57 research outputs found

    Controllable tunability of a Chern number within the electronic-nuclear spin system in diamond

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    Chern numbers are gaining traction as they characterize topological phases in various physical systems. However, the resilience of the system topology to external perturbations makes it challenging to experimentally investigate transitions between different phases. In this study, we demonstrate the transitions of Chern number from 0 to 3, synthesized in an electronic-nuclear spin system associated with the nitrogen-vacancy (NV) centre in diamond. The Chern number is characterized by the number of degeneracies enclosed in a control Hamiltonian parameter sphere. The topological transitions between different phases are depicted by varying the radius and offset of the sphere. We show that the measured topological phase diagram is not only consistent with the numerical calculations but can also be mapped onto an interacting three-qubit system. The NV system may also allow access to even higher Chern numbers, which can be applied to exploring exotic topology or topological quantum information

    In pursuit of impact: how psychological contract research can make the work-world a better place

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    This paper is the result of the collective work undertaken by a group of Psychological Contract (PC) and Sustainability scholars from around the world, following the 2023 Bi-Annual PC Small Group Conference (Kedge Business School, Bordeaux, France). As part of the conference, scholars engaged in a workshop designed to generate expert guidance on how to aid the PC field to be better aligned with the needs of practice, and thus, impact the creation and maintenance of high-quality and sustainable exchange processes at work. In accordance with accreditation bodies for higher education, research impact is not limited to academic papers alone but also includes practitioners, policymakers, and students in its scope. This paper therefore incorporates elements from an impact measurement tool for higher education in management so as to explore how PC scholars can bolster the beneficial influence of PC knowledge on employment relationships through different stakeholders and means. Accordingly, our proposals for the pursuit of PC impact are organized in three parts: (1) research, (2) practice and society, and (3) students. Further, this paper contributes to the emerging debate on sustainable PCs by developing a construct definition and integrating PCs with an ‘ethics of care’ perspective

    In Pursuit of Impact: How Psychological Contract Research Can Make the Work-World a Better Place

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    This paper is the result of the collective work undertaken by a group of Psychological Contract (PC) and Sustainability scholars from around the world, following the 2023 Bi-Annual PC Small Group Conference (Kedge Business School, Bordeaux, France). As part of the conference, scholars engaged in a workshop designed to generate expert guidance on how to aid the PC field to be better aligned with the needs of practice, and thus, impact the creation and maintenance of high-quality and sustainable exchange processes at work. In accordance with accreditation bodies for higher education, research impact is not limited to academic papers alone but also includes practitioners, policymakers, and students in its scope. This paper therefore incorporates elements from an impact measurement tool for higher education in management so as to explore how PC scholars can bolster the beneficial influence of PC knowledge on employment relationships through different stakeholders and means. Accordingly, our proposals for the pursuit of PC impact are organized in three parts: (1) research, (2) practice and society, and (3) students. Further, this paper contributes to the emerging debate on sustainable PCs by developing a construct definition and integrating PCs with an ‘ethics of care’ perspective

    Multiple Pathway-Based Genetic Variations Associated with Tobacco Related Multiple Primary Neoplasms

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    BACKGROUND: In order to elucidate a combination of genetic alterations that drive tobacco carcinogenesis we have explored a unique model system and analytical method for an unbiased qualitative and quantitative assessment of gene-gene and gene-environment interactions. The objective of this case control study was to assess genetic predisposition in a biologically enriched clinical model system of tobacco related cancers (TRC), occurring as Multiple Primary Neoplasms (MPN). METHODS: Genotyping of 21 candidate Single Nucleotide Polymorphisms (SNP) from major metabolic pathways was performed in a cohort of 151 MPN cases and 210 cancer-free controls. Statistical analysis using logistic regression and Multifactor Dimensionality Reduction (MDR) analysis was performed for studying higher order interactions among various SNPs and tobacco habit. RESULTS: Increased risk association was observed for patients with at least one TRC in the upper aero digestive tract (UADT) for variations in SULT1A1 ArgÂČÂčÂłHis, mEH TyrÂčÂčÂłHis, hOGG1 SerÂłÂČ⁶Cys, XRCC1 ArgÂČ⁞⁰His and BRCA2 Asn³⁷ÂČHis. Gene-environment interactions were assessed using MDR analysis. The overall best model by MDR was tobacco habit/p53(Arg/Arg)/XRCC1(ArgÂłâčâčHis)/mEH(TyrÂčÂčÂłHis) that had highest Cross Validation Consistency (8.3) and test accuracy (0.69). This model also showed significant association using logistic regression analysis. CONCLUSION: This is the first Indian study on a multipathway based approach to study genetic susceptibility to cancer in tobacco associated MPN. This approach could assist in planning additional studies for comprehensive understanding of tobacco carcinogenesis

    Exome-wide association study to identify rare variants influencing COVID-19 outcomes : Results from the Host Genetics Initiative

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    Publisher Copyright: Copyright: © 2022 Butler-Laporte et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75–10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.Peer reviewe

    Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative

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    Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

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    The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

    SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

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    Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

    A first update on mapping the human genetic architecture of COVID-19

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