The co-colonization prevalence of Pseudomonas aeruginosa and Aspergillus fumigatus in cystic fibrosis: A systematic review and meta-analysis.

PURPOSE: The co-colonization prevalence of P. aeruginosa and A. fumigatus in cystic fibrosis (CF) has been inconsistently reported. The purpose of this systematic review and meta-analysis was to estimate the overall co-colonization prevalence of P. aeruginosa and A. fumigatus in CF. METHODS: The Embase, PubMed and Web of Science databases were systematically searched for studies reporting the co-colonization prevalence of P. aeruginosa and A. fumigatus in CF. The co-colonization prevalence of two pathogenic microorganisms in the individual studies was assessed by calculating the proportion and 95% confidence interval (CI). The random effects model was used to calculate the pooled prevalence. The I2 test was used to assess statistical heterogeneity. The funnel plot and two statistical methods were used to assess publication bias. RESULTS: Twenty-three eligible studies were included in this analysis. The pooled co-colonization prevalence of P. aeruginosa and A. fumigatus in CF patients was 15.8% (95% CI: 9.9-21.8). The co-colonization prevalence of P. aeruginosa and A. fumigatus chronic colonization was lower than that of intermittent colonization, higher in sputum cultures than in bronchoalveolar lavage (BAL) cultures, and lower in children than in adults. There was a statistically significant difference in co-colonization prevalence among studies from different decades, but the prevalence was similar in different geographical regions and with different study types. CONCLUSIONS: The co-colonization prevalence of P. aeruginosa and A. fumigatus in the lower respiratory tract of CF patients was high. The anti-infective treatment in exacerbation of CF should be considered to cover the two pathogenic microorganisms simultaneously. Large-scale research is still needed to obtain more accurate co-colonization data.

Association of furanone C-30 with biofilm formation & antibiotic resistance in Pseudomonas aeruginosa.

Background & objectives: Pseudomonas aeruginosa is an opportunistic pathogen that can cause nosocomial bloodstream infections in humans. This study was aimed to explore the association of furanone C-30 with biofilm formation, quorum sensing (QS) system and antibiotic resistance in P. aeruginosa. Methods: An in vitro model of P. aeruginosa bacterial biofilm was established using the standard P. aeruginosa strain (PAO-1). After treatment with 2.5 and 5 µg/ml of furanone C-30, the change of biofilm morphology of PAO-1 was observed, and the expression levels of QS-regulated virulence genes (lasB, rhlA and phzA2), QS receptor genes (lasR, rhlR and pqsR) as well as QS signal molecule synthase genes (lasI, rhlI, pqsE and pqsH) were determined. Besides, the AmpC expression was quantified in planktonic and mature biofilm induced by antibiotics. Results: Furanone C-30 treatment significantly inhibited biofilm formation in a dose-dependent manner. With the increase of furanone C-30 concentration, the expression levels of lasB, rhlA, phzA2, pqsR, lasI, rhlI pqsE and pqsH significantly decreased in mature biofilm bacteria while the expression levels of lasR and rhlR markedly increased. The AmpC expression was significantly decreased in both planktonic and biofilm bacteria induced by imipenem and ceftazidime. Interpretation & conclusions: Furanone C-30 may inhibit biofilm formation and antibiotic resistance in P. aeruginosa through regulating QS genes. The inhibitory effect of furanone C-30 on las system appeared to be stronger than that on rhl system. Further studies need to be done with different strains of P. aeruginosa to confirm our findings.

Construction of a specific SVM classifier and identification of molecular markers for lung adenocarcinoma based on lncRNA-miRNA-mRNA network.

BACKGROUND: Novel diagnostic predictors and drug targets are needed for LUAD (lung adenocarcinoma). We aimed to build a specific SVM (support vector machine) classifier for diagnosis of LUAD and identify molecular markers with prognostic value for LUAD. METHODS: The expression differences of miRNAs, lncRNAs and mRNAs between LUAD and normal samples were compared using data from TCGA (The Cancer Genome Atlas) database. A LUAD related miRNA-lncRNA-mRNA network was constructed, based on which feature genes were selected for the construction of LUAD specific SVM classifier. The robustness and transferability of SVM classifier were validated using gene expression profile datasets GSE43458 and GSE10072. Prognostic markers were identified from the network. A set of LUAD-related differentially expressed miRNAs, lncRNAs and miRNAs were identified and a LUAD related miRNA-lncRNA-mRNA network was obtained. The LUAD specific SVM classifier constructed on the basis of the network was robust and efficient for classification of samples from TCGA dataset and two independent validation datasets. RESULTS: Eight RNAs with prognostic value were identified, including hsa-miR-96, hsa-miR-204, PGM5P2 (phosphoglucomutase 5 pseudogene 2), SFTA1P (surfactant associated 1), RGS20 (regulator of G protein signaling 20), RGS9BP (RGS9-binding protein), FGB (fibrinogen beta chain) and INA (alpha-internexin). Among them, RGS20 and INA were regulated by hsa-miR-96. RGS20 was also regulated by hsa-miR-204, which was a potential target of SFTA1P. CONCLUSION: The LUAD specific SVM classifier may serve as a novel diagnostic predictor. hsa-miR-96, hsa-miR-204, PGM5P2, SFTA1P, RGS20, RGS9BP, FGB and INA may serve as prognostic markers in clinical practice.

