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Abstract Objective: Ovarian torsion (OT) represents a severe gynecological emergency in female pediatric patients, necessitating immediate surgical intervention to prevent ovarian ischemia and preserve fertility. Prompt diagnosis is, therefore, paramount. This retrospective study set out to assess the utility of combined clinical, ultrasound, and laboratory features in diagnosing OT. Methods: The authors included 326 female pediatric patients aged under 14 years who underwent surgical confirmation of OT over a five-year period. Logistic regression analysis was employed to pinpoint factors linked with OT, and the authors compared clinical presentation, laboratory results, and ultrasound characteristics between patients with OT (OT group) and without OT (N-OT group). The authors conducted receiver operating characteristic (ROC) curve analysis to gauge the predictive capacity of the combined features. Results: Among 326, OTwas confirmed in 24.23 % (79 cases) of the patients. The OT group had a higher incidence of prenatal ovarian masses than the N-OT (22 cases versus 7 cases) (p < 0.0001). Similarly, the authors observed significant differences in the presence of lower abdominal pain, suspected torsion on transabdominal ultrasound, and a high neutrophil-lymphocyte ratio (NLR > 3) between the OTand non-OT groups (p < 0.05). Furthermore, when these parameters were combined, the resulting area under the curve (AUC) was 0.868, demonstrating their potential utility in OT diagnosis. Conclusion: This study demonstrates a prediction model integrating clinical, laboratory, and ultrasound findings that can support the preoperative diagnosis of ovarian torsion, thereby enhancing diagnostic precision and improving patient management. Future prospective studies should concentrate on developing clinical predictive models for OTin pediatric patients.
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Objective To study the expression,immunological effect and prognosis analysis of G2 and S phase-expressed protein 1(GTSE1)in hepatocellular carcinoma(HCC),and its potential action mechanism.Methods Using the data provided by the public da-tabases The Cancer Genome Atlas(TCGA),the Kaplan-Meier,Tumor Immune Estimation Resource(TIMER)and Gene Expression Profiling Interactive Analysis(GEPIA)databases were used to analyze the gene expression,immunological effect and prognosis of GTSE1,and the expression of GTSE1 in clinical samples was verified by immunohistochemical experiments.Gene Ontology(GO)and Kyoto Ency-clopedia of Genes and Genomes(KEGG)enrichment analysis of GTSE1-related differential genes was performed by R software.Results GTSE1 was significantly overexpressed in human cancer tissues,and was significantly associated with poor prognosis of liver cancer(P<0.05).GTSE1 gene expression was significantly correlated with the abundance of infiltrating immune cells in HCC(P<0.001).GTSE1-related differentially expressed genes were mainly enriched in gene modules such as nuclear division,organelle fission and ion channel activity.The signaling pathways involved mainly include neuroactive ligand-receptor interaction and cell cycle.Conclusion GTSE1 expression is significantly up-regulated in HCC and is significantly associated with poor prognosis,and plays an important role in immune cell infiltration,which can be used as a prognostic marker and immunotherapeutic target for HCC.
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In 2023,numerous theoretical advancements and technological breakthroughs have been achieved in the field of immunology research.In this article,we summarized representative research achievements in the field of immunology both domestically and internationally in 2023,and discussed the challenges and opportunities for future research.
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Objective:To investigate effects of short-term cigarette smoke exposure combined with poly(I:C)stimulation on lung immune response and interferon expression in mice.Methods:BALB/c mice were randomly divided into 4 groups:control group,smoke group,poly(I:C)group and smoke combined poly(I:C)group.Total cell number and cell classification count of bronchoalveo-lar lavage fluid(BALF)were detected,and cell morphology was observed under ordinary light.Cytokines,chemokines,interferon and interferon stimulating genes expressions in lung tissues were detected by fluorescence quantitative PCR.Results:Compared with control group,total cell count,macrophage count and neutrophil count in smoke combined poly(I:C)group were significantly increased(P<0.05),and macrophage count was higher than that in poly(I:C)group.Macrophages of airway lavage fluid of mice in smoke combined with poly(I:C)group were larger in size,round or irregular in shape,and had more vacuoles in cytoplasm.Com-pared with control group,mRNA expressions of neutrophil chemokine CXCL1(P<0.05),CXCL2(P<0.01)and lymphocyte chemo-kine CCL2(P<0.01)in lung tissues of mice in smoke combined with poly(I:C)group were increased.IL-1β,IL-6,TNF-α mRNA expressions were significantly increased(P<0.01),IFN-β(P<0.01),IFN-γ(P<0.05),MX2(P<0.01)and IP-10(P<0.01)expre-ssions in lung tissues were significantly increased,and compared with poly(I:C)group,mRNA expressions of CXCL2(P<0.05),TNF-α(P<0.01)and IFN-β(P<0.05)in lung tissues of mice in smoke combined with poly(I:C)group were significantly increased.Conclusion:Cigarette smoke combined with poly(I:C)induces lung inflammation and expressions of interferon and interferon stimu-lating genes in mice.Cigarette exposure also increases poly(I:C)-induced acute lung inflammation and type Ⅰ interferon expression in mice.
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Objective:To study the differential gene expression and immune cell infiltration of gout patients,to find the key genes and immune cells of gout pathogenesis,and to explore the relationship between immune cells and gout.Methods:The gout chip GSE160170 was downloaded from the GEO database,and the differential gene expression analysis was carried out with the help of R language.Then,the STRING database was used to analyze the differential gene,and the Cytoscape software was used to screen the key genes,and then carry out enrichment analysis.At the same time,the infiltration of immune cells were analyzed.Results:The study found that IL-6,IL-1β,TNF,CCL3,CXCL8 and CXCL1 were key genes in the pathogenesis of gout,which were mainly exerted by IL-17,Toll-like receptor,NOD-like receptor,NF-κB and other signaling pathways.Processes such as cellular responses to lipo-polysaccharides,bacteria-derived molecules,and biological stimuli lead to disease;immune infiltration results indicate that memory B cells,activated NK cells,activated dendritic cells,activated mast cells and eosinophils were involved in the disease.It was signifi-cantly expressed in gout patients;the correlation analysis between immune cells showed that the expression of follicular helper T cells were positively correlated with the expression of activated mast cells,and the expression of unactivated NK cells and monocyte were negatively correlated.Conclusion:Key genes and differentially expressed immune cells are closely related to the pathogenesis of gout,providing new ideas for the study of the molecular mechanism of gout.
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Endoplasmic reticulum stress(ERS)is a subcellular pathological state formed by imbalance of environment in endoplasmic reticulum,and is regarded as an important pathway that mediates apoptosis.Recent studies have found that after ERS occurs in various immune tissues and cells,immunosuppressive effect that produced is involved in regulating body's immune homeo-stasis,affecting occurrence,outcome and prognosis of many diseases.This article reviews production of ERS,signal regulation and pathophysiological changes in immune organs and immune cells,and its role in development of inflammatory diseases and tumors.
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AIM: To identify immune-related key genes and the extent of immune cell infiltration in a oxygen-induced retinopathy(OIR)model by bioinformatics method.METHODS: Microarray data were obtained from the GEO database, differentially expressed genes(DEGs)were identified using the “limma” R package, GO function enrichment and KEGG pathway analysis were conducted, and immune cell infiltration based on the CIBERSORT algorithm was analyzed. Weighted gene co-expression network analysis(WGCNA)was used to screen DEGs in the immune-related gene module, constructing a protein-protein interaction(PPI)network using STRING online database and Cytoscape software, and further screening final target genes using the cytoHubba plug-in.RESULTS: A total of 467 DEGs were screened, including 270 up-regulated and 197 down-regulated genes. Helper T cell 2(Th2 cells), an immune cell type, exhibited significantly high expression levels(P<0.05). WGCNA analysis identified 66 differential genes in modules most closely related to immunity. After constructing the PPI network, 5 key genes were screened through plug-ins: von Willebrand factor(vWF), vascular endothelial growth factor A(VEGF-A), Serping1, apoptosis inducing factor 1(AIF1)and signal transducers and activators of transcription 3(STAT3).CONCLUSION: The findings of this study provide valuable insights into immune cell infiltration in OIR as well as key genes related to immunity through bioinformatics analysis, which can serve as a reference for further research and treatment of retinal neovascular diseases.
