Characterization and validation of fatty acid metabolism-related genes predicting prognosis, immune infiltration, and drug sensitivity in endometrial cancer.

Endometrial cancer is considered to be the second most common tumor of the female reproductive system, and patients diagnosed with advanced endometrial cancer have a poor prognosis. The influence of fatty acid metabolism in the prognosis of patients with endometrial cancer remains unclear. We constructed a prognostic risk model using transcriptome sequencing data of endometrial cancer and clinical information of patients from The Cancer Genome Atlas (TCGA) database via least absolute shrinkage and selection operator regression analysis. The tumor immune microenvironment was analyzed using the CIBERSORT algorithm, followed by functional analysis and immunotherapy efficacy prediction by gene set variation analysis. The role of model genes in regulating endometrial cancer in vitro was verified by CCK-8, colony formation, wound healing, and transabdominal invasion assays, and verified in vivo by subcutaneous tumor transplantation in nude mice. A prognostic model containing 14 genes was constructed and validated in 3 cohorts and clinical samples. The results showed differences in the infiltration of immune cells between the high-risk and low-risk groups, and that the high-risk group may respond better to immunotherapy. Experiments in vitro confirmed that knockdown of epoxide hydrolase 2 (EPHX2) and acyl-CoA oxidase like (ACOXL) had an inhibitory effect on EC cells, as did overexpression of hematopoietic prostaglandin D synthase (HPGDS). The same results were obtained in experiments in vivo. Prognostic models related to fatty acid metabolism can be used for the risk assessment of endometrial cancer patients. Experiments in vitro and in vivo confirmed that the key genes HPGDS, EPHX2, and ACOXL in the prognostic model may affect the development of endometrial cancer.

Differential genetic mutations and immune cell infiltration in high- and low-risk STAD: Implications for prognosis and immunotherapy efficacy.

This study investigates genetic mutations and immune cell dynamics in stomach adenocarcinoma (STAD), focusing on identifying prognostic markers and therapeutic targets. Analysis of TCGA-STAD samples revealed C > A as the most common single nucleotide variant (SNV) in both high and low-risk groups. Key mutated driver genes included TTN, TP53 and MUC16, with frame-shift mutations more prevalent in the low-risk group and missense mutations in the high-risk group. Interaction analysis of hub genes such as C1QA and CD68 showed significant correlations, impacting immune cell infiltration patterns. Using ssGSEA, we found higher immune cell infiltration (B cells, CD4+ T cells, CD8+ T cells, DC cells, NK cells) in the high-risk group, correlated with increased risk scores. xCell algorithm results indicated distinct immune infiltration levels between the groups. The study's risk scoring model proved effective in prognosis prediction and immunotherapy efficacy assessment. Key molecules like CD28, CD27 and SLAMF7 correlated significantly with risk scores, suggesting potential targets for high-risk STAD patients. Drug sensitivity analysis showed a negative correlation between risk scores and sensitivity to certain treatments, indicating potential therapeutic options for high-risk STAD patients. We also validated the carcinogenic role of RPL14 in gastric cancer through phenotypic experiments, demonstrating its influence on cancer cell proliferation, invasion and migration. Overall, this research provides crucial insights into the genetic and immune aspects of STAD, highlighting the importance of a risk scoring model for personalized treatment strategies and clinical decision-making in gastric cancer management.

Exploring the metastasis-related biomarker and carcinogenic mechanism in liver cancer based on single cell technology.

Background: Hepatocellular carcinoma (HCC) is a fatal primary malignancy characterized by high invasion and migration. We aimed to explore the underlying metastasis-related mechanism supporting the development of HCC. Methods: The dataset of single cell RNA-seq (GSE149614) were collected for cell clustering by using the Seurat R package, the FindAllMarkers function was used to find the highly expression and defined the cell cluster. The WebGestaltR package was used for the GO and KEGG function analysis of shared genes, the Gene Set Enrichment Analysis (GSVA) was performed by clusterProfiler R package, the hTFtarget database was used to identify the crucial transcription factors (TFs), the Genomics of Drug Sensitivity in Cancer (GDSC) database was used for the drug sensitivity analysis. Finally, the overexpression and trans-well assay was used for gene function analysis. Results: We obtained 9 cell clusters from the scRNA-seq data, including the nature killer (NK)/T cells, Myeloid cells, Hepatocytes, Epithelial cells, Endothelial cells, Plasma B cells, Smooth muscle cells, B cells, Liver bud hepatic cells. Further cell ecological analysis indicated that the Hepatocytes and Endothelial cell cluster were closely related to the cancer metastasis. Subsequently, the NDUFA4L2-Hepatocyte, GTSE1-Hepatocyte, ENTPD1-Endothelial and NDUFA4L2-Endothelial were defined as metastasis-supporting cell clusters, in which the NDUFA4L2-Hepatocyte cells was closely related to angiogenesis, while the NDUFA4L2-Endothelial was related with the inflammatory response and complement response. The overexpression and trans-well assay displayed that NDUFA4L2 exhibited clearly metastasis-promoting role in HCC progression. Conclusion: We identified and defined 4 metastasis-supporting cell clusters by using the single cell technology, the specify shared gene was observed and played crucial role in promoting cancer progression, our findings were expected to provide new insight in control cancer metastasis.

