Objective:To establish a niraparib-resistant ovarian cancer cell line and preliminarily explore its biological characteristics and metabolic signatures.Methods:(1) Using ovarian adenocarcinoma cell line A2780 as parental cells, the niraparib-resistant cell line A2780-NiraR was established by the method of concentration gradient increased induction, and its morphological characteristics were observed using inverted phase-contrast microscope. The half-inhibitory concentration (IC 50) of niraparib was determined by cytotoxicity assay. (2) Cell proliferation was determined by cell count kit-8 (CCK-8) assay and direct cell counting assay, cell cycle distribution was analyzed by flow cytometry. (3) The differential metabolites between A2780 and A2780-NiraR cells were detected by non-target metabolomics based on ultra-high performance liquid chromatography-high resolution mass spectrometry (UPLC/HRMS). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted on the above differential metabolites to explore related metabolic pathways. Results:(1) Compared with the parental A2780 cells, A2780-NiraR cells exhibited predominantly short-spindle or oval morphology with reduced cellular projections and indistinct cell borders. The IC 50 values of niraparib were 3.17 and 26.19 μmol/L against A2780 cells and A2780-NiraR cells, respectively ( F=98.50, P<0.001). (2) A2780-NiraR cells had a slower proliferation rate compared with A2780 cells ( F=146.80, P<0.001). The doubling time of A2780-NiraR cells [(37.5±1.9) hours] was significantly longer than that of A2780 cells [(14.5±1.0) hours; t=10.50, P<0.001]. Compared with the parental A2780 cells, A2780-NiraR cells had a significantly lower S phase fraction [(44.5±0.7)% in A2780 cells, (30.2±2.9)% in A2780-NiraR cells; t=4.78, P<0.001] and higher G 0/G 1 phase fraction [(35.4±1.2)% in A2780 cells, (52.2±3.1)% in A2780-NiraR cells; t=5.10, P<0.001]. (3) The metabolites of A2780 and A2780-NiraR cells were analyzed by non-target metabolomics. Forty-four differential metabolites between A2780 and A2780-NiraR cells were screened using the orthogonal partial least squares-discriminant analysis (OPLS-DA) model, the majority of which were significantly increased, such as pyrrolidone carboxylic acid, L-lysine and 1-pyrroline-4-hydroxy-2-carboxylate. Pathway enrichment analysis indicated that the arginine metabolism, purine metabolism, and pyrimidine metabolism were the most significantly enriched pathways. Conclusion:A2780-NiraR cells have acquired a stable niraparib resistance phenotype, and metabolic pathways including arginine metabolism may serve as potential therapeutic targets for enhancing niraparib efficacy in ovarian cancer.

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.

The Chinese medicine Zha Gui,the senior manager of traditional Chinese medicine dispensing,plays an important role and key function in the"front store and back factory"Chinese medicine pharmacy.Inheriting the valuable experience and excellent culture of Chinese medicine Zha Gui is of great academic value and practical significance in clarifying the development of the discipline of traditional Chinese medicine,standardizing the technical operation of traditional Chinese medicine preparation,and promoting the"living inheritance"of the old pharmacist's skills.At the start of the new era and opening up to new thinking,this paper examined the rise of old Chinese medicine stores and Chinese medicine Zha Gui,analyzed the post responsibility,inheritance path and future development of Chinese medicine Zha Gui,and put forward the strategy of cultivating high-quality Chinese medicine Zha Gui talents,aiming at cultivating compound innovative talents in the traditional Chinese medicine industry in line with the needs of the contemporary society.

Objective To construct an enhancer-based prognostic risk prediction model for non-small cell lung cancer (NSCLC) by integrating DNA methylome data and transcriptome data. Methods The weighted gene co-expression network analysis (WGCNA) was used to identify NSCLC related genes from the differentially methylated positions (DMPs) of enhancers. Based on the transcriptome data,the prognostic risk prediction model was constructed using LASSO-Cox regression algorithm. Results Through the analysis on DNA methylome data of NSCLC,19784 DMPs were obtained and their distribution patterns were characterized,including 6089 DMPs of enhancers. WGCNA analysis screened 79 highly correlated DMPs of enhancer with NSCLC from the 6089 DMPs. After analyzing the target genes of 79 DMPs with LASSO-Cox regression based on the transcriptome data,10 genes were used to construct a prognostic risk prediction model. The prognostic risk prediction model was evaluated by calculating the areas under the curve (AUC) of 3-,5-,and 10-year time-dependent receiver operating characteristic (ROC) curves in training set and validation set;and the results showed that the 3-,5-,and 10-year AUC in training set and validation set were all higher than 0.7. Finally,a nomogram was constructed to predict the 3-,5-,and 10-year survival probabilities of NSCLC. Conclusion This study provides new insights into the role of enhancers in NSCLC and has the potential to improve the prognosis by guiding personalized treatment decisions.

