Erythrocytes: Member of the immune system that should not be ignored.

Erythrocytes are the most abundant type of cells in the blood and have a relatively simple structure when mature; they have a long life-span in the circulatory system. The primary function of erythrocytes is as oxygen carriers; however, they also play an important role in the immune system. Erythrocytes recognize and adhere to antigens and promote phagocytosis. The abnormal morphology and function of erythrocytes are also involved in the pathological processes of some diseases. Owing to the large number and immune properties of erythrocytes, their immune functions should not be ignored. Currently, research on immunity is focused on immune cells other than erythrocytes. However, research on the immune function of erythrocytes and the development of erythrocyte-mediated applications is of great significance. Therefore, we aimed to review the relevant literature and summarize the immune functions of erythrocytes.

Cbl-b restrains priming of pathogenic Th17 cells via the inhibition of IL-6 production by macrophages.

E3 ubiquitin ligase Cbl-b is involved in the maintenance of a balance between immunity and tolerance. Mice lacking Cbl-b are highly susceptible to experimental autoimmune encephalomyelitis (EAE), a Th17-mediated autoimmune disease. However, how Cbl-b regulates Th17 cell responses remains unclear. In this study, utilizing adoptive transfer and cell type-specific Cblb knockout strains, we show that Cbl-b expression in macrophages, but not T cells or dendritic cells (DCs), restrains the generation of pathogenic Th17 cells and the development of EAE. Cbl-b inhibits IL-6 production by macrophages that is induced by signaling from CARD9-dependent C-type lectin receptor (CLR) pathways, which directs T cells to generate pathogenic Th17 cells. Therefore, our data unveil a previously unappreciated function for Cbl-b in the regulation of pathogenic Th17 responses.

Factors affecting minimal manifestation status induction in myasthenia gravis.

Background: Minimal manifestation status (MMS) is an important landmark in the treatment of myasthenia gravis (MG), and predictors of MMS induction have rarely been identified in previous studies. Objective: The objective of this study is to evaluate the clinical factors associated with MMS induction among patients with MG. Design: This two-step retrospective cohort study with a single center investigated the factors that may be associated with MMS induction and retested these predictors in a test cohort. Methods: A total of 388 diagnosed MG patients who visited Xiangya Hospital between 1 July 2015 and 1 July 2019 were involved. We performed detailed chart reviews and recorded all cases achieving MMS. Demographics and clinical characteristics were also collected and their relationships to achieving MMS were investigated. Results: MMS was achieved in 124 patients (50.2%), and the median time to achieve MMS was 26 months. Several factors were found to be associated with MMS induction in exploring cohort, including muscle-specific tyrosine-protein kinase receptor (MuSK) antibody positivity (adjusted hazard ratio, HR = 4.333, 95% confidence interval, CI: 1.862-10.082), isolated ocular involvement (adjusted HR = 1.95, 95% CI: 1.284-2.961), and low baseline quantitative myasthenia gravis score (QMG score; adjusted HR = 2.022, 95% CI: 1.086-3.764). These factors were then retested in the test cohort. Isolated ocular involvement or low baseline QMG scores were factors found to be beneficial for MMS induction were confirmed. Conclusion: Isolated ocular involvement and low baseline QMG score are predictors of MMS induction in MG patients.

Single-cell RNA-Seq reveals transcriptional heterogeneity and immune subtypes associated with disease activity in human myasthenia gravis.

Myasthenia gravis (MG) is a rare autoimmune disease. Although the impact of immune cell disorder in MG has been extensively studied, little is known about the transcriptomes of individual cells. Here, we assessed the transcriptional profiles of 39,243 cells by single-cell sequencing and identified 13 major cell clusters, along with 39 subgroups of cells derived from patients with new-onset myasthenia gravis and healthy controls. We found that B cells, CD4+ T cells, and monocytes exhibited more heterogeneity in MG patients. CD4+ T cells were expanded in MG patients. We reclustered B cells and CD4+ T cells, and predict their essential regulators. Further analyses demonstrated that B cells in MG exhibited higher transcriptional activity towards plasma cell differentiation, CD4+ T cell subsets were unbalanced, and inflammatory pathways of monocytes were highly activated. Notably, we discovered a disease-relevant subgroup, CD180- B cells. Increased CD180- B cells in MG are indicative of a high IgG composition and were associated with disease activity and the anti-AChR antibody. Together, our data further the understanding of the cellular heterogeneity involved in the pathogenesis of MG and provide large cell-type-specific markers for subsequent research.

