Structural Identification and Observation of Dose Rate-Dependent Beam-Induced Structural Changes of Micro- and Nanoplastic Particles by Pair Distribution Function Analysis in the Transmission Electron Microscope (ePDF).

Micro- and nanoplastics (MNPs) are considered a possible threat to microorganisms in the aquatic environment. Here, we show that total scattering intensity analysis of electron diffraction (ED) data measured by transmission electron microscopy, which yields the electron pair distribution function (ePDF), is a feasible method for the characterization and identification of MNPs down to 100 nm. To demonstrate the applicability, cryo ball-milled powders of the most common polymers [i.e., polyethylene , polypropylene, polyethylene terephthalate, and polyamide] and nano-sized polystyrene and silica spheres were used as model systems. The comparison of the experimentally determined reduced pair density functions (RDFs) with model RDFs derived from crystallographic data of the respective polymers allows the distinction of the different types of polymers. Furthermore, carbon-based polymers are highly beam-sensitive materials. The degradation of the samples under the electron beam was analyzed by conducting time-resolved ED measurements. Changes in the material can be visualized by the RDF analysis of the time-series of ED patterns, and information about the materials in question can be gained by this beam damage analysis. Prospectively, ePDF analytics will help to understand and study more precisely the input of MNPs into the environment.

Influence of random zone positioning errors on the resolving power of Fresnel zone plates.

Fresnel zone plates produced by electron beam lithography and planar etching techniques provide a resolving power of about 10 nm. An alternative zone plate fabrication approach is based on alternately coating a micro-wire with two different materials. With this process, very thin zone layers with very high aspect ratios can be deposited. However, depending on the fabrication method, random zone positioning errors may introduce strong aberrations. We simulate the effect of positioning errors using different random fluctuations and study their influence on zone plate resolution. We find that random errors significantly decrease the contrast transfer of X-ray microscopes. Additionally, we derive an upper bound for the mean acceptable variance of the deposition rate.

Automated quantification of vacuole fusion and lipophagy in Saccharomyces cerevisiae from fluorescence and cryo-soft X-ray microscopy data using deep learning.

During starvation in the yeast Saccharomyces cerevisiae vacuolar vesicles fuse and lipid droplets (LDs) can become internalized into the vacuole in an autophagic process named lipophagy. There is a lack of tools to quantitatively assess starvation-induced vacuole fusion and lipophagy in intact cells with high resolution and throughput. Here, we combine soft X-ray tomography (SXT) with fluorescence microscopy and use a deep-learning computational approach to visualize and quantify these processes in yeast. We focus on yeast homologs of mammalian NPC1 (NPC intracellular cholesterol transporter 1; Ncr1 in yeast) and NPC2 proteins, whose dysfunction leads to Niemann Pick type C (NPC) disease in humans. We developed a convolutional neural network (CNN) model which classifies fully fused versus partially fused vacuoles based on fluorescence images of stained cells. This CNN, named Deep Yeast Fusion Network (DYFNet), revealed that cells lacking Ncr1 (ncr1∆ cells) or Npc2 (npc2∆ cells) have a reduced capacity for vacuole fusion. Using a second CNN model, we implemented a pipeline named LipoSeg to perform automated instance segmentation of LDs and vacuoles from high-resolution reconstructions of X-ray tomograms. From that, we obtained 3D renderings of LDs inside and outside of the vacuole in a fully automated manner and additionally measured droplet volume, number, and distribution. We find that ncr1∆ and npc2∆ cells could ingest LDs into vacuoles normally but showed compromised degradation of LDs and accumulation of lipid vesicles inside vacuoles. Our new method is versatile and allows for analysis of vacuole fusion, droplet size and lipophagy in intact cells.Abbreviations: BODIPY493/503: 4,4-difluoro-1,3,5,7,8-pentamethyl-4-bora-3a,4a-diaza-s-Indacene; BPS: bathophenanthrolinedisulfonic acid disodium salt hydrate; CNN: convolutional neural network; DHE; dehydroergosterol; npc2∆, yeast deficient in Npc2; DSC, Dice similarity coefficient; EM, electron microscopy; EVs, extracellular vesicles; FIB-SEM, focused ion beam milling-scanning electron microscopy; FM 4-64, N-(3-triethylammoniumpropyl)-4-(6-[4-{diethylamino} phenyl] hexatrienyl)-pyridinium dibromide; LDs, lipid droplets; Ncr1, yeast homolog of human NPC1 protein; ncr1∆, yeast deficient in Ncr1; NPC, Niemann Pick type C; NPC2, Niemann Pick type C homolog; OD600, optical density at 600 nm; ReLU, rectifier linear unit; PPV, positive predictive value; NPV, negative predictive value; MCC, Matthews correlation coefficient; SXT, soft X-ray tomography; UV, ultraviolet; YPD, yeast extract peptone dextrose.

Copper(II) and Cobalt(II) Complexes Based on Abietate Ligands from Pinus Resin: Synthesis, Characterization and Their Antibacterial and Antiviral Activity against SARS-CoV-2.

Co-abietate and Cu-abietate complexes were obtained by a low-cost and eco-friendly route. The synthesis process used Pinus elliottii resin and an aqueous solution of CuSO4/CoSO4 at a mild temperature (80 °C) without organic solvents. The obtained complexes are functional pigments for commercial architectural paints with antipathogenic activity. The pigments were characterized by Fourier-transform infrared spectroscopy (FTIR), mass spectrometry (MS), thermogravimetry (TG), near-edge X-ray absorption fine structure (NEXAFS), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and colorimetric analysis. In addition, the antibacterial efficiency was evaluated using the minimum inhibitory concentration (MIC) test, and the antiviral tests followed an adaptation of the ISO 21702:2019 guideline. Finally, virus inactivation was measured using the RT-PCR protocol using 10% (w/w) of abietate complex in commercial white paint. The Co-abietate and Cu-abietate showed inactivation of >4 log against SARS-CoV-2 and a MIC value of 4.50 µg·mL-1 against both bacteria Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). The results suggest that the obtained Co-abietate and Cu-abietate complexes could be applied as pigments in architectural paints for healthcare centers, homes, and public places.

3D membrane segmentation and quantification of intact thick cells using cryo soft X-ray transmission microscopy: A pilot study.

Structural analysis of biological membranes is important for understanding cell and sub-cellular organelle function as well as their interaction with the surrounding environment. Imaging of whole cells in three dimension at high spatial resolution remains a significant challenge, particularly for thick cells. Cryo-transmission soft X-ray microscopy (cryo-TXM) has recently gained popularity to image, in 3D, intact thick cells (∼10µm) with details of sub-cellular architecture and organization in near-native state. This paper reports a new tool to segment and quantify structural changes of biological membranes in 3D from cryo-TXM images by tracking an initial 2D contour along the third axis of the microscope, through a multi-scale ridge detection followed by an active contours-based model, with a subsequent refinement along the other two axes. A quantitative metric that assesses the grayscale profiles perpendicular to the membrane surfaces is introduced and shown to be linearly related to the membrane thickness. Our methodology has been validated on synthetic phantoms using realistic microscope properties and structure dimensions, as well as on real cryo-TXM data. Results demonstrate the validity of our algorithms for cryo-TXM data analysis.