The unprecedented navigation ability in micro/nanoscale and tailored functionality tunes micro/nanomotors as new target drug delivery systems, open up new horizons for biomedical applications. Herein, we designed a light-driven rGO/Cu2 + 1O tubular nanomotor for active targeting of cancer cells as a drug delivery system. The propulsion performance is greatly enhanced in real cell media (5% glucose cells isotonic solution), attributing to the introduction of oxygen vacancy and reduced graphene oxide (rGO) layer for separating photo-induced electron-hole pairs. The motion speed and direction can be readily modulated. Meanwhile, doxorubicin (DOX) can be loaded quickly on the rGO layer because of π-π bonding effect. The Cu2 + 1O matrix in the tiny robots not only serves as a photocatalyst to generate a chemical concentration gradient as the driving force but also acts as a nanomedicine to kill cancer cells as well. The strong propulsion of light-driven rGO/Cu2 + 1O nanomotors coupled with tiny size endow them with active transmembrane transport, assisting DOX and Cu2 + 1O breaking through the barrier of the cell membrane. Compared with non-powered nanocarrier and free DOX, light-propelled rGO/Cu2 + 1O nanomotors exhibit greater transmembrane transport efficiency and significant therapeutic efficacy. This proof-of-concept nanomotor design presents an innovative approach against tumor, enlarging the list of biomedical applications of light-driven micro/nanomotors to the superficial tissue treatment.

A comprehensive knowledge of the physical and chemical properties of nanomaterials (NMs) is necessary to design them effectively for regulated use. Although NMs are utilized in therapeutics, their cytotoxicity has attracted great attention. Nanoscale quantitative structure-property relationship (nano-QSPR) models can help in understanding the relationship between NMs and the biological environment and provide new ways for modeling the structural properties and bio-toxic effects of NMs. The goal of the study is to construct fully validated property-based models to extract relevant features for estimating and influencing the zeta potential and obtaining the toxicity profile regarding cell damage in the treatment of cancer cells. To achieve this, QSPR modeling was first performed with 18 metal oxide (MeOx) NMs to measure their materials properties using periodic table-based descriptors. The features obtained were later applied for zeta potential calculation (imputation for sparse data) for MeOx NMs that lack such information. To further clarify the influence of the zeta potential on cell damage, a QSPR model was developed with 132 MeOx NMs to understand the possible mechanisms of cell damage. The results showed that zeta potential, along with seven other descriptors, had the potential to influence oxidative damage through free radical accumulation, which could lead to changes in the survival rate of cancerous cells. The developed QSPR and quantitative structure-activity relationship models also give hints regarding safer design and toxicity assessment of MeOx NMs.

One of the most challenging frontiers in biological systems understanding is fluorescent label-free imaging. We present here the NeuriTES platform that revisits the standard paradigms of video analysis to detect unlabeled objects and adapt to the dynamic evolution of the phenomenon under observation. Object segmentation is reformulated using robust algorithms to assure regular cell detection and transfer entropy measures are used to study the inter-relationship among the parameters related to the evolving system. We applied the NeuriTES platform to the automatic analysis of neurites degeneration in presence of amyotrophic lateral sclerosis (ALS) and to the study of the effects of a chemotherapy drug on living prostate cancer cells (PC3) cultures. Control cells have been considered in both the two cases study. Accuracy values of 93% and of 92% are achieved, respectively. NeuriTES not only represents a tool for investigation in fluorescent label-free images but demonstrates to be adaptable to individual needs.