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.
HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023
For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.
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