Production and characterization of methionine γ- lyase from Pseudomonas putida and its effect on cancer cell lines

This article aims to estimate the partially linear model by using two methods, which are the Wavelet and Kernel Smoothers. Simulation experiments are used to study the small sample behavior depending on different functions, sample sizes, and variances. Results explained that the wavelet smoother is the best depending on the mean average squares error criterion for all cases that used.

Oral carcinoma is the 6th most common cancer in the world. MicroRNAs are small non-coding single stranded RNAs. They have been shown to be capable of altering mRNA expression; thus some are oncogenic or tumor suppressive in nature. The salivary microRNA-31 has been proposed as a sensitive marker for oral malignancy since it was abundant in saliva more than in plasma. A total of 55 whole saliva samples were collected from 35 cases diagnosed with OC their ages and gender matched with 20 healthy subjects. TaqManq RT-PCR was performed for RNA samples. Mean age was 52.23+13.73 years in cases (range:17-70 years) with male predominance represented 69%. Risk of smoking and alcoholism was highly significant. The median fold change of miR-31 was sign

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 focused on extracting the outer membrane nanovesicles (OMVs) from Escherichia coli BE2 (EC- OMVs) by ultracentrifugation, and the yield was 2.3mg/ml. This was followed by purification with gel filtration chromatography using Sephadex G-150, which was 2mg/ml. The morphology and size of purified EC-OMVs were confirmed by transmission electron microscopy (TEM) at 40-200 nm. The nature of functional groups in the vesicle vesicle was determined by Fourier transforms infrared spectroscopy (FT-IR) analysis. The antitumor activity of EC-OMVs was conducted in vitro by MTT assay in human ovarian (OV33) cancer cell line at 24,48 and 96hrs. The cytotoxicity test showed high susceptibility to the vesicles in ovarian compared to normal

Cytokines are A type of protein that is made by certain immune and non-immune cells and has an effect on the immune system. Some cytokines stimulate the immune system and others slow it down. Interleukins (ILs) can be divided into several families with more than 40 subfamily members. They can interact with a variety of cells that alter the immune system and act on a wide range of cancers. In the past several years, ILs have attracted substantial attention because of their distinct roles in CRC that provide a new and promising strategy for CRC. In general, ILs facilitate CRC by promoting tumorigenesis, tumour growth, angiogenesis, and cancer cell invasion and metastasis and inhibit CRC via complex pathways. The Bioassay Technology Human Inte

Background: The incidence of oral cancers is increasing all over the world. Early detection ofthis important public health matter makes them more amenable to treatment and allows the greatest chance of cure.The aim of this study was to investigate the awareness and knowledge on oral cancer among final -year dental students in Iraq. Materials and methods: Questionnaires were delivered to 160 final–year dental students in the College of Dentistry in Baghdad. The questionnaire focused on the awareness/knowledge of oral cancer, earlyand common clinical signs and symptoms andassociated risk factors. Results: It was found that 87% of students were aware of oral cancer. The followings were recognized as signs and symptoms of oral cancer: persis