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Cerium dioxide nanoparticles (CeO 2 NPs) are among the most broadly used engineered nanoparticles that will be increasingly released into the environment. Thus, understanding their uptake, transportation, and transformation in plants, especially food crops, is critical because it represents a potential pathway for human consumption. One of the primary challenges for the endeavor is the inadequacy of current analytical methodologies to characterize and quantify the nanomaterial in complex biological samples at environmentally relevant concentrations. Herein, a method was developed using single particle-inductively coupled plasma-mass spectrometry (SP-ICP-MS) technology to simultaneously detect the size and size distribution of particulate Ce, particle concentration, and dissolved cerium in the shoots of four plant species including cucumber, tomato, soybean, and pumpkin. An enzymatic digestion method with Macerozyme R-10 enzyme previously used for gold nanoparticle extraction from the tomato plant was adapted successfully for CeO 2 NP extraction from all four plant species. This study is the first to report and demonstrate the presence of dissolved cerium in plant seedling shoots exposed to CeO 2 NPs hydroponically. The extent of plant uptake and accumulation appears to be dependent on the plant species, requiring further systematic investigation of the mechanisms.

ABCB1 detoxifies cells by exporting diverse xenobiotic compounds, thereby limiting drug disposition and contributing to multidrug resistance in cancer cells. Multiple small-molecule inhibitors and inhibitory antibodies have been developed for therapeutic applications, but the structural basis of their activity is insufficiently understood. We determined cryo-EM structures of nanodisc-reconstituted, human ABCB1 in complex with the Fab fragment of the inhibitory, monoclonal antibody MRK16 and bound to a substrate (the antitumor drug vincristine) or to the potent inhibitors elacridar, tariquidar, or zosuquidar. We found that inhibitors bound in pairs, with one molecule lodged in the central drug-binding pocket and a second extending into a phenylalanine-rich cavity that we termed the “access tunnel.” This finding explains how inhibitors can act as substrates at low concentration, but interfere with the early steps of the peristaltic extrusion mechanism at higher concentration. Our structural data will also help the development of more potent and selective ABCB1 inhibitors.

Nanomaterials have tremendous potential to increase electrochromic smart window efficiency, speed, and durability. However, nanoparticles vary in size, shape, and surface defects, and it is unknown how nanoparticle heterogeneity contributes to particle-dependent electrochromic properties. Here, we use single-nanoparticle-level electro-optical imaging to measure structure–function relationships in electrochromic tungsten oxide nanorods. Single nanorods exhibit a particle-dependent waiting time for tinting (from 100 ms to 10 s) due to Li-ion insertion at optically inactive surface sites. Longer nanorods tint darker than shorter nanorods and exhibit a Li-ion gradient that increases from the nanorod ends to the middle. The particle-dependent ion-insertion kinetics contribute to variable tinting rates and magnitudes across large-area smart windows. Next, we quantified how particle–particle interactions impact tinting dynamics and reversibility as the nanorod building blocks are assembled into a thin film. Interestingly, single particles tint 4 times faster and cycle 20 times more reversibly than thin films made of the same particles. These findings allow us to propose a nanostructured electrode architecture that optimizes optical modulation rates and reversibility across large-area smart windows.

The Sample Environment and Characterization (SEC) group of the European X‐ray Free‐Electron Laser (EuXFEL) develops sample delivery systems for the various scientific instruments, including systems for the injection of liquid samples that enable serial femtosecond X‐ray crystallography (SFX) and single‐particle imaging (SPI) experiments, among others. For rapid prototyping of various device types and materials, sub‐micrometre precision 3D printers are used to address the specific experimental conditions of SFX and SPI by providing a large number of devices with reliable performance. This work presents the current pool of 3D printed liquid sample delivery devices, based on the two‐photon polymerization (2PP) technique. These devices encompass gas dynamic virtual nozzles (GDVNs), mixing‐GDVNs, high‐viscosity extruders (HVEs) and electrospray conical capillary tips (CCTs) with highly reproducible geometric features that are suitable for time‐resolved SFX and SPI experiments at XFEL facilities. Liquid sample injection setups and infrastructure on the Single Particles, Clusters, and Biomolecules and Serial Femtosecond Crystallography (SPB/SFX) instrument are described, this being the instrument which is designated for biological structure determination at the EuXFEL. Presented here are 3D printed sample delivery devices for precise control over fluids and the generation of micrometre‐sized gas‐focused liquid jets, high‐viscosity streams and near‐monodisperse droplets suitable for X‐ray scattering experiments on X‐ray free‐electron laser (XFEL) instruments.