Objective:To establish a niraparib-resistant ovarian cancer cell line and preliminarily explore its biological characteristics and metabolic signatures.Methods:(1) Using ovarian adenocarcinoma cell line A2780 as parental cells, the niraparib-resistant cell line A2780-NiraR was established by the method of concentration gradient increased induction, and its morphological characteristics were observed using inverted phase-contrast microscope. The half-inhibitory concentration (IC 50) of niraparib was determined by cytotoxicity assay. (2) Cell proliferation was determined by cell count kit-8 (CCK-8) assay and direct cell counting assay, cell cycle distribution was analyzed by flow cytometry. (3) The differential metabolites between A2780 and A2780-NiraR cells were detected by non-target metabolomics based on ultra-high performance liquid chromatography-high resolution mass spectrometry (UPLC/HRMS). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted on the above differential metabolites to explore related metabolic pathways. Results:(1) Compared with the parental A2780 cells, A2780-NiraR cells exhibited predominantly short-spindle or oval morphology with reduced cellular projections and indistinct cell borders. The IC 50 values of niraparib were 3.17 and 26.19 μmol/L against A2780 cells and A2780-NiraR cells, respectively ( F=98.50, P<0.001). (2) A2780-NiraR cells had a slower proliferation rate compared with A2780 cells ( F=146.80, P<0.001). The doubling time of A2780-NiraR cells [(37.5±1.9) hours] was significantly longer than that of A2780 cells [(14.5±1.0) hours; t=10.50, P<0.001]. Compared with the parental A2780 cells, A2780-NiraR cells had a significantly lower S phase fraction [(44.5±0.7)% in A2780 cells, (30.2±2.9)% in A2780-NiraR cells; t=4.78, P<0.001] and higher G 0/G 1 phase fraction [(35.4±1.2)% in A2780 cells, (52.2±3.1)% in A2780-NiraR cells; t=5.10, P<0.001]. (3) The metabolites of A2780 and A2780-NiraR cells were analyzed by non-target metabolomics. Forty-four differential metabolites between A2780 and A2780-NiraR cells were screened using the orthogonal partial least squares-discriminant analysis (OPLS-DA) model, the majority of which were significantly increased, such as pyrrolidone carboxylic acid, L-lysine and 1-pyrroline-4-hydroxy-2-carboxylate. Pathway enrichment analysis indicated that the arginine metabolism, purine metabolism, and pyrimidine metabolism were the most significantly enriched pathways. Conclusion:A2780-NiraR cells have acquired a stable niraparib resistance phenotype, and metabolic pathways including arginine metabolism may serve as potential therapeutic targets for enhancing niraparib efficacy in ovarian cancer.

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.

The Chinese medicine Zha Gui,the senior manager of traditional Chinese medicine dispensing,plays an important role and key function in the"front store and back factory"Chinese medicine pharmacy.Inheriting the valuable experience and excellent culture of Chinese medicine Zha Gui is of great academic value and practical significance in clarifying the development of the discipline of traditional Chinese medicine,standardizing the technical operation of traditional Chinese medicine preparation,and promoting the"living inheritance"of the old pharmacist's skills.At the start of the new era and opening up to new thinking,this paper examined the rise of old Chinese medicine stores and Chinese medicine Zha Gui,analyzed the post responsibility,inheritance path and future development of Chinese medicine Zha Gui,and put forward the strategy of cultivating high-quality Chinese medicine Zha Gui talents,aiming at cultivating compound innovative talents in the traditional Chinese medicine industry in line with the needs of the contemporary society.

Objective To construct an enhancer-based prognostic risk prediction model for non-small cell lung cancer (NSCLC) by integrating DNA methylome data and transcriptome data. Methods The weighted gene co-expression network analysis (WGCNA) was used to identify NSCLC related genes from the differentially methylated positions (DMPs) of enhancers. Based on the transcriptome data,the prognostic risk prediction model was constructed using LASSO-Cox regression algorithm. Results Through the analysis on DNA methylome data of NSCLC,19784 DMPs were obtained and their distribution patterns were characterized,including 6089 DMPs of enhancers. WGCNA analysis screened 79 highly correlated DMPs of enhancer with NSCLC from the 6089 DMPs. After analyzing the target genes of 79 DMPs with LASSO-Cox regression based on the transcriptome data,10 genes were used to construct a prognostic risk prediction model. The prognostic risk prediction model was evaluated by calculating the areas under the curve (AUC) of 3-,5-,and 10-year time-dependent receiver operating characteristic (ROC) curves in training set and validation set;and the results showed that the 3-,5-,and 10-year AUC in training set and validation set were all higher than 0.7. Finally,a nomogram was constructed to predict the 3-,5-,and 10-year survival probabilities of NSCLC. Conclusion This study provides new insights into the role of enhancers in NSCLC and has the potential to improve the prognosis by guiding personalized treatment decisions.

