We then carried out a follow up of the antibody responses in villagers who experienced clinical malaria during the 5-month transmission season, using archived fingerprick sera collected monthly, and when available, sera on the day of the clinical malaria episode. Transient

fluctuations were observed, with in some cases boosting of a pre-existing response (see a representative example in Figure 9A), in others a decrease in antibodies (idem Figure 9B) or evidence of a short-lived response (idem Figure 9C). This was also observed in children experiencing multiple clinical episodes during that same time period (idem Figure 9D). In nine out of 10 subjects in whom peripheral blood parasites

collected at diagnosis of the clinical malaria episode were genotyped, the three allelic families were detected, and one individual harboured only Fedratinib cost 2 allelic families. In all 10 cases, infection with an allele against which there was no evidenced pre-existing response did not elicit any long lasting novel antibody specificity. Figure 9 Temporal fluctuation of MSP1 block2- specific buy EPZ015938 IgG during the 1998 rainy season. Antibodies were assayed on 16 pools of biotinylated peptides (sequence and composition of the pools described in Table 5). Typical individual patterns are shown, with the dates of blood sampling shown on each graph. A) Transient boosting of a pre-existing response in a 14 y old subject (code 11/21), who had a clinical malaria attack on 29/10/98. B) Transient loss of a pre-existing response in a 5 y old child (code 8/15), who had a clinical malaria attack on 28/08/98. C) Transient acquisition of a novel specificity

in a 9.5 y old child (code 02/04), selleck chemicals who had a clinical malaria on 10/09/98. D) Transient changes in a 5 y old child (code 03/18), who experienced three successive clinical episodes during that time period on 17/09/98, 22/10/98 and 11/12/98. For each cinical episode, an antimalarial treatment was administered to the patient on the day of diagnosis. Long term temporal analysis of the response to MSP1-block2 To analyse antibody patterns over several years, we used archived systematic blood samples collected during the longitudinal survey. Confirming a previous study in this village [27], once acquired, the response to MSP1-block2 was essentially fixed over time. A typical example is shown in Figure 10, where a 6-year follow-up was carried out on child 01/13, starting at 6 months of age. The child had been exposed to a mean of 200 infected bites each year over the six years. A single peptide pool was recognised by this child from the age of 2.5 years onwards (Figure 10A). The intensity of the signal fluctuated subsequently, including a drop during malaria attacks [e.g.

Antonie van Leeuwenhoek 2002, 82:341–352.CrossRefPubMed 19. de Vos WM, Bron PA, Kleerebezem M: Post-genomics of lactic acid bacteria and other food-grade bacteria to discover gut functionality. Current Opinion in Biotechnology 2004, LY2109761 cell line 15:86–93.CrossRefPubMed 20. Le Breton Y, Pichereau

V, Sauvageot N, Auffray Y, Rince A: Maltose utilization in Enterococcus faecalis. Journal of Applied Microbiology 2005, 98:806–813.CrossRefPubMed 21. Andersson U, Radstrom P: Beta-Glucose 1-phosphate-interconverting enzymes in maltose- and trehalose-fermenting lactic acid bacteria. Environmental Microbiology 2002, 4:81–88.CrossRefPubMed 22. Haller D, Colbus H, Gänzle M, Scherenbacher P, Bode C, Hammes W: Metabolic and functional properties of lactic acid bacteria in the gastro-intestinal ecosystem: a comparative in vitro study between bacteria of intestinal and fermented food origin.

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Dis 1995, 8:151–157.CrossRef 26. Jones BV, Begley Mi, Hill C, Gahan CGM, Marchesi BI 2536 mw JR: Functional and comparative metagenomic analysis of bile salt hydrolase activity in the human gut microbiome. Proc Natl Acad Sci U S A 2008,105(36):13580–5.CrossRefPubMed 27. Denou E, Pridmore RD, Berger B, Panoff J-M, Arigoni F, Brussow H: Identification of Genes Associated with the Long-Gut-Persistence Phenotype of the Probiotic Lactobacillus johnsonii Strain NCC533 Using a Combination of Genomics and Transcriptome Analysis. J Bacteriol 2008, 190:3161–3168.CrossRefPubMed 28. Pfeiler EA, Azcarate-Peril MA, Klaenhammer TR: Characterization of a Novel Bile-Inducible Operon Encoding a Two-Component Regulatory System in Lactobacillus acidophilus. J Bacteriol 2007, 189:4624–4634.CrossRefPubMed 29. Kok J: Genetics of the proteolytic system of lactic acid bacteria. FEMS Microbiol Rev 1990,7(1–2):15–42.PubMed 30. Savijoki K, Ingmer H, Varmanen P: Proteolytic systems of lactic acid bacteria. Appl Microbiol Biotechnol 2006,71(4):394–406.CrossRefPubMed 31. Sridhar VR, Hughes JE, Welker DL, Broadbent JR, Steele JL: Identification of Endopeptidase Genes from the Genomic Sequence of Lactobacillus helveticus CNRZ32 and the Role of These Genes in Hydrolysis of Model Bitter Peptides. Appl Environ Microbiol 2005, 71:3025–3032.CrossRefPubMed 32.

Subsequently, the AGS cells were morphologically examined using a fluorescent

microscope (Olympus IX81, Olympus, Japan) under a 40x objective. RNA isolation, quality control and cDNA synthesis Total RNA was isolated using RNeasy Mini selleck screening library (Qiagen GmBH, Germany) according to the manufacturer’s protocol. RNA concentration and quality were determined using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, USA) and Agilent 2100 Bioanalyzer (Agilent Technologies, USA). For real-time PCR, cDNA was prepared using a First-Strand cDNA Synthesis Kit (GE Healthcare, USA), according to standard protocol. The Illumina TotalPrep RNA amplification Kit (Ambion Inc., USA) was used to amplify RNA for hybridization on Illumina BeadChips. selleck To synthesize first strand cDNA by reverse transcription, we used total RNA from each sample collected above. Following the second strand cDNA synthesis and cDNA purification steps, the in vitro transcription to synthesize cRNA was prepared overnight for 12 h. Real-time PCR analysis Each sample was tested in triplicate by real-time quantitative PCR (rt-PCR) on the 7900HT

Fast Real-Time PCR system (Applied Biosystems). Expression of IL-8 was analyzed using custom IL-8 primer and probe (part no: 4331348, assay ID: Hs00174103_m1, Applied Biosystems). Mean cycle time (Ct) was calculated, and the comparative Ct-method [84] was utilized to control for background gene expression using reference gene GADPH (part no: 4333764F, Applied Biosystems). ELISA IL-8 protein was measured in the cell culture supernatant by the Quantikine Human CXCL8/IL-8 enzyme linked immunosorbent assay (ELISA) kit, according to manufacturer’s instructions (R&D Systems, USA). The test samples were not diluted. Serial dilutions of recombinant human IL-8 were used for

standard curves. The optical density of the wells was determined using a microtitre plate reader (Varioskan, Thermo Scientific, USA) set to a wavelength of 450 nm, with wavelength correction set to 540 nm cDNA oligonucleotide microarray analysis The gene expression profiles were measured using Illumina Human HT-12 v3 Expression BeadChip (Illumina, USA), which enables genome-wide expression analysis (48 800 transcripts, corresponding to approximately 37 800 genes) of 12 samples in parallel on a single microarray. 35967 of the probes were designed 4-Aminobutyrate aminotransferase using the RefSeq (build 36.2, release 22) library and 12.837 probes were derived from the UniGene (build 199) database [85, 86]. Bioinformatics and statistics R/BioConductor [87, 88], with the package Beadarray [82], were used for preprocessing of the microarray text data from BeadStudio. Spatial artifacts were removed using BASH [89] before the expression data were log2-transformed and quantile normalized. Moderated t-tests [90] were then performed for each probe on the array to test whether the differential expression between the starting point and the later time points was significant.

B. Flow cytometry analysis demonstrated that significantly more endothelial cells were positive for fluorescence when incubated with PknD sensor-coated microspheres compared to BSA-coated microspheres (7.7% vs. 0.6%; P = 0.0003). Cell counts are presented as mean ± standard deviation. C. Histograms show that discrete fluorescent-positive populations are evident in the cells inoculated with PknD sensor-coated microspheres, indicating that cell populations took up multiple quantities of microspheres. D. Microspheres were again pre-incubated with either custom anti-PknD

serum or naïve serum, followed by inoculation onto endothelial cells. Pre-incubation with anti-PknD (1:250) significantly reduced the population of cells AZD0156 which were positive for fluorescent microspheres, compared to naïve serum, as is indicated in the figure by a horizontal bar (P = 0.001). Pre-incubation with anti-PknD (1:1250) had no effect on internalization, when compared to untreated cells (P = 0.07). M. tuberculosis

