Extracting unrecognized gene relationships from the biomedical literature via matrix factorizations-1

<p><b>Copyright information:</b></p><p>Taken from "Extracting unrecognized gene relationships from the biomedical literature via matrix factorizations"</p><p>http://www.biomedcentral.com/1471-2105/8/S9/S6</p><p>BMC Bioinformatics 2007;8(Suppl 9):S6-S6.</p><p>Published online 27 Nov 2007</p><p>PMCID:PMC2217664.</p><p></p>atrix built from known genes associated with the Alzheimer's disease pathway. The -th gene is located at (, , ), where ∈ ℝ= []. (A red circle: APP; A red circle and blue diamonds: genes associated with the Alzheimer's disease pathway; Black dots: other genes

Extracting unrecognized gene relationships from the biomedical literature via matrix factorizations-0

<p><b>Copyright information:</b></p><p>Taken from "Extracting unrecognized gene relationships from the biomedical literature via matrix factorizations"</p><p>http://www.biomedcentral.com/1471-2105/8/S9/S6</p><p>BMC Bioinformatics 2007;8(Suppl 9):S6-S6.</p><p>Published online 27 Nov 2007</p><p>PMCID:PMC2217664.</p><p></p>atrix built from genes directly associated with Reelin signaling pathway. The -th gene is located at (, , ), where ∈ ℝ= []. (A red circle: RELN; A red circle and blue diamonds: genes associated with the Reelin signaling pathway; Black dots: other genes

Quantitative Proteomics Reveals Temporal Proteomic Changes in Signaling Pathways during BV2 Mouse Microglial Cell Activation

The development of systematic proteomic quantification techniques in systems biology research has enabled one to perform an in-depth analysis of cellular systems. We have developed a systematic proteomic approach that encompasses the spectrum from global to targeted analysis on a single platform. We have applied this technique to an activated microglia cell system to examine changes in the intracellular and extracellular proteomes. Microglia become activated when their homeostatic microenvironment is disrupted. There are varying degrees of microglial activation, and we chose to focus on the proinflammatory reactive state that is induced by exposure to such stimuli as lipopolysaccharide (LPS) and interferon-gamma (IFN-γ). Using an improved shotgun proteomics approach, we identified 5497 proteins in the whole-cell proteome and 4938 proteins in the secretome that were associated with the activation of BV2 mouse microglia by LPS or IFN-γ. Of the differentially expressed proteins in stimulated microglia, we classified pathways that were related to immune-inflammatory responses and metabolism. Our label-free parallel reaction monitoring (PRM) approach made it possible to comprehensively measure the hyper-multiplex quantitative value of each protein by high-resolution mass spectrometry. Over 450 peptides that corresponded to pathway proteins and direct or indirect interactors via the STRING database were quantified by label-free PRM in a single run. Moreover, we performed a longitudinal quantification of secreted proteins during microglial activation, in which neurotoxic molecules that mediate neuronal cell loss in the brain are released. These data suggest that latent pathways that are associated with neurodegenerative diseases can be discovered by constructing and analyzing a pathway network model of proteins. Furthermore, this systematic quantification platform has tremendous potential for applications in large-scale targeted analyses. The proteomics data for discovery and label-free PRM analysis have been deposited to the ProteomeXchange Consortium with identifiers and , respectively

Generation of calibration curve for nonglycopeptide (GYQELLEK) and deglycopeptide (V<i>D</i>FTEIQK) of AFP.

<p>To generate a calibration curve for the nonglycopeptide and deglycopeptide, SIS heavy peptides were serially diluted (9 concentration points: 0.0, 0.8, 1.6, 3.1, 6.3, 12.5, 25.0, 50.0, and 100.0 fmol) with the endogenous light peptide as an internal standard (pooled serum: 5 µg), added to each serially diluted sample. Each experiment was performed in triplicate to generate coefficients of variation (%CV) and calibration curve values (<i>R</i>²).</p

Development of MRM-MS method for measuring glycoproteins.

