Dopexamine can attenuate the inflammatory response and protect against organ injury in the absence of significant effects on hemodynamics or regional microvascular flow

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Modeling of Diffusion and Incorporation of Interstitial Oxygen Ions at the TiN/SiO2 Interface

Silica-based resistive random access memory devices have become an active research area due to complementary metal-oxide-semiconductor compatibility and recent dramatic increases in their performance and endurance. In spite of both experimental and theoretical insights gained into the electroforming process, many atomistic aspects of the set and reset operation of these devices are still poorly understood. Recently a mechanism of electroforming process based on the formation of neutral oxygen vacancies (VO0) and interstitial O ions (Oi2-) facilitated by electron injection into the oxide has been proposed. In this work, we extend the description of the bulk (Oi2-) migration to the interface of amorphous SiO2 with the polycrystaline TiN electrode, using density functional theory simulations. The results demonstrate a strong kinetic and thermodynamic drive for the movement of Oi2- to the interface, with dramatically reduced incorporation energies and migration barriers close to the interface. The arrival of Oi2- at the interface is accompanied by preferential oxidation of undercoordinated Ti sites at the interface, forming a Ti-O layer. We investigate how O ions incorporate into a perfect and defective ∑5(012)[100] grain boundary (GB) in TiN oriented perpendicular to the interface. Our simulations demonstrate the preferential incorporation of Oi at defects within the TiN GB and their fast diffusion along a passivated grain boundary. They explain how, as a result of electroforming, the system undergoes very significant structural changes with the oxide being significantly reduced, interface being oxidized, and part of the oxygen leaving the system

Penetrance and expressivity of mitochondrial variants in a large clinically unselected population

\ua9 The Author(s) 2023. Published by Oxford University Press. Whole genome sequencing (WGS) from large clinically unselected cohorts provides a unique opportunity to assess the penetrance and expressivity of rare and/or known pathogenic mitochondrial variants in population. Using WGS from 179 862 clinically unselected individuals from the UK Biobank, we performed extensive single and rare variant aggregation association analyses of 15 881 mtDNA variants and 73 known pathogenic variants with 15 mitochondrial disease-relevant phenotypes. We identified 12 homoplasmic and one heteroplasmic variant (m.3243A>G) with genome-wide significant associations in our clinically unselected cohort. Heteroplasmic m.3243A>G (MAF = 0.0002, a known pathogenic variant) was associated with diabetes, deafness and heart failure and 12 homoplasmic variants increased aspartate aminotransferase levels including three low-frequency variants (MAF ~0.002 and beta~0.3 SD). Most pathogenic mitochondrial disease variants (n = 66/74) were rare in the population (<1:9000). Aggregated or single variant analysis of pathogenic variants showed low penetrance in unselected settings for the relevant phenotypes, except m.3243A>G. Multi-system disease risk and penetrance of diabetes, deafness and heart failure greatly increased with m.3243A>G level ≥ 10%. The odds ratio of these traits increased from 5.61, 12.3 and 10.1 to 25.1, 55.0 and 39.5, respectively. Diabetes risk with m.3243A>G was further influenced by type 2 diabetes genetic risk. Our study of mitochondrial variation in a large-unselected population identified novel associations and demonstrated that pathogenic mitochondrial variants have lower penetrance in clinically unselected settings. m.3243A>G was an exception at higher heteroplasmy showing a significant impact on health making it a good candidate for incidental reporting

