AIMC Topic: Erythrocytes
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Objective assessment of stored blood quality by deep learning.
Proceedings of the National Academy of Sciences of the United States of America
Aug 24, 2020
Stored red blood cells (RBCs) are needed for life-saving blood transfusions, but they undergo continuous degradation. RBC storage lesions are often assessed by microscopic examination or biochemical and biophysical assays, which are complex, time-con...
Numerical simulation of deformed red blood cell by utilizing neural network approach and finite element analysis.
Computer methods in biomechanics and biomedical engineering
Aug 10, 2020
In order to have research on the deformation characteristics and mechanical properties of human red blood cells (RBCs), finite element models of RBC optical tweezers stretching and atomic force microscope (AFM) indentation were established. Non-linea...
A Comparative Study of the Diagnostic Potential of Plasma and Erythrocytic α-Synuclein in Parkinson's Disease.
Neuro-degenerative diseases
Jun 2, 2020
BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disease characterized by intracellular α-synuclein (α-Syn) deposition. Alternation of the α-Syn expression level in plasma or erythrocytes may be used as a potential PD biomarker. However, n...
Intelligent image-based deformation-assisted cell sorting with molecular specificity.
Nature methods
May 25, 2020
Although label-free cell sorting is desirable for providing pristine cells for further analysis or use, current approaches lack molecular specificity and speed. Here, we combine real-time fluorescence and deformability cytometry with sorting based on...
An Effective Convolutional Neural Network for Classifying Red Blood Cells in Malaria Diseases.
Interdisciplinary sciences, computational life sciences
May 11, 2020
Malaria is one of the epidemics that can cause human death. Accurate and rapid diagnosis of malaria is important for treatment. Due to the limited number of data and human factors, the prediction performance and reliability of traditional classificat...
A neural network approach for real-time particle/cell characterization in microfluidic impedance cytometry.
Analytical and bioanalytical chemistry
Mar 18, 2020
Microfluidic applications such as active particle sorting or selective enrichment require particle classification techniques that are capable of working in real time. In this paper, we explore the use of neural networks for fast label-free particle c...
Sequential classification system for recognition of malaria infection using peripheral blood cell images.
Journal of clinical pathology
Mar 16, 2020
AIMS: Morphological recognition of red blood cells infected with malaria parasites is an important task in the laboratory practice. Nowadays, there is a lack of specific automated systems able to differentiate malaria with respect to other red blood ...
Applications of machine learning for simulations of red blood cells in microfluidic devices.
BMC bioinformatics
Mar 11, 2020
BACKGROUND: For optimization of microfluidic devices for the analysis of blood samples, it is useful to simulate blood cells as elastic objects in flow of blood plasma. In such numerical models, we primarily need to take into consideration the moveme...
Regular cold water swimming during winter time affects resting hematological parameters and serum erythropoietin.
Journal of physiology and pharmacology : an official journal of the Polish Physiological Society
Jan 30, 2020
Recreational winter swimming in cold sea water evokes body responses to regularly repeated cold water immersion. However, the understanding of adaptive changes is still limited and data regarding very short-term exposure to severe cold stress are sca...
Clot Analog Attenuation in Non-contrast CT Predicts Histology: an Experimental Study Using Machine Learning.
Translational stroke research
Jan 14, 2020
Exact histological clot composition remains unknown. The purpose of this study was to identify the best imaging variables to be extrapolated on clot composition and clarify variability in the imaging of thrombi by non-contrast CT. Using a CT-phantom ...
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