Objective : Multiple sclerosis (MS) is a common neurological disease deeply linked with the immune-inflammatory disorders whereas the term (multiple) mostly refers to the multi-focal zones of Inflammation caused by lymphocytes and macrophages infiltration besides oligodendrocytes death. Accordingly , the dysfunctional immune system able to damage myelin ( a pivotal component of the central nervous system ) which responsible for communication among neurons. The aim of the present study is to innovate a biochemical relationship between MS and thyroid hormones (THs) by highlighting immunological responses and also to examine the action of Interferon beta (IFNβ) drug on thyroid hormone (THs) and thyroid stimulation hormone (TSH). Materials and methods: Sixty (60) Iraqi women in the age ranged (36-43) years were enrolled in the present study, (30) of them were MS patients and the other (30) were healthy. Anyway, the protocol of the study involved four groups: G1 is a healthy control group, G2 involved untreated MS patients, G3 included the MS patients treated with IFNβ for (6) weeks and G4 composed of the same patients treated with IFNβ for (12) weeks. THs (T4 and T3) and TSH levels were determined in sera of all groups. Results: Data of the present study have reported that T4 level was highly significant increase in sera of G2 compared with G1 while it was significant and highly significant decreased in G3 and G4 respectively compared with G2, the difference between G4 and G1 and also between G4 and G3 was significant. T3 level was highly significant increase in sera of G2 compared with G1 but it was highly significant decreased in G3 and G4 compared with G2, the difference between G4 and G1 was non-significant while the difference between G4 and G3 was significant. Conversely, TSH level was highly significant decreased in G2 compared with G1 but it was highly significant increase in G3 and G4 compared with G2, the difference between G4 and G1 and also between G4 and G3 was highly significant. Conclusions : Interestingly , the present study is the first in Iraq reporting that MS may be a key risk factor for hyperthyroidism and also the first suggesting that IFNβ regulates THs biosynthesis via novel immuno-neuro-enzymological mechanisms regarding thyroid peroxidase (TPO) and iodothyronine deiodinase 1 (D1), meanwhile the present study indicates that IFNβ has an indirect antioxidant activity. Moreover, the present study provides a definite clarification for the changed NF kappa B level in MS. Remarkably, the present study reveals that IFNβ is more potent on T3 than T4 while it has less action on TSH.
Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in
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tock markets changed up and down during time. Some companies’ affect others due to dependency on each other . In this work, the network model of the stock market is discribed as a complete weighted graph. This paper aims to investigate the Iraqi stock markets using graph theory tools. The vertices of this graph correspond to the Iraqi markets companies, and the weights of the edges are set ulrametric distance of minimum spanning tree.
Background: The Covid-19 pandemic changed the world; its most important achievement for education was changing the approach from traditional to virtual education. The present study aimed to investigate the role of virtual education networks on mental health of students including personality, beliefs, scientific, and cultural dimensions, in selected countries.Methods: This was an exploratory and applied study. According to the phenomenology strategy, theoretical saturation occurred after 24 semi-structured and targeted qualitative interviews with teachers from Iran, Iraq, Syria and Lebanon, in 2023. Quantitative data was collected through a researcher-made online questionnaire with 423 participants. Teachers with at least a Bachelor’s degr
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Far infrared photoconductive detectors based on multi-wall carbon nanotubes (MWCNTs) were fabricated and their characteristics were tested. MWCNTs films deposited on porous silicon (PSi) nanosurface by dip and drop coating techniques. Two types of deposited methods were used; dip coating sand drop –by-drop methods. As well as two types of detector were fabricated one with aluminum mask and the other without, and their figures of merits were studied. The detectors were illuminated by 2.2 and 2.5 Watt from CO2 of 10.6 m and tested. The surface morphology for the films is studied using AFM and SEM micrographs. The films show homogeneous distributed for CNTs on the PSi layer. The root mean square (r.m.s.) of the films surface roughness in
... Show MoreThe process of discovering pharmaceuticals is of great importance in our contemporary life, in a way that without life becomes almost impossible, as this process is the first building block in the field of pharmaceutical industries to search for new methods and means of treatment and treatment. But in fact, the fact that talking about this process is not that simple and easy, because this process is complicated and difficult in a way that makes it take a time range that in some cases reaches what is permissible ten years to reach a chemical formula that can be used later in the manufacturing process Pharmacokinetics, and during this long period of time, this process will have a set of effects, some of which are specific to the researcher di
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HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023
Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f
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