Objective: Detection the presumptive prevalence of
silent celiac disease in patients with type 1 diabetes
mellitus with determination of which gender more
likely to be affected.
Methods: One hundred twenty asymptomatic patients
[75 male , 45 female] with type 1 diabetes mellitus
with mean age ± SD of 11.25 ± 2.85 year where
included in the study . All subjects were serologically
screened for the presence of anti-tissue transglutaminase
IgA antibodies (anti-tTG antibodies) by Enzyme-
Linked Immunosorbent Assay (ELISA) & total IgA
was also measured for all using radial
immunodiffusion plate . Anti-tissue transglutaminase
IgG was selectively done for patients who were
expressing negative anti-tissue transglutaminase IgA
with low total IgA levels & results were compared
to that obtained from healthy 60 persons with mean
age ± SD for them was 15.25 ± 3.85 year .
Results : Fourteen out of one hundred twenty (11.66
% ) diabetic patients had expressed positivity to antitissue
transglutaminase IgA compared to 1/60 ( 1.66
%) of non diabetic patients who had expressed such
positivity , P value equals to 0.0221 & it is
considered to be statistically significant. Three out of
one hundred twenty (2.5 % ) diabetic patients had
expressed total IgA deficiency whereas all of non
diabetic patients were expressing total IgA within
the normal range , P value equals to 0.55 & it is
considered to be not statistically significant. All of
three diabetic patients with total IgA deficiency were
not showing positivity to anti-tissue transglutaminase
IgG . Six mals & Eight female of those with type 1
diabetes mellitus had expressed positivity to anti-tissue
transglutaminase IgA , P value equals to 0.1426 &
it is considered to be not statistically significant .
Conclusion : There is an increased prevalence of IgA antitissue transglutaminase antibodies ( 11.66 % ) in children & adolescent with type 1 diabetes mellitus in comparison with control group.
Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem. In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a
... Show MorePolymer metal complexes of poly ethylene glycol acetal and Ag (I), Cu (II), Ni (II), Mn (II), Co (III) and Hg (II) were prepared from the reaction of PEG with aldehyde derived from Erythro-ascorbic acid (pentulosono-ɣ-lactone-2, 3- enedianisoate). All these compounds were characterized by Thin Layer Chromatography (TLC) and FTIR spectra and aldehyde was also characterized by (U.V-Vis), 1HNMR,13CNMR, and mass spectra. It has been established that, the polymer and its metal complexes showed good activities against four pathogenic bacteria (Escherichia coli ,Klebsiellapneumonae, Staphylococcusaureus, Staphylococcus Albus) and two fungal (Aspergillus Niger,Yeast). The polymer metal complexes showed higher activity than the free polymer. The
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... Show MoreThe Purpose of this research is a comparison between two types of multivariate GARCH models BEKK and DVECH to forecast using financial time series which are the series of daily Iraqi dinar exchange rate with dollar, the global daily of Oil price with dollar and the global daily of gold price with dollar for the period from 01/01/2014 till 01/01/2016.The estimation, testing and forecasting process has been computed through the program RATS. Three time series have been transferred to the three asset returns to get the Stationarity, some tests were conducted including Ljung- Box, Multivariate Q and Multivariate ARCH to Returns Series and Residuals Series for both models with comparison between the estimation and for
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