Effects of weight loss on QTc in people with obesity: a systematic review and meta-analysis.

BACKGROUND AND AIMS: Overweight and obesity have been found to exhibit a statistically significant increase in corrected QT interval (QTc), a major contributing factor to sudden death. However, the influence of widely used weight loss strategies including diet, exercise, anti-obesity drugs, and bariatric surgery on QTc remains inconsistent. Therefore, the present systematic review and meta-analysis aim to quantitatively analyse and evaluate the effect of weight loss on QTc in obese patients after diet control with exercise intervention and anti-obesity drugs, as well as bariatric surgery. METHODS: Twenty randomised controlled trials (RCT) and observational studies were included in the meta-analysis on the effects of weight loss on QTc. The fixed-effects model was employed in the RCTs, and the random-effects model was employed due to the presence of statistical heterogeneity among observational studies. Subgroup analysis was conducted to understand the differences in distinct weight loss methods and follow-up time. RESULTS: Overall, the QTc of people with obesity after weight loss was shorter than that before (mean difference (MD) = 21.97 ms, 95% confidence interval (CI) = 12.42, 31.52, p < .0001). Subgroup analysis restricted to seven included studies whose intervention was diet control with exercise showed a decrease of QTc with statistical significance (MD = 9.35 ms, 95%CI = 2.56, 37.54, p = .007). In the remaining 11 studies, bariatric surgery was the weight loss method. The results also showed a shortening of QTc after surgery, and the difference was statistically significant (MD = 29.04 ms, 95%CI = -16.46, 41.62, p < .00001). A statistically significant difference in QTc shortening at 6 months compared to pre-operation values was further observed (MD = -31.01 ms, 95%CI = -2.89, -59.12, p = .03). The shortening of QTc at 12 months of follow-up was also significantly different from that before surgery (MD = 36.47 ms, 95%CI = 14.17, 58.78, p < .00001). Moreover, the differences became more pronounced as the follow-up time extended. CONCLUSIONS: We demonstrate that weight loss links to a shortened QTc, without considering the means of weight loss. Bariatric surgery has been found to result in a greater reduction in QTc.

Identification of Lipotoxicity-Related Biomarkers in Diabetic Nephropathy Based on Bioinformatic Analysis.

Objective: This study is aimed at investigating diagnostic biomarkers associated with lipotoxicity and the molecular mechanisms underlying diabetic nephropathy (DN). Methods: The GSE96804 dataset from the Gene Expression Omnibus (GEO) database was utilized to identify differentially expressed genes (DEGs) in DN patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted using the DEGs. A protein-protein interaction (PPI) network was established to identify key genes linked to lipotoxicity in DN. Immune infiltration analysis was employed to identify immune cells with differential expression in DN and to assess the correlation between these immune cells and lipotoxicity-related hub genes. The findings were validated using the external dataset GSE104954. ROC analysis was performed to assess the diagnostic performance of the hub genes. The Gene set enrichment analysis (GSEA) enrichment method was utilized to analyze the key genes associated with lipotoxicity as mentioned above. Result: In this study, a total of 544 DEGs were identified. Among them, extracellular matrix (ECM), fatty acid metabolism, AGE-RAGE, and PI3K-Akt signaling pathways were significantly enriched. Combining the PPI network and lipotoxicity-related genes (LRGS), LUM and ALB were identified as lipotoxicity-related diagnostic biomarkers for DN. ROC analysis showed that the AUC values for LUM and ALB were 0.882 and 0.885, respectively. The AUC values for LUM and ALB validated in external datasets were 0.98 and 0.82, respectively. Immune infiltration analysis revealed significant changes in various immune cells during disease progression. Macrophages M2, mast cells activated, and neutrophils were significantly associated with all lipotoxicity-related hub genes. These key genes were enriched in fatty acid metabolism and extracellular matrix-related pathways. Conclusion: The identified lipotoxicity-related hub genes provide a deeper understanding of the development mechanisms of DN, potentially offering new theoretical foundations for the development of diagnostic biomarkers and therapeutic targets related to lipotoxicity in DN.

Losartan alleviates renal fibrosis by inhibiting the biomechanical stress-induced epithelial-mesenchymal transition of renal epithelial cells.

Angiotensin receptor blockers (ARBs) have been reported to be beneficial of renal fibrosis, but the molecular and cellular mechanisms are still unclear. In this study, we investigated the effectiveness and relevant mechanism of ARBs in alleviating renal fibrosis, especially by focusing on biomechanical stress-induced epithelial to mesenchymal transition (EMT) of renal epithelial cells. Unilateral ureteral obstruction (UUO) renal fibrosis model was established in mice by ligating the left ureter, and then randomly received losartan at a low dose (1 mg/kg) or a regular dose (3 mg/kg) for 2 weeks. Compared to the control, histological analysis showed that losartan treatment at either a low dose or a regular dose effectively attenuated renal fibrosis in the UUO model. To further understand the mechanism, we ex vivo loaded primary human renal epithelial cells to 50 mmHg hydrostatic pressure. Western blot and immunostaining analyses indicated that the loading to 50 mmHg hydrostatic pressure for 24 h significantly upregulated vimentin, ß-catenin and α-SMA, but downregulated E-cadherin in renal epithelial cells, suggesting the EMT. The addition of 10 or 100 nM losartan in medium effectively attenuated the EMT of renal epithelial cells induced by 50 mmHg hydrostatic pressure loading. Our in vivo and ex vivo experimental data suggest that losartan treatment, even at a low dose can effectively alleviate renal fibrosis in mouse UUO model, at least partly by inhibiting the biomechanical stress-induced EMT of renal epithelial cells. A low dose of ARBs may repurpose for renal fibrosis treatment.

Inhibition of Autophagy in Renal Cells With Human, Urine-derived, Stem-cell Exosomes to Improve Diabetic Nephropathy.

Context: Clinicians can use stem cells to repair kidney injury. The kidneys' exosome secretions hold the secret to this therapeutic impact. Exosomes from urine-derived stem cells can prevent and treat glomerular damage that diabetes can cause, but the underlying process has remained a mystery. Objective: The study aimed to investigate the protective impact of exosomes from urine-derived stem cells (USCs) against diabetic nephropathy (DN) and to determine the mechanisms involved. Design: The research team performed an animal study. Setting: The study took place at the Affiliated Hospital of Jiujiang University in Jiujiang, Jiangxi, China. Animals: The animals were rats, SD male rats, weighing 200-220g, 40 animals, purchased from Weitong Lihua Experimental Animal Technology Co., Ltd. (certificate number: SCXK (Beijing) 2021-0006). Intervention: Except for a control group, the rats in the groups had induced DN. The five groups, with 10 rats each, were: (1) the negative control group, which received 0.2 ml of PBS solution; (2) the DN group, a second negative control group, which received 0.2 ml of PBS solution, (3) the inhibitor group, an intervention group that received 20 mg/kg of autophagy inhibitor; (4) the exosomes group, an intervention group that received 100 ug/kg of exosomes; and (5) the exosomes + inhibitor group, an intervention group that received 100 ug/kg of exosomes + 20 mg/kg of autophagy inhibitor. From week 8, for four weeks the team injected the inhibitor, exosomes, and exosomes + inhibitor groups with the appropriate treatments using the rats' tail veins. Outcome Measures: The research team: (1) examined the USCs in the exosomes of stem cells; (2) assessed the rats' weights and fasting blood glucose (FBG), using a blood glucose meter; (3) used Coomassie brilliant blue (CBB) staining to determine the amount of protein in the rats' urine and assessed their biochemical indexes; and (4) used Western blot (WB) and a quantitative polymerase chain reaction (Q-PCR) to detect autophagy and the signal transduction pathway. Results: Human exosomes from USCs alleviated injury in the rats that DN caused by reducing urinary-protein levels, serum creatinine (SCR), blood urea nitrogen (BUN), glomerular cell accumulation, and kidney weights. In rats with induced DN, the exosomes + inhibitor significantly reduced the activation of the mTOR signaling pathway, reduced the autophagy of their kidney cells, increased the protein expression of Bcl-2 in the kidney tissues, and lessened the damage to glomerular cells. Conclusions: Human urine-derived stem cell exosomes can significantly reduce the activation of the mTOR signaling pathway, reduce the autophagy of rats' kidney cells, increase the protein expression of LC3B in kidney tissues, and reduce the damage to glomerular cells. By blocking the mTOR signaling pathway, human urogenic exosomes can alleviate the signs and symptoms of DN.

Triptolide exposure induces oxidative stress and decreases oocyte quality in mouse.

