Deep ensemble learning enables highly accurate classification of stored red blood cell morphology.

Changes in red blood cell (RBC) morphology distribution have emerged as a quantitative biomarker for the degradation of RBC functional properties during hypothermic storage. Previously published automated methods for classifying the morphology of stored RBCs often had insufficient accuracy and relied on proprietary code and datasets, making them difficult to use in many research and clinical applications. Here we describe the development and validation of a highly accurate open-source RBC morphology classification pipeline based on ensemble deep learning (DL).

Optical Imaging of Magnetic Particle Cluster Oscillation and Rotation in Glycerol.

Magnetic particles have been evaluated for their biomedical applications as a drug delivery system to treat asthma and other lung diseases. In this study, ferromagnetic barium hexaferrite (BaFe12O19) and iron oxide (Fe3O4) particles were suspended in water or glycerol, as glycerol can be 1000 times more viscous than water. The particle concentration was 2.

Magnetic Nanodrug Delivery Through the Mucus Layer of Air-Liquid Interface Cultured Primary Normal Human Tracheobronchial Epithelial Cells.

Superparamagnetic iron oxide (FeO) and highly anisotropic barium hexaferrite (BaFeO) nanoparticles were coated with an anti-inflammatory drug and magnetically transported through mucus produced by primary human airway epithelial cells. Using wet planetary ball milling, dl-2-amino-3-phosphonopropionic acid-coated BaFeO nano-particles (BaNPs) of 1-100 nm in diameter were prepared in water. BaNPs and conventional 20-30-nm FeO nanoparticles (FeNPs) were then encased in a polymer (PLGA) loaded with dexamethasone (Dex) and tagged for imaging.