The vibrational spectrum of FeO2+ isomers

Infrared photodissociation is used to record the vibrational spectrum of FeO2+(He)2–4 which shows three bands at 1035, 980, and 506 cm−1. Quantum chemical multi-reference configuration interaction calculations (MRCISD) of structures and harmonic frequencies show that these bands are due to two different isomers, an inserted dioxo complex with Fe in the +V oxidation state and a side-on superoxo complex with Fe in the +II oxidation state. These two are separated by a substantial barrier, 53 kJ/mol, whereas the third isomer, an end-on complex between Fe+ and an O2 molecule, is easily converted into the side-on complex. For all three isomers, states of different spin multiplicity have been considered. Our best energies are computed at the MRCISD+Q level, including corrections for complete active space and basis set extension, core-valence correlation, relativistic effects, and zero-point vibrational energy. The average coupled pair functional (ACPF) yields very similar energies. Density functional theory (DFT) differs significantly from our best estimates for this system, with the TPSS functional yielding the best results. The other functionals tested are BP86, PBE, B3LYP, TPSSh, and B2PLYP. Complete active space second order perturbation theory, (CASPT2) performs better than DFT, but less good than ACPF

The role of networks to overcome large-scale challenges in tomography: The non-clinical tomography users research network

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives

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

Three new pancreatic cancer susceptibility signals identified on chromosomes 1q32.1, 5p15.33 and 8q24.21.

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

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

Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer

We performed a multistage genome-wide association study including 7,683 individuals with pancreatic cancer and 14,397 controls of European descent. Four new loci reached genome-wide significance: rs6971499 at 7q32.3 (LINC-PINT, per-allele odds ratio (OR) = 0.79, 95% confidence interval (CI) 0.74-0.84, P = 3.0 x 10(-12)), rs7190458 at 16q23.1 (BCAR1/CTRB1/CTRB2, OR = 1.46, 95% CI 1.30-1.65, P = 1.1 x 10(-10)), rs9581943 at 13q12.2 (PDX1, OR = 1.15, 95% CI 1.10-1.20, P = 2.4 x 10(-9)) and rs16986825 at 22q12.1 (ZNRF3, OR = 1.18, 95% CI 1.12-1.25, P = 1.2 x 10(-8)). We identified an independent signal in exon 2 of TERT at the established region 5p15.33 (rs2736098, OR = 0.80, 95% CI 0.76-0.85, P = 9.8 x 10(-14)). We also identified a locus at 8q24.21 (rs1561927, P = 1.3 x 10(-7)) that approached genome-wide significance located 455 kb telomeric of PVT1. Our study identified multiple new susceptibility alleles for pancreatic cancer that are worthy of follow-up studies

The role of networks to overcome large-scale challenges in tomography : the non-clinical tomography users research network

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives

Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer

We performed a multistage genome-wide association study (GWAS) including 7,683 individuals with pancreatic cancer and 14,397 controls of European descent. Four new loci reached genome-wide significance: rs6971499 at 7q32.3 (LINC-PINT; per-allele odds ratio [OR] = 0.79; 95% confidence interval [CI] = 0.74–0.84; P = 3.0×10−12), rs7190458 at 16q23.1 (BCAR1/CTRB1/CTRB2; OR = 1.46; 95% CI = 1.30–1.65; P = 1.1×10−10), rs9581943 at 13q12.2 (PDX1; OR = 1.15; 95% CI = 1.10–1.20; P = 2.4×10−9), and rs16986825 at 22q12.1 (ZNRF3; OR = 1.18; 95% CI = 1.12–1.25; P = 1.2×10−8). An independent signal was identified in exon 2 of TERT at the established region 5p15.33 (rs2736098; OR = 0.80; 95% CI = 0.76–0.85; P = 9.8×10−14). We also identified a locus at 8q24.21 (rs1561927; P = 1.3×10−7) that approached genome-wide significance located 455 kb telomeric of PVT1. Our study has identified multiple new susceptibility alleles for pancreatic cancer worthy of follow-up studies

The vibrational spectrum of FeO2+ isomers

Infrared photodissociation is used to record the vibrational spectrum of FeO2+(He)2–4 which shows three bands at 1035, 980, and 506 cm−1. Quantum chemical multi-reference configuration interaction calculations (MRCISD) of structures and harmonic frequencies show that these bands are due to two different isomers, an inserted dioxo complex with Fe in the +V oxidation state and a side-on superoxo complex with Fe in the +II oxidation state. These two are separated by a substantial barrier, 53 kJ/mol, whereas the third isomer, an end-on complex between Fe+ and an O2 molecule, is easily converted into the side-on complex. For all three isomers, states of different spin multiplicity have been considered. Our best energies are computed at the MRCISD+Q level, including corrections for complete active space and basis set extension, core-valence correlation, relativistic effects, and zero-point vibrational energy. The average coupled pair functional (ACPF) yields very similar energies. Density functional theory (DFT) differs significantly from our best estimates for this system, with the TPSS functional yielding the best results. The other functionals tested are BP86, PBE, B3LYP, TPSSh, and B2PLYP. Complete active space second order perturbation theory, (CASPT2) performs better than DFT, but less good than ACPF