IntroductionAnti-N-methyl-D-aspartate receptor encephalitis (anti-NMDARE) is a rare autoimmune disease, and the peripheral immune characteristics associated with anti-NMDARE antibodies remain unclear.MethodsHerein, we characterized peripheral blood mononuclear cells from patients with anti-NMDARE and healthy individuals by single-cell RNA sequencing (scRNA-seq).ResultsThe transcriptional profiles of 129,217 cells were assessed, and 21 major cell clusters were identified. B-cell activation and differentiation, plasma cell expansion, and excessive inflammatory responses in innate immunity were all identified. Patients with anti-NMDARE showed higher expression levels of CXCL8, IL1B, IL6, TNF, TNFSF13, TNFSF13B, and NLRP3. We observed that anti-NMDARE patients in the acute phase expressed high levels of DC_CCR7 in human myeloid cells. Moreover, we observed that anti-NMDARE effects include oligoclonal expansions in response to immunizing agents. Strong humoral immunity and positive regulation of lymphocyte activation were observed in acute stage anti-NMDARE patients.DiscussionThis high-dimensional single-cell profiling of the peripheral immune microenvironment suggests that potential mechanisms are involved in the pathogenesis and recovery of anti-NMDAREs.

Background Anti-N-methyl-D-aspartate (NMDA) receptor encephalitis is a type of autoimmune encephalitis (AE) characterized by antibodies against NMDA receptor. As the most common autoimmune encephalitis, anti-NMDAR encephalitis, affects 54% ~ 80% of patients with AE. It is associated with a high percentage of severe illness. It typically manifests as behavioural and psychiatric disturbance, epilepsy, cognitive decline, decreased level of consciousness, involuntary movements, autonomic dysfunction, and central hypoventilation, et.al. Case presentation We report two refractory anti-NMDAR encephalitis. One of them decribes a case of anti-NMDA encephalitis coexisting with MOG antibodies. The two patients were administered first-line therapy with glucocorticoids and intravenous immunoglobulin but did not improved clinically. Therefore, the patient was switched to the fully human anti-CD20 monoclonal antibody, ofatumumab. Their consciousness, behavioural and psychiatric disturbance, and capacity to conduct daily tasks improved markedly after sequential therapy with ofatumumab, as demonstrated by the modified Rankin scale (mRS) score. Conclusion For the first time, we report a successful approach to the treatment of refractory anti-NMDAR encephalitis using the fully human anti-CD20 monoclonal antibody ofatumumab, which serves as an important reference for the treatment of autoimmune encephalitis.

Purpose: Many moyamoya disease (MMD) ischemic strokes were misdiagnosed and could not be treated effectively. To address this question, we aimed to screen easily obtainable clinical variables to construct a differential diagnostic model between MMD and non-MMD ischemic stroke. Methods: A total of 300 patients (150 MMD and 150 non-MMD ischemic strokes) in Henan Provincial People's Hospital were selected and divided into training (210) and validation cohorts (90). Binary logistic regression analysis, lasso regression, and support vector machine (SVM) were used to construct the diagnostic model. The optimal model was visualized by nomograms, and the discriminant ability of the nomogram was tested in the training and validation cohorts, respectively. Results: Among the three models, binary logistic regression has the most significant C statistic (0.87 and 0.88) in the training cohort and validation cohort, respectively. The variables that showed a significant difference in the multivariate logistic regression analysis were systolic blood pressure (SBP), total cholesterol (TC), albumin (ALB), free triiodothyronine (FT3), homocysteine (HCY), and age. The Hosmer-Lemeshow test P values of nomograms in the training and validation cohorts were 0.28 and 0.19, respectively, and the calibration curves were well corrected. Patients with nomogram scores below or above 168 were considered to have a low or high risk of ischemic stroke in MMD, respectively. Conclusion:Using nomograms to identify MMD and non-MMD ischemic stroke, the model has been validated to have a good discriminatory ability in both the training and validation cohorts, improving clinicians’ awareness of MMD ischemic stroke.