Serum level of A-kinase anchoring protein 1, negatively correlated with insulin resistance and body mass index, decreases slightly in patients with newly diagnosed T2DM

Introduction: At present, the number of people suffering from diabetes and obesity is increasing in China, and also all over the world. Researchers found that decreased expression of A-kinase anchoring protein 1 (AKAP1), which was thought to regulate the function and structure of mitochondria, might be related to these two diseases. However, as far as we know, there is no study about the changes of serum AKAP1 protein in these two diseases. Hence we conducted this experiment to study the relationship between serum levels of AKAP1 with T2DM and obesity. Material and methods: There were 261 subjects involved in the experiment, including 130 patients with newly diagnosed T2DM and 131 individuals with normal glucose tolerance (NGT). They were further divided into four groups as follows. Subjects with NGT and normal weight (NW) were assigned to the NGT+NW group, those with NGT but with overweight (OW) or obesity (OB) were assigned to the NGT+OW/OB group, and so on; the rest were divided into the T2DM+NW group and the T2DM+OW/OB group. Serum AKAP1 levels were tested by ELISA method and compared by T-test. Linear regression was applied to discuss independent factors of AKAP1. Multiple logistic regression was used to analyse the relationship between AKAP1 and the prevalence of T2DM. Results: Serum AKAP1 in the NGT+NW group was 1.74 ± 0.42 ng/mL, higher than that in the NGT+OW/OB group, at 1.59 ± 0.41 ng/mL (t = 2.114, p = 0.036), and the T2DM+OW/OB group, at 1.52 ± 0.36 ng/ml (t = 3.219, p = 0.002). A-kinase anchoring protein 1 in 130 subjects with T2DM was lower than that in subjects with NGT, 1.57 ± 0.35 ng/mL vs. 1.67 ± 0.42 ng/mL, t = 2.036, p = 0.043. Liner regression showed that insulin resistance (IR) and body mass index (BMI) were independent factors negatively related to AKAP1: b = –0.019 and –0.032, respectively. Compared to the highest tertile of AKAP1, the prevalence of T2DM was higher in the other two tertiles; OR was 2.207 (1.203, 4.050) and 2.051 (1.121, 3.753), respectively. Conclusions: Serum AKAP1 level decreases slightly in patients with T2DM and obesity. Subjects with lower leve1s of serum AKAP1 are susceptible to T2DM.

Interactive Data Analysis with Next-step Natural Language Query Recommendation

Natural language interfaces (NLIs) provide users with a convenient way to interactively analyze data through natural language queries. Nevertheless, interactive data analysis is a demanding process, especially for novice data analysts. When exploring large and complex SQL databases from different domains, data analysts do not necessarily have sufficient knowledge about different data tables and application domains. It makes them unable to systematically elicit a series of topically-related and meaningful queries for insight discovery in target domains. We develop a NLI with a step-wise query recommendation module to assist users in choosing appropriate next-step exploration actions. The system adopts a data-driven approach to suggest semantically relevant and context-aware queries for application domains of users' interest based on their query logs. Also, the system helps users organize query histories and results into a dashboard to communicate the discovered data insights. With a comparative user study, we show that our system can facilitate a more effective and systematic data analysis process than a baseline without the recommendation module.Comment: 14 pages, 6 figure

TPD52L2 as a potential prognostic and immunotherapy biomarker in clear cell renal cell carcinoma

BackgroundTumor Protein D52-Like 2 (TPD52L2) is a tumor-associated protein that participates in B-cell differentiation. However, the role of TPD52L2 in the pathological process of clear cell renal cell carcinoma (ccRCC) is unclear.MethodsMultiple omics data of ccRCC samples were obtained from public databases, and 5 pairs of ccRCC tissue samples were collected from the operating room. Wilcox, chi-square test, Kaplan-Meier method, receiver operating characteristic curve, regression analysis, meta-analysis, and correlation analysis were used to clarify the relationship of TPD52L2 with clinical features, prognosis, and immune microenvironment. Functional enrichment analysis was performed to reveal the potential pathways in which TPD52L2 participates in the progression of ccRCC. The siRNA technique was used to knockdown in the expression level of TPD52L2 in 786-O cells to verify its effect on ccRCC progression.ResultsFirst, TPD52L2 was found to be upregulated in ccRCC at both mRNA and protein levels. Second, TPD52L2 was significantly associated with poor prognosis and served as an independent prognostic factor. Moreover, TPD52L2 expression was regulated by DNA methylation, and some methylation sites were associated with ccRCC prognosis. Third, TPD52L2 overexpression may participate in the pathological process through various signaling pathways such as cytokine-cytokine receptor interactions, PI3K-Akt, IL-17, Wnt, Hippo signaling pathway, and ECM-receptor interactions. Interestingly, TPD52L2 expression level was also closely related to the abundance of various immune cells, immune checkpoint expression, and TMB. Finally, in vitro experiments confirmed that knocking down TPD52L2 can inhibit the proliferation, migration, and invasion abilities of ccRCC cells.ConclusionThis study for the first time revealed the upregulation of TPD52L2 expression in ccRCC, which is closely associated with poor prognosis of patients and is a potentially valuable therapeutic and efficacy assessment target for immunotherapy

miR-132-3p and KLF7 as novel regulators of aortic stiffening-associated EndMT in type 2 diabetes mellitus

Background: The prevalence of diabetes mellitus has risen considerably and currently affects more than 422 million people worldwide. Cardiovascular diseases including myocardial infarction and heart failure represent the major cause of death in type 2 diabetes (T2D). Diabetes patients exhibit accelerated aortic stiffening which is an independent predictor of cardiovascular disease and mortality. We recently showed that aortic stiffness precedes hypertension in a mouse model of diabetes (db/db mice), making aortic stiffness an early contributor to cardiovascular disease development. Elucidating how aortic stiffening develops is a pressing need in order to halt the pathophysiological process at an early time point. Methods: To assess EndMT occurrence, we performed co-immunofluorescence staining of an endothelial marker (CD31) with mesenchymal markers (α-SMA/S100A4) in aortic sections from db/db mice. Moreover, we performed qRT-PCR to analyze mRNA expression of EndMT transcription factors in aortic sections of db/db mice and diabetic patients. To identify the underlying mechanism by which EndMT contributes to aortic stiffening, we used aortas from db/db mice and diabetic patients in combination with high glucose-treated human umbilical vein endothelial cells (HUVECs) as an in vitro model of diabetes-associated EndMT. Results: We demonstrate robust CD31/α-SMA and CD31/S100A4 co-localization in aortic sections of db/db mice which was almost absent in control mice. Moreover, we demonstrate a significant upregulation of EndMT transcription factors in aortic sections of db/db mice and diabetic patients. As underlying regulator, we identified miR-132-3p as the most significantly downregulated miR in the micronome of db/db mice and high glucose-treated HUVECs. Indeed, miR-132-3p was also significantly downregulated in aortic tissue from diabetic patients. We identified Kruppel-like factor 7 (KLF7) as a target of miR-132-3p and show a significant upregulation of KLF7 in aortic sections of db/db mice and diabetic patients as well as in high glucose-treated HUVECs. We further demonstrate that miR-132-3p overexpression and KLF7 downregulation ameliorates EndMT in high glucose-treated HUVECs. Conclusions: We demonstrate for the first time that EndMT contributes to aortic stiffening in T2D. We identified miR-132-3p and KLF7 as novel EndMT regulators in this context. Altogether, this gives us new insights in the development of aortic stiffening in T2D.</p

Exploring the relationship between abnormally high expression of NUP205 and the clinicopathological characteristics, immune microenvironment, and prognostic value of lower-grade glioma