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Objective To explore the causal relationship among 731 types of immune cells and breast cancer. Methods Genome-wide association data for immune cells and breast cancer were used. Mendelian randomization analysis was performed using the inverse variance weighting (IVW) and weighted median (WM) methods, and sensitivity analysis was conducted to assess heterogeneity and pleiotropy. Results A total of 19 immune cell phenotypes were identified to potentially have a causal association with breast cancer, using IVW as the main analysis method (P>0.05) and correcting P values using the false discovery rate method at a significance level of 0.05, excluding reverse causality. Of these, eight and 11 immune phenotypes may increase and decrease the risk of breast cancer, respectively. Conclusion This study explored the causal relationship between immune cells and breast cancer. Results show that certain immune cell phenotypes could serve as predictive markers for the early diagnosis of breast cancer and the development of new immunotherapeutic strategies.
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Objective To explore the role of retinol binding protein 7(RBP7)in breast cancer by bioinformatics.Methods R sofrware was used to explore the differential expression of the RBP7 gene in breast cancer by the cancer genome atlas(TCGA)dataset and the human protein atlas(HPA).Relationship between RBP7 and clinical data of breast cancer was evaluated by Kaplan-Meier survival analysis and receiver operating characteristic(ROC)curves.Correlation between high and low RBP7 expression groups and different tumor-infiltrating immune cells(TIICs)were analyzed based on the TCGA database.Gene set enrichment analysis(GSEA)was used to assess the distribute trends of RBP7 in gene tables sorted by phenotypic relatedness.Results RBP7 mRNA expression levels were down-regulated in breast cancer compared to paracancerous tissues,which were expressed in the nucleus.ROC curve analysis showed that the area under curve(AUC)of RBP7 for the diagnosis of breast cancer was 0.943(95%CI:0.926~0.960),and the best cut-off value of RBP7 was 6.29,with a sensitivity and specificity of 82.32%and 93.69%,respectively.Kaplan-Meier survival analysis showed that low expression of RBP7 was associated with overall survival rate in breast cancer patients(HR=0.68,95%CI:0.49~0.93,P=0.017),indicating that RBP7 was an independent risk factor for breast cancer.Spearman correlation showed that RBP7 was positively associated with pDC cells and NK cells(r=0.290,0.253,all P<0.05),and negatively associated with Th2 cells(r=-0.217,P<0.05)in breast cancer.GSEA showed that RBP7 was enriched in pathways such as adipogenesis,ribosome,peptiden ligand binding receptors,and calcium signaling pathway(all P<0.001).Conclusion RBP7 affects the occurrence and development of breast cancer,which may be a potential biomarker and therapeutic target for breast cancer.
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@#Objective To investigate the expression,prognostic value of acetyl-coa carboxylase 1(ACACA)gene in liver cancer,its correlation with immune cells,and to construct a prognostic model.Methods Integrating genotype-tissue expression(GTEx)and the cancer genome atlas(TCGA)data to analyze ACACA expression in cancers and adjacent tissues,and perform prognosis analysis.Examine the correlation between ACACA and immune cells.Use GSE156625 cell RNA seq(scRNA-seq)data to study ACACA expression in dendritic cells(DCs).Construct an hepatocellular carcinoma(HCC)prognosis model based on apolipoprotein c-Ⅰ(APOC1)and apolipoprotein c-Ⅲ(APOC3),using Kaplan-Meier survival curves and time-dependent receiver operator characteristic(ROC)curves to evaluate prognostic capability,and analyze the effect of traditional Chinese medicine components on APOC1 and APOC3 through molecular docking.Results ACACA shows significant differential expression in various cancers and is associated with the prognosis of liver cancer.High expression of ACACA reduces the content of dendritic cells.APOC1 and APOC3,the major DCs marker genes,were positively correlated with ACACA expression.Using Kaplan-Meier curves,we predicted the 1-year,3-year,and 5-year overall survival(OS)probabilities for HCC patients in the TCGA cohort,and confirmed the reliability through calibration curve analysis.Salvianolic acid B,Asiaticoside,and Neohesperidin may have potential effects on APOC1 and APOC3.Conclusion ACACA is closely related to HCC prognosis,and the prognostic model based on APOC1 and APOC3 can serve as a predictive indicator.Some traditional Chinese medicine components may hold therapeutic potential for HCC treatment.