Chronic Obstructive Pulmonary Disease Molecular Subtyping and Pathway Deviation-Based Candidate Gene Identification.

OBJECTIVE: The aim of this study was to identify the molecular subtypes of chronic obstructive pulmonary disease (COPD) and to prioritize COPD candidate genes using bioinformatics methods. MATERIALS AND METHODS: In this bioinformatics study, the gene expression dataset GSE76705 (including 229 COPD samples) and known COPD-related genes (candidate genes) were downloaded from the Gene Expression Omnibus (GEO) and the Online Mendelian Inheritance in Man (OMIM) databases respectively. Based on the expression values of the candidate genes, COPD samples were divided into molecular subtypes through hierarchical clustering analysis. Candidate genes were accordingly allocated into the defined molecular subtypes and functional enrichment analysis was undertaken. Pathway deviation scores were then analyzed, followed by the analysis of clinical indicators (FEV1, FEV1/FVC, age and gender) of COPD patients in each subtype, and prediction models were constructed. Furthermore, the gene expression dataset GSE71220 was used to bioinformatically validate our results. RESULTS: A total of 213 COPD-related genes were identified, which divided samples into three subtypes based on the gene expression values. After intersection analysis, 160 common genes including transforming growth factor ß1 (TGFB1), epidermal growth factor receptor (EGFR) and interleukin 13 (IL13) were obtained. Functional enrichment analysis identified 22 pathways such as 'hsa04060: cytokine-cytokine receptor interaction pathways, 'hsa04110: cell cycle' and 'hsa05222: small cell lung cancer'. Pathways in subtype 2 had higher deviation scores. Furthermore, three receiver operating characteristic (ROC) curves (accuracies >80%) were constructed. The three subtypes in COPD samples were also identified in the validation dataset GSE71220. CONCLUSION: COPD may be further subdivided into several molecular subtypes, which may be useful in improving COPD therapy based on the molecular subtype of a patient.

High Expression of S100A6 Predicts Unfavorable Prognosis of Lung Squamous Cell Cancer.

BACKGROUND S100 family of proteins is mainly involved in regulation of intracellular calcium homeostasis. Aberrant expression of S100 family members has been reported in many types of cancers. However, as a member of S100 family, the prognostic value of S100A6 for lung squamous cell carcinoma (SCC) has not been well-studied. MATERIAL AND METHODS Using immunohistochemistry, we investigated the expression of S100A6 in 177 patients with SCC and further divided the cohort into a high S100A6 expression group and a low S100A6 expression group. The chi-square test was applied to analyze the correlation between S100A6 expression and clinicopathological factors. Univariate analysis using the Kaplan-Meier method was performed to compare the difference in survival rates between the high S100A6 expression group and the low S100A6 expression group; multivariate analysis with Cox regression model was used to identify independent prognostic risk factors. RESULTS In our experiment, we demonstrated that the expression of S100A6 was significantly associated with patient age and tumor differentiation. High-expression of S100A6 was shown to be substantially related to the unfavorable prognosis of SCC. Moreover, our results confirmed that S100A6 was an independent risk factor for SCC prognosis, and could predict unfavorable prognosis. CONCLUSIONS High-expression of S100A6 was identified as an independent unfavorable prognostic factor for SCC, suggesting that targeting S100A6 may result in the development of potential targeted drug for SCC.

Protective Effects of Arachidonic Acid Against Paraquat-Induced Pulmonary Injury.

In this study, we aimed to study the effects of arachidonic acid (AA) on acute lung injury (ALI) caused by paraquat (PQ) in mice. Male Kunming mice were randomly divided into three groups: control group, PQ group, and PQ + AA group (n = 24). The mice in the PQ and PQ + AA groups received a single oral dose of 20 mg/kg bodyweight PQ, and the mice of the PQ + AA group were challenged by 500 mg/kg bodyweight AA posttreatment 2 h after PQ administration. The results indicated that the administration of AA significantly increased the activity of superoxide dismutase (SOD), decreased the activity of myeloperoxidase (MPO), the content of malondialdehyde (MDA), and the level of lactate dehydrogenase (LDH). Pathological examination also revealed that AA effectively alleviated PQ-induced histological damage. Furthermore, AA significantly reduced PQ-induced upregulations of inflammatory mediators such as tumor necrosis factor (TNF)-α, interleukin (IL)-1ß, IL-6, and IL-8. These results demonstrated that AA had effective protection against PQ-induced ALI.