Synthesis and application of Fe3O4/GO/PVP composite material for methylene blue adsorption

In this study, Fe3O4/GO/PVP (FGP) was successfully synthesized and efficiently applied for absorbing methylene blue. First, GO was synthesized by Hummer’s method from waste home-batteries. The chemical co-precipitation method was used to fabricate Fe3O4/GO from a mixture solution of GO, Fe3+, Fe2+. Polyvinylpyrrolidone PVP was selected to functionalize Fe3O4/GO and form Fe3O4/GO/PVP for improving dispersibility purpose in aqueous solution. The obtained Fe3O4/GO/PVP was characterized by XRD, FT-IR, BET, FE-SEM, UV-Vis techniques. Moreover, the effecting factors as pH, time adsorption, initial concentration of methylene blue were conducted. Adsorption isotherm models were also identified. The results showed that specific surface area of FGP-3 was 70.0 m2.g-1, the Freundlich isotherm model was suitable and the Dubinin - Radushkevich isotherm model showed that the process was physical adsorption. The maximum capacity (qmax) was 30.4 mg.g-1. These findings prove Fe3O4/GO/PVP as an inexpensive and efficient adsorbent for removal of cationic dyes

Frequent inappropriate use of unweighted summary statistics in systematic reviews of pathogen genotypes or genogroups.

OBJECTIVES: Our study aimed to systematically assess and report the methodological quality used in epidemiological systematic reviews (SRs) and meta-analysis (MA) of pathogen genotypes/genogroups. STUDY DESIGN AND SETTING: Nine electronic databases and manual search of reference lists were used to identify relevant studies. The method types were divided into three groups: 1) with weighted pooling analysis (which we call MA), (2) unweighted analysis of the study-level measures (which we call summary statistics), and (3) without any data pooling (which we call SR only). Characteristics were evaluated using Assessment of Multiple Systematic Reviews (AMSTAR), Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA), and Risk Of Bias In Systematic reviews (ROBIS) tools. The protocol was registered in PROSPERO with CRD42017078146. RESULTS: Among 36 included articles, 5 (14%) studies conducted SR only, 16 (44%) performed MA, and 15 (42%) used summary statistics. The univariable and multivariable linear regression of AMSTAR and PRISMA scores showed that MA had higher quality compared with those with summary statistics. The SR only and summary statistics groups had approximately equal scores among three scales of AMSTAR, PRISMA, and ROBIS. The methodological quality of epidemiological studies has improved from 1999 to 2017. CONCLUSION: Despite the frequent use of unweighted summary statistics, MA remains the most suitable method for reaching rational conclusions in epidemiological studies of pathogen genotypes/genogroups

BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Background: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC

Identification of six new susceptibility loci for invasive epithelial ovarian cancer.

Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.COGS project is funded through a European Commission's Seventh Framework Programme grant (agreement number 223175 ] HEALTH ]F2 ]2009 ]223175). The CIMBA data management and data analysis were supported by Cancer Research.UK grants 12292/A11174 and C1287/A10118. The Ovarian Cancer Association Consortium is supported by a grant from the Ovarian Cancer Research Fund thanks to donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07). The scientific development and funding for this project were in part supported by the US National Cancer Institute GAME ]ON Post ]GWAS Initiative (U19 ]CA148112). This study made use of data generated by the Wellcome Trust Case Control consortium. Funding for the project was provided by the Wellcome Trust under award 076113. The results published here are in part based upon data generated by The Cancer Genome Atlas Pilot Project established by the National Cancer Institute and National Human Genome Research Institute (dbGap accession number phs000178.v8.p7). The cBio portal is developed and maintained by the Computational Biology Center at Memorial Sloan ] Kettering Cancer Center. SH is supported by an NHMRC Program Grant to GCT. Details of the funding of individual investigators and studies are provided in the Supplementary Note. This study made use of data generated by the Wellcome Trust Case Control consortium, funding for which was provided by the Wellcome Trust under award 076113. The results published here are, in part, based upon data generated by The Cancer Genome Atlas Pilot Project established by the National Cancerhttp://dx.doi.org/10.1038/ng.3185This is the Author Accepted Manuscript of 'Identification of six new susceptibility loci for invasive epithelial ovarian cancer' which was published in Nature Genetics 47, 164–171 (2015) © Nature Publishing Group - content may only be used for academic research

