scholarly journals Single Cell Analysis of Stored Red Blood Cells Using Ultra-High Throughput Holographic Cytometry

Cells ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 2455
Author(s):  
Han-Sang Park ◽  
Hillel Price ◽  
Silvia Ceballos ◽  
Jen-Tsan Chi ◽  
Adam Wax
Keyword(s):  
Red Blood Cells ◽  
High Throughput ◽  
Blood Cells ◽  
Storage Time ◽  
Single Cells ◽  
Machine Learning Algorithms ◽  
Training Data ◽  
Microfluidic Channels ◽  
Phase Imaging ◽  
Time Points

Holographic cytometry is introduced as an ultra-high throughput implementation of quantitative phase imaging of single cells flowing through parallel microfluidic channels. Here, the approach was applied for characterizing the morphology of individual red blood cells during storage under regular blood bank conditions. Samples from five blood donors were examined, over 100,000 cells examined for each, at three time points. The approach allows high-throughput phase imaging of a large number of cells, greatly extending our ability to study cellular phenotypes using individual cell images. Holographic cytology images can provide measurements of multiple physical traits of the cells, including optical volume and area, which are observed to consistently change over the storage time. In addition, the large volume of cell imaging data can serve as training data for machine-learning algorithms. For the study here, logistic regression was used to classify the cells according to the storage time points. The analysis showed that at least 5000 cells are needed to ensure accuracy of the classifiers. Overall, results showed the potential of holographic cytometry as a diagnostic tool.

scholarly journals Characterizing stored red blood cells using ultra-high throughput holographic cytometry

2021 ◽  
Author(s):  
Han Sang Park ◽  
Hillel Price ◽  
Silvia Ceballos ◽  
Jen-Tsan Chi ◽  
Adam Wax
Keyword(s):  
Red Blood Cells ◽  
High Throughput ◽  
Blood Cells ◽  
Storage Time ◽  
Morphological Changes ◽  
Machine Learning Algorithms ◽  
Training Data ◽  
Phase Image ◽  
Microfluidic Channels ◽  
Imaging Data

AbstractHolographic cytometry is introduced as an ultra-high throughput implementation of quantitative phase image based on off-axis interferometry of cells flowing through parallel microfluidic channels. Here, it is applied for characterizing morphological changes of red blood cells during storage under regular blood bank condition. The approach allows high quality phase imaging of a large number of cells greatly extending our ability to study cellular phenotypes using individual cell images. Holographic cytology measurements show multiple physical traits of the cells, including optical volume and area, which are observed to consistently change over the storage time. In addition, the large volume of cell imaging data can serve as training data for machine learning algorithms. For the study here, logistic regression is used to classify the cells according to the storage time points. The results of the classifiers demonstrate the potential of holographic cytometry as a diagnostic tool.

scholarly journals Learning-based screening of hematologic disorders using quantitative phase imaging of individual red blood cells

2018 ◽  
Author(s):  
Geon Kim ◽  
YoungJu Jo ◽  
Hyungjoo Cho ◽  
Hyun-seok Min ◽  
YongKeun Park
Keyword(s):  
Machine Learning ◽  
Red Blood Cells ◽  
Blood Cells ◽  
Single Cells ◽  
Deficiency Anemia ◽  
High Dimensional ◽  
Phase Imaging ◽  
Label Free ◽  
Quantitative Phase Imaging ◽  
Quantitative Phase

We present a rapid and label-free method for hematologic screening for diseases and syndromes, utilizing quantitative phase imaging (QPI) and machine learning. We aim to establish an efficient blood examination framework that does not suffer from the drawbacks of conventional blood assays, which are incapable of profiling single cells or using labeling procedures. Our method involves the synergistic employment of QPI and machine learning. The high-dimensional refractive index information arising from the QPI-based profiling of single red blood cells is processed to screen for diseases and syndromes using machine learning, which can utilize high-dimensional data beyond the human level. Accurate screening for iron-deficiency anemia, reticulocytosis, hereditary spherocytosis, and diabetes mellitus is demonstrated (>99% accuracy) using the proposed method. Furthermore, we highlight the synergy between QPI and machine learning in the proposed method by analyzing the performance of the method.

Sonoporation enables high-throughput loading of trehalose into red blood cells

Cryobiology ◽  
2020 ◽  
Author(s):  
Brett R. Janis ◽  
Mariah C. Priddy ◽  
Meghan R. Otto ◽  
Jonathan A. Kopechek ◽  
Michael A. Menze
Keyword(s):  
Red Blood Cells ◽  
High Throughput ◽  
Blood Cells

scholarly journals High-throughput assessment of mechanical properties of stem cell derived red blood cells, toward cellular downstream processing

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Ewa Guzniczak ◽  
Maryam Mohammad Zadeh ◽  
Fiona Dempsey ◽  
Melanie Jimenez ◽  
Henry Bock ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Stem Cell ◽  
Red Blood Cells ◽  
High Throughput ◽  
Blood Cells ◽  
Downstream Processing

scholarly journals Using Redox Potential as a Feasible Marker for Banked Blood Quality and the State of Oxidative Stress in Stored Red Blood Cells

