A. Jenkins, G. Kilov, E. Scott, G. Fulcher, D. O’Neal, Andrzej S. Januszewski
{"title":"Type 1 Diabetes Glucose Control related Home-Based Testing: A Mini-Review of Tools and Patient Knowledge and Implementation","authors":"A. Jenkins, G. Kilov, E. Scott, G. Fulcher, D. O’Neal, Andrzej S. Januszewski","doi":"10.18689/MJD-1000111","DOIUrl":"https://doi.org/10.18689/MJD-1000111","url":null,"abstract":"Alicia J Jenkins1-3, Gary Kilov4,5, Emma Scott1,6, Greg R Fulcher6, David N O’Neal1-3 and Andrzej S Januszewski1,3* 1NHMRC Clinical Trials Centre, The University of Sydney, Australia 2Department of Diabetes and Endocrinology, St. Vincent’s Hospital Melbourne, Australia 3Department of Medicine, University of Melbourne, Australia 4Seaport Diabetes incorporated within Seaport Practice, Australia 5Department of General Practice, University of Melbourne, Australia 6Department of Endocrinology, Royal North Shore Hospital, The University of Sydney, Australia","PeriodicalId":92820,"journal":{"name":"Madridge journal of diabetes","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43547026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unidentified Polymorphism in Ip-10/CXCL10 Gene linked to Type 1 Diabetes","authors":"T. Daneva","doi":"10.18689/mjd-1000110","DOIUrl":"https://doi.org/10.18689/mjd-1000110","url":null,"abstract":"The development of insulin dependent type 1 diabetes (T1D) is considered to be an autoimmune proinflammatory process mediated by T-cell destruction of pancreatic beta cells. It is believed to be triggered by some environmental factors and human enteroviruses are among the candidates. After infection the virus enters beta cells and triggers the expression of immunological factors as chemokines, interferons, interleukins which attract and activate autoreactive immune cells. The attracted and activated immune cells destroy infected beta cells. The viruses may trigger T1D, but the genes play important role in this process. Improved knowledge of gene polymorphisms of chemokines and their receptors could be useful to predict the onset of diabetes and define its progression. When searching for polymorphisms in the genes encoding chemokines MIG/CXCL9, IP-10/CXCL10 and I-TAC/CXCL11 I found a difference in the IP-10 gene between patients with type 1 diabetes and control patients. Identification of this polymorphism would give more light and explanation for the reason and mechanism by which some individuals develop autoimmune diabetes. This knowledge would help us develop a strategy for prediction and prevention of T1D. These investigations will contribute to fighting diabetes on national and international level. The chemokine IP-10 expressed from pancreatic beta cells and its receptor CXCR3, expressed on the surface of immune cells are of interest as a predictive marker for the risk assessment of the autoimmune destruction of beta cells. By screening the people for this polymorphism we may be able to identify the predisposed to T1D individuals in early childhood and prevent the development of T1D by trying different experimental preventive therapies and approaches.","PeriodicalId":92820,"journal":{"name":"Madridge journal of diabetes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44037673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Kuntarattanakool, N. Isarakul, O. Tangvarasittichai, S. Tangvarasittichai
{"title":"Postprandial Dysmetabolism (Postprandial Hyperglycemia and Hypertriglyceridemia) in Type 2 Diabetes Patients","authors":"M. Kuntarattanakool, N. Isarakul, O. Tangvarasittichai, S. Tangvarasittichai","doi":"10.18689/MJD-1000109","DOIUrl":"https://doi.org/10.18689/MJD-1000109","url":null,"abstract":"Postprandial dysmetabolism [postprandial hyperglycemia (PPG) and postprandial hypertriglyceridemia (PPTG)] was used as acardiovascular disease (CVD) risk factor and as the biomarker for carbohydrates and lipids homeostasis assessment. Postprandial dysmetabolism is an underlying riskin type 2 diabetesmellitus (T2DM) patients even their have good control fasting glucose (FGlu) and triglyceride (FTG) levels. We tried to evaluate the postprandial dysmetabolismin T2DM patients. Twenty fiveT2DM patients, who reached the criteriavolunteered to participate and answered the questionnaires in the present study. Anthropometric and blood pressure (BP) were measured. All patients were received their regular medication. Fasting blood samples were collected for plasma Glu, total cholesterol (TC) and TGanalysis as in Fasting (F) condition.After that all patients received a conventional meal type as their lifestyle in everydaywith a duration time about 10-15 min. Then, blood samples were drawn after 2 hour of this meal load as Postprandialcondition. These patients were older, obesewith good control on FGlu and FTG levels and demonstrated PPG with 41.83% Glu retention and PPTG with 17.30% TG retention after 2 hours of meal load. There is no significant change in FTC and PPTC levels. FGlu, FTC, FTG, PPG and PPTG were significantly correlated with PPG, PPTC, PPTG, % Glu retention and %TG retention. Conclusion, postprandial dysmetabolism is the good biomarker for CVD risk factor and the carbohydrates and lipids homeostasis assessment after meal load, especially in T2DM and obese patient even their apparently good Glu and TG control.","PeriodicalId":92820,"journal":{"name":"Madridge journal of diabetes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48373589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Morpho-Anthropological characteristic of the distribution of Adipose Connective Tissue in Elderly Bulgarian Males with Type 2 Diabetes Mellitus","authors":"A. Baltadjiev","doi":"10.18689/mjd-1000108","DOIUrl":"https://doi.org/10.18689/mjd-1000108","url":null,"abstract":"Patients and Methods: Subjects of the research were 97 men suffering from T2DM, with age range 60-80 years. The control group included 40 Bulgarian healthy men in the same age range. Directly measured parameters: body height, body weight, 9 skinfolds (sf) and Bioelectrical Impedance analysis. Calculated indexes: Body mass index (BMI), the ratio sfTrunk/sfLimbs, the ratio skin folds upper half of body/skin folds lower half of body, fat mass and subcutaneous fat mass.","PeriodicalId":92820,"journal":{"name":"Madridge journal of diabetes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49250190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Satish P RamachandraRao, Alyssa Hamlin, L. Awdishu, R. Overcash, Marcela Zhou, J. Proudfoot, Michelle Ishaya, Eamon Aghania, Assael A. Madrigal, Chanthel Kokoy-Mondragon, K. Kao, Roni Khoshaba, Anousone Bounkhoun, M. Ghassemian, M. Tarsa, R. Naviaux
{"title":"Proteomic analyses of Urine Exosomes reveal New Biomarkers of Diabetes in Pregnancy","authors":"Satish P RamachandraRao, Alyssa Hamlin, L. Awdishu, R. Overcash, Marcela Zhou, J. Proudfoot, Michelle Ishaya, Eamon Aghania, Assael A. Madrigal, Chanthel Kokoy-Mondragon, K. Kao, Roni Khoshaba, Anousone Bounkhoun, M. Ghassemian, M. Tarsa, R. Naviaux","doi":"10.18689/MJD-1000103","DOIUrl":"https://doi.org/10.18689/MJD-1000103","url":null,"abstract":"Objective To evaluate 24 hour urine exosome protein content changes among pregnant US subjects with diabetes and obesity during early pregnancy. Methods The exosome proteome content from 24 hour urine samples of pregnant subjects with gestational diabetes mellitus (GDM, N=8) and pre-gestational Type 2 diabetes (PGD, N = 10) were compared with control samples (CTRL, N = 10) obtained at week 20 of pregnancy. Differences in exosome protein load between groups was identified by liquid chromatography/mass spectrometry, analyzed by linear regression in negative binomial distribution, visualized in MetaboAnalyst (version 3.0), and validated by western immunoblotting. Results At the 20th week of pregnancy, we identified 646, 734 and 856 proteins in exosomes from 24 hour urine samples of patients from the CTRL, GDM and PGD groups, respectively. S100 calcium binding protein A9, damage associated molecular pattern (DAMP) signal, was found to be significantly increased in both GDM and PGD subjects. In GDM subjects the peptide counts for S100A9 protein independently correlated with maternal obesity and macrosomia of the newborn infants. Early to late pregnancy developmental changes in the GDM group were shown to utilize pathways and protein expression levels differently from those in PGD or CTRL groups. Conclusions Urinary exosome proteomic analysis non-invasively provides insights into maternal changes during diabetic pregnancy. Exosome biomarkers early in pregnancy can be potentially used to better understand pathophysiologic mechanisms of diabetes at a cellular level, and to distinguish between gestational and pre-gestational diabetes at the pathway level. This information can aid intervention efforts to improve pregnancy outcomes in women with diabetes.","PeriodicalId":92820,"journal":{"name":"Madridge journal of diabetes","volume":"1 1","pages":"11 - 22"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67766000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}