Evaluation of outcome measures for myasthenia gravis subgroups.

INTRODUCTION: Disease evaluation and long-term follow-up of myasthenia gravis (MG) patients rely on disease-specific measures. We evaluated four widely used MG-specific assessments, and compared the response to disease change in different MG subgroups. METHODS: We used the Cronbach's α coefficient to test reliability, Pearson correlation coefficients to test construct validity, as well as one-way ANOVA and independent-sample t-tests to access discriminant validity. Analyses of similar items between QMG and MG-ADL included paired-sample t-tests and mean score comparisons. Pearson correlation coefficients were used to describe the correlation between changes of QMG, MG-ADL, MG-QOL15r and MGC. The Wilcoxon matched-pairs signed-ranks test was performed to compare the outcomes. RESULTS: 872 MG patients were enrolled. QMG, MG-ADL, MG-QOL15r, and MGC all exhibited high reliability. All four scales displayed good discriminant validity according to the MGFA classification and MGC score. MG-ADL showed significant differences between patients grouped by age and gender, and MG-QOL15r showed significant differences between patients grouped by age. Analyses of similar items showed that MG-ADL achieved higher scores in bulbar items, whereas QMG produced higher scores in limb items. For patients in remission or minimal manifestation status, QMG exhibited significantly greater improvement than MG-QOL15r. In patients of MGFA I, II, III, and IV, QMG showed significantly greater improvement than MG-ADL. CONCLUSIONS: Patient-reported scale is an important supplement for a given period. MG-ADL has a better response to severe disease, and MG-QOL15r is more comprehensive for patients in remission or minimal manifestation status.

HECT E3 Ubiquitin Ligase Nedd4 Is Required for Antifungal Innate Immunity.

Candida albicans is the most common cause of fungal infections in humans, and disseminated candidiasis has become one of the leading causes of hospital-acquired bloodstream infections with a high mortality rate. However, little is known about the host-pathogen interactions and the mechanisms of antifungal immunity. Here, we report that Nedd4 (neuronal precursor cell-expressed developmentally downregulated 4) is essential for signaling through Dectin-1 and Dectin-2/3. We showed that mice that lack Nedd4 globally or only in the myeloid compartment are highly susceptible to systemic C. albicans infection, which correlates with heightened organ fungal burden, defective inflammatory response, impaired leukocyte recruitment to the kidneys, and defective reactive oxygen species expression by granulocytes. At the molecular level, Nedd4 -/- macrophages displayed impaired activation of TGF-ß-activating kinase-1 and NF-κB, but normal activation of spleen tyrosine kinase and protein kinase C-δ on C. albicans yeast and hyphal infections. These data suggest that Nedd4 regulates signaling events downstream of protein kinase C-δ but upstream of or at TGF-ß-activating kinase-1.

Sequential ubiquitination of NLRP3 by RNF125 and Cbl-b limits inflammasome activation and endotoxemia.

Aberrant NLRP3 inflammasome activation contributes to the development of endotoxemia. The importance of negative regulation of NLRP3 inflammasomes remains poorly understood. Here, we show that the E3 ubiquitin ligase Cbl-b is essential for preventing endotoxemia induced by a sub-lethal dose of LPS via a caspase-11/NLRP3-dependent manner. Further studies show that NLRP3 undergoes both K63- and K48-linked polyubiquitination. Cbl-b binds to the K63-ubiquitin chains attached to the NLRP3 leucine-rich repeat domain (LRR) via its ubiquitin-associated region (UBA) and then targets NLRP3 at K496 for K48-linked ubiquitination and proteasome-mediated degradation. We also identify RNF125 as an additional E3 ubiquitin ligase that initiates K63-linked ubiquitination of the NLRP3 LRR domain. Therefore, NLRP3 is sequentially ubiquitinated by K63- and K48-linked ubiquitination, thus keeping the NLRP3 inflammasomes in check and restraining endotoxemia.