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Abstract Cancer is a fatal malignancy and its increasing worldwide prevalence demands the discovery of more sensitive and reliable molecular biomarkers. To investigate the GINS1 expression level and its prognostic value in distinct human cancers using a series of multi-layered in silico approach may help to establish it as a potential shared diagnostic and prognostic biomarker of different cancer subtypes. The GINS1 mRNA, protein expression, and promoter methylation were analyzed using UALCAN and Human Protein Atlas (HPA), while mRNA expression was further validated via GENT2. The potential prognostic values of GINS1 were evaluated through KM plotter. Then, cBioPortal was utilized to examine the GINS1-related genetic mutations and copy number variations (CNVs), while pathway enrichment analysis was performed using DAVID. Moreover, a correlational analysis between GINS1 expression and CD8+ T immune cells and a the construction of gene-drug interaction network was performed using TIMER, CDT, and Cytoscape. The GINS1 was found down-regulated in a single subtypes of human cancer while commonly up-regulated in 23 different other subtypes. The up-regulation of GINS1 was significantly correlated with the poor overall survival (OS) of Liver Hepatocellular Carcinoma (LIHC), Lung Adenocarcinoma (LUAD), and Kidney renal clear cell carcinoma (KIRC). The GINS1 was also found up-regulated in LIHC, LUAD, and KIRC patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of GINS1 in two diverse pathways, while few interesting correlations were also documented between GINS1 expression and its promoter methylation level, CD8+ T immune cells level, and CNVs. Moreover, we also predicted few drugs that could be used in the treatment of LIHC, LUAD, and KIRC by regulating the GINS1 expression. The expression profiling of GINS1 in the current study has suggested it a novel shared diagnostic and prognostic biomarker of LIHC, LUAD, and KIRC.
Resumo O câncer é uma doença maligna fatal e sua crescente prevalência mundial exige a descoberta de biomarcadores moleculares mais sensíveis e confiáveis. Investigar o nível de expressão de GINS1 e seu valor prognóstico em cânceres humanos distintos, usando uma série de abordagens in silico em várias camadas, pode ajudar a estabelecê-lo como um potencial biomarcador de diagnóstico e prognóstico compartilhado de diferentes subtipos de câncer. O mRNA de GINS1, a expressão da proteína e a metilação do promotor foram analisados usando UALCAN e Human Protein Atlas (HPA), enquanto a expressão de mRNA foi posteriormente validada via GENT2. Os valores prognósticos potenciais de GINS1 foram avaliados por meio do plotter KM. Em seguida, o cBioPortal foi utilizado para examinar as mutações genéticas relacionadas ao GINS1 e as variações do número de cópias (CNVs), enquanto a análise de enriquecimento da via foi realizada usando DAVID. Além disso, uma análise correlacional entre a expressão de GINS1 e células imunes T CD8 + e a construção de uma rede de interação gene-droga foi realizada usando TIMER, CDT e Cytoscape. O GINS1 foi encontrado regulado negativamente em um único subtipo de câncer humano, enquanto comumente regulado positivamente em 23 outros subtipos diferentes. A regulação positiva de GINS1 foi significativamente correlacionada com a sobrevida global pobre (OS) de Carcinoma Hepatocelular de Fígado (LIHC), Adenocarcinoma de Pulmão (LUAD) e Carcinoma de Células Claras Renais de Rim (KIRC). O GINS1 também foi encontrado regulado positivamente em pacientes LIHC, LUAD e KIRC de diferentes características clínico-patológicas. A análise de enriquecimento de vias revelou o envolvimento de GINS1 em duas vias diversas, enquanto poucas correlações interessantes também foram documentadas entre a expressão de GINS1 e seu nível de metilação do promotor, nível de células imunes T CD8 + e CNVs. Além disso, também previmos poucos medicamentos que poderiam ser usados no tratamento de LIHC, LUAD e KIRC, regulando a expressão de GINS1. O perfil de expressão de GINS1 no estudo atual sugeriu que é um novo biomarcador de diagnóstico e prognóstico compartilhado de LIHC, LUAD e KIRC.