Apoptosis Compound Library pknD mutant exhibits reduced adherence to a component of the host ECM Since M. tuberculosis PknD sensor is homologous to proteins that bind to the host ECM, we measured the adherence of M. tuberculosis pknD mutant to major components of the ECM using laminin, collagen, and fibronectin matrices generated in vitro. The M. tuberculosis pknD mutant demonstrated a reduction in association with the in vitro laminin matrix (P = 0.001), but not to collagen or fibronectin matrices (Figure 4A). Endothelia secrete laminin to generate a matrix for adhesion and maintenance of cell structure. To determine whether PknD protein associates with laminin secreted by brain endothelia, PknD-coated microspheres were incubated with HBMEC and stained for host laminin. It was observed that, relative to BSA-coated microspheres, PknD-coated microspheres

were more likely to localize with the laminin-stained HBMEC (Figure 4B-C). Figure 4 M. tuberculosis PknD sensor domain interacts with host laminin. A. M. tuberculosis WT and pknD mutant were incubated in wells coated with components Sucrase of the extracellular matrix (laminin, fibronectin, and collagen). The pknD mutant demonstrated a 2-fold reduction in adhesion to the laminin matrix (P = 0.001), while not exhibiting significantly reduced adhesion to fibronectin or collagen. CFU counts are represented as mean ± standard deviation. N.S. = not significantly different. B and C. Coated microspheres were incubated with HBMEC, followed by immunostaining for laminin. Microspheres coated with PknD sensor (panel C) associated with the periphery of laminin staining more than those coated with BSA (panel B), which were evenly distributed throughout the field of view. Invasion of brain endothelial cells by M.

Pain 150:451–457. doi:10.​1016/​j.​pain.​2010.​05.​019 CrossRef Tuomi K, Eskelinen L, Toikkanen J, Järvinen E, Ilmarinen J, Klockars, M (1991) Work load and individual factors affecting work ability among aging municipal employees. Scand J Work Environ Health 17(suppl1):128–134. Retrieved from: http://​www.​sjweh.​fi/​show_​abstract.​php?​abstract_​id=​1743

Viikari-Juntura E, Rauas S, Martikainen R (1996) Validity of self-reported physical work load in epidemiological studies on musculoskeletal disorders. Scand J Work Environ Health 22:251–259. doi:10.​5271/​sjweh.​139 CrossRef Wiesel SW (ed) (2011) If the Treatment see more Effects Are So Modest, Why Do My Patients Usually Get Better?. this website The BackLetter 26:75″
“Introduction The symptoms that compose the hand-arm vibration syndrome (HAVS) have previously been extensively described and are referred to as mainly vascular, neurological and muscular (Chetter et al. 1998; Heaver et al. 2011). The most prominent symptoms

are made up of vascular and peripheral neurological disorders (i.e., sensorineural), where the latter symptoms are described as the most frequent and also the most resistant to recovery (Chetter et al. 1998; Futatsuka et al. 1989; Koskimies et al. 1992). The HAVS is a complex condition, and it has been suggested that all involved signs and symptoms are not yet discovered (Griffin 2008). Several symptoms associated with or possibly associated with the syndrome have been explored in previous studies, and as early as the beginning of the twentieth century, the symptom of tremor was mentioned among vibration-exposed workers (Bylund et al. 2002; Futatsuka et al. 2005; Griffin 1997). However, the studies investigating tremor among HAV-exposed workers are few, and one of the studies was conducted on only women (Bylund et al. 2002; Futatsuka et al. 2005). Thus, little is known about tremor as a symptom possibly associated

with prolonged HAV, and to our knowledge, there has been no previous study on quantitative measurements of tremor in HAV-exposed workers. According to Deuschl et al., oxyclozanide peripheral mechanisms may cause some types of tremor (Deuschl et al. 1996). It has been observed that patients with acquired and hereditary peripheral neuropathies exhibit differing forms of tremor and more often than compared to a control group (Elble 2009; Wasielewska et al. 2013), but no exact pathophysiological pathways have been revealed (Elble 2009). The various neurological disorders in the HAVS are not clearly defined, and their form is poorly understood (Griffin 2008). Neurological symptoms including tremor can be disturbing and also potentially disabling. In view of these facts, and also because of clinical observations of tremor in HAV-exposed patients, further exploration is desirable.