Polygenic Risk Modelling for Prediction of Epithelial Ovarian Cancer Risk

Funder: Funding details are provided in the Supplementary MaterialAbstractPolygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally-efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestry; 7,669 women of East Asian ancestry; 1,072 women of African ancestry, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestry. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38(95%CI:1.28–1.48,AUC:0.588) per unit standard deviation, in women of European ancestry; 1.14(95%CI:1.08–1.19,AUC:0.538) in women of East Asian ancestry; 1.38(95%CI:1.21-1.58,AUC:0.593) in women of African ancestry; hazard ratios of 1.37(95%CI:1.30–1.44,AUC:0.592) in BRCA1 pathogenic variant carriers and 1.51(95%CI:1.36-1.67,AUC:0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.</jats:p

Selecting Partners in Strategic Alliances: An Application of the SBM DEA Model in the Vietnamese Logistics Industry

Background: Strategic alliance is a popular strategic option for business entities to strengthen the competitive advantages of all partners in a partnership. The global logistics industry has witnessed the formulation of several successful strategic alliances. However, the Vietnamese logistics industry seems to grow slowly and lacks long-term inter-firm partnerships. In such a context, it is critical to have a more effective approach to selecting partners in strategic alliances to increase long-term relationships and firm performance. Method: Thus, this study proposes using the SBM-I-C DEA model to examine and suggest partners for Vietnamese logistics firms to form strategic alliances. Results: Our findings show that integrating technology in managing strategic alliances will foster companies in the alliance to formulate a better strategy with up-to-date information on policies. Conclusion: Using the SBM-I-C DEA model, companies can minimize operating costs and optimize delivery time. Thus, companies can better satisfy customers. From the research findings, some implications are proposed for Vietnamese logistics companies

Selecting Partners in Strategic Alliances: An Application of the SBM DEA Model in the Vietnamese Logistics Industry

Background: Strategic alliance is a popular strategic option for business entities to strengthen the competitive advantages of all partners in a partnership. The global logistics industry has witnessed the formulation of several successful strategic alliances. However, the Vietnamese logistics industry seems to grow slowly and lacks long-term inter-firm partnerships. In such a context, it is critical to have a more effective approach to selecting partners in strategic alliances to increase long-term relationships and firm performance. Method: Thus, this study proposes using the SBM-I-C DEA model to examine and suggest partners for Vietnamese logistics firms to form strategic alliances. Results: Our findings show that integrating technology in managing strategic alliances will foster companies in the alliance to formulate a better strategy with up-to-date information on policies. Conclusion: Using the SBM-I-C DEA model, companies can minimize operating costs and optimize delivery time. Thus, companies can better satisfy customers. From the research findings, some implications are proposed for Vietnamese logistics companies

A porphodimethene chemical inhibitor of uroporphyrinogen decarboxylase.

Uroporphyrinogen decarboxylase (UROD) catalyzes the conversion of uroporphyrinogen to coproporphyrinogen during heme biosynthesis. This enzyme was recently identified as a potential anticancer target; its inhibition leads to an increase in reactive oxygen species, likely mediated by the Fenton reaction, thereby decreasing cancer cell viability and working in cooperation with radiation and/or cisplatin. Because there is no known chemical UROD inhibitor suitable for use in translational studies, we aimed to design, synthesize, and characterize such a compound. Initial in silico-based design and docking analyses identified a potential porphyrin analogue that was subsequently synthesized. This species, a porphodimethene (named PI-16), was found to inhibit UROD in an enzymatic assay (IC50 = 9.9 µM), but did not affect porphobilinogen deaminase (at 62.5 µM), thereby exhibiting specificity. In cellular assays, PI-16 reduced the viability of FaDu and ME-180 cancer cells with half maximal effective concentrations of 22.7 µM and 26.9 µM, respectively, and only minimally affected normal oral epithelial (NOE) cells. PI-16 also combined effectively with radiation and cisplatin, with potent synergy being observed in the case of cisplatin in FaDu cells (Chou-Talalay combination index <1). This work presents the first known synthetic UROD inhibitor, and sets the foundation for the design, synthesis, and characterization of higher affinity and more effective UROD inhibitors