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
The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge
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tool size. In this work investigation studies have been carried out to find the different tool
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incremental sheet metal forming (SPIF), an adaptive tool path strategy was proposed and
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