scholarly journals Changes in Leukogram and Erythrogram Results in Bitches with Vaginitis

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1403
Author(s):  
Maria Chmurska-Gąsowska ◽  
Bartosz Bojarski ◽  
Natalia Sowińska ◽  
Magdalena Strus
Keyword(s):  
Clinical Practice ◽  
Inflammatory Response ◽  
Blood Cell ◽  
Blood Cells ◽  
White Blood Cells ◽  
Diagnostic Process ◽  
Blood Smears ◽  
Different Types ◽  
Blood Cell Morphology ◽  
Hematological Changes

Vaginitis in female dogs is a problem most veterinarians face in their practice. It manifests as localized inflammation, and its variable etiology and different severities often make diagnosis problematic. The study consisted of comparing blood smears taken from 16 animals: 8 healthy bitches and 8 bitches with confirmed vaginitis. We analyzed the percentage of different types of white blood cells (leukogram) and changes in the shape of red blood cells (erythrogram) in both groups. We observed changes in red blood cell morphology, i.e., a higher percentage of lacrimocytes and schistocytes in female dogs with vaginitis compared to their healthy counterparts. The observed hematological changes may illustrate the severity of inflammation. The analysis of erythrograms showed a significantly higher percentage of lacrimocytes and schistocytes in diseased bitches (1.58 ± 1.19% and 0.13 ± 0.12%) compared to healthy animals (0.58 ± 0.38 and 0.00 ± 0.00, respectively). The obtained results may indicate that the analysis of erythrograms throughout the course of vaginitis in bitches may constitute a diagnostic tool, as opposed to the analysis of leukograms, which is more sensitive when it comes to the systemic inflammatory response of the organism. It seems that simultaneous analysis of erythrograms and leukograms may facilitate the diagnostic process in clinical practice.

scholarly journals Hematological changes of Anemia`s in Horses of Equestrian club in Baghdad

2012 ◽  
Vol 36 (0A) ◽  
pp. 92-97
Author(s):  
Faisal G. Habasha
Keyword(s):  
Blood Cell ◽  
Sedimentation Rate ◽  
Red Blood Cell ◽  
Packed Cell Volume ◽  
Blood Cells ◽  
White Blood Cells ◽  
Blood Samples ◽  
Erythrocyte Sedimentation ◽  
Blood Smears ◽  
Hematological Changes

This study was conducted to know thehematological changes of anemia in horsesat equestrian club in Baghdad. Blood samples were collected from 151 horses of both sexes(74 male and 77 female) and different agesrandomly. The study includedred blood cells count, white blood cells, hemoglobin, packed cell volume and differential blood smears, togetherwith erythrocyte sedimentation rate readings. The study showed increased white blood cells count mainly neutrophilwith decreased hemoglobinand red blood cell countin addition to erythrocyte sedimentation rate.The blood smears showeddifferent changes of red blood cell.

scholarly journals Klasifikasi Sel Darah Putih dan Sel Limfoblas Menggunakan Metode Multilayer Perceptron Backpropagation

2019 ◽  
Vol 9 (2) ◽  
pp. 173
Author(s):  
Apri Nur Liyantoko ◽  
Ika Candradewi ◽  
Agus Harjoko
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Blood Cells ◽  
White Blood Cells ◽  
Back Propagation ◽  
Cell Types ◽  
Diagnostic Process ◽  
The Subject ◽  
Processing Techniques

 Leukemia is a type of cancer that is on white blood cell. This disease are characterized by abundance of abnormal white blood cell called lymphoblast in the bone marrow. Classification of blood cell types, calculation of the ratio of cell types and comparison with normal blood cells can be the subject of diagnosing this disease. The diagnostic process is carried out manually by hematologists through microscopic image. This method is likely to provide a subjective result and time-consuming.The application of digital image processing techniques and machine learning in the process of classifying white blood cells can provide more objective results. This research used thresholding method as segmentation and  multilayer method of back propagation perceptron with variations in the extraction of textural features, geometry, and colors. The results of segmentation testing in this study amounted to 68.70%. Whereas the classification test shows that the combination of feature extraction of GLCM features, geometry features, and color features gives the best results. This test produces an accuration value 91.43%, precision value of 50.63%, sensitivity 56.67%, F1Score 51.95%, and specitifity 94.16%.

scholarly journals STUDIES ON THE PHYSIOLOGY OF THE WHITE BLOOD CELL

Blood ◽  
1947 ◽  
Vol 2 (3) ◽  
pp. 235-243 ◽  
Author(s):  
RICHARD WAGNER
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Blood Cells ◽  
Glycogen Content ◽  
Striated Muscle ◽  
White Blood Cells ◽  
Glycogen Storage ◽  
Different Types ◽  
Blast Cells ◽  
Reducing Substances