Improving the predictive accuracy of efficacy evaluation using tumor orthotopic transplant and resection model.

Preclinical efficacy evaluation and tumor drug sensitivity analysis are two main applications of efficacy evaluation. Preclinical efficacy evaluation is to predict whether candidate drugs or therapies may improve patient outcomes in clinical trials. Tumor drug sensitivity analysis is an approach for the personalized evaluation and optimization of approved anti-cancer drugs and treatment regimens. Overall survival (OS) is the gold standard to evaluate the outcome of drugs or therapies in both clinical trials and clinical treatment. Many efficacy evaluation models, such as cell model, tumor cell-line transplant model, patient-derived tumor xenograft model, tumor organoid model, have been developed to assess the inhibitory effect of tested drugs or therapies on tumor growth. In fact, many treatments may also lead to malignant progression of tumors, such as chemotherapy, which can lead to metastasis. Therefore, tumor growth inhibition does not necessarily predict OS benefit. Whether it can prevent or inhibit tumor recurrence and metastasis is the key to whether drugs and therapies can improve patient outcomes. In this perspective, we summarize the current understanding of the pathological progression of tumor recurrence and metastasis, point out the shortcomings of existing tumor transplant models for simulating the clinical scenario of malignant progression of tumors, and propose five improved indicators for comprehensive efficacy evaluation to predict OS benefit using tumor orthotopic transplant and resection model. Improvement in the accuracy of efficacy evaluation will accelerate the development process of anti-cancer drugs or therapies, optimize treatment regimens to improve OS benefit, and reduce drug development and cancer treatment costs.

A novel immunogenic cell death-related gene risk signature can identify biomarkers of gliomas and predict the immunotherapeutic response.

Immunogenic cell death (ICD) is a type of cell death that plays a pivotal role in immunity. Recent studies have identified the critical role of ICD in glioma treatment. This study aimed to use ICD-associated differentially expressed genes (ICD-DEGs) to predict survival of glioma patients. We investigated the relationship between clinical prognosis and the date-to-clinical prognosis of 1,721 glioma patients by examining the expression, methylation, and mutation status of ICD-related genes (IRGs) in these patients. Our prediction of survival in glioma patients was based on three risk genes, and we explored the association between these genes and clinical outcomes. Additionally, IRG expression was used to stratify glioma patients. We further examined the relationship among the three subgroups in terms of immune microenvironment heterogeneity and immunotherapy response. In addition, this study also included analyses of histograms and sensitivity to antitumor drugs. The expression of these genes was externally validated by RT-qPCR, Western blot (WB), and immunohistochemistry (IHC) in glioma and normal brain tissue. Our findings reveal that most IRGs are overexpressed in glioma tumor tissues, and this high expression was confirmed through histological validation. We successfully developed predictive models for three prognostic genes associated with ICD. These models not only predict survival in glioma but also correlate with the tumor's immune microenvironment. Finally, using consensus clustering, we identified three ICD-associated subtypes. Notably, patients with the C3 subtype showed high levels of immune cell infiltration, whereas those with the C1 subtype exhibited lower levels of immune cell infiltration. We successfully developed an innovative IRG-based systematic approach for evaluating glioma patients. This stratification in experimental studies opens new avenues for prognosis and assessing immunotherapy responses in glioma patients. Our study demonstrates the effectiveness of this approach in treating glioma, potentially paving the way for more promising and effective therapeutic strategies in the future.

Ferroptosis-related genes prognostic signature for pancreatic cancer and immune infiltration: potential biomarkers for predicting overall survival.