<p>To develop the MRM-MS method for measuring nonglycopeptides, glycopeptides, and deglycopeptides, we determined whether our MRM-MS approach was suitable for measuring glycoproteins using a standard glycoprotein, such as yeast invertase 1 (INV1), and applied the MRM-MS method to measure the alpha-fetoprotein (AFP) in human serum samples.</p

Characteristics of clinical subjects for MRM-MS analysis.

<p><b>Abbreviations</b></p><p>TACE: Transcatheter arterial chemoembolization.</p><p>PEIT: Percutaneous ethanol injection therapy.</p><p>RFA: Radiofrequency ablation.</p><p>AFP: Alpha-fetoprotein.</p><p>ALT: Alanine aminotransferase; AST: Aspartate aminotransferase; ALP: Alkaline phosphatase.</p><p>CR: Complete Response; PR: Partial Response; SD: Stable disease; PD: Progressive disease.</p><p>Albumin, Bilirubin, AST, ALT, ALP, and HBV DNA levels data are presented as mean ± SD.</p>a<p>HBV DNA levels were provided for 26 among a total of 35 liver cirrhosis patients, and 29 among the 60 HCC patients.</p>b<p>Antiviral therapy was treatment with Entecavir, Tenofovir, Zeffix, Hepsera and Revovir.</p>c<p>Tumor size was provided for 40 among a total of 60 HCC patients.</p>d<p>According to American Joint Committee on Cancer (AJCC) staging system (7^th edition, 2010).</p><p>Characteristics of clinical subjects for MRM-MS analysis.</p

Receiver operating characteristic (ROC) curves and interactive plots for the nonglycopeptide (GYQELLEK) and deglycopeptide (V<i>D</i>FTEIQK) of AFP, respectively.

<p>The normalized peak areas of transitions were compared between normal and HCC group. In the interactive plots, sensitivity was calculated based on a specificity of 68.3%, which was calculated per an AFP cutoff value of 20 ng/mL (56.7% sensitivity), representing significant prognostic impact for HCC (A) LC was compared to Stage I HCC subgroup, in the interactive plots, sensitivity was calculated based on a specificity of 80.0% which was calculated with optimal deglycopeptide level (B).</p

Preliminary MRM-MS analysis using pooled serum samples.

<p>Normal samples (n = 20) and HCC samples (n = 20) were pooled separately and analyzed by MRM-MS using the nonglycopeptide (GYQELLEK) and deglycopeptide (V<i><u>D</u></i>FTEIQK).</p

MOESM1 of Quantitative proteomic analysis of pancreatic cyst fluid proteins associated with malignancy in intraductal papillary mucinous neoplasms

Additional file 1. Supplementary Figures S1–S9

Stretchable Fiber Biofuel Cell by Rewrapping Multiwalled Carbon Nanotube Sheets

The fiber-type biofuel cell is attractive as an implantable energy source because the fiber can modify various structures and the wound can be stitched like a suture. In addition, in daily life, the biofuel cell is forced by human motion, and stretchability is a critical requirement for real applications. Therefore, we introduce a new type of highly stretchable, stable, soft fiber biofuel cell with microdiameter dimensions as an energy harvester. The completed biofuel cell operated well in fluids similar to human fluids, such as 20 mM phosphate-buffered 0.14 M NaCl solution (39.5 mW/cm²) and human serum (36.6 μW/cm²). The fiber-type biofuel cell can be reversibly stretched up to 100% in tensile direction while producing sustainable electrical power. In addition, the unique rewrapping structure, which traps the enzyme between multiwalled carbon nanotube sheets, enormously enhanced the stability of the biofuel cell when the biofuel cell was repeatedly stretched (the power density retention increased from 63 to 99%) and operated in human serum (the power density retention increased from 29 to 86%). The fiber can be easily woven into various structures, such as McKibben braid yarn, and scaled up by series and parallel connections