Focal adhesion kinase (FAK), ephrin receptor type A4 (EphA4), and adiponectin (ADPN) are important indicators in inflammation, tumor growth, migration, and angiogenesis in some cancers. The predictive impact of their concentrations in acute myeloid leukemia (AML) patients to be identified remains. The research sought to explore the effect of FAK, EphA4, and ADPN as prognostic biomarkers, and their influence on patient survival, and to look for any potential correlation between their levels with hematological parameters in AML patients.

Here, a high sensitive method for biomarker identification according to nanostructure, using enzyme-linked immunosorbent assays (ELISAs), called Nano-ELISA, was presented. Different shapes of gold nanostructures (star and sphere; GNSs and GNPs) with a particle size of 40 nm for sphere particles were altered with a monoclonal antibody (Ab) as a detector Ab. To amplify the optical signal, gold nanostructures were employed as carriers of the signaling specific antibody against insulin growth factor binding protein- 3 (IGFBP-3). The substrate was catalytically oxidized by the Horseradish Peroxidase (HRP) conjugated gold nanostructure, and HRP also enhanced the optical signals, reflecting the amount of the targeting IGFBP-3. In comparison to t

Poverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distanc

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

It aim current researchs֬ to identify the impact of a proposed strategy in accordance with the objectives of science in the achievement and some science processes, where the experimental method was adopted, and define the research community was students second grade averag in Education Bagdad / Rusafa third, research sample intentionally chosen as school Radwan, and (30) students experimental group and (29) of control group, research tools were achievement test and the test of science operations and use the appropriate statistical tools to process information and data, showing results, the experimental group surpassed the control group in the collection and operations science, and light it, the researcher recommended several recommendat

Background: The oral cavity is considered as a complex ecological niche, its complex microbial community is reflected to it. Streptococcus mutans has been implicated as one of the major etiological factor of dental caries. Tooth surfaces colonized with Streptococcus mutans are at a higher risk for developing caries, while lactobacilli are considered as the secondary invaders, not initiators of the carious lesion. The main purpose of this study was to correlate the dental caries (for primary and permanent teeth) in the upper jaw with the streptococcus mutans and lactobacilli count in the dental plaque and saliva, also to correlate the dental caries (for primary and permanent teeth) in the lower jaw with the streptococcus mutans and lactobaci

Oxidative stress markers are of important diagnostic parameters for many disorders including cholelithiasis. This present study has aimed to assess the state of oxidative stress in symptomatic radiographically confirmed (Cholelithiasis) patients by measuring two parameters used as oxidative stress parameters which are serum myeloperoxidase (MPO) and superoxide dismutase (SOD). This study was carried out on 100 patient diagnosed as (Cholelithiasis) patients with 30 age and sex matched healthy controls by measuring serum (MPO) and (SOD) by ELIZA technique .Results showed significantly decrease in antioxidant enzyme(SOD) and increase in serum level of (MPO) comparing with controls.

Keywords: Cholelithiasis , Oxidative stress

The majority of used clothes represented a passion for brilliant
appearance and could be a reason for hiding body defects , as to avoid
criticism .
This may lead to purchase and wear un healthy or uncomfortable clothes
such as tide .As to appreciate the differences between wearing healthy clothes or
otherwise .
The study was carried out to assess healthy cloth awareness for university
girls as related to possibility of being subjected to harm caused by wearing tide
clothes .
The measurement items was determined and numbered ( 23 ). The answer
for these scale criteria was ( Always , Sometime ,Never ) for the weights (3,2,1)
. The scale was applied to a randomly selected sample of research community
that

A frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm co