Genetically engineered membrane-based nanoengagers for immunotherapy of pancreatic cancer.

Modulating macrophages presents a promising avenue in tumor immunotherapy. However, tumor cells have evolved mechanisms to evade macrophage activation and phagocytosis. Herein, we introduced a bispecific antibody-based nanoengager to facilitate the recognition and phagocytosis of tumor cells by macrophages. Specifically, we genetically engineered two single chain variable fragments (scFv) onto cell membrane: anti-CD40 scFv for engaging with macrophages and anti-Claudin18.2 (CLDN18.2) scFv for interacting with tumor cells. These nanoengagers were further constructed by coating scFv-anchored membrane into PLGA nanoparticle core. Our developed nanoengagers significantly boosted immune responses, including increased recognition and phagocytosis of tumor cells by macrophages, enhanced activation and antigen presentation, and elevated cytotoxic T lymphocyte activity. These combined benefits resulted in enhancing antitumor efficacy against highly aggressive "cold" pancreatic cancer. Overall, this study offers a versatile nanoengager design for immunotherapy, achieved through genetically engineering to incorporate antibody-anchored membrane.

Prediction and Design of Nanozymes using Explainable Machine Learning.

An abundant number of nanomaterials have been discovered to possess enzyme-like catalytic activity, termed nanozymes. It is identified that a variety of internal and external factors influence the catalytic activity of nanozymes. However, there is a lack of essential methodologies to uncover the hidden mechanisms between nanozyme features and enzyme-like activity. Here, a data-driven approach is demonstrated that utilizes machine-learning algorithms to understand particle-property relationships, allowing for classification and quantitative predictions of enzyme-like activity exhibited by nanozymes. High consistency between predicted outputs and the observations is confirmed by accuracy (90.6%) and R2 (up to 0.80). Furthermore, sensitive analysis of the models reveals the central roles of transition metals in determining nanozyme activity. As an example, the models are successfully applied to predict or design desirable nanozymes by uncovering the hidden relationship between different periods of transition metals and their enzyme-like performance. This study offers a promising strategy to develop nanozymes with desirable catalytic activity and demonstrates the potential of machine learning within the field of material science.

Biomimetic Design of Artificial Hybrid Nanocells for Boosted Vascular Regeneration in Ischemic Tissues.

Restoration of sufficient blood supply for the treatment of ischemia remains a significant scientific and clinical challenge. Here, a cell-like nanoparticle delivery technology is introduced that is capable of recapitulating multiple cell functions for the spatiotemporal triggering of vascular regeneration. Specifically, a copper-containing protein is successfully prepared using a recombinant protein scaffold based on a de novo design strategy, which facilitates the timely release of nitric oxide and improved accumulation of particles within ischemic tissues. Through closely mimicking physiological cues, the authors demonstrate the benefits of bioactive factors secreted from hypoxic stem cells on promoting angiogenesis. Following this cell-mimicking manner, artificial hybrid nanosized cells (Hynocell) are constructed by integrating the hypoxic stem cell secretome into nanoparticles with surface coatings of cell membranes fused with copper-containing protein. The Hynocell, hybridized with different cell-derived components, provides synergistic effects on targeting ischemic tissues and promoting vascular regeneration in acute hindlimb ischemia and acute myocardial infarction models. This study offers new insights into the utilization of nanotechnology to potentiate the development of cell-free therapeutics.