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      Intermediate and low abundant protein analysis of vitamin D deficient obese and non-obese subjects by MALDI-profiling

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          Abstract

          Obesity is a pathological condition caused by genetic and environmental factors, including vitamin D deficiency, which increases the risk of developing cardiovascular disorders and diabetes. This case-control study was designed to verify whether serum profiles could be identified differentiating obese and non-obese Saudis characterized by vitamin D deficiency and pathological levels of triglycerides, high-density lipoprotein cholesterol and high total cholesterol levels. The serum protein profiles of 64 vitamin D deficient (serum 25(OH)D < 50nmol/L) individuals with metabolic syndrome and with (n = 31; BMI ≥ 30) or without (n = 33; BMI < 30) obesity were analyzed by a quantitative label-free mass spectrometry approach (MALDI-profiling), combined with different serum immunodepletion strategies (Human7 and Human14 immuno-chromatographies), to analyze the intermediate- and low-abundant protein components. The analysis of intermediate-abundant proteins (Human7) in obese vs. non-obese subjects identified 14 changed peaks (p < 0.05) in the m/z range 1500–35000. Furthermore, the Human14 depletion provided new profiles related to obesity (121 changed peaks). Among changed peaks, 11 were identified in the m/z range 1500–4000 Da by high-resolution tandem mass spectrometry, belonging to apolipoprotein CIII, apolipoprotein B100, alpha-1-antichymotrypsin and complement C3. Data herein show that distinct protein profiles identify specific peptides belonging to lipid metabolism and inflammation processes that are associated with obesity and vitamin D deficiency.

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          EDF Statistics for Goodness of Fit and Some Comparisons

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            Obesity and Associated Factors — Kingdom of Saudi Arabia, 2013

            Introduction Data on obesity from the Kingdom of Saudi Arabia (KSA) are nonexistent, making it impossible to determine whether the efforts of the Saudi Ministry of Health are having an effect on obesity trends. To determine obesity prevalence and associated factors in the KSA, we conducted a national survey on chronic diseases and their risk factors. Methods We interviewed 10,735 Saudis aged 15 years or older (51.1% women) through a multistage survey. Data on sociodemographic characteristics, health-related habits and behaviors, diet, physical activity, chronic diseases, access to and use of health care, and anthropometric measurements were collected through computer-assisted personal interviews. We first compared sociodemographic factors and body mass index between men and women. Next, we conducted a sex-specific analysis for obesity and its associated factors using backward elimination multivariate logistic regression models. We used SAS 9.3 for the statistical analyses and to account for the complex sampling design. Results Of the 10,735 participants evaluated, 28.7% were obese (body mass index ≥30 kg/m2). Prevalence of obesity was higher among women (33.5% vs 24.1%). Among men, obesity was associated with marital status, diet, physical activity, diagnoses of diabetes and hypercholesterolemia, and hypertension. Among women, obesity was associated with marital status, education, history of chronic conditions, and hypertension. Conclusion Obesity remains strongly associated with diabetes, hypercholesterolemia, and hypertension in the KSA, although the epidemic’s characteristics differ between men and women.
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              Quantitative analysis of peptides and proteins in biomedicine by targeted mass spectrometry.

              Targeted mass spectrometry (MS) is becoming widely used in academia and in pharmaceutical and biotechnology industries for sensitive and quantitative detection of proteins, peptides and post-translational modifications. Here we describe the increasing importance of targeted MS technologies in clinical proteomics and the potential key roles these techniques will have in bridging biomedical discovery and clinical implementation.
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                Author and article information

                Contributors
                cecilia.gelfi@unimi.it
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                3 October 2017
                3 October 2017
                2017
                : 7
                : 12633
                Affiliations
                [1 ]ISNI 0000 0004 1773 5396, GRID grid.56302.32, Prince Mutaib Chair for Biomarkers of Osteoporosis, Biochemistry Department, College of Science, King Saud University, ; Riyadh, 11451 Saudi Arabia
                [2 ]ISNI 0000 0004 1757 2822, GRID grid.4708.b, Department of Biomedical Sciences for Health, University of Milan, ; Segrate (Milan), Italy
                [3 ]ISNI 0000 0004 1766 7370, GRID grid.419557.b, Clinical Proteomics Unit, Scientific Institute for Research, Hospitalization and Health Care (IRCCS) Policlinico San Donato, ; San Donato Milanese (Milan), Italy
                [4 ]GRID grid.414603.4, Don C. Gnocchi Foundation, IRCCS, ; Milan, Italy
                [5 ]ISNI 0000 0004 1757 2822, GRID grid.4708.b, Department of Physiopathology and Transplants, University of Milan, ; Milan, Italy
                Author information
                http://orcid.org/0000-0001-5472-1725
                http://orcid.org/0000-0001-7701-728X
                http://orcid.org/0000-0002-2996-6912
                Article
                13020
                10.1038/s41598-017-13020-z
                5626753
                28974732
                d1be5199-3c95-4b06-bc6f-1b12521ad7b6
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 23 May 2017
                : 12 September 2017
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