:The required exposure and outcome data(calcium,magnesium,iron,vitamin E,carotenoids,retinol&osteonecrosis)were extracted from the IEU OpenGWAS database,GWAS catalog database,and FinnGen database.Data were analyzed by bidirectional Mendelian randomization with inverse-variance weighted as the primary study method,and weighted median method,simple mode method,weighted mode method,and MR-Egger regression to complement the results.The reliability of the data was then verified through sensitivity analyses. RESULTS AND CONCLUSION:(1)The results found a positive correlation between serum iron concentration and osteonecrosis,while no correlation was found for other micronutrients.There was no reverse causality in all the data.(2)The results of sensitivity analysis showed a robust causality.(3)By Mendelian randomization method,this study provided evidence of causality between serum iron concentration and osteonecrosis,and understanding the causality of micronutrient elements on osteonecrosis can help in the clinical diagnosis and treatment of osteonecrosis,which is of great clinical significance.
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BACKGROUND:It has been found in recent observational studies that assessing localized fat mass is crucial in the evaluation of disc degeneration.Although obesity has been recognized as a risk factor for disc degeneration,the causal relationship between fat mass,which is a key factor in obesity,and intervertebral disc degeneration has been unclear in previous studies. OBJECTIVE:To investigate the causal risk factors of intervertebral disc degeneration associated with different distributions of fat mass,thereby enhancing the understanding of the pathogenesis of intervertebral disc degeneration and contributing to the development of preventive,therapeutic,and prognostic strategies. METHODS:Genetic markers associated with trunk and lower limb fat mass were extracted as instrumental variables from the publicly available IEU Open GWAS under the conditions of strong correlation and fulfillment of linkage disequilibrium.These markers were combined with the Mendelian randomization analysis to investigate the relationship between body fat and intervertebral disc degeneration.We used the latest version 9 database of FinnGen and assessed the results using several regression models,including inverse variance weighting,MR-Egger regression,simple mode,weighted mode,and weighted median estimator.We also assessed the heterogeneity of the genetic markers using Cochran's Q test,and multiplicity was assessed using the MR-Egger intercept test.Additionally,we used the leave-one-out method to determine the sensitivity of individual genetic markers to the causal effect of the exposure and outcome.The results were presented as odds ratios(OR)and 95%confidence intervals(CI). RESULTS AND CONCLUSION:The results from the inverse variance weighting method revealed that there was a positive causal relationship between trunk fat mass and the risk of developing intervertebral disc degeneration(OR=1.25,95%CI:1.15-1.35,P＜0.001).Additionally,there was an inverse causal relationship between bilateral lower limb fat mass and the risk of developing intervertebral disc degeneration(OR=0.7,95%CI:0.63-0.78,P＜0.001;OR=0.69,95%CI:0.62-0.76,P＜0.001).Furthermore,the MR-Egger intercept analysis did not detect any potential horizontal pleiotropy.No bias single nucleotide polymorphisms were detected,while heterogeneity tests were present,and the leave-one-out sensitivity analysis suggested reliable results.The results above demonstrate a positive causal relationship between trunk fat mass and intervertebral disc degeneration.As trunk fat mass increases,the risk of intervertebral disc degeneration rises.With an increase in both lower limb fat mass,the risk of intervertebral disc degeneration decreases.Fat content and distribution affects the risk of developing intervertebral disc degeneration and should be given more attention.
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@#Objective To analyze the whole genome sequence and genetic characteristics of the Yunnan isolate of Coxsackievirus A8(CVA8),A8-1/YN/CHN/2019,in order to understand the prevalence and variation of CVA8.Methods The primers for CVA8 were designed,the viral RNA was extracted,the VP1 sequence was amplified by RT-PCR and sequenced,and the whole genome was spliced using BioEdit 7.2.3. MEGA 7.0 software was used for the phylogenetic analysis,and Simplot 3.5.1 and RDP4 software were used for the recombination analysis.Results Strain A8-1/YN/CHN/2019 was7 396 nt long and encoded 2 188 amino acids. The homologies of nucleotide and amino acid sequences between VP1 and CVA8 prototype strain AF081299/Donovan/USA/1998 were 81. 04% and 95. 24%,respectively. Strain A8-1/YN/CHN/2019 belonged to genotype E,while the other Chinese isolates were located in genotypes D and E. Recombination analysis revealed that strain A8-1/YN/CHN/2019 recombined on segments P2 and P3 of the non-structural coding region.Conclusion Strain A8-1/YN/CHN/2019 is of genotype E and has recombination events in the non-structural regions of the P2 and P3 segments.
