Genetic and phenotypic links between obesity and extracellular vesicles

Obesity has a highly complex genetic architecture, making it difficult to understand the genetic mechanisms, despite the large number of discovered loci via genome-wide association studies (GWAS). Omics techniques have provided a better resolution to view this problem. As a proxy of cell-level biology, extracellular vesicles (EVs) are useful for studying cellular regulation of complex phenotypes such as obesity. Here, in a well-established Scottish cohort, we utilized a novel technology to detect surface proteins across millions of single EVs in each individual’s plasma sample. Integrating the results with established obesity GWAS, we inferred 78 types of EVs carrying one or two of 12 surface proteins to be associated with adiposity-related traits such as waist circumference. We then verified that particular EVs’ abundance is negatively correlated with body adiposity, while no association with lean body mass. We also revealed that genetic variants associated with protein-specific EVs capture 2–4-fold heritability enrichment for blood cholesterol levels. Our findings provide evidence that EVs with specific surface proteins have phenotypic and genetic links to obesity and blood lipids, respectively, guiding future EV biomarker research

Recent Progress in Ohmic/Schottky-Contacted ZnO Nanowire Sensors

We review the recent progress of zinc oxide (ZnO) nanowire sensors with ohmic-contacted and Schottky-contacted configurations and the enhancement of the performances of Schottky-contacted ZnO NW sensors (SCZNSs) by the piezotronic effect. Comparing with the traditional ohmic-contacted ZnO NW sensors (OCZNSs), the SCZNSs have higher sensitivities and faster responses controlled by the barrier height at the metal-semiconductor (M-S) interface. The piezotronic effect was applied to tune the Schottky barrier height (SBH) with the strain-induced piezoelectric polarization charges at the interface of the M-S contact. The piezotronic effect can thus improve the detection limitation, sensitivity, and response time of the SCZNSs in different applications, such as UV detection, gas and bio/chemical sensing. These piezotronic-enhanced SCZNSs may find potential applications in human-machine interfacing and flexible electronics skin technologies

Comparison of Proteome Differences between Whole Milk and Skim Milk Based on High-throughput Quantitative Proteomics

Protein is an important nutrient in bovine milk, however, it is not clear about the effect of defatting on the protein content of bovine milk. In this paper, quantitative proteomics labeled with TMT (tandem mass tags) was used to analyze the proteome in whole milk and skim milk to investigate the effect of skimming on milk proteins. A total of 1352 proteins were identified in whole milk and skim milk, and 199 differentially expressed proteins were screened. Compared with whole milk, 67 proteins were up-regulated and 132 proteins were down-regulated after defatting. Among the major active proteins in bovine milk, κ-casein decreased in relative content after defatting, while β-lactoglobulin and lactoferrin increased in relative content after defatting. α-lactalbumin, αs1-casein, αs2-casein, β-casein, bovine serum protein and lactoperoxidase did not differ significantly in relative content. The relative levels of butyrophilin and lactadherin in milk fat globule membrane proteins decreased after defatting. Skimming also had effects on cytoskeleton, metabolism-related proteins in milk, changing the quality and nutritional value of the milk. The analysis of protein in whole and skim milk clarified the effect of skimming on bovine milk protein, which could provide a reference for the development of infant dairy products and the purchase of milk with different fat content by consumers

