Systemic lupus erythematosus (SLE) is an autoimmune disease of unknown etiology, primarily characterized by systemic inflammation and hyperactivation of both B and T lymphocytes. Key immunological features include increased consumption of complement components, sustained overproduction of type I interferons (IFN-I), and persistent production of a broad spectrum of autoantibodies, such as anti-dsDNA antibodies. However, the use of autoantibodies as biomarkers for the early detection of SLE is associated with a high false-positive rate, suggesting that antibody characteristics evolve during disease progression.N-glycosylation is a critical post-translational modification of antibodies that significantly influences their structure and receptor-binding properties, thereby modulating biological activities and functions. In particular, glycosylation patterns affect the antibody’s affinity for Fc gamma receptors (FcγRs), subsequently regulating various antibody-mediated immune responses. Numerous studies have investigated the impact of individual monosaccharides—such as sialic acid, fucose, and N-acetylglucosamine, which constitute N-glycans—on the immunological functions of antibodies. This review systematically summarizes the aberrant immunoglobulin G (IgG) N-glycosylation patterns observed in SLE patients, with a focus on correlations between disease progression or complications and quantitative alterations in individual glycan components. We first review how different types of N-glycosylation modifications affect the biological activity and functional properties of IgG, particularly regarding the effects of specific monosaccharides—such as sialic acid, fucose, and galactose—on FcγR binding affinity and the resulting downstream immune functions. We then summarize the differential expression of IgGN-glycans and glycosyltransferase genes between SLE patients and healthy controls, and outline the associations between glycosylation changes and SLE-related pathological responses. In response to the inconsistencies and limitations in current research, we propose potential explanations from the perspectives of study methodologies, participant characteristics, and variations in N-glycan structures, aiming to provide a constructive reference for future studies. Given the close relationship between antibody glycosylation and SLE, this review highlights the potential of IgG N-glycosylation patterns as promising biomarkers for early diagnosis and disease monitoring. In terms of therapy, we discuss how IgG glycosylation can enhance the efficacy of intravenous immunoglobulin (IVIg) treatment and introduce emerging therapeutic strategies that aim to modulate endogenous IgG N-glycans as a novel glycan-based approach for SLE management. In summary, N-glycans are essential structural components of antibodies that regulate immune responses by modulating antibody-receptor interactions. Aberrant glycosylation is closely associated with the pathogenesis of autoimmune diseases, including SLE. However, due to the structural diversity of N-glycans and the complexity of glycosylation processes, the precise roles of IgGN-glycosylation in SLE pathophysiology remain incompletely understood. Moreover, therapeutic strategies targeting IgG glycosylation are still in early development and have not yet reached clinical application. Continued progress in glycan analysis technologies and other biological tools, along with interdisciplinary collaboration, will be essential for advancing this field.

OBJECTIVE: To determine the role of Tripterygium wilfordii multiglycoside (TGW) in the treatment of psoriatic dermatitis from a cellular immunological perspective. METHODS: Mouse models of psoriatic dermatitis were established by imiquimod (IMQ). Twelve male BALB/c mice were assigned to IMQ or IMQ₊TGW groups according to a random number table. Histopathological changes in vivo were assessed by hematoxylin and eosin staining. Ratios of immune cells and cytokines in mice, as well as PAM212 cell proliferation in vitro were assessed by flow cytometry. Pro-inflammatory cytokine expression was determined using reverse transcription quantitative polymerase chain reaction. RESULTS: TGW significantly ameliorated the severity of IMQ-induced psoriasis-like mouse skin lesions and restrained the activation of CD45⁺ cells, neutrophils and T lymphocytes (all P<0.01). Moreover, TGW significantly attenuated keratinocytes (KCs) proliferation and downregulated the mRNA levels of inflammatory cytokines including interleukin (IL)-17A, IL-23, tumor necrosis factor α, and chemokine (C-X-C motif) ligand 1 (P<0.01 or P<0.05). Furthermore, it reduced the number of γ δ T17 cells in skin lesion of mice and draining lymph nodes (P<0.01). CONCLUSIONS TGW improved psoriasis-like inflammation by inhibiting KCs proliferation, as well as the associated immune cells and cytokine expression. It inhibited IL-17 secretion from γ δ T cells, which improved the immune-inflammatory microenvironment of psoriasis.
Male ; Animals ; Mice ; Tripterygium ; Psoriasis/drug therapy* ; Keratinocytes ; Skin Diseases/metabolism* ; Cytokines/metabolism* ; Imiquimod/metabolism* ; Dermatitis/pathology* ; Disease Models, Animal ; Mice, Inbred BALB C ; Skin/metabolism*

