Background: The immunogenetic predisposition
may be considered as an important factor for the
development of Type 1 Diabetes Mellitus (T1DM)
in association with the HLA antigens.
Objective:This study was designed to investigate
the role of HLA-class II antigens in the etiology of
type T1DM and in prediction of this disease in
siblings, and its effect on expression of glutamic
acid decarboxylase autoantibodies (GADA).
methods:Sixty children who were newly diagnosed
type 1 diabetes (diagnosed less than five months)
were selected. Their age ranged from 3-17 years.
Another 50 healthy siblings were available for this
study, their ages range from 3-16 years. Eighty
apparently healthy control subjects, matched with
age (4-17) years, sex and ethnic backgrounds
(Iraqi Arabs) underwent the HLA-typing
examination. Finally 50 healthy individuals were
selected randomly to undergo GADA test.
Results:At HLA-class II region, DR3 and DR4
were significantly increased in patients (53.33
vs.26.25% and 50.0 vs. 12.5% respectively) as
compared to controls. In
addition to that, T1DM was significantly associated
with DQ2 (33.33 vs.15%) and DQ3 (40.0 vs.20%)
antigens as compared to controls, suggesting that
these antigens had a role in disease susceptibility,
while the frequency of DR2 and DQ1 antigens were
significantly lowered in patients compared to
controls (6.66 vs.25% and 6.66 vs.22.5%
respectively). These molecules might have
protective effect. In siblings a significant increase
frequency of DR4 antigen (34.0 vs.12.5%) was
observed in comparison to controls, suggesting that
it might be much useful for predicting T1DM in
affected families.Anti-GAD autoantibodies were
present in 50% of Type 1Diabetic children, and in
16% of their siblings. High proportion of GADA
was found in the patients carrying HLA-DR3/DR4
heterozygous.
conclusion:Both the T1DM patients and their
siblings shared the HLA- DQ1 as protective
antigens, while DR3 and DR4 were susceptible one,
and high proportion of GADA was found in the
T1DM patients and siblings carrying HLADR3/DR4 heterozygous
This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.
The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20
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Preparation and Identification of some new Pyrazolopyrin derivatives and their Polymerizations study