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Abstract Background and objectives The study investigated the pathogenesis of Yao syndrome (YAOS), a rare systemic autoinflammatory disease associated with the nucleotide-binding oligomerization domain containing 2 (NOD2) gene variants. Methods RNA sequencing analyses were used to detect transcriptomic profile changes. Immunoblot and immunohistochemistry were used to examine the NOD2-mediated inflammatory signaling pathways and ELISA was used to detect cytokines. Results Transcriptome analysis of YAOS revealed NOD-like receptor signaling pathway enrichment. Compared with HCs, P-RIP2, p-p65, p-p38, p-ERK, and p-JNK notably increased in PBMCs of a patient with YAOS. P-RIP2, p-p65, and p-p38 elevated in small intestinal mucosa tissues. P-p65 and p-p38 in synovial tissues from YAOS were higher than those in patients with rheumatoid arthritis (RA) and osteoarthritis (OA). Serum interleukin (IL)-6 level along with tumor necrosis factor (TNF)-α and IL-6 secreted from PBMCs were markedly higher in patients with YAOS in comparison to healthy controls (HCs). The supernatants of synovial cells from a patient with YAOS showed substantially higher IL-1β and IL-6 levels than those of RA and OA. Canakinumab therapy of a Q902K heterozygous patient with YAOS resulted in notable clinical improvement. Conclusion Overproduction of pro-inflammatory cytokines and the hyperactivation of NOD2-mediated signaling pathways were found in the NOD2 variant Q902K patient with YAOS. NOD2-RIP2-MAPK pathway might play a pivotal role in the pathogenesis of YAOS. These results provide new perspectives for targeted therapies in YAOS.

Abstract Backgrounds Traditional Chinese medicine and Western medicine combination (TCM-WMC) increased the complexity of compounds ingested. Objective To develop a method for screening hepatotoxic compounds in TCM-WMC based on chemical structures using artificial intelligence (AI) methods. Methods Drug-induced liver injury (DILI) data was collected from the public databases and published literatures. The total dataset formed by DILI data was randomly divided into training set and test set at a ratio of 3:1 approximately. Machine learning models of SGD (Stochastic Gradient Descent), kNN (k-Nearest Neighbor), SVM (Support Vector Machine), NB (Naive Bayes), DT (Decision Tree), RF (Random Forest), ANN (Artificial Neural Network), AdaBoost, LR (Logistic Regression) and one deep learning model (deep belief network, DBN) were adopted to construct models for screening hepatotoxic compounds. Result Dataset of 2035 hepatotoxic compounds was collected in this research, in which 1505 compounds were as training set and 530 compounds were as test set. Results showed that RF obtained 0.838 of classification accuracy (CA), 0.827 of F1-score, 0.832 of Precision, 0.838 of Recall, 0.814 of area under the curve (AUC) on the training set and 0.767 of CA, 0.731 of F1, 0.739 of Precision, 0.767 of Recall, 0.739 of AUC on the test set, which was better than other eight machine learning methods. The DBN obtained 82.2% accuracy on the test set, which was higher than any other machine learning models on the test set. Conclusion The DILI AI models were expected to effectively screen hepatotoxic compounds in TCM-WMC.

Abstract Objectives Blau syndrome (BS) is a rare dominantly inherited autoinflammatory disorder associated with mutations in the nucleotide-binding oligomerization domain containing 2 (NOD2) gene. Biologic therapy of BS yielded diverse results. We aimed to evaluate clinical features and outcomes of Chinese patients with BS who were treated with tumor necrosis factor (TNF)α inhibitors. Methods A total of four patients with BS were diagnosed and treated with infliximab (IFX) at the Peking Union Medical College Hospital during 2015 to 2018 and were followed up for 18 months. All patients were systematically studied for treatment outcomes including the clinical manifestations and inflammatory markers. We also conducted a comprehensive literature review about TNFα inhibitor therapy in BS. Results Four BS patients were all Chinese Han, and three were women. The mean age of disease onset was 4 ± 3.5 years, and the mean time of diagnosis delay was 19 ± 11 years. All patients received IFX plus methotrexate, and all achieved clinical remission of skin lesions and polyarthritis rapidly, as well as normalization of erythrocyte sedimentation rate and C-reactive protein and improvements in inflammatory cytokines, patient visual analogue scale, physician global assessment, and Short Form (SF)-36, at the first follow-up of 6 months. The disease relapsed in two patients after they lengthened the interval of IFX and discontinued methotrexate. According to the 38 English-language publications, 62 patients with BS were reported who underwent TNFα inhibitor therapy, including IFX used in 31, adalimumab in 24, and etanercept in 7. IFX was well tolerated in 27 patients, while 2 still had uveitis, and the other 2 experienced an adverse drug reaction. Conclusions Early recognition and effective treatment of BS are very important to avoid irreversible organ damage. TNFα inhibitors such as IFX may be a promising approach for BS patients who have unsatisfactory response to corticosteroids and traditional disease-modifying antirheumatic drugs.