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ObjectiveTo explore the potential mechanism of Zuogui Jiangtang Jieyu Formula （左归降糖解郁方， ZJJF） for diabetic rats with depression. MethodsSixty rats were randomly divided into normal group， model group， wingless MMTV integration site family member 5a （Wnt5a） agonist group， ZJJF group， and ZJJF plus Wnt5a inhibitor group， with 12 rats in each group. Except for the normal group， the rats were fed with high-fat chow， streptozotocin injection， and chronic mild unpredictable stress combination， to establish model of diabetes mellitus complicated with depression. After successful modelling， rats in the Wnt5a agonist group were given bilateral hippocampal stereotactic injections of Wnt5a agonist Foxy-5 with 5 μl each for 7 consecutive days； rats in ZJJF group were given 20.52 g/（kg·d） of ZJJF by gavage； rats in ZJJF plus Wnt5a inhibitor group were given the drug by gavage， and bilateral hippocampal stereotactic injections of Wnt5a inhibitors Box5， with the same dosage and injection method as above. The normal group and model group were given 10 ml/（kg·d） of normal saline by gavage. All groups were gavaged for 4 consecutive weeks. At the end of the intervention， the depression-like behaviour of rats was evaluated using the forced swimming experiment （immobility time） and the absent field experiment （number of activities）； the blood glucose and insulin levels of rats were measured and the insulin resistance index was calculated； the dendritic morphology of dentate gyrus neurons in the hippocampus was observed using Golgi staining； the level of dentate gyrus neuron proliferation was measured using 5-bromodeoxyuracil nucleoside （Brdu） injection and immunofluorescence； RT-qPCR and Western blot were used to detect the mRNA and protein expression of Wnt5a， Ras homologue genomic member A （RhoA） and Rho homologue-associated coiled-coil protein kinase 1 （ROCK1） in the dentate gyrus. ResultsCompared with the normal group， rats in the model group had significantly higher blood glucose， insulin and insulin resistance indices， longer immobility time， fewer activities， lower Brdu integral optical density values and Wnt5a， RhoA， ROCK1 protein and mRNA expression in the dentate gyrus of the hippocampus （P＜0.05 or P＜ 0.01）； the dendritic branches of rat hippocampal dentate gyrus neurons could be seen to be significantly reduced or broken， and their length shortened. Compared with the model group， the blood glucose， insulin and insulin resistance indices of rats in ZJJF group and the ZJJF plus Wnt5a inhibitor group significantly reduced （P＜0.05 or P＜0.01）； the immobility time of rats in the Wnt5a agonist group and ZJJF group was significantly shortened， the number of activities increased， the Brdu integral optical density values elevated， and the Wnt5a， RhoA， ROCK1 protein and mRNA expression elevated （P＜0.05 or P＜0.01）， and the number of dendritic branches of hippocampal dentate gyrus neurons significantly increased， the length lengthened， and the complexity of dendrites increased. Compared with the Wnt5a agonist group， rats in the ZJJF group showed significant decrease in blood glucose， insulin and insulin resistance indices， prolongation of immobilisation time， reduction in the number of activities， and reduction in the Brdu integral optical density value； except for the Wnt5a mRNA in ZJJF group， Wnt5a， RhoA， ROCK1 protein and mRNA expression reduced in both ZJJF group and ZJJF plus Wnt5a inhibitor group （P＜0.05 or P＜0.01）. Compared with ZJJF group， Wnt5a， RhoA， ROCK1 protein and mRNA expression were reduced in ZJJF plus Wnt5a inhibitor group （P＜0.05 or P＜0.01）. ConclusionZJJF can improve hyperglycemia and depressive-like behaviours in rat models of diabetes with depression， and its antidepressant effects may be related to the activation of hippocampal Wnt5a/RhoA signaling and promotion of dentate gyrus neuron dendritic growth.
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【Objective】 To analyze the association between copper death-related genes and prognosis of prostate cancer and immune cell infiltration based on the cancer genome atlas (TCGA). 【Methods】 The mRNA transcriptome data of all prostate cancer patients were downloaded from TCGA, including 501 prostate cancer tissues and 52 normal tissues.The expression matrix of copper death-related genes was extracted with R software.Differential analysis and multivariate regression analysis were conducted to screen out the prognostic genes, which were then analyzed to explore the correlation between prognosis-related genes and immune cells. 【Results】 GCSH gene was significantly correlated with the prognosis of prostate cancer, and significantly correlated with dendritic cells, CD8+ T cells and plasma cells (P<0.05). 【Conclusion】 GCSH gene plays an important role in the occurrence and development of prostate cancer, and may become a prognostic marker of the disease.
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【Objective】 To investigate the effects of emotions (subjective well-being, depressed effect, worry, and guilt) on cancer (colorectal cancer, hepatic cancer, thyroid cancer, lung cancer, and breast cancer). 【Methods】 Two-sample bi-directional Mendelian randomization (MR) method was adopted. All data were based on summary data from genome-wide association studies (GWAS). Inverse variance weighting (IVW) was used to generate the main results, and weighted median (WM) and MR-Egger methods were employed to calculate supplementary results. The outcome measure was odds ratio (OR), and sensitivity analysis was conducted. 【Results】 For depressed effect, a significant association with lung cancer (OR=1.005, 95% CI: 1.001-1.009, P=0.015) was found. For worry, a significant association with breast cancer (OR=1.199, 95% CI: 1.011-1.423, P=0.038) was observed. For guilt, a significant association with thyroid cancer (OR=2.083, 95% CI: 1.080-4.017, P=0.029) was identified. After removing all potentially pleiotropic SNPs detected by MR PRESSO, the association between worry and breast cancer showed no statistical difference (P=0.064), while the association between worry and colorectal cancer remained significant (OR=0.739, 95% CI: 0.571-0.956, P=0.021). No causal relationship was found between cancer and emotions. 【Conclusion】 There is a causal relationship between depression and increased lung cancer incidence, guilt and increased thyroid cancer incidence, as well as anxiety and decreased colorectal cancer incidence.