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

Mutations in genes encoding proteins necessary for detoxifying oxidative stress products have been predicted to increase susceptibility to lung cancer (LC). Despite this, the association between waterpipe tobacco smoking (WP), genetic polymorphisms, and LC risk remains poorly understood. This is the first study to explore the relationship between WP tobacco smoking and these genetic factors. Previously, we investigated the association of GSTP1 SNPs (rs1695-A/G and rs1138272-C/T) with LC in Iraqi males who smoke WP. Here, we expanded our analysis to include GSTM1 (active/null) and GSTT1 (active/null) genotypes, both individually and in combination with GSTP1 SNPs. Multiplex PCR and RFLP-PCR assays were utilized to determine the genotypes of

KE Sharquie, SA Al-Meshhadani, AA Al-Nuaimy, Saudi medical journal, 2007 - Cited by 9

Leishmania species are the causative agent of a tropical disease known as leishmaniasis. Previous studies on the old world species Leishmania major, showed that the amastigotes form which resides inside the macrophage of the vertebrate host, utilize host’s sphingolipids for survival and proliferation. In this study, gene expression of serine palmitoyltransferase (SPT) subunit two (MmLCB2) of the mouse macrophage cell line (RAW264.7), which is the first enzyme in the de novo sphingolipid biosynthesis, was detected in both infected and non-infected macrophages. This was detected under condition where available sphingolipid was reduced, with the new world species Leishmania mexicana. Results of qPCR analysis showed that there was no differen

Rheumatoid arthritis is a chronic systemic inflammatory disease. Inflammation leads to joint damage and increases the risk of cardiovascular diseases. Neutrophil lymphocyte ratio (NLR) is a measure of inflammation in many diseases. Therefore, we aimed to evaluate the usefulness of NLR to detect inflammation in RA, and its correlation to RA disease activity indices and some hematological parameters. A cross-sectional study involving 24 patients with active rheumatoid arthritis (RA) who are using MTX participated in this study. All patients were clinically evaluated using disease activity score of 28 joints (DAS28) and simplified disease activity index (SDAI), whereas functional disability was assessed by health assessment questionnaire di

This study was carried out to describe the gene expression of the micro RNA 122a gene with the development of diabetes in Iraq. The difference in gene expression between patients and healthy controls was properly considered. In this study, blood was isolated from 121 individuals divided into two groups as follows: 80 samples of diabetic patients and 41 samples from a healthy control. miRNA was isolated and transformed into cDNA, and the expression of mi122a was measured by qRT-PCR. The researchers looked at the relationship between age and gender and the occurrence of diabetes, as well as how they compared to controls. When comparing the mean gene expression level (Ct) of patient groups to the corresponding Ct means in the control group, th