Abstract The technic of determining glycogen in isolated white blood cells was applied to the study of the different types of leukemia and of polycythemia, in order to obtain information on the physiology of the white blood cell. From this study it is concluded that the granulated leukocyte is the only carrier of glycogen in whole blood. The "reducing substances" in lymphocytes and blast cells are not considered as true glycogen. The glycogen content of wet white blood cells in the rabbit amounts to about 1 per cent. In the human being a range of from 0.17 to 0.67 per cent was calculated. In disease higher percentages occur, in polycythemia up to 1.64 per cent and in glycogen storage disease up to 3.05 per cent. The glycogen concentration of normal white blood cells is within the same range as that of the striated muscle.

scholarly journals Deep Learning Model for the Automatic Classification of White Blood Cells

2022 ◽  
Vol 2022 ◽  
pp. 1-13
Author(s):  
Sarang Sharma ◽  
Sheifali Gupta ◽  
Deepali Gupta ◽  
Sapna Juneja ◽  
Punit Gupta ◽  
...  
Keyword(s):  
Deep Learning ◽  
Blood Cell ◽  
Cell Count ◽  
Blood Cells ◽  
White Blood Cells ◽  
Batch Size ◽  
Blood Cell Count ◽  
Sophisticated Equipment ◽  
Different Types ◽  
Batch Sizes

Blood cell count is highly useful in identifying the occurrence of a particular disease or ailment. To successfully measure the blood cell count, sophisticated equipment that makes use of invasive methods to acquire the blood cell slides or images is utilized. These blood cell images are subjected to various data analyzing techniques that count and classify the different types of blood cells. Nowadays, deep learning-based methods are in practice to analyze the data. These methods are less time-consuming and require less sophisticated equipment. This paper implements a deep learning (D.L) model that uses the DenseNet121 model to classify the different types of white blood cells (WBC). The DenseNet121 model is optimized with the preprocessing techniques of normalization and data augmentation. This model yielded an accuracy of 98.84%, a precision of 99.33%, a sensitivity of 98.85%, and a specificity of 99.61%. The proposed model is simulated with four batch sizes (BS) along with the Adam optimizer and 10 epochs. It is concluded from the results that the DenseNet121 model has outperformed with batch size 8 as compared to other batch sizes. The dataset has been taken from the Kaggle having 12,444 images with the images of 3120 eosinophils, 3103 lymphocytes, 3098 monocytes, and 3123 neutrophils. With such results, these models could be utilized for developing clinically useful solutions that are able to detect WBC in blood cell images.

scholarly journals Early White Blood Cell Dynamics after Traumatic Brain Injury: Effects on the Cerebral Microcirculation

1997 ◽  
Vol 17 (11) ◽  
pp. 1210-1220 ◽  
Author(s):  
Roger Härtl ◽  
Max B. Medary ◽  
Maximilian Ruge ◽  
Karl E. Arfors ◽  
Jam Ghajar
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Intracranial Pressure ◽  
Inflammatory Response ◽  
Blood Cell ◽  
White Blood Cell ◽  
Blood Cells ◽  
White Blood Cells ◽  
Cerebral Microcirculation ◽  
Fluid Percussion Injury

Increasing clinical and experimental evidence suggests that traumatic brain injury (TBI) elicits an acute inflammatory response. In the present study we investigated whether white blood cells (WBC) are activated in the cerebral microcirculation early after TBI and whether WBC accumulation affects the posttraumatic cerebrovascular response. Twenty-four anesthetized rabbits had chronic cranial windows implanted 3 weeks before experimentation. Animals were divided into four experimental groups and were studied for 7 hours (groups I, IIa, and III) or 2 hours (group IIb). Intravital fluorescence videomicroscopy was used to visualize WBC (rhodamine 6G, intravenously), pial vessel diameters, and blood–brain barrier (BBB) integrity (Na+-fluorescein) at 6 hours (groups I, IIa, and III) or 1 hour (group IIb) after TBI. Group I (n = 5) consisted of sham-operated animals. Groups IIa (n = 7) and IIb (n = 5) received fluid-percussion injury at 1 hour. Group III (n = 7) received fluid-percussion injury and 1 mg/kg anti–adhesion monoclonal antibody (MoAb) “IB4” 5 minutes before injury. Venular WBC sticking, intracranial pressure (ICP), and arterial vessel diameters increased significantly for 6 hours after trauma. IB4 reduced WBC margination and prevented vasodilation. Intracranial pressure was not reduced by treatment with IB4. Blood–brain barrier damage occurred at 1 hour but not at 6 hours after TBI and was independent of WBC activation. This first report using intravital videomicroscopy to study the inflammatory response after TBI reveals upregulated interaction between WBC and cerebral endothelium that can be manipulated pharmacologically. White blood cell activation is associated with pial arteriolar vasodilation. White blood cells do not induce BBB breakdown less than 6 hours after TBI and do not contribute to posttraumatic ICP elevation. The role of WBC more than 6 hours after TBI should be investigated further.