BACKGROUND: Pancreatic adenocarcinoma (PAAD) constitutes a lethal malignancy, notorious for its elevated mortality rates due to the difficulties in early diagnosis and rapid metastasis. The emerging paradigm of ferroptosis-an iron-catalyzed, regulated cell death distinguished by the accrual of lipid peroxides-has recently garnered scholarly focus. However, the expression landscape of ferroptosis-related genes (FRGs) in PAAD and their prognostic implications remain enigmatic. METHODS: We undertook a rigorous quantification of FRGs in PAAD samples, sourcing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. These repositories also provided extensive metadata, encompassing mesenchymal stemness index (mRNAsi), genomic mutations, copy number variations (CNV), tumor mutational burden (TMB), and other clinical attributes. A predictive model was constructed utilizing Lasso regression analysis, and a co-expression study was executed to elucidate the complex interconnections between FRGs and other gene sets. RESULTS: Intriguingly, FRGs were substantially upregulated in the high-risk cohort, even in the absence of clinically manifest symptoms, emphasizing their utility as prognostic biomarkers. Gene set enrichment analysis (GSEA) revealed significant enrichment of immune and tumor-related pathways in this high-risk demographic. Striking heterogeneities in immune function and N6-methyladenosine (m6A) RNA modification were observed between the low- and high-risk groups. Our analysis further implicated a cohort of genes-including LINC01559, C11orf86, SERPINB5, DSG3, MSLN, EREG, FAM83A, CXCL5, LY6D, and PSCA-as cardinal mediators in PAAD pathogenesis. A convergence of our predictive model with an analysis of CNVs, single nucleotide polymorphisms (SNPs), and drug sensitivities, revealed an intricate relationship with the FRGs. CONCLUSIONS: Our findings accentuate the salient role of FRGs as critical modulators in the pathogenesis and progression of PAAD. Importantly, our composite prognostic framework offers invaluable insights into PAAD clinical trajectory. Moreover, the complex crosstalk between FRGs and immune cell landscapes in the tumor microenvironment (TME) may elucidate prospective therapeutic strategies. The clinical translational utility of these insights, however, requires further in-depth empirical exploration. Accordingly, the FRG signature introduces a compelling new avenue for risk stratification and targeted therapeutic interventions in this devastating malignancy.

Significance of cuproptosis- related genes in the diagnosis and classification of psoriasis.

Cuproptosis is a novel form of cell death linked to mitochondrial metabolism and is mediated by protein lipoylation. The mechanism of cuproptosis in many diseases, such as psoriasis, remains unclear. In this study, signature diagnostic markers of cuproptosis were screened by differential analysis between psoriatic and non-psoriatic patients. The differentially expressed cuproptosis-related genes (CRGs) for patients with psoriasis were screened using the GSE178197 dataset from the gene expression omnibus database. The biological roles of CRGs were identified by GO and KEGG enrichment analyses, and the candidates of cuproptosis-related regulators were selected from a nomogram model. The consensus clustering approach was used to classify psoriasis into clusters and the principal component analysis algorithms were constructed to calculate the cuproptosis score. Finally, latent diagnostic markers and drug sensitivity were analyzed using the pRRophetic R package. The differential analysis revealed that CRGs (MTF1, ATP7B, and SLC31A1) are significantly expressed in psoriatic patients. GO and KEGG enrichment analyses showed that the biological functions of CRGs were mainly related to acetyl-CoA metabolic processes, the mitochondrial matrix, and acyltransferase activity. Compared to the machine learning method used, the random forest model has higher accuracy in the occurrence of cuproptosis. However, the decision curve of the candidate cuproptosis regulators analysis showed that patients can benefit from the nomogram model. The consensus clustering analysis showed that psoriasis can be grouped into three patterns of cuproptosis (clusterA, clusterB, and clusterC) based on selected important regulators of cuproptosis. In advance, we analyzed the immune characteristics of patients and found that clusterA was associated with T cells, clusterB with neutrophil cells, and clusterC predominantly with B cells. Drug sensitivity analysis showed that three cuproptosis regulators (ATP7B, SLC31A1, and MTF1) were associated with the drug sensitivity. This study provides insight into the specific biological functions and related mechanisms of CRGs in the development of psoriasis and indicates that cuproptosis plays a non-negligible role. These results may help guide future treatment strategies for psoriasis.

Analysis of Pathogenic Bacteria and Drug Resistance Among Girls with Bacterial Vaginitis.