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Humanos , Carcinoma de Células Renais/genética , Neoplasias Renais/genética , Neoplasias Hepáticas , Prognóstico , Biomarcadores Tumorais/genética , Regulação Neoplásica da Expressão Gênica , Regulação para Cima , Proteínas de Ligação a DNA , Variações do Número de Cópias de DNARESUMO
Abstract Cancer is a fatal malignancy and its increasing worldwide prevalence demands the discovery of more sensitive and reliable molecular biomarkers. To investigate the GINS1 expression level and its prognostic value in distinct human cancers using a series of multi-layered in silico approach may help to establish it as a potential shared diagnostic and prognostic biomarker of different cancer subtypes. The GINS1 mRNA, protein expression, and promoter methylation were analyzed using UALCAN and Human Protein Atlas (HPA), while mRNA expression was further validated via GENT2. The potential prognostic values of GINS1 were evaluated through KM plotter. Then, cBioPortal was utilized to examine the GINS1-related genetic mutations and copy number variations (CNVs), while pathway enrichment analysis was performed using DAVID. Moreover, a correlational analysis between GINS1 expression and CD8+ T immune cells and a the construction of gene-drug interaction network was performed using TIMER, CDT, and Cytoscape. The GINS1 was found down-regulated in a single subtypes of human cancer while commonly up-regulated in 23 different other subtypes. The up-regulation of GINS1 was significantly correlated with the poor overall survival (OS) of Liver Hepatocellular Carcinoma (LIHC), Lung Adenocarcinoma (LUAD), and Kidney renal clear cell carcinoma (KIRC). The GINS1 was also found up-regulated in LIHC, LUAD, and KIRC patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of GINS1 in two diverse pathways, while few interesting correlations were also documented between GINS1 expression and its promoter methylation level, CD8+ T immune cells level, and CNVs. Moreover, we also predicted few drugs that could be used in the treatment of LIHC, LUAD, and KIRC by regulating the GINS1 expression. The expression profiling of GINS1 in the current study has suggested it a novel shared diagnostic and prognostic biomarker of LIHC, LUAD, and KIRC.
Resumo O câncer é uma doença maligna fatal e sua crescente prevalência mundial exige a descoberta de biomarcadores moleculares mais sensíveis e confiáveis. Investigar o nível de expressão de GINS1 e seu valor prognóstico em cânceres humanos distintos, usando uma série de abordagens in silico em várias camadas, pode ajudar a estabelecê-lo como um potencial biomarcador de diagnóstico e prognóstico compartilhado de diferentes subtipos de câncer. O mRNA de GINS1, a expressão da proteína e a metilação do promotor foram analisados usando UALCAN e Human Protein Atlas (HPA), enquanto a expressão de mRNA foi posteriormente validada via GENT2. Os valores prognósticos potenciais de GINS1 foram avaliados por meio do plotter KM. Em seguida, o cBioPortal foi utilizado para examinar as mutações genéticas relacionadas ao GINS1 e as variações do número de cópias (CNVs), enquanto a análise de enriquecimento da via foi realizada usando DAVID. Além disso, uma análise correlacional entre a expressão de GINS1 e células imunes T CD8 + e a construção de uma rede de interação gene-droga foi realizada usando TIMER, CDT e Cytoscape. O GINS1 foi encontrado regulado negativamente em um único subtipo de câncer humano, enquanto comumente regulado positivamente em 23 outros subtipos diferentes. A regulação positiva de GINS1 foi significativamente correlacionada com a sobrevida global pobre (OS) de Carcinoma Hepatocelular de Fígado (LIHC), Adenocarcinoma de Pulmão (LUAD) e Carcinoma de Células Claras Renais de Rim (KIRC). O GINS1 também foi encontrado regulado positivamente em pacientes LIHC, LUAD e KIRC de diferentes características clínico-patológicas. A análise de enriquecimento de vias revelou o envolvimento de GINS1 em duas vias diversas, enquanto poucas correlações interessantes também foram documentadas entre a expressão de GINS1 e seu nível de metilação do promotor, nível de células imunes T CD8 + e CNVs. Além disso, também previmos poucos medicamentos que poderiam ser usados no tratamento de LIHC, LUAD e KIRC, regulando a expressão de GINS1. O perfil de expressão de GINS1 no estudo atual sugeriu que é um novo biomarcador de diagnóstico e prognóstico compartilhado de LIHC, LUAD e KIRC.
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Objective To observe the expression differences of peripheral blood immune cells in healthy people,myelodysplastic syndrome(MDS)patients and acute myeloid leukemia(AML)patients,and to further analyze the correlation between the differences and International Prognostic Scoring System(IPSS)score,original cell number and other factors in MDS patients.Methods A total of 55 MDS patients admitted to Dongzhimen Hospital,Beijing University of Chinese Medicine from January 2012 to April 2022 were retrospec-tively analyzed,and 25 healthy people and 67 AML patients were included as control groups.The expression of T lymphocyte subsets(CD3+,CD4+,CD8+,CD4+/CD8+,CD3+CD4+CD25+FoxP3+),B cells(CD19+)and NK cells(CD3-CD16+CD56+)were compared according to the absolute count of immune cells and their percentage in lymphocytes.The correlation between the difference in-dex and IPSS score and the number of original cells was analyzed.Results There were differences in the expression levels of immune in-dicators among the three groups.Pairwise comparison indicated that compared with the control groups,the immune cells count of MDS group were lower(P<0.025),which was considered to be related to the total lymphocyte count in MDS patients were lower than those in the healthy group.The expression levels of immune cells in the three groups were different in the percentage of Treg cells,B cells and T lymphocytes.Pairwise comparison showed that compared with the healthy group,the proportion of T lymphocytes and Treg cells in MDS group was higher,and the proportion of B cells was lower,and the difference between T lymphocytes and B cells was statistically signifi-cant(P<0.025).Compared with MDS group,the proportion of Treg cells was higher and the proportion of B cells was lower in AML group,the difference was statistically significant(P<0.025).The proportion of Treg cells was positively correlated with IPSS score and the number of original cells.Conclusion The expression level of Treg cells in healthy people,MDS and AML showed an overall increasing trend.The higher expression level of Treg cells in MDS patients may be an important factor to evaluate the prognosis and progression of MDS patients.
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Objective:To investigate the immune cell infiltration width on lesion microenvironment (LME) based on different hepatic alveolar echinococcosis lesion features to underlie referential sampling range for experimental and control tissues aiming at avoiding false negativity in basic researches.Methods:Using prospective research methods, from January 2017 to December 2019, patients with hepatic alveolar echinococcosis who were diagnosed and treated surgically at the First Affiliated Hospital of Xinjiang Medical University and met the multi-site sampling method (MSS method) were investigated. A total of 26 cases were included, aged 34 (15, 65) years old, with a gender ratio of 12/14. Lesions were classified into six groups based on heterogenic scales of calcification and liquefaction: A. non-calcified and non-liquefied; B. obvious calcified and non-liquefied; C. partial calcified and partial liquefied; D. obvious calcified and partial liquefied; E. partial calcified and subtotal liquefied; F. obvious calcified and subtotal liquefied. Liver specimens were acquired with 5 mm interval off the lesion shore in LME area using MSS method. Performed immunohistochemical staining of CD3, CD19, CD68, and Masson staining of fibrous tissue, and after pathological evaluation, the layer with a sharp decrease in immune cell infiltration abundance was determined as the maximum infiltration range (width, W value). The experimental group conservatively estimated the maximum sampling range for the integer value of Q1 of W value. The control group conservatively estimated the minimum sampling range for the integer value after Q3 rounding plus 5 mm of W value. Results were analyzed using Kruskal-Wallis H and Mann-Whitney U tests, referential ranges were concluded. Results:Median W values (interquartile) for each group were 20.0 (12.5, 22.5), 15.0 (10.0, 15.0), 10.0 (10.0, 15.0), 5.0 (5.0, 10.0), 12.5 (6.3, 15.0), and 5.0 (5.0, 10.0) mm, among which A > D, A > F, C > D, and C > F ( P≤0.05); from the perspective of calcification, A > C + E, A > B + D + F ( P < 0.05), while A + B > C + D, A + B > E + F ( P < 0.05) from the perspective of liquefaction. In these groups, the experimental group conservatively estimated the maximum distance for sampling to be 12.0, 10.0, 10.0, 5.0, 6.0, and 5.0 mm, while the control group conservatively estimated the minimum distance for sampling to be 28.0, 20.0, 20.0, 15.0, 20.0, and 15.0 mm. Conclusions:Less calcification and liquefaction implicates wider immune cell infiltration range in those lesions. Tissue sampling should be individualized based on different lesion features in basic research to avoid false negativity.