scholarly journals Design and Simulation of a Point-of-Care Microfluidic Device for Acoustic Blood Cell Separation

2020 ◽  
Vol 2 (1) ◽  
pp. 76
Author(s):  
Fatemeh Sharifi ◽  
Armin Sedighi ◽  
Mubashar Rehman
Keyword(s):  
Blood Cell ◽  
Red Blood Cells ◽  
Blood Cells ◽  
Cell Separation ◽  
Numerical Study ◽  
Point Of Care ◽  
Surface Acoustic Waves ◽  
White Blood Cells ◽  
Microfluidic Channel ◽  
Diagnostic Process

Hematology tests, considered as an initial step in the patient diagnostic process, require laboratory equipment and technicians which is a time- and labor-consuming procedure. Such facilities may be available in a few central laboratories in under-resourced countries. The growing need for low cost and rapid diagnostic tests contributes to point-of-care (POC) medical diagnostic devices providing convenient and rapid test tools particularly in areas with limited medical resources. In the present study, a comprehensive numerical simulation of a POC blood cell separation device (POC-BCS) has been modeled using a finite element method. Tag-less separation of blood cells, i.e., platelets, red blood cells, and white blood cells, was carried out using standing surface acoustic waves (SSAWs) generated by interdigital transducers (IDTs) located at lateral sides of the microfluidic channel. Blood sample intake along with sheath flow was introduced via two symmetrical tilted angle inlets and a middle inlet, respectively. Superposition of acoustic radiation force applied by SSAWs accompanied by drag force caused by medium flow drove the blood cells toward different path lines correlated to their size. White blood cells were sorted out in the middle outlet and red blood cells and platelets were sorted out through the separate locations of the side outlets. Each cell was then guided to their respected visualization chamber for further image processing analysis. The results of the presented numerical study would be very promising in designing and optimizing the POC blood testing device.

scholarly journals White Blood Cells and Severe COVID-19: A Mendelian Randomization Study

2021 ◽  
Vol 11 (3) ◽  
pp. 195
Author(s):  
Yitang Sun ◽  
Jingqi Zhou ◽  
Kaixiong Ye
Keyword(s):  
Blood Cell ◽  
Cell Count ◽  
White Blood Cell Count ◽  
White Blood Cell ◽  
Blood Cells ◽  
Mendelian Randomization ◽  
Association Studies ◽  
White Blood Cells ◽  
Genome Wide Association Studies ◽  
Blood Cell Count

Increasing evidence shows that white blood cells are associated with the risk of coronavirus disease 2019 (COVID-19), but the direction and causality of this association are not clear. To evaluate the causal associations between various white blood cell traits and the COVID-19 susceptibility and severity, we conducted two-sample bidirectional Mendelian Randomization (MR) analyses with summary statistics from the largest and most recent genome-wide association studies. Our MR results indicated causal protective effects of higher basophil count, basophil percentage of white blood cells, and myeloid white blood cell count on severe COVID-19, with odds ratios (OR) per standard deviation increment of 0.75 (95% CI: 0.60–0.95), 0.70 (95% CI: 0.54–0.92), and 0.85 (95% CI: 0.73–0.98), respectively. Neither COVID-19 severity nor susceptibility was associated with white blood cell traits in our reverse MR results. Genetically predicted high basophil count, basophil percentage of white blood cells, and myeloid white blood cell count are associated with a lower risk of developing severe COVID-19. Individuals with a lower genetic capacity for basophils are likely at risk, while enhancing the production of basophils may be an effective therapeutic strategy.

scholarly journals Blood Cell Count Using Deep Learning Semantic Segmentation

2019 ◽  
Author(s):  
Thanh Tran ◽  
Lam Binh Minh ◽  
Suk-Hwan Lee ◽  
Ki-Ryong Kwon
Keyword(s):  
Deep Learning ◽  
Blood Cell ◽  
Cell Count ◽  
Blood Cells ◽  
Blood Smear ◽  
White Blood Cells ◽  
Semantic Segmentation ◽  
Peripheral Blood Smear ◽  
Cell Counting ◽  
Blood Cell Count

