scholarly journals Early Diagnosis of Irkut Virus Infection Using Magnetic Bead-Based Serum Peptide Profiling by MALDI-TOF MS in a Mouse Model

2014 ◽  
Vol 15 (4) ◽  
pp. 5193-5198 ◽  
Author(s):  
Nan Li ◽  
Ye Liu ◽  
Zhuo Hao ◽  
Shoufeng Zhang ◽  
Rongliang Hu ◽  
...  
2012 ◽  
Vol 12 (6) ◽  
pp. 462-466 ◽  
Author(s):  
Jiping Li ◽  
Hongtao Jin ◽  
Lixia Li ◽  
Limin Shang ◽  
Yongkun Zhao ◽  
...  

2010 ◽  
Vol 4 (8-9) ◽  
pp. 697-705 ◽  
Author(s):  
Henning G. Hansen ◽  
Julie Overgaard ◽  
Maria Lajer ◽  
Frantisek Hubalek ◽  
Peter Højrup ◽  
...  

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Abeer A. Abdelati ◽  
Rehab A. Elnemr ◽  
Noha S. Kandil ◽  
Fatma I. Dwedar ◽  
Rasha A. Ghazala

Over the last decades, there has been an increasing need to discover new diagnostic RA biomarkers, other than the current serologic biomarkers, which can assist early diagnosis and response to treatment. The purpose of this study was to analyze the serum peptidomic profile in patients with rheumatoid arthritis (RA) by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). The study included 35 patients with rheumatoid arthritis (RA), 35 patients with primary osteoarthritis (OA) as the disease control (DC), and 35 healthy controls (HC). All participants were subjected to serum peptidomic profile analysis using magnetic bead (MB) separation (MALDI-TOF-MS). The trial showed 113 peaks that discriminated RA from OA and 101 peaks that discriminated RA from HC. Moreover, 95 peaks were identified and discriminated OA from HC; 38 were significant (p<0.05) and 57 nonsignificant. The genetic algorithm (GA) model showed the best sensitivity and specificity in the three trials (RA versus HC, OA versus HC, and RA versus OA). The present data suggested that the peptidomic pattern is of value for differentiating individuals with RA from OA and healthy controls. We concluded that MALDI-TOF-MS combined with MB is an effective technique to identify novel serum protein biomarkers related to RA.


2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e18094-e18094
Author(s):  
Maria Rovithi ◽  
Joline S. Lind ◽  
Thang V Pham ◽  
Jaco C Knol ◽  
Henk M.W. Verheul ◽  
...  

e18094 Background: Mass spectrometry can be used to generate diagnostic peptide peak profiles "signatures" of serum samples1. Peak profiles can be used to compare different sera and correlate samples (i.e., patient groups) with clinical data to assist in diagnosis, monitoring, and/or prediction. Indeed, in recent studies, we and other researchers have successfully combined serum peptide profiling by mass spectrometry (MS) with bioinformatics and have established distinctive serum polypeptide MS patterns that correlate with cancer types and clinically relevant outcomes2. We performed serum peptide profiling of patients with advanced stage non-small cell lung cancer (NSCLC) treated with erlotinib and sorafenib in a previously reported clinical trial at baseline, after one week of treatment, and after three weeks of treatment, to establish treatment efficacy signatures. Methods: Using automated magnetic C18 bead-assisted serum peptide capture coupled to matrix-assisted laser desorption/ ionization time of flight mass spectrometry (MALDI-TOF MS), serum peptide profiling1 of 50 NSCLC patients was conducted and peptide mass profiles (spectra) obtained. Data analyses of pretreatment serum peptide profiles, as well as dynamic changes in peptide abundance during treatment, were performed to establish support-vector machine-based algorithms that can predict treatment efficacy. Results: A 13 ion-peptide signature could discriminate with a sensitivity of 93% and specificity of 71% a training group of patients with short progression free survival (n=14) and long progression free survival (n=14). The signature shows discriminative power for the remaining non-overlapping set of 22 patients, as well as for the complete dataset of 50 patients. Pattern analysis of overall responses and toxicity is ongoing. Conclusions: Serum peptidome profiling using MALDI-TOF-MS coupled to pattern diagnostics may provide biomarkers predictive of response to targeted treatment in patients with NSCLC, thus enabling pretreatment selection of appropriate subgroups.


2016 ◽  
Vol 42 (5) ◽  
pp. 552-560
Author(s):  
O. M. Ivanova ◽  
R. H. Ziganshin ◽  
G. P. Arapidi ◽  
S. I. Kovalchuk ◽  
I. V. Azarkin ◽  
...  

2016 ◽  
Vol 10 (7) ◽  
pp. 743-749 ◽  
Author(s):  
Maria Rovithi ◽  
Joline S. W. Lind ◽  
Thang V. Pham ◽  
Johannes Voortman ◽  
Jaco C. Knol ◽  
...  

2005 ◽  
Vol 51 (6) ◽  
pp. 973-980 ◽  
Author(s):  
Sven Baumann ◽  
Uta Ceglarek ◽  
Georg Martin Fiedler ◽  
Jan Lembcke ◽  
Alexander Leichtle ◽  
...  

Abstract Background: Magnetic bead purification for the analysis of low-abundance proteins in body fluids facilitates the identification of potential new biomarkers by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The aims of our study were to establish a proteome fractionation technique and to validate a standardized blood sampling, processing, and storage procedure for proteomic pattern analysis. Methods: We used magnetic bead separation for proteome profiling of human blood by MALDI-TOF MS (mass range, 1000–10 000 Da) and studied the effects on the quality and reproducibility of the proteome analysis of anticoagulants, blood clotting, time and temperature of sample storage, and the number of freeze–thaw cycles of samples. Results: The proteome pattern of human serum was characterized by ∼350 signals in the mass range of 1000–10 000 Da. The proteome profile showed time-dependent dynamic changes before and after centrifugation of the blood samples. Serum mass patterns differed between native samples and samples frozen once. The best reproducibility of proteomic patterns was with a single thawing of frozen serum samples. Conclusion: Application of the standardized preanalytical blood sampling and storage procedure in combination with magnetic bead-based fractionation decreases variability of proteome patterns in human serum assessed by MALDI-TOF MS.


2012 ◽  
Vol 13 (12) ◽  
pp. 13704-13712 ◽  
Author(s):  
Siyan Zhao ◽  
Wen-Sen Liu ◽  
Meng Wang ◽  
Jiping Li ◽  
Yucheng Sun ◽  
...  
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