Human red blood cells (RBCs) are approximately 8 μm in diameter, but must repeatedly deform through capillaries as small as 2 μm in order to deliver oxygen to all parts of the body. The loss of this capability is associated with the pathology of many diseases, and is therefore a potential biomarker for disease status and treatment efficacy. Measuring RBC deformability is a difficult problem because of the minute forces (∼pN) that must be exerted on these cells, as well as the requirements for throughput and multiplexing. The development of technologies for measuring RBC deformability date back to the 1960s with the development of micropipette aspiration, ektacytometry, and the cell transit analyzer. In the past 10 years, significant progress has been made using microfluidics by leveraging the ability to precisely control fluid flow through microstructures at the size scale of individual RBCs. These technologies have now surpassed traditional methods in terms of sensitivity, throughput, consistency, and ease of use. As a result, these efforts are beginning to move beyond feasibility studies and into applications to enable biomedical discoveries. In this review, we provide an overview of both traditional and microfluidic techniques for measuring RBC deformability. We discuss the capabilities of each technique and compare their sensitivity, throughput, and robustness in measuring bulk and single-cell RBC deformability. Finally, we discuss how these tools could be used to measure changes in RBC deformability in the context of various applications including pathologies caused by malaria and hemoglobinopathies, as well as degradation during storage in blood bags prior to blood transfusions.

Technologies for measuring red blood cell deformability.

The work investigates neural network model for prediction of post-surgical treatment risks. The descriptors of the risk classifiers are formed on the basis of the analysis of the current-voltage characteristics of one, two and three biologically active points. The training and verification samples were formed by examining 120 patients with a diagnosis of benign prostatic hyperplasia. Of these, 62 patients were successfully operated on (class C1), 30 had various complications after surgery (class C2), 28 patients required additional treatment (class C3). The constructed classifiers showed a high quality of predicting critical conditions during surgical treatment.

Application of fuzzy neural network model and current-voltage analysis of biologically active points for prediction post-surgery risks.

Application of Machine Learning and Deep Learning in Finite Element Analysis: A Comprehensive Review

Background: “Artificial intelligence” and “big data” increasingly take the step from just being interesting concepts to being relevant or even part of our lives. This general statement holds also true for transfusion medicine. Besides all advancements in transfusion medicine, there is not yet an established red blood cell quality measure, which is generally applied. Summary: We highlight the usefulness of big data in transfusion medicine. Furthermore, we emphasize in the example of quality control of red blood cell units the application of artificial intelligence. Key Messages: A variety of concepts making use of big data and artificial intelligence are readily available but still await to be implemented into any clinical routine. For the quality control of red blood cell units, clinical validation is still required.

Big Data in Transfusion Medicine and Artificial Intelligence Analysis for Red Blood Cell Quality Control

Optical tweezers (OTs) can transfer light momentum to particles, achieving the precise manipulation of particles through optical forces. Due to the properties of non-contact and precise control, OTs have provided a gateway for exploring the mysteries behind nonlinear optics, soft-condensed-matter physics, molecular biology, and analytical chemistry. In recent years, OTs have been combined with microfluidic chips to overcome their limitations in, for instance, speed and efficiency, creating a technology known as “optofluidic tweezers.” This paper describes static OTs briefly first. Next, we overview recent developments in optofluidic tweezers, summarizing advancements in capture, manipulation, sorting, and measurement based on different technologies. The focus is on various kinds of optofluidic tweezers, such as holographic optical tweezers, photonic-crystal optical tweezers, and waveguide optical tweezers. Moreover, there is a continuing trend of combining optofluidic tweezers with other techniques to achieve greater functionality, such as antigen–antibody interactions and Raman tweezers. We conclude by summarizing the main challenges and future directions in this research field.

/pdf/optofluidic-tweezers-efficient-and-versatile-micro-nano-1zh8437m.pdf

Optofluidic Tweezers: Efficient and Versatile Micro/Nano-Manipulation Tools

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 mic...

Numerical simulation of deformed red blood cell by utilizing neural network approach and finite element analysis.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Yu Ma

Author Tools

Chat about Author

Papers

Numerical simulation of deformed red blood cell by utilizing neural network approach and finite element analysis.