GenDrux: A biomedical literature search system to identify gene expression-based drug sensitivity in breast cancer

Background This paper describes the development of a web-based tool, GenDrux, which extracts and presents (over the Internet) information related to the disease-gene-drug nexus. This information is archived from the relevant biomedical literature using automated methods. GenDrux is designed to alleviate the difficulties of manually processing the vast biomedical literature to identify disease-gene-drug relationships. GenDrux will evolve with the literature without additional algorithmic modifications. Results GenDrux, a pilot system, is developed in the domain of breast cancer and can be accessed at http://www.microarray.uab.edu/drug_gene.pl. GenDrux can be queried based on drug, gene and/or disease name. From over 8,000 relevant abstracts from the biomedical literature related to breast cancer, we have archived a corpus of more than 4,000 articles that depict gene expression-drug activity relationships for breast cancer and related cancers. The archiving process has been automated. Conclusions The successful development, implementation, and evaluation of this and similar systems when created may provide clinicians with a tool for literature management, clinical decision making, thus setting the platform for personalized therapy in the future

GenDrux: A biomedical literature search system to identify gene expression-based drug sensitivity in breast cancer

Background This paper describes the development of a web-based tool, GenDrux, which extracts and presents (over the Internet) information related to the disease-gene-drug nexus. This information is archived from the relevant biomedical literature using automated methods. GenDrux is designed to alleviate the difficulties of manually processing the vast biomedical literature to identify disease-gene-drug relationships. GenDrux will evolve with the literature without additional algorithmic modifications. Results GenDrux, a pilot system, is developed in the domain of breast cancer and can be accessed at http://www.microarray.uab.edu/drug_gene.pl. GenDrux can be queried based on drug, gene and/or disease name. From over 8,000 relevant abstracts from the biomedical literature related to breast cancer, we have archived a corpus of more than 4,000 articles that depict gene expression-drug activity relationships for breast cancer and related cancers. The archiving process has been automated. Conclusions The successful development, implementation, and evaluation of this and similar systems when created may provide clinicians with a tool for literature management, clinical decision making, thus setting the platform for personalized therapy in the future

Hybrid Models Identified a 12-Gene Signature for Lung Cancer Prognosis and Chemoresponse Prediction

Lung cancer remains the leading cause of cancer-related deaths worldwide. The recurrence rate ranges from 35-50% among early stage non-small cell lung cancer patients. To date, there is no fully-validated and clinically applied prognostic gene signature for personalized treatment.From genome-wide mRNA expression profiles generated on 256 lung adenocarcinoma patients, a 12-gene signature was identified using combinatorial gene selection methods, and a risk score algorithm was developed with Naïve Bayes. The 12-gene model generates significant patient stratification in the training cohort HLM & UM (n = 256; log-rank P = 6.96e-7) and two independent validation sets, MSK (n = 104; log-rank P = 9.88e-4) and DFCI (n = 82; log-rank P = 2.57e-4), using Kaplan-Meier analyses. This gene signature also stratifies stage I and IB lung adenocarcinoma patients into two distinct survival groups (log-rank P<0.04). The 12-gene risk score is more significant (hazard ratio = 4.19, 95% CI: [2.08, 8.46]) than other commonly used clinical factors except tumor stage (III vs. I) in multivariate Cox analyses. The 12-gene model is more accurate than previously published lung cancer gene signatures on the same datasets. Furthermore, this signature accurately predicts chemoresistance/chemosensitivity to Cisplatin, Carboplatin, Paclitaxel, Etoposide, Erlotinib, and Gefitinib in NCI-60 cancer cell lines (P<0.017). The identified 12 genes exhibit curated interactions with major lung cancer signaling hallmarks in functional pathway analysis. The expression patterns of the signature genes have been confirmed in RT-PCR analyses of independent tumor samples.The results demonstrate the clinical utility of the identified gene signature in prognostic categorization. With this 12-gene risk score algorithm, early stage patients at high risk for tumor recurrence could be identified for adjuvant chemotherapy; whereas stage I and II patients at low risk could be spared the toxic side effects of chemotherapeutic drugs

JavaStat: a Java/R-based statistical computing environment

R, Java, JavaStat, RMI, JRI,

Mullite-based ceramic tiles produced solely from high-alumina fly ash: Preparation and sintering mechanism

Mullite-based ceramic tiles were successfully prepared using only high-alumina fly ash (HAFA) at relatively low sintering temperatures (1100-1400 degrees C). The effects of alkali activation on the chemical composition, mineral phase, and morphology of the HAFA were respectively characterised by ICP-OES, XRD, and SEM methods. The alkali-activation pretreatment not only modifies the chemical composition of HAFA to match that of mullite, but also can introduce Na-rich compounds to promote sintering. The macroscopic and microscopic characteristics of the fully ash-based ceramic tiles formed at different sintering temperatures were examined. The ceramic samples sintered at 1300 degrees C exhibited optimal post-sintering properties (relative density: 90.85%, water absorption: 0.10%, rupture modulus: 109.67 MPa, linear shrinkage: 15.70%, and apparent porosity: 0.68%) and a well-developed cubic puncheon-shaped mullite morphology. Finally, through the isothermal sintering method, the melt viscosities and the sintering kinetics were calculated theoretically, and the results show that the alkali activation could dramatically reduce the melt viscosity and the apparent activation energy. This research may provide a new method in utilising the vast amounts of HAFA waste to produce mullite-based ceramic tiles at low costs. (C) 2017 Elsevier B.V. All rights reserved

MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes

The majority of lung cancer patients are diagnosed with metastatic disease. This study identified a set of 73 microRNAs (miRNAs) that classified lung cancer tumors from normal lung tissues with an overall accuracy of 96.3% in the training patient cohort (n = 109) and 91.7% in unsupervised classification and 92.3% in supervised classification in the validation set (n = 375). Based on association with patient survival (n = 1016), 10 miRNAs were identified as potential tumor suppressors (hsa-miR-144, hsa-miR-195, hsa-miR-223, hsa-miR-30a, hsa-miR-30b, hsa-miR-30d, hsa-miR-335, hsa-miR-363, hsa-miR-451, and hsa-miR-99a), and 4 were identified as potential oncogenes (hsa-miR-21, hsa-miR-31, hsa-miR-411, and hsa-miR-494) in lung cancer. Experimentally confirmed target genes were identified for the 73 diagnostic miRNAs, from which proliferation genes were selected from CRISPR-Cas9/RNA interference (RNAi) screening assays. Pansensitive and panresistant genes to 21 NCCN-recommended drugs with concordant mRNA and protein expression were identified. DGKE and WDR47 were found with significant associations with responses to both systemic therapies and radiotherapy in lung cancer. Based on our identified miRNA-regulated molecular machinery, an inhibitor of PDK1/Akt BX-912, an anthracycline antibiotic daunorubicin, and a multi-targeted protein kinase inhibitor midostaurin were discovered as potential repositioning drugs for treating lung cancer. These findings have implications for improving lung cancer diagnosis, optimizing treatment selection, and discovering new drug options for better patient outcomes

Is SubcellularLocalization Informative for Modeling Protein-protein Interaction Signal?

Statistical methods have been intensively applied in genomic signal processing (Dougherty et al. 2005). For budding yeast Saccharomyces cerevisiae with around 6000 proteins, genome-wide protein-protein-interaction (PPI) (Fromont-Racine et al. 2000, Ito et al. 2001, Newman et al. 2000, and Uetz et al. 2000 among others) and protein subcellular localization (PSL) (Huh et al. 2003) data recently became available and for the latter the presence of 4152 proteins is experimentally tested in each of the 22 subcellular compartments. Recent work shows that multiple biological sources are helpful for both PSL and PPI predictions, and this paper studies statistical feasibility of modeling PPI from PSL since PSLs may play different marginal or joint roles in the complex regulatory network. However, our results indicate that PSL may be controversial for this purpose as an independent source

Preparation of aromatic polyamide with ultra-high intrinsic breakdown strength via layered stacking structure induced by coplanar monomer

Dielectric polymers with high breakdown strength (Eb) and high retention rate of breakdown strength at elevated temperature have important application potential in advanced electrical insulation devices. Herein, the aromatic heterocyclic diamine monomer, 5-amino-2-(2-hydroxy-4-aminobenzene)-benzoxazole (HBOA), was synthesized. Theoretical calculation and single crystal date demonstrated fully the formation of intramolecular H-bond of OH?N]C between benzoxazole and benzene ring in HBOA, which endows the monomer a coplanar geometry. Moreover, the aromatic polyamide films were prepared by polycondensation of HBOA, and the in -plane orientation of films increases with increasing the coplanar HBOA content, which reduces the orientation confusion and cavity of chains packing. When the HBOA content is over 70%, the films exhibit dense-layered stacking structure with high crystallinity. It is found that the dense-layered stacking structure can prevent the films breakdown and failure effectively, which endows the homopolymerization (HBOA-100) film with Eb of 771 kV/mm. Moreover, the Eb of the HBOA-100 film is still as high as 634 kV/mm at 150 ?C, and its retention rate of Eb reaches 82% in high temperature environment. In addition, tensile strength of the HBOA-100 film is nearly 343 MPa, glass transition temperature is about 334 ?C and the thermal stability up to 487 ?C

Preparation of aromatic polyamide with ultra-high intrinsic breakdown strength via layered stacking structure induced by coplanar monomer

Dielectric polymers with high breakdown strength (Eb) and high retention rate of breakdown strength at elevated temperature have important application potential in advanced electrical insulation devices. Herein, the aromatic heterocyclic diamine monomer, 5-amino-2-(2-hydroxy-4-aminobenzene)-benzoxazole (HBOA), was synthesized. Theoretical calculation and single crystal date demonstrated fully the formation of intramolecular H-bond of OH?N]C between benzoxazole and benzene ring in HBOA, which endows the monomer a coplanar geometry. Moreover, the aromatic polyamide films were prepared by polycondensation of HBOA, and the in -plane orientation of films increases with increasing the coplanar HBOA content, which reduces the orientation confusion and cavity of chains packing. When the HBOA content is over 70%, the films exhibit dense-layered stacking structure with high crystallinity. It is found that the dense-layered stacking structure can prevent the films breakdown and failure effectively, which endows the homopolymerization (HBOA-100) film with Eb of 771 kV/mm. Moreover, the Eb of the HBOA-100 film is still as high as 634 kV/mm at 150 ?C, and its retention rate of Eb reaches 82% in high temperature environment. In addition, tensile strength of the HBOA-100 film is nearly 343 MPa, glass transition temperature is about 334 ?C and the thermal stability up to 487 ?C