Immunologic Research最新文献

Good syndrome (GS), a rare acquired immunodeficiency disorder characterized by thymoma and hypogammaglobulinemia, predisposes individuals to recurrent infections. This study reports a case of a 37-year-old male GS with multiple pulmonary infections and reviews relevant literature. The patient, with a history of thymoma resection, experienced multiple hospitalizations due to lung infections and neutropenia. The alveolar lavage fluid was detected by macro-genomic sequencing (NGS) to detect multiple pathogens, and targeted anti-infective and immunity-enhancing treatments led to improved symptoms and normal neutrophil counts. A literature review of 98 case reports from 2000 to 2023 was conducted, summarizing the associated diseases and pathogens in GS patients. Regular immunoglobulin monitoring in thymoma patients is essential for early GS diagnosis. When empirical antimicrobial therapy fails, mNGS for pathogen detection and targeted therapy are crucial, and regular IVIG injections can reduce infection rates in GS patients.

Hereditary angioedema (HAE) is a rare genetic disorder. The pattern of HAE is different in children as compared to adults. There is limited literature from developing countries where all first-line treatments are either unavailable or not easily accessible. Data of children with HAE were retrieved from medical records of patients registered in the Pediatric Immunodeficiency Clinic at our institute. Of the 206 patients with HAE, 61 were diagnosed before the age of 18 years. Male: female ratio was 1.1:1. Median age at onset of symptoms and diagnosis were 6.2 years (range 1-17 years) and 10.7 years (range 1.5-18 years) respectively. Median delay in diagnosis was 4.9 years (range 0-16 years). The commonest presentation was facial swelling (51/61) followed by swelling of extremities (47/61). Laryngeal edema and abdominal symptoms were reported in 28/61 and 31/61 patients respectively. Abdominal attacks were found to be less common in children as compared to adults. Most patients in our cohort received fresh-frozen plasma (n = 5/61) as on-demand therapy. Long-term prophylaxis included attenuated androgens (n = 25/61) and tranexamic acid (n = 23/61). Median duration of follow-up was 2242 patient months. One patient died on follow-up in this cohort. This is the largest single-centre cohort of pediatric HAE from resource-constrained settings. Facial attacks were more common, and there were significant delays in diagnosis when the age of onset of symptoms was younger. Gastrointestinal symptoms were less common in children than adults. HIGHLIGHTS: One of the largest single-centre cohorts of pediatric HAE and the only one from resource-constrained settings. There were significant delays in diagnosis when the age of onset of symptoms was younger. Abdominal attacks were found to be less common in children as compared to adults.

Lung adenocarcinoma (LUAD) is a malignancy affecting the respiratory system. Most patients are diagnosed with advanced or metastatic lung cancer due to the fact that most of their clinical symptoms are insidious, resulting in a bleak prognosis. Given that abnormal reprogramming of asparagine metabolism (AM) has emerged as an emerging therapeutic target for anti-tumor therapy. However, the clinical significance of abnormal reprogramming of AM in LUAD patients is unclear. In this study, we collected 864 asparagine metabolism-related genes (AMGs) and used a machine-learning computational framework to develop an asparagine metabolism immunity index (AMII) for LUAD patients. Through the utilization of median AMII scores, LUAD patients were segregated into either a low-AMII group or a high-AMII group. We observed outstanding performance of AMII in predicting survival prognosis in LUAD patients in the TCGA-LUAD cohort and in three externally independently validated GEO cohorts (GSE72094, GSE37745, and GSE30219), and poorer prognosis for LUAD patients in the high-AMII group. The results of univariate and multivariate analyses showed that AMII can be used as an independent risk factor for LUAD patients. In addition, the results of C-index analysis and decision analysis showed that AMII-based nomograms had a robust performance in terms of accuracy of prognostic prediction and net clinical benefit in patients with LUAD. Excitingly, LUAD patients in the low-AMII group were more sensitive to commonly used chemotherapeutic drugs. Consequently, AMII is expected to be a novel diagnostic tool for clinical classification, providing valuable insights for clinical decision-making and personalized management of LUAD patients.

Background: Pomalidomide, a third-generation oral immunomodulatory drug, exhibits efficacy in patients with relapsed multiple myeloma or those refractory to bortezomib and lenalidomide (RRMM).

Methods: In this clinical context, we employed flow cytometry and CDR3 spectratyping to monitor the dynamics of the T-cell repertoire during Pomalidomide treatment, aiming to investigate its potential to reverse the immunological abnormalities characteristic of RRMM.

Results: By flow cytometry at baseline we found a significant decrease in CD4 + frequency in MM patients, while CD8 + frequency were significantly higher in patients when compared to controls. Most T cell populations remained stable across all time points, except for CD4 + frequency, which notably decreased from t1 to subsequent assessments. Our investigation revealed as most relevant finding the notable increase in CD4 + expansions and the growing prevalence of patients manifesting these expansions. This pattern is even more evident in patients receiving their treatment until t3 and therefore still responding to treatment with Pomalidomide. We also conducted a comparison of spectratyping data before and after treatment, substantially demonstrating a relatively stable pattern throughout the course of Pomalidomide treatment.

Conclusions: These observations imply that Pomalidomide treatment influences the T-cell repertoire, particularly in the CD4 + subpopulation during the later stages of treatment, raising speculation about the potential involvement of these lymphocyte expansions in mechanisms related to antitumor immunity.

Sorting nexin 10 (SNX10) expression induces intestinal barrier dysfunction and inflammatory responses; in contrast, its inhibition promotes intestinal mucosal healing through sterol regulatory element-binding protein 2 (SREBP2)-mediated cholesterol synthesis. However, its regulatory mechanism for the pathogenesis of inflammatory bowel disease (IBD) remains unclear. In this study, we examined SNX10 and SREBP2 expression in ulcerative colitis (UC) and Crohn's disease (CD). A total of 30 and 28 patients with UC and CD, respectively, were recruited. The expression of SNX10 and SREBP2 in the colonic mucosa was measured by immunohistochemistry (IHC). We discovered that patients with CD had significantly higher expression levels of SNX10 and SREBP2 than patients with UC and healthy controls. In addition, the expression of SREBP2 in patients with UC was significantly higher than that in healthy controls. In our study, we indicated that SNX10 and SREBP2 may serve as biomarkers for identifying patients with UC and CD, thereby providing a clinical therapeutic strategy for the treatment of IBD by inhibiting SNX10.

LGALS9, also known as Galectin-9 and a member of the β-galactosidase family, plays a crucial role in immune regulation. However, its expression and function in CD8 T cells, as well as its association with cytotoxic T lymphocytes (CTL), remain unclear. This study aims to investigate LGALS9 expression patterns in human circulating CD8 T lymphocytes and elucidate its clinical significance in Systemic Lupus Erythematosus (SLE). Blood samples from 56 healthy controls and 50 new-onset SLE patients were collected. Flow cytometry was utilized to analyze LGALS9 expression in circulating CD8 T lymphocytes via intracellular staining. Compared to LGALS9 + CD8 + T cells, LGALS9-CD8 + T cells showed increased secretion of Granzyme B (GZMB) and Perforin, along with elevated expression levels of GPR56, CX3CR1, KLRD1, KLRF1, PD1, and CD29. A higher proportion of Tn (naive T cells) and TCM (central memory T cells) showed LGALS9 positivity, compared to TEM (effector memory T cells) and TEMRA (terminally differentiated effector memory T cells re-expressing CD45RA). Clinically, the downregulation of LGALS9 expression was significant in SLE patients. LGALS9 + CD8 + T cells exhibited an Area Under the Curve (AUC) of 0.6916, while CX3CR1 + in LGALS9 + CD8 + T cells had an AUC of 0.6478, and KLRF1 + had an AUC of 0.6419, for distinguishing SLE from healthy individuals. In conclusion, CD8 + LGALS9 + T cells display characteristics of low cytotoxicity, and their reduction is evident in SLE patients, potentially implicating them in SLE pathogenesis and providing diagnostic assistance.

The cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling pathway has been identified as a significant modulator of inflammation in various clinical contexts, including infection, cellular stress, and tissue injury. The extensive participation of the cGAS-STING pathway can be attributed to its ability to detect and control the cellular reaction to DNAs originating from both microorganisms and hosts. These DNAs are well recognized as molecules linked with potential risks. At physiological levels, the STING signaling system exhibits protective effects. However, prolonged stimulation of this pathway contributes to autoimmune disorder pathogenesis. The present paper provides an overview of the activation mechanism of the cGAS-STING signaling pathways and their associated significant functions, as well as therapeutic interventions in the context of systemic lupus erythematosus (SLE). The primary objective is to enhance our comprehension of SLE and facilitate more effective diagnosis and treatment strategies for this condition.

Persistent activation of polymorphonuclear neutrophils (PMNs) plays a crucial role in the development of sepsis-related acute lung injury (ALI). This study investigated key molecular mechanisms involved in the hyperactivation of PMNs during ALI. A mouse model of sepsis-related ALI was generated by lipopolysaccharide (LPS) injection. RNA sequencing identified myosin light chain kinase (MLCK) as the most significant differentially expressed gene (DEG) between PMNs isolated from model and control mice. Myocardin (MYOCD) and serum response factor (SRF) were two of the DEGs that could promote transcription of MLCK by binding to its promoter. Either knockdown of MLCK, MYOCD, or SRF ameliorated dysfunction and edema in the lungs of LPS-treated mice. Kyoto Encyclopedia of Genes and Genomes enrichment analysis suggested that the DEGs are enriched in a ferroptosis-related signaling pathway. The MLCK, MYOCD, or SRF knockdown increased contents of ROS, MDA, ferritin, and ferrous iron, and reduced levels of GSH and GPX4 in the PMNs. However, the MLCK overexpression restored ferroptosis resistance and activity of the PMNs, resulting in increased lung injury. Collectively, this study demonstrates that MYOCD and SRF-mediated MLCK upregulation is correlated with ferroptosis resistance and hyperactivation of PMNs in sepsis-related ALI.

It is known that 1,7-dihydroxy-3,4-dimethoxyxanthone (XAN), derived from Securidaca inappendiculata Hassk., exhibits anti-inflammatory and analgesic activities and inhibits M1 polarization of macrophages. However, its ability to alleviate inflammation induced by pro-inflammatory cytokines in THP-1 cells and its anti-inflammatory mechanisms remain unclear. THP-1 cells were treated with phorbol 12-myristate-13-acetate to differentiate and divided into three groups. They were stimulated with lipopolysaccharide (LPS) and interferon-γ (IFN-γ). The toxicity of XAN was assessed using Cell Counting Kit-8, and the expression of various genes and proteins was analyzed using real-time quantitative polymerase chain reaction, flow cytometry, and western blotting. Transmission electron microscopy was used to observe changes in mitochondrial structure. XAN at concentrations ≤ 10 µg/mL did not affect THP-1 cell viability and reduced the mRNA expression of pro-inflammatory factors, including interleukin (IL)-1β, inducible nitric oxide synthase (iNOS), NOD-like receptor thermal protein domain protein 3 (NLRP3), and tumor necrosis factor-α (TNF-α). XAN also increased the levels of anti-inflammatory factors, including chemokine ligand 22, mannose receptor (CD206), IL-10, peroxisome proliferator-activated receptor-γ, and transglutaminase 2. Additionally, XAN downregulated the expression of inflammation-related proteins iNOS, NLRP3, and IL-1β; significantly increased the expression of arginase 1, ornithine decarboxylase, and arginine metabolism-related proteins and genes; inhibited mitochondrial damage; and reduced reactive oxygen species (ROS) generation. XAN enhanced the arginine metabolism pathway, prevented mitochondrial damage, reduced ROS levels, and provided an effective defensive response against LPS/IFN-γ-induced inflammation.

Artificial intelligence (AI) is increasingly being used in medicine to enhance the speed and accuracy of disease diagnosis and treatment. AI-based image analysis is expected to play a crucial role in future healthcare facilities and laboratories, offering improved precision and cost-effectiveness. As technology advances, the requirement for specialized software knowledge to utilize AI applications is diminishing. Our study will examine the advantages and challenges of employing AI-based image analysis in the field of immunology and will investigate whether physicians without software expertise can use MS Azure Portal for ANA IIF test classification and image analysis. This is the first study to perform Hep-2 image analysis using MS Azure Portal. We will also assess the potential for AI applications to aid physicians in interpreting ANA IIF results in immunology laboratories. The study was designed in four stages by two specialists. Stage 1: creation of an image library, Stage 2: finding an artificial intelligence application, Stage 3: uploading images and training artificial intelligence, Stage 4: performance analysis of the artificial intelligence application. In the first training, the average pattern identification accuracy for 72 testing images was 81.94%. After the second training, this accuracy increased to 87.5%. Patterns Precision improved from 71.42 to 79.96% after the second training. As a result, the number of correctly identified patterns and their accuracy increased with the second training process. Artificial intelligence-based image analysis shows promising potential. This technology is expected to become essential in healthcare facility laboratories, offering higher accuracy rates and lower costs.