We demonstrate a novel approach to the controlled loading of inorganic nanoparticles and proteins into submicron- and micron-sized porous particles. The approach is based on freezing/thawing cycles, which lead to high loading densities. The process was tested for the inclusion of Au, magnetite nanoparticles, and bovine serum albumin in biocompatible vaterite carriers of micron and submicron sizes. The amounts of loaded nanoparticles or substances were adjusted by the number of freezing/thawing cycles. Our method afforded at least a three times higher loading of magnetite nanoparticles and a four times higher loading of protein for micron vaterite particles, in comparison with conventional methods such as adsorption and coprecipitation. The capsules loaded with magnetite nanoparticles by the freezing-induced loading method moved faster in a magnetic field gradient than did the capsules loaded by adsorption or coprecipitation. Our approach allows the preparation of multicomponent nanocomposite materials with designed properties such as remote control (e.g. via the application of an electromagnetic or acoustic field) and cargo unloading. Such materials could be used as multimodal contrast agents, drug delivery systems, and sensors.

In modern biomedical science and developmental biology, there is significant interest in optical tagging to study individual cell behavior and migration in large cellular populations. However, there is currently no tagging system that can be used for labeling individual cells on demand in situ with subsequent discrimination in between and long-term tracking of individual cells. In this article, we demonstrate such a system based on photoconversion of the fluorescent dye rhodamine B co-confined with carbon nanodots in the volume of micron-sized polyelectrolyte capsules. We show that this new fluorescent convertible capsule coding system is robust and is actively uptaken by cell lines while demonstrating low toxicity. Using a variety of cellular lines, we demonstrate how this tagging system can be used for code-like marking and long-term tracking of multiple individual cells in large cellular populations.