Objectives: This study is to investigate whether microRNA (miR)-21 inhibits platelet-derived growth factor-induced human aortic vascular smooth muscle cell (VSMC) proliferation and migration through targeting activator protein-1 (AP-1). Methods: VSMCs were transfected with the miR-21 or miR-21 inhibitor. Cell proliferation was determined using methyl thiazolyl tetrazolium assay. Cell migration was detected by transwell assay. Luciferase reporter assay was used to study the interaction between miR-21 and AP-1. The levels of mRNA were determined using quantitative real-time polymerase chain reaction, while protein expression was measured using Western blotting assay. Results: Low expression of miR-21 significantly inhibited VSMC proliferation, invasion and migration. The mRNA levels and protein expression of α-SMA and AP-1 were down-regulated by low expression of miR-21. In addition, luciferase reporter assay demonstrated that AP-1 might be a direct target gene of miR-21 in VSMC initiation and development. Moreover, up-regulation of AP-1 was critical for miR-21-mediated inhibitory effects on platelet-derived growth factor-induced cell proliferation and migration in human VSMCs. Conclusions: In summary, miR-21 is a key molecule in regulating human VSMC proliferation and migration by targeting AP-1, suggesting that specific modulation of miR-21 in human VSMCs may become an attractive approach for the treatment of proliferative vascular diseases.
microRNA-21; vascular smooth muscle cells; proliferation; migration; activator protein-1; platelet-derived growth factor
On-bead high throughput screening of a medium sized (1000–2000 Da) branched peptide boronic acid (BPBA) library consisting of 46,656 unique sequences against HIV-1 RRE RNA generated peptides with binding affinities in the low micromolar range. In particular, BPBA1 had a Kd of 1.4 µM with RRE IIB, preference for RNA over DNA (27 fold), and selectivity of up to >75 fold against a panel of RRE IIB variants. Structure-activity studies suggest that the boronic acid moiety and “branching” in peptides are key structural features for efficient binding and selectivity for the folded RNA target. BPBA1 was efficiently taken up by HeLa and A2780 cells. RNA-footprinting studies revealed that the BPBA1 binding site encompasses a large surface area that spans both the upper stem as well as the internal loop regions of RRE IIB.
Cracks are an important indicator reflecting the safety status of infrastructures. This paper presents an automatic crack detection and classification methodology for subway tunnel safety monitoring. With the application of high-speed complementary metal-oxide-semiconductor (CMOS) industrial cameras, the tunnel surface can be captured and stored in digital images. In a next step, the local dark regions with potential crack defects are segmented from the original gray-scale images by utilizing morphological image processing techniques and thresholding operations. In the feature extraction process, we present a distance histogram based shape descriptor that effectively describes the spatial shape difference between cracks and other irrelevant objects. Along with other features, the classification results successfully remove over 90% misidentified objects. Also, compared with the original gray-scale images, over 90% of the crack length is preserved in the last output binary images. The proposed approach was tested on the safety monitoring for Beijing Subway Line 1. The experimental results revealed the rules of parameter settings and also proved that the proposed approach is effective and efficient for automatic crack detection and classification.
crack detection; crack classification; subway tunnel; line scan cameras
Agaricus blazei Murrill (ABM), an edible mushroom native to Brazil, is widely used for nonprescript and medicinal purposes. Alcohol liver disease (ALD) is considered as a leading cause for a liver injury in modern dietary life, which can be developed by a prolonged or large intake of alcohol. In this study, the medium composition of ABM was optimized using response surface methodology for maximum mycelial biomass and extracellular polysaccharide (EPS) production. The model predicts to gain a maximal mycelial biomass and extracellular polysaccharide at 1.047 g/100 mL, and 0.367 g/100 mL, respectively, when the potato is 29.88 g/100 mL, the glucose is 1.01 g/100 mL, and the bran is 1.02 g/100 mL. The verified experiments showed that the model was significantly consistent with the model prediction and that the trends of mycelial biomass and extracellular polysaccharide were predicted by artificial neural network. After that, the optimized medium was used for the submerged culture of ABM. Then, alcohol-induced liver injury in mice model was used to examine the protective effect of ABM cultured using the optimized medium on the liver. And the hepatic histopathological observations showed that ABM had a relatively significant role in mice model, which had alcoholic liver damage.