Objective: The aim of this study was to analyze the prevalence of vaginal flora and drug resistance in bacterial vaginitis among girls. Methods: A total of 3099 girls (0-10 years old) with vaginitis who visited the Beijing Children's Hospital from January 2020 to December 2021 were included in the present study. The clinical data, results of bacterial culture of vaginal secretions, and drug sensitivity reports of the subjects were collected and analyzed. Results: Of the 3099 girls with vaginitis, 399 girls had a positive bacterial culture of vaginal secretions. Nineteen types of bacteria were cultured from the vaginal secretions of these 399 girls, with a total of 419 strains. The top three infective bacteria were Haemophilus influenzae (127 strains, 30.31%), Staphylococcus aureus (66 strains, 15.75%), and Streptococcus agalactiae (32 strains, 7.64%). Additionally, 20 girls were simultaneously infected with two types of bacteria. Staphylococcus aureus, Group G Streptococcus, Haemophilus parainfluenzae, and Pseudomonas aeruginosa more frequently occurred in mixed infections. The number and bacterial detection rate among school-age girls were higher than those of preschool-age girls. We found seasonal variation in infection rates, and vaginitis among girls was higher in summer. Recurrence of vaginitis in girls was not related to the type of pathogenic bacteria in the infection. Drug sensitivity analyses showed that the resistance rates of clindamycin and erythromycin were generally high, 70-100%. After the coronavirus disease 2019 outbreak, the resistance rates of some antibiotics had decreased to varying degrees. Conclusion: Improving the understanding of vaginal flora and drug resistance in girls with vaginitis will facilitate the selection of highly effective and sensitive antibacterial drugs and reduce the production of drug-resistant strains.

A prognostic risk model, tumor immune environment modulation, and drug prediction of ferroptosis and amino acid metabolism-related genes in hepatocellular carcinoma.

The prognosis of hepatocellular carcinoma (HCC) is challenging due to its heterogeneity. Ferroptosis and amino acid metabolism have been shown to be closely related to HCC. We obtained HCC-related expression data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. We then crossed differentially expressed genes (DEGs), amino acid metabolism genes, and ferroptosis-related genes (FRGs) to obtain amino acid metabolism-ferroptosis-related differentially expressed genes (AAM-FR DEGs). Moreover, we developed a prognostic model using Cox analysis, followed by a correlation analysis of risk scores with clinical characteristics. We also performed an immune microenvironment analysis and drug sensitivity analysis. Finally, the expression levels of model genes were verified by quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemical assays. We found that the 18 AAM-FR DEGs were mainly enriched to the alpha-amino acid metabolic process and amino acid biosynthesis pathways. Cox analysis identified CBS, GPT2, SUV39H1, and TXNRD1 as prognostic biomarkers for the risk model construction. Our results showed that the risk scores differed between pathology stage, pathology T stage, and HBV, and the number of HCC patients in the two groups. In addition, the expression of PD-L1 and CTLA-4 was high in the high-risk group, and the half-maximal inhibitory concentration (IC50) of sorafenib also differed between the two groups. Finally, the experimental validation demonstrated that the expression of biomarkers was consistent with the study analysis. Therefore, in this study, we constructed and validated a prognostic model (CBS, GPT2, SUV39H1, and TXNRD1) related to ferroptosis and amino acid metabolism and examined their prognostic value for HCC.

N6-methyladenosine long non-coding RNAs reveal novel tool to implicate overall survival and immune microenvironment in renal clear cell carcinoma.

PURPOSE: This study aimed to investigate whether N6-methyladenosine (m6A)-related long non-coding RNAs (m6ARelncRNAs) could provide novel tools to predict overall survival of renal clear cell carcinoma. METHODS: The transcriptomic data and clinical information of patients with renal clear cell carcinoma from The Cancer Genome Atlas (TCGA) were analysed. Distinct m6A modification patterns were systemically analysed via consensus clustering analysis. An m6ARelncRNA signature was constructed in the training cohort using the least absolute shrinkage and selection operator (LASSO) analysis and validated in the test cohort. Potential predictive accuracy of the signature was further assessed via Kaplan-Meier survival, univariate and multivariate Cox regression and subgroup analyses. The Tumour Immune Dysfunction and Exclusion (TIDE) algorithm was used to investigate the role of m6ARelncRNAs in guiding immunotherapy for patients with renal carcinoma. RESULTS: An m6ARelncRNA signature based on only six lncRNAs was successfully constructed. The high-risk group derived from this signature had significantly poorer overall survival in both training and test cohorts (p < 0.001). Independent prognostic analysis further revealed that m6ARelncRNA risk (p < 0.01) was an independent risk factor for survival outcomes of renal carcinoma. TIDE algorithm revealed that immunotherapy response was poorer in the high-risk group than in the low-risk group. Drug sensitivity analysis based on IC50 revealed that high-risk patients were potentially sensitive to various anti-tumour drugs, including bortezomib, cisplatin, docetaxel, etoposide and sunitinib. CONCLUSION: m6ARelncRNAs provide novel tools that can be used to predict overall survival and examine the immune microenvironment of renal clear cell carcinoma.