Triptolide is a major active ingredient isolated from the traditional Chinese medicine Tripterygium wilfordii, which has anti-inflammatory, anti-cancer, and immunomodulatory effects. However, in clinical studies, triptolide has toxic side effects on the heart, kidney, liver and reproductive organs. With respect to female reproductive toxicity, damaging effects of triptolide on the ovary have been reported, but it has remained unknown whether oocytes are affected by triptolide. Therefore, this study established a concentration gradient of triptolide exposure in mice using 0 (control), 30, 60, and 90 µg triptolide/kg body weight/day administered by gavage. Triptolide administration for 28 d reduced body weight and ovarian weight and affected the developmental potential of oocytes. The triptolide-treated group exhibited meiotic failure of oocytes due to impaired spindle assembly, chromosome alignment, and tubulin stability. Triptolide was also found to induce mitochondrial dysfunction, autophagy and early apoptosis, iron homeostasis, and abnormal histone modifications. These adverse effects could be associated with oxidative stress induced by triptolide. In conclusion, our findings suggest detrimental effects of triptolide on mouse oocytes and, thus, on female reproduction.

Analysis of Immune and Inflammation Characteristics of Atherosclerosis from Different Sample Sources.

Background: Atherosclerosis is the predominant cause of cardiovascular diseases. Existing studies suggest that the development of atherosclerosis is closely related to inflammation and immunity, but whether there are differences and similarities between atherosclerosis occurring at different sites is still unknown. We elucidated the pathological characteristics of peripheral vascular diseases by using bioinformatic analyses on immune cells and inflammation-related gene expression in atherosclerotic arteries and plaques. Methods: Eight data sets regarding atherosclerosis were downloaded from the Gene Expression Omnibus database. Human immune genes were obtained from the IMMPORT website. The samples were scored and divided into high- and low-immune groups. Then the samples were analysed using weighted gene co-expression network analysis, while the modules were analysed using functional enrichment. The protein-protein interaction network was constructed using the STRING and Cytoscape databases. The hub immune genes were screened, and the correlation between hub immune genes and immune cells was analysed. Results: Immune cells and their functions were significantly different during atherosclerosis development. The infiltration proportion of immune cells was approximately similar in samples from different sources of patients with carotid atherosclerosis. However, the sensitivity of lower extremity atherosclerosis samples to immune cells is lower than that of carotid atherosclerosis samples.The samples from the plaque and artery were mainly infiltrated by macrophages, T cells and mast cells. After immune cells were assessed, resting NK cells, activated mast cells and M0 macrophages were found to be key immune cells in atherosclerosis and plaque formation. In addition, CCL4, TLR2, IL1B and PTPRC were considered to be immune marker genes in atherosclerosis development. Conclusion. Bioinformatic data analysis confirms the essential role of immune cells in cardiovascular diseases, and also indicates some differences of immune and inflammation characteristics of atherosclerosis between carotid and lower extremity arteries.

Left abdominal wall proliferative myositis resection and patch repair: A case report.

BACKGROUND: Proliferative myositis is a rare benign tumor that is typically self-limiting and does not become malignant. It can be cured by simple resection without reported recurrence. Due to its rapid growth, hard structure and ill-defined borders, it can however be mistaken for malignant tumors such as sarcomas. CASE SUMMARY: We investigate the case of a 64-year-old male with proliferative myositis of the abdominal wall, who was preoperatively administered a needle aspiration biopsy and given a simple excision and patch repair. We then compared it with other similar cases to determine the effectiveness of this treatment method. CONCLUSION: Resection with follow-up observation has shown to be an effective treatment method for proliferative myositis. To avoid unnecessarily extended or destructive resection, a thorough and conclusive diagnosis is crucial, which requires adequate imaging and pathological knowledge.

Identification of Aging-Related Genes Associated with Prognostic Value and Immune Microenvironment Characteristics in Diffuse Large B-Cell Lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is a complex invasive tumour that occurs mainly among the elderly. Therefore, we analysed the relationship between ageing-related genes (AG) and DLBCL prognosis. Datasets related to DLBCL and human AGs were downloaded and screened from the Gene Expression Omnibus (GEO) database and HAGR website, respectively. LASSO and Cox regression were used to analyse AGs in the dataset and construct an AG predictive model related to DLBCL prognosis. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes enrichment were used to analyse the function of the AG predictive model. The immune microenvironment and immune cell infiltration in DLBCL and their relationship with the AG prediction model were also analysed. After the analysis, 118 AGs were identified as genes related to DLBCL prognosis. Using the LASSO and Cox regression analyses, 9 AGs (PLAU, IL7R, MYC, S100B, IGFBP3, NR3C1, PTK2, TBP, and CLOCK) were used to construct an AG prognostic model. In the training and verification sets, this model exhibited excellent predictive ability for the prognosis of patients with DLBCL who have different clinical characteristics. Further analysis revealed that the high- and low-risk groups of the AG prognostic model were significantly correlated with immune cell infiltration and tumour microenvironment in DLBCL. Functional enrichment analysis also showed that the genes in the AG model were associated with immune-related functions and pathways. In conclusion, we constructed an AG model with a strong predictive function in DLBCL, with the ability to predict the prognosis of patients with different clinical features. This model provides new ideas and potential therapeutic targets for the study of the pathogenesis of DLBCL.

Effects of Medication Use on Small Airway Function and Airway Inflammation in Patients with Clinically Controlled Asthma.

OBJECTIVE: To observe effects of medication use on small airway function, airway inflammation and acute exacerbations in patients with clinically controlled asthma. METHODS: Forced expiratory flow over the middle half of the forced expiratory curve (FEF25%-75%), percentage of eosinophil, concentrations of eosinophil cationic protein (ECP) and interleukin (IL)-5 in induced sputum were assessed in patients with clinically controlled asthma who were given oral anti-inflammatory agents alone or in combination with inhaled therapy and inhaled therapy alone. Subsequently, acute exacerbations were compared between two groups during the 24-week follow-up period. RESULTS: FEF25%-75% in 43 patients with clinically controlled asthma given oral anti-inflammatory agents alone or in combination with inhaled therapy was significantly higher than that in 49 patients given inhaled therapy alone. Meanwhile, the percentage of eosinophils and levels of IL-5 and ECP in patients with clinically controlled asthma given oral anti-inflammatory agents alone or in combination with inhaled therapy were significantly lower than those in patients given inhaled therapy alone. Additionally, the patients with clinically controlled asthma given inhaled therapy were likely to have more acute exacerbation than the patients given oral anti-inflammatory agents alone or in combination with inhaled therapy during the 24-week follow-up period. CONCLUSION: Systemic anti-inflammatory agents may have a greater effect on parameters reflecting small airway patency and reducing acute exacerbations, presumably secondary to reduction in airway inflammation.

Corrigendum: Seven Glycolysis-Related Genes Predict the Prognosis of Patients With Pancreatic Cancer.

[This corrects the article DOI: 10.3389/fcell.2021.647106.].

Based on bioinformatics analysis lncrna SNHG5 modulates the function of vascular smooth muscle cells through mir-205-5p/SMAD4 in abdominal aortic aneurysm.

OBJECTIVE: The aim of this study was to explore expression profiles of long noncoding RNA (lncRNA)-messenger RNA (mRNA) in abdominal aortic aneurysm (AAA) patients. Further, we explored the mechanisms by which lncRNA SNHG5 modulates the function of vascular smooth muscle cells (VSMC) in AAA. METHODS: Human gene expression profile GSE57691 dataset, was retrieved from Gene Expression Omnibus database. The dataset included gene expression array data of 49 AAA patients and 10 control aortic specimens from organ donors. To explore the main roles of the biological network, differentially expressed lncRNA and mRNAs in the aortic aneurysm (AAA) and normal aortic specimens were determined. Differentially expressed lncRNA and mRNAs were then used to construct a competing endogenous RNA (ceRNA) network using Cytoscape software, and the five key lncRNA were identified. SNHG5 which was significantly downregulated in the AAA was chosen and analysis showed that it regulates mir-205-5p and SMAD4 by binding to mir-205-5p. Double luciferase reporter gene assays, RNA immunoprecipitation, and RNA knockdown studies were used to establish the relationship between SNHG5 and mir-205-5p. Apoptosis rate was determined using flow cytometry, whereas cell proliferation was evaluated using Edu, and 24 well Transwell assay. Western blot analysis was used to determine protein expression levels. RESULTS: The five differentially expressed lncRNAs were significantly correlated with 34 microRNAs and 112 mRNAs. mRNAs in the ceRNA network are implicated in protein binding, signal transduction, DNA and RNA transcription, development, and cell differentiation. SNHG5 was downregulated in the AAA and acts as a molecular sponge for mir-205. Downregulation of SNHG5 induces expression of mir-205-5p. Increased mir-205-5p expression level inhibits SMAD4 production, thus inhibiting proliferation and migration and promotes apoptosis of smooth muscle cells. CONCLUSION: Bioinformatics were used to explore molecular mechanism of AAA progression. The findings of this study show that lncRNA SNHG5 regulates proliferation and apoptosis of VSMC cells through modulation of the mir-205-5p/SMAD4 axis. Therefore, SNHG5 is a potential therapeutic target for AAA disease.