Objective To analyze the prognostic factors in the patients with HER2-positive breast cancer adjuvant treated with trastuzumab.Methods We conducted a retrospective analysis of clinical data of 1 246 patients diagnosed with HER2-positive breast cancer between January 2009 and December 2019 who received treatment with trastuzumab.We investigated the factors impacting their prognosis by the Log-rank test univariate analysis and multivariate COX regression analysis.Results HER2-positive patients treated with trastuzumab had a poor prognosis in pT2-3(HR=2.10,P=0.003),pN2-3(HR=2.81,P<0.001),and no endocrine therapy(HR=2.50,P<0.001),and that had a better prognosis combined with taxane or other chemotherapy regimens(HR=0.40,P=0.017).We divided the patients into two subgroups according to the status of lymph node metastasis,and we found that in the negative lymph nodes group the patients with pT2-3 stage had poor prognosis(P=0.020),while the patients combined with taxane or other chemotherapy had better prognosis(P=0.032).In the positive lymph nodes group the patients with pT2-3 stage and no endocrine therapy had poor prognosis(P=0.012,P=0.001).Conclusions The patients with HER2-positive breast cancer treated with trastuzumab can be managed in different categories,for individuals without lymph node involvement and small tumor sizes,combining therapy with non-anthracycline chemotherapy is preferable for achieving improved outcomes,for patients with lymph node metastasis and large tumor sizes,if chemotherapy options are available,it is more recommended to use an anthracycline-free regimen to ensure the same prognosis while reducing the harm caused by the toxic side effects of chemotherapy.

