Background: Transplantation of human-induced pluripotent stem cell (hiPSC)-derived islet organoids is a promising cell replacement therapy for type 1 diabetes (T1D). It is important to improve the efficacy of islet organoids transplantation by identifying new transplantation sites with high vascularization and sufficient accommodation to support graft survival with a high capacity for oxygen delivery.
Methods: A human-induced pluripotent stem cell line (hiPSCs-L1) was generated constitutively expressing luciferase.
Caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease 2019 (COVID-19) has shown extensive lung manifestations in vulnerable individuals, putting lung imaging and monitoring at the forefront of early detection and treatment. Magnetic particle imaging (MPI) is an imaging modality, which can bring excellent contrast, sensitivity, and signal-to-noise ratios to lung imaging for the development of new theranostic approaches for respiratory diseases. Advances in MPI tracers would offer additional improvements and increase the potential for clinical translation of MPI.
View Article and Find Full Text PDFDiabetes is a chronic condition which affects the glucose metabolism in the body. In lieu of any clinical "cure," the condition is managed through the administration of pharmacological aids, insulin supplements, diet restrictions, exercise, and the like. The conventional clinical prescriptions are limited by their life-long dependency and diminished potency, which in turn hinder the patient's recovery.
View Article and Find Full Text PDFThe properties of cancer stem cells (CSCs) have recently gained attention as an avenue of intervention for cancer therapy. In this review, we highlight some of the key roles of CSCs in altering the cellular microenvironment in favor of cancer progression. We also report on various studies in this field which focus on transformative properties of CSCs and their influence on surrounding cells or targets through the release of cellular cargo in the form of extracellular vesicles.
View Article and Find Full Text PDFPurpose: Current approaches to quantification of magnetic particle imaging (MPI) for cell-based therapy are thwarted by the lack of reliable, standardized methods of segmenting the signal from background in images. This calls for the development of artificial intelligence (AI) systems for MPI analysis.
Procedures: We utilize a canonical algorithm in the domain of unsupervised machine learning, known as K-means++, to segment the regions of interest (ROI) of images and perform iron quantification analysis using a standard curve model.