Magnetic and electronic properties of bimagnetic materials comprising cobalt particles within hollow silica decorated with magnetite nanoparticles

Bimagnetic materials were fabricated by decorating the external surface of rattle-type hollow silica microspheres (which themselves contain metallic cobalt nanoparticles) with magnetite nanoparticles; thus, each magnetic substance was spatially isolated by the silica shell. The amount of magnetite decoration on the co-occluded hollow silica was varied from 1 to 17 mass %. Magnetic and electronic properties of the resulting bimagnetic materials were characterized by superconducting quantum interference device measurements and X-ray absorption spectroscopy, respectively. The ferrous iron in the bimagnetic sample was slightly more oxidized than in the magnetite reference, probably from some charge-transfer because of the SiO2 surface contact, although the overall oxidation state of the samples is very similar to that of magnetite. The temperature dependence of the sample magnetization recorded with Zero Field Cooling and Field Cooling resulted in blocking temperatures for the bimagnetic materials that were close to that of magnetite nanoparticles (176K) and were lower than that for the bare Co-occluded hollow silica (which was above room temperature). Values of coercive force and exchange bias at 300K became quite small after decoration with only minimal amounts of magnetite nanoparticles (1-3 mass %) and were lower than those of magnetite. This is the first example of enhancing superparamagnetism by spatial separation of both Co and magnetite magnetic nanoparticles using a thin wall of diamagnetic silica.ArticleJOURNAL OF APPLIED PHYSICS. 114(12):124304 (2013)journal articl

Magnetic and electronic properties of bimagnetic materials comprising cobalt particles within hollow silica decorated with magnetite nanoparticles

Bimagnetic materials were fabricated by decorating the external surface of rattle-type hollow silica microspheres (which themselves contain metallic cobalt nanoparticles) with magnetite nanoparticles; thus, each magnetic substance was spatially isolated by the silica shell. The amount of magnetite decoration on the co-occluded hollow silica was varied from 1 to 17 mass %. Magnetic and electronic properties of the resulting bimagnetic materials were characterized by superconducting quantum interference device measurements and X-ray absorption spectroscopy, respectively. The ferrous iron in the bimagnetic sample was slightly more oxidized than in the magnetite reference, probably from some charge-transfer because of the SiO2 surface contact, although the overall oxidation state of the samples is very similar to that of magnetite. The temperature dependence of the sample magnetization recorded with Zero Field Cooling and Field Cooling resulted in blocking temperatures for the bimagnetic materials that were close to that of magnetite nanoparticles (176K) and were lower than that for the bare Co-occluded hollow silica (which was above room temperature). Values of coercive force and exchange bias at 300K became quite small after decoration with only minimal amounts of magnetite nanoparticles (1-3 mass %) and were lower than those of magnetite. This is the first example of enhancing superparamagnetism by spatial separation of both Co and magnetite magnetic nanoparticles using a thin wall of diamagnetic silica.ArticleJOURNAL OF APPLIED PHYSICS. 114(12):124304 (2013)journal articl

Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P&lt;5×10 - 8 ) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care. </p

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

HLA-B*15:01-positive severe COVID-19 patients lack CD8 + T cell pools with highly expanded public clonotypes

Understanding host factors driving asymptomatic versus severe disease outcomes is of key importance if we are to control emerging and re-emerging viral infections. HLA-B*15:01 has been associated with asymptomatic SARS-CoV-2 infection in nonhospitalized individuals of European ancestry, with protective immunity attributed to preexisting cross-reactive CD8+ T-cells directed against HLA-B*15:01-restricted Spike-derived S919-927 peptide (B15/S919+CD8+ T-cells). However, fundamental questions remained on the abundance and clonotypic nature of CD8+ T-cell responses in HLA-B*15:01-positive patients who succumbed to life-threatening COVID-19. Here, we analyzed B15/S919+CD8+ T-cell responses in COVID-19 patients from independent HLA-typed COVID-19 patient cohorts across three continents, Australia, Asia and Europe. We assessed B15/S919+CD8+ T-cells in COVID-19 patients across disease outcomes ranging from asymptomatic to hospitalized critical illness. We found that severe/critical COVID-19 patients mounted B15/S919+CD8+ T-cell responses lacking a highly expanded key public B15/S919+CD8+ T-cell receptor (TCR; TRAV9-2/TRBV7-2) which recurred across multiple individuals in COVID-19 patients with a mild disease. Instead, B15/S919+CD8+ T-cell responses in life-threatening disease had a prevalence of an alternate TCR clonotypic motif (TRAV38-2/DV8/TRBV20-1), potentially contributing, at least in part, to why B15/S919+CD8+ T-cells in severe COVID-19 patients were less protective. Interestingly, the frequency, memory phenotype, and activation profiles of circulating B15/S919+CD8+ T-cells did not differ across disease severity. Moreover, B15/S919+CD8+ T-cells were better maintained into convalescence compared to other SARS-CoV-2-specificities. Our study thus provides evidence on the differential nature of the TCR clonal repertoire in 22.37% of HLA-B*15:01-positive COVID-19 patients who developed severe or critical disease in our cohorts, comparing to HLA-B*15:01-expressing individuals with mild COVID-19