Amino acids have the role in the process of proteins synthesis. They are an essential source of nitrogen atoms that have a role in the pathways of synthetic reaction pathways. The carbon skeletons of the amino acids are the source of energy in addition to their role as precursors in the paths of interactions. The amino acids analysis for the brain of the quail bird in different stage of development (10-16 days of incubation) in addition to the hatching stage (17th day) and the adult. Materials and Methods: Amino Acids Analysis The amino acids were separated from the embryos and adult brains of the quail bird Coturnix coturnix and were diagnosed based on standard amino acids, using high performance liquid chromatographic device (H.P.L.C.). Results: The results revealed that there are 16 amino acid: Aspartic acid, Glutamine, Serine, Histidine, Threonine, Glycine, Arginine, Alanine, Tyrosine, Cysteine, Valinine, Methionine, Isoleucine, Phenylalanine , Lysine, and the highest concentration of amino acid at age of [(13,13) days of incubation, adult, (13, 13, 16) days of incubation, adult, (13) days of incubation, adult, (13, 13, 11, 13, 13) days of incubation, adult, (13) days of incubation] respectively and the low concentration at age of [(14, 12, 10, 10,12,10,10,10,10, 14, 12, 12, 15, 10, 14, 10) days of incubation respectively]. Conclusions: It concluded from this that there was found 16 amino acid that were analyzed in the brains of the quail embryos at the stage (10-16) days of incubation and hatching stage (17) days of incubation and adult (Asp, Glu, Ser, His, Thr, Gly, Arg, Aln, Tyr, Cys, Val, Met, Ili, Leu, Phe, Lys, and Lys) the highest concentration of aging (13, 13, adult, 13, 13, 16, adult, 13, 13, 11, 13, 13, adult and 13) respectively, and less concentrated in ages (14, 12, 10, 10, 10, 10, 14, 12, 12, 15 10, 14, 10) days of incubation, respectively.
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Background: Toll-like receptors (TLRs) play a significant role in the activation of adaptive immunity and may have an essential role in the development of rheumatoid arthritis (RA). Objectives: To assess the gene expression of TLR4 in individuals with RA compared to healthy individuals. Methods: From July to December 2022. A total of 100 individuals were encompassed in the study, consisting of 50 individuals diagnosed with RA, of whom 42 were females and 8 were males, with an average age of 45.22 years. Additionally, there were 50 healthy control participants, 40 of whom were females and 10 were males, with an average age of 45.64 years. To assess the TLR4 transcript levels, blood samples were collected from each participant, and RN
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AW Ali T, Journal of the Faculty of Medicine, 2015 - Cited by 3
Type 1 diabetes (T1D) is an autoimmune disease with chronic nature resulting from a combination of both factors genetic and environmental. The genetic contributors of T1D among Iraqis are unexplored enough. The study aimed to shed a light on the contribution between genetic variation of interleukin2 (IL2) gene to T1D as a risk influencer in a sample of Iraqi patients. The association between IL2−330 polymorphism (rs2069762) was investigated in 322 Iraqis (78 T1D patients and 244 volunteers as controls). Genotyping for the haplotypes using polymerase chain reaction test – specific sequence primer (PCR-SSP) for (GG, GT, and TT) genotypes corresponding to (G and T) alleles were performed. A significant association revealed a decreased freq
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The aim of t his p aper is t o const ruct t he (k,r)-caps in t he p rojective 3-sp ace PG(3,p ) over Galois field GF(4). We found t hat t he maximum comp let e (k,2)-cap which is called an ovaloid, exist s in PG(3,4) when k = 13. Moreover t he maximum (k,3)-cap s, (k,4)-cap s and (k,5)-caps.
In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
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