The New Hematology Analyzer Sysmex XE-2100

2001 ◽  
Vol 125 (3) ◽  
pp. 391-396 ◽  
Author(s):  
Katharina Ruzicka ◽  
Mario Veitl ◽  
Renate Thalhammer-Scherrer ◽  
Ilse Schwarzinger
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Blood Cells ◽  
White Blood Cells ◽  
Reference Method ◽  
University Hospital ◽  
National Committee ◽  
Medical Electronics ◽  
Cell Counts ◽  
Hematology Analyzer

Abstract Context.—The new hematology analyzer Sysmex XE-2100 (TOA Medical Electronics, Kobe, Japan) has a novel, combined, white blood cell differential technology and a special reagent system to enumerate nucleated red blood cells. Design.—Performance evaluation of both technologies of the Sysmex XE-2100 according to the H20-A protocol of the National Committee for Clinical and Laboratory Standards and comparison of the results with those for the hematology analyzer Sysmex NE-8000 (TOA Medical Electronics). Specimens.—Five hundred forty-four blood samples randomly chosen from various inpatient and outpatient departments of the Vienna University hospital. Results.—Five-part white blood cell differential counts on the XE-2100 revealed excellent correlation with the manual reference method for neutrophils, lymphocytes, and eosinophils (r = .925, .922, and .877, respectively) and good correlation for monocytes and basophils (r = .756 and .763, respectively). The efficiency rates of flagging for the presence of ≥1% abnormal white blood cells were 83% (XE-2100) and 66% (NE-8000). The correlation of automated and microscopic nucleated red blood cell counts was excellent (r = .97). Conclusions.—From the present evaluation and our former experience with other types of Sysmex analyzers, we conclude that the new white blood cell differential technology of the XE-2100 represents a further development toward more efficient flagging of abnormal white blood cells.

scholarly journals High intake of vegetables is linked to lower white blood cell profile and the effect is mediated by the gut microbiome

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Cristina Menni ◽  
Panayiotis Louca ◽  
Sarah E. Berry ◽  
Amrita Vijay ◽  
Stuart Astbury ◽  
...  
Keyword(s):  
Blood Cell ◽  
Chronic Inflammation ◽  
White Blood Cell ◽  
Gut Microbiome ◽  
Blood Cells ◽  
Vegetable Intake ◽  
White Blood Cells ◽  
Cell Counts ◽  
Habitual Diet ◽  
Cell Profile

Abstract Background Chronic inflammation, which can be modulated by diet, is linked to high white blood cell counts and correlates with higher cardiometabolic risk and risk of more severe infections, as in the case of COVID-19. Methods Here, we assessed the association between white blood cell profile (lymphocytes, basophils, eosinophils, neutrophils, monocytes and total white blood cells) as markers of chronic inflammation, habitual diet and gut microbiome composition (determined by sequencing of the 16S RNA) in 986 healthy individuals from the PREDICT-1 nutritional intervention study. We then investigated whether the gut microbiome mediates part of the benefits of vegetable intake on lymphocyte counts. Results Higher levels of white blood cells, lymphocytes and basophils were all significantly correlated with lower habitual intake of vegetables, with vegetable intake explaining between 3.59 and 6.58% of variation in white blood cells after adjusting for covariates and multiple testing using false discovery rate (q < 0.1). No such association was seen with fruit intake. A mediation analysis found that 20.00% of the effect of vegetable intake on lymphocyte counts was mediated by one bacterial genus, Collinsella, known to increase with the intake of processed foods and previously associated with fatty liver disease. We further correlated white blood cells to other inflammatory markers including IL6 and GlycA, fasting and post-prandial glucose levels and found a significant relationship between inflammation and diet. Conclusion A habitual diet high in vegetables, but not fruits, is linked to a lower inflammatory profile for white blood cells, and a fifth of the effect is mediated by the genus Collinsella. Trial registration The ClinicalTrials.gov registration identifier is NCT03479866.

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 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%.

White Blood Cells Classification with Deep Convolutional Neural Networks

2018 ◽  
Vol 32 (09) ◽  
pp. 1857006 ◽  
Author(s):  
Ming Jiang ◽  
Liu Cheng ◽  
Feiwei Qin ◽  
Lian Du ◽  
Min Zhang
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Blood Cells ◽  
Network Architecture ◽  
White Blood Cells ◽  
Activation Function ◽  
Training Set ◽  
Deep Convolutional Neural Networks ◽  
Cell Image ◽  
Attending Physician

The necessary step in the diagnosis of leukemia by the attending physician is to classify the white blood cells in the bone marrow, which requires the attending physician to have a wealth of clinical experience. Now the deep learning is very suitable for the study of image recognition classification, and the effect is not good enough to directly use some famous convolution neural network (CNN) models, such as AlexNet model, GoogleNet model, and VGGFace model. In this paper, we construct a new CNN model called WBCNet model that can fully extract features of the microscopic white blood cell image by combining batch normalization algorithm, residual convolution architecture, and improved activation function. WBCNet model has 33 layers of network architecture, whose speed has greatly been improved compared with the traditional CNN model in training period, and it can quickly identify the category of white blood cell images. The accuracy rate is 77.65% for Top-1 and 98.65% for Top-5 on the training set, while 83% for Top-1 on the test set. This study can help doctors diagnose leukemia, and reduce misdiagnosis rate.

