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- Zhang, Mingfeng, et al.
(författare)
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Three new pancreatic cancer susceptibility signals identified on chromosomes 1q32.1, 5p15.33 and 8q24.21
- 2016
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Ingår i: Oncotarget. - : Impact Journals, LLC. - 1949-2553. ; 7:41, s. 66328-66343
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have identified common pancreatic cancer susceptibility variants at 13 chromosomal loci in individuals of European descent. To identify new susceptibility variants, we performed imputation based on 1000 Genomes (1000G) Project data and association analysis using 5,107 case and 8,845 control subjects from 27 cohort and case-control studies that participated in the PanScan I-III GWAS. This analysis, in combination with a two-staged replication in an additional 6,076 case and 7,555 control subjects from the PANcreatic Disease ReseArch (PANDoRA) and Pancreatic Cancer Case-Control (PanC4) Consortia uncovered 3 new pancreatic cancer risk signals marked by single nucleotide polymorphisms (SNPs) rs2816938 at chromosome 1q32.1 (per allele odds ratio (OR) = 1.20, P = 4.88x10(-15)), rs10094872 at 8q24.21 (OR = 1.15, P = 3.22x10(-9)) and rs35226131 at 5p15.33 (OR = 0.71, P = 1.70x10(-8)). These SNPs represent independent risk variants at previously identified pancreatic cancer risk loci on chr1q32.1 (NR5A2), chr8q24.21 (MYC) and chr5p15.33 (CLPTM1L-TERT) as per analyses conditioned on previously reported susceptibility variants. We assessed expression of candidate genes at the three risk loci in histologically normal (n = 10) and tumor (n = 8) derived pancreatic tissue samples and observed a marked reduction of NR5A2 expression (chr1q32.1) in the tumors (fold change -7.6, P = 5.7x10(-8)). This finding was validated in a second set of paired (n = 20) histologically normal and tumor derived pancreatic tissue samples (average fold change for three NR5A2 isoforms -31.3 to -95.7, P = 7.5x10(-4)-2.0x10(-3)). Our study has identified new susceptibility variants independently conferring pancreatic cancer risk that merit functional follow-up to identify target genes and explain the underlying biology.
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- Berg, Frenk van den, et al.
(författare)
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How the EU project “Online Microstructure Analytics” advances inline sensing of microstructure during steel manufacturing
- 2023
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Ingår i: Research and Review Journal of Nondestructive Testing (ReJNDT). - Lisabon : NDT.net GmbH & Co. KG. - 2941-4989. ; 1:1
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Tidskriftsartikel (refereegranskat)abstract
- Weight savings in mobility and transport are mandatory in order to reduce CO2 emissions and energy consumption. The steel industry offers weight saving solutions by a growing portfolio of Advanced High Strength Steel (AHSS) products. AHSS owe their strength to their largely refined and complex microstructures, containing multiple metallurgical phases. Optimal control of the thermo-mechanical processing of AHSS requires inline sensors for real-time monitoring of evolution and consistency of microstructure and material properties.
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- Berg, Frenk van den, et al.
(författare)
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Results of the European collaborative project "Product Uniformity Control" to improve the inline sensing of mechanical properties and microstructure of automotive steels
- 2018
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Ingår i: e-Journal of Nondestructive Testing (eJNDT). - 1435-4934. ; 23:8
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Tidskriftsartikel (refereegranskat)abstract
- A European consortium consisting of four major steel manufacturers and ten academic technology institutes has conducted a research and development project, called “Product Uniformity Control“ (PUC) in the period 2013 to 2017. This project aimed to develop and improve non-destructive (inline) measurement techniques to characterise the (uniformity of the) microstructure of steel strip products. In this project, a multitude of strip steel samples from various stages of production have been collected from the four participating steel manufacturers. The samples have been characterised in various ways, namely on their (1) non-destructive measurement parameters using different techniques suited for inline evaluation, (2) fundamental ultrasonic and electromagnetic properties (wave speed, ultrasonic attenuation, magnetisation loops, coercive field), (3) tensile properties (stress-strain curves) and (4) microstructure (by optical micrographs and EBSD images). The correlations between these different characterisations will be addressed. Besides the experimental characterisation, a strong accent has been on modelling activities: during the project, fundamental models have been developed to describe, starting from 2D and 3D microstructures, the ultrasonic and magnetic properties, which are next used as input to sensor models that predict the output of the inline measurement systems. This contribution presents the recent results of experimental work, which underlines the importance of associated modelling studies for the interpretation of the measurement data for the benefit of inline characterisation of the mechanical properties complementary to traditional destructive tensile testing.
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- Coroaba, Adina, et al.
(författare)
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Probing the supramolecular features via π–π interaction of a di-iminopyrene-di-benzo-18-crown-6-ether compound : experimental and theoretical study
- 2020
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Ingår i: RSC Advances. - : Royal Society of Chemistry (RSC). - 2046-2069. ; 10:63, s. 38304-38315
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Tidskriftsartikel (refereegranskat)abstract
- A novel DPyDB-CN-18C6 compound was synthesised by linking a pyrene moiety to each phenyl group of dibenzo-18-crown-6-ether, the crown ether, through –HCN– bonds and characterized by FTIR, 1H-NMR, 13C-NMR, TGA, and DSC techniques. The quantitative 13C-NMR analysis revealed the presence of two position isomers. The electronic structure of the DPyDB-CN-18C6 molecule was characterized by UV-vis and fluorescence spectroscopies in four solvents with different polarities to observe particular behavior of isomers, as well as to demonstrate a possible non-bonding chemical association (such as ground- and excited-state associations, namely, to probe if there were forming dimers/excimers). The interpretation of the electronic structure was realized through QM calculations. The TD-CAM-B3LYP functional, at the 6-311+G(d,p) basis set, indicated the presence of predominant π → π* and mixed π → π* + n → π* transitions, in line with the UV-vis experimental data. Even though DPyDB-CN-18C6 computational studies revealed a π-extended conjugation effect with predominantly π → π* transitions, thorough fluorescence analysis was observed a weak emission, as an effect of PET and ACQ. In particular, the WAXD analysis of powder and thin films obtained from n-hexane, 1,2-dichloroethane, and ethanol indicated an amorphous organization, whereas from toluene a smectic ordering was obtained. These results were correlated with MD simulation, and it was observed that the molecular geometry of DPyDB-CN-18C6 molecule played a defining role in the pyrene stacking arrangement.
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- Klein, Alison P., et al.
(författare)
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Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer
- 2018
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Ingår i: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- 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 x 10(-8)). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PAN-DoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 (NOC2L, P = 8.36 x 10(-14)), rs2941471 at 8q21.11 (HNF4G, P = 6.60 x 10(-10)), rs4795218 at 17q12 (HNF1B, P = 1.32 x 10(-8)), and rs1517037 at 18q21.32 (GRP, P = 3.28 x 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.
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