Tires, bitumen, and road markings are important sources of traffic-derived carbonaceous wear particles and microplastic (MP) pollution. In this study, we further developed a machine-learning algorithm coupled to an automated scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDX) analytical approach to classify and quantify the relative number of the following subclasses contained in environmental road dust: tire wear particles (TWP), bitumen wear particles (BiWP), road markings, reflecting glass beads, metallics, minerals, and biogenic/organics. The method is non-destructive, rapid, repeatable, and enables information about the size, shape, and elemental composition of particles 2–125 µm. The results showed that the method enabled differentiation between TWP and BiWP for particles > 20 µm with satisfying results. Furthermore, the relative number concentration of the subclasses was similar in both analyzed size fractions (2–20 µm and 20–125 µm), with minerals as the most dominant subclass (2–20 µm x̄ = 78%, 20–125 µm x̄ = 74%) followed by tire and bitumen wear particles, TBiWP, (2–20 µm x̄ = 19%, 20–125 µm x̄ = 22%). Road marking wear, glass beads, and metal wear contributed to x̄ = 1%, x̄ = 0.1%, and x̄ = 1% in the 2–20-µm fraction and to x̄ = 0.5%, x̄ = 0.2%, and x̄ = 0.4% in the 20–125-µm fraction. The present results show that road dust appreciably consists of TWP and BiWP within both the coarse and the fine size fraction. The study delivers quantitative evidence of the importance of tires, bitumen, road marking, and glass beads besides minerals and metals to wear particles and MP pollution in traffic environments based on environmental (real-world) samples

Background Identification and selection of protein particles in cryo-electron micrographs is an important step in single particle analysis. In this study, we developed a deep learning-based particle picking network to automatically detect particle centers from cryoEM micrographs. This is a challenging task due to the nature of cryoEM data, having low signal-to-noise ratios with variable particle sizes, shapes, distributions, grayscale variations as well as other undesirable artifacts. Results We propose a double convolutional neural network (CNN) cascade for automated detection of particles in cryo-electron micrographs. This approach, entitled Deep Regression Picker Network or “DRPnet”, is simple but very effective in recognizing different particle sizes, shapes, distributions and grayscale patterns corresponding to 2D views of 3D particles. Particles are detected by the first network, a fully convolutional regression network (FCRN), which maps the particle image to a continuous distance map that acts like a probability density function of particle centers. Particles identified by FCRN are further refined to reduce false particle detections by the second classification CNN. DRPnet’s first CNN pretrained with only a single cryoEM dataset can be used to detect particles from different datasets without retraining. Compared to RELION template-based autopicking, DRPnet results in better particle picking performance with drastically reduced user interactions and processing time. DRPnet also outperforms the state-of-the-art particle picking networks in terms of the supervised detection evaluation metrics recall, precision, and F-measure. To further highlight quality of the picked particle sets, we compute and present additional performance metrics assessing the resulting 3D reconstructions such as number of 2D class averages, efficiency/angular coverage, Rosenthal-Henderson plots and local/global 3D reconstruction resolution. Conclusion DRPnet shows greatly improved time-savings to generate an initial particle dataset compared to manual picking, followed by template-based autopicking. Compared to other networks, DRPnet has equivalent or better performance. DRPnet excels on cryoEM datasets that have low contrast or clumped particles. Evaluating other performance metrics, DRPnet is useful for higher resolution 3D reconstructions with decreased particle numbers or unknown symmetry, detecting particles with better angular orientation coverage.

