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Forty-five electropolished and 62 nonelectropolished NiTi engine files were subjected to rotational bending at various curvatures in 1.2% hypochlorite solution.
All shotgun-MS files were subjected to searches against the mouse UniProt Swiss-Prot database (May 2017 release) using ProteinPilot software v. 4.5 with the Paragon algorithm (Sciex) for protein identification.
Microarray data from GenePix image analysis software (i.e gpr files) were subjected to Lowess normalization.
Raw sequence files were subjected to quality control analysis using FastQC software (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/).ac.uk/projects/fastqc/
Mascot output.dat files were subjected to statistical validation and protein inference using Scaffold Q+ v 3.0 (Proteome Software, Portland, OR).
The raw confocal image files were subjected to 10 iterations of deconvolution (AutoDeblur, AutoQuant, Troy, NY, United States).
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The raw hybridization data (CEL files) was subjected to robust multiarray average (Irizarry et al. 2003), background correction, and normalization and quality controls were as in Truco et al. (2013).
Gating results, provided in a ppt or pdf file, were subjected to a visual inspection.
For calculating spectral counts (SpCs) at the protein level, triplicate X!Tandem [48] results for each patient were simultaneously analyzed with PeptideProphet and the single output file was subjected to ProteinProphet [49].
The resulting file was subjected to phylogenic analysis using the MEGA4.0 program [ 70].
The resulting output file was subjected to clustering using the Markov chain clustering algorithm [ 45].
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