Harnessing RNA sequencing for global, unbiased evaluation of two new adjuvants for dendritic-cell immunotherapy

Effective stimulation of immune cells is crucial for the success of cancer immunotherapies. Current approaches to evaluate the efficiency of stimuli are mainly defined by known flow cytometry-based cell activation or cell maturation markers. This method however does not give a complete overview of the achieved activation state and may leave important side effects unnoticed. Here, we used an unbiased RNA sequencing (RNA-seq)-based approach to compare the capacity of four clinical-grade dendritic cell (DC) activation stimuli used to prepare DC-vaccines composed of various types of DC subsets; the already clinically applied GM-CSF and Frühsommer meningoencephalitis (FSME) prophylactic vaccine and the novel clinical grade adjuvants protamine-RNA complexes (pRNA) and CpG-P. We found that GM-CSF and pRNA had similar effects on their target cells, whereas pRNA and CpG-P induced stronger type I interferon (IFN) expression than FSME. In general, the pathways most affected by all stimuli were related to immune activity and cell migration. GMCSF stimulation, however, also induced a significant increase of genes related to nonsense-mediated decay, indicating a possible deleterious effect of this stimulus. Taken together, the two novel stimuli appear to be promising alternatives. Our study demonstrates how RNA-seq based investigation of changes in a large number of genes and gene groups can be exploited for fast and unbiased, global evaluation of clinicalgrade stimuli, as opposed to the general limited evaluation of a pre-specified set of genes, by which one might miss important biological effects that are detrimental for vaccine efficacy

Shape characterization of polymersome morphologies via light scattering techniques

Polymersomes, vesicles self-assembled from amphiphilic block copolymers, are well known for their robustness and for their broad applicability. Generating polymersomes of different shape is a topic of recent attention, specifically in the field of biomedical applications. To obtain information about their exact shape, tomography based on cryo-electron microscopy is usually the most preferred technique. Unfortunately, this technique is rather time consuming and expensive. Here we demonstrate an alternative analytical approach for the characterization of differently shaped polymersomes such as spheres, prolates and discs via the combination of multi-angle light scattering (MALS) and quasi-elastic light scattering (QELS). The use of these coupled techniques allowed for accurate determination of both the radius of gyration (Rg) and the hydrodynamic radius (Rh). This afforded us to determine the shape ratio ρ (Rg/Rh) with which we were able to distinguish between polymersome spheres, discs and rods.</p

Characterization of Irradiated Metal Waste from the Pyrometallurgical Treatment of Used EBR-II Fuel

As part of the pyrometallurgical treatment of used Experimental Breeder Reactor-II fuel, a metal waste stream is generated consisting primarily of cladding hulls laden with fission products noble to the electrorefining process. Consolidation by melting at high temperature [1873 K (1600 degrees C)] has been developed to sequester the noble metal fission products (Zr, Mo, Tc, Ru, Rh, Te, and Pd) which remain in the iron-based cladding hulls. Zirconium from the uranium fuel alloy (U-10Zr) is also deposited on the hulls and forms Fe-Zr intermetallics which incorporate the noble metals as well as residual actinides during processing. Hence, Zr has been chosen as the primary indicator for consistency of the metal waste. Recently, the first production-scale metal waste ingot was generated and sampled to monitor Zr content for Fe-Zr intermetallic phase formation and validation of processing conditions. Chemical assay of the metal waste ingot revealed a homogeneous distribution of the noble metal fission products as well as the primary fuel constituents U and Zr. Microstructural characterization of the ingot confirmed the immobilization of the noble metals in the Fe-Zr intermetallic phase

Investigating web-based recruitment sources: Employee testimonials vs word-of-mouse

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Effects of eight neuropsychiatric copy number variants on human brain structure

peer reviewedMany copy number variants (CNVs) confer risk for the same range of neurodevelopmental symptoms and psychiatric conditions including autism and schizophrenia. Yet, to date neuroimaging studies have typically been carried out one mutation at a time, showing that CNVs have large effects on brain anatomy. Here, we aimed to characterize and quantify the distinct brain morphometry effects and latent dimensions across 8 neuropsychiatric CNVs. We analyzed T1-weighted MRI data from clinically and non-clinically ascertained CNV carriers (deletion/duplication) at the 1q21.1 (n = 39/28), 16p11.2 (n = 87/78), 22q11.2 (n = 75/30), and 15q11.2 (n = 72/76) loci as well as 1296 non-carriers (controls). Case-control contrasts of all examined genomic loci demonstrated effects on brain anatomy, with deletions and duplications showing mirror effects at the global and regional levels. Although CNVs mainly showed distinct brain patterns, principal component analysis (PCA) loaded subsets of CNVs on two latent brain dimensions, which explained 32 and 29% of the variance of the 8 Cohen’s d maps. The cingulate gyrus, insula, supplementary motor cortex, and cerebellum were identified by PCA and multi-view pattern learning as top regions contributing to latent dimension shared across subsets of CNVs. The large proportion of distinct CNV effects on brain morphology may explain the small neuroimaging effect sizes reported in polygenic psychiatric conditions. Nevertheless, latent gene brain morphology dimensions will help subgroup the rapidly expanding landscape of neuropsychiatric variants and dissect the heterogeneity of idiopathic conditions. © 2021, The Author(s)

Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns

Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike’s information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk