American journal of clinical and experimental immunology最新文献

Background: Whole-body vibration (WBV) is a commonly used physical exercise for disease prevention and rehabilitation. Recent studies indicated the beneficial mechanism of WBV may be associated with its anti-inflammatory potential, however, its regulatory roles on different inflammatory mediators remained controversial. The aim of this study was to perform a meta-analysis to re-confirm the effects of WBV exercise on various inflammatory factors.

Methods: The PubMed, EMBASE and Cochrane Library databases were searched up to September 2023 to collect all articles comparing WBV with control (or post-pre trials). The effect size was expressed as the standardized mean difference (SMD) and 95% confidence intervals (CI).

Results: A total of 31 eligible studies were included, including 14 pre-clinical and 17 clinical studies. The meta-analysis of pre-clinical studies showed that compared with the control group, WBV exercise could significantly reduce the level of IL-6 (SMD: -1.03, 95% CI: -1.93, -0.13), TNF-α (SMD: -1.36, 95% CI: -2.54, -0.17) (for disease subgroup), IL-1β (SMD: -2.20, 95% CI: -3.24, -1.15), IFN-γ (SMD: -1.91, 95% CI: -2.71, -1.12), IL-4 (SMD: -0.71, 95% CI: -1.39, -0.03) and IL-17 (SMD: -1.32, 95% CI: -2.05, -0.59) overall. Pooling of clinical studies revealed WBV exercise significantly reduced the level of TNF-α (WBV vs control: SMD: -1.11, 95% CI: -2.16, -0.06; post vs pre: SMD: -1.29, 95% CI: -1.91, -0.67), CRP (SMD: -3.59, 95% CI: -6.36, -0.82, P = 0.011) and enhanced the level of IL-10 (WBV vs control: SMD: 2.90, 95% CI: 1.10, 4.71; post vs pre: SMD: 1.75, 95% CI: 0.64, 2.87) and IL-6 (SMD: 0.91, 95% CI: 0.31, 1.52) (healthy subgroup).

Conclusion: WBV may be an effective prevention and rehabilitation tool for inflammatory diseases.

Background: Coronavirus disease 2019 (COVID-19) affects different organ systems, including the skin. A retrospective analysis of skin manifestations in Chinese outpatient and inpatient settings is lacking. The study aims to analyze cutaneous manifestations in COVID-19 patients and the recurrence or aggravation of previous skin diseases.

Materials and methods: A retrospective cross-sectional study was conducted from November 2022 to July 2023 in a university hospital in eastern China. It involved reverse transcriptase polymerase chain reaction (RT-PCR)-positive COVID-19 patients, documenting various skin manifestations and the recurrence or aggravation of pre-existing skin conditions. The pattern of skin lesions and other variables were assessed.

Results: The study included 303 patients, with 127 males and 176 females. Maculopapular rash was the predominant new cutaneous manifestation (54.92%), mainly in middle-aged individuals. Other findings included urticaria (16.39%), herpes zoster (11.89%), and herpes simplex (4.10%), vesicular rashes (2.46%), purpura (2.05%), erythema multiforme (1.64%), livedo reticularis (0.41%) and so on. Severe disease was associated with herpes zoster and livedo reticularis. Critical COVID-19 cases were linked to vesicular rashes, purpura, and erythema multiforme. The mean time for skin lesion emergence post-infection varied from 3 days for seborrheic dermatitis to 17.48 days for herpes zoster. Vasculitic manifestations correlated with elevated D-dimer levels. A total of 59 cases (19.47%) of recurrent or aggravated skin diseases were reported following infection with COVID-19, with dermatitis being the most common, followed by acne and folliculitis, psoriasis, urticaria, bullous pemphigoid, pemphigus, tinea corporis and androgenetic alopecia.

Conclusion: The cutaneous phenotypes delineated in this study expand the dermatologic spectrum associated with COVID-19. Cutaneous manifestations may result from overactive immune responses, complement activation, and microvascular damage. Herpes zoster typically occurs in elderly COVID-19 patients with weaker immune systems or more severe diseases. Purpura and livedo reticularis, although rare, may indicate disease severity. It is possible to predict the course of COVID-19 with different severity through cutaneous manifestations. Recognizing these skin manifestations could aid in predicting COVID-19 severity and guide dermatologists in managing the pandemic response.

To explore the characteristics of hematologic indicators and related risk factors of lower extremity deep vein thrombosis (LDVT) in patients with cerebral infarction.

Methods: This study retrospectively analyzed data from 174 patients with cerebral infarction admitted to The Rehabilitation Department of Shanghai Fifth Rehabilitation Hospital and Shanghai First People's Hospital from June 2022 to June 2023. Based on the results of lower limb venous color Doppler ultrasound examinations, patients were divided into two groups: the LDVT group (35 cases) and the non-LDVT group (139 cases). We compared the clinical data and hematologic indicators (D-dimer value, fibrinogen, white blood cells, platelets, uric acid, creatinine, etc.) of the two groups to identify the risk factors of cerebral infarction complicated with LDVT.

Results: Statistical analysis revealed that the D-dimer values of the LDVT group were significantly (P<0.05) higher than those of the non-LDVT group. The uric acid value of the LDVT group was significantly lower than that of the non-LDVT group, with statistical significance (P<0.05). The Brunnstrom staging in the LDVT group was significantly different from that in the non-LDVT group (P<0.05). Meanwhile, binary logistic regression analysis showed that LDVT complicated with cerebral infarction was associated with D-dimer level [OR=1.302, 95% CI (1.077, 1.575)], uric acid level [OR=0.995, 95% CI (0.990, 1.000)], and Brunnstrom staging [OR=3.005, 95% CI (1.312, 6.880)].

Conclusion: D-dimer value, uric acid value, and Brunnstrom stage I to II are closely related to the occurrence of LDVT in patients with cerebral infarction. High D-dimer value, low uric acid value, and Brunnstrom stage I to II are independent risk factors for LDVT in cerebral infarction. Early assessment of D-dimer value, uric acid value, and Brunnstrom stage of cerebral infarction should be considered in clinical practice.

Background: Leucine rich pentatricopeptide repeat containing (LRPPRC) protein is a multifunctional protein involved in cell cycle progression and tumor development. However, its prognostic significance and association with immune infiltration in Liver hepatocellular carcinoma (LIHC) remain unclear.

Methods: We utilized transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) databases of LIHC patients to investigate the potential pro-cancer role of LRPPRC, including differential expression of LRPPRC in LIHC, prognostic value, clinicopathological features, immune cell infiltration relevance and function enrichment analysis.

Results: Our findings suggest that LRPPRC is upregulated in LIHC and exhibits correlations with survival, clinical stage, and tumor grade in LIHC patients. Additionally, immune infiltration analysis revealed significant negative correlations between LRPPRC expression and multiple tumor-infiltrating immune cells, including CTLs, DCs, pDCs, B cells, Th17 cells, neutrophils, T cells, Mast cells, Th1 cells, Tregs, and NK cells, whereas a significant positive correlation was observed with infiltration of Th2 cells, T helper cells and Tcms. Furthermore, functional enrichment analysis indicated that LRPPRC may be involved in G2m checkpoint, mitotic spindle, E2f targets, Wnt Beta catenin signaling, spermatogenesis and other processes.

Single-cell sequencing is an emerging technology that can effectively identify cell types in tumors. In the tumor microenvironment of bladder cancer, macrophages play a crucial role in invasion and immune escape. This study aimed to assess the expression of macrophage-related genes (MRGs) in the tumor microenvironment of bladder cancer patients and construct a prognostic model based on MRGs using bioinformatics methods.

Methods: Single-cell sequencing data from bladder cancer patients was downloaded from the GEO. After quality control and cell type identification, macrophages in the samples were extracted for re-clustering. Feature genes were then identified, and MRGs were assessed. Genetic data from TCGA database bladder cancer patients was also downloaded and organized. The intersection of MRGs and the TCGA gene set was determined. Clinical information was connected with this intersection, and the data was divided into training and validation sets. The training set was used for model construction and the validation set for model verification. A prognostic model based on MRGs was built using the LASSO algorithm and Cox regression. Patients were divided into high-risk and low-risk groups based on their prognostic features, and survival information in the training and validation sets was observed. The predictive ability of the model was assessed using a ROC curve, followed by a calibration plot to predict 1-, 3-, and 5-year survival rates.

Results: Four cell types were identified, and after extracting macrophages, three cell subgroups were clustered, resulting in 1,078 feature genes. The top 100 feature genes from each macrophage subgroup were extracted and intersected with TCGA expressed genes to construct the model. A risk prediction model composed of CD74, METRN, PTPRR, and CDC42EP5 was obtained. The survival and ROC curves showed that this model had good predictive ability. A calibration curve also demonstrated good prognostic ability for patients.

Conclusion: This study, based on single-cell data, TCGA data, and clinical information, constructed an MRG-based prognostic model for bladder cancer using multi-omics methods. This model has good accuracy and reliability in predicting the survival and prognosis of patients with bladder cancer, providing a reference for understanding the interaction between MRGs and bladder cancer.

Around 80 to 85% of all lung cancers are non-small cell lung cancer (NSCLC). Previous research has aimed at exploring the genetic basis of NSCLC through individual approaches, but studies have yet to investigate the results of combining them. Here we show that analyzing NSCLC genetics through three approaches simultaneously creates unique insights into our understanding of the disease. Through a combination of previous research and bioinformatics tools, we determined 35 NSCLC candidate genes. We analyzed these genes in 3 different approaches. First, we found the gene fusions between these candidate genes. Second, we found the common superfamilies between genes. Finally, we identified mutational signatures that are possibly associated with NSCLC. Each approach has its individual, unique results. Fusion relationships identify specific gene fusion targets, common superfamilies identify possible avenues to determine novel target genes, and identifying NSCLC associated mutational signatures has diagnostic and prognostic benefits. Combining the approaches, we found that gene CD74 has significant fusion relationships, but it has no association with the other two approaches, suggesting that CD74 is associated with NSCLC mainly because of its fusion relationships. Targeting the gene fusions of CD74 may be an alternative NSCLC treatment. This genetic analysis has indeed created unique insight into NSCLC genes. Both the results from each of the approaches separately and combined allow pursuit of more effective treatment strategies for this cancer. The methodology presented can also apply to other cancers, creating insights that current analytical methods could not find.

