Nebulized Inhalation of Peptide-Modified DNA Origami To Alleviate Acute Lung Injury.

Acute lung injury (ALI) is a severe inflammatory lung disease, with high mortality rates. Early intervention by reactive oxygen species (ROS) scavengers could reduce ROS accumulation, break the inflammation expansion chain in alveolar macrophages (AMs), and avoid irreversible damage to alveolar epithelial and endothelial cells. Here, we reported cell-penetrating R9 peptide-modified triangular DNA origami nanostructures (tDONs-R9) as a novel nebulizable drug that could reach the deep alveolar regions and exhibit an enhanced uptake preference of macrophages. tDONs-R9 suppressed the expression of pro-inflammatory cytokines and drove polarization toward the anti-inflammatory M2 phenotype in macrophages. In the LPS-induced ALI mouse model, treatment with nebulized tDONs-R9 alleviated the overwhelming ROS, pro-inflammatory cytokines, and neutrophil infiltration in the lungs. Our study demonstrates that tDONs-R9 has the potential for ALI treatment, and the programmable DNA origami nanostructures provide a new drug delivery platform for pulmonary disease treatment with high delivery efficiency and biosecurity.

Visible Meta-Displays for Anti-Counterfeiting with Printable Dielectric Metasurfaces.

Metasurfaces, 2D arrays of nanostructures, have gained significant attention in recent years due to their ability to manipulate light at the subwavelength scale. Their diverse applications range from advanced optical devices to sensing and imaging technologies. However, the mass production of dielectric metasurfaces with tailored properties for visible light has remained a challenge. Therefore, the demand for efficient and cost-effective fabrication methods for metasurfaces has driven the continuing development of various techniques. In this research article, a high-throughput production method is presented for multifunctional dielectric metasurfaces in the visible light range using one-step high-index TiO2-polymer composite (TPC) printing, which is a variant of nanoprinting lithography (NIL) for the direct replication of patterned multifunctional dielectric metasurfaces using a TPC material as the printing ink. The batch fabrication of dielectric metasurfaces is demonstrated with controlled geometry and excellent optical response, enabling high-performance light-matter interactions for potential applications of visible meta-displays.

Simple route for high-throughput fabrication of metasurfaces using one-step UV-curable resin printing.

Phase-gradient metasurfaces are two-dimensional (2D) optical elements that can manipulate light by imposing local, space-variant phase changes on an incident electromagnetic wave. These metasurfaces hold the potential and the promise to revolutionize photonics by providing ultrathin alternatives for a wide range of common optical elements such as bulky refractive optics, waveplates, polarizers, and axicons. However, the fabrication of state-of-the-art metasurfaces typically requires some time-consuming, expensive, and possibly hazardous processing steps. To overcome these limitations on conventional metasurface fabrication, a facile methodology to produce phase-gradient metasurfaces through one-step UV-curable resin printing is developed by our research group. The method dramatically reduces the required processing time and cost, as well as eliminates safety hazards. As a proof-of-concept, the advantages of the method are clearly demonstrated via a rapid reproduction of high-performance metalenses based on the Pancharatnam-Berry phase gradient concept in the visible spectrum.

Scientometric and multidimensional contents analysis of PM2.5 concentration prediction.

The foundation for the environmental department to take suitable measures and make a significant contribution towards improving air quality is the precise and dependable prediction of PM2.5 concentration. It is essential to review the development process and hotspots of PM2.5 concentration prediction studies over the past 20 years (2000-2021) comprehensively and quantitatively. This study used detailed bibliometric methods and CiteSpace software to visually analyze the PM2.5 pollution level. The outcomes found that the prediction research phases of PM2.5 can be broadly divided into three phases and enter the rapid growth phase after 2017. Five categories of keywords are clustered, and the forecasting data and forecasting methods are typical cluster representatives. Then, the construction and processing of PM2.5 concentration prediction datasets, the prediction methods and technical processes, and the determination of the prediction spatial-temporal scales are the main content of the analysis. In the future, it is necessary to concentrate on multi-source data fusion for PM2.5 concentration prediction at multiple spatial-temporal scales and focus on technology integration and innovative applications in forecasting models, especially the optimal use of deep machine learning methods to improve prediction accuracy and practical application conversion.