PENGARUH PEMBERIAN MELATONIN TERHADAP JUMLAH LEUKOSIT PADA TIKUS WISTAR MODEL SEPSIS

Background : Melatonin was a free radical frequently used as an antioxidant. Melatonin played a role in increasing immune response, and supporting cytoprotective process. On some animal models, melatonin has been identified to be able to resist bacteria infections, viruses, and parasites through some mechanisms such as immunomodulation or antioxidant activities. Melatonin could decrease the level of inflammation cytokine, oxidative stress, and mitochondria dysfunction. Melatonin was one of medicine developed as a sepsis therapy. Objective : this research was to find out the melatonin influence on the amount of white blood cells of a wistar rat sepsis model and to obtain the information that melatonin could decrease the number of white blood cells. Methods : this research was an experimental research with a randomized control group using pre and post test. The samples were 12 male wistar rats with certain criteria divided into 2 groups. The first group was given an intraperitoneal injection of lipopolysaccharide (LPS) and was not given melatonin as control group. The second group was given an intraperitoneal injection of lipopolysaccharide (LPS) and was given melatonin by oral sonde as treatment group. After a week, in the eighth day, the blood of each rat was taken from the retro-orbital blood vessel. The statistical test used paired t-test, independent t-test, and Mann Whitney test. Results : In the independent test, the average score of the amount of white blood cells from control group was higher than the experimental group. In the paired t-test, the control group underwent a significant change (p<0,05) compared to experimental group which showed a meaningless result. In the Mann Whitney test, the result of pre-post 1 and post 2 from the control group got a significant increase while the result of pre LPS – post 1 and post 2 from the experimental group got a significant decrease (p<0,05). Conclusion : The melatonin treatment did not cause a significant decrease of the amount of white blood cells. Keywords : Sepsis,The amount of white blood cells, Melatonin, Lipopolysaccharide

Synergistic effect of zero-G and radiation on white blood cells. An experiment for the Gemini III manned space flight Annual report, period ending 30 Jun. 1965

Synergistic effect of weightlessness and radiation on white blood cells during Gemini 3 missio

An Investigation of Image and Video Classification Algorithm for White Blood Cells Detection in Real Time View

Medical industry is struggling in finding the cure for many types of disease especially cancer. It is known that white blood cell is used to protect the body against bacteria and diseases. Nowadays, many ways in separating white blood cells in human body were introduced for example; centrifugation. In this report, the author is using a new approach in separating the white blood cells to help with the immune system of human body. The new approach used in separating it by using image classification algorithm to separate the white blood cells from the blood capillaries and it will be done live from a video. By separating the white blood cells, we can study the behaviour of the immune system since white blood cells is responsible for immune system in human body

Automatic Leukemia Cell Counting using Iterative Distance Transform for Convex Sets

The calculation of white blood cells on the acute leukemia microscopic images is one of the stages in the diagnosis of Leukemia disease. The main constraint on calculating the number of white blood cells is the precision in the area of overlapping white blood cells. The research on the calculation of the number of white blood cells overlapping generally based on geometry. However, there was still a calculation error due to over segment or under segment. This paper proposed an Iterative Distance Transform for Convex Sets (IDTCS) method to determine the markers and calculate the number of overlapping white blood cells. Determination of marker was performed on every cell both in single and overlapping white blood cell area. In this study, there were tree stages: segmentation of white blood cells, marker detection and white blood cell count, and contour estimation of every white blood cell. The used data testing was microscopic acute leukemia image data of Acute Lymphoblastic Leukemia (ALL) and Acute Myeloblastic Leukemia (AML). Based on the test results, Iterative Distance Transform for Convex Sets IDTCS method performs better than Distance Transform (DT) and Ultimate Erosion for Convex Sets (UECS) method

Identification of White Blood Cells Using Machine Learning Classification Based on Feature Extraction

In various disease diagnoses, one of the parameters is white blood cells, consisting of eosinophils, basophils, neutrophils, lymphocytes, and monocytes. Manual identification takes a long time and tends to be subjective depending on the staff's experience, so the automatic identification of white blood cells will be faster and more accurate. White blood cells are identified by examining a colored blood smear (SADT) and examined under a digital microscope to obtain a cell image. Image identification of white blood cells is determined through HSV color space segmentation (Hue, Saturation Value) and feature extraction of the Gray Level Cooccurrence Matrix (GLCM) method using the Angular Second Moment (ASM), Contrast, Entropy, and Inverse Different Moment (IDM) features. The purpose of this study was to identify white blood cells by comparing the classification accuracy of the K-nearest neighbor (KNN), Naïve Bayes Classification (NBC), and Multilayer Perceptron (MLP) methods. The classification results of 100 training data and 50 white blood cell image testing data. Tests on the KNN, NBC, and MLP methods yielded an accuracy of 82%, 80%, and 94%, respectively. Therefore, MLP was chosen as the best classification model in the identification of white blood cells

