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This article investigated the effects of airborne-particle abrasion and nanosilica (nano-Si) infiltration treatment on the surface characteristics of dental zirconia. A total of 15 unsintered zirconia ceramic green bodies (10 × 10 × 3 mm) were divided into three groups (n = 5): Group C, no treatment after sintering; Group S, airborne-particle abrasion with 50-µm aluminum oxide particles after sintering; and Group N, infiltration of nano-Si followed by sintering and hydrofluoric acid (HF) etching. The zirconia disks' surface roughness was analyzed by atomic force microscopy (AFM). The surface morphology of the specimens was analyzed using scanning electron microscopy (SEM), and the chemical composition was analyzed by energy-dispersive x-ray (EDX). Data were statistically analyzed by Kruskal-Wallis test (P < .05). Zirconia surface treatments by infiltration of nano-Si, sintering, and HF etching showed multiple changes in the surface features. The surface roughness of Groups C, S, and N were 0.88 ± 0.07 µm, 1.26 ± 0.10 µm, and 1.69 ± 0.15 µm, respectively. The surface roughness of Group N was significantly higher than that of Groups C and S (P < .05). EDX analysis showed peaks that corresponded to silica (Si) after infiltration with colloidal Si that disappeared following acid etching. Infiltrating nano-Si increases the surface roughness of zirconia. The formation of retentive nanopores on the surface potentially improves the zirconia-resin cement bonding strengths. [ABSTRACT FROM AUTHOR]

Photocatalytic water-splitting represents a promising avenue for clean hydrogen production, necessitating an in-depth understanding of the photocatalytic reaction mechanism. The majority of the photocatalytic materials need cocatalysts to enhance the photo-oxidation or reduction reactions. However, the working mechanism, such as collecting charge carriers or reducing the reaction barrier, is not clear because they disperse inhomogeneously on a surface, and it is difficult to follow the local charge carrier behavior. This study employs the pattern-illumination time-resolved phase microscopy (PI-PM) method to unravel the spatial charge carrier behavior in photocatalytic systems, utilizing time-resolved microscopic image (refractive index change) sequences and their clustering analyses. This approach is robust for studying the change in local charge carrier behavior. We studied two major cocatalyst effects on photocatalysts: TiO2 with/without Pt and hematite with/without CoPi. The PI-PM method, supported by charge type clustering and the effects of scavengers, allowed for the analysis of local activity influenced by cocatalysts. This approach revealed that the introduction of cocatalysts alters the local distribution of charge carrier behavior and significantly impacts their decay rates. In TiO2 systems, the presence of Pt cocatalysts led to a local electron site on the micron scale, extending the lifetime to a few tens of microseconds from a few microseconds. Similarly, in hematite films with CoPi, we observed a notable accumulation of holes at cocatalyst sites, emphasizing the role of cocatalysts in enhancing photocatalytic efficiency. The study's findings highlight the complexity of charge carrier dynamics in photocatalytic processes and the significant influence of cocatalysts. [ABSTRACT FROM AUTHOR]

High tilt angle (45 °) ferroelectric liquid crystal (F L C) in surface stabilized geometry, having no chiral smectic A (S m A ∗) phase, has been studied for the reorientation of the smectic layers near the transition temperature (T c). The electro-optical studies have shown the stripe domain formation in which the liquid crystal molecules are aligned along the rubbing direction, but the smectic layers are tilted away from the rubbing direction at room temperature. In such high tilt angle F L C s , the molecular alignment and smectic layer formation start from bottom and top rubbed grooves at T c. The domain formation of the FLC takes place in the middle of the top and bottom surfaces due to the frustration of the dipolar interaction. The smectic layer switching is observed by optical microscopy and confirmed by the dielectric spectroscopy method near T c of S m C ∗ and chiral nematic phases. Domain switching has shown a larger switching angle than the molecular tilt angle within the smectic layer. These studies are expected to be significant for understanding the smectic layer structure and the domain switching process, which may pave the way for large optical switching devices. [ABSTRACT FROM AUTHOR]

Fast carrier dynamics in organic thin-film transistors (OTFTs) was investigated by time-resolved electrostatic force microscopy (tr-EFM). We found that the carrier diffusion in the OTFTs proceeded in two stages: fast diffusion and slow diffusion. By applying the instantaneous frequency method to EFM, the temporal evolution of the spatial distribution of fast carriers in the channel region of the OTFTs, which took place on the timescale of several hundreds of nanoseconds, was evaluated. The inhomogeneous distribution of the local decay time constant showed that the carrier diffusion of the OTFTs was limited by the grain boundaries between each crystalline region. The quantitative capability of the method was verified by comparing the values of the carrier mobility estimated by the tr-EFM measurement and a numerical simulation. The mobility estimated from the experiment and the simulation showed good agreement, showing the possibility of the tr-EFM to evaluate the time evolution of dynamic phenomena in semiconductor devices. [ABSTRACT FROM AUTHOR]

Colloidal probes are often used in force microscopy when the geometry of the tip–sample interaction should be well controlled. Their calibration requires an understanding of their mechanical response, which is very sensitive to the details of the force sensor consisting of a cantilever and the attached colloid. We present some analytical models to describe the dynamics of the cantilever and its load positioned anywhere along its length. The thermal noise calibration of such probes is then studied from a practical point of view, leading to correction coefficients that can be applied in standard force microscope calibration routines. Experimental measurements of resonance frequencies and thermal noise profiles of raw and loaded cantilevers demonstrate the validity of the approach. [ABSTRACT FROM AUTHOR]

An approach for the crystallographic mapping of two-phase alloys on the nanoscale using a combination of scanned precession electron diffraction and open-source python libraries is introduced in this paper. This method is demonstrated using the example of a two-phase α/β titanium alloy. The data were recorded using a direct electron detector to collect the patterns, and recently developed algorithms to perform automated indexing and analyse the crystallography from the results. Very high-quality mapping is achieved at a 3 nm step size. The results show the expected Burgers orientation relationships between the α laths and β matrix, as well as the expected misorientations between α laths. A minor issue was found that one area was affected by 180° ambiguities in indexing occur due to this area being aligned too close to a zone axis of the α with twofold projection symmetry (not present in 3D) in the zero-order Laue Zone, and this should be avoided in data acquisition in the future. Nevertheless, this study demonstrates a good workflow for the analysis of nanocrystalline two- or multi-phase materials, which will be of widespread use in analysing two-phase titanium and other systems and how they evolve as a function of thermomechanical treatments.

The controlled creation and manipulation of defects in 2D materials has become increasingly popular as a means to design and tune new material functionalities. However, defect characterization by direct atomic-scale imaging is often severely limited by surface contamination due to a blanket of hydrocarbons. Thus, analysis techniques that can characterize atomic-scale defects despite the contamination layer are advantageous. In this work, we take inspiration from X-ray absorption spectroscopy and use broad-beam electron energy loss spectroscopy (EELS) to characterize defect structures in 2D hexagonal boron nitride (hBN) based on averaged fine structure in the boron K-edge. Since EELS is performed in a transmission electron microscope (TEM), imaging can be performed in-situ to assess contamination levels and other factors such as tears in the fragile 2D sheets, which can affect the spectroscopic analysis. We demonstrate the TEM-EELS technique for 2D hBN samples irradiated with different ion types and doses, finding spectral signatures indicative of boron-oxygen bonding that can be used as a measure of sample defectiveness depending on the ion beam treatment. We propose that even in cases where surface contamination has been mitigated, the averaging-based TEM-EELS technique can be useful for efficient sample surveys to support atomically resolved EELS experiments.

The molecular foundations of epidermal cell wall mechanics are critical for understanding structure-function relationships of primary cell walls in plants and facilitating the design of bioinspired materials. To uncover the molecular mechanisms regulating the high extensibility and strength of the cell wall, the onion epidermal wall is stretched uniaxially to various strains and cell wall structures from mesoscale to atomic scale are characterized. Upon longitudinal stretching to high strain, epidermal walls contract in the transverse direction, resulting in a reduced area. Atomic force microscopy shows that cellulose microfibrils exhibit orientation-dependent rearrangements at high strains: longitudinal microfibrils are straightened out and become highly ordered, while transverse microfibrils curve and kink. Small-angle X-ray scattering detects a 7.4 nm spacing aligned along the stretch direction at high strain, which is attributed to distances between individual cellulose microfibrils. Furthermore, wide-angle X-ray scattering reveals a widening of (004) lattice spacing and contraction of (200) lattice spacing in longitudinally aligned cellulose microfibrils at high strain, which implies longitudinal stretching of the cellulose crystal. These findings provide molecular insights into the ability of the wall to bear additional load after yielding: the aggregation of longitudinal microfibrils impedes sliding and enables further stretching of the cellulose to bear increased loads.

The structural diversity of biological macromolecules in different environments contributes complexity to enzymological processes vital for cellular functions. Fluorescence resonance energy transfer and electron microscopy are used to investigate the enzymatic reaction of T4 DNA ligase catalyzing the ligation of nicked DNA. The data show that both the ligase-AMP complex and the ligase-AMP-DNA complex can have four conformations. This finding suggests the parallel occurrence of four ligation reaction pathways, each characterized by specific conformations of the ligase-AMP complex that persist in the ligase-AMP-DNA complex. Notably, these complexes have DNA bending angles of ≈0°, 20°, 60°, or 100°. The mechanism of parallel reactions challenges the conventional notion of simple sequential reaction steps occurring among multiple conformations. The results provide insights into the dynamic conformational changes and the versatile attributes of T4 DNA ligase and suggest that the parallel multiple reaction pathways may correspond to diverse T4 DNA ligase functions. This mechanism may potentially have evolved as an adaptive strategy across evolutionary history to navigate complex environments.