Nuclear pore complex (NPC) is a major transport pivot for nucleocytoplasmic molecule exchange. Nucleoporin 205 (NUP205)—a main component of NPC—plays a key regulatory role in tumor cell proliferation; however, few reports document its effect on the pathological progression of lower-grade glioma (LGG). Therefore, we conducted an integrated analysis using 906 samples from multiple public databases to explore the effects of NUP205 on the prognosis, clinicopathological characteristics, regulatory mechanism, and tumor immune microenvironment (TIME) formation in LGG. First, multiple methods consistently showed that the mRNA and protein expression levels of NUP205 were higher in LGG tumor tissue than in normal brain tissue. This increased expression was mainly noted in the higher WHO Grade, IDH-wild type, and 1p19q non-codeleted type. Second, various survival analysis methods showed that the highly expressed NUP205 was an independent risk indicator that led to reduced survival time of patients with LGG. Third, GSEA analysis showed that NUP205 regulated the pathological progress of LGG via the cell cycle, notch signaling pathway, and aminoacyl-tRNA biosynthesis. Ultimately, immune correlation analysis suggested that high NUP205 expression was positively correlated with the infiltration of multiple immune cells, particularly M2 macrophages, and was positively correlated with eight immune checkpoints, particularly PD-L1. Collectively, this study documented the pathogenicity of NUP205 in LGG for the first time, expanding our understanding of its molecular function. Furthermore, this study highlighted the potential value of NUP205 as a target of anti-LGG immunotherapy

GNG12 as A Novel Molecular Marker for the Diagnosis and Treatment of Glioma

PurposeGNG12 influences a variety of tumors; however, its relationship with glioma remains unclear. The aim of this study was to comprehensively investigate the relationship between GNG12 and the clinical characteristics and prognosis of glioma patients and reveal the mechanisms causing the malignant process of GNG12.Materials and MethodsWe obtained information on clinical samples from multiple databases. The expression level of GNG12 was validated using a RT-qPCR and IHC. KM curves were used to assess the correlation between the GNG12 expression and OS of glioma patients. An ROC curve was drawn to assess the predictive performance of GNG12. Univariate and multivariate Cox analyses were performed to analyze the factors affecting the prognosis of patients with glioma. GSEA and TIMER databases were used to estimate the relationship between GNG12 expression, possible molecular mechanisms, and immune cell infiltration. CMap analysis was used to screen candidate drugs for glioma. Subsequent in vitro experiments were used to validate the proliferation and migration of glioma cells and to explore the potential mechanisms by which GNG12 causes poor prognosis in gliomas.ResultsGNG12 was overexpressed in glioma patients and GNG12 expression level correlated closely with clinical features, including age and histological type, etc. Subsequently, the K-M survival analysis indicated that the expression level of GNG12 was relevant to the prognosis of glioma, and the ROC curve implied that GNG12 can predict glioma stability. Univariate and multivariate analyses showed that GNG12 represents a risk factor for glioma occurrence. GNG12 expression is closely associated with some immune cells. Additionally, several in vitro experiments demonstrated that down-regulation of GNG12 expression can inhibits the proliferation and migration capacity of glioma cells. Ultimately, the results for the GSEA and WB experiments revealed that GNG12 may promote the malignant progression of gliomas by regulating the cell adhesion molecule cell signaling pathway.ConclusionIn this study, we identified GNG12 as a novel oncogene elevated in gliomas. Reducing GNG12 expression inhibits the proliferation and migration of glioma cells. In summary, GNG12 can be used as a novel biomarker for the early diagnosis of human gliomas and as a potential therapeutic target

Energy-Efficient Algorithm for Broadcasting in Ad Hoc Wireless Sensor Networks

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Identification of key genes and small molecule drugs in osteoarthritis by integrated bioinformatics analysis

