Thymus and Activation-regulated Chemokine as a Biomarker for IgG4-related Disease

High serum concentrations of thymus and activation-regulated chemokine (TARC) are observed in allergic diseases such as atopic dermatitis and bronchial asthma. Frequent allergic symptoms have been reported in patients with IgG4-related disease (IgG4-RD). We investigated the pathogenic role of TARC as a biomarker in IgG4-RD patients. We evaluated the serum concentrations of TARC from 29 IgG4-RD patients, 28 primary Sjogren syndrome (pSS) patients, and 23 healthy controls (HCs) by enzyme-linked immunosorbent assay (ELISA). We analyzed the correlations between the TARC concentrations and the subjects’ clinical parameters. To investigate the biological effect of TARC on the pathogenesis of IgG4-RD, we evaluated the in vitro induction of plasmablasts from IgG4-RD patients by TARC. The serum concentrations of TARC in the IgG4-RD patients were significantly higher than those of the pSS patients and HCs. The serum TARC concentration of the IgG4-RD group was positively correlated with the IgG4-RD responder index (IgG4-RD RI) score and with the number of organs involved, but it was not correlated with the serum IgG4 level or eosinophil number in the IgG4-RD patients’ peripheral blood. The patients who had lung involvement had higher serum TARC concentrations. In vitro, TARC clearly induced the formation of plasmablasts from the IgG4-RD patients’ peripheral blood mononuclear cells. Collectively, our data suggest that a systemic increment of TARC may contribute to the development of IgG4-RD through an aberrant induction of plasmablasts

Granulocyte-macrophage colony-stimulating factor and tumor necrosis factor-α in combination is a useful diagnostic biomarker to distinguish familial Mediterranean fever from sepsis

Objective: To identify potential biomarkers to distinguish familial Mediterranean fever (FMF) from sepsis.Method: We recruited 28 patients diagnosed with typical FMF (according to the Tel Hashomer criteria), 22 patients with sepsis, and 118 age-matched controls. Serum levels of 40 cytokines were analyzed using multi-suspension cytokine array. We performed a cluster analysis of each cytokine in the FMF and sepsis groups in order to identify specific molecular networks. Multivariate classification (random forest analysis) and logistic regression analysis were used to rank the cytokines by importance and determine specific biomarkers for distinguishing FMF from sepsis.Results: Fifteen of the 40 cytokines were found to be suitable for further analysis. Levels of serum granulocyte-macrophage colony-stimulating factor (GM-CSF), fibroblast growth factor 2, vascular endothelial growth factor, macrophage inflammatory protein-1b, and interleukin-17 were significantly elevated, whereas tumor necrosis factor-α (TNF-α) was significantly lower in patients with FMF compared with those with sepsis. Cytokine clustering patterns differed between the two groups. Multivariate classification followed by logistic regression analysis revealed that measurement of both GM-CSF and TNF-α could distinguish FMF from sepsis with high accuracy (cut-off values for GM-CSF = 8.3 pg/mL; TNF-α = 16.3 pg/mL; sensitivity, 92.9%; specificity, 94.4%; accuracy, 93.4%).Conclusion: Determination of GM-CSF and TNF-α levels in combination may represent a biomarker for the differential diagnosis of FMF from sepsis, based on measurement of multiple cytokines

Monte Carlo Thompson sampling-guided design for antibody engineering

ABSTRACTAntibodies are one of the predominant treatment modalities for various diseases. To improve the characteristics of a lead antibody, such as antigen-binding affinity and stability, we conducted comprehensive substitutions and exhaustively explored their sequence space. However, it is practically unfeasible to evaluate all possible combinations of mutations owing to combinatorial explosion when multiple amino acid residues are incorporated. It was recently reported that a machine-learning guided protein engineering approach such as Thompson sampling (TS) has been used to efficiently explore sequence space in the framework of Bayesian optimization. For TS, over-exploration occurs when the initial data are biasedly distributed in the vicinity of the lead antibody. We handle a large-scale virtual library that includes numerous mutations. When the number of experiments is limited, this over-exploration causes a serious issue. Thus, we conducted Monte Carlo Thompson sampling (MTS) to balance the exploration-exploitation trade-off by defining the posterior distribution via the Monte Carlo method and compared its performance with TS in antibody engineering. Our results demonstrated that MTS largely outperforms TS in discovering desirable candidates at an earlier round when over-exploration occurs on TS. Thus, the MTS method is a powerful technique for efficiently discovering antibodies with desired characteristics when the number of rounds is limited

A novel methodology utilizing microchip implants to monitor individual activity and body temperature for assessing knee pain in group-housed rats

Abstract The pain assessment in animals is challenging as they cannot verbally express the site and severity of pain. In this study, we tried a small implantable actimeter, “Nanotag”, to monitor spontaneous locomotor activity and body temperature in animals suffering from a chemical-induced rat knee arthritis as compared to naïve and steroid-treated rats. Nanotag could detect the decrease in locomotor activity quickly after the arthritis induction and anti-inflammation analgesic treatment by intra-articular injection of steroid significantly improved locomotor activity. These changes were in the same line with those of a conventional knee pain evaluation method (incapacitance test). Nanotag can be utilized as the non-interventional, continuous, and completely objective monitoring the amount of pain in rat knee arthritis model. This traditional yet innovative method may be universally applicable to various pain models and species, making it a worthwhile device for research across diverse fields

Therapeutic effect of C-type natriuretic peptide on persistent pain in a rat knee arthritis model

Background Intra-articular injection of C-type natriuretic peptide (CNP) at the acute inflammatory stage suppressed fibrotic changes in the infrapatellar fat pad (IFP), articular cartilage degeneration, and persistent pain in a monoiodoacetic acid (MIA)-induced rat knee arthritis model. In this study, we administered CNP during the inflammation subsiding period to evaluate CNP effectiveness in knees with osteoarthritis (OA) pathology. Methods 20 male Wistar rats were randomly divided into two groups. The rats received an intra-articular injection of MIA solution in the right knee to induce inflammation-induced joint degeneration. One group subsequently received an intra-articular CNP injection for six consecutive days from day 8, whereas another group received vehicle solution. Pain avoidance behavior tests and histological analyses were conducted to examine the therapeutic effects of CNP. Results The incapacitance test indicated that the percent weight on the ipsilateral limb decreased after MIA injection by day 4 and continued to decrease until the end of the experiment in the vehicle group, suggesting persistent pain in the knee. Intra-articular injection of CNP reversed the weight-bearing ratio on day 19. Histological evaluation showed that the CNP group had more residual fat tissue in the IFP and fewer calcitonin gene-related peptide-positive nerve endings compared to the vehicle group. CNP could not reverse articular cartilage degeneration. Conclusions Intra-articular injection of CNP after the IFP fibrosis onset had no significant effect on OA severity and extent. Nevertheless, CNP might be utilized therapeutically for OA treatment since it can alleviate persistent knee pain and inhibit structural changes in residual fat tissue

08 【3.2.2 強風観測結果】成果 23号館(免震棟)の強風時実挙動観測

３．研究成果の概要　３.２〈研究テーマ②〉デバイスを設置した建物の実挙動観