Seven Glycolysis-Related Genes Predict the Prognosis of Patients With Pancreatic Cancer.

Objectives: To identify the key glycolysis-related genes (GRGs) in the occurrence and development of pancreatic ductal carcinoma (PDAC), and to construct a glycolysis-related gene model for predicting the prognosis of PDAC patients. Methodology: Pancreatic ductal carcinoma (PDAC) data and that of normal individuals were downloaded from the TCGA database and Genotype-Tissue Expression database, respectively. GSEA analysis of glycolysis-related pathways was then performed on PDAC data to identify significantly enriched GRGs. The genes were combined with other patient's clinical information and used to construct a glycolysis-related gene model using cox regression analysis. The model was further evaluated using data from the validation group. Mutations in the model genes were subsequently identified using the cBioPortal. In the same line, the expression levels of glycolysis related model genes in PDAC were analyzed and verified using immunohistochemical images. Model prediction for PDAC patients with different clinical characteristics was then done and the relationship between gene expression level, clinical stage and prognosis further discussed. Finally, a nomogram map of the predictive model was constructed to evaluate the prognosis of patients with PDAC. Results: GSEA results of the training set revealed that genes in the training set were significantly related to glycolysis pathway and iconic glycolysis pathway. There were 108 differentially expressed GRGs. Among them, 29 GRGs were closely related to prognosis based on clinical survival time. Risk regression analysis further revealed that there were seven significantly expressed glycolysis related genes. The genes were subsequently used to construct a predictive model. The model had an AUC value of more than 0.85. It was also significantly correlated with survival time. Further expression analysis revealed that CDK1, DSC2, ERO1A, MET, PYGL, and SLC35A3 were highly expressed in PDAC and CHST12 was highly expressed in normal pancreatic tissues. These results were confirmed using immunohistochemistry images of normal and diseases cells. The model could effectively evaluate the prognosis of PDAC patients with different clinical characteristics. Conclusion: The constructed glycolysis-related gene model effectively predicts the occurrence and development of PDAC. As such, it can be used as a prognostic marker to diagnose patients with PDAC.

Five immune-gene-signatures participate in the development and pathogenesis of Kawasaki disease.

OBJECTIVE: To screen for immune genes that play a major role in Kawasaki disease and to investigate the pathogenesis of Kawasaki disease through bioinformatics analysis. METHODS: Kawasaki disease-related datasets GSE18606, GSE68004, and GSE73461 were downloaded from the Gene Expression Omnibus database. Three microarrays were integrated and standardized to include 173 Kawasaki disease samples and 101 normal samples. The samples were analyzed using CIBERSORT to obtain the infiltration of 22 immune cells and analyze the differential immune cells in the samples and correlations. The distribution of the samples was analyzed using principal component analysis (PCA). Immune-related genes were downloaded, extracted from the screened samples and analyzed for differential analysis (different expression genes [DEG]) and weighted gene co-expression network analysis (WGCNA). We constructed coexpression networks, and used the cytohobbe tool in Cytoscape to analyze the coexpression networks and select the immune genes that played a key role in them. RESULTS: Immune cell infiltration analysis showed that B cells naive, T cells CD8, natural killer (NK) cells activated, and so forth were highly expressed in normal samples. T cells CD4 memory activated, monocytes, neutrophils, and so forth were highly expressed in Kawasaki disease samples. PCA results showed a significant difference in the distribution of normal and Kawasaki disease samples. From the screened samples, 97 upregulated and 103 downregulated immune-related genes were extracted. WGCNA analysis of DEG yielded 10 gene modules, of which the three most relevant to Kawasaki disease were red, yellow, and gray modules. They were associated with cytokine regulation, T-cell activation, presentation of T-cell receptor signaling pathways, and NK cell-mediated cytotoxicity. CXCL8, CCL5, CCR7, CXCR3, and CCR1 were identified as key genes by constructing a coexpression network. CONCLUSION: Our study shows that we can distinguish normal samples from Kawasaki disease samples based on the infiltration of immune cells, and that CXCL8, CCL5, CCR7, CXCR3, and CCR1 may play important roles in the development of Kawasaki disease.