2020 ◽  
Author(s):  
Rodney C Daniels ◽  
Hyesun Jun ◽  
Robertson D Davenport ◽  
Maryanne M Collinson ◽  
Kevin R Ward
Keyword(s):  
Oxidative Stress ◽  
Redox Potential ◽  
Red Blood Cells ◽  
Healthy Volunteers ◽  
Blood Cells ◽  
Storage Time ◽  
Cell Function ◽  
Venous Blood ◽  
Functional Changes ◽  
Over Time

Abstract Background Stored Red Blood Cells (RBCs) may undergo oxidative stress over time, with functional changes affecting critical tasks such as oxygen delivery. Central to these changes are oxidation-reduction (redox) reactions and the redox potential (RP) that must be maintained for proper cell function. RP imbalance can lead to oxidative stress that may contribute to storage lesions and transfusion-related morbidities. Direct measures of RP may allow for evaluation of erythrocyte quality and enable corrections of RP prior to transfusion. Methods Multiple random RBC segments were tested, ranging in age from 5 to 40 days at 5 day intervals. RP was recorded by measuring open circuit potential of RBCs using novel nanoporous gold electrodes with Ag/AgCl reference. RP measures were also performed on peripheral venous blood samples from 10 healthy volunteers. RP measures were compared between groups of aged RBCs, and with volunteer blood. Results Stored RBCs show time-dependent increases in RP. There were significant differences in Day 5 RP compared to all other groups (p≤0.005), Day 10-15 vs ages ≥ Day 20 (p≤0.025), Day 20-25 vs Day 40 (p=0.039), and all groups compared to healthy volunteers. RP became more positive over time suggesting ongoing oxidation as RBCs age. However, storage time alone does not predict the ultimate RP value measured from a given unit.Conclusions There are significant differences in RP between freshly stored RBCs and all others, with RP becoming more positive over time. However, storage time alone does not predict RP, indicating RP screening may be important independent of storage time and may serve as a marker of RBC quality and state of oxidative stress. RP measurements may also provide a target by which to restore RP balance in aged pRBCs, improving their clinical effectiveness while reducing associated morbidities.

scholarly journals High‐throughput adaptation for the quantitation of total folate in human red blood cells by LC‐MS/MS

2006 ◽  
Vol 20 (4) ◽  
Author(s):  
Janel Elizabeth Owens ◽  
Dirk M. Holstege ◽  
Andrew J. Clifford
Keyword(s):  
Red Blood Cells ◽  
High Throughput ◽  
Blood Cells ◽  
Human Red Blood Cells

NEW POSSIBILITIES OF STRUCTURAL MORPHOLOGICAL PECULIARITIES INVESTIGATION BY QUANTITATIVE PHASE IMAGING METHOD

2020 ◽  
pp. 133-135
Author(s):  
M. Zolotova ◽  
M. Ivashchenko ◽  
P. Ignatiev ◽  
V. Metelin ◽  
M. Talamanova
Keyword(s):  
Red Blood Cells ◽  
Blood Cells ◽  
Stress Conditions ◽  
Imaging Method ◽  
Phase Imaging ◽  
Quantitative Phase Imaging ◽  
Quantitative Phase ◽  
Stress Influence

The possibility of quantitative phase imaging method for the assessment of structural morphological erythrocytes peculiarities under normal and stress conditions were studied. It is stated that quantitative phase imaging is an important instrument which allows to visualize red blood cells. New aspects of stress influence on functional cells morphology are defined.

Erythroplateletapheresis: A New Strategy in the Global Apheresis Program

1998 ◽  
Vol 21 (6_suppl) ◽  
pp. 17-19
Author(s):  
G. Menichella ◽  
M. Ciarli ◽  
R. Serafini ◽  
L. Pierelli ◽  
M. Vittori ◽  
...  
Keyword(s):  
Blood Cell ◽  
Red Blood Cells ◽  
Plasma Volume ◽  
Blood Cells ◽  
Storage Time ◽  
Blood Donation ◽  
Mean Values ◽  
Packed Red Blood Cells ◽  
New Strategy ◽  
The Mean

Blood donation allowed by cell separators can offer higher performance and higher yield to guarantee better quality and pureness of collected products. New systems for the collection of platelet concentrate (PC) and packed red blood cells (PRBC) are currently available. The aim of our work was to test the possibility of preparing PC routinely from normal apheresis donors in a minimum amount of time while providing a second product. Over a 3-month period we performed 40 procedures using the Hemonetics MCS3P blood cell separator and the Dideco Excel. The mean values of platelet yield were 2.8 x 1011 (range 1.4-4.1) with the MCS3P and 3.49 x 1011 (range 2.9-3.9) with the Excel, in a plasma volume of 240 ml and 215 ml respectively; the PRBC units were added with SAG-Mannitol allowing a storage time of 42 days. Collection times were 71’ and 48’ respectively. Donor tolerance was analogous to phateletapheresis or plasmapheresis.

Sign in / Sign up

Export Citation Format

Share Document