Smooth-threshold multivariate genetic prediction incorporating gene–environment interactions

We propose a genetic prediction modeling approach for genome-wide association study (GWAS) data that can include not only marginal gene effects but also gene–environment (GxE) interaction effects—i.e., multiplicative effects of environmental factors with genes rather than merely additive effects of each. The proposed approach is a straightforward extension of our previous multiple regression-based method, STMGP (smooth-threshold multivariate genetic prediction), with the new feature being that genome-wide test statistics from a GxE interaction analysis are used to weight the corresponding variants. We develop a simple univariate regression approximation to the GxE interaction effect that allows a direct fit of the STMGP framework without modification. The sparse nature of our model automatically removes irrelevant predictors (including variants and GxE combinations), and the model is able to simultaneously incorporate multiple environmental variables. Simulation studies to evaluate the proposed method in comparison with other modeling approaches demonstrate its superior performance under the presence of GxE interaction effects. We illustrate the usefulness of our prediction model through application to real GWAS data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI)

Transformation of cyclodextrin glucanotransferase (CGTase) from aqueous suspension to fine solid particles via electrospraying

In this study, the potential of electrohydrodynamic atomization or electrospraying to produce nanometer-order CGTase particles from aqueous suspension was demonstrated. CGTase enzyme was prepared in acetate buffer solution (1% v/v), followed by electrospraying in stable Taylor cone-jet mode. The deposits were collected on aluminium foil (collector) at variable distances from the tip of spraying needle, ranging from 10 to 25 cm. The Coulomb fission that occurs during electrospraying process successfully transformed the enzyme to the solid state without any functional group deterioration. The functional group verification was conducted by FTIR analysis. Comparison between the deposit and the as-received enzyme in dry state indicates almost identical spectra. By increasing the distance of the collector from the needle tip, the average particle size of the solidified enzyme was reduced from 200 ± 117 nm to 75 ± 34 nm. The average particle sizes produced from the droplet fission were in agreement with the scaling law models. Enzyme activity analysis showed that the enzyme retained its initial activity after the electrospraying process. The enzyme particles collected at the longest distance (25 cm) demonstrated the highest enzyme activity, which indicates that the activity was controlled by the enzyme particle size

Preparation and characterisation of Cyclodextrin glucanotransferase enzyme immobilised in electrospun nanofibrous membrane

An industrial enzyme, Cyclodextrin glucanotransferase (CGTase), was immobilised in polyvinyl alcohol (PVA) nanofiber (average diameter around 200 nm) membrane via co-electrospinning of the CGTase/PVA mixture followed with glutaraldehyde vapour phase cross-linking. Addition of enzyme with concentration ranging from 1.5 to 7.5 % to the PVA solution (8 wt%) caused significant changes to the liquid jet behaviours which consequently affected the nanofiber structures and sizes. Incorporation of CGTase in the PVA membrane was confirmed by Raman spectroscopic analysis. The Raman spectra also showed no structural changes occured to the enzyme after subjected to the electrostatic spinning and cross-linking reaction. The immobilised enzyme showed excellent catalytic efficiency with up to 3.6 times higher enzyme loading, 25 % higher activity and good reusability in comparison with CGTase/PVA film made up from the same starting solution (control)

Preparation and characterisation of cyclodextrin glucanotransferase enzyme immobilised in electrospun nanofibrous membrane

An industrial enzyme, Cyclodextrin glucanotransferase (CGTase), was immobilised in polyvinyl alcohol (PVA) nanofiber (average diameter around 200 nm) membrane via co-electrospinning of the CGTase/PVA mixture followed with glutaraldehyde vapour phase cross-linking. Addition of enzyme with concentration ranging from 1.5 to 7.5 % to the PVA solution (8 wt%) caused significant changes to the liquid jet behaviours which consequently affected the nanofiber structures and sizes. Incorporation of CGTase in the PVA membrane was confirmed by Raman spectroscopic analysis. The Raman spectra also showed no structural changes occured to the enzyme after subjected to the electrostatic spinning and cross-linking reaction. The immobilised enzyme showed excellent catalytic efficiency with up to 3.6 times higher enzyme loading, 25 % higher activity and good reusability in comparison with CGTase/PVA film made up from the same starting solution (control)

Using spin to understand the formation of LIGO's black holes

With the detection of four candidate binary black hole (BBH) mergers by the Advanced LIGO detectors thus far, it is becoming possible to constrain the properties of the BBH merger population in order to better understand the formation of these systems. Black hole (BH) spin orientations are one of the cleanest discriminators of formation history, with BHs in dynamically formed binaries in dense stellar environments expected to have spins distributed isotropically, in contrast to isolated populations where stellar evolution is expected to induce BH spins preferentially aligned with the orbital angular momentum. In this work we propose a simple, model-agnostic approach to characterizing the spin properties of LIGO's BBH population. Using measurements of the effective spin of the binaries, which is LIGO's best constrained spin parameter, we introduce a simple parameter to quantify the fraction of the population that is isotropically distributed, regardless of the spin magnitude distribution of the population. Once the orientation characteristics of the population have been determined, we show how measurements of effective spin can be used to directly constrain the underlying BH spin magnitude distribution. Although we find that the majority of the current effective spin measurements are too small to be informative, with LIGO's four BBH candidates we find a slight preference for an underlying population with aligned spins over one with isotropic spins (with an odds ratio of 1.1). We argue that it will be possible to distinguish symmetric and anti-symmetric populations at high confidence with tens of additional detections, although mixed populations may take significantly more detections to disentangle. We also derive preliminary spin magnitude distributions for LIGO's black holes, under the assumption of aligned or isotropic populations

南大洋110E度線の季節海氷域におけるpCO2の変動

第6回極域科学シンポジウム分野横断セッション：[IB1] 海氷域における生物地球化学的研究11月17日（火）　国立極地研究所１階交流アトリウ

Autoimmune Th17 Cells Induced Synovial Stromal and Innate Lymphoid Cell Secretion of the Cytokine GM-CSF to Initiate and Augment Autoimmune Arthritis

Despite the importance of Th17 cells in autoimmune diseases, it remains unclear how they control other inflammatory cells in autoimmune tissue damage. Using a model of spontaneous autoimmune arthritis, we showed that arthritogenic Th17 cells stimulated fibroblast-like synoviocytes via interleukin-17 (IL-17) to secrete the cytokine GM-CSF and also expanded synovial-resident innate lymphoid cells (ILCs) in inflamed joints. Activated synovial ILCs, which expressed CD25, IL-33Ra, and TLR9, produced abundant GM-CSF upon stimulation by IL-2, IL-33, or CpG DNA. Loss of GM-CSF production by either ILCs or radio-resistant stromal cells prevented Th17 cell-mediated arthritis. GM-CSF production by Th17 cells augmented chronic inflammation but was dispensable for the initiation of arthritis. We showed that GM-CSF-producing ILCs were present in inflamed joints of rheumatoid arthritis patients. Thus, a cellular cascade of autoimmune Th17 cells, ILCs, and stromal cells, via IL-17 and GM-CSF, mediates chronic joint inflammation and can be a target for therapeutic intervention

Amino acid polymorphisms in human histocompatibility leukocyte antigen class II and proinsulin epitope have impacts on type 1 diabetes mellitus induced by immune-checkpoint inhibitors

IntroductionImmune-checkpoint inhibitors are effective in various advanced cancers. Type 1 diabetes mellitus induced by them (ICI-T1DM) is a serious complication requiring prompt insulin treatment, but the immunological mechanism behind it is unclear.MethodsWe examined amino acid polymorphisms in human histocompatibility leukocyte antigen (HLA) molecules and investigated proinsulin epitope binding affinities to HLA molecules.Results and DiscussionTwelve patients with ICI-T1DM and 35 patients in a control group without ICI-T1DM were enrolled in the study. Allele and haplotype frequencies of HLA-DRB1*04:05, DQB1*04:01, and most importantly DPB1*05:01 were significantly increased in patients with ICI-T1DM. In addition, novel amino acid polymorphisms in HLA-DR (4 polymorphisms), in DQ (12 polymorphisms), and in DP molecules (9 polymorphisms) were identified. These amino acid polymorphisms might be associated with the development of ICI-T1DM. Moreover, novel human proinsulin epitope clusters in insulin A and B chains were discovered in silico and in vitro peptide binding assays to HLA-DP5. In conclusion, significant amino acid polymorphisms in HLA-class II molecules, and conformational alterations in the peptide-binding groove of the HLA-DP molecules were considered likely to influence the immunogenicity of proinsulin epitopes in ICI-T1DM. These amino acid polymorphisms and HLA-DP5 may be predictive genetic factors for ICI-T1DM