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Gene epigenetic modification can turn on and off the program of gene expression without changing the DNA sequence, and the underlying mechanisms mainly include DNA methylation, histone modification and miRNA regulation. A series of studies have shown that epigenetic regulation is involved in the pathogenesis of atopic dermatitis. This review briefly summarizes the role of gene epigenetic modification in the pathogenesis of atopic dermatitis.
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Systemic lupus erythematosus (SLE) is an autoimmune disease with multiple organ involvement. There are still many limitations and individual differences in the treatment based on glucocorticoids and immunosuppressants. In recent years, more and more studies have shown that the combination of traditional Chinese medicine in the treatment of SLE has the advantages of good efficacy, low adverse reactions, and high safety. However, the exact regulatory mechanism and combined traditional Chinese medicine in the treatment of SLE are still unclear. This paper reviews the research on the mechanism of traditional Chinese medicine in the treatment of SLE from metabonomic, immune cells, lymphocyte factors and apoptosis, etc, provides ideas for exploring the mechanism of traditional Chinese medicine in the treatment of SLE with modern methods.
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Objective:To investigate the effects of estimated dose of radiation to immune cells (EDRIC) on overall survival (OS), local progression-free survival (LPFS) and distant metastasis-free survival (DMFS) in limited-stage small-cell lung cancer (LS-SCLC) with different tumor burdens.Methods:Clinical data of 216 patients with LS-SCLC who initially received conventional fractionated radiotherapy of the chest for radical treatment in Tianjin Medical University Cancer Institute and Hospital from 2013 to 2019 were retrospectively analyzed. EDRIC was calculated based on the model developed by Jin et al. and tumor burdens were assessed by gross tumor volume (GTV) or clinical stage. The study endpoints were OS, LPFS and DMFS, which were calculated from the date of diagnosis. The optimal cut-off value of EDRIC was calculated by R language. The correlation between EDRIC and tumor burdens was analyzed using Spearman's correlations. Survival analysis was performed by Cox proportional hazards regression model and Kaplan-Meier curve. Results:The median follow-up time for the whole group was 47.8 months, and the median OS and DMFS was 34.6 months and 18.5 months, respectively, while the median LPFS did not reach. The optimal cut-off value of EDRIC was 6.8 Gy. Cox multivariate analysis showed that EDRIC was an independent prognostic factor affecting OS and DMFS. EDRIC was weakly correlated with GTV or clinical stage. Stratified by the median GTV, OS ( P=0.021) and DMFS ( P=0.030) were significantly shortened and LPFS had a tendency of shortening ( P=0.107) when EDRIC>6.8 Gy compared with those when EDRIC ≤ 6.8 Gy in the GTV ≤ 34.6 cm 3 group; EDRIC had little effect on OS, LPFS, and DMFS ( P=0.133, 0.420, 0.374) in the GTV>34.6 cm 3 group. Stratified by clinical stage, OS ( P=0.003) and DMFS ( P=0.032) were significantly shortened and LPFS ( P=0.125) tended to shorten when EDRIC>6.8 Gy in stage I, II and IIIA groups; EDRIC exerted slight effect on OS, LPFS, and DMFS ( P=0.377, 0.439, 0.484) in stage IIIB and IIIC groups. Conclusion:EDRIC is an important factor affecting prognosis and exerts more significant impact on prognosis in patients with smaller tumor burden.
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Aspergillus fumigatus ( A. fumigatus) is an environmental filamentous fungus and an opportunistic pathogen that can cause chronic and invasive aspergillosis. The development of aspergillosis is the result of the interaction between the host and the pathogen, and the symptoms of A. fumigatus infection varied in patients with different immune status. The host innate immune response to inhaled fungal spores is a key determinant of the development of aspergillosis. This review focused on the role of innate immune cells including macrophages, neutrophils, natural killer cells, natural killer T cells and mast cells in host defense against A. fumigatus, aiming to provide reference for further research on the pathogenesis, clinical prevention and treatment of aspergillosis.
