Tumors have complex properties that depend on interactions between epithelial cancer cells and the surrounding stromal compartment within the tumor microenvironment. In particular, immune infiltration plays a role in controlling tumor development and is now considered one of the hallmarks of cancer. The last few years has seen an explosion in immunotherapy as a targeted strategy to fight cancer without damaging healthy cells. In this way, long-lasting results are elicited by activation of an antitumor immune response, utilizing the body’s own surveillance mechanisms to reprogram the tumour microenvironment. The next challenge is to ensure targeted delivery of these therapies for increased efficacy and reduction in immune-related adverse events. Liposomes are an attractive drug delivery system providing versatility in their formulation including material type, charge, size and importantly surface chemical modifications that confer their tumour specificity. These tunable properties make them an attractive platform for the treatment of cancer. In this chapter, we will discuss clinically approved immunotherapies and those undergoing clinical trials together with, recent liposomal approaches for enhanced specificity and efficacy.
The versatility of nanomedicines allows for various modifications of material type, size, charge and functionalization, offering a promising platform for biomedical applications including tumor targeting. One such material, silk fibroin (SF) has emerged, displaying an excellent combination of mechanical and biological properties characterized by its high tensile and breaking strength, elongation, stiffness and ductility. High stability allows SF to maintain its chemical structure even at high temperatures (around 250°C) and compared with other biological polymers like polylactide (PLA), poly(lactic-co-glycolic acid) (PLGA), and collagen, SF shows excellent biocompatibility and lower immunogenic response making it a very suitable material for drug delivery and tissue engineering. Here we describe the structure, synthesis and properties of SF nanoparticles. We evaluate its emergence as a multi-functional polymer for its utility as a nanocarrier to deliver cancer therapies directly to tumors together with considerations for its clinical use.
To improve localization and pose precision of visual–inertial simultaneous localization and mapping (viSLAM) in complex scenarios, it is necessary to tune the weights of the visual and inertial inputs during sensor fusion. To this end, we propose a resilient viSLAM algorithm based on covariance tuning. During back-end optimization of the viSLAM process, the unit-weight root-mean-square error (RMSE) of the visual reprojection and IMU preintegration in each optimization is computed to construct a covariance tuning function, producing a new covariance matrix. This is used to perform another round of nonlinear optimization, effectively improving pose and localization precision without closed-loop detection. In the validation experiment, our algorithm outperformed the OKVIS, R-VIO, and VINS-Mono open-source viSLAM frameworks in pose and localization precision on the EuRoc dataset, at all difficulty levels.
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