Background: CD4⁺ T cell responses in HCV infection have a crucial role in the immunopathology of hepatitis C virus (HCV) infection. Our aim was to investigate the frequency of Th1, Th17, and Th22 cells in HCV-infected patients and elucidate their role in the progression of the disease.

Methods: Twenty-six HCV-infected patients and 26 healthy individuals were recruited. Peripheral blood mononuclear cells (PBMCs) were stained to separate CD4, IFN-γ, IL-17, and IL-22 producing cells using flow cytometry.

Results: Results showed that the mean expression of IL-22 in CD4⁺ T cells was significantly lower in HCV-infected patients compared to healthy controls. About correlation with clinical factor and T subsets, a negative correlation between the frequency of CD4⁺ IFN-γ⁺ cells and Thyroxine level (T4) was observed in the patients. The data showed a positive link between thyroid-stimulating hormone (TSH), cholesterol levels, and the frequency of Th17 cells. In addition, a positive correlation was seen between serum creatinine level with both Th1 and Th17. Ultimately, it was found that there was a positive link between viral burden and IL-17⁺ IL-22⁺ cells and a negative correlation between viral load and pure Th22.

Conclusions: Our findings indicate that Th22 cells may play a part in the immunopathology of HCV and show the associations between Thelper subsets and the clinical signs of the disease.

NAA40 belongs to the N-terminal acetyltransferase (NATs) family, responsible for protein N-terminal modification, and it exerts crucial roles across various cancers. However, its impact on patient prognosis and immune infiltration in hepatocellular carcinoma (HCC) remains elusive. To address this, our study delved into the comprehensive analysis of NAA40 in the context of cancer. Our pan-cancer analysis unveiled elevated NAA40 expression in multiple tumor types, including BLCA, BRCA, CHOL, COAD, ESCA, HNSC, LIHC, LUAD, LUSC, STAD, and THCA. Additionally, through a comprehensive examination across various cancer types within TCGA, we discovered that high NAA40 gene expression correlated with poor prognosis in HCC, pointing toward its role in promoting oncogenesis. Further investigation illuminated the association of increased NAA40 expression with T stage, pathologic stage, tumor status, and histologic grade. Interestingly, we noted a significant inverse correlation between NAA40 expression and the infiltration levels of immune cells, such as DC cells, neutrophils, NK cells, and T cells, in liver cancer. This observation underpins the hypothesis that NAA40 influences HCC development by modulating immune cell infiltration. Functional enrichment analysis provided valuable insights into the pathways influenced by NAA40. Enriched pathways encompassed oxidative phosphorylation, xenobiotic metabolism, bile acid metabolism, fatty acid metabolism, G2M checkpoint, and E2F targets. These findings collectively position NAA40 as a potential biomarker for prognostic prediction and monitoring the effects of immunotherapy in HCC.

Background: Glycosyltransferases (GT) play a crucial role in glycosylation reactions, and aberrant expression of glycosyltransferase-related genes (GTs) leads to abnormal glycosylation, which is associated with tumor progression. However, the prognostic value of aberrant expression of GTs in ovarian cancer (OC) and the correlation between GTs and tumor microenvironment (TME) remain unknown.

Methods: TCGA and GSE53963 databases were used to obtain data on OC patient samples. The association of GTs with OC was analyzed. Molecular subtypes were identified by consensus unsupervised clustering, followed by immune infiltration and functional enrichment analyses. Survival analysis was performed using Kaplan-Meier curves and log-rank tests. Least Absolute Shrinkage and Selection Operator (LASSO) and multifactorial cox regression were used to screen for signature genes associated with OC and used to establish prognostic models.

Result: OC patients were categorized into 5 GTs clusters using consensus unsupervised cluster analysis. Clusters D and E showed significant differences between survival, signaling pathways and immune infiltration. Then, a risk model was developed based on the 12 signature genes, which provides a more accurate evaluation of the prognosis of OC patients. We categorized patients into high-risk and low-risk groups based on the risk score and found that the survival of patients in the high-risk group was significantly lower than that in the low-risk group. Moreover, the risk score was significantly correlated with tumor microenvironment, immune infiltration, and chemotherapy sensitivity.

Conclusion: Overall, we performed a comprehensive analysis of GTs in OC patients and developed a risk model for OC. Our findings will provide a new insight to OC prognosis and treatment.