Extracellular vesicles (EVs) play key roles in diverse biological processes, transport biomolecules between cells and have been engineered for therapeutic applications. A useful EV bioengineering strategy is to express engineered proteins on the EV surface to confer targeting, bioactivity and other properties. Measuring how incorporation varies across a population of EVs is important for characterising such materials and understanding their function, yet it remains challenging to quantitatively characterise the absolute number of engineered proteins incorporated at single-EV resolution. To address these needs, we developed a HaloTag-based characterisation platform in which dyes or other synthetic species can be covalently and stoichiometrically attached to engineered proteins on the EV surface. To evaluate this system, we employed several orthogonal quantification methods, including flow cytometry and fluorescence microscopy, and found that HaloTag-mediated quantification is generally robust across EV analysis methods. We compared HaloTag-labelling to antibody-labelling of EVs using single vesicle flow cytometry, enabling us to measure the substantial degree to which antibody labelling can underestimate proteins present on an EV. Finally, we demonstrate the use of HaloTag to compare between protein designs for EV bioengineering. Overall, the HaloTag system is a useful EV characterisation tool which complements and expands existing methods.

SIGNIFICANCE: Information about the spatial organization of fibers within a nerve is crucial to our understanding of nerve anatomy and its response to neuromodulation therapies. A serial block-face microscopy method [three-dimensional microscopy with ultraviolet surface excitation (3D-MUSE)] has been developed to image nerves over extended depths ex vivo. To routinely visualize and track nerve fibers in these datasets, a dedicated and customizable software tool is required. AIM: Our objective was to develop custom software that includes image processing and visualization methods to perform microscopic tractography along the length of a peripheral nerve sample. APPROACH: We modified common computer vision algorithms (optic flow and structure tensor) to track groups of peripheral nerve fibers along the length of the nerve. Interactive streamline visualization and manual editing tools are provided. Optionally, deep learning segmentation of fascicles (fiber bundles) can be applied to constrain the tracts from inadvertently crossing into the epineurium. As an example, we performed tractography on vagus and tibial nerve datasets and assessed accuracy by comparing the resulting nerve tracts with segmentations of fascicles as they split and merge with each other in the nerve sample stack. RESULTS: We found that a normalized Dice overlap ( Dice norm ) metric had a mean value above 0.75 across several millimeters along the nerve. We also found that the tractograms were robust to changes in certain image properties (e.g., downsampling in-plane and out-of-plane), which resulted in only a 2% to 9% change to the mean Dice norm values. In a vagus nerve sample, tractography allowed us to readily identify that subsets of fibers from four distinct fascicles merge into a single fascicle as we move ∼ 5    mm along the nerves length. CONCLUSIONS: Overall, we demonstrated the feasibility of performing automated microscopic tractography on 3D-MUSE datasets of peripheral nerves. The software should be applicable to other imaging approaches. The code is available at https://github.com/ckolluru/NerveTracker.

Poly(ethylene oxide) (PEO) is a well-known biocompatible polymer and has widely been used for medical applications. Recently, we have investigated the dynamic behavior of hydration water in the vicinity of PEO chains at physiological temperature and shown the presence of slow water with diffusion coefficient one order of magnitude less than that of bulk water. This could be evidence for the intermediate water that is critical for biocompatibility; however, its detailed dynamical features were not established. In this article, we analyze the quasi-elastic neutron scattering from hydration water through mode distribution analysis and present a microscopic picture of hydration water as well as its relation to cold crystallization. [ABSTRACT FROM AUTHOR]

Objectives: To compare marginal gap width and depth with different cementation systems, excess removal, and after polishing. Method and materials: In total, 80 composite crowns were milled, divided into ten groups, and cemented on identical artificial teeth. Eight crowns per group were fixed with (i) zinc phosphate cement (ZnOPh), (ii) glass-ionomer cement (GIC), (iii) resin-reinforced glass-ionomer cement (GIC mod), (iv) dual-curing adhesive composite (Comp dual), or (v) dual-curing self-adhesive composite (Comp SE dual). Excess removal was performed with a scaler after brief light-cure (tack-cure), final light-cure, during rubber or gel phase or by wiping with foam pellet. Curing was completed in chemical, dark cure, or light-curing modus. The specimens were polished and stored in water (37°C). The margins were digitized using a 3D laser-scanning microscope (VK-X100 series, Keyence). The width and the depth of the marginal gap were measured at 10 points between the crown margin and the preparation margin. Results: The width after excess removal varied between 65.1 ± 15.7 µm (Comp dual, wipe, with polishing) and 208.6 ± 266.7 µm (Comp SE dual, dark cure, without polishing). The depth varied between 29.8 ± 22.2 µm (Comp dual, wipe, with polishing) and 89.5 ± 45.2 µm (Comp SE dual, dark cure, without polishing). The impact on gap width and depth was detected for fixation material, excess removal, and polishing. Conclusion: The gap depth and width depend on the luting material and the mode of access removal. Polishing can improve the gap quality, especially for GIC and resin-based systems. [ABSTRACT FROM AUTHOR]

