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The aim of this study was to compare nonrandom associations between physically adjacent single methylation polymorphism loci among rheumatoid arthritis (RA) and normal subjects for investigating RA‐risk methylation haplotypes (meplotype). With 354 ACPA‐positive RA patients and 335 normal controls selected from a case–control study based on Swedish population, we conducted the first RA epigenome‐wide meplotype association study using our software EWAS2.0, mainly including (i) converted the β value to methylation genotype (menotype) data, (ii) identified methylation disequilibrium (MD) block, (iii) calculated frequent of each meplotypes in MD block and performed case–control association test and (iv) screened for RA‐risk meplotypes by odd ratio (OR) and p‐values. Ultimately, 545 meplotypes on 334 MD blocks were identified significantly associated with RA (p‐value <.05). These meplotypes were mapped to 329 candidate genes related to RA. Subsequently, combined with gene optimization, eight RA‐risk meplotypes were identified on three risk genes: HLA‐DRB1, HLA‐DRB5 and HLA‐DQB1. Our results reported the relationship between DNA methylation pattern on HLA‐DQB1 and the risk of RA for the first time, demonstrating the co‐demethylation of 'cg22984282' and 'cg13423887' on HLA‐DQB1 gene (meplotype UU, p‐value = 2.90E − 6, OR = 1.68, 95% CI = [1.35, 2.10]) may increase the risk of RA. Our results demonstrates the potential of methylation haplotype analysis to identify RA‐related genes from a new perspective and its applicability to the study of other disease. [ABSTRACT FROM AUTHOR]

Tumour heterogeneity is an obstacle to effective breast cancer diagnosis and therapy. DNA methylation is an important regulator of gene expression, thus characterizing tumour heterogeneity by epigenetic features can be clinically informative. In this study, we explored specific prognosis‐subtypes based on DNA methylation status using 669 breast cancers from the TCGA database. Nine subgroups were distinguished by consensus clustering using 3869 CpGs that significantly influenced survival. The specific DNA methylation patterns were reflected by different races, ages, tumour stages, receptor status, histological types, metastasis status and prognosis. Compared with the PAM50 subtypes, which use gene expression clustering, DNA methylation subtypes were more elaborate and classified the Basal‐like subtype into two different prognosis‐subgroups. Additionally, 1252 CpGs (corresponding to 888 genes) were identified as specific hyper/hypomethylation sites for each specific subgroup. Finally, a prognosis model based on Bayesian network classification was constructed and used to classify the test set into DNA methylation subgroups, which corresponded to the classification results of the train set. These specific classifications by DNA methylation can explain the heterogeneity of previous molecular subgroups in breast cancer and will help in the development of personalized treatments for the new specific subtypes. [ABSTRACT FROM AUTHOR]

Plantation Chinese fir wood was modified by low molecular weight phenol melamine urea formaldehyde (PMUF) resin, boron compounds (BB), and the mixture of PMUF/BB (PMUF-BB), followed by a curing step. The fire performance and thermal degradation of wood was measured by limiting oxygen index instrument, cone calorimeter, and simultaneous thermal analysis. The results showed that the limiting oxygen index increased to 50.7%, 43.5%, and 55.0% for BB, PMUF, and PMUF-BB samples, respectively. The PMUF resin decreased the heat release rate of wood but increased the total heat release compared with the control samples. The thermal analysis results demonstrated that PMUF resin enhanced the thermal stability of wood, however, had little impact on the residual chars. Combinative treatment with boron compounds could substantially reduce the fire risk for PMUF-modified wood, making them especially useful for application in public settings. [ABSTRACT FROM AUTHOR]

Background: Both genetic and environmental factors contribute to the development of periodontitis. Genetic studies identified a variety of candidate genes for periodontitis. The aim of the present study is to identify the most promising candidate genes for periodontitis using an integrative gene ranking method. Methods: Seed genes that were confirmed to be associated with periodontitis were identified using text mining. Three types of candidate genes were then extracted from different resources (expression profiles, genome-wide association studies). Combining the seed genes, four freely available bioinformatics tools (ToppGene, DIR, Endeavour, and GPEC) were integrated for prioritization of candidate genes. Candidate genes that identified with at least three programs and ranked in the top 20 by each program were considered the most promising. Results: Prioritization analysis resulted in 21 promising genes involved or potentially involved in periodontitis. Among them, IL18 (interleukin 18), CD44 (CD44 molecule), CXCL1 (chemokine [CXC motif] ligand 1), IL6ST (interleukin 6 signal transducer), MMP3 (matrix metallopeptidase 3), MMP7, CCR1 (chemokine [C--C motif] receptor 1), MMP13, and TLR9 (Toll-like receptor 9) had been associated with periodontitis. However, the roles of other genes, such as CSF3 (colony stimulating factor 3 receptor), CD40, TNFSF14 (tumor necrosis factor receptor superfamily, member 14), IFNB1 (interferon-β1), TIRAP (toll--interleukin 1 receptor domain containing adaptor protein), IL2RA (interleukin 2 receptor α), ETS1 (v-ets avian erythroblastosis virus E26 oncogene homolog 1), GADD45B (growth arrest and DNA-damage-inducible 45 β), BIRC3 (baculoviral IAP repeat containing 3), VAV1 (vav 1 guanine nucleotide exchange factor), COL5A1 (collagen, type V, α1), and C3 (complement component 3), have not been investigated thoroughly in the process of periodontitis. These genes are mainly involved in bacterial infection, immune response, and inflammatory reaction, suggesting that further characterizing their roles in periodontitis will be important. Conclusions: A combination of computational tools will be useful in mining candidate genes for periodontitis. These theoretical results provide new clues for experimental biologists to plan targeted experiments. [ABSTRACT FROM AUTHOR]

A surface plasmon resonance (SPR) sensor based on exposed‐core microstructured optical fibres (EC‐MOFs) is presented and numerically characterised. The exposed section (analyte channel) of the EC‐MOF is coated with a SPR supporting thin film of gold. The asymmetrically coated fibre can support two separate resonance peaks, with orthogonal polarisations (x‐ and y‐polarised peaks). Although the sensitivity of both the polarised peaks is very similar, the narrower linewidth of the y‐polarised peak provides a much enhanced signal‐to‐noise ratio. The SPR sensing performance for a large refractive index (RI) range from 1.33 to 1.42 is evaluated. The sensor has higher sensitivity for detecting the high analyte RI. The feasibility of using EC‐MOFs to develop a fast‐response, real‐time and distributed SPR sensor is determined. [ABSTRACT FROM AUTHOR]