Prognostic risk assessment model and drug sensitivity analysis of colon adenocarcinoma (COAD) based on immune-related lncRNA pairs.

PURPOSE: The aim of this study was to identify and screen long non-coding RNA (lncRNA) associated with immune genes in colon cancer, construct immune-related lncRNA pairs, establish a prognostic risk assessment model for colon adenocarcinoma (COAD), and explore prognostic factors and drug sensitivity. METHOD: Our method was based on data from The Cancer Genome Atlas (TCGA). To begin, we obtained all pertinent demographic and clinical information on 385 patients with COAD. All lncRNAs significantly related to immune genes and with differential expression were identified to construct immune lncRNA pairs. Subsequently, least absolute shrinkage and selection operator and Cox models were used to screen out prognostic-related immune lncRNAs for the establishment of a prognostic risk scoring formula. Finally, We analysed the functional differences between subgroups and screened the drugs, and establish an individual prediction nomogram model. RESULTS: Our final analysis confirmed eight lncRNA pairs to construct prognostic risk assessment model. Results showed that the high-risk and low-risk groups had significant differences (training (n = 249): p < 0.001, validation (n = 114): p = 0.022). The prognostic model was certified as an independent prognosis model. Compared with the common clinicopathological indicators, the prognostic model had better predictive efficiency (area under the curve (AUC) = 0.805). Finally, We have analysed highly differentiated cellular pathways such as mucosal immune response, identified 9 differential immune cells, 10 sensitive drugs, and establish an individual prediction nomogram model (C-index = 0.820). CONCLUSION: Our study verified that the eight lncRNA pairs mentioned can be used as biomarkers to predict the prognosis of COAD patients. Identified cells, drugs may have an positive effect on colon cancer prognosis.

Development and experimental verification of a prognosis model for cuproptosis-related subtypes in HCC.

BACKGROUND: Cuproptosis is a recently discovered mechanism of programmed cell death caused by intracellular aggregation of mitochondrial lipoylated proteins and destabilization of iron-sulfur proteins triggered by copper. Hepatocellular carcinoma (HCC) is a common malignant tumor with a poor prognosis. We aimed to predict the survival of patients with HCC using the cuproptosis-related gene (CRG) expression. METHODS: We analyzed the expression, methylation, and mutation status of CRGs in 538 HCC patients and correlated the date with clinical prognosis. HCC patients were divided into two clusters based on their CRG expression. The relationship between CRGs, risk genes, and the immune microenvironment was analyzed using the CIBERSORT algorithm and the single-cell data analysis method. A cuproptosis risk model was constructed according to the five risk genes using the LASSO COX method. To facilitate the clinical applicability of the proposed risk model, we constructed a nomogram and conducted an antineoplastic drug sensitivity analysis. RESULTS: Our results suggest that the expression levels of CRGs in HCC are regulated by methylation. The prognoses were significantly different between the patients of the two clusters. The prognostic risk score positively correlated with memory T cell activation and negatively correlated with natural killer (NK) and regulatory T cell activation. CONCLUSION: Our findings indicate the involvement of CRG regulation in HCC and provide new insights into prognosis assessment. Drug sensitivity analysis predicted drug candidates for the treatment of patients with different HCC subtypes.

Prognostic Value of Genomic Instability of m6A-Related lncRNAs in Lung Adenocarcinoma.

Background: Genomic instability of N6-methyladenosine (m6A)-related long noncoding RNAs (lncRNAs) plays a pivotal role in the tumorigenesis of lung adenocarcinoma (LUAD). Our study identified a signature of genomic instability of m6A-associated lncRNA signature and revealed its prognostic role in LUAD. Methods: We downloaded RNA-sequencing data and somatic mutation data for LUAD from The Cancer Genome Atlas (TCGA) and the GSE102287 dataset from the Gene Expression Omnibus (GEO) database. The "Limma" R package was used to identify a network of regulatory m6A-related lncRNAs. We used the Wilcoxon test method to identify genomic-instability-derived m6A-related lncRNAs. A competing endogenous RNA (ceRNA) network was constructed to identify the mechanism of the genomic instability of m6A-related lncRNAs. Univariate and multivariate Cox regression analyses were performed to construct a prognostic model for internal testing and validation of the prognostic m6A-related lncRNAs using the GEO dataset. Performance analysis was conducted to compare our prognostic model with the previously published lncRNA models. The CIBERSORT algorithm was used to explore the relationship of m6A-related lncRNAs and the immune microenvironment. Prognostic m6A-related lncRNAs in prognosis, the tumor microenvironment, stemness scores, and anticancer drug sensitivity were analyzed to explore the role of prognostic m6A-related lncRNAs in LUAD. Results: A total of 42 genomic instability-derived m6A-related lncRNAs were differentially expressed between the GS (genomic stable) and GU (genomic unstable) groups of LUAD patients. Four differentially expressed lncRNAs, 17 differentially expressed microRNAs, and 75 differentially expressed mRNAs were involved in the genomic-instability-derived m6A-related lncRNA-mediated ceRNA network. A prediction model based on 17 prognostic m6A-associated lncRNAs was constructed based on three TCGA datasets (all, training, and testing) and validated in the GSE102287 dataset. Performance comparison analysis showed that our prediction model (area under the curve [AUC] = 0.746) could better predict the survival of LUAD patients than the previously published lncRNA models (AUC = 0.577, AUC = 0.681). Prognostic m6A-related-lncRNAs have pivotal roles in the tumor microenvironment, stemness scores, and anticancer drug sensitivity of LUAD. Conclusion: A signature of genomic instability of m6A-associated lncRNAs to predict the survival of LUAD patients was validated. The prognostic, immune microenvironment and anticancer drug sensitivity analysis shed new light on the potential novel therapeutic targets in LUAD.