ALLIUM SATIVUM ESSENTIAL OIL (ASEO);

2017 ◽  
Vol 24 (04) ◽  
pp. 612-616
Author(s):  
Faisal Irshad ◽  
Hina Mawani ◽  
Sana Naz
Keyword(s):  
Essential Oil ◽  
Blood Cell ◽  
Blood Cells ◽  
Allium Sativum ◽  
White Blood Cells ◽  
Albino Rats ◽  
Serum Triglycerides ◽  
Cell Counts ◽  
Blood Cell Counts ◽  
Animal House

Objectives: To determine the effects of Allium sativum essential oil (ASEO)phytotherapy on serum triglycerides, total cholesterol, HDLc, LDLc and blood cell counts inalbino rat model. Study design: Experimental study. Setting and Duration: Animal House,Sindh Agriculture University and Isra University Hyderabad from May 2014 to January 2015.Materials and Methods: 60 albino rats were divided into four groups. Controls were givenPlacebo. Experimental rat groups were given ASEO 100 mg/kg, 200 mg/kg and 300 mg/kgorally for 30 days. Cardiac puncture was performed for blood sampling. Research variableswere analyzed on Statistix 10.0 (USA). Results: Blood lipids showed significant reduction invarious blood lipid fractions. Serum LDLc exhibited with a concomitant rise in serum HDLc (p=0.0001) in high ASEO treated rats. Red blood cells, white blood cells and platelet showedsignificant improvement ASEO fed rats (p=0.001). Conclusion: Allium sativum essential oil(ASEO) phytotherapy showed a rise in HDLc and a reduction in LDLc, triglycerides and totalcholesterol with improvement in red blood cell counts.

scholarly journals A Neural-Network-Based Approach to White Blood Cell Classification

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Mu-Chun Su ◽  
Chun-Yen Cheng ◽  
Pa-Chun Wang
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Classification System ◽  
Blood Cells ◽  
White Blood Cells ◽  
Recognition Rate ◽  
Color Space ◽  
Segmentation Algorithm ◽  
Cell Classification ◽  
Morphological Process

This paper presents a new white blood cell classification system for the recognition of five types of white blood cells. We propose a new segmentation algorithm for the segmentation of white blood cells from smear images. The core idea of the proposed segmentation algorithm is to find a discriminating region of white blood cells on the HSI color space. Pixels with color lying in the discriminating region described by an ellipsoidal region will be regarded as the nucleus and granule of cytoplasm of a white blood cell. Then, through a further morphological process, we can segment a white blood cell from a smear image. Three kinds of features (i.e., geometrical features, color features, and LDP-based texture features) are extracted from the segmented cell. These features are fed into three different kinds of neural networks to recognize the types of the white blood cells. To test the effectiveness of the proposed white blood cell classification system, a total of 450 white blood cells images were used. The highest overall correct recognition rate could reach 99.11% correct. Simulation results showed that the proposed white blood cell classification system was very competitive to some existing systems.

Comparison of white blood cell counts by WNR, WDF, and WPC channels in Sysmex XN hematology analyzer

2015 ◽  
Vol 37 (6) ◽  
pp. 869-875 ◽  
Author(s):  
H. Kim ◽  
M. Hur ◽  
S.-G. Choi ◽  
K.-M. Oh ◽  
H.-W. Moon ◽  
...  
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Cell Counts ◽  
Blood Cell Counts ◽  
Hematology Analyzer ◽  
White Blood Cell Counts

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 Evaluation of total and differential white blood cell counts in workers exposed to lead

2022 ◽  
Author(s):  
F Kargar-Shouroki ◽  
HR Mehri ◽  
F Sepahi-Zoeram
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Lead Level ◽  
White Blood Cells ◽  
Blood Lead ◽  
Exposed Group ◽  
Toxic Heavy Metal ◽  
Cell Counts ◽  
Differential White Blood Cell ◽  
Battery Workers

Introduction: Lead is a toxic heavy metal that has adverse health effects on blood parameters. About 80% of lead produced is used in batteries, especially vehicle batteries. Therefore, the present study aimed to assess the hematological changes, including total and differential white blood cell (WBC) counts in battery workers exposed to lead, and compare with the non-exposed group. Materials and Methods: This cross-sectional study was carried out in a battery industry in Semnan city. The study population consisted of 78 battery workers and 78 healthy non-exposed office workers. A hematology cell counter was used to determine the total, and differential WBC counts. Blood lead level was measured in accordance with the NIOSH method 8003. Results: Blood lead levels were about two times higher than the TLV recommended by the American Conference of Governmental Industrial Hygienists (ACGIH) for this compound (20 µg/dl). The level of WBC (8.07± 2.55 mm3 blood×103 vs. 7.27 ± 1.58 mm3 blood×103) was significantly higher, while the level of monocyte was significantly lower (6.96 ± 1.72 % vs. 7.67 ± 1.87 %) in the exposed group than in the non-exposed group. After adjustment for potential confounders such as age and work history, a significant association between exposure to lead and WBC and monocyte levels was reported. Conclusion: The present study's findings indicated that exposure to lead was associated with total and differential white blood cells changes in the exposed group compared to the non-exposed group.

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