A color and shape based algorithm for segmentation of white blood cells in peripheral blood and bone marrow images

Cataloged from PDF version of article.Computer-based imaging systems are becoming important tools for quantitative assessment of peripheral blood and bone marrow samples to help experts diagnose blood disorders such as acute leukemia. These systems generally initiate a segmentation stage where white blood cells are separated from the background and other nonsalient objects. As the success of such imaging systems mainly depends on the accuracy of this stage, studies attach great importance for developing accurate segmentation algorithms. Although previous studies give promising results for segmentation of sparsely distributed normal white blood cells, only a few of them focus on segmenting touching and overlapping cell clusters, which is usually the case when leukemic cells are present. In this article, we present a new algorithm for segmentation of both normal and leukemic cells in peripheral blood and bone marrow images. In this algorithm, we propose to model color and shape characteristics of white blood cells by defining two transformations and introduce an efficient use of these transformations in a marker-controlled watershed algorithm. Particularly, these domain specific characteristics are used to identify markers and define the marking function of the watershed algorithm as well as to eliminate false white blood cells in a postprocessing step. Working on 650 white blood cells in peripheral blood and bone marrow images, our experiments reveal that the proposed algorithm improves the segmentation performance compared with its counterparts, leading to high accuracies for both sparsely distributed normal white blood cells and dense leukemic cell clusters. (C) 2014 International Society for Advancement of Cytometr

Glucose transporter-4 in mononuclear cells of sled dogs

Thesis (M.S.) University of Alaska Fairbanks, 2013The glucose transporter-4 (GLUT4) is the glucose transporter most responsive to insulin and has been thought to exist predominately in muscle and adipose cells. There have been findings that the glucose transporter-4 isoform is also expressed in subpopulations of white blood cells such as mononuclear cells. This study was designed to validate the presence of GLUT4 in subpopulations of white blood cells of sled dogs and to investigate whether changes in GLUT4 protein levels in white blood cells might be associated with age and stage of conditioning, as it has been reported in muscle. Our initial results have shown the ability to detect GLUT4 in white blood cells of sled dogs with a non-significant trend observed in GLUT4 levels based on age. Subsequent testing showed a statistically significant difference in GLUT4 levels in mononuclear cells based on conditioning in sled dogs. Using sled dogs as a model should enhance our understanding of GLUT4 expression on the surface of subpopulations of white blood cells. The presented projects are groundbreaking for the development of an easy, reliable and minimally invasive diagnostic tool for insulin sensitivity. Our next step in this research is to examine whether the conditioning response of GLUT4 is also observed in human mononuclear cells

Factors Leading to White Blood Cell Misidentification

A study done to understand what factors lead to the correct identification of white blood cells (WBCs), and what factors are misleading. Research was conducted through an online survey where respondents who are trained to read peripheral blood smears were shown pictures of white blood cells, asked to identify them, and provide their reasoning

RBC and WBC fatty acid composition following consumption of an omega 3 supplement: Lessons for future clinical trials

<p>Abstract</p> <p>Background</p> <p>Results from increasing numbers of <it>in vitro </it>and <it>in vivo </it>studies have demonstrated that omega 3 fatty acids incorporated in cell culture media or in the diet of the animals can suppress the growth of cancers. When human clinical trials are initiated to determine the ability of omega 3 fatty acids to alter growth or response to chemotherapeutic interventions of cancers, it will be essential to determine the omega 3 intake of individuals in the trial to determine compliance with consumption of the supplement and to correlate with endpoints of efficacy. We wondered if the fatty acid composition of RBCs might accurately indicate incorporation of omega 3 fatty acids in the WBCs. In this report we determine and compare the changes in fatty acid compositions of red blood cells and white blood cells in response to consumption of three doses of an omega 3 fatty acid supplement.</p> <p>Results</p> <p>We found that the fraction of omega 3 fatty acids in both red blood cells and white blood cells increased following consumption of the supplement. There was a linear, dose responsive increase in the fraction of omega 3 fatty acids in red blood cells but the increase in omega 3 in white blood cells was not linear. The magnitude of increase in omega 3 fatty acids was different between the two cell types.</p> <p>Conclusions</p> <p>Fatty acid analysis of red blood cells is a good measure of compliance with supplement consumption. However, fatty acid analysis of white blood cells is needed to correlate changes in fatty acid composition of white blood cells with other biochemical changes in the white blood cells.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov NCT00899353.</p