TNFRSF10C methylation is a new epigenetic biomarker for colorectal cancer

Background Abnormal methylation of TNFRSF10C was found to be associated with different types of cancers, excluding colorectal cancer (CRC). In this paper, the performance of TNFRSF10C methylation in CRC was studied in two stages. Method The discovery stage was involved with 38 pairs of CRC tumor and paired adjacent non-tumor tissues, and 69 pairs of CRC tumor and paired adjacent non-tumor tissues were used for the validation stage. Quantitative methylation specific PCR (qMSP) method and percentage of methylated reference (PMR) were used to test and represent the methylation level of TNFRSF10C, respectively. A dual-luciferase reporter gene experiment was conducted to evaluate the promoter activity of TNFRSF10C fragment. Results A significant association of TNFRSF10C promoter hypermethylation with CRC was found and validated (discovery stage: 24.67 ± 7.52 vs. 3.36 ± 0.89; P = 0.003; validation stage: 31.21 ± 12.48 vs. 4.52 ± 1.47; P = 0.0005). Subsequent analyses of TCGA data among 46 pairs of CRC samples further confirmed our findings (cg23965061: P = 4E − 6; cg14015044: P = 1E − 7). Dual-luciferase reporter gene assay revealed that TNFRSF10C fragment was able to significantly promote gene expression (Fold change = 2.375, P = 0.013). Our data confirmed that TNFRSF10C promoter hypermethylation can predict shorter overall survival of CRC patients (P = 0.032). Additionally, bioinformatics analyses indicated that TNFRSF10C hypermethylation was significantly associated with lower TNFRSF10C expression. Conclusion Our work suggested that TNFRSF10C hypermethylation was significantly associated with the risk of CRC

miR-3666 inhibits lung cancer cell proliferation, migration and invasion by targeting BPTF

Our previous study suggested that BPTF overexpression was observed in lung adenocarcinoma, and closely associated with advanced clinical stage, more metastatic lymph nodes, present distant metastasis, low histological grade and poor prognosis. Down-regulation of BPTF inhibited lung adenocarcinoma cells proliferation and promoted lung adenocarcinoma cells apoptosis. The purpose of this study is to identify valuable microRNAs (miRNAs), which target BPTF to modulate lung adenocarcinoma cells proliferation. In our results, we found that miR-3666 was notably reduced in lung adenocarcinoma tissues and cell lines. By using miR-3666 mimics, cells proliferation, migration, and invasion were suppressed by miR-3666 overexpression, while were enhanced by reduction of miR-3666. Moreover, bioinformatics analysis using Targetscan database and miRanda software suggested a putative targeting site in BPTF 3â -UTR. Furthermore, we verified that miR-3666 directly targeted to 3â -UTR of BPTF by luciferase reporter assay. Overexpression of miR-3666 negatively regulated protein expression of BPTF by western blot. Finally, PI3K/AKT and EMT was demonstrated to be inhibited by miR-3666 overexpression in lung cancer cells. In conclusion, our data indicate that miR-3666 might play an essential role in cell proliferation, migration and invasion by targeting BPTF and partly inhibited PI3K/AKT and EMT signaling pathways in human lung cancers.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Research on Soft Sensing Modeling Method Based on the Algorithm of Adaptive Affinity Propagation Clustering and Bayesian Theory

Abstract: The industrial data has the characteristic of clustering and migrating with the operating point. The accuracy and generalization ability of the single-model prediction are poor because of the large amount of information lost in single-model modeling. In order to overcome these problems, a modeling method of multimodel soft sensor was proposed based on adaptive affinity propagation clustering (ADAP) and Bayesian filtering. ADAP algorithm was utilized in this method to realize the clustering and tracking of multiple operating points. The sub-models of various types of samples were established utilizing Bayesian filtering method, and the joint output and estimation were carried out based on the model of the subclass of current working point. The soft sensor models of CO and CO2 in PX oxidation side reaction were utilized in the method. The simulation results show that the estimation and generalization ability of soft sensing model is significantly improved by the method. Copyright © 2013 IFSA

Genome-Wide Identification and Characterization of MADS-box Family Genes Related to Floral Organ Development and Stress Resistance in Hevea brasiliensis Müll. Arg.

Elucidating the genetic mechanisms associated with the transition from the vegetative to reproductive phase in the rubber tree has great importance for both theoretical guidance and practical application to yield genetic improvement. At present, many transcription factors, including those that belong to the MADS-box gene family, have been revealed to have roles in regulating the transition from vegetative growth to reproductive growth. However, to the best of our knowledge, the Mad-box gene family from H. brasiliensis Müll. Arg. has not been characterized in detail. To investigate members of the HbMADS-box gene family associated with floral organ and inflorescence development in H. brasiliensis, we performed genome-wide identification and analysis of the MADS-box gene family related to flower development in H. brasiliensis, and a total of 20 MADS-box genes were newly identified in the H. brasiliensis genome. Expression profiling revealed that HbMad-box genes were differentially expressed in various tissues, which indicated that HbMad-box genes may exert different functions throughout the life cycle. Additionally, 12 genes (HbSEP, HbAGL9.1, HbAGL9.2, HbCMB1, HbCMB1-L, HbAGL6, HbAGL8, HbAP1, HbAG, HbDEFL, HbTT16, and HbPADS2) were found to be associated with the differentiation of flower buds and may be involved in flower development in H. brasiliensis. All of these floral-enriched HbMADS-box genes were regulated by hormone, salt, cold, high-temperature, and drought stresses. The present study is the first to carry out the genome-wide identification and analysis of the MADS-box gene family related to flower development in H. brasiliensis, and 20 new HbMad-box genes were identified in H. brasiliensis. Most of the newly identified HbMad-box genes were found to be associated with the differentiation of flower buds and may be involved in flower development in H. brasiliensis. Our results demonstrated that HbMad-box genes may be multifunctional regulators that have roles in distinct aspects of development, and are mainly involved in the maintenance of floral organ and inflorescence development

Simulation on the effectiveness of carbon emission trading policy: A system dynamics approach

As a flexible market mechanism based on the control of total quantity, the carbon emission trading system aims to achieve economic development while reducing carbon emissions and energy consumption. How to improve the effectiveness of carbon emission trading (CET) policy and achieve the established emission reduction targets have attracted widespread attention from scholars. Taking Guangdong Province as an example, this paper constructed a system dynamics (SD) model to investigate the interaction between internal factors of CET system and simulated the effectiveness of CET policy from 2016-2026. The results indicate that (1) Relative errors between historical data and simulated data are controlled within 5%, which indicates that the system model is suitable to simulate real system. (2) The average sensitivity of the quota variation rate, paid ratio and penalty coefficient are 0.42, 0.56 and 0.29, respectively, indicating that these three parameters can be identified as leverage parameters affecting the efficiency of the CET policy. (3) A single type of policy is difficult to achieve emission reduction targets. The policy portfolio scenario will achieve the reduction target in Thirteenth Five-Year plan of Guangdong, that is, the total amount of quota decreases by 0.5% per year, the paid ratio rises 2% in that ratio per year, and the penalty coefficient is triple the carbon price

Pan-Cancer Analysis of TLE3 Revealed Its Value in Tumor Microenvironment and Prognosis

Background. Transducin-like enhancer of split 3 (TLE3), a member of the TLE gene family, is related to tumor genesis and progression. However, whether TLE3 played a crucial role in the whole pan-cancer remained unknown. Methods. Comprehensive analysis of TCGA, GEO, and GTEx data with an online tool, and R language was performed to explore the relationship of TLE3 expression between prognosis, gene mutation, protein phosphorylation, DNA methylation, tumor microenvironment, and related pathways in 33 tumors. Results. TLE3 was high-expressed in most tumors, and TLE3 expression and the prognosis of some tumor types were significantly correlated. The level of TLE3 expression in 33 cancer types was closely associated with DNA methylation. High-level phosphorylation sites of Tle3, such as S267 and S217, may promote cancers. In terms of the tumor microenvironment, TLE3 affected a wide variety of cancers, especially PRAD and LIHC, and TLE3 may act on them via immune-related pathways. Conclusions. The current work provided the first comprehensive investigation of TLE3 in a pan-cancer study, highlighting the role of TLE3 in the tumor immune microenvironment, and also determined the potential of TLE3 as a prognostic, immunotherapy response, and diagnostic biomarker in many cancers. However, the present results were preliminary and required further validation as this study was based on bioinformatics analyses