Multiple genetic factors affecting the pharmacokinetic and pharmacodynamic processes of tacrolimus in Chinese myasthenia gravis patients.

PURPOSE: Tacrolimus is a novel effective immunosuppressant for myasthenia gravis (MG) patients. However, the narrow therapeutic window, and high inter- and intrapatient variation in bioavailability largely limited its clinical application. This article intended to find the SNPs influencing clinical outcome and discover the possible mechanisms. METHODS: Based on the tagSNPs genotyped by Improved Multiple Ligase Detection Reaction, Plink 1.07 was used to find the SNPs having close interaction to tacrolimus serum concentration, QMG score changes or even reasonable drug dose. Then we searched several databases to predict the possible miRNA binding rs15524 sequence. Based on the prediction, dual-luciferase reporter assay and miRNA transfection were used to discover the mechanism of how SNP rs15524 controls tacrolimus serum concentration through influencing CYP3A5 expression. RESULTS: In this article, we found multiple SNPs on CYP3A4, CYP3A5, FKBP1A, NFATC2 genes were predicted closely related to tacrolimus serum concentration, therapeutic effect which reflected by QMG score changes or even reasonable drug dose. After in silico miRNA selection, possible relationship between hsa-miR-500a and rs15524 was found. With the help of dual-luciferase reporter assay, wild-type rs15524 (T allele) was found having a stronger binding affinity for hsa-miR-500a. Higher expression of CYP3A5 may also led by lower hsa-miR-500a level. CONCLUSIONS: SNP rs15524 may control CYP3A5 expression by affecting the binding affinity between CYP3A5 3'UTR and hsa-miR-500a. Wild type (T allele) 3'UTR of CYP3A5 has stronger binding affinity to hsa-miR-500a and cause lower CYP3A5 expression and higher tacrolimus serum concentration.

The Application of Machine Learning Techniques in Clinical Drug Therapy.

INTRODUCTION: The development of a novel drug is an extremely complicated process that includes the target identification, design and manufacture, and proper therapy of the novel drug, as well as drug dose selection, drug efficacy evaluation, and adverse drug reaction control. Due to the limited resources, high costs, long duration, and low hit-to-lead ratio in the development of pharmacogenetics and computer technology, machine learning techniques have assisted novel drug development and have gradually received more attention by researchers. METHODS: According to current research, machine learning techniques are widely applied in the process of the discovery of new drugs and novel drug targets, the decision surrounding proper therapy and drug dose, and the prediction of drug efficacy and adverse drug reactions. RESULTS AND CONCLUSION: In this article, we discussed the history, workflow, and advantages and disadvantages of machine learning techniques in the processes mentioned above. Although the advantages of machine learning techniques are fairly obvious, the application of machine learning techniques is currently limited. With further research, the application of machine techniques in drug development could be much more widespread and could potentially be one of the major methods used in drug development.

SNPs affecting the clinical outcomes of regularly used immunosuppressants.

Recent studies have suggested that genomic diversity may play a key role in different clinical outcomes, and the importance of SNPs is becoming increasingly clear. In this article, we summarize the bioactivity of SNPs that may affect the sensitivity to or possibility of drug reactions that occur among the signaling pathways of regularly used immunosuppressants, such as glucocorticoids, azathioprine, tacrolimus, mycophenolate mofetil, cyclophosphamide and methotrexate. The development of bioinformatics, including machine learning models, has enabled prediction of the proper immunosuppressant dosage with minimal adverse drug reactions for patients after organ transplantation or for those with autoimmune diseases. This article provides a theoretical basis for the personalized use of immunosuppressants in the future.