Single Molecular Nanomedicines Based on Macrocyclic Carrier-Drug Conjugates for Concentration-Independent Encapsulation and Precise Activation of Drugs.

Nanomedicines often rely on noncovalent self-assembly and encapsulation for drug loading and delivery. However, challenges such as reproducibility issues due to the multicomponent nature, off-target activation caused by premature drug release, and complex pharmacokinetics arising from assembly dissociation have hindered their clinical translation. In this study, we introduce an innovative design concept termed single molecular nanomedicine (SMNM) based on macrocyclic carrier-drug conjugates. Through the covalent linkage of two chemotherapy drugs to a hypoxia-cleavable macrocyclic carrier, azocalix[4]arene, we obtained two self-included complexes to serve as SMNMs. The intramolecular inclusion feature of the SMNMs has not only demonstrated comprehensive shielding and protection for the drugs but also effectively prevented off-target drug leakage, thereby significantly reducing their side effects and enhancing their antitumor therapeutic efficacy. Additionally, the attributes of being a single component and molecularly dispersed confer advantages such as ease of preparation and good reproducibility for SMNMs, which is desirable for clinical applications.

Expanding the Hydrophobic Cavity Surface of Azocalix[4]arene to Enable Biotin/Avidin Affinity with Controlled Release.

The development of artificial receptors that combine ultrahigh-affinity binding and controllable release for active guests holds significant importance in biomedical applications. On one hand, a complex with an exceedingly high binding affinity can resist unwanted dissociation induced by dilution effect and complex interferents within physiological environments. On the other hand, stimulus-responsive release of the guest is essential for precisely activating its function. In this context, we expanded hydrophobic cavity surface of a hypoxia-responsive azocalix[4]arene, affording Naph-SAC4A. This modification significantly enhanced its aqueous binding affinity to 1013 M-1, akin to the naturally occurring strongest recognition pair, biotin/(strept-)avidin. Consequently, Naph-SAC4A emerges as the first artificial receptor to simultaneously integrate ultrahigh recognition affinity and actively controllable release. The markedly enhanced affinity not only improved Naph-SAC4A's sensitivity in detecting rocuronium bromide in serum, but also refined the precision of hypoxia-responsive doxorubicin delivery at the cellular level, demonstrating its immense potential for diverse practical applications.

Supramolecular interaction in the action of drug delivery systems.

Complex diseases and diverse clinical needs necessitate drug delivery systems (DDSs), yet the current performance of DDSs is far from ideal. Supramolecular interactions play a pivotal role in various aspects of drug delivery, encompassing biocompatibility, drug loading, stability, crossing biological barriers, targeting, and controlled release. Nevertheless, despite having some understanding of the role of supramolecular interactions in drug delivery, their incorporation is frequently overlooked in the design and development of DDSs. This perspective provides a brief analysis of the involved supramolecular interactions in the action of drug delivery, with a primary emphasis on the DDSs employed in the clinic, mainly liposomes and polymers, and recognized phenomena in research, such as the protein corona. The supramolecular interactions implicated in various aspects of drug delivery systems, including biocompatibility, drug loading, stability, spatiotemporal distribution, and controlled release, were individually analyzed and discussed. This perspective aims to trigger a comprehensive and systematic consideration of supramolecular interactions in the further development of DDSs. Supramolecular interactions embody the true essence of the interplay between the majority of DDSs and biological systems.

Active targeting tumor therapy using host-guest drug delivery system based on biotin functionalized azocalix[4]arene.

Host-guest drug delivery systems (HGDDSs) provided a facile method for incorporating biomedical functions, including efficient drug-loading, passive targeting, and controlled drug release. However, developing HGDDSs with active targeting is hindered by the difficult functionalization of popular macrocycles. Herein, we report an active targeting HGDDS based on biotin-modified sulfonated azocalix[4]arene (Biotin-SAC4A) to efficiently deliver drug into cancer cells for improving anti-tumor effect. Biotin-SAC4A was synthesized by amide condensation and azo coupling. Biotin-SAC4A demonstrated hypoxia responsive targeting and active targeting through azo and biotin groups, respectively. DOX@Biotin-SAC4A, which was prepared by loading doxorubicin (DOX) in Biotin-SAC4A, was evaluated for tumor targeting and therapy in vitro and in vivo. DOX@Biotin-SAC4A formulation effectively killed cancer cells in vitro and more efficiently delivered DOX to the lesion than the similar formulation without active targeting. Therefore, DOX@Biotin-SAC4A significantly improved the in vivo anti-tumor effect of free DOX. The facilely prepared Biotin-SAC4A offers strong DOX complexation, active targeting, and hypoxia-triggered release, providing a favorable host for effective breast cancer chemotherapy in HGDDSs. Moreover, Biotin-SAC4A also has potential to deliver agents for other therapeutic modalities and diseases.

Multiscale Unsupervised Segmentation of SAR Imagery Using the Genetic Algorithm.

A valid unsupervised and multiscale segmentation of synthetic aperture radar(SAR) imagery is proposed by a combination GA-EM of the Expectation Maximization(EM) algorith with the genetic algorithm (GA). The mixture multiscale autoregressive(MMAR) model is introduced to characterize and exploit the scale-to-scale statisticalvariations and statistical variations in the same scale in SAR imagery due to radar speckle,and a segmentation method is given by combining the GA algorithm with the EMalgorithm. This algorithm is capable of selecting the number of components of the modelusing the minimum description length (MDL) criterion. Our approach benefits from theproperties of the Genetic and the EM algorithm by combination of both into a singleprocedure. The population-based stochastic search of the genetic algorithm (GA) exploresthe search space more thoroughly than the EM method. Therefore, our algorithm enablesescaping from local optimal solutions since the algorithm becomes less sensitive to itsinitialization. Some experiment results are given based on our proposed approach, andcompared to that of the EM algorithms. The experiments on the SAR images show that theGA-EM outperforms the EM method.