Recent evidence suggests that a substantial portion of complex disease risk alleles modify gene expression in a cell-specific manner. To identify candidate causal genes and biological pathways of immune-related complex diseases, we conducted expression quantitative trait loci (eQTL) analysis on five subsets of immune cells (CD4 T cells, CD8 T cells, B cells, natural killer (NK) cells and monocytes) and unfractionated peripheral blood from 105 healthy Japanese volunteers. We developed a three-step analytical pipeline comprising (i) prediction of individual gene expression using our eQTL database and public epigenomic data, (ii) gene-level association analysis and (iii) prediction of cell-specific pathway activity by integrating the direction of eQTL effects. By applying this pipeline to rheumatoid arthritis data sets, we identified candidate causal genes and a cytokine pathway (upregulation of tumor necrosis factor (TNF) in CD4 T cells). Our approach is an efficient way to characterize the polygenic contributions and potential biological mechanisms of complex diseases.

To obtain high quality of drinking water free from biocontaminants is especially important issue. A new strategy employing smectic liquid‐crystalline ionic membranes exhibiting 2D structures of layered nanochannels for water treatment is proposed for efficient virus removal and sufficient water flux. The smectic A (SmA) liquid‐crystalline membranes obtained by in situ polymerization of an ionic mesogenic monomer are examined for removal of three distinct viruses with small size: Qβ bacteriophage, MS2 bacteriophage, and Aichi virus. The semi‐bilayer structure of the SmA significantly obstructs the virus penetration with an average log reduction value of 7.3 log10 or the equivalent of reducing 18 million viruses down to 1. Furthermore, the layered nanochannels of the SmA liquid crystal allow efficient water permeation compared to other types of liquid‐crystalline membrane consisting of nanopores.

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Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease that leads to destructive arthritis. Although the HLA class II locus is the strongest genetic risk factor for rheumatoid arthritis, the relationship between HLA class II alleles and lymphocyte activation remains unclear. We performed immunophenotyping of peripheral blood mononuclear cells on 91 HLA-DRB1-genotyped RA patients and 110 healthy donors. The frequency of memory CXCR4+CD4+ T cells, and not Th1 and Th17 cells, was significantly associated with disease severity by multiple linear regression analysis. RA patients with one or more susceptible HLA-DR haplotypes (shared epitope: SE) displayed a significantly higher frequency of memory CXCR4+CD4+ T cells. Moreover, the frequency of memory CXCR4+CD4+ T cells significantly correlated with the expression level of HLA-DR on B cells, which was elevated in RA patients with SE. In vitro analysis and transcriptomic pathway analysis suggested that the interaction between HLA-DR and T cell receptors is an important regulator of memory CXCR4+CD4+ T cells. Clinically, a higher frequency of memory CXCR4+CD4+ T cells predicted a better response to CTLA4-Ig. Memory CXCR4+CD4+ T cells may serve as a powerful biomarker for unraveling the linkage between HLA-DRB1 genotype and disease activity in RA.

Structural color colloidal sols of perovskite nanosheets were synthesized and were immobilized in a polymer hydrogel film by in situ photopolymerization, leading to a novel mechanochromic material. Visible absorption spectroscopy, polarized optical microscopy and small-angle X-ray scattering revealed that the nanosheets are aligned parallel to the film surface with the periodic distance of up to ca. 300 nm, giving the structural color tunable over full color range. The present structural color gel showed reversible mechanochromic response that detects weak stress of 1 kPa with the quick response time less than 1 ms as well as high mechanical toughness (compressive breaking stress of up to 3 MPa). These excellent properties are suitable for applications for mechanosensors and displays.