Branch lengths are drawn to scale. Phylogenetic analyses of recA partial gene sequences Our phylogenetic inferences based on recA partial gene sequences yielded clearer insights into the branching order of the members of the salivarius group (Figure 3), which were clustered together in all the ML and MP bootstrap replicates, while the two S. vestibularis strains formed a united clade in all the replicates, and the three S. thermophilus strains branched together in the vast majority of the bootstrap replicates. The monophyly of the S. salivarius species was

recovered in 98% of the MP bootstrap replicates, although ML-based phylogenetic inferences could not discriminate between paraphyletic and monophyletic S. salivarius clades (52% selleckchem vs. 48% of the bootstrap replicates, respectively). Like the secA-based phylogenetic inferences, the analyses derived from the recA gene sequences strongly supported a sister-relationship between the S. vestibularis and S. thermophilus species. The node comprising these two species was robust and was recovered in all the ML and MP bootstrap replicates. Figure 3 Branching order of members of the salivarius group as inferred from ML and MP analyses of recA partial gene sequences (798 positions; Protease Inhibitor Library 309 variable,

289 phylogenetically informative). The best ML tree computed with PHYML 3.0 under the GTR+Γ4+I model of nucleotide substitution is shown here. Bootstrap support for the major nodes is indicated over the corresponding nodes: ML values left, MP values right. Asterisks denote nodes that were retrieved in all the bootstrap replicates. Dashes indicate nodes that were retrieved in fewer than 50% of the bootstrap replicates. Streptococcal species belonging to the salivarius group are shown in orange (S. salivarius), blue (S. vestibularis) or green (S. thermophilus). Other streptococcal species shown in black were outgroups. Branch lengths are drawn to scale. Phylogenetic analyses of 16S rRNA-encoding gene sequences Building on the phylogeny published by Kawamura et al. [2], we reinvestigated the branching order among the salivarius streptococci using

16S rRNA-encoding gene sequences and expanded taxon sampling within the salivarius group. As can be seen in Figure 4, even though the salivarius group Amisulpride was recovered in all the bootstrap replicates, the branching order within this taxonomic entity was not well defined. Of the three species, only S. thermophilus composed a monophyletic assemblage. The other two, S. vestibularis and S. salivarius, were not resolved. This contrasted with the results obtained by Kawamura et al. [2], who reported that the S. vestibularis and S. thermophilus species branched together with strong bootstrap support. It should be noted, however, that the 16S rRNA-encoding gene sequences exhibited almost no variability among salivarius streptococci.

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8. Nassiopoulou AG, Grigoropoulos S, Gogolides E, Papadimitriou D: Visible luminescence from one- and two-dimensional silicon structures produced by conventional lithographic and reactive ion etching techniques. Appl Phys Let 1995, 66:1114.CrossRef 9. Dresselhaus MS, Lin YM, Oded R, Black MR, Kong J, Dresselhaus GN: Springer Handbook of Nanotechnology. Edited by: Bhushan B. Berlin: Springer; 2010:99. 10. Peng K, Fang H, Hu J, Wu Y, Zhu J, Yan Y, Lee S: Metal-particle-induced, highly localized site-specific etching of Si and formation of single-crystalline Si nanowires in aqueous fluoride solution. Chemistry (Weinheim an der Bergstrasse, Germany) 2006, 12:7942–7947.CrossRef 11. Hochbaum AI, Gargas D, Hwang YJ, Yang P: Single crystalline mesoporous silicon nanowires. Selleck BMS-936558 Nano Lett 2009, 9:3550–3554.CrossRef 12. Zhong X, Qu Y, Lin YC, Liao L, Duan X: Unveiling the drug discovery formation pathway of single crystalline porous silicon nanowires. ACS Appl Mater Interfaces 2011, 3:261–270.CrossRef 13. Qu Y, Liao L, Li Y, Zhang H, Huang Y, Duan X: Electrically conductive and optically active porous silicon nanowires. Nano Lett 2009, 9:4539–4543.CrossRef 14. Lin L, Guo S, Sun X, Feng J, Wang Y: Synthesis and photoluminescence properties of porous silicon nanowire arrays. Nano Res Lett 2010, 5:1822–1828.CrossRef 15. Voigt F, Sivakov V, Gerliz V, Bauer GH, Hoffmann

B, Radnoczi GZ, Pecz B, Christiansen S: Photoluminescence of samples produced by electroless wet chemical etching: between silicon nanowires and porous structures. Phys Status Solidi A 2011, 208:893–899.CrossRef 16. Chen H, Zou R, Chen H, Wang N, Sun Y, Tian Q, Wu J, Chen Z, Hu J: Lightly doped single crystalline porous Si nanowires with improved optical and electrical properties. J Mater Chemistry 2011, 21:801.CrossRef 17. He H, Liu C, Sun L, Ye Z: Temperature-dependent photoluminescence properties of porous silicon nanowire arrays. Appl Phys Let 2011, 99:23106.CrossRef 18. Artoni P, Irrera A, Iacona F, Pecora EF, Franzo G, Priolo F: Temperature dependence and aging effects on silicon nanowires photoluminescence. Opt Express 2012, 20:1483–1490.CrossRef 19. To

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However when counting just confident protein identifications (two or Selumetinib nmr more peptide hits) this increase is less pronounced. Looking at confident protein identifications with PPS Silent®, the total number of outer membrane proteins increased from 38 to 42. However, PPS Silent® appears to enhance detection of non-membrane proteins over outer membrane proteins as the proportion of non-membrane proteins increased marginally, while the proportion of outer membrane proteins decreased in the samples

subjected to PPS Silent®. This suggests that outer membrane proteins are relatively resistant to solubilising in PPS Silent®, while non-membrane associated proteins solubilise more readily. When comparing the data generated from this study with previously published work by Coldham & Woodward, more OMPs (total of 54) were identified here in comparison to 34 reported in their study. However, there were proteins that were not identified by using the LPI™ FlowCell. Coldham & Woodward[20] identified 34 outer membrane proteins using a method based on fractionating the whole cell lysate into its various intracellular parts coupled with KPT-330 research buy two dimensional HPLC-mass spectrometry (2D-LC-MS/MS). Of the 34 outer membrane proteins identified,

just over half (18) were found in our dataset. Overall there were 36 S. typhimurium OMPs identified in our dataset that were not reported previously [20] (Additional DNA ligase file 2). Some of these differences may be due to the use of different strains and variation in microbial culture

conditions between both studies which will be reflected in their protein expression profiles. In addition, since the method used by Coldham & Woodward relied on multiple fractionation steps of the whole cell lysate, potential loss of outer membrane proteins, especially lower abundant ones could have occurred at each step in their workflow. Furthermore, it has been reported that results generated from mass spectrometry vary depending on the database search algorithm used to identify proteins [22]. The work carried out by Coldham &Woodward used the search algorithm SEQUEST, while in this study the search algorithm MASCOT was used. Therefore, the differences observed between the two methods could also be attributed to the database search algorithms and parameters used. Previous work carried out by Molloy et al [13] identified 30 outer membrane proteins from Escherichia coli (E. coli) which is closely related to S. Typhimurium using a method based on the enrichment of outer membrane proteins using sodium carbonate washes and incorporating the detergent ASB-14 to aid in solubilising them prior 2D GE. This study manages to identify 15 of the 30 outer membrane proteins. A further 15 outer membrane proteins reported by Molloy et al were not seen in this study while 39 outer membrane proteins were identified in this study that was not reported by Molloy et al.

The resulting PCR product Trametinib ic50 was digested with isocaudarner SpeI and XbaI and ligated into XbaI-digested pRE112 to yield plasmid pYA4680. In addition, undigested, agarose-gel purified PCR product was electroporated into the cat-sacB Salmonella strains carrying plasmid pKD46 and spread onto LB plates containing 5% sucrose to select for

deletion of the cat-sacB cassette. Chloramphenicol-sensitive isolates were verified as ΔrecA62 by PCR using primers P15 and P16 (ΔrecA62: 1360 bp; wt: 2412 bp). S. Typhimurium strains χ9833 and χ9939 were constructed by this method (Table 2). For construction of a ΔrecA62 mutant of S. Typhi, wild-type strain Ty2 was mated with E. coli strain χ7213(pYA4680). Transconjugants were selected on LB plates containing chloramphenicol, followed by counterselection on sucrose plates as described above. The resulting ΔrecA62 strain was designated χ11159. The S. Paratyphi A strain χ11243 was generated from wild-type strain χ8387 using the same strategy. The ΔrecF deletion strains were constructed using suicide vectors pYA3886 and pYA4783. From the S. Typhimurium

chromosome, a 397-bp sequence upstream KU-57788 manufacturer of the recF gene was amplified with primers P17 and P18, which were engineered with XbaI and KpnI sites, respectively. The downstream 296-bp sequence (including 78 bp from the 3′ ORF of recF) was amplified with primers P19 and P20 containing KpnI and SphI sites, respectively. The two fragments were digested and inserted into XbaI-SphI digested pRE112, resulting in plasmid pYA3886. The corresponding deletion was designated ΔrecF126. Strains χ9070, χ9081 and χ11244 were generated by conjugation using E. coli strain χ7213(pYA3886). Phage P22HTint mediated transduction was used to construct Typhi strain χ11053 [56]. The ΔrecF126 deleted 996 bp from the 5′end of recF in serovars Typhimurium and Paratyphi. The upstream flanking sequence of S. Typhi is different with the other serotypes. To construct a serovar Typhi-specific Cediranib (AZD2171) ΔrecF mutation, we constructed a new suicide vector. The recF upstream flanking sequence in plasmid

pYA3886 was replaced with the corresponding DNA sequence (447 bp) from S. Typhi Ty2. Primers P21 and P22 were used for this modification. The resulting plasmid was designated as pYA4783. The Typhi-specific ΔrecF1074 mutation was introduced into S. Typhi strains ISP1820 and Ty2 by conjugation with E. coli strain χ7213(pYA4783) to yield strains χ11133 and χ11134, respectively. Primers P23 and P24 were used to verify the recF126 and recF1074 deletions. Similar strategies were used to construct the Δ recJ1315 deletion with suicide vector pYA3887. From the S. Typhimurium chromosome, 330 bp upstream of the recJ gene was amplified with primers P25 and P26, which were engineered with XbaI and KpnI sites, respectively. The 299-bp downstream sequence was amplified with primers P27 and P28, engineered with KpnI and SphI sites, respectively.

Western blot detecting E-cadherin and vimentin protein expression showed similar

results (Figure 2C and 2D). Taken together, we confirmed that sustained TGF-β1 stimuli induced EMT in BxPC-3 cells, which was consistent with the report by Vogelmann R788 R et al [9]. In addition, qRT-PCR demonstrated that RGC-32 mRNA expression was up-regulated significantly at 48 h of TGF-β1 treatment and dramatically increased by about 6 folds at 72 h of treatment (Figure 2B) and western blot showed that RGC-32 protein expression was up-regulated significantly within 48 h of treatment (Figure 2C). These results above indicated that TGF-β enhanced RGC-32 expression as well as inducing EMT in BxPC-3 cells. Figure 2 TGF-β induces EMT and enhances RGC-32 expression in BxPC-3 cells. BxPC-3 cells were cultured and treated with 10 ng/ml of TGF-β1 for 24 h, 48 h and 72 h, respectively. The morphology of cells at 72 h of TGF-β1 treatment was visualized with a phase contrast microscope (original magnification × 200, Nikon). (A) mRNA expression of E-cadherin, vimentin and selleck screening library RGC-32 was quantified by qRT-PCR with β-actin as an internal control. (B) Protein expression of E-cadherin, vimentin and RGC-32 was detected by western blot, (C) and normalized by β-actin (D). *P < 0.05 compared with the control group (0 h). RGC-32

overexpression induces EMT independently in BxPC-3 cells To investigate whether RGC-32 alone could induce EMT in Ureohydrolase BxPC-3 cells, we transiently

transfected RGC-32 plasmid (pcDNA3.1/myc-His C-RGC-32) into BxPC-3 cells to overexpress RGC-32. Empty vector (pcDNA3.1/myc-His C) was used as a negative control. mRNA expression and protein expression of EMT markers such as E-cadherin and vimentin were detected by qRT-PCR and western blot respectively. As shown in Figure 3, RGC-32 overexpression significantly down-regulated E-cadherin expression and up-regulated vimentin expression at both mRNA and protein levels, indicating that RGC-32 overexpression induced EMT in BxPC-3 cells independently. Figure 3 RGC-32 overexpression promotes EMT of BxPC-3 cells. BxPC-3 cells were transiently transfected with RGC-32 plasmid (pcDNA3.1/myc-His C-RGC32) or empty vector (pcDNA3.1/myc-His C). 72 h after transfection, qPCR (A) and western blot (B and C) were performed to examine the expression of RGC-32, E-cadherin and vimentin at mRNA and protein levels respectively. β-actin was used as an internal control. *P < 0.05. RGC-32 mediates TGF-β-induced EMT in BxPC-3 cells We used RNA interference technique to further determine the role of RGC-32 in TGF-β-induced EMT. As shown in Figure 4, compared with the negative control, RGC-32 siRNA transfection significantly attenuated the expression of RGC-32 mRNA and in turn led to the inhibition of RGC-32 protein expression.