Permutation-based Pathway Testing using the Super Learner Algorithm

Many diseases and other important phenotypic outcomes are the result of a combination of factors. For example, expression levels of genes have been used as input to various statistical methods for predicting phenotypic outcomes. One particular popular variety is the so-called gene set enrichment analysis (GSEA). This paper discusses an augmentation to an existing strategy to estimate the significance of an associations between a disease outcome and a predetermined combination of biological factors, based on a specific data adaptive regression method (the Super Learner, van der Laan et al., 2007). The procedure uses an aggressive search procedure, potentially resulting in final models that imply associations that would not be discovered using non data-adaptive procedures (e.g., multiple linear regression). A test statistic derived from the fit of the Super Learner model to the original data is compared to the permutation distribution of the same statistic, the latter being generated by permuting the outcome labels with respect to the covariate vectors. This comparison is the basis for rejection criteria for the null hypothesis of no association between a set of biological factors (e.g., gene expression levels) and binary phenotypic outcomes. We include simulations that compare the statistical power of the test derived from the Super Learner method with that of other methods for two different data generating distributions

Scaling down the great Egypt pyramids to enhance CO2 splitting in a micro DBD reactor

The CO2 splitting reaction has been investigated in a plate-to-plate micro DBD reactor with a high voltage electrode having pyramid charge injection points. The presence of sharp points (pyramids) creates zones with enhanced electric field around them. The minimum discharge voltage in the pyramid micro DBD reactor reduced from 6.5 to 5.2 kV (peak-to-peak). At the same time, the CO2 conversion increased 1.5 times as compared to that in the reactor with a flat electrode. Lowering the discharge gap from 0.50 to 0.25 mm resulted in more intense microdischarges, further increasing CO2 conversion by 1.3 times. At the same time, the energy efficiency increased further by 1.3 times. There exists an optimum residence time of 0.5 ms as a result of an interplay between plasma contact time and flow non-uniformity. The highest energy efficiency of 20% was obtained at a 3 W power, achieving a CO2 conversion of 16%

Effect of temperature on CO2 splitting rate in a DBD microreactor

A novel plate-to-plate dielectric barrier discharge microreactor (micro DBD) has been demonstrated in CO2 splitting. In this design, the ground electrode has a cooling microchannel to maintain the electrode temperature in the 263-298 K range during plasma operation. A small gap size between the electrodes of 0.50 mm allowed efficient heat transfer from the surrounding plasma to the ground electrode surface to compensate for heat released in the reaction zone and maintain a constant temperature. The effect of temperature on CO2 conversion and energy efficiency was studied at a voltage of 6-9 kV, a frequency of 60 kHz and a constant CO2 flow rate of 20 ml min-1. The CO2 decomposition rate first increased and then decreased as the electrode temperature decreased from 298 to 263 K with a maximum rate observed at 273 K. Operation at lower temperatures enhanced the vibrational dissociation of CO2 molecule as opposed to electronic excitation which is the main mechanism at room temperature in conventional DBD reactors, however it also reduced the rate of elementary reaction steps. The counterplay between these two effects leads to a maximum in the reaction rate. The power consumption monotonously increased as the temperature decreased. The effective capacitance of the reactor increased by 1.5 times at 263 K as compared to that at 298 K changing the electric field distribution inside the plasma zone

A Multifunctional, Charge-Neutral, Chiral Octahedral M12 L12 Cage.

peer reviewedA chiral, octahedral M12 L12 cage, which is charge neutral and contains an internal void of about 2000 Å3 , is reported. The cage was synthesised as an enantiopure complex by virtue of amino-acid-based dicarboxylate ligands, which assemble around copper paddlewheels at the vertices of the octahedron. The cage persists in solution with retention of the fluorescence properties of the parent acid. The solid-state structure contains large pores both within and between the cages, and displays permanent porosity for the sorption of gases with retention of crystallinity. Initial tests show some enantioselectivity of the cage towards guests in solution

