Background: Diabetic neuropathy can affect any peripheral nerve, including sensory neurons, motor neurons, and the autonomic nervous system. Therefore, diabetic neuropathy has the potential to affect essentially any organ and can affect parts of the nervous system like the optic nerve, spinal cord, and brain. In addition, chronic hyperglycemia affects Schwann cells, and more severe patterns of diabetic neuropathy in humans involve demyelization. Schwann cell destruction might cause a number of changes in the axon. study aims to evaluate serum myelin protein level as a predicting marker in the diagnosis of diabetic neuropathy and to prevent early neuropathy complications of type 2 diabetes.

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Background: Pregnancy is a physiological condition that affects the general and oral health.It is also associated with an increase in oxidative stress, which may presispose to oral diseases including dental caries. Aim of the study: This study aimed to measure salivary protein carbonyl, glutathione peroxidase and selenium levels of women who are pregnant and their association with dental caries in comparison to non-pregnant women, and to find out the mostly affected biomarker of oxidative stress during pregnancy. Subjects, materials and methods: A cross-sectional research was performed for a samples of 30 pregnant and 30 non-pregnant women who were chosen from city of Baghdad's Primary Healthcare Centers. Both groups aged 25-30 years. In

Background: The protective roles of vitamin C and total proteins in gingival inflammation were reported by several studies. The aim of this study was to measure the concentration of salivary vitamin C, total protein and their relation to gingival health among dental students. Materials and methods: The sample consisted of 67 dental students (33 males and 34 females) from College of Dentistry, University of Baghdad. Sillness and Löe (1964) was used for recording of dental plaque, while the gingival index (GI) was measured according to Löe and Sillness criteria (1963). Stimulated salivary samples were collected and chemically analyzed in Poisoning Center/Surgical Specialty Hospital by using colorimetric method to measure the salivary v

All the prepared metal complexes of Pt (IV), Au(III), Rh (III), Co (II) and V(IV) with new ligand sodium [5-(p-nitro phenyl)-/4-phenyl-1,2,4-triazole-3-dithiocarbamato hydrazide] (TRZ.DTC) have been synthesized and characterized in solid state by using flame atomic absorption, elemental analysis C.H.N.S, FT-IR ,UV-Vis Spectroscopy, conductivity and magnetic susceptibility measurements. The nature of the complexes formed in ethanolic solution has been studied following the molar ratio method also was studied stability constant and found to be stable in molar ratio1:1 of VL (IV) and CoL(II) while Pt(IV), Au(III) and Rh(III) complexes stable in molar ratio 1:2 as well as the molar absorptivity for these complexes were calculated. From the prev

New series of 4,4'-((2-(Aryl)-1H-benzo[d]imidazole1,3(2H)-diyl)bis(methylene))Diphenol(3a-g) was successfully synthesized from cyclization of the reduction product of bis Schiff bases (2) with aryl aldehydes bearing phenolic hydroxyl in the presence of acetic acid. The structure of these compounds was identified from FT-IR, 1H NMR, 13C NMR and EIMs. The Antioxidant capability was screened by DPPH and FRAP assays. Both assays showed antioxidant capability more than BHT as well. Compounds 3b and 3c showed antioxidant capacity slightly less than ascorbic acid. The docking study for theses compound was carried out as III DNA polymerase inhibitor. The results of docking demonstrated that the increase in hinderances around phenolic hydroxyl for t

New series of 4,4'-((2-(Aryl)-1H-benzo[d]imidazole-1,3(2H)-diyl)bis(methylene))Diphenol(3a-g) was successfully synthesized from cyclization of the reduction product of bis Schiff bases (2) with aryl aldehydes bearing phenolic hydroxyl in the presence of acetic acid. The structure of these compounds was identified from FT-IR, 1H NMR, 13C NMR and EIMs. The Antioxidant capability was screened by DPPH and FRAP assays. Both assays showed antioxidant capability more than BHT as well. Compounds 3b and 3c showed antioxidant capacity slightly less than ascorbic acid. The docking study for theses compound was carried out as III DNA polymerase inhibitor. The results of docking demonstrated that the increase in hinderances around phenolic hydr

     The current study was carried out to explore gene expression of the LTB4R gene with the development of chronic myeloid leukemia (CML) in Iraqi patients. The differences in the expression of this gene between patients and healthy controls were studied. The correlation of gender and age with CML patients compared with controls was included as well as the correlation of gene expression folding 2^-ΔΔCt of LTB4R with clinical parameters (WBC, RBC, haemoglobin, platelets, and BCR-ABL gene). Results revealed significant increases in the mean of gene expression level (ΔCt) of patient groups compared to the corresponding ΔCt means in the healthy control group, the gene expression folding (2^-∆∆Ct) of the L

In two commercial broiler breeds (Cobb 500 and Hubbard F-15), the polymorphisms of the chicken insulin-like growth factor 2 (IGF2) gene were studied. A total of three hundred avian blood samples were obtained. Using a fast salt-extraction technique, genomic DNA was isolated. Using polymerase chain reaction, 1146 bp fragments of the gene were amplified (PCR). The amplified fragments were subjected to restriction enzyme digestion using HinfI endonuclease enzyme, and the digested products were separated on a 2% agarose gel. The findings indicated two alleles T and C for the target locus, with respective frequencies of 73.3% and 26.7%. Three distinct genotype variations, TT, TC, and CC, were found, with genotype frequencies of 59.1 percent, 28.

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a