A biological nanofoam: The wall of coniferous bisaccate pollen

The development of multifunctional materials for water pollution remediation using pollen and sporopollenin

Pollen is a promising material for water treatment owing to its renewable nature, abundant sources, and vast reserves. The natural polymer sporopollenin, found within pollen exine, possesses a distinctive layered porous structure, mechanical strength, and stable chemical properties, which can be utilized to prepare sporopollenin exine capsules (SECs). Leveraging these attributes, pollen or SECs can be used to develop water pollution remediation materials. In this review, the structure of pollen is first introduced, followed by the categorization of various methods for extracting SECs. Then, the functional expansion of pollen adsorbents, with an emphasis on their recyclability, reusability, and visual sensing capabilities, as opposed to mere functional group modification, is discussed. Furthermore, the progress made in utilizing pollen as a biological template for synthesizing catalysts is summarized. Intriguingly, pollen can also be engineered into self-propelled micromotors, enhancing its potential application in adsorption and catalysis. Finally, the challenges associated with the application of pollen in water pollution treatment are discussed. These challenges include the selection of environmentally friendly, non-toxic reagents in synthesizing pollen water remediation products and the large-scale application after synthesis. Moreover, the multifunctional synthesis and application of different water remediation products are prospected.

How scanning probe microscopy can be supported by artificial intelligence and quantum computing?

The impact of Artificial Intelligence (AI) is rapidly expanding, revolutionizing both science and society. It is applied to practically all areas of life, science, and technology, including materials science, which continuously requires novel tools for effective materials characterization. One of the widely used techniques is scanning probe microscopy (SPM). SPM has fundamentally changed materials engineering, biology, and chemistry by providing tools for atomic-precision surface mapping. Despite its many advantages, it also has some drawbacks, such as long scanning times or the possibility of damaging soft-surface materials. In this paper, we focus on the potential for supporting SPM-based measurements, with an emphasis on the application of AI-based algorithms, especially Machine Learning-based algorithms, as well as quantum computing (QC). It has been found that AI can be helpful in automating experimental processes in routine operations, algorithmically searching for optimal sample regions, and elucidating structure-property relationships. Thus, it contributes to increasing the efficiency and accuracy of optical nanoscopy scanning probes. Moreover, the combination of AI-based algorithms and QC may have enormous potential to enhance the practical application of SPM. The limitations of the AI-QC-based approach were also discussed. Finally, we outline a research path for improving AI-QC-powered SPM. RESEARCH HIGHLIGHTS: Artificial intelligence and quantum computing as support for scanning probe microscopy. The analysis indicates a research gap in the field of scanning probe microscopy. The research aims to shed light into ai-qc-powered scanning probe microscopy.

Dose-efficient scanning Compton X-ray microscopy

The highest resolution of images of soft matter and biological materials is ultimately limited by modification of the structure, induced by the necessarily high energy of short-wavelength radiation. Imaging the inelastically scattered X-rays at a photon energy of 60 keV (0.02 nm wavelength) offers greater signal per energy transferred to the sample than coherent-scattering techniques such as phase-contrast microscopy and projection holography. We present images of dried, unstained, and unfixed biological objects obtained by scanning Compton X-ray microscopy, at a resolution of about 70 nm. This microscope was realised using novel wedged multilayer Laue lenses that were fabricated to sub-ångström precision, a new wavefront measurement scheme for hard X rays, and efficient pixel-array detectors. The doses required to form these images were as little as 0.02% of the tolerable dose and 0.05% of that needed for phase-contrast imaging at similar resolution using 17 keV photon energy. The images obtained provide a quantitative map of the projected mass density in the sample, as confirmed by imaging a silicon wedge. Based on these results, we find that it should be possible to obtain radiation damage-free images of biological samples at a resolution below 10 nm.

Pollen-Inspired Shell-Core Aerosol Particles Capable of Brownian Motion for Pulmonary Vascularization

Nebulization is the most widely used respiratory delivery technique with non-invasive properties. However, nebulized drugs often fail to function due to the excretion and immune clearance of the respiratory system. In this work, inspired by pollen in nature, novel shell-core aerosol particles (APs) capable of Brownian motion are constructed for respiratory delivery. Drugs-loaded poly(lactic-co-glycolic acid) nanoparticles are prepared by emulsification to form the inner core, and the membranes of macrophages are extracted to form the outer shell. The optimized size and the shell-core structure endow APs with Brownian motion and atomization stability, thus enabling the APs to reach the bronchi and alveoli deeply for effective deposition. Camouflaging the macrophage membranes equips the APs with immune evasion. In vitro experiments prove that deferoxamine (DFO)-loaded APs (DFO@APs) can promote the angiogenesis of human umbilical vein endothelial cells. A hyperoxia-induced bronchopulmonary dysplasia (BPD) model is constructed to validate the efficiency of DFO@APs. In BPD mice, DFO@APs can release DFO in the alveolar interstitium, thus promoting the reconstruction of microvasculature, ultimately inducing lung development for treating BPD. In conclusion, this study develops "pollen"-inspired shell-core aerosol particles capable of Brownian motion, which provides a novel idea and theoretical basis for respiratory administration.