45 research outputs found

    Atomic magnetometers and their application in industry

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    In modern detection techniques, high-precision magnetic field detection plays a crucial role. Atomic magnetometers stand out among other devices due to their high sensitivity, large detection range, low power consumption, high sampling rate, continuous gradient measurements, and good confidentiality. Atomic magnetometers have become a hot topic in the field of magnetometry due to their ability to measure not only the total strength of the Earth’s magnetic field, but also its gradients, both slow- and high-velocity transient magnetic fields, both strong and weak. In recent years, researchers have shifted their focus from improving the performance of atomic magnetometers to utilizing their exceptional capabilities for practical applications. The objective of this study is to explore the measurement principle and detection method of atomic magnetometers, and it also examines the technological means and research progress of atomic magnetometers in various industrial fields, including magnetic imaging, material examination, underwater magnetic target detection, and magnetic communication. Additionally, this study discusses the potential applications and future development trends of atomic magnetometers

    Functional Architectures of Local and Distal Regulation of Gene Expression in Multiple Human Tissues

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    Genetic variants that modulate gene expression levels play an important role in the etiology of human diseases and complex traits. Although large-scale eQTL mapping studies routinely identify many local eQTLs, the molecular mechanisms by which genetic variants regulate expression remain unclear, particularly for distal eQTLs, which these studies are not well powered to detect. Here, we leveraged all variants (not just those that pass stringent significance thresholds) to analyze the functional architecture of local and distal regulation of gene expression in 15 human tissues by employing an extension of stratified LD-score regression that produces robust results in simulations. The top enriched functional categories in local regulation of peripheral-blood gene expression included coding regions (11.41×), conserved regions (4.67×), and four histone marks (p < 5 × 10 -5 for all enrichments); local enrichments were similar across the 15 tissues. We also observed substantial enrichments for distal regulation of peripheral-blood gene expression: coding regions (4.47×), conserved regions (4.51×), and two histone marks (p < 3 × 10 -7 for all enrichments). Analyses of the genetic correlation of gene expression across tissues confirmed that local regulation of gene expression is largely shared across tissues but that distal regulation is highly tissue specific. Our results elucidate the functional components of the genetic architecture of local and distal regulation of gene expression

    Detecting signatures of positive selection associated with musical aptitude in the human genome

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    Abilities related to musical aptitude appear to have a long history in human evolution. To elucidate the molecular and evolutionary background of musical aptitude, we compared genome-wide genotyping data (641 K SNPs) of 148 Finnish individuals characterized for musical aptitude. We assigned signatures of positive selection in a case-control setting using three selection methods: haploPS, XP-EHH and F-ST. Gene ontology classification revealed that the positive selection regions contained genes affecting inner-ear development. Additionally, literature survey has shown that several of the identified genes were known to be involved in auditory perception (e.g. GPR98, USH2A), cognition and memory (e.g. GRIN2B, IL1A, IL1B, RAPGEF5), reward mechanisms (RGS9), and song perception and production of songbirds (e.g. FOXP1, RGS9, GPR98, GRIN2B). Interestingly, genes related to inner-ear development and cognition were also detected in a previous genome-wide association study of musical aptitude. However, the candidate genes detected in this study were not reported earlier in studies of musical abilities. Identification of genes related to language development (FOXP1 and VLDLR) support the popular hypothesis that music and language share a common genetic and evolutionary background. The findings are consistent with the evolutionary conservation of genes related to auditory processes in other species and provide first empirical evidence for signatures of positive selection for abilities that contribute to musical aptitude.Peer reviewe

    Paxbp1 is indispensable for the survival of CD4 and CD8 double-positive thymocytes

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    The lifespan of double-positive (DP) thymocytes is critical for intrathymic development and shaping the peripheral T cell repertoire. However, the molecular mechanisms that control DP thymocyte survival remain poorly understood. Paxbp1 is a conserved nuclear protein that has been reported to play important roles in cell growth and development. Its high expression in T cells suggests a possible role in T cell development. Here, we observed that deletion of Paxbp1 resulted in thymic atrophy in mice lacking Paxbp1 in the early stages of T cell development. Conditional loss of Paxbp1 resulted in fewer CD4+CD8+ DP T cells, CD4 and CD8 single positive (SP) T cells in the thymus, and fewer T cells in the periphery. Meanwhile, Paxbp1 deficiency had limited effects on the CD4-CD8- double negative (DN) or immature single-positive (ISP) cell populations. Instead, we observed a significant increase in the susceptibility of Paxbp1-deficient DP thymocytes to apoptosis. Consistent with this, RNA-Seq analysis revealed a significant enrichment of the apoptotic pathway within differentially expressed genes in Paxbp1-deficient DP cells compared to control DP cells. Together, our results suggest a new function for Paxbp1, which is an important mediator of DP thymocyte survival and critical for proper thymic development

    A statistical method for region-based meta-analysis of genome-wide association studies in genetically diverse populations

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    Genome-wide association studies (GWAS) have become the preferred experimental design in exploring the genetic etiology of complex human traits and diseases. Standard SNP-based meta-analytic approaches have been utilized to integrate the results from multiple experiments. This fundamentally assumes that the patterns of linkage disequilibrium (LD) between the underlying causal variants and the directly genotyped SNPs are similar across the populations for the same SNPs to emerge with surrogate evidence of disease association. We introduce a novel strategy for assessing regional evidence of phenotypic association that explicitly incorporates the extent of LD in the region. This provides a natural framework for combining evidence from multi-ethnic studies of both dichotomous and quantitative traits that (i) accommodates different patterns of LD, (ii) integrates different genotyping platforms and (iii) allows for the presence of allelic heterogeneity between the populations. Our method can also be generalized to perform gene-based or pathway-based analyses. Applying this method on real GWAS data in type 2 diabetes (T2D) boosted the association evidence in regions well-established for T2D etiology in three diverse South-East Asian populations, as well as identified two novel gene regions and a biologically convincing pathway that are subsequently validated with data from the Wellcome Trust Case Control Consortium

    Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees

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    Significance Contributions of rare variants to common and complex traits such as type 2 diabetes (T2D) are difficult to measure. This paper describes our results from deep whole-genome analysis of large Mexican-American pedigrees to understand the role of rare-sequence variations in T2D and related traits through enriched allele counts in pedigrees. Our study design was well-powered to detect association of rare variants if rare variants with large effects collectively accounted for large portions of risk variability, but our results did not identify such variants in this sample. We further quantified the contributions of common and rare variants in gene expression profiles and concluded that rare expression quantitative trait loci explain a substantive, but minor, portion of expression heritability.</jats:p

    A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

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    Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants
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