SavvyCNV: Genome-wide CNV calling from off-target reads

This is the uncorrected proof. The final version is available on open access from Public Library of Science via the DOI in this recordData Availability: The SavvyCNV tool and the code used to run the benchmarking comparisons are freely available on github. The tool is available at https://github.com/rdemolgen/SavvySuite. The code used to run the benchmarking comparisons is available at: https://github.com/exeter-matthew-wakeling/SavvyCNV_benchmarking. Our study uses the ICR96 data set for benchmarking, which is publicly available and can be accessed through the European-Genome phenome Archive (EGA) under the accession number EGAS00001002428. The dataset of 2591 samples referred to the molecular genetics department at the Royal Devon and Exeter Hospital for genetic testing cannot be shared due to patient confidentiality issues, as the genotype data could be used to identify individuals and so cannot be made openly available. Requests for access to the anonymised data by researchers will be considered following an application to the Genetic Beta Cell Research Bank (https://www.diabetesgenes.org/current-research/genetic-beta-cell-research-bank/) with proposals reviewed by the Genetic Data Access Committee.Identifying copy number variants (CNVs) can provide diagnoses to patients and provide important biological insights into human health and disease. Current exome and targeted sequencing approaches cannot detect clinically and biologically-relevant CNVs outside their target area. We present SavvyCNV, a tool which uses off-target read data from exome and targeted sequencing data to call germline CNVs genome-wide. Up to 70% of sequencing reads from exome and targeted sequencing fall outside the targeted regions. We have developed a new tool, SavvyCNV, to exploit this 'free data' to call CNVs across the genome. We benchmarked SavvyCNV against five state-of-the-art CNV callers using truth sets generated from genome sequencing data and Multiplex Ligation-dependent Probe Amplification assays. SavvyCNV called CNVs with high precision and recall, outperforming the five other tools at calling CNVs genome-wide, using off-target or on-target reads from targeted panel and exome sequencing. We then applied SavvyCNV to clinical samples sequenced using a targeted panel and were able to call previously undetected clinically-relevant CNVs, highlighting the utility of this tool within the diagnostic setting. SavvyCNV outperforms existing tools for calling CNVs from off-target reads. It can call CNVs genome-wide from targeted panel and exome data, increasing the utility and diagnostic yield of these tests. SavvyCNV is freely available at https://github.com/rdemolgen/SavvySuite.Medical Research Council (MRC)Research EnglandDiabetes U

Properties of Light Flavour Baryons in Hypercentral quark model

The light flavour baryons are studied within the quark model using the hyper central description of the three-body system. The confinement potential is assumed as hypercentral coulomb plus power potential ($hCPP_\nu$) with power index $\nu$. The masses and magnetic moments of light flavour baryons are computed for different power index, $\nu$ starting from 0.5 to 1.5. The predicted masses and magnetic moments are found to attain a saturated value with respect to variation in $\nu$ beyond the power index $\nu>$ 1.0. Further we computed transition magnetic moments and radiative decay width of light flavour baryons. The results are in good agreement with known experimental as well as other theoretical models.Comment: Accepted in Pramana J. of Physic

Evaluation of Evidence for Pathogenicity Demonstrates that BLK, KLF11 and PAX4 Should not be Included in Diagnostic Testing for MODY

This is the author accepted manuscript. The final version is available from the American Diabetes Association via the DOI in this recordData and Resource Availability: UK Biobank data is accessible via application: https://www.ukbiobank.ac.uk/enable-yourresearch. GnomAD data is publically available: https://gnomad.broadinstitute.org/. The MODY cohort data is not publicly available due the limitations of the current ethics and to protect patient confidentiality but is available from the corresponding authors on reasonable request. No applicable resources were generated or analyzed during the current study.Maturity Onset Diabetes of the Young (MODY) is an autosomal dominant form of monogenic diabetes, reported to be caused by variants in 16 genes. Concern has been raised about whether variants in BLK (MODY11), KLF11 (MODY7) and PAX4 (MODY9) cause MODY. We examined variant-level genetic evidence (co-segregation with diabetes and frequency in population) for published putative pathogenic variants in these genes and used burden testing to test gene-level evidence in a MODY cohort (n=1227) compared to population control (UK Biobank, n=185,898). For comparison we analysed well-established causes of MODY, HNF1A and HNF4A. The published variants in BLK, KLF11 and PAX4 showed poor co-segregation with diabetes (combined LOD scores ≤1.2), compared to HNF1A and HNF4A (LOD scores >9), and are all too common to cause MODY (minor allele frequency >4.95x10-5). Ultra-rare missense and protein-truncating variants (PTVs) were not enriched in a MODY cohort compared to the UK Biobank (PTVs P>0.05, missense P>0.1 for all three genes) while HNF1A and HNF4A were enriched (P<10-6). Sensitivity analyses using different population cohorts supported our results. Variant and gene-level genetic evidence does not support BLK, KLF11 or PAX4 as causes of MODY. They should not be included in MODY diagnostic genetic testing.Medical Research Council (MRC)Diabetes UKResearch EnglandWellcome Trus