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 Interleukin 6, Interleukin 1 alpha (E0090Hu) and C-reactive protein Kits was used. The quantitative determination of human interleukins concentrations and CRP were used in serum, plasma, cell culture supernatant, cell lysates and tissue homogenates .One hundred and twenty blood samples were collected from patients in gastrointestinal and hepatic hospital during the period from Feb 2019 to Feb 2020. Results revealed that the measuring the interleukin-alpha and intravenous blood levels of the subjects in our sample were different, but the difference with the other groups was very small, where the concentration rate was reported in the 699.84 ±51.39 colorectal cancer group and was similar to the other three groups, the average concentration of interleukin 6 in samples of patients with colorectal cancer was 48.81 + - 15.96 compared to the remaining groups, The analyses of the serum CRP concentration measurement were in patients with colorectal cancer, the concentration ratio was 31.45 ±7.94 relative to the performance of the other groups.
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
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Lung cancer is the most common dangerous disease that, if treated late, can lead to death. It is more likely to be treated if successfully discovered at an early stage before it worsens. Distinguishing the size, shape, and location of lymphatic nodes can identify the spread of the disease around these nodes. Thus, identifying lung cancer at the early stage is remarkably helpful for doctors. Lung cancer can be diagnosed successfully by expert doctors; however, their limited experience may lead to misdiagnosis and cause medical issues in patients. In the line of computer-assisted systems, many methods and strategies can be used to predict the cancer malignancy level that plays a significant role to provide precise abnormality detectio
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This study tries to clear the correlation and association between asthma, obesity and leptin levels. Also it will work to indicate the main risk factors which play role in the elevation of leptin level within asthmatic patients. This is a case control study conducted on (38) asthmatic patients and (20) healthy control who were closely similar by age, gender and BMI. The main statistical tests used were student t test, linear regression test and correlation test. Significance was set at P < 0.05. Sampling method used for this study was convenience sampling method. The main results of this study show a significant association and positive correlation between age (old age ≥ 40 ye
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Theresearch took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide a practical evident that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial andthat includes all of them spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. Spatial analysis had
... Show MoreThe research took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide practical evidence that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial and that includes all of the spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. The spatial analysis had been applied to Iraq Household Socio-Economic Survey: IHS
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Objectives: With the advent of ongoing novel modalities toward the treatment of human epidermal growth factor receptor 2 (HER2)/NEU - positive malignancies, the serious side effects of chemoradiotherapy have been minimized. Hence, this study was conducted to identify the patterns of immunohistochemical expression of the promising therapeutic target (HER2/NEU) among Iraqi patients with medulloblastoma in an attempt to provide basic histological information’s that would help in future clinical researches.Materials and Methods: In this retrospective study, 42 formalin - fixed paraffin - embedded tissue blocks represent cases of surgically removed medulloblastomas were retrieved from the archived materials in a specialized surgical ho
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Type 2 diabetes mellitus which abbreviate as T2DM is a complex endocrine and metabolic disorder arisingfrom genetic and environmental factors interaction which in turn induce various degrees of insulin functionalalteration on peripheral tissues. Globally, T2DM has develop into a public health problem. Therefore, Thestudy included (75) patients(37 female and 38 males) suffering from T2DM who visit al-kadhimiya teachinghospital with age range 20-80 years and (70) as healthy controls with age range 20-70 years. All studiedgroups were evaluated CMV IgG by ELISA,B. urea, S. Creatinine, cholesterol and triglyceride the resultsshowed that B.urea, S.creatinine and serum cholesterol showed a non-significant differences between studiedgroup,
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Afamin, which is a human plasma glycoprotein, a putative multifunctional transporter of hydrophobic molecules and a marker for metabolic syndrome. Afamin concentration have been proposed to have a significant role as a predictor of metabolic disorders. Since NAFLD is associated with metabolic risk factors, e.g., dyslipidemia, insulin resistance and visceral obesity, it is considered as the hepatic manifestation of the metabolic syndrome. The objective of this study is to determine Afamin levels in hypothyroid patients with and without fatty liver disease and compare the results with controls. Also to study the relationship of Afamin level with the Anthropometric and Clinical Features (Age, Gender, BMI and Duration of Hypothyroidism) , Serum
... Show MoreDetermining risk indicators for dental implants is an essential strategy for preventing peri-implant diseases and effective diagnosis of dental implant success. To investigate the impact of certain potential factors on the osseointegrated dental implant. Eighty-four individuals were included in our study, 50 cases as a patient’s group and 34 participants as a control group. All cases were diagnosed based on certain criteria, 30 (60%) of patients had peri-implantitis, 20 (40%) with severe periimplantitis, 36(72%) were generalized, and 15 (30%) as localized peri-implantitis cases. The study has indicated that 44.7% of dental implants were in the anterior maxilla, followed by (27.3%) posterior maxilla, (17.4%) posterior mandible, and (10.4%)
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