49 research outputs found

    The EIPeptiDi tool: enhancing peptide discovery in ICAT-based LC MS/MS experiments-1

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    <p><b>Copyright information:</b></p><p>Taken from "The EIPeptiDi tool: enhancing peptide discovery in ICAT-based LC MS/MS experiments"</p><p>http://www.biomedcentral.com/1471-2105/8/255</p><p>BMC Bioinformatics 2007;8():255-255.</p><p>Published online 15 Jul 2007</p><p>PMCID:PMC1939855.</p><p></p> in the 7 samples data set A

    The EIPeptiDi tool: enhancing peptide discovery in ICAT-based LC MS/MS experiments-4

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    <p><b>Copyright information:</b></p><p>Taken from "The EIPeptiDi tool: enhancing peptide discovery in ICAT-based LC MS/MS experiments"</p><p>http://www.biomedcentral.com/1471-2105/8/255</p><p>BMC Bioinformatics 2007;8():255-255.</p><p>Published online 15 Jul 2007</p><p>PMCID:PMC1939855.</p><p></p

    The EIPeptiDi tool: enhancing peptide discovery in ICAT-based LC MS/MS experiments-3

    No full text
    <p><b>Copyright information:</b></p><p>Taken from "The EIPeptiDi tool: enhancing peptide discovery in ICAT-based LC MS/MS experiments"</p><p>http://www.biomedcentral.com/1471-2105/8/255</p><p>BMC Bioinformatics 2007;8():255-255.</p><p>Published online 15 Jul 2007</p><p>PMCID:PMC1939855.</p><p></p

    The EIPeptiDi tool: enhancing peptide discovery in ICAT-based LC MS/MS experiments-0

    No full text
    <p><b>Copyright information:</b></p><p>Taken from "The EIPeptiDi tool: enhancing peptide discovery in ICAT-based LC MS/MS experiments"</p><p>http://www.biomedcentral.com/1471-2105/8/255</p><p>BMC Bioinformatics 2007;8():255-255.</p><p>Published online 15 Jul 2007</p><p>PMCID:PMC1939855.</p><p></p>w represents a sample. Colored boxes indicate that a H/L ratio is available for the corresponding peptide

    The EIPeptiDi tool: enhancing peptide discovery in ICAT-based LC MS/MS experiments-2

    No full text
    <p><b>Copyright information:</b></p><p>Taken from "The EIPeptiDi tool: enhancing peptide discovery in ICAT-based LC MS/MS experiments"</p><p>http://www.biomedcentral.com/1471-2105/8/255</p><p>BMC Bioinformatics 2007;8():255-255.</p><p>Published online 15 Jul 2007</p><p>PMCID:PMC1939855.</p><p></p> in the 10 samples data set B

    FHC is required for caffeine modulation of H460 proliferation.

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    <p>(A) Real-time PCR analysis of FHC mRNA amounts was performed on total RNA from H460<sup>siFHC</sup> and H460<sup>siRNA</sup> cells treated with the indicated doses of caffeine. Results are representative of two different experiments (*<i>p</i> < 0.05 of each caffeine concentration compared with untreated cells; NS not significant). (B) Cell proliferation was assessed using the MTT method on H460<sup>siFHC</sup> and H460<sup>siRNA</sup>cells treated with caffeine at the indicated doses. Final results represent mean ± SD of three independent experiments each performed in triplicate (*<i>p</i> < 0.05 of each caffeine concentration compared withuntreated cells; NS not significant). (C) Direct cell counting of H460<sup>siFHC</sup> and H460<sup>siRNA</sup>cells treated with caffeine at the indicated doses. Final results represent mean ± SD of two independent experiments (*<i>p</i> < 0.05 of each caffeine concentration compared with untreated cells; NS not significant). (D) Western blot analysis forCCND1, p53 and pAKT were performed on 50μg of total proteins extracted from H460<sup>siFHC</sup> and H460<sup>siRNA</sup> treated with 80μM caffeine or untreated. γ-Tubulin and AKT were used as loading controls.</p

    Caffeine reduces H460 cell proliferation.

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    <p>(A) Cell proliferation was assessed using the MTT method as indicated in the Materials and Methods section. Final results represent mean ± SD of three independent experiments each performed in triplicate (*<i>p</i> < 0.05 of each caffeine concentration compared with NT-untreated cells). (B) Direct cell counting of NT-untreated and 80μM caffeine<b>-</b>treated cells. The results are the mean of two independent experiments (*<i>p</i> < 0.05 compared with NT-untreated cells). (C) and (D)Western blot analysis for CCND1, p53 and pAKT were performed on 50μg of total proteins. Blots are representative of three independent experiments. γ-Tubulin and AKT were used as loading controls. (E) DNA was extracted from cells and analyzed on a 2% agarose gel as described in Materials and Methods. The image is a representative experiment.</p

    FHC silencing increases cell proliferation.

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    <p>(A) Western blot analysis for FHC was performed on 50μg of total proteins extracted from FHC-silenced H460 (H460<sup>siFHC</sup>) or from H460 control cells (H460<sup>siRNA</sup>). Blots are representative of three independent experiments. γ-Tubulin was used as a loading control. The graph represents the mean of the optical densities (*<i>p</i> < 0.05 compared with H460<sup>siRNA</sup>). (B) Real-time PCR analysis of FHC mRNA amounts performed on total RNA from H460<sup>siFHC</sup> and H460<sup>siRNA</sup>cells. Results are representative of three different experiments (*<i>p</i><0,05 compared with H460<sup>siRNA</sup>). (C) H460<sup>siRNA</sup>and H460<sup>siFHC</sup>cells were incubated for 15 min with 20 μM of 2’-7’-DCF and washed with HBSS solution. Fluorescence was measured at 485 nm and 535 nm after60 min. (D) Cell proliferation was assessed using the MTT method as indicated in the Materials and Methods section. Final results represent mean ± SD of three independent experiments each performed in octuplicate (*<i>p</i>< 0.05 compared with H460<sup>siRNA</sup>). (E) Western blot analysis for CCND1, p53 and pAKT were performed on 50μg of total proteins extracted from H460<sup>siFHC</sup> and H460<sup>siRNA</sup>. Blots are representative of three independent experiments. γ-Tubulin and AKT were used as loading controls.(F) Western blot analysis for FHC was performed on 50μg of total proteins extracted from FHC-stably silenced H460 (H460<sup>shFHC</sup>) or from H460 control cells (H460<sup>shRNA</sup>). Blots are representative of three independent experiments. γ-Tubulin was used as a loading control. The graph represents the mean of the optical densities (*<i>p</i> < 0.05 compared with H460<sup>shRNA</sup>). (G) Cell proliferation of stably silenced cells was assessed using the MTT method. Final results represent mean ± SD of three independent experiments each performed in octuplicate (*<i>p</i>< 0.05 compared with H460<sup>shRNA</sup>).</p

    Proteome Speciation by Mass Spectrometry: Characterization of Composite Protein Mixtures in Milk Replacers

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    The ability of tandem mass spectrometry to determine the primary structure of proteolytic peptides can be exploited to trace back the organisms from which the corresponding proteins were extracted. This information can be important when food products, such as protein powders, can be supplemented with lower-quality starting materials. In order to dissect the origin of proteinaceous material composing a given unknown mixture, a two-step database search strategy for bottom-up nanoscale liquid chromatography–tandem mass spectrometry (nanoLC–MS/MS) data was implemented. A single nanoLC–MS/MS analysis was sufficient not only to determine the qualitative composition of the mixtures under examination, but also to assess the relative percent composition of the various proteomes, if dedicated calibration curves were previously generated. The approach of two-step database search for qualitative analysis and proteome total ion current (pTIC) calculation for quantitative analysis was applied to several binary and ternary mixtures which mimic the composition of milk replacers typically used in calf feeding

    N‑Glycoprotein Analysis Discovers New Up-Regulated Glycoproteins in Colorectal Cancer Tissue

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    Colorectal cancer is one of the leading causes of death due to cancer worldwide. Therefore, the identification of high-specificity and -sensitivity biomarkers for the early detection of colorectal cancer is urgently needed. Post-translational modifications, such as glycosylation, are known to play an important role in cancer progression. In the present work, we used a quantitative proteomic technique based on <sup>18</sup>O stable isotope labeling to identify differentially expressed N-linked glycoproteins in colorectal cancer tissue samples compared with healthy colorectal tissue from 19 patients undergoing colorectal cancer surgery. We identified 54 up-regulated glycoproteins in colorectal cancer samples, therefore potentially involved in the biological processes of tumorigenesis. In particular, nine of these (PLOD2, DPEP1, SE1L1, CD82, PAR1, PLOD3, S12A2, LAMP3, OLFM4) were found to be up-regulated in the great majority of the cohort, and, interestingly, the association with colorectal cancer of four (PLOD2, S12A2, PLOD3, CD82) has not been hitherto described
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