Objective:To explore the biological role and clinical significance of ubiquitin-specific protease 7 (USP7) in the carcinogenesis of scar ulcer.Methods:A retrospective observational study combined with bioinformatics analysis was used. The RNA expression profile data of USP7 in tumor and/or its corresponding paracancular normal tissue were obtained from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus database, and the RNA sequencing data were transformed by log 2. The variations of USP7 gene were analyzed by cBioPortal database. The USP7 mRNA expression in tumor and adjacent normal tissue in TCGA database were obtained by using the "Gene_DE" module in TIMER 2.0 database. The survival rates of patients with high and low USP7 expression in cutaneous melanoma (SKCM), cervical squamous cell carcinoma (CESC), lung squamous cell carcinoma (LUSC), and head and neck squamous cell carcinoma (HNSC) were analyzed using the Gene Expression Profile Interactive Analysis 2 (GEPIA2) database, and the Kaplan-Meier survival curves were drawn. Sangerbox database was used to analyze the correlation of USP7 expression in pan-cancer with microsatellite instability (MSI) or tumor mutation burden (TMB) pan-cancer. Through the "correlation analysis" module in the GEPIA2 database, the correlation of USP7 expression in pan-cancer with the expression levels of five DNA mismatch repair genes ( MLH1, MSH2, MSH6, PMS2, and EPCAM) and three essential DNA methyltransferases (DNMT)--DNMT1, DNMT3A, and DNMT3B were evaluated. The USP7 expression in CESC, HNSC, LUSC, and SKCM and its correlation with infiltration of immune cells (B cells, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and dendritic cells) were analyzed by the "Immune-Gene" module in TIMER 2.0 database. The "Similar Genes Detection" module of GEPIA2 database was used to obtain the top 100 protein sets with similar expression patterns to USP7. Intersection analysis was performed between the aforementioned protein sets and the top 50 protein sets that were directly physically bound to USP7 obtained by using the STRING database. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis were performed for the two protein sets mentioned above using the DAVID database. The samples of normal skin, hypertrophic scar, scar ulcer, and scar carcinoma with corresponding clinicopathologic features were collected from the Department of Pathology of Tongren Hospital of Wuhan University & Wuhan Third Hospital from October 2018 to October 2022, and the USP7 expression in tissue was detected by immunohistochemical method, with the number of samples of 6. Data were statistically analyzed with Log-rank test, one-way analysis of variance, and Bonferroni test. Results:In pan-cancer, the main gene variations of USP7 were mutation and amplification, and the top 3 tumors with the highest variation frequency (>6%) were bladder urothelial carcinoma, SKCM, and endometrial carcinoma. The main mutation of USP7 gene in pan-cancer was missense mutation. In SKCM with the highest mutation frequency, the main type of mutation was missense mutation in USP7_ICP0_bdg domain. USP7 mRNA expression in breast invasive carcinoma, bile duct carcinoma, colon carcinoma, esophageal carcinoma, HNSC, renal chromophobe cell carcinoma, hepatocellular carcinoma, lung adenocarcinoma, LUSC, prostate carcinoma, and gastric carcinoma was significantly higher than that in corresponding paracancer normal tissue ( P<0.05). USP7 mRNA expression in glioblastoma multiforme, renal clear cell carcinoma, renal papillary cell carcinoma, and thyroid carcinoma was significantly lower than that in corresponding paracancular normal tissue ( P<0.05). In addition, USP7 mRNA expression in SKCM metastases was much higher than that in primary tumor tissue ( P<0.05). Survival curves showed no significant difference in survival rate between patients with high USP7 expression and patients with low USP7 expression in CESC, HNSC, LUSC, and SKCM (Log-rank P>0.05, with hazard ratios of 1.00, 0.99, 1.00, and 1.30, respectively). USP7 expression in colon cancer, colorectal cancer, thymic cancer, and thyroid cancer was negatively correlated with TMB (with Pearson correlation coefficients of -0.26, -0.19, -0.19, and 0.11, respectively, P<0.05). USP7 expression in glioma, CESC, lung adenocarcinoma, mixed renal carcinoma, and LUSC was positively correlated with MSI expression (with Pearson correlation coefficients of 0.22, 0.14, 0.15, 0.08, and 0.14, respectively, P<0.05), and USP7 expression in colon cancer, colorectal cancer, invasive breast cancer, prostate cancer, HNSC, thyroid cancer, and diffuse large B-cell lymphoma were significantly negatively correlated with MSI expression (with Pearson correlation coefficients of -0.31, -0.27, -0.13, -0.19, -0.16, -0.18, and -0.53, respectively, P<0.05). The expression of USP7 in CESC was positively correlated with that of both MSH2 and MSH6 (with Spearman correlation coefficients of 0.51 and 0.44, respectively, P<0.05), and the expression of USP7 in HNSC was positively correlated with the expression of EPCAM, MLH1, MSH2, MSH6, and PMS2 (with Spearman correlation coefficients of 0.39, 0.14, 0.49, 0.54, and 0.41, respectively, P<0.05), and the expression of USP7 in LUSC was positively correlated with the expression of EPCAM, MSH2, MSH6, and PMS2 (with Spearman correlation coefficients of 0.20, 0.36, 0.40, and 0.34, respectively, P<0.05), and the expression of USP7 in SKCM was positively correlated with the expression of EPCAM, MLH1, MSH2, MSH6, and PMS2 (with Spearman correlation coefficients of 0.11, 0.33, 0.42, 0.55, and 0.34, respectively, P<0.05). The expression of USP7 in CESC, HNSC, LUSC, and SKCM was significantly positively correlated with the expression of DNMT1, DNMT3A, and DNMT3B (with Spearman correlation coefficients of 0.42, 0.34, 0.22, 0.45, 0.52, 0.22, 0.36, 0.36, 0.22, 0.38, 0.46, and 0.21, respectively, P<0.05). The expression of USP7 in CESC, HNSC, LUSC, and SKCM was positively correlated with CD4 + T cell infiltration (with Partial correlation coefficients of 0.14, 0.22, 0.13, and 0.16, respectively, P<0.05). Being similar to the pattern of USP7 expression and ranked among top 100 protein sets, the top 5 proteins were C16orf72, BCLAF1, UBN, GSPT1, ERI2 (with Spearman correlation coefficients of 0.83, 0.74, 0.73, and 0.72, respectively, all P values<0.05). The top 50 protein sets that directly physically bind to USP7 overlapped with the aforementioned protein set by only one protein, thyroid hormone receptor interaction factor 12. KEGG enrichment analysis showed that USP7 related genes were involved in cell cycle, spliceosome, cell senescence, and p53 signal pathway. GO enrichment analysis showed that USP7 related genes were involved in transcriptional regulation, protein ubiquitination, DNA repair, and cytoplasmic pattern recognition receptor signal pathways. Analysis of clinical samples showed that USP7 expression was significantly higher in hypertrophic scars (0.35±0.05), scar ulcers (0.43±0.04), and scar cancers (0.61±0.03) than in normal skin (0.18±0.04), P<0.05. Conclusions:USP7 may be a clinical biomarker for the progression of cicatricial ulcer cancer.