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Serum Biomarkers are Promising Tools to Predict Traumatic Brain Injury Outcome
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Traumatic Brain Injury (TBI) is still considered a worldwide leading cause of mortality and morbidity. Within the last decades, different modalities were used to assess severity and outcome including Glasgow Coma Scale (GCS), imaging modalities, and even genetic polymorphism, however, determining the prognosis of TBI victims is still challenging requiring the emerging of more accurate and more applicable tools to surrogate other old modalities

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Publication Date
Thu Apr 27 2023
Journal Name
Journal Of The Faculty Of Medicine Baghdad
High Serum High Mobility Group A1 (HMGA1) Levels are associated with presence of Metabolic Syndrome: Case-control study
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Background: Metabolic syndrome is a complex series of metabolic defects, characterized by high levels of serum glucose, hypertension, abdominal obesity, and dyslipidemia. The high mobility group AT-hook1, an architectural transcript factor, affects the homeostasis of glucose. No previous studies have been performed to examine whether HMGA1 can be secreted into the extracellular milieu.

Objectives: this case-control study aimed to examine whether HMGA1 secretes into the extracellular milieu and compares its serum level in two groups of metabolic syndrome (with and without diabetes) and a control group composed of apparently healthy individuals of Iraqi population with different nationalities.

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Advanced Biotechnology And Experimental Therapeutics
Kidney injury molecule-1 and cystatin C as early biomarkers for renal dysfunction in Iraqi type 2 diabetes mellitus patients
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Diabetic 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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Publication Date
Wed May 22 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Assessment of Urine and Serum Exosomes as Biomarkers for the Diagnosis of Bladder Cancer
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Background: Bladder cancer (BC) is the most common malignant tumor in the urinary tract and the tenth most common malignancy worldwide. Exosomes are 40–100 nm-diameter nanovesicles that are either released straight from the plasma membrane during budding or merged with the plasma membrane by multivesicular bodies. Objectives: To assess the proportion of serum and urinary Exosome levels in urinary bladder cancer patients, as well as their impact on the disease. Methods: From January 2023 to June 2023, a total of 45 samples of blood and urine were collected from individuals diagnosed with bladder cancer at the Ghazi Hariri Hospital for Specialized Surgery. They included 45 male and female patients, varying in age, as well as 45 heal

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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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Publication Date
Sat Jul 31 2021
Journal Name
Brain Sciences
Robust EEG Based Biomarkers to Detect Alzheimer’s Disease
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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, reductio

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Publication Date
Wed Nov 13 2019
Journal Name
International Journal Of Research In Pharmaceutical Sciences
Prediction of maternal diabetes and adverse neonatal outcome in normotensive pregnancy using serum uric acid
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Diabetes mellitus, with adverse neonatal events are challenging issues to all obstetricians and pediatricians, where uric acid could play a vital role. We aimed to assess the relationship and prognostic benefits of serum uric acid measured at about 20 weeks’ gestation in normotensive pregnancy, with subsequent maternal diabetes, and neonatal complications. All singleton normotensive pregnant women with normal blood glucose, serum creatinine, and weight before pregnancy, whom attended Medical City Hospital, Department of Obstetrics and Gynecology in Baghdad, were involved and regarded as the case group, on the condition that their serum uric acid measured at 20 weeks’ gestation > 3 mg/dl, but if ≤ 3 mg/dl, they would be regi

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Publication Date
Sun Mar 04 2018
Journal Name
Iraqi Journal Of Science
Effects of RVLM Stimulation on Blood Pressure and Vasopressin-Like Levels in Brain Sites and Plasma are an Anesthetic Dependent. Rashid IH
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The study is sought to determine specific alteration in AVP-LI level of plasma and sites of the hypothalamic-neurohypophysial-system; supraoptic nucleus (SON), paraventricular nucleus (PVN), neurointermediate lobe (NIL), and median eminence (ME), related to effects of stress of different anesthetics and electrical stimulation of RVLM/C1area. Urethane or halothane anesthetized Wistar rats were subjected to intra-RVLM electrical stimulation of 10 sec train, 1msec pulse duration at 40 Hz, and 2V every 30s.  After 30min stimulation, AVP-LI extracted from plasma, NIL, ME, SON, and PVN and measured by RIA, were compared with that of sham-stimulated urethane- or halothane-anesthetized rats and unstimulated unanesthetized control rats. Data

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Relation between Serum Leptin, Lipid Profiles and other biomarkers levels in patients with type 2 diabetic nephropathy
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Background: In advanced diabetes mellitus, serum levels of the most hormones are altered due to several interplaying mechanisms. Objective: To assess the relation of serum leptin and lipid profile in type 2 diabetic nephropathy. Patients and Method: Serum leptin levels and its relation to lipid profile were estimated in 62 patients with type 2 diabetic nephropathy attending the National Diabetes Center in Al- Mustansiriya University, and (26) healthy individuals considered as control group. The diabetic patients were classified into three groups, (24) pathients with normoalbuminuria (21) patients with microalbuminuria and (17) patients with macroalbuminuria. Fasting plasma glucose, serum creatinine, Hb A1c %, lipid profile (Total c

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Publication Date
Sun May 01 2022
Journal Name
International Journal Of Multiphase Flow
Application of artificial neural network to predict slug liquid holdup
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Publication Date
Tue Feb 01 2022
Journal Name
Journal Of Engineering
Geomechanical study to predict the onset of sand production formation
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One of the costliest problems facing the production of hydrocarbons in unconsolidated sandstone reservoirs is the production of sand once hydrocarbon production starts. The sanding start prediction model is very important to decide on sand control in the future, including whether or when sand control should be used. This research developed an easy-to-use Computer program to determine the beginning of sanding sites in the driven area. The model is based on estimating the critical pressure drop that occurs when sand is onset to produced. The outcomes have been drawn as a function of the free sand production with the critical flow rates for reservoir pressure decline. The results show that the pressure drawdown required to

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