The recent government tendering process being conducted in an electronic way is becoming an inevitable affair for numerous governmental agencies to further exploit the superiorities of conventional tendering. Thus, developing an effective web-based bid evaluation methodology so as to realize an efficient and effective government E-tendering (GeT) system is imperative. This paper firstly investigates the potentiality of employing fuzzy analytic hierarchy process (AHP) along with fuzzy gray relational analysis (GRA) for optimal selection of candidate tenderers in GeT process with consideration of a hybrid fuzzy environment with incomplete weight information. We proposed a novel hybrid fuzzy AHP-GRA (HFAHP-GRA) method that combines an extended fuzzy AHP with a modified fuzzy GRA. The extended fuzzy AHP which combines typical AHP with interval AHP is proposed to obtain the exact weight information, and the modified fuzzy GRA is applied to aggregate different types of evaluation information so as to identify the optimal candidate tenderers. Finally, a prototype system is built and validated with an illustrative example for GeT to confirm the feasibility of our approach.
There is continuously increasing interest in research on multi-sensor data fusion technology. Because Dempster’s rule of combination can be problematic when dealing with conflicting data, there are numerous issues that make data fusion a challenging task, including the exponential explosion, Zadeh Paradox, and one-vote veto. These issues lead to a great difference between the fusion results and real results. This paper applies the idea of analyzing distance-based evidence conflicts, introduces the concept of vector space, and proposes a new cosine theorem-based method of identifying and expressing conflicting data. In addition, this paper proposes a new data fusion algorithm based on the degree of mutual support between beliefs, which is based on the Jousselme distance-based combination rule proposed by Deng et al. Simulation results demonstrate that the presented algorithm achieves great improvements in both the accuracy of identifying conflicting data and that of fusing conflicting data.
wireless sensor network data fusion; keyword; DS theory; evidential conflict
This study is to investigate the expression of miR-21 in nasopharyngeal carcinoma (NPC) cells, and the effect of miR-21 in the biological behavior and expression of B-cell lymphoma 2 (BCL2) in NPC cells. Paired NPC and adjacent non-tumor tissues were obtained from 53 patients who underwent primary surgical resection of NPC tissues. Luciferase reporter assay was performed to test whether BCL2 is a direct target of miR-21. Methylthiazolyl blue tetrazolium assay and colony assay were used to evaluate the effect of miR-21 on NPC cell proliferation. Transwell and wound-healing assays were carried out to test the effect of low expression of miR-21 on cancer cell migration and invasion. QRT-PCR and Western blotting were used to measure the levels of mRNA and protein expression, respectively. Tumor tissues showed a positive correlation between the levels of miR-21 and BCL2 protein expression. Cells transfected with miR-21 inhibitor healed slower compared the control (P < 0.05). In addition, cell migration was notably inhibited by the down-regulation of miR-21 in vitro (P < 0.05). The reduction in miR-21 expression showed a remarkable effect on the biological behavior of NPC cell clone formation (P < 0.05). Low expression of miR-21 by transfection with miRNA expression plasmid led to a decrease in BCL2 expression, which was accompanied by reduced migration and proliferation of the cancer cells. Our results demonstrated that miR-21 inhibitor down-regulated BCL2 expression level, suggesting that BCL2 might be a target gene for the initiation and development of NPC cells.
MicroRNA; miR-21; nasopharyngeal carcinoma; B-cell lymphoma 2
GPBAR1/TGR5 is a novel plasma membrane-bound G protein–coupled bile acid (BA) receptor. BAs are known to induce the expression of inflammatory cytokines in the liver with unknown mechanism. Here we show that without other external stimuli, TGR5 activation alone induced the expression of interleukin 1β (IL-1β) and tumor necrosis factor-α (TNF-α) in murine macrophage cell line RAW264.7 or murine Kupffer cells. The TGR5-mediated increase of pro-inflammatory cytokine expression was suppressed by JNK inhibition. Moreover, the induced pro-inflammatory cytokine expression in mouse liver by 1% cholic acid (CA) diet was blunted in JNK−/− mice. TGR5 activation by its ligands enhanced the phosphorylation levels, DNA-binding and trans-activities of c-Jun and ATF2 transcription factors. Finally, the induced pro-inflammatory cytokine expression in Kupffer cells by TGR5 activation correlated with the suppression of Cholesterol 7α-hydroxylase (Cyp7a1) expression in murine hepatocytes. These results suggest that TGR5 mediates the BA-induced pro-inflammatory cytokine production in murine Kupffer cells through JNK-dependent pathway. This novel role of TGR5 may correlate to the suppression of Cyp7a1 expression in hepatocytes and contribute to the delicate BA feedback regulation.
Dempster-Shafer evidence theory (DSET) is a flexible and popular paradigm for multisource data fusion in wireless sensor networks (WSNs). This paper presents a novel and easy implementing method computing masses from the hundreds of pieces of data collected by a WSN. The transfer model is based on the Mahalanobis distance (MD), which is an effective method to measure the similarity between an object and a sample. Compared to the existing methods, the proposed method concerns the statistical features of the observed data and it is good at transferring multi-dimensional data to belief assignment correctly and effectively. The main processes of the proposed method, which include the calculation of the intersection classes of the power set and the algorithm mapping MDs to masses, are described in detail. Experimental results in transformer fault diagnosis show that the proposed method has a high accuracy in constructing masses from multidimensional data for DSET. Additionally, the results also prove that higher dimensional data brings higher accuracy in transferring data to mass.
mass; Dempster-Shafer evidence theory; Mahalanobis Distance; WSN
We report branched peptide boronic acids (BPBAs) that bind to RRE IIB from an on-bead high-throughput screening of a 3.3.4-library (46,656 compounds). We demonstrate that boronic acids are tunable moieties that afford a novel binding mode towards RNA.
Next-generation sequencing (NGS) technology has rapidly advanced and generated the massive data volumes. To align and map the NGS data, biologists often randomly select a number of aligners without concerning their suitable feature, high performance, and high accuracy as well as sequence variations and polymorphisms existing on reference genome. This study aims to systematically evaluate and compare the capability of multiple aligners for NGS data analysis. To explore this capability, we firstly performed alignment algorithms comparison and classification. We further used long-read and short-read datasets from both real-life and in silico NGS data for comparative analysis and evaluation of these aligners focusing on three criteria, namely, application-specific alignment feature, computational performance, and alignment accuracy. Our study demonstrated the overall evaluation and comparison of multiple aligners for NGS data analysis. This serves as an important guiding resource for biologists to gain further insight into suitable selection of aligners for specific and broad applications.
MicroRNAs (miRNAs) are a class of non-coding regulatory RNAs approximately 22 nucleotides in length that play a role in a wide range of biological processes. Abnormal miRNA function has been implicated in various human cancers including prostate cancer (PCa). Altered miRNA expression may serve as a biomarker for cancer diagnosis and treatment. However, limited data are available on the role of cancer-specific miRNAs. Integrative computational bioinformatics approaches are effective for the detection of potential outlier miRNAs in cancer.
The human miRNA-mRNA target network was reconstructed by integrating multiple miRNA-mRNA interaction datasets. Paired miRNA and mRNA expression profiling data in PCa versus benign prostate tissue samples were used as another source of information. These datasets were analyzed with an integrated bioinformatics framework to identify potential PCa miRNA signatures. In vitro q-PCR experiments and further systematic analysis were used to validate these prediction results.
Using this bioinformatics framework, we identified 39 miRNAs as potential PCa miRNA signatures. Among these miRNAs, 20 had previously been identified as PCa aberrant miRNAs by low-throughput methods, and 16 were shown to be deregulated in other cancers. In vitro q-PCR experiments verified the accuracy of these predictions. miR-648 was identified as a novel candidate PCa miRNA biomarker. Further functional and pathway enrichment analysis confirmed the association of the identified miRNAs with PCa progression.
Our analysis revealed the scale-free features of the human miRNA-mRNA interaction network and showed the distinctive topological features of existing cancer miRNA biomarkers from previously published studies. A novel cancer miRNA biomarker prediction framework was designed based on these observations and applied to prostate cancer study. This method could be applied for miRNA biomarker prediction in other cancers.
miRNA biomarker; Gene expression; miRNA regulatory network; Prostate cancer
The evaluation is an important approach to promote the development of the E-Government. Since the rapid development of E-Government in the world, the E-Government performance evaluation has become a hot issue in the academia. In this paper, we develop a new evaluation method for the development of the E-Government based on the interval-valued intuitionistic fuzzy set which is a powerful technique in expressing the uncertainty of the real situation. First, we extend the geometric Heronian mean (GHM) operator to interval-valued intuitionistic fuzzy environment and proposed the interval-valued intuitionistic fuzzy GHM (IIFGHM) operator. Then, we investigate the relationships between the IIFGHM operator and some existing ones, such as generalized interval-valued intuitionistic fuzzy HM (GIIFHM) and interval-valued intuitionistic fuzzy weighted Bonferoni mean operator. Furthermore, we validate the effectiveness of the proposed method using a real case about the E-Government evaluation in Hangzhou City, China.
Nowadays, as the Internet services increase faster than ever before, government systems are reinvented as E-government services. Therefore, government procurement sectors have to face challenges brought by the explosion of service information. This paper presents a novel method for E-government procurement (eGP) to search for the optimal procurement scheme (OPS). Item-based collaborative filtering and Bayesian approach are used to evaluate and select the candidate services to get the top-M recommendations such that the involved computation load can be alleviated. A trapezoidal fuzzy number similarity algorithm is applied to support the item-based collaborative filtering and Bayesian approach, since some of the services' attributes can be hardly expressed as certain and static values but only be easily represented as fuzzy values. A prototype system is built and validated with an illustrative example from eGP to confirm the feasibility of our approach.
This study was to investigate the molecular mechanisms underlying the 27nt-miRNA-mediated regulation of expression of the endothelial nitric oxide synthase (eNOS) gene.
Cell lines overexpressing 27nt-miRNA or its mutant were established by transfecting the miRNA expression vector into the endothelial cells. eNOS mRNA and protein expression were examined by RT-PCR and Western Blotting, respectively. Luciferase activity reporter system was used to study the target of 27nt-miRNA.
The results showed that overexpression of 27nt-miRNA significantly inhibited eNOS mRNA level and protein expression, and reduced the eNOS transcriptional efficiency. Such inhibitory effects of 27nt-miRNA were attenuated by the sequence mutations in 27nt-miRNA. Interestingly, the transcription factor SP-1 expression was reduced by 27nt-miRNA. Meanwhile, overxpression of SP-1 protein partially restored eNOS expression, and rescued the 27nt-miRNA-mediated reduction of endothelial cell proliferation. Moreover, certain sites in the SP-1 mRNA were found to be the direct target of 27nt-miRNA by a luciferase reporter system.
These results demonstrate that the 27nt-miRNA suppresses eNOS gene expression and SP-1 expression in vascular endothelial cells. The 27nt-miRNA directly target to SP-1 mRNA, thereby contributing to proliferation of endothelial cells.
Autoimmune Type 1 Diabetes (T1D) in humans and NOD mice results from interactions between multiple susceptibility genes (termed Idd) located within and outside the MHC. Despite sharing ~88% of their genome with NOD, including the H2g7 MHC haplotype and other important Idd genes, the closely related NOR strain fails to develop T1D due to resistance alleles in residual genomic regions derived from C57BLKS mice mapping to Chromosomes (Chr.) 1, 2 and 4. We previously produced an NOD background strain developing a greatly decreased T1D incidence due to a NOR-derived 44.31 Mb congenic region on distal Chr. 4 containing disease resistance alleles decreasing the pathogenic activity of autoreactive B and CD4 T cells. In this study a series of subcongenic strains for the NOR-derived Chr. 4 region were utilized to significantly refine genetic loci regulating diabetogenic B and CD4 T cell activity. Analyses of these subcongenic strains revealed the presence of at least two NOR origin T1D resistance genes within this region. A 6.22Mb region between rs13477999 and D4Mit32, not previously known to contain a locus affecting T1D susceptibility and now designated Idd25, was found to contain the main NOR gene(s) dampening diabetogenic B cell activity, with Ephb2 and/or Padi2 being strong candidates as the causal variants. Penetrance of this Idd25 effect was influenced by genes in surrounding regions controlling B cell responsiveness and anergy induction. Conversely, the gene(s) controlling pathogenic CD4 T cell activity was mapped to a more proximal 24.26Mb region between the rs3674285 and D4Mit203 markers.
Rodent; B cells; T cells; Diabetes; Gene Regulation
Clear cell renal cell carcinoma (ccRCC) represents the most invasive and common adult kidney neoplasm. Mounting evidence suggests that microRNAs (miRNAs) are important regulators of gene expression. But their function in tumourigenesis in this tumour type remains elusive. With the development of high throughput technologies such as microarrays and NGS, aberrant miRNA expression has been widely observed in ccRCC. Systematic and integrative analysis of multiple microRNA expression datasets may reveal potential mechanisms by which microRNAs contribute to ccRCC pathogenesis.
We collected 5 public microRNA expression datasets in ccRCC versus non-matching normal renal tissues from GEO database and published literatures. We analyzed these data sets with an integrated bioinformatics framework to identify expression signatures. The framework incorporates a novel statistic method for abnormal gene expression detection and an in-house developed predictor to assess the regulatory activity of microRNAs. We then mapped target genes of DE-miRNAs to different databases, such as GO, KEGG, GeneGo etc, for functional enrichment analysis.
Using this framework we identified a consistent panel of eleven deregulated miRNAs shared by five independent datasets that can distinguish normal kidney tissues from ccRCC. After comparison with 3 RNA-seq based microRNA profiling studies, we found that our data correlated well with the results of next generation sequencing. We also discovered 14 novel molecular pathways that are likely to play a role in the tumourigenesis of ccRCC.
The integrative framework described in this paper greatly improves the inter-dataset consistency of microRNA expression signatures. Consensus expression profile should be identified at pathway or network level to address the heterogeneity of cancer. The DE-miRNA signature and novel pathways identified herein could provide potential biomarkers for ccRCC that await further validation.
Meta-analysis; Network biomarker; MicroRNA; Clear cell renal cell carcinoma; Pathway analysis; Heterogeneity
Rational design of RNA ligands continues to be a formidable challenge, but the potential powerful applications in biology and medicine catapults it to the forefront of chemical research. Indeed, small molecule and macromolecular intervention are attractive approaches but selectivity and cell permeability can be a hurdle. An alternative strategy is to use molecules of intermediate molecular weight that possess large enough surface area to maximize interaction with the RNA structure but are small enough to be cell permeable. Herein, we report the discovery of non-toxic and cell permeable branched peptide (BP) ligands that bind to TAR RNA in the low micromolar range from on-bead high throughput screening of 4,096 compounds. TAR is a short RNA motif in the 5′-UTR of HIV-1 that is responsible for efficient generation of full RNA transcripts. We demonstrate that BPs are selective for the native TAR RNA structure and that "branching" in peptides provides multivalent interaction, which increases binding affinity to RNA.
VPS4B, an AAA ATPase (ATPase associated with various cellular activities), participates in vesicular trafficking and autophagosome maturation in mammalian cells. In solid tumors, hypoxia is a common feature and an indicator of poor treatment outcome. Our studies demonstrate that exogenous or endogenous (assessed with anchorage-independent three-dimensional multicellular spheroid culture) hypoxia induces VPS4B downregulation by the ubiquitin-proteasome system. Inhibition of VPS4B function by short hairpin VPS4B (sh-VPS4B) or expression of dominant negative VPS4B(E235Q) promotes anchorage-independent breast cancer cell growth and resistance to gefitinib, U0126, and genotoxicity. Biochemically, hyperactivation of epidermal growth factor receptor (EGFR), a receptor tyrosine kinase essential for cell proliferation and survival, accompanied by increased EGFR accumulation and altered intracellular compartmentalization, is observed in cells with compromised VPS4B. Furthermore, enhanced FOS/JUN induction and AP-1 promoter activation are noted in EGF-treated cells with VPS4B knockdown. However, VPS4B depletion does not affect EGFRvIII stability or its associated signaling. An inverse correlation between VPS4B expression and EGFR abundance is observed in breast tumors, and high-grade or recurrent breast carcinomas exhibit lower VPS4B expression. Together, our findings highlight a potentially critical role of VPS4B downregulation or chronic-hypoxia-induced VPS4B degradation in promoting tumor progression, unveiling a nongenomic mechanism for EGFR overproduction in human breast cancer.
We report a facile method to prepare a nanoarchitectured lithium manganate/graphene (LMO/G) hybrid as a positive electrode for Li-ion batteries. The Mn2O3/graphene hybrid is synthesized by exfoliation of graphene sheets and deposition of Mn2O3 in a one-step electrochemical process, which is followed by lithiation in a molten salt reaction. There are several advantages of using the LMO/G as cathodes in Li-ion batteries: (1) the LMO/G electrode shows high specific capacities at high gravimetric current densities with excellent cycling stability, e.g., 84 mAh·g−1 during the 500th cycle at a discharge current density of 5625 mA·g−1 (~38.01 C capacity rating) in the voltage window of 3–4.5 V; (2) the LMO/G hybrid can buffer the Jahn–Teller effect, which depicts excellent Li storage properties at high current densities within a wider voltage window of 2–4.5 V, e.g., 93 mAh·g−1 during the 300th cycle at a discharge current density of 5625 mA·g−1 (~38.01 C). The wider operation voltage window can lead to increased theoretical capacity, e.g., 148 mAh·g−1 between 3 and 4.5 V and 296 mAh·g−1 between 2 and 4.5 V; (3) more importantly, it is found that the attachment of LMO onto graphene can help to reduce the dissolution of Mn2+ into the electrolyte, as indicated by the inductively coupled plasma (ICP) measurements, and which is mainly attributed to the large specific surface area of the graphene sheets.
cathode; graphene; Li-ion battery; lithium manganate
Interest in peptides incorporating boronic acid moieties is increasing due to their potential as therapeutics/diagnostics for a variety of diseases such as cancer. The utility of peptide boronic acids may be expanded with access to vast libraries that can be deconvoluted rapidly and economically. Unfortunately, current detection protocols using mass spectrometry are laborious and confounded by boronic acid trimerization, which requires time consuming analysis of dehydration products. These issues are exacerbated when the peptide sequence is unknown, as with de novo sequencing, and especially when multiple boronic acid moieties are present. Thus, a rapid, reliable and simple method for peptide identification is of utmost importance. Herein, we report the identification and sequencing of linear and branched peptide boronic acids containing up to five boronic acid groups by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Protocols for preparation of pinacol boronic esters were adapted for efficient MALDI analysis of peptides. Additionally, a novel peptide boronic acid detection strategy was developed in which 2,5-dihydroxybenzoic acid (DHB) served as both matrix and derivatizing agent in a convenient, in situ, on-plate esterification. Finally, we demonstrate that DHB-modified peptide boronic acids from a single bead can be analyzed by MALDI-MSMS analysis, validating our approach for the identification and sequencing of branched peptide boronic acid libraries.
MALDI-MS; peptide sequencing; matrix; deconvolution; high throughput screen
The advent of next-generation sequencing technologies is accompanied with the development of many whole-genome sequence assembly methods and software, especially for de novo fragment assembly. Due to the poor knowledge about the applicability and performance of these software tools, choosing a befitting assembler becomes a tough task. Here, we provide the information of adaptivity for each program, then above all, compare the performance of eight distinct tools against eight groups of simulated datasets from Solexa sequencing platform. Considering the computational time, maximum random access memory (RAM) occupancy, assembly accuracy and integrity, our study indicate that string-based assemblers, overlap-layout-consensus (OLC) assemblers are well-suited for very short reads and longer reads of small genomes respectively. For large datasets of more than hundred millions of short reads, De Bruijn graph-based assemblers would be more appropriate. In terms of software implementation, string-based assemblers are superior to graph-based ones, of which SOAPdenovo is complex for the creation of configuration file. Our comparison study will assist researchers in selecting a well-suited assembler and offer essential information for the improvement of existing assemblers or the developing of novel assemblers.