Agnostic Pathway/Gene Set Analysis of Genome-Wide Association Data Identifies Associations for Pancreatic Cancer

Background Genome-wide association studies (GWAS) identify associations of individual single-nucleotide polymorphisms (SNPs) with cancer risk but usually only explain a fraction of the inherited variability. Pathway analysis of genetic variants is a powerful tool to identify networks of susceptibility genes. Methods We conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product method to identify gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDAC) in 9040 cases and 12 496 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes contributing to the top associated pathways and gene sets. All statistical tests were two-sided. Results We identified 14 pathways and gene sets associated with PDAC at a false discovery rate of less than 0.05. After Bonferroni correction (P Conclusion Our agnostic pathway and gene set analysis integrated with functional annotation and eQTL analysis provides insight into genes and pathways that may be biologically relevant for risk of PDAC, including those not previously identified.Peer reviewe

Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer.

In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Here, we find significant evidence of a novel association at rs78417682 (7p12/TNS3, P = 4.35 × 10-8). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PANDoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 (NOC2L, P = 8.36 × 10-14), rs2941471 at 8q21.11 (HNF4G, P = 6.60 × 10-10), rs4795218 at 17q12 (HNF1B, P = 1.32 × 10-8), and rs1517037 at 18q21.32 (GRP, P = 3.28 × 10-8). rs78417682 is not statistically significantly associated with pancreatic cancer in PANDoRA. Expression quantitative trait locus analysis in three independent pancreatic data sets provides molecular support of NOC2L as a pancreatic cancer susceptibility gene

Integrated genomic characterization of pancreatic ductal adenocarcinoma

We performed integrated genomic, transcriptomic, and proteomic profiling of 150 pancreatic ductal adenocarcinoma (PDAC) specimens, including samples with characteristic low neoplastic cellularity. Deep whole-exome sequencing revealed recurrent somatic mutations in KRAS, TP53, CDKN2A, SMAD4, RNF43, ARID1A, TGFβR2, GNAS, RREB1, and PBRM1. KRAS wild-type tumors harbored alterations in other oncogenic drivers, including GNAS, BRAF, CTNNB1, and additional RAS pathway genes. A subset of tumors harbored multiple KRAS mutations, with some showing evidence of biallelic mutations. Protein profiling identified a favorable prognosis subset with low epithelial-mesenchymal transition and high MTOR pathway scores. Associations of non-coding RNAs with tumor-specific mRNA subtypes were also identified. Our integrated multi-platform analysis reveals a complex molecular landscape of PDAC and provides a roadmap for precision medicine

Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome

To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events42Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases

Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome

To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events >2 Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases

Aminopropyl-Functionalized Silica CO2 Adsorbents via Sonochemical Methods

Aminopropyl-functionalized hexagonal mesoporous silica (HMS) products, as are of interest for CO2 capture applications, were separately prepared by mixing aminopropyltrimethoxysilane (APTS) and HMS in toluene via a conventional stirred reactor and via sonication assisted methods, to investigate the potential of sonication to facilitate the preparation of products with higher tether loadings and correspondingly higher CO2 sorption capacities. Sonication was expected to improve both the dispersion of the substrate in the solvent and the diffusion of the silane throughout the mesoporous substrate. Structural properties of the products were determined by X-ray diffraction, N2 adsorption/desorption (77 K), helium pycnometry, and elemental analysis, and CO2 adsorption/desorption properties were determined via thermogravimetric and differential thermal analysis. The tether loadings of the sonication products (up to 1.8 tethers·nm−2) were found to increase with sonication time and in each case were greater than the corresponding product prepared by the conventional approach. It was also found that the concentration of the reagent mixture influenced the extent of functionalization, that the crude products cured effectively under N2 flow as under vacuum, and that rinsing the crude products prior to curing was not essential. Sonication products with higher tether loadings were found to exhibit higher CO2 sorption capacities as expected