Combining Bioinformatics Techniques to Study the Key Immune-Related Genes in Abdominal Aortic Aneurysm.

Approximately 13,000 people die of an abdominal aortic aneurysm (AAA) every year. This study aimed to identify the immune response-related genes that play important roles in AAA using bioinformatics approaches. We downloaded the GSE57691 and GSE98278 datasets related to AAA from the Gene Expression Omnibus database, which included 80 AAA and 10 normal vascular samples. CIBERSORT was used to analyze the samples and detect the infiltration of 22 types of immune cells and their differences and correlations. The principal component analysis showed significant differences in the infiltration of immune cells between normal vascular and AAA samples. High proportions of CD4+ T cells, activated mast cells, resting natural killer cells, and 12 other types of immune cells were found in normal vascular tissues, whereas high proportions of macrophages, CD8+ T cells, resting mast cells, and six other types of immune cells were found in AAA tissues. In the selected samples, we identified 39 upregulated (involved in growth factor activity, hormone receptor binding, and cytokine receptor activity) and 133 downregulated genes (involved in T cell activation, cell chemotaxis, and regulation of immune response mediators). The key differentially expressed immune response-related genes were screened using the STRING database and Cytoscape software. Two downregulated genes, PI3 and MAP2K1, and three upregulated genes, SSTR1, GPER1, and CCR10, were identified by constructing a protein-protein interaction network. Functional enrichment of the differentially expressed genes was analyzed, and the expression of the five key genes in AAA samples was verified using quantitative polymerase chain reaction, which revealed that MAP2K1 was downregulated in AAA, whereas SSTR1, GEPR1, and CCR10 were upregulated; there was no significant difference in PI3 expression. Our study shows that normal vascular and AAA samples can be distinguished via the infiltration of immune cells. Five genes, PI3, MAP2K1, SSTR1, GPER1, and CCR10, may play important roles in the development, diagnosis, and treatment of AAA.

Using Machine Learning Modeling to Explore New Immune-Related Prognostic Markers in Non-Small Cell Lung Cancer.

OBJECTIVE: To find new immune-related prognostic markers for non-small cell lung cancer (NSCLC). METHODS: We found GSE14814 is related to NSCLC in GEO database. The non-small cell lung cancer observation (NSCLC-OBS) group was evaluated for immunity and divided into high and low groups for differential gene screening according to the score of immune evaluation. A single factor COX regression analysis was performed to select the genes related to prognosis. A prognostic model was constructed by machine learning, and test whether the model has a test efficacy for prognosis. A chip-in-chip non-small cell lung cancer chemotherapy (NSCLC-ACT) sample was used as a validation dataset for the same validation and prognostic analysis of the model. The coexpression genes of hub genes were obtained by pearson analysis and gene enrichment, function enrichment and protein interaction analysis. The tumor samples of patients with different clinical stages were detected by immunohistochemistry and the expression difference of prognostic genes in tumor tissues of patients with different stages was compared. RESULTS: By screening, we found that LYN, C3, COPG2IT1, HLA.DQA1, and TNFRSF17 is closely related to prognosis. After machine learning, we constructed the immune prognosis model from these 5 genes, and the model AUC values were greater than 0.9 at three time periods of 1, 3, and 5 years; the total survival period of the low-risk group was significantly better than that of the high-risk group. The results of prognosis analysis in ACT samples were consistent with OBS groups. The coexpression genes are mainly involved B cell receptor signaling pathway and are mainly enriched in apoptotic cell clearance. Prognostic key genes are highly correlated with PDCD1, PDCD1LG2, LAG3, and CTLA4 immune checkpoints. The immunohistochemical results showed that the expression of COPG2IT1 and HLA.DQA1 in stage III increased significantly and the expression of LYN, C3, and TNFRSF17 in stage III decreased significantly compared with that of stage I. The experimental results are consistent with the previous analysis. CONCLUSION: LYN, C3, COPG2IT1, LA.DQA1, and NFRSF17 may be new immune markers to judge the prognosis of patients with non-small cell lung cancer.

A signature of 18 immune-related gene pairs to predict the prognosis of pancreatic cancer patients.

Pancreatic cancer is one of the most lethal malignancies. With the promising prospects conveyed by immunotherapy in cancers, we aimed to construct an immune-related gene pairs (IRGPs) signature to predict the prognosis of pancreatic cancer patients. We downloaded clinical and transcriptional data of pancreatic cancer patients from The Cancer Genome Atlas data set as the training group and GSE57495 data set as the verification group. We filtered immune-related transcriptional data by IMMPORT. With the assistance of lasso penalized Cox regression, we constructed our prognostic IRGPs signature and divided all samples into high-/low-risk groups by receiver operating characteristic curve for further comparisons. The comparisons between high- and low-risk groups including survival rate, multivariate, and univariate Cox proportional-hazards analysis, infiltration of immune cells, and Gene Set Enrichment Analysis (GSEA). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) are facilitated to analyze the proceedings in which our IRGPs signature may involve in. The results revealed that 18 IRGPs were defined as our prognostic signature. The prognostic value of this IRGPs signature was verified from the GSE57495 data set. We further demonstrated the independent prognostic value of this IRGPs signature. The contents of six immune cells between high-/low-risk groups were different, which was associated with the progression of diverse cancers. Results from GO, KEGG, and GSEA revealed that this IRGPs signature was involved in extracellular space, immune response, cancer pathways, cation channel, and gated channel activities. Evidently, this IRGPs signature will provide remarkable value for the therapy of pancreatic cancer patients.

29 immune-related genes pairs signature predict the prognosis of cervical cancer patients.

To screen the key immune genes in the development of cervical cancer, construct immune related gene pairs (IRGPs), and evaluate their influence on the prognosis of cervical cancer. Tumor Genome Atlas (TCGA) database and geo database were downloaded as training set and validation set respectively, and immune related gene data were downloaded from immport. IRGPs model is established by machine learning, and the model is analyzed and evaluated. Using the Uclcan to analyze the immune genes expression in cervical cancer, and to further explore the association with the expression level and the clinical stage and prognosis of cervical cancer. According to the analysis of training set, we identified 29 IRGPs as key gene pairs and constructed the model. The AUC value of the model was greater than 0.9, and the model group survival rate was conspicuous different (P < 0.001). The reliability of the model was confirmed in the validation group. Our IRGPs play an important role in the occurrence and development of cervical cancer, and can be used as a prognostic marker and potential new target of cervical cancer.

The Clinical Role of Changes of Maximum Expiratory Flow at 25% and 50% of Vital Capacity before and after Bronchodilator Reversibility Test in Diagnosing Asthma.

Changes of maximum expiratory flow at 25% and 50% of vital capacity (MEF25 and MEF50, respectively), and predominant parameters indicating small airways function in asthmatics before and after bronchodilator (BD) reversibility test have been less interpreted. Our study aimed to investigate the clinical role of changes of MEF25 and MEF50 before and after BD reversibility test in diagnosing asthma. Forced expiratory volume in the first second (FEV1), MEF25, and MEF50 were measured before and after BD reversibility test in 207 asthmatic patients using standard process. Forty healthy individuals were enrolled as controls. Receiver operating characteristic (ROC) curve was used to assess the diagnostic accuracy of reversibility of MEF25 and MEF50 before and after BD reversibility test (ΔMEF25% and ΔMEF50%, respectively) in diagnosing asthma. Among these functional criteria, ΔMEF25% and ΔMEF50% ≥ 25% performed the best diagnostic performance. The sensitivity, specificity, and accuracy of ΔMEF25% ≥ 25% as an objective diagnostic test for asthma were 63.29%, 87.50%, and 67.21%, and of ΔMEF50% ≥ 25% were 79.23%, 85.00%, and 80.16%, respectively. The area under the ROC curve of the indicators was 0.8203 and 0.9104, respectively. By contrast, an increase in FEV1 ≥ 12% and 200 mL demonstrated a sensitivity of 62.32%, specificity of 82.50%, and accuracy of 65.59% in diagnosing asthma. The changes of MEF25 and MEF50 before and after BD reversibility test may be of additional value in the clinical diagnosis of asthma, with cutoff values of 25% being the most.