Effect of Cooling Rate after Solution Treatment on Subsequent Phase Separation Evolution in Super Duplex Stainless Steel 25Cr-7Ni (wt.%)

The effect of cooling rate after solution treatment on the initial structure of super duplex stainless steel 25Cr-7Ni (wt.%), and the effect of the initial structure on phase separation (PS) evolution during subsequent aging were investigated. The nanostructure in the bulk of the steel was studied using small-angle neutron scattering (SANS). Ex situ SANS experiments showed that the rate of PS differs during aging, due to the different initial structures imposed by the difference in cooling rate after solution treatment. In situ SANS experiments revealed that the PS is already pronounced after aging at 475 ◦C for 180 min and that a slower cooling rate after solution treatment will lead to more significant PS. Hence, PS depends on the plate thickness, imposing different cooling rates in the production of duplex stainless steels

Quantitative Nanostructure and Hardness Evolution in Duplex Stainless Steels: Under Real Low-Temperature Service Conditions

Duplex stainless steels are a group of widely used stainless steels, because of their attractive combination of strength and corrosion resistance. However, these steels embrittle because of a phase separation phenomenon in the ferrite phase when exposed to temperatures within the miscibility gap. This manuscript investigates the phase separation in two commercial stainless steels, the duplex stainless steel (DSS) 22Cr-5Ni (2205 or UNS S32205), and the super-duplex stainless steel (SDSS) 25Cr-7Ni (2507 or UNS S32750), and its subsequent effect on mechanical property evolution. Long-term isothermal aging heat treatments were carried out at industrially relevant temperatures between 250 °C and 350 °C for up to 48,000 hours, and quantitative measurements of the amplitude and wavelength of the phase separated nanostructure were obtained using Small-Angle Neutron Scattering (SANS). These quantifications were used as input parameters in hardness models to predict the hardness evolution. It is concluded that the quantitative information from SANS combined with these hardness models enables the prediction of hardness evolution in DSS at low temperatures, which in turn correlates with the embrittlement of the DSS

Small-angle neutron scattering study on phase separation in a super duplex stainless steel at 300 °C – Comparing hot-rolled and TIG welded material

The evolution of nanoscale phase separation in the ferrite phase of super duplex stainless steel 25Crsingle bond7Ni (wt%) (SDSS 2507) and two SDSS TIG (tungsten inert gas) weldments have been quantitatively investigated by small-angle neutron scattering (SANS). The results show that the phase separation is more pronounced in the SDSS weldments in comparison to the base metal SDSS 2507, especially after aging for 35,000 h at 300 °C. These results correlate with the higher ferrite micro-hardness in the aged TIG weldments than in the SDSS 2507. The enhanced phase separation is partly due to the higher contents of Cr and Ni in the ferrite of TIG weldments compared to SDSS 2507 base metal, revealed by energy-dispersive X-ray spectroscopy (EDS). Additionally, the residual strain measurements through focused ion beam and digital image correlation (FIB-DIC), indicate larger residual strains in the ferrite of weldments than in the base metal SDSS 2507. This is also believed to contribute to the enhanced phase separation

Novel subgroups of adult-onset diabetes and their association with outcomes : a data-driven cluster analysis of six variables

Background Diabetes is presently classified into two main forms, type 1 and type 2 diabetes, but type 2 diabetes in particular is highly heterogeneous. A refined classification could provide a powerful tool to individualise treatment regimens and identify individuals with increased risk of complications at diagnosis. Methods We did data-driven cluster analysis (k-means and hierarchical clustering) in patients with newly diagnosed diabetes (n=8980) from the Swedish All New Diabetics in Scania cohort. Clusters were based on six variables (glutamate decarboxylase antibodies, age at diagnosis, BMI, HbA(1c), and homoeostatic model assessment 2 estimates of beta-cell function and insulin resistance), and were related to prospective data from patient records on development of complications and prescription of medication. Replication was done in three independent cohorts: the Scania Diabetes Registry (n=1466), All New Diabetics in Uppsala (n=844), and Diabetes Registry Vaasa (n=3485). Cox regression and logistic regression were used to compare time to medication, time to reaching the treatment goal, and risk of diabetic complications and genetic associations. Findings We identified five replicable clusters of patients with diabetes, which had significantly different patient characteristics and risk of diabetic complications. In particular, individuals in cluster 3 (most resistant to insulin) had significantly higher risk of diabetic kidney disease than individuals in clusters 4 and 5, but had been prescribed similar diabetes treatment. Cluster 2 (insulin deficient) had the highest risk of retinopathy. In support of the clustering, genetic associations in the clusters differed from those seen in traditional type 2 diabetes. Interpretation We stratified patients into five subgroups with differing disease progression and risk of diabetic complications. This new substratification might eventually help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes.Peer reviewe

Current Issues in Migraine Genetics

Migraine often runs in families and is associated with both genetic and environmental factors. Clinical and genetic heterogeneity as well as the influence of environmental factors have hampered the identification of the gene responsible for migraine disorder. Family/twin studies suggest the presence of hereditary susceptibility. Several different types of mutations or association studies with genetic polymorphism in neurotransmitters, inflammatory cytokines, homocysteine metabolism, mitochondria, or other risk genes in cerebrovascular disorders have been reported. Recently, progress of molecular genetics in familial hemiplegic migraine has provided important insights, a channelopathy, and now extending to a growing list of membrane excitability disorders. Further identification of candidate genes for migraine and exploring the correlation between phenotype and genotype are expected in the future for the understanding of migraine pathophysiology

Corticosteroid tapering with benralizumab treatment for eosinophilic asthma: PONENTE Trial.

Benralizumab is an interleukin-5 receptor α-directed cytolytic monoclonal antibody approved in several countries for the add-on maintenance treatment of patients with severe eosinophilic asthma aged 12 years and older. In the 28-week Phase III ZONDA trial (ClinicalTrials.gov identifier: NCT02075255), benralizumab produced a median 75% reduction from baseline in oral corticosteroid (OCS) dosage (versus 25% for placebo) while maintaining asthma control for patients with OCS-dependent severe asthma. This manuscript presents the detailed protocol for the Phase IIIb PONENTE (ClinicalTrials.gov identifier: NCT03557307), a study that will build on the findings from ZONDA. As the largest steroid-sparing study undertaken in severe asthma, PONENTE has a faster steroid tapering schedule for prednisone dosages ≥7.5 mg·day-1 than previous studies, and it includes an evaluation of adrenal insufficiency and an algorithm to taper OCS dosage when prednisone dosage is ≤5 mg·day-1. It also has a longer maintenance phase to assess asthma control for up to 6 months after completion of OCS tapering. The two primary endpoints are whether patients achieve 100% reduction in daily OCS use and whether patients achieve 100% reduction in daily OCS or achieve OCS dosage ≤5 mg·day-1, if adrenal insufficiency prevented further reduction, both sustained over ≥4 weeks without worsening of asthma. Safety and change from baseline in health-related quality of life will also be assessed. PONENTE should provide valuable guidance for clinicians on tapering OCS dosage, including the management of adrenal insufficiency, following benralizumab initiation for the treatment of patients who are OCS-dependent with severe, uncontrolled eosinophilic asthma

The population history of northeastern Siberia since the Pleistocene.

Northeastern Siberia has been inhabited by humans for more than 40,000 years but its deep population history remains poorly understood. Here we investigate the late Pleistocene population history of northeastern Siberia through analyses of 34 newly recovered ancient genomes that date to between 31,000 and 600 years ago. We document complex population dynamics during this period, including at least three major migration events: an initial peopling by a previously unknown Palaeolithic population of 'Ancient North Siberians' who are distantly related to early West Eurasian hunter-gatherers; the arrival of East Asian-related peoples, which gave rise to 'Ancient Palaeo-Siberians' who are closely related to contemporary communities from far-northeastern Siberia (such as the Koryaks), as well as Native Americans; and a Holocene migration of other East Asian-related peoples, who we name 'Neo-Siberians', and from whom many contemporary Siberians are descended. Each of these population expansions largely replaced the earlier inhabitants, and ultimately generated the mosaic genetic make-up of contemporary peoples who inhabit a vast area across northern Eurasia and the Americas

Cerebral small vessel disease genomics and its implications across the lifespan

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.Peer reviewe

Evaluation of univariate surveillance procedures for some multivariate problems

The continual surveillance to detect changes has so far received large attention in the area of industrial quality control, where the monitoring of manufacturing processes to detect decreases in quality play an important role. However, also in other areas important examples can be found such as the surveillance of intensity care patients or the monitoring of economic trends. Often more than one measurement is made, resulting in a multivariate observation process. Many surveillance procedures for multivariate observation processes are based on summarizing statistics that reduces the multivariate process to a univariate process. This thesis studies such surveillance procedures when a change to a specific alternative is of interest. We give special attention to procedures based on likelihood ratio statistics of the observation vectors since these are known to have several optimality properties. Also, many procedures in use today can be formulated in terms of likelihood ratios. In report I we consider the surveillance of a multivariate process with a common change point for all component processes. We show that the univariate reduction using the likelihood ratio statistic for the observation vector from each observation time is sufficient for detecting the change. Furthermore, the use of a likelihood ratio-based method, the LR method, for constructing surveillance procedures is suggested for multivariate surveillance situations. The LR procedure, as several other multivariate surveillance procedures, can be formulated as univariate procedures based on the univariate process of likelihood ratios. Thus, evaluating these multivariate surveillance procedures which are based on this reduction can be done by using results for univariate procedures, for example those given in report II. The effects of not using a sufficient univariate statistic is also illustrated. In the second report a simulation study of some methods based on likelihood ratios of univariate processes is made. The LR method and the Roberts procedure are compared with two methods that today are in common use, the Shewhart and the CUSUM methods. Several different measurements of performance are used, such as the probability of successful detection, the predictive value and the expected delay of an alarm. The evaluation is made for geometrically distributed change points. For this situation the LR procedure meets several optimality criteria and is therefore suitable as a benchmark. The LR procedure is shown to be robust against misspecifications of the intensities. The CUSUM method appears in the simulations to be closer to the Shewhart method than to the Roberts method in several of the properties investigated, for example the run length distribution and the predictive value. Furthermore, the Roberts procedure is shown to have properties close to the LR procedure for moderately large intensities. It has therefore near optimal properties in these cases

Some principles for surveillance adopted for multivariate processes with a common change point

The surveillance of multivariate processes has received growing attention during the last decade. Several generalizations of well-known methods such as Shew hart , CUSUM and EWMA charts have been proposed. Many of these multivariate procedures are based on a univariate summarized statistic of the multivariate observations, usually the likelihood ratio statistic. In this paper we consider the surveillance of multivariate observation processes for a shift between two fully specified alternatives. The effect of the dimension reduction using likelihood ratio statistics are discussed in the context of sufficiency properties. Also, an example of the loss of efficiency when not using the univariate sufficient statistic is given. Furthermore, a likelihood ratio method, the LR method, for constructing surveillance procedures is suggested for multivariate surveillance situations. It is shown to produce univariate surveillance procedures based on the sufficient likelihood ratios. As the LR procedure has several optimality properties in the univariate, it is also used here as a benchmark for comparisons between multivariate surveillance procedures