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Objective:To evaluate the value of preoperative peripheral blood neutrophil-lymphocyte ratio (NLR) and blood platelet-lymphocyte ratio (PLR) and immune indexes in the evaluation of the prognosis of cervical cancer patients.Methods:The clinical data of 283 patients with cervical cancer who underwent radical surgery in Shanxi Province Cancer Hospital from May 2017 to September 2018 were retrospectively analyzed, and 100 healthy people who underwent physical examination during the same period were collected as the healthy control group. Test results of blood cells and immune cells expressions of all subjects were collected. Peripheral blood NLR and PLR of cervical cancer patients, people in the healthy control group and cervical cancer patients with different pathological characteristics were compared. Kaplan-Meier method was used to make survival analysis and Cox regression risk model was used to analyze the factors influencing the prognosis of patients with cervical cancer.Results:The preoperative peripheral blood NLR and PLR in patients with cervical cancer was higher than that of the healthy control group (NLR: 2.53±1.35 vs. 2.00±1.21, t = 5.35, P < 0.001; PLR: 163±57 vs.144±38, t = 4.71, P = 0.006). Pathological results showed that there were no statistically significant differences in NLR and PLR in peripheral blood of cervical cancer patients with different pathological types, tumor diameter, vascular invasion, and nerve invasion (all P > 0.05), while there were statistically significant differences in NLR and PLR in peripheral blood of cervical cancer patients with different clinical staging and muscle wall invasion (all P < 0.05). When the proportions of the expression levels of preoperative CD3 positive cells, CD4 positive cells, CD8 positive cells, CD19 positive cells, CD56 positive cells, and CD127 positive cells were 60%-85%, 30%-40%, < 25%, 8%-15%, 15%-25% and < 5%, respectively, the overall survival of cervical cancer patients was the best. Univariate analysis showed that pathological type, clinical staging, vascular invasion, preoperative NLR, preoperative PLR,CD3 positive cells, CD4 positive cells, CD8 positive cells, CD19 positive cells, CD56 positive cells and CD127 positive cells were influencing factors of the overall survival of cervical cancer patients (all P < 0.05). Multivariate analysis showed that clinical staging, vascular invasion, preoperative NLR, preoperative PLR, and preoperative CD4 positive cells were independent influencing factors for the overall survival of cervical cancer patients (all P < 0.05). Conclusions:Preoperative high NLR and PLR in peripheral blood have a certain impact on the clinicopathological characteristics and poor prognosis of cervical cancer patients. When the immune cells in peripheral blood are in dynamic balance, the prognosis of cervical cancer patients is the best.
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OBJECTIVES@#Graves' ophthalmopathy (GO) is a multifactorial disease, and the mechanism of non coding RNA interactions and inflammatory cell infiltration patterns are not fully understood. This study aims to construct a competing endogenous RNA (ceRNA) network for this disease and clarify the infiltration patterns of inflammatory cells in orbital tissue to further explore the pathogenesis of GO.@*METHODS@#The differentially expressed genes were identified using the GEO2R analysis tool. The Kyoto encyclopedia of genes and genomes (KEGG) and gene ontology analysis were used to analyze differential genes. RNA interaction relationships were extracted from the RNA interactome database. Protein-protein interactions were identified using the STRING database and were visualized using Cytoscape. StarBase, miRcode, and DIANA-LncBase Experimental v.2 were used to construct ceRNA networks together with their interacted non-coding RNA. The CIBERSORT algorithm was used to detect the patterns of infiltrating immune cells in GO using R software.@*RESULTS@#A total of 114 differentially expressed genes for GO and 121 pathways were detected using both the KEGG and gene ontology enrichment analysis. Four hub genes (SRSF6, DDX5, HNRNPC,and HNRNPM) were extracted from protein-protein interaction using cytoHubba in Cytoscape, 104 nodes and 142 edges were extracted, and a ceRNA network was identified (MALAT1-MIR21-DDX5). The results of immune cell analysis showed that in GO, the proportions of CD8+ T cells and CD4+ memory resting T cells were upregulated and downregulated, respectively. The proportion of CD4 memory resting T cells was positively correlated with the expression of MALAT1, MIR21, and DDX5.@*CONCLUSIONS@#This study has constructed a ceRNA regulatory network (MALAT1-MIR21-DDX5) in GO orbital tissue, clarifying the downregulation of the proportion of CD4+ stationary memory T cells and their positive regulatory relationship with ceRNA components, further revealing the pathogenesis of GO.