Clinically, knowing the number of red blood cells (RBCs) and white blood cells (WBCs) helps doctors to make the better decision on accurate diagnosis of numerous diseases. The manual cell counting is a very time-consuming and expensive process, and it depends on the experience of specialists. Therefore, a completely automatic method supporting cell counting is a viable solution for clinical laboratories. This paper proposes a novel blood cell counting procedure to address this challenge. The proposed method adopts SegNet - a deep learning semantic segmentation to simultaneously segment RBCs and WBCs. The global accuracy of the segmentation of WBCs, RBCs, and the background of peripheral blood smear images obtains 89% when segment WBCs and RBCs from the background of blood smear images. Moreover, an effective solution to separate grouped or overlapping cells and cell count is presented using Euclidean distance transform, local maxima, and connected component labeling. The counting result of the proposed procedure achieves an accuracy of 93.3% for red blood cell count using dataset 1 and 97.38% for white blood cell count using dataset 2.

scholarly journals PO-283 Correlation Analysis between Blood Cell Viability, Five Elements and Competition Performance of Elite Men’s Rowers

2018 ◽  
Vol 1 (5) ◽  
Author(s):  
Junbei Bai
Keyword(s):  
Blood Cell ◽  
Red Blood Cells ◽  
Aerobic Capacity ◽  
Red Blood Cell ◽  
Iron Content ◽  
Blood Cells ◽  
White Blood Cells ◽  
Cell Activity ◽  
Ordinary People ◽  
Five Elements

Objective To observe the national elite male rowers blood, red blood cell activity and serum copper, zinc, calcium, magnesium and iron content of the five elements, and compared with the ordinary people. Aimed to investigate the between athletes, athletes and ordinary differences between the two sets of indicators and to explore the impact of element contents in red blood cell activity and five factors. Trying to bring two sets of indicators and specific combining ability, used in training on the monitoring function, and for the future to provide some references for further study. Methods It was included 22 athletes and 22 ordinary men, as the research object, in the collection of blood, measuring red blood cell activity in the blood content of the five elements, simultaneous measurement of physical indicators , will be doing all the data at the differences between the two groups compared to the group to do correlation analysis. The recent record of 2000m, 6000m rowing Dynamometer test results, and red blood cell activity associated with the five elements of content analysis. Results 1. Athletes indicators related to aerobic exercise were significantly higher than ordinary people. The white blood cells of athletes group were average.It shows that athletes have high aerobic capacity, while white blood cells are more stable than normal people. The members of the national rowing men's iron, magnesium content was significantly higher than ordinary group, the iron content is higher than the normal reference value; blood calcium levels were significantly lower than ordinary people, and lower than the normal reference value. The total number of red blood cells and the number of living cells was very significant positive correlation in two groups subjects; Red blood cell activity and red blood cell diameter is proportional, and red blood cell roundness in inverse proportion to the relationship; from this experiment a special ability to see red blood cell activity and there is no correlation. In both groups, hemoglobin was positively correlated with iron content, while iron was positively correlated with copper content. Conclusions 1. Increasing the number and volume of red blood cells can effectively increase the activity of red blood cells; red blood cell activity has no correlation with specific ability, and can not be used as an indicator to determine specific ability. The content of iron and magnesium in rowers is higher than that in ordinary people, which indicates that the adjustment of aerobic capacity and nerve control is very effective. The lower calcium content indicates that the injury caused by calcium loss should be prevented and the urgency of calcium supplementation should be emphasized. In training, we should pay attention to increasing hemoglobin content and aerobic capacity by supplementing iron. We can further consider the effect of supplementing copper to promote iron supplementation.

scholarly journals Effects of dietary Mannan oligosaccharide (MOS) on grown, survival rate, intestinal morphology and blood cell count of the golden trevally fish (Gnathanodon specious)

2019 ◽  
Vol 19 (4A) ◽  
pp. 241-250
Author(s):  
Dang Tran Tu Tram ◽  
Nguyen Thi Nguyet Hue ◽  
Ho Son Lam ◽  
Nguyen Truong Tan Tai ◽  
Dao Thi Hong Ngoc
Keyword(s):  
Survival Rate ◽  
Blood Cell ◽  
Blood Cells ◽  
White Blood Cells ◽  
Intestinal Morphology ◽  
The Other ◽  
Control Group ◽  
Blood Cell Count ◽  
Mannan Oligosaccharide ◽  
Erythrocyte Density

The golden trevally fishes (Gnathanodon specious) (2.19 ± 0.23 g) were cultured in glass tanks with density of 20 fishes/tank and they were fed supplemental diets of different MOS concentrations (0; 0.2; 0.4 and 0.6%) for 90 days. Collected data included growth rate, survival rate and some hematological characteristics of this fish. The results demonstrated that MOS supplementation did not affect growth performance, erythrocyte density and blood cell size, however the survival rate was significantly increased. On the other hand, the total number of white blood cells (BC) on the 60th day in the fish fed with MOS supplements (5.78–6.96 × 104TB/mm3) was higher than that in the control group (only 5.43 × 104TB/mm3) with the largest total leukocytes (6.96 ± 0.50 × 104TB /mm3) at 0.2% MOS (p < 0.05).

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