HIPPO signaling-related signature for predicting prognosis and therapeutic response in gastric cancer.

Background: Gastric cancer (GC) is a multifactorial progressive disease with high mortality and heterogeneous prognosis. Effective prognostic biomarkers for GC were critically needed. Hippo signaling pathway is one of the critical mechanisms regulating the occurrence and development of GC, and has potential clinical application value for the prognosis and treatment of GC patients. However, there is no effective signature based on Hippo signaling pathway-related genes (HSPRGs) to predict the prognosis and treatment response of GC patients. Our study aimed to build a HSPRGs signature and explore its performance in improving prognostic assessment and drug therapeutic response in GC. Methods: Based on gene expression profiles obtained from The Cancer Genome Atlas (TCGA) database, we identified differentially expressed HSPRGs and conducted univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct a multigene risk signature. Subsequently, the Kaplan-Meier curve and receiver operating characteristic (ROC) were performed to evaluate the predictive value of the risk signature in both training and validation cohort. Furthermore, we carried out univariate and multivariate Cox regression analysis to investigate the independent prognostic factors and establish a predictive nomogram. The enriched signaling pathways in risk signature were analyzed by gene set enrichment analysis (GSEA). Tumor immune dysfunction and exclusion (TIDE) and drug sensitivity analysis were performed to depict therapeutic response in GC. Results: In total, 38 differentially expressed HSPRGs were identified, and final four genes (DLG3, TGFB3, TGFBR1, FZD6) were incorporated to build the signature. The ROC curve with average 1-, 3-, and 5-year areas under the curve (AUC) equal to .609, .634, and .639. Clinical ROC curve revealed that risk signature was superior to other clinicopathological factors in predicting prognosis. Calibration curves and C-index (.655) of nomogram showed excellent consistency. Besides, in the immunotherapy analysis, exclusion (p < 2.22 × 10-16) and microsatellite instability (p = .0058) performed significantly differences. Finally, our results suggested that patients in the high-risk group were more sensitive to specific chemotherapeutic agents. Conclusion: Results support the hypothesis that Hippo-related signature is a novel prognostic biomarker and predictor, which could help optimize GC prognostic stratification and inform clinical medication decisions.

Analysis of pathogens and drug sensitivity in bronchoalveolar lavage fluid of children with severe community acquired pneumonia in Qingdao area / 中国小儿急救医学

Objective:To analyze the distribution and drug sensitivity of pathogens in bronchoalveolar lavage fluid(BALF)of children with severe community acquired pneumonia(CAP)in Qingdao from 2018 to 2020.Methods:The clinical data of 482 children with severe CAP in Qingdao admitted to Women and Children′s Hospital of Qingdao University were collected.BALF was collected by bronchoscopy for detection of bacteria and mycoplasma.Results:(1)Bacterial infection was detected in 139 cases(27.84%), mycoplasma infection in 119 cases(24.69%), and virus infection in 141 cases(29.25%). (2)The detection rates of bacteria and virus infection in the 1-12 months old group were higher.The detection rate of mycoplasma pneumoniae was the highest in the group over 5 years old.(3)A total of 139 strains were positive in bacterial culture of lavage fluid under bronchoscope: 55 strains(39.57%) of gram-negative bacilli and 84 strains(60.43%) of gram-positive cocci.Streptococcus pneumoniae was the most common gram-positive bacteria.Haemophilus influenzae was the most common gram-negative strain.(4)Streptococcus pneumoniae and Staphylococcus aureus were highly sensitive to amoxicillin clavulanate potassium, vancomycin and linezolid.The resistance rate to erythromycin was high(100%). (5)Haemophilus influenzae, Escherichia coli, Pseudomonas aeruginosa and Klebsiella pneumoniae were highly sensitive to meropenem and cefoperazone sulbactam.They were highly resistant to amoxicillin, ampicillin and cefuroxime(>80%).Conclusion:Severe CAP in Qingdao area is mainly caused by virus and bacteria within 1 year old.Mycoplasma pneumoniae infection is the main cause of children over 5 years old.Respiratory syncytial virus, adenovirus and parainfluenza virus are main causes of virus infection.Streptococcus pneumoniae and haemophilus influenzae are the main pathogens, which are more sensitive to vancomycin, linezolid, meropenem and cefoperazone sulbactam, but resistant to erythromycin and amoxicillin.