Objective To evaluate the characteristics of different antigen-specific T cell immune responses to severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)after inoculation with 2 doses of SARS-CoV-2 inactivated vaccine for 12 months.Methods Fifteen healthy adults were enrolled in this study and blood samples collected at 12 months after receiving two doses of SARS-CoV-2 inactivated vaccine.The level and phenotypic characteristics of SARS-CoV-2 antigen-specific T lymphocytes were detected by activation-induced markers(AIM)based on polychromatic flow cytometry.Results After 12 months of inoculation with 2 doses of SARS-CoV-2 inactivated vaccine,more than 90%of adults had detectable Spike and Non-spike antigen-specific CD4+ T cells immune responses(Spike:14/15,P=0.0001;Non-spike:15/15,P<0.0001).80%of adults had detectable Spike and Non-spike antigen-specific CD8+ T cells immune responses(Spike:12/15,P=0.0463;Non-spike:12/15,P=0.0806).Antigen-specific CD4+ T cells induced by SARS-CoV-2 inactivated vaccination after 12 months were composed of predominantly central memory(CM)and effector memory 1(EM1)cells.On the other hand,in terms of helper subsets,antigen-specific CD4+ T cells mainly showed T helper 1/17(Th1/17)and T helper 2(Th2)phenotypes.Conclusions SARS-CoV-2 inactivated vaccination generates durable and extensive antigen-specific CD4+ T cell memory responses,which may be the key factor for the low proportion of severe coronavirus disease 2019(COVID-19)infection in China.

Objective To investigate the role of bone marrow mesenchymal stem cells derived from diabetic mice and their paracrine roles in inducing insulin resistance(IR).Methods The mouse model of diabetes mellitus was established,bone marrow mesenchymal stem cells(BMSC)were extracted and cultured,and the culture supernatant(M-BMSC-CS)was collected.(1)Cell experiment:HepG2 hepatocytes were divided into normal low-glycemic culture group[cultured with low-glycemic DMEM(5.55 mmol·L-1)],M-BMSC-CS experimental group(M-BMSC-CS 75 μL),and high-glycemic and high-lipid control group(given 25 mmol·L-1 high-glycemic DMEM+0.25 mmol·L-1 palmitic acid);(2)Animal experiments:Mice were divided into normal mice group(0.9％NaCl by intraperitoneal injection)and M-BMSC-CS-m group(M-BMSC-CS by intraperitoneal injection of normal mice(injection dose 0.2 mL/10 g)].Glucose intake was measured by glucose oxidase method.The fluorescence intensity of Glut2 protein was detected by immunofluorescence.The expression of insulin signaling pathway protein was detected by Western blot.Test oral glucose tolerance(OGTT)and insulin tolerance(ITT).Results The glucose intakes of the normal low-glucose culture group,the M-BMSC-CS experimental group and the high-glucose and high-lipid control group were(2.96±0.05),(1.64±0.28)and(1.42±0.32)mmol·L-1,respectively;the fluorescence expressions of glucose transporter 2(Glut2)were 53.21±2.70,30.95±3.39 and 34.96±7.60,respectively;the protein expression levels of phosphorylated insulin receptor substrate 1-ser307(p-IRS-1ser307)were 0.46±0.21,1.09±0.24 and 0.91±0.16,respectively;phosphorylated protein kinase(p-AKT)protein expression levels were 0.94±0.05,0.59±0.06 and 0.53±0.05;Glut2 protein expression levels were 1.08±0.14,0.58±0.14 and 0.62±0.09,respectively.The above indexes in M-BMSC-CS experimental group were statistically significant compared with those in normal low-glycemic culture group(all P＜0.05).Fasting blood glucose levels in the normal group and M-BMSC-CS-m group were(5.23±0.57)and(9.30±1.14)mmol·L-1;p-AKT protein expression level were 1.27±0.21 and 0.51±0.19;Glut2 protein expression level were 1.17±0.17 and 0.79±0.09,respectively.The above indexes in M-BMSC-CS-m group were significantly different from those in normal mouse group(P＜0.05).Conclusion BMSC culture supernatant from diabetic mice induced insulin resistance of normal HepG2 hepatocytes in vitro and normal mice in vivo.

