Biomarkers to detect Alzheimer’s disease (AD) would enable patients to gain access to appropriate services and may facilitate the development of new therapies. Given the large numbers of people affected by AD, there is a need for a low-cost, easy to use method to detect AD patients. Potentially, the electroencephalogram (EEG) can play a valuable role in this, but at present no single EEG biomarker is robust enough for use in practice. This study aims to provide a methodological framework for the development of robust EEG biomarkers to detect AD with a clinically acceptable performance by exploiting the combined strengths of key biomarkers. A large number of existing and novel EEG biomarkers associated with slowing of EEG, reduction in EEG complexity and decrease in EEG connectivity were investigated. Support vector machine and linear discriminate analysis methods were used to find the best combination of the EEG biomarkers to detect AD with significant performance. A total of 325,567 EEG biomarkers were investigated, and a panel of six biomarkers was identified and used to create a diagnostic model with high performance (≥85% for sensitivity and 100% for specificity).
Pregnancy and delivery are physiological conditions that are marked by abrupt alterations to hormones, immunological and molecular characters. The current study aimed to evaluate oxytocin (OT), prolactin (PRL), cortisol and insulin growth factor-2 (IGF-2) levels as physiological biomarkers; programmed cell death protein-1 (PD-1), programmed cell death ligand-1 (PD-L1),interleukin-6 (IL-6) as immunological biomarkers, and single nucleotide polymorphisms (SNPs; rs53576 and rs2254298) of oxytocin receptor gene OXTR as molecular factors in samples of Iraqi women undergoing caesarean section (CS) and normal delivery (ND). Blood samples were collected from 96 pregnant women at term with ages ranging between 16-43 years. Regarding
... Show MoreAnalyzing plantar pressure trajectories is crucial for assessing foot behavior in dynamic gait stability. We propose the identification of foot symmetry and the detection of deformities by analyzing the trajectories of the center of pressure (CoP) and peak pressure (PP). First, using a foot pressure mapping system, plantar pressure data are acquired during a normal gait cycle. After the data have been acquired, post processing extracts both the CoP and PP trajectories over the spatiotemporal domain of foot motion for each foot independently. For this purpose, we used the optical flow technique which accurately estimates the direction of foot motion. The extracted trajectories of each foot are then segmented into, the medial and lateral regi
... Show MoreLearning the vocabulary of a language has great impact on acquiring that language. Many scholars in the field of language learning emphasize the importance of vocabulary as part of the learner's communicative competence, considering it the heart of language. One of the best methods of learning vocabulary is to focus on those words of high frequency. The present article is a corpus based approach to the study of vocabulary whereby the research data are analyzed quantitatively using the software program "AntWordprofiler". This program analyses new input research data in terms of already stored reliable corpora. The aim of this article is to find out whether the vocabularies used in the English textbook for Intermediate Schools in Iraq are con
... Show MoreIn this paper, the researcher suggested using the Genetic algorithm method to estimate the parameters of the Wiener degradation process, where it is based on the Wiener process in order to estimate the reliability of high-efficiency products, due to the difficulty of estimating the reliability of them using traditional techniques that depend only on the failure times of products. Monte Carlo simulation has been applied for the purpose of proving the efficiency of the proposed method in estimating parameters; it was compared with the method of the maximum likelihood estimation. The results were that the Genetic algorithm method is the best based on the AMSE comparison criterion, then the reliab
... Show MoreThis paper is devoted to an inverse problem of determining discontinuous space-wise dependent heat source in a linear parabolic equation from the measurements at the final moment. In the existing literature, a considerably accurate solution to the inverse problems with an unknown space-wise dependent heat source is impossible without introducing any type of regularization method but here we have to determine the unknown discontinuous space-wise dependent heat source accurately using the Haar wavelet collocation method (HWCM) without applying the regularization technique. This HWCM is based on finite-difference and Haar wavelets approximation to the inverse problem. In contrast to othe
Often times, especially in practical applications, it is difficult to obtain data that is not tainted by a problem that may be related to the inconsistency of the variance of error or any other problem that impedes the use of the usual methods represented by the method of the ordinary least squares (OLS), To find the capabilities of the features of the multiple linear models, This is why many statisticians resort to the use of estimates by immune methods Especially with the presence of outliers, as well as the problem of error Variance instability, Two methods of horsepower were adopted, they are the robust weighted least square(RWLS)& the two-step robust weighted least square method(TSRWLS), and their performance was verifie
... Show MoreBackground: Colorectal cancer (CRC) is a major killer, and nonalcoholic fatty liver disease (NAFLD) affects almost one-quarter of the global population. The aim of the study is to Investigate the correlation between nonalcoholic fatty liver disease (NAFLD) and an increased risk of colorectal cancer (CRC), as well as the relationship between liver function enzymes and specific serum biomarkers in CRC patients with NAFLD. Methods: A case-control study involving 60 participants was conducted from February to August 2022. The patients with colon cancer were examined at Baghdad Medical City's Al-Amal Hospital for Radiation and Nuclear Medicine and Oncology Teaching Hospital, and blood samples were taken. Thirty patients with NAFLD who ha
... Show MoreBackground: Periodontitis (PD) is well-known chronic disease affecting the periodontal ligament and alveolar bone, Osteoarthritis (OA) is a chronic joint disease with compound reasons characterized by synovial inflammation, subchondral bone remodeling, also the formation of osteophytes, that cause cartilage degradation. Chronic periodontitis and osteoarthritis are considered widely prevalent diseases and related to tissue destruction due to chronic inflammation in general health and oral health. The aim of this study is todetermine the association of chronic periodontitis and osteoarthritits in patients by analysing tumor necrosis factor alpha TNFα and high sensitive c-reactive protein (hsCRP) in the serum. Materials and Method: A tot
... Show MoreDiabetic kidney disease (DKD) is caused by a variety of processes. As a result, one biomarker is insufficient to represent the complete process. This study Evaluate the diagnostic value of serum kidney injury molecule-1(KIM-1) and cystatin C (CysC) as early biochemical markers of DKD and predictive their sensitivities and specificities as biomarkers of nephropathy in Iraqi type 2 diabetic (T2DM) patients. This cross-sectional study include 161 T2DM patients from Diabetes and Endocrinology Center at Merjan medical city in Babylon. Patients divided according to urinary albumin creatinine ratio(ACR) (Group1:ACR≤30mg/g,Group2:ACR>30mg/g). Random spot urine and fasting blood samples were taken from each patient and urinary ACR, bloo
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