The quality of the quantitative information in single-particle inductively coupled plasma mass spectrometry (SP-ICP-MS) depends directly on the number concentration of the nanoparticles in the sample analyzed, which is proportional to the flux of nanoparticles through the plasma. Particle number concentrations must be selected in accordance with the data acquisition frequency, to control the precision from counting statistics and the bias, which is produced by the occurrence of multiple-particle events recorded as single-particle events. With quadrupole mass spectrometers, the frequency of data acquisition is directly controlled by the dwell time. The effect of dwell times from milli- to microseconds (10 ms, 5 ms, 100 μs, and 50 μs) on the quality of the quantitative data has been studied. Working with dwell times in the millisecond range, precision figures about 5 % were achieved, whereas using microsecond dwell times, the suitable fluxes of nanoparticles are higher and precision was reduced down to 1 %; this was independent of the dwell time selected. Moreover, due to the lower occurrence of multiple-nanoparticle events, linear ranges are wider when dwell times equal to or shorter than 100 μs are used. A calculation tool is provided to determine the optimal concentration for any instrument or experimental conditions selected. On the other hand, the use of dwell times in the microsecond range reduces significantly the contribution of the background and/or the presence of dissolved species, in comparison with the use of millisecond dwell times. Although the use of dwell times equal to or shorter than 100 μs offers improved performance working in single-particle mode, the use of conventional dwell times (3–10 ms) should not be discarded, once their limitations are known.

This work investigates the performance of the electrospray aerosol generator at the European X‐ray Free Electron Laser (EuXFEL). This generator is, together with an aerodynamic lens stack that transports the particles into the X‐ray interaction vacuum chamber, the method of choice to deliver particles for single‐particle coherent diffractive imaging (SPI) experiments at the EuXFEL. For these experiments to be successful, it is necessary to achieve high transmission of particles from solution into the vacuum interaction region. Particle transmission is highly dependent on efficient neutralization of the charged aerosol generated by the electrospray mechanism as well as the geometry in the vicinity of the Taylor cone. We report absolute particle transmission values for different neutralizers and geometries while keeping the conditions suitable for SPI experiments. Our findings reveal that a vacuum ultraviolet ionizer demonstrates a transmission efficiency approximately seven times greater than the soft X‐ray ionizer used previously. Combined with an optimized orifice size on the counter electrode, we achieve >40% particle transmission from solution into the X‐ray interaction region. These findings offer valuable insights for optimizing electrospray aerosol generator configurations and data rates for SPI experiments. We investigate the performance of an electrospray aerosol generator at the European X‐ray Free Electron Laser for single‐particle coherent diffractive imaging. The findings highlight enhanced particle transmission efficiency with VUV ionization, larger orifice diameters, electric fields and 3D‐printed twin‐nozzle design, providing insights for optimizing aerosol injection in XFEL experiments.

The respiratory chain in the inner mitochondrial membrane contains three large multi‐enzyme complexes that together establish the proton gradient for ATP synthesis, and assemble into a supercomplex. A 19‐Å 3D map of the 1.7‐MDa amphipol‐solubilized supercomplex I 1 III 2 IV 1 from bovine heart obtained by single‐particle electron cryo‐microscopy reveals an amphipol belt replacing the membrane lipid bilayer. A precise fit of the X‐ray structures of complex I, the complex III dimer, and monomeric complex IV indicates distances of 13 nm between the ubiquinol‐binding sites of complexes I and III, and of 10–11 nm between the cytochrome c binding sites of complexes III and IV. The arrangement of respiratory chain complexes suggests two possible pathways for efficient electron transfer through the supercomplex, of which the shorter branch through the complex III monomer proximal to complex I may be preferred. The respiratory chain complexes of the mitochondrial inner membrane are organized as three higher‐order multi‐enzyme complexes. This study puts forward the first cryo‐EM map for one of these supercomplexes and provides insight into possible pathways for efficient electron transfer.

Bacterial extracellular vesicles (BEVs) are nano‐size particles secreted by bacteria that carry various bioactive components. These vesicles are thought to provide a new window into the mechanisms by which bacteria affect their hosts, but their fundamental proprieties within human remain poorly understood. Here, we developed a single‐vesicle analytical platform that enabled BEV detection in complex biological samples of host. Using this platform, we found the presence of BEVs in the host circulation and they were mainly derived from gut microbes. We showed that the levels of circulating BEVs in humans significantly increased with aging due to an age‐related increase in intestinal permeability. Significantly different levels of BEVs in blood were also found in patients with colorectal cancer and colitis. Together, our study provides new insights into circulating BEV biology and reveals their potential as a new class of biomarkers.