The Purinergic Receptor P2X4 Promotes Th17 Activation and the Development of Arthritis.

Purinergic signaling plays a major role in T cell activation leading to IL-2 production and proliferation. However, it is unclear whether purinergic signaling contributes to the differentiation and activation of effector T cells. In this study, we found that the purinergic receptor P2X4 was associated with human Th17 cells but not with Th1 cells. Inhibition of P2X4 receptor with the specific antagonist 5-BDBD and small interfering RNA inhibited the development of Th17 cells and the production of IL-17 by effector Th17 cells stimulated via the CD3/CD28 pathway. Our results showed that P2X4 was required for the expression of retinoic acid-related orphan receptor C, which is the master regulator of Th17 cells. In contrast, inhibition of P2X4 receptor had no effect on Th1 cells and on the production of IFN-γ and it did not affect the expression of the transcription factor T-bet (T-box transcription factor). Furthermore, inhibition of P2X4 receptor reduced the production of IL-17 but not of IFN-γ by effector/memory CD4+ T cells isolated from patients with rheumatoid arthritis. In contrast to P2X4, inhibition of P2X7 and P2Y11 receptors had no effects on Th17 and Th1 cell activation. Finally, treatment with the P2X4 receptor antagonist 5-BDBD reduced the severity of collagen-induced arthritis in mice by inhibiting Th17 cell expansion and activation. Our findings provide novel insights into the role of purinergic signaling in T cell activation and identify a critical role for the purinergic receptor P2X4 in Th17 activation and in autoimmune arthritis.

Phospholipase A1 Member A Activates Fibroblast-like Synoviocytes through the Autotaxin-Lysophosphatidic Acid Receptor Axis.

Lysophosphatidylserine (lysoPS) is known to regulate immune cell functions. Phospholipase A1 member A (PLA1A) can generate this bioactive lipid through hydrolysis of sn-1 fatty acids on phosphatidylserine (PS). PLA1A has been associated with cancer metastasis, asthma, as well as acute coronary syndrome. However, the functions of PLA1A in the development of systemic autoimmune rheumatic diseases remain elusive. To investigate the possible implication of PLA1A during rheumatic diseases, we monitored PLA1A in synovial fluids from patients with rheumatoid arthritis and plasma of early-diagnosed arthritis (EA) patients and clinically stable systemic lupus erythematosus (SLE) patients. We used human primary fibroblast-like synoviocytes (FLSs) to evaluate the PLA1A-induced biological responses. Our results highlighted that the plasma concentrations of PLA1A in EA and SLE patients were elevated compared to healthy donors. High concentrations of PLA1A were also detected in synovial fluids from rheumatoid arthritis patients compared to those from osteoarthritis (OA) and gout patients. The origin of PLA1A in FLSs and the arthritic joints remained unknown, as healthy human primary FLSs does not express the PLA1A transcript. Besides, the addition of recombinant PLA1A stimulated cultured human primary FLSs to secrete IL-8. Preincubation with heparin, autotaxin (ATX) inhibitor HA130 or lysophosphatidic acid (LPA) receptor antagonist Ki16425 reduced PLA1A-induced-secretion of IL-8. Our data suggested that FLS-associated PLA1A cleaves membrane-exposed PS into lysoPS, which is subsequently converted to LPA by ATX. Since primary FLSs do not express any lysoPS receptors, the data suggested PLA1A-mediated pro-inflammatory responses through the ATX-LPA receptor signaling axis.

Multitask Interactive Attention Learning Model Based on Hand Images for Assisting Chinese Medicine in Predicting Myocardial Infarction.

Acute myocardial infarction (AMI) is one of the most serious and dangerous cardiovascular diseases. In recent years, the number of patients around the world has been increasing significantly, among which people under the age of 45 have become the high-risk group for sudden death of AMI. AMI occurs quickly and does not show obvious symptoms before onset. In addition, postonset clinical testing is also a complex and invasive test, which may cause some postoperative complications. Therefore, it is necessary to propose a noninvasive and convenient auxiliary diagnostic method. In traditional Chinese medicine (TCM), it is an effective auxiliary diagnostic strategy to complete the disease diagnosis through some body surface features. It is helpful to observe whether the palmar thenar undergoes hypertrophy and whether the metacarpophalangeal joint is swelling in detecting acute myocardial infarction. Combined with deep learning, we propose a depth model based on traditional palm image (MTIALM), which can help doctors of traditional Chinese medicine to predict myocardial infarction. By building the shared network, the model learns information that covers all the tasks. In addition, task-specific attention branch networks are built to simultaneously detect the symptoms of different parts of the palm. The information interaction module (IIM) is proposed to further integrate the information between task branches to ensure that the model learns as many features as possible. Experimental results show that the accuracy of our model in the detection of metacarpophalangeal joints and palmar thenar is 83.16% and 84.15%, respectively, which are significantly improved compared with the traditional classification methods.