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Exosomes are extracellular vesicles that can participate in autoimmune diseases. The purpose of this study was to explore whether circulating exosomes are involved in Graves' disease (GD) pathogenesis. In this study, serum exosomes were extracted from 26 healthy controls (HC-EXO), 26 GD patients (GD-EXO), and 7 Graves' ophthalmopathy patients (GO-EXO). For each group, the total protein content was detected, and thyrotropin receptor, insulin-like growth factor 1 receptor (IGF-1R), heat shock protein 60 (HSP60), and cluster of differentiation (CD) 63 expression were analyzed by Western blotting (WB). Healthy volunteer-derived peripheral blood mononuclear cells (PBMCs) and HC-EXO or GD-EXO were cocultured for 24 h, and immunofluorescence was used to observe the locations of the exosomes and toll-like receptor (TLR) 2/3. CD11c+TLR2+ and CD11c+TLR3+ cell percentages were determined by flow cytometry. Myeloid differentiation factor 88 (MyD88), toll/interleukin (IL)-1 receptor domain-containing adaptor inducing interferon-β (TRIF) and p-P65 expression were analyzed by WB. IL-6 and IL-1β supernatant levels were detected using enzyme-linked immunosorbent assay. The results showed that the total protein concentration was similar among GD-EXO, GO-EXO, and HC-EXO. IGF-1R and HSP60 expression was significantly higher in GD-EXO and GO-EXO than in HC-EXO. After coculturing PBMCs with GD-EXO or HC-EXO for 24 h, GD-EXO could bind to TLR2/3. GD-EXO significantly increased CD11c+TLR2+ and CD11c+TLR3+ cell percentages; MyD88, TRIF, and p-P65 protein expression; and IL-6 and IL-1β levels. In conclusion, we first demonstrated that GD-EXO and GO-EXO highly expressed IGF-1R and HSP60. GD-EXO may induce an inflammatory response through the TLR/NF-κB signaling pathway and be involved in the pathogenesis of GD., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The etiology of schizophrenia (SCZ) is regarded as one of the most fundamental puzzles in current medical research, and its diagnosis is limited by the lack of objective molecular criteria. Although plenty of studies were conducted, SCZ gene signatures identified by these independent studies are found highly inconsistent. As one of the most important factors contributing to this inconsistency, the feature selection methods used currently do not fully consider the reproducibility among the signatures discovered from different datasets. Therefore, it is crucial to develop new bioinformatics tools of novel strategy for ensuring a stable discovery of gene signature for SCZ. In this study, a novel feature selection strategy (1) integrating repeated random sampling with consensus scoring and (2) evaluating the consistency of gene rank among different datasets was constructed. By systematically assessing the identified SCZ signature comprising 135 differentially expressed genes, this newly constructed strategy demonstrated significantly enhanced stability and better differentiating ability compared with the feature selection methods popular in current SCZ research. Based on a first-ever assessment on methods' reproducibility cross-validated by independent datasets from three representative studies, the new strategy stood out among the popular methods by showing superior stability and differentiating ability. Finally, 2 novel and 17 previously reported transcription factors were identified and showed great potential in revealing the etiology of SCZ. In sum, the SCZ signature identified in this study would provide valuable clues for discovering diagnostic molecules and potential targets for SCZ., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Interleukin (IL)-10 is a highly important anti-inflammatory cytokine in the immune system. CD1dhi and CD5+ B cells are both traditionally defined IL-10-secreting B cells. In recent years, a B cell group with combined markers of CD1dhi and CD5+ has been widely studied as it has been reported to suppress autoimmunity in mouse models of autoimmune diseases through IL-10 mechanisms. From the perspective of origination, CD1dhi and CD5+ B cells are developed from different B cell lineages. Whether the regulatory capacity of these 2 B cell groups is consistent with their ability to secrete IL-10 has not been determined. In this study, we generated IL-10 knockout NOD.H-2h4 mice to investigate the function of endogenous IL-10 in autoimmune thyroiditis and conducted adoptive transfer experiments to explore the respective roles of CD5+ and CD1dhi B cells. In our results, the IL-10-/- NOD.H-2h4 mice developed thyroiditis, similar to wild-type NOD.H-2h4 mice. The CD5+ B cells were more capable of secreting IL-10 than CD1dhi B cells in flow cytometric analysis, but the CD1dhi B cells showed more suppressive effects on thyroiditis development and autoantibody production, as well as Th17 cell response. In conclusion, endogenous IL-10 does not play an important role in autoimmune thyroiditis. CD1dhi B cells may play regulatory roles through mechanisms other than secreting IL-10., (© Endocrine Society 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Label-free quantification (LFQ) with a specific and sequentially integrated workflow of acquisition technique, quantification tool and processing method has emerged as the popular technique employed in metaproteomic research to provide a comprehensive landscape of the adaptive response of microbes to external stimuli and their interactions with other organisms or host cells. The performance of a specific LFQ workflow is highly dependent on the studied data. Hence, it is essential to discover the most appropriate one for a specific data set. However, it is challenging to perform such discovery due to the large number of possible workflows and the multifaceted nature of the evaluation criteria. Herein, a web server ANPELA (https://idrblab.org/anpela/) was developed and validated as the first tool enabling performance assessment of whole LFQ workflow (collective assessment by five well-established criteria with distinct underlying theories), and it enabled the identification of the optimal LFQ workflow(s) by a comprehensive performance ranking. ANPELA not only automatically detects the diverse formats of data generated by all quantification tools but also provides the most complete set of processing methods among the available web servers and stand-alone tools. Systematic validation using metaproteomic benchmarks revealed ANPELA's capabilities in 1 discovering well-performing workflow(s), (2) enabling assessment from multiple perspectives and (3) validating LFQ accuracy using spiked proteins. ANPELA has a unique ability to evaluate the performance of whole LFQ workflow and enables the discovery of the optimal LFQs by the comprehensive performance ranking of all 560 workflows. Therefore, it has great potential for applications in metaproteomic and other studies requiring LFQ techniques, as many features are shared among proteomic studies., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Objective: This study explored whether circulating exosomes effectively participate in the inflammatory response in Hashimoto thyroiditis (HT)., Design: Exosomes were extracted from the serum of 30 patients with HT and 30 healthy control (HC) subjects. The expression of thyroperoxidase (TPO), thyroglobulin, high mobility group box 1 (HMGB1), heat shock protein 60 (HSP60), major histocompatibility complex class II (MHC-II), and intercellular adhesion molecule 1 (ICAM1) in exosomes was determined by Western blotting. Flow cytometry and immunofluorescence were performed to confirm that exosomes were taken up by healthy peripheral blood mononuclear cells (PBMCs) and dendritic cells (DCs). Then, either DCs or PBMCs were stimulated with HT exosomes (serum exosomes from patients with HT) or HC exosomes (serum exosomes from HC subjects) in the presence or absence of Toll-like receptor (TLR)2/3 inhibitors., Results: TPO, HSP60, and MHC-II expression was higher in HT exosomes than in HC exosomes. Exosomes were mainly taken up by CD14+ monocytes and CD11c+ DCs. After DCs were stimulated by HT exosomes, significant elevations were observed in MyD88, TRIF, and p-P65 expression; median fluorescence intensity of CD40 and CD83; and IL-6 production. After stimulating PBMCs with HT exosomes, CD11c+TLR2+/TLR3+ and CD4+IFN-γ+Th1/IL-17A+Th17A cell percentages were significantly elevated, and CD4+CD25+Foxp3+ Treg cell percentage was significantly decreased. HT exosomes induced increased IL-17A and IFN-γ production, whereas IL-10 production was suppressed. However, addition of TLR2 or TLR3 inhibitor reversed most of the abovementioned results., Conclusions: Our study demonstrates that HT exosomes can present antigens to DCs and bind TLR2/3, causing DC activation via the nuclear factor κB signaling pathway, leading to an imbalance in CD4+ T lymphocyte differentiation, and potentially contributing to HT onset., (Copyright © 2019 Endocrine Society.)

Extensive efforts have been directed at the discovery, investigation and clinical monitoring of targeted therapeutics. These efforts may be facilitated by the convenient access of the genetic, proteomic, interactive and other aspects of the therapeutic targets. Here, we describe an update of the Therapeutic target database (TTD) previously featured in NAR. This update includes: (i) 2000 drug resistance mutations in 83 targets and 104 target/drug regulatory genes, which are resistant to 228 drugs targeting 63 diseases (49 targets of 61 drugs with patient prevalence data); (ii) differential expression profiles of 758 targets in the disease-relevant drug-targeted tissue of 12 615 patients of 70 diseases; (iii) expression profiles of 629 targets in the non-targeted tissues of 2565 healthy individuals; (iv) 1008 target combinations of 1764 drugs and the 1604 target combination of 664 multi-target drugs; (v) additional 48 successful, 398 clinical trial and 21 research targets, 473 approved, 812 clinical trial and 1120 experimental drugs, and (vi) ICD-10-CM and ICD-9-CM codes for additional 482 targets and 262 drugs against 98 disease conditions. This update makes TTD more useful for facilitating the patient focused research, discovery and clinical investigations of the targeted therapeutics. TTD is accessible at http://bidd.nus.edu.sg/group/ttd/ttd.asp., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Diverse forms of unwanted signal variations in mass spectrometry-based metabolomics data adversely affect the accuracies of metabolic profiling. A variety of normalization methods have been developed for addressing this problem. However, their performances vary greatly and depend heavily on the nature of the studied data. Moreover, given the complexity of the actual data, it is not feasible to assess the performance of methods by single criterion. We therefore developed NOREVA to enable performance evaluation of various normalization methods from multiple perspectives. NOREVA integrated five well-established criteria (each with a distinct underlying theory) to ensure more comprehensive evaluation than any single criterion. It provided the most complete set of the available normalization methods, with unique features of removing overall unwanted variations based on quality control metabolites and allowing quality control samples based correction sequentially followed by data normalization. The originality of NOREVA and the reliability of its algorithms were extensively validated by case studies on five benchmark datasets. In sum, NOREVA is distinguished for its capability of identifying the well performed normalization method by taking multiple criteria into consideration and can be an indispensable complement to other available tools. NOREVA can be freely accessed at http://server.idrb.cqu.edu.cn/noreva/., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)