Dysregulation of SAA1, TUBA8 and Monocytes Are Key Factors in Ankylosing Spondylitis With Femoral Head Necrosis.

Introduction: The mechanism of ankylosing spondylitis with femoral head necrosis is unknown, and our study aimed investigate the effects of genetic and immune cell dysregulation on ankylosing spondylitis. Materials and Methods: The protein expression of all ligaments in ankylosing spondylitis with femoral head necrosis was obtained using label-free quantification protein park analysis of six pairs of specimens. The possible pathogenesis was explored using differential protein analysis, weighted gene co-expression network analysis, recording intersections with hypoxia-related genes, immune cell correlation analysis, and drug sensitivity analysis. Finally, routine blood test data from 502 AS and 162 healthy controls were collected to examine immune cell differential analysis. Results: SAA1 and TUBA8 were significantly expressed differentially in these two groups and correlated quite strongly with macrophage M0 and resting mast cells (P < 0.05). Routine blood data showed that monocytes were significantly more expressed in AS than in healthy controls (P < 0.05). SAA1 and TUBA8 were closely related to the sensitivity of various drugs, which might lead to altered drug sensitivity. Conclusion: Dysregulation of SAA1, TUBA8 and monocytes are key factors in ankylosing spondylitis with femoral head necrosis.

Comparison of the positive rate of microbiological examination in different clinical specimens / 中国基层医药

Objective@#To compare the positive rate of microbiological examination in different clinical specimens, and to provide reliable basis for improving the quality of microbiological examination and management of nosocomial infection.@*Methods@#A total of 2 028 bacterial culture specimens were collected from the hospitalized patients in the Second People's Hospital of Jinanfrom March 2016 to February 2018.The samples were examined by Micro Scan autoSCAN4 automatic bacteriological identification analyzer.Strictly according to the specification of the standard operation, the positive rates of microbial testingof all kinds of clinical specimens were statistically analyzed.@*Results@#The positive rate of microbiological examination in 2 028 clinical specimens was 44.33%.The positive rate of microbiological examination in sputum was the highest(58.96%), followed by ophthalmic secretion(40.64%), eye contents(37.96%), urine(34.55%), blood(21.11%).@*Conclusion@#The positive rate of microbiological examination is different in different clinical specimens.The epidemiological situation of nosocomial infection can be understood by analyzing the microbiological examination of different clinical specimens in clinic.In order to provide a reliable basis for clinical prevention and treatment of nosocomial infection, and to further improve the positive rate of clinical microbiological examination, we should actively carry out improvement countermeasures against its influencing factors.

[Effect of semen bacterial infection on semen parameters and analysis of drug resistance in 74376 male infertility patients].

OBJECTIVE: To investigate the effect of semen bacterial infection on semen parameters in male infertility patients and analyze of the drug resistance profile of the bacterial isolates. METHODS: According to the results of bacterial culture, the semen samples of 74376 infertile men collected between April, 2016 and April, 2017 were divided into infection group and non-infection group, and the infertility type and semen parameters were compared between the two groups. The bacterial species and the drug sensitivity of the isolates were analyzed. RESULTS: Bacterial infections were detected in 1.38% of the total semen samples collected. The positivity rate of semen bacterial infection was 1.41% in normal semen group, 1.55% in asthenospermia group, 1.18% in oligospermia group, 1.57% in asthenospermia/ oligospermia group, and 0.17% in azoospermia group. The positivity rate was lower in azoospermia group than in the other groups. Bacterial infection mainly affected sperm motility (P < 0.05), sperm density and forward motile sperm ratio (P < 0.01). The most common bacterial species causing the infections included, in the descending order of frequencies, Escherichia coli (63.59%), Klebsiella pneumoniae subspecies (19.80%) and Proteus mirabilis (13.22%). Drug susceptibility tests showed that the isolates of Escherichiacoli, Pneumonia Klebsiella pneumonia subspecies and Citrobacter koseri were commonly resistant to amoxicillin; Pseudomonas aeruginosa isolates were resistant to Bactrim and ampicillin/sulbactam; Staphylococcus aureus isolates were resistant to penicillin. CONCLUSIONS: Male infertile patients have a low bacterial infection rate in the semen. Bacterial infection severely affects the sperm fertilization process by causing impairment of sperm motility and lowered sperm density. Escherichia coli is the most common pathogenic bacterium for the semen infection. With the exception of Staphylococcus aureus, the other bacterial strains isolated were found to be sensitive to imipenem and meropenem.

