Chronic myelogenous leukemia (CML) is a myeloproliferative neoplasm arises from Bcr-Abl gene translocation (called Ph chromosome) in hematopoietic stem cells (HSCs). This genetic abnormality results in constitutive activation of tyrosine kinase and subsequent uncontrol growth and multiplication of granulocytes. The cornerstone in treatment of CML are tyrosine kinase inhibitors, of which imatinib is the most effectively used. JAK2V617F mutation is an acquired single nucleotide polymorphism (SNP) occurs in JAK2 gene and is associated with many hematological malignancy other than CML. It was thought that the two genetic abnormalities (Bcr-Abl and JAK2V617F) occur mutually; however, growing body of evidences suggested the reverse. This study aimed to investigate the prevalence of JAK2V617 mutation associated with serum levels of alkaline phophatase (ALK) and lactate dehydrogenase (LDH) in Ph+ CML Iraqi patients treated with imatinib. A total of 43 Ph+ CML patients (24 males and 18 females, age range 16-80 years) who attend Iraqi National Center of Hematology for Research and Treatment/Baghdad were enrolled in this study. Each patient has been received at least six month therapy with imatinib. A consent form involving age, gender, height, weight, smoking status, residency and first family relative history of leukemia was obtained from each patient. Besides, blood samples were collected, from which the granulocytes were separated and then DNA was extracted using a ready kit. Two assays were used for detection of JAK2V617F mutation; real time polymerase chain reaction (qPCR) using specific primers and probe, and allele specific PCR (AS-PCR) using specific primers. Total white blood corpuscles (WBC) as well as serum levels of ALP and LDH were measured. qPCR assay revealed 5 patients out of 43 (11.62%) were heterozygous for the muatant allele of JAK2V617F mutation (genotype GT). The concentration of this allele ranged from 0.01% to 0.12%. None of blood sample gave positive result for AS-PCR assay. From the all risk factors, only gender had significant association with the incidence of JAK2V617F mutation (p= 0.034, OR= 0.5, 95%CI= 0.364-0.687). Average total WBC count, and serum levels of ALP and LDH were higher in JAK2V617F-positive patients (9042±1512.55, 146.05±8.028 IU/L and 204±10.85 IU/L respectively) than that of JAK2V617F-negative patients (6039±1772.239, 64.45±40.15 IU/L and 178.33±13.693 IU/L respectively) with significant differences. These results indicate that JAK2V617F mutation can occur simultaneously with Ph chromosome in CML patients, and qPCR is a highly sensitive method for the detection of this mutation. Furthermore, serum activity of APL can be used as an indicator for the presence of JAK2V617F mutation in CML patients.
A total of 165 clinical sample included Urine, Swab wounds and Burns were collected from Baghdad Governorate. Results showed that rate all isolates of E. coli was 50(30.3%) and rate of urine infection was 46(92%) and rate of swab wounds infection 4(8%). Where was diagnostic based on streaked on MacConkey agar, then single colony was transferred to Eosin Methylene Blue (EMB). Identification some of the biochemical test included: Catalase test, Oxidase test, Indole test, Methyl red, Vogues - Proskauer test and Citrate Utilization test. Then confirmed by the Vitek - 2 Compact System. The ability of E.coli isolate to biofilm formation to be studied it is considered one of the most important factors of virulence and has role in causing injury an
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The method of heavy metals deposition which is based on cobalt in detection of Carbonic anhydrase enzyme in the Sulcus median in the hid brain (fourth ventricle) in the adult white rat (Rutts rutts). An essential amended in the method has been done by using cobalt chloride (CoCl2) instead of cobalt phosphate (Co3(PO4)2) in the reaction medium. Any efficacy of enzymic histochemical for carbonic anhydrase enzyme did not show in histological sections. The floor of the fourth ventricle of the brain is specific, clearly any histochemical reaction sediments have not been found in sulcus median of the floor of the fourth ventricle. The corresponding stain to green methyl which was observed clearly in sulcus median region. The ventral surface of
... Show MoreEchocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.
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Lymphoma is a cancer arising from B or T lymphocytes that are central immune system components. It is one of the three most common cancers encountered in the canine; lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic conditions and to improve decision-making around treating and what treatment type to use. This study aimed to evaluate a potential novel biomarker related to iron metabolism,
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with
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Detection of virulence gene agglutinin-like sequence (ALS) 1 by using molecular technology from clinical samples (
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Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio
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