Background: Osteoarthritis (OA) is a common joint degenerative disease that can affect multiple joints. Genetic events may play an important regulatory role in the early stages of the disease, but the specific mechanisms have not yet been fully elucidated. The main purpose of this study was to screen for disease-causing hub genes and effective small molecule drugs to reveal the pathogenesis of OA and to develop novel drugs for treatment. Methods: Two gene expression profile datasets, GSE55235 and GSE55457, were integrated and further analyzed. The consistently differentially expressed genes (DEGs) were identified, and functional annotation and pathway analysis of these genes were performed with GO and KEGG. A protein–protein interaction network (PPI) of the DEGs was generated using STRING, and potential small molecule drug screening was performed on the connectivity map (CMap). Results: A total of 158 consistently differentially expressed genes were identified from the two profile datasets. The functions of these DEGs are mainly related to the TNF signaling pathway, osteoclast differentiation, MAPK signaling pathway and so on. The PPI network contains 127 nodes and 1802 edges, and the ten hub genes were interleukin 6 (IL6), vascular endothelial growth factor A (VEGFA)and so on. 7 small molecule drugs were identified as potential interactors with these hubs. Conclusions: This study explains the disorder of expression in the pathological process of OA at transcriptome, which will help to understand the pathogenesis of OA

Gene Expression Profiling of Type 2 Diabetes Mellitus by Bioinformatics Analysis

Objective. The aim of this study was to identify the candidate genes in type 2 diabetes mellitus (T2DM) and explore their potential mechanisms. Methods. The gene expression profile GSE26168 was downloaded from the Gene Expression Omnibus (GEO) database. The online tool GEO2R was used to obtain differentially expressed genes (DEGs). Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using Metascape for annotation, visualization, and comprehensive discovery. The protein-protein interaction (PPI) network of DEGs was constructed by using Cytoscape software to find the candidate genes and key pathways. Results. A total of 981 DEGs were found in T2DM, including 301 upregulated genes and 680 downregulated genes. GO analyses from Metascape revealed that DEGs were significantly enriched in cell differentiation, cell adhesion, intracellular signal transduction, and regulation of protein kinase activity. KEGG pathway analysis revealed that DEGs were mainly enriched in the cAMP signaling pathway, Rap1 signaling pathway, regulation of lipolysis in adipocytes, PI3K-Akt signaling pathway, MAPK signaling pathway, and so on. On the basis of the PPI network of the DEGs, the following 6 candidate genes were identified: PIK3R1, RAC1, GNG3, GNAI1, CDC42, and ITGB1. Conclusion. Our data provide a comprehensive bioinformatics analysis of genes, functions, and pathways, which may be related to the pathogenesis of T2DM

Responses of Fine Roots and Soil N Availability to Short- Term Nitrogen Fertilization in a Broad-Leaved Korean Pine Mixed Forest in Northeastern China

Knowledge of the responses of soil nitrogen (N) availability, fine root mass, production and turnover rates to atmospheric N deposition is crucial for understanding fine root dynamics and functioning in forest ecosystems. Fine root biomass and necromass, production and turnover rates, and soil nitrate-N and ammonium-N in relation to N fertilization (50 kg N ha 21 year 21) were investigated in a temperate forest over the growing season of 2010, using sequential soil cores and ingrowth cores methods. N fertilization increased soil nitrate-N by 16 % (P,0.001) and ammonium-N by 6 % (P,0.01) compared to control plots. Fine root biomass and necromass in 0–20 cm soil were 13 % (4.61 vs. 5.23 Mg ha 21, P,0.001) and 34 % (1.39 vs. 1.86 Mg ha 21, P,0.001) less in N fertilization plots than those in control plots. The fine root mass was significantly negatively correlated with soil N availability and nitrate-N contents, especially in 0–10 cm soil layer. Both fine root production and turnover rates increased with N fertilization, indicating a rapid underground carbon cycling in environment with high nitrogen levels. Although high N supply has been widely recognized to promote aboveground growth rates, the present study suggests that high levels of nitrogen supply may reduce the pool size of the underground carbon. Hence, we conclude that high levels of atmospheric N deposition will stimulate the belowground carbon cycling, leading to changes in the carbon balance between aboveground and underground storage. The implications of the present study suggest tha