Objective Studies on the relationship between iodine,vitamin A(VA),and vitamin D(VD)and thyroid function are limited.This study aimed to analyze iodine and thyroid-stimulating hormone(TSH)status and their possible relationships with VA,VD,and other factors in postpartum women. Methods A total of 1,311 mothers(896 lactating and 415 non-lactating)from Hebei,Zhejiang,and Guangxi provinces were included in this study.The urinary iodine concentration(UIC),TSH,VA,and VD were measured. Results The median UIC of total and lactating participants were 142.00 μg/L and 139.95 μg/L,respectively.The median TSH,VA,and VD levels in all the participants were 1.89 mIU/L,0.44 μg/mL,and 24.04 ng/mL,respectively.No differences in the UIC were found between lactating and non-lactating mothers.UIC and TSH levels were significantly different among the three provinces.The rural UIC was higher than the urban UIC.Obese mothers had a higher UIC and a higher prevalence of excessive TSH.Higher UICs and TSHs levels were observed in both the VD deficiency and insufficiency groups than in the VD-sufficient group.After adjustment,no linear correlation was observed between UIC and VA/VD.No interaction was found between vitamins A/D and UIC on TSH levels. Conclusion The mothers in the present study had no iodine deficiency.Region,area type,BMI,and VD may be related to the iodine status or TSH levels.

Objective To describe the outcomes of extracorporeal membrane oxygenation (ECMO) for patients after aortic surgery and to summarize the experience. Methods The clinical data of patients who received ECMO support after aortic surgery in Fuwai Hospital from 2009 to 2020 were retrospectively analyzed. The patients who received an aortic dissection surgery were allocated into a dissection group, and the other patients were allocated into a non-dissection group. The in-hospital and follow-up survival rates were compared between the two groups, and the causes of death were analyzed. Results A total of 22 patients were enrolled, including 17 patients in the dissection group [13 males and 4 females, with a median age of 54 (46, 61) years] and 5 patients in the non-dissection group [3 males and 2 females, with a median age of 51 (41, 65) years]. There was no statistical difference in the age and gender between the two groups (P>0.05). The in-hospital survival rate (11.8% vs. 100.0%, P=0.001) and follow-up survival rate (11.8% vs. 80.0%, P=0.009) of the patients in the dissection group were significantly lower than those in the non-dissection group. The causes of death in the dissection group included massive bleeding and disseminated intravascular coagulation (3 patients), ventricular thrombosis (1 patient), irreversible brain injury (2 patients), visceral malperfusion syndrome (4 patients) and irreversible heart failure (5 patients). Conclusion ECMO after aortic dissection surgery is associated with high mortality, which is related to the pathological features of aortic dissection and severely disrupted coagulation system after the surgery. For these patients, strict indication selection and optimal management strategy are important.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.