No abstract

Preclinical screening with animal models is an important initial step in clinical translation of new drug delivery systems. However, establishing efficacy, biodistribution, and biotoxicity of complex, multicomponent systems in small animal models can be expensive and time-consuming. Zebrafish models represent an alternative for preclinical studies for nanoscale drug delivery systems. These models allow easy optical imaging, large sample size, and organ-specific studies, and hence an increasing number of preclinical studies are employing zebrafish models. In this review, we introduce various models and discuss recent studies of nanoscale drug delivery systems in zebrafish models. Also in the end, we proposed a guideline for the preclinical trials to accelerate the progress in this field.

Oligonucleotide-based aptamers, which have a three-dimensional structure with a single-stranded fragment, feature various characteristics with respect to size, toxicity, and permeability. Accordingly, aptamers are advantageous in terms of diagnosis and treatment and are materials that can be produced through relatively simple experiments. Systematic evolution of ligands by exponential enrichment (SELEX) is one of the most widely used experimental methods for generating aptamers; however, it is highly expensive and time-consuming. To reduce the related costs, recent studies have used in silico approaches, such as aptamer-protein interaction (API) classifiers that use sequence patterns to determine the binding affinity between RNA aptamers and proteins. Some of these methods generate candidate RNA aptamer sequences that bind to a target protein, but they are limited to producing candidates of a specific size. In this study, we present a machine learning approach for selecting candidate sequences of various sizes that have a high binding affinity for a specific sequence of a target protein. We applied the Monte Carlo tree search (MCTS) algorithm for generating the candidate sequences using a score function based on an API classifier. The tree structure that we designed with MCTS enables nucleotide sequence sampling, and the obtained sequences are potential aptamer candidates. We performed a quality assessment using the scores of docking simulations. Our validation datasets revealed that our model showed similar or better docking scores in ZDOCK docking simulations than the known aptamers. We expect that our method, which is size-independent and easy to use, can provide insights into searching for an appropriate aptamer sequence for a target protein during the simulation step of SELEX.

Herein, we report a charge-transfer complex electrolyte additive, 7,7,8,8-tetracyanoquinodimethane (TCNQ), with high Zn affinity, which was tightly adsorbed on the surface of a Zn anode to form a dense and robust interfacial complex layer and suppress the activity of H2O. As verified by comprehensive experimental and computational analyses, this complex layer could construct a Zn–Zn(TCNQ)2 Ohmic contact interface, guide rapid ion/electron transport, ameliorate electric field distribution, and inhibit the direct contact between the active H2O and Zn anode, demonstrating a dendrite-free Zn anode and facile Zn plating/stripping kinetics. Consequently, the Zn||Zn symmetrical cell exhibits a high Zn plating/stripping reversibility of over 1000 h at 20 mA cm–2 and 5 mA h cm–2 and a high depth of discharge (43%). Moreover, the Zn||MnO2 full cell delivers a high capacity of 143.3 mA h g–1 at 2000 mA g–1 even after 4000 cycles and a capacity retention of 94.7% after returning to 100 mA g–1.