Groupe sanguin

Résumé

Un 'groupe sanguin' est une classification reposant sur la présence ou l'absence de substances antigéniques héritées à la surface des globules rouges (hématies). Ces antigènes peuvent être des protéines, des glucides, des glycoprotéines ou des glycolipides, selon le système de groupe sanguin, et certains de ces antigènes sont également présents à la surface d'autres types de cellules de différents tissus. Les divers groupes sanguins sont regroupés en systèmes. Appartient à un même système de groupes sanguins l'ensemble des épitopes ou phénotypes résultant de l'action des divers allèles d'un même gène ou de gènes étroitement liés. Le sang est un tissu liquide que l’on peut facilement prélever sur un individu sain pour le transfuser à un individu malade. Or, malgré une composition cellulaire identique de ce tissu, il existe une variabilité, ou polymorphisme des divers éléments du sang entre les individus, ce qui rend impossible la transfusion entre certains groupes de personnes. On d

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https://fr.wikipedia.org/wiki/Groupe_sanguin

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Séances de cours associées (27)

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Chargement

Forecasting respiratory rate in sedated patients with partial least squares regression

Jérémie Guignard

Remifentanil, like the other sedative drugs used to achieve conscious sedation, has an impact on the efficiency of patient ventilation. Since the quality of breathing has an indirect effect on blood O2 and CO2 concentrations, keeping patients' blood homeostasis relies on anesthetists' and nurses' vigilence. The current state of patient monitoring during conscious sedation can detect unsuccessful respirations only after they have occurred. Hence, there is a clinical need for a signal classifier to predict potential respiration failure in sedated patients. Given that the physiological changes involved in this context are transitory, and that opioids affect the Central Nervous System, the hypothesis is that opioids' effect on a patient drive to breath will result in detectable changes in electrocardiogram and capnogram signals. The purpose of this project is to design a signal classiffier to predict respiratory rate (RR) based on the analysis of the ECG spectrum and capnogram shape. Using patient audit data, a modeling set was created. Power Spectral Density calculation on a sliding Hamming window was the feature extraction used on ECG. A custom filter was designed to extract values describing the shape of each breaths in terms of slope, curvature and integral of the capnographic trace. Both patient specific (single user) and robust (mulit-user) solution were investigated. PLS regression resulted in parsimonious patient specific models capable of predicting the respiratory rate with an average accuracy of 90%. The performance, however, dropped for low RR. The analysis of the weights showed that the frequencies under 7.5Hz contain the majority of the information. Several limitations are addressed in the building of a robust multi-user model. The results obtained suggest an existing patient-specific correlation between the frequency content of ECG and the upcoming RR. Further investigation is required to achieve clinically useful prediction

2009

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Rhesus Blood Typing within a Few Seconds by Packing-Enhanced Nanoscattering on Individual Erythrocytes

Po-Ling Chang, Sebastian James Davis, Aleksandra Radenovic

A method for the ABO and Rhesus (Rh) blood group typing from individual erythrocytes is proposed in this study. Blood-group-specific antibodies immobilized to gold nanoparticles (BG-AuNP) were utilized for the identification of blood groups from individual erythrocytes by objective-type dark-field microscopy (OTDFM). The scattering of free BG-AuNP and their Brownian motion as well as BG-AuNP attached on erythrocytes is easily observed by OTDFM. The strong scattering intensity caused by BG-AuNP packing-enhanced nanoscattering (PENS) on erythrocytes is first demonstrated. PENS combined with OTDFM allows us to identify blood groups within 5 s for all blood group antigens including A, B, D, C, c, E, and e. This was immediately identified by mixing with BG-AuNP without any washing step or waiting for hemoagglutination. Therefore, PENS combined with OTDFM demonstrates feasibility and advantages for use in emergency transfusions where the blood group of patients is unknown. Moreover, matching RhD+ in the case of emergency transfusions may also be beneficial in reducing the shortage of RhD- red blood cell concentrate in the case of a population with a high frequency in RhD-.

AMER CHEMICAL SOC2021

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In this paper, we present an automated approach to quantify information about three-dimensional (3D) morphology, hemoglobin content and density of mature red blood cells (RBCs) using off-axis digital holographic microscopy (DHM) and statistical algorithms. The digital hologram of RBCs is recorded by a CCD camera using an off-axis interferometry setup and quantitative phase images of RBCs are obtained by a numerical reconstruction algorithm. In order to remove unnecessary parts and obtain clear targets in the reconstructed phase image with many RBCs, the marker-controlled watershed segmentation algorithm is applied to the phase image. Each RBC in the segmented phase image is three-dimensionally investigated. Characteristic properties such as projected cell surface, average phase, sphericity coefficient, mean corpuscular hemoglobin (MCH) and MCH surface density of each RBC is quantitatively measured. We experimentally demonstrate that joint statistical distributions of the characteristic parameters of RBCs can be obtained by our algorithm and efficiently used as a feature pattern to discriminate between RBC populations that differ in shape and hemoglobin content. Our study opens the possibility of automated RBC quantitative analysis suitable for the rapid classification of a large number of RBCs from an individual blood specimen, which is a fundamental step to develop a diagnostic approach based on DHM. (C) 2012 Optical Society of America

Optical Society of America2012

Chargement

Forecasting respiratory rate in sedated patients with partial least squares regression

Jérémie Guignard

2009