ArticleThe open proteomics journal2013
Short Gel, Long Gradient Liquid Chromatography Tandem Mass Spectrometry to Discover Urinary Biomarkers of Chronic Pancreatitis.
Article in The open proteomics journal, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Biomarkers of Chronic Pancreatitis: A systematic literature review.Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] · 2021Pooled it
- Protocols for isolation and characterization of nanoparticle biomolecular corona complexes.Frontiers in toxicology · 2024Article
- Interaction between parasite-encoded JAB1/CSN5 and macrophage migration inhibitory factor proteins attenuates its proinflammatory function.Scientific reports · 2018Article
- Advances in Pancreatic Biomarker Measures: A Novel Approach to An Obscure Organ.Clinical and translational gastroenterology · 2016Article
- Sample preparation for proteomic analysis using a GeLC-MS/MS strategy.Journal of biological methodsArticle
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
backgroundChronic pancreatitis (CP) is currently diagnosed using invasive endoscopic as well as radiation and non-radiation-based imaging techniques. However, urine can be safely and non-invasively collected and as such may offer a superior alternative to current techniques of CP diagnosis. We use mass spectrometry-based methods to discover proteins which are exclusive to or differentially abundant in urine of chronic pancreatitis patients.
methodsWe have performed a comparative quantitative proteomic analysis of urine collected from 5 healthy controls and 5 severe CP patients. Proteins from urine were fractionated briefly on SDS-PAGE and subsequently digested in-gel with trypsin. The resulting peptides were fractionated for 3 hours by reversed-phase liquid chromatography in-line with a mass spectrometer. ProteinPilot software and the QSPEC algorithm identified proteins and determined statistically significant differences between cohorts. In addition, we used a third cohort of non-CP disease patients to filter out those proteins which may be indicative of an ailment other than CP.
resultsWe identified over 600 proteins from urine, of which several hundred were either exclusive to or differ quantitatively between healthy controls and severe CP patients. Members of the cathepsin protein family were of significantly higher abundance in the severe CP cohort. In addition, we have identified a core set of 50 proteins in all 15 samples, 25 of which showed no significant difference among the cohorts.
conclusionsProteomic analysis identified differentially abundant proteins in healthy controls and severe CP patients. Such proteins represent an initial set of targets for directed proteomics experiments for further validation studies. However, larger cohorts will be required to determine if these differences have statistically significant diagnostic potential.
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