Background: Metabolic syndrome (Mets) is partially heritable. High mobility group AT-hook1 (HMGA1), an architectural transcription factor, affects the homeostasis of glucose. The marked inter-individual differences between T

Objective: Zerumbone (ZER) is a well-known natural compound that has been reported to have anti-cancer effect. Thus, this study investigated the ZER potential to inhibit Thymidine Phosphorylase (TP) and the ability to trigger Reactive oxygen species (ROS)-mediated cytotoxicity in non-small cell lung cancer, NCI-H460, cell line. Material and Method: The antiangiogenic activity for ZER was evaluated by using the thymidine phosphorylase inhibitory test. Reactive oxygen species (ROS) production was determined via DCFDA dye by using flow cytometry. Result and Discussion: ZER was found to be potent TP inhibitory with the IC50 value of 50.3± 0.31 μg/ml or 230±1.42 µM. NCI-H460 cells upon treatment with ZER produced sign

Objective: Zerumbone (ZER) is a well-known natural compound that has been reported to have anti-cancer effect. Thus, this study investigated the ZER potential to inhibit Thymidine Phosphorylase (TP) and the ability to trigger Reactive oxygen species (ROS)-mediated cytotoxicity in non-small cell lung cancer, NCI-H460, cell line. Material and Method: The antiangiogenic activity for ZER was evaluated by using the thymidine phosphorylase inhibitory test. Reactive oxygen species (ROS) production was determined via DCFDA dye by using flow cytometry. Result and Discussion: ZER was found to be potent TP inhibitory with the IC50 value of 50.3± 0.31 μg/ml or 230±1.42 µM. NCI-H460 cells upon treatment with ZER produced sign

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

Anaemia is a crucial issue among cancer patients and need to be treated properly. High incidence of anaemia in patients with cancer have been associated with several physiological manifestations, leading to decreased quality of life (QOL).

The current study aimed to assess the severity of anaemia, evaluate the current treatment guideline of anaemia, and to determine the association between the level of anaemia and its treatment on quality of life of breast cancer patients in Malaysia. This prospective study conducted among breast cancer patients in multicancer centers in Malaysia including three follow ups after receiving their chemotherapy. Clinical data were collected from their medical records and at each follow up, they asked

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

This study was aimed to determine the mutations and single nucleotide polymorphisms (SNPs) in exon 3 and 7 of estrogen receptor beta (ESR2) gene in women with breast cancer from Iraq. Different samples (blood, fresh tissue with blood from same patient, and formalin fixed paraffin embedded, FFPE) were collected from women with breast cancer. Molecular analysis exon 3 and 7 in ESR2 has been studied by using PCR. It was found exon 3 and 7 in ESR2 were revealed as a single band with size 151 and 157 bp, respectively. There was no SNP in exon 3 has been identified. While three novel polymorphisms (ACT, AGG and GCA) were detected in exon 7, the type of those polymorphisms deletion for ACT and AGG while substitution polymorphism for GCA. From this

The nature and intensity of the association of myasthenia gravis (MG) with distinct human leukocyte antigen (HLA) haplotypes differ between ethnic populations, so this study determined the association of HLA class II antigens with myasthenia gravis (MG) in Iraq.The study included Iraqi patients diagnosed with MG and two control groups the first of 54 insulin dependent diabetes mellitus patients and the second of 237 subjects as a normal control group. The test used was microlymphocytotoxicity test.The work was done in the Teaching Laboratories/Medical City/Baghdad.Results: positive associations were observed (etiological risk factors) as follows: 1. HLA-DR locus showed one positively associated allele when compared to healthy control and th

Background: Acute radiodermatitis is a common side effect during and after radiotherapy course in breast cancer patients treated by radiotherapy. This study assess the frequency of acute radiodermatitis and record the predictive factors for acute radiodermatitis. Patients and Methods: A descriptive case series study conducted at Baghdad, Iraq from August 2020 to September 2021. 70 female scheduled for radiotherapy sessions enrolled in this study. sociodemographic data were recorded and Skin examination before radiotherapy and weekly till the end of the radiotherapy sessions was done to report the frequency, risk factors, clinical picture and grades of acute radiodermatitis based on The National Cancer Institute’s Common Terminology Crite