Analysis of frequent species and antibacterial resistance of pathogenic bacteria causing infections in burn patients in a hospital from 2012 to 2014 / 国际检验医学杂志

Objective To investigate the frequent species of pathogenic bacteria causing infections in burn patients and their re‐sistance to commonly used antibacterial agents ,so as to provide references for rational use of antibacterials in clinic .Methods The distribution and drug susceptibility of pathogenic bacteria isolated from secretions of wound surfaces of 140 cases of burn patients from January 2012 to December 2014 were retrospectively analyzed .Results A total of 152 strains of pathogenic bacteria were iso‐lated .The gram‐negative bacteria accounted for 59 .2% ,in which Pseudomonas aeruginosa ,Proteus mirabilis and Acinetobacter bau‐mannii were the most common isolates ;the gram‐positive bacteria accounted for 34 .2% ,in which Staphylococcus aures ,Staphylo‐coccus haemolyticus and Enterococcus faecalis were the most common isolates ;and fungi were accounted for 6 .6% .A majority of these isolates were multiple resistant to the antibacterial agents .Conclusion Culturing ,identifing and carring out drug‐sensitivity test of pathogenic bacteria isolated from burn patients could provide basis for rational application of antibacterial agents and effec‐tive control of infection .

Analysis of Candida infections and drug sensitivity in intensive care unit / 中国中西医结合急救杂志

Objective To study the distribution of Candida infection and drug tolerance in intensive care unit(ICU). Methods A retrospective study was conducted. The critical patients admitted from January 2011 to December 2013 in ICU of the First Hospital of Jiaxing in Zhejiang Province were enrolled,and their clinical data with positive Candida culture and drug susceptibility results in specimens of sputum,urine,blood,ascites,bile, etc were collected. In the study of these 3 years in ICU,the situation of Candida infection,the distribution of positive specimen,the condition of distribution of different strains of Candida,and the Candida tolerance to antifungal drugs were analyzed. Results From 2011 to 2013,2 412 times of patients(including one patient had admitted into ICU for more than one time)were admitted into ICU in which 407 cases were of Candida infection(16.9%),and the rate of Candida infection was rising gradually in the 3 years〔2011 to 2013 Candida positive rates were 13.4%(77/573), 16.1%(146/907),19.7%(184/932)〕,the difference being statistically significant(P<0.01). In the 407 strains of Candida,166 strains(40.8%)were isolated from sputum,157(38.6%)from urine,53 strains(13.0%)ascites, 13 strains(3.1%)blood,11 strains(2.7%)bile,7 strains(1.7%)from other specimens. The strain distribution of Candida was mainly as follows:Candida albicans(174 strains),Candida glabrata(131 strains),Candida tropicalis (83 strains),Candida parapailosis(5 strains),Candida krusei(12 strains),and 2 strains of rare Candida portugal and Lipolztica. From 2011 to 2013,the highest tolerance of Candida albicans,Candida glabrata,Candida tropicalis to fluconazole,itraconazole,Fushita Yasu and other antifungal drugs was in 2013,and the lowest was in 2012,the rates of tolerance of the above 3 strains of Candida to amphotericin B being 0,to itraconazole being the highest(10.9%, 27.8%,9.6%,respectively),to Fushita Yasu the secondary(6.6%,11.0%,0,respectively)and to fluconazole the last(4.7%,7.4%,1.9%,respectively),and the rates of tolerance of Candida parapsilosis,Candida krusei,Candida Portugal,Candida lipolztica to amphotericin B,fluconazole,itraconazole,Fushita Yasu were all 0. Conclusion In ICU,the Candida infection is mainly in the respiratory tract and urinary tract,its rate of infection has a tendency of rising,and the rate of Candida tolerance to itraconazole is the highest.