Multiparameter phenotyping of platelets and characterization of the effects of agonists using machine learning.

ABSTRACT:

Background

Platelet function is driven by the expression of specialized surface markers. The concept of distinct circulating subpopulations of platelets has emerged in recent years, but their exact nature remains debatable.

Objectives

To design a spectral flow cytometry-based phenotyping workflow to provide a more comprehensive characterization, at a global and individual level, of surface markers in resting and activated healthy platelets, and to apply this workflow to investigate how responses differ according to platelet age.

Methods

A 14-marker flow cytometry panel was developed and applied to vehicle- or agonist-stimulated platelet-rich plasma and whole blood samples obtained from healthy volunteers, or to platelets sorted according to SYTO-13 (Thermo Fisher Scie

SUBMITTER: Vadgama A 

PROVIDER: S-EPMC11381873 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature