Background: Beta thalassemia major (β-TM) is an inheritable condition with many complications, especially in children. The blood-borne viral infection was proposed as a risk factor due to the recurrent blood transfusion regimen (hemotherapy) as human parvovirus B19 (B19V). Objective: This study investigated the B19V seroprevalence, DNA presence, B19V viral load, and B19V genotypes in β-TM patients and blood donors. Methods: This is a cross-sectional study incorporating 180 subjects, segregated into three distinct groups each of 60 patients, namely control, β-TM, and β-TM infected with Hepatitis C Virus (HCV). For the B19V prevalence in the studied group, the ELISA technique and real-time PCR were used. The genotyping was followed by the resultant sequence. Results: Both B19V IgM and IgG antibody positivity rates are higher among β-TM patients compared to controls. The B19V IgM (35%) and B19V IgG (21.67%) antibodies positivity in β-TM patients compared to 23.3% and 18.33% positivity in the controls was significantly observed. The prevalence of B19V was (8.3%), and the viral copy number in β-TM patients ranged from ≥104– 106 copies/ml than in controls. The B19V genotype 1 subtype a was the only genotype according to the VP1-VP2 region (288 pb) in this study. Conclusions: The prevalence of B19V in patients may be higher than in controls. B19V screening in high-risk groups, such as blood donors, may considerably reduce the prevalence of B19V.
Coaches and analysts face a significant challenge of inaccurate estimation when analyzing Men's 100 Meter Sprint Performance, particularly when there is limited data available. This necessitates the use of modern technologies to address the problem of inaccurate estimation. Unfortunately, current methods used to estimate Men's 100 Meter Sprint Performance indexes in Iraq are ineffective, highlighting the need to adopt new and advanced technologies that are fast, accurate, and flexible. Therefore, the objective of this study was to utilize an advanced method known as artificial neural networks to estimate four key indexes: Accelerate First of 10 meters, Speed Rate, Time First of 10 meters, and Reaction Time. The application of artifi
... Show MoreLongitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.
In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.
The longitudinal balanced data profile was compiled into subgroup
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