Monoolein-based liquid crystal phases are established media that are researched for various biological applications, including drug delivery. While water is the most common solvent for self-assembly, some ionic liquids (ILs) can support lipidic self-assembly. However, currently, there is limited knowledge of IL-lipid phase behavior in ILs. In this study, the lyotropic liquid crystal phase behavior of monoolein was investigated in six protic ILs known to support amphiphile self-assembly, namely ethylammonium nitrate, ethanolammonium nitrate, ethylammonium formate, ethanolammonium formate, ethylammonium acetate, and ethanolammonium acetate. These ILs were selected to identify specific ion effects on monoolein self-assembly, specifically increasing the alkyl chain length of the cation or anion, the presence of a hydroxyl group in the cation, and varying the anion. The lyotropic liquid crystal phases with 20–80 wt. % of monoolein were characterized over a temperature range from 25 to 65 °C using synchrotron small angle x-ray scattering and cross-polarized optical microscopy. These results were used to construct partial phase diagrams of monoolein in each of the six protic ILs, with inverse hexagonal, bicontinuous cubic, and lamellar phases observed. Protic ILs containing the ethylammonium cation led to monoolein forming lamellar and bicontinuous cubic phases, while those containing the ethanolammonium cation formed inverse hexagonal and bicontinuous cubic phases. Protic ILs containing formate and acetate anions favored bicontinuous cubic phases across a broader range of protic IL concentrations than those containing the nitrate anion. [ABSTRACT FROM AUTHOR]

Time-resolved pump–probe and two-dimensional spectroscopy are widely used to study ultrafast chemical and biological processes in solutions. However, the corresponding signals at long times can be contaminated by molecular photothermal effects, which are caused by the nonradiative heat dissipation of photoexcited molecules to the surroundings. Additionally, molecular diffusion affects the transient spectroscopic signals because photoexcited molecules can diffuse away from the pump and probe beam focuses. Recently, a theoretical description of molecular photothermal effects on time-resolved IR spectroscopy was reported. In this work, I consider the molecular photothermal process, molecular diffusion, and sample flow to develop a generalized theoretical description of time-resolved spectroscopy. The present work can be used to interpret time-resolved spectroscopic signals of electronic or vibrational chromophores and understand the rate and mechanisms of the conversion of high-frequency molecular electronic and vibrational energy to solvent kinetic energy in condensed phases. [ABSTRACT FROM AUTHOR]

Gamma-prefoldin (γPFD), a unique chaperone found in the extremely thermophilic methanogen Methanocaldococcus jannaschii, self-assembles into filaments in vitro, which so far have been observed using transmission electron microscopy and cryo-electron microscopy. Utilizing three-dimensional stochastic optical reconstruction microscopy (3D-STORM), here we achieve ∼20 nm resolution by precisely locating individual fluorescent molecules, hence resolving γPFD ultrastructure both in vitro and in vivo. Through CF647 NHS ester labeling, we first demonstrate the accurate visualization of filaments and bundles with purified γPFD. Next, by implementing immunofluorescence labeling after creating a 3xFLAG-tagged γPFD strain, we successfully visualize γPFD in M. jannaschii cells. Through 3D-STORM and two-color STORM imaging with DNA, we show the widespread distribution of filamentous γPFD structures within the cell. These findings provide valuable insights into the structure and localization of γPFD, opening up possibilities for studying intriguing nanoscale components not only in archaea but also in other microorganisms.

Cell plate formation during cytokinesis entails multiple stages occurring concurrently and requiring orchestrated vesicle delivery, membrane remodelling, and timely deposition of polysaccharides, such as callose. Understanding such a dynamic process requires dissection in time and space; this has been a major hurdle in studying cytokinesis. Using lattice light sheet microscopy (LLSM), we studied cell plate development in four dimensions, through the behavior of yellow fluorescent protein (YFP)-tagged cytokinesis-specific GTPase RABA2a vesicles. We monitored the entire duration of cell plate development, from its first emergence, with the aid of YFP-RABA2a, in both the presence and absence of cytokinetic callose. By developing a robust cytokinetic vesicle volume analysis pipeline, we identified distinct behavioral patterns, allowing the identification of three easily trackable cell plate developmental phases. Notably, the phase transition between phase I and phase II is striking, indicating a switch from membrane accumulation to the recycling of excess membrane material. We interrogated the role of callose using pharmacological inhibition with LLSM and electron microscopy. Loss of callose inhibited the phase transitions, establishing the critical role and timing of the polysaccharide deposition in cell plate expansion and maturation. This study exemplifies the power of combining LLSM with quantitative analysis to decode and untangle such a complex process.

Despite much progress, image processing remains a significant bottleneck for high-throughput analysis of microscopy data. One popular platform for single-cell time-lapse imaging is the mother machine, which enables long-term tracking of microbial cells under precisely controlled growth conditions. While several mother machine image analysis pipelines have been developed in the past several years, adoption by a non-expert audience remains a challenge. To fill this gap, we implemented our own software, MM3, as a plugin for the multidimensional image viewer napari. napari-MM3 is a complete and modular image analysis pipeline for mother machine data, which takes advantage of the high-level interactivity of napari. Here, we give an overview of napari-MM3 and test it against several well-designed and widely used image analysis pipelines, including BACMMAN and DeLTA. Researchers often analyze mother machine data with custom scripts using varied image analysis methods, but a quantitative comparison of the output of different pipelines has been lacking. To this end, we show that key single-cell physiological parameter correlations and distributions are robust to the choice of analysis method. However, we also find that small changes in thresholding parameters can systematically alter parameters extracted from single-cell imaging experiments. Moreover, we explicitly show that in deep learning-based segmentation, what you put is what you get (WYPIWYG) - that is, pixel-level variation in training data for cell segmentation can propagate to the model output and bias spatial and temporal measurements. Finally, while the primary purpose of this work is to introduce the image analysis software that we have developed over the last decade in our lab, we also provide information for those who want to implement mother machine-based high-throughput imaging and analysis methods in their research.

A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies, in comparison, has been much more complex, largely owing to the irregular shapes of protein structures1. Here we describe extendable linear, curved and angled protein building blocks, as well as inter-block interactions, that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight 'train track' assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence-structure relationships, it has not previously been possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank three-dimensional canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to 'back of an envelope' architectural blueprints.

In this work, we examine the use of environment-sensitive fluorescent dyes in fluorescence lifetime imaging microscopy (FLIM) biosensors. We screened merocyanine dyes to find an optimal combination of environment-induced lifetime changes, photostability, and brightness at wavelengths suitable for live-cell imaging. FLIM was used to monitor a biosensor reporting conformational changes of endogenous Cdc42 in living cells. The ability to quantify activity using phasor analysis of a single fluorophore (e.g., rather than ratio imaging) eliminated potential artifacts. We leveraged these properties to determine specific concentrations of activated Cdc42 across the cell.

Neural networks are promising tools for high-throughput and accurate transmission electron microscopy (TEM) analysis of nanomaterials, but are known to generalize poorly on data that is "out-of-distribution" from their training data. Given the limited set of image features typically seen in high-resolution TEM imaging, it is unclear which images are considered out-of-distribution from others. Here, we investigate how the choice of metadata features in the training dataset influences neural network performance, focusing on the example task of nanoparticle segmentation. We train and validate neural networks across curated, experimentally collected high-resolution TEM image datasets of nanoparticles under various imaging and material parameters, including magnification, dosage, nanoparticle diameter, and nanoparticle material. Overall, we find that our neural networks are not robust across microscope parameters, but do generalize across certain sample parameters. Additionally, data preprocessing can have unintended consequences on neural network generalization. Our results highlight the need to understand how dataset features affect deployment of data-driven algorithms.

In material processing and handling processes, premixed interlayer often replace the ideal Ni/Al interface, which would become a new origin of alloying reaction. This work investigates shock-induced reaction mechanism and kinetics of premixed Ni/Al nanolaminates with molecular dynamics simulations and theoretical analysis. The reaction is found to be driven by the crystallization evolution in premixed interlayer and the diffusion of premixed atoms. Among them, multi-stage reaction patterns are strongly manifested by the crystallization evolution characteristics. Specifically, "crystallization-dissolution-secondary growth" and "crystallization-dissolution" of B2 phase respectively correspond to the solid-state and solid-liquid reaction cases, where crystallizations are fitted well by Johnson–Mehl–Avrami kinetics model. Interestingly, the different growth mechanisms of B2 grain are revealed, namely nuclei coalescence and atomic diffusion. Moreover, the analysis of microscopic diffusion theory indicates a certain non-random diffusion nature for solid-state reaction initiation, but near-purely random diffusion for solid-liquid reaction initiation. The diffused Al atoms possess a limited diffusion coefficient and enhanced diffusion correlation, resulting in extremely slow mixing rate in Ni layer. In addition, the influence law of Ni concentration in premixed interlayer on reactivity parameters can be quantitatively described by a quadratic function. [ABSTRACT FROM AUTHOR]

This article investigated the effects of airborne-particle abrasion and nanosilica (nano-Si) infiltration treatment on the surface characteristics of dental zirconia. A total of 15 unsintered zirconia ceramic green bodies (10 x 10 x 3 mm) were divided into three groups (n = 5): Group C, no treatment after sintering; Group S, airborne-particle abrasion with 50-p.m aluminum oxide particles after sintering; and Group N, infiltration of nano-Si followed by sintering and hydrofluoric acid (HF) etching. The zirconia disks' surface roughness was analyzed by atomic force microscopy (AFM). The surface morphology of the specimens was analyzed using scanning electron microscopy (SEM), and the chemical composition was analyzed by energy-dispersive x-ray (EDX). Data were statistically analyzed by the Kruskal-Wallis test (P < .05). Zirconia surface treatments by infiltration of nano-Si, sintering, and HF etching showed multiple changes in the surface features. The surface roughness of Groups C, S, and N were 0.88 ± 0.07 µm, 1.26 ± 0.10 µm, and 1.69 ± 0.15 µm, respectively. The surface roughness of Group N was significantly higher than that of Groups C and S (P < .05). EDX analysis showed peaks that corresponded to silica (Si) after infiltration with colloidal Si that disappeared following acid etching. Infiltrating nano-Si increases the surface roughness of zirconia. The formation of retentive nanopores on the surface potentially improves the zirconia-resin cement bonding strengths. [ABSTRACT FROM AUTHOR]

Photoinduced force microscopy (PiFM) is a technique for nanoscale characterization of optically active materials. For correct data analysis, it is important to understand and recognize potential artifacts. In this study, we provide a Fourier-based framework for the different origins of the photoinduced force, including the photothermal motion of the atomic force microscopy (AFM) tip in PiFM measurements. We use individual gold nanoparticles as a model system to explore such tip-related phenomena and to demonstrate the benefits of three-dimensional analysis of the photoinduced force. Comparison of the in-phase heterodyne PiFM signal and the derivative of the tip–sample interaction, ∂ ⟨ k ts ⟩ / ∂ z c , directly reveals a photothermal origin for the PiFM signal in our experiments. Furthermore, we observe a lateral photothermal vibration of the tip apex induced by tip asymmetry. This lateral vibration emphasizes the importance of considering the motion of the AFM tip during data analysis. The improved lateral resolution conferred by ∂ ⟨ k ts ⟩ / ∂ z c can lead to misinterpretation. Our findings highlight that meticulous data analysis is required to ensure the correct interpretation of PiFM data. [ABSTRACT FROM AUTHOR]

Purpose: To compare the fit of 3D-printed titanium (Ti) and cobalt-chromium (Co-Cr) abutments with implants to computer numerical control (CNC)-milled, ready-made abutment-implant assemblies. Their clinical applicability was also evaluated by measuring removal torque values (RTVs) and percentage torque loss of abutment screws. Materials and Methods: A total of 138 abutments were included in the study: 92 abutments were fabricated with Ti and Co-Cr alloys using computerassisted design (CAD) through selective laser melting, and 46 ready-made abutments were prepared. The fit of interfaces between 90 abutments from the three groups (30 ready-made, 30 3D-printed Ti, and 30 3D-printed Co-Cr abutments) and implant assemblies was demonstrated by scanning electron microscopy (SEM) and confocal scanning laser microscopy (CSLM). After 30-Ncm torque tightening of Ti abutment screws twice within 10 minutes, the RTVs and percentage torque loss of screws of 48 abutments (16 ready-made, 16 3D-printed Ti, and 16 3D-printed Co-Cr) were evaluated after 10 minutes of thermocycling and cyclic loading. Results: The fits of 3D-printed Co-Cr abutments were not statistically different from those of ready-made abutments (P = .383), while the fit of 3D-printed Ti abutments was inadequate (P < .001). The RTVs of 3D-printed abutments after cyclic loading were significantly decreased compared with those of CNC-milled abutments (P < .001). Conclusion: The fit of interfaces between 3D-printed Co-Cr abutments and implants was adequate. The RTVs of 3D-printed Co-Cr abutments were not significantly different from those of CNC-milled abutments after 10 minutes of 30-Ncm torque tightening and thermocycling. [ABSTRACT FROM AUTHOR]

BACKGROUND: The infection of the liver by Plasmodium parasites is an obligatory step leading to malaria disease. Following hepatocyte invasion, parasites differentiate into replicative liver stage schizonts and, in the case of Plasmodium species causing relapsing malaria, into hypnozoites that can lie dormant for extended periods of time before activating. The liver stages of Plasmodium remain elusive because of technical challenges, including low infection rate. This has been hindering experimentations with well-established technologies, such as electron microscopy. A deeper understanding of hypnozoite biology could prove essential in the development of radical cure therapeutics against malaria. RESULTS: The liver stages of the rodent parasite Plasmodium berghei, causing non-relapsing malaria, and the simian parasite Plasmodium cynomolgi, causing relapsing malaria, were characterized in human Huh7 cells or primary non-human primate hepatocytes using Correlative Light-Electron Microscopy (CLEM). Specifically, CLEM approaches that rely on GFP-expressing parasites (GFP-CLEM) or on an immunofluorescence assay (IFA-CLEM) were used for imaging liver stages. The results from P. berghei showed that host and parasite organelles can be identified and imaged at high resolution using both CLEM approaches. While IFA-CLEM was associated with more pronounced extraction of cellular content, samples features were generally well preserved. Using IFA-CLEM, a collection of micrographs was acquired for P. cynomolgi liver stage schizonts and hypnozoites, demonstrating the potential of this approach for characterizing the liver stages of Plasmodium species causing relapsing malaria. CONCLUSIONS: A CLEM approach that does not rely on parasites expressing genetically encoded tags was developed, therefore suitable for imaging the liver stages of Plasmodium species that lack established protocols to perform genetic engineering. This study also provides a dataset that characterizes the ultrastructural features of liver stage schizonts and hypnozoites from the simian parasite species P. cynomolgi.

The development of high-resolution microscopes has made it possible to investigate cellular processes in 3D and over time. However, observing fast cellular dynamics remains challenging because of photobleaching and phototoxicity. Here we report the implementation of two content-aware frame interpolation (CAFI) deep learning networks, Zooming SlowMo and Depth-Aware Video Frame Interpolation, that are highly suited for accurately predicting images in between image pairs, therefore improving the temporal resolution of image series post-acquisition. We show that CAFI is capable of understanding the motion context of biological structures and can perform better than standard interpolation methods. We benchmark CAFIs performance on 12 different datasets, obtained from four different microscopy modalities, and demonstrate its capabilities for single-particle tracking and nuclear segmentation. CAFI potentially allows for reduced light exposure and phototoxicity on the sample for improved long-term live-cell imaging. The models and the training and testing data are available via the ZeroCostDL4Mic platform.

We present super-resolution microscopy of isolated functional mitochondria, enabling real-time studies of structure and function (voltages) in response to pharmacological manipulation. Changes in mitochondrial membrane potential as a function of time and position can be imaged in different metabolic states (not possible in whole cells), created by the addition of substrates and inhibitors of the electron transport chain, enabled by the isolation of vital mitochondria. By careful analysis of structure dyes and voltage dyes (lipophilic cations), we demonstrate that most of the fluorescent signal seen from voltage dyes is due to membrane bound dyes, and develop a model for the membrane potential dependence of the fluorescence contrast for the case of super-resolution imaging, and how it relates to membrane potential. This permits direct analysis of mitochondrial structure and function (voltage) of isolated, individual mitochondria as well as submitochondrial structures in the functional, intact state, a major advance in super-resolution studies of living organelles.

The adaptive mechanical properties of soft and fibrous biological materials are relevant to their functionality. The emergence of the macroscopic response of these materials to external stress and intrinsic cell traction from local deformations of their structural components is not well understood. Here, we investigate the nonlinear elastic behavior of blood clots by combining microscopy, rheology, and an elastic network model that incorporates the stretching, bending, and buckling of constituent fibrin fibers. By inhibiting fibrin cross-linking in blood clots, we observe an anomalous softening regime in the macroscopic shear response as well as a reduction in platelet-induced clot contractility. Our model explains these observations from two independent macroscopic measurements in a unified manner, through a single mechanical parameter, the bending stiffness of individual fibers. Supported by experimental evidence, our mechanics-based model provides a framework for predicting and comprehending the nonlinear elastic behavior of blood clots and other active biopolymer networks in general.

The thymus, a key organ in the adaptive immune system, is sensitive to a variety of insults including cytotoxic preconditioning, which leads to atrophy, compression of the blood vascular system, and alterations in hemodynamics. Although the thymus has innate regenerative capabilities, the production of T cells relies on the trafficking of lymphoid progenitors from the bone marrow through the altered thymic blood vascular system. Our understanding of thymic blood vascular hemodynamics is limited due to technical challenges associated with accessing the native thymus in live mice. To overcome this challenge, we developed an intravital two-photon imaging method to visualize the native thymus in vivo and investigated functional changes to the vascular system following sublethal irradiation. We quantified blood flow velocity and shear rate in cortical blood vessels and identified a subtle but significant increase in vessel leakage and diameter ~24 hrs post-sublethal irradiation. Ex vivo whole organ imaging of optically cleared thymus lobes confirmed a disruption of the thymus vascular structure, resulting in an increase in blood vessel diameter and vessel area, and concurrent thymic atrophy. This novel two-photon intravital imaging method enables a new paradigm for directly investigating the thymic microenvironment in vivo.

Our sense of hearing is mediated by cochlear hair cells, of which there are two types organized in one row of inner hair cells and three rows of outer hair cells. Each cochlea contains 5-15 thousand terminally differentiated hair cells, and their survival is essential for hearing as they do not regenerate after insult. It is often desirable in hearing research to quantify the number of hair cells within cochlear samples, in both pathological conditions, and in response to treatment. Machine learning can be used to automate the quantification process but requires a vast and diverse dataset for effective training. In this study, we present a large collection of annotated cochlear hair-cell datasets, labeled with commonly used hair-cell markers and imaged using various fluorescence microscopy techniques. The collection includes samples from mouse, rat, guinea pig, pig, primate, and human cochlear tissue, from normal conditions and following in-vivo and in-vitro ototoxic drug application. The dataset includes over 107,000 hair cells which have been identified and annotated as either inner or outer hair cells. This dataset is the result of a collaborative effort from multiple laboratories and has been carefully curated to represent a variety of imaging techniques. With suggested usage parameters and a well-described annotation procedure, this collection can facilitate the development of generalizable cochlear hair-cell detection models or serve as a starting point for fine-tuning models for other analysis tasks. By providing this dataset, we aim to give other hearing research groups the opportunity to develop their own tools with which to analyze cochlear imaging data more fully, accurately, and with greater ease.

Lipids play crucial roles in many biological processes. Mapping spatial distributions and examining the metabolic dynamics of different lipid subtypes in cells and tissues are critical to better understanding their roles in aging and diseases. Commonly used imaging methods (such as mass spectrometry-based, fluorescence labeling, conventional optical imaging) can disrupt the native environment of cells/tissues, have limited spatial or spectral resolution, or cannot distinguish different lipid subtypes. Here we present a hyperspectral imaging platform that integrates a Penalized Reference Matching algorithm with Stimulated Raman Scattering (PRM-SRS) microscopy. Using this platform, we visualize and identify high density lipoprotein particles in human kidney, a high cholesterol to phosphatidylethanolamine ratio inside granule cells of mouse hippocampus, and subcellular distributions of sphingosine and cardiolipin in human brain. Our PRM-SRS displays unique advantages of enhanced chemical specificity, subcellular resolution, and fast data processing in distinguishing lipid subtypes in different organs and species.

Raman microscopy is a vibrational imaging technology that can detect molecular chemical bond vibrational signals. Since this signal is originated from almost every vibrational mode of molecules with different vibrational energy levels, it provides spatiotemporal distribution of various molecules in living organisms without the need for any labeling. The limitations of low signal strength in Raman microscopy have been effectively addressed by incorporating a stimulated emission process, leading to the development of stimulated Raman scattering (SRS) microscopy. Furthermore, the issue of low spatial resolution has been resolved through the application of computational techniques, specifically image deconvolution. In this article, we present a comprehensive guide to super-resolution SRS microscopy using an Adam-based pointillism deconvolution (A-PoD) algorithm, complemented by a user-friendly graphical user interface (GUI). We delve into the crucial parameters and conditions necessary for achieving super-resolved images through SRS imaging. Additionally, we provide a step-by-step walkthrough of the preprocessing steps and the use of GUI-supported A-PoD. This complete package offers a user-friendly platform for super-resolution SRS microscopy, enhancing the versatility and applicability of this advanced microscopy technique to reveal nanoscopic multimolecular nature. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Super-resolution stimulated Raman scattering microscopy with graphical user interface-supported A-PoD Support Protocol: Deuterium labeling on cells with heavy water for metabolic imaging.

Whereas traditional histology and light microscopy require multiple steps of formalin fixation, paraffin embedding, and sectioning to generate images for pathologic diagnosis, Microscopy using Ultraviolet Surface Excitation (MUSE) operates through UV excitation on the cut surface of tissue, generating images of high resolution without the need to fix or section tissue and allowing for potential use for downstream molecular tests. Here, we present the first study of the use and suitability of MUSE microscopy for neuropathological samples. MUSE images were generated from surgical biopsy samples of primary and metastatic brain tumor biopsy samples (n = 27), and blinded assessments of diagnoses, tumor grades, and cellular features were compared to corresponding hematoxylin and eosin (H&E) images. A set of MUSE-treated samples subsequently underwent exome and targeted sequencing, and quality metrics were compared to those from fresh frozen specimens. Diagnostic accuracy was relatively high, and DNA and RNA integrity appeared to be preserved for this cohort. This suggests that MUSE may be a reliable method of generating high-quality diagnostic-grade histologic images for neuropathology on a rapid and sample-sparing basis and for subsequent molecular analysis of DNA and RNA.

Multiphoton microscopy can resolve fluorescent structures and dynamics deep in scattering tissue and has transformed neural imaging, but applying this technique in vivo can be limited by the mechanical and optical constraints of conventional objectives. Short working distance objectives can collide with compact surgical windows or other instrumentation and preclude imaging. Here we present an ultra-long working distance (20 mm) air objective called the Cousa objective. It is optimized for performance across multiphoton imaging wavelengths, offers a more than 4 mm2 field of view with submicrometer lateral resolution and is compatible with commonly used multiphoton imaging systems. A novel mechanical design, wider than typical microscope objectives, enabled this combination of specifications. We share the full optical prescription, and report performance including in vivo two-photon and three-photon imaging in an array of species and preparations, including nonhuman primates. The Cousa objective can enable a range of experiments in neuroscience and beyond.

Hollow vaterite microspheres are important materials for biomedical applications such as drug delivery and regenerative medicine owing to their biocompatibility, high specific surface area, and ability to encapsulate a large number of bioactive molecules and compounds. We demonstrated that hollow vaterite microspheres are produced by an Escherichia coli strain engineered with a urease gene cluster from the ureolytic bacteria Sporosarcina pasteurii in the presence of bovine serum albumin. We characterized the 3D nanoscale morphology of five biogenic hollow vaterite microspheres using 3D high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM) tomography. Using automated high-throughput HAADF-STEM imaging across several sample tilt orientations, we show that the microspheres evolved from a smaller more ellipsoidal shape to a larger more spherical shape while the internal hollow core increased in size and remained relatively spherical, indicating that the microspheres produced by this engineered strain likely do not contain the bacteria. The statistical 3D morphology information demonstrates the potential for using biogenic calcium carbonate mineralization to produce hollow vaterite microspheres with controlled morphologies. STATEMENT OF SIGNIFICANCE: The nanoscale 3D structures of biomaterials determine their physical, chemical, and biological properties, however significant efforts are required to obtain a statistical understanding of the internal 3D morphology of materials without damaging the structures. In this study, we developed a non-destructive, automated technique that allows us to understand the nanoscale 3D morphology of many unique hollow vaterite microspheres beyond the spectroscopy methods that lack local information and microscopy methods that cannot interrogate the full 3D structure. The method allowed us to quantitatively correlate the external diