CellVisioner: A Generalizable Cell Virtual Staining Toolbox based on Few-Shot Transfer Learning for Mechanobiological Analysis.

Visualizing cellular structures especially the cytoskeleton and the nucleus is crucial for understanding mechanobiology, but traditional fluorescence staining has inherent limitations such as phototoxicity and photobleaching. Virtual staining techniques provide an alternative approach to addressing these issues but often require substantial amount of user training data. In this study, we develop a generalizable cell virtual staining toolbox (termed CellVisioner) based on few-shot transfer learning that requires substantially reduced user training data.

AV-casNet: Fully Automatic Arteriole-Venule Segmentation and Differentiation in OCT Angiography.

Automatic segmentation and differentiation of retinal arteriole and venule (AV), defined as small blood vessels directly before and after the capillary plexus, are of great importance for the diagnosis of various eye diseases and systemic diseases, such as diabetic retinopathy, hypertension, and cardiovascular diseases. Optical coherence tomography angiography (OCTA) is a recent imaging modality that provides capillary-level blood flow information. However, OCTA does not have the colorimetric and geometric differences between AV as the fundus photography does.

Fabrication and Biomedical Applications of Heart-on-a-chip.

Heart diseases have become the main killer threatening human health, and various methods have been developed to study heart disease. Among them, heart-on-a-chip has emerged in recent years as a method for constructing disease (or normal) models and is considered as a promising tool to study heart diseases. Compared with other methods, the advantages of heart-on-a-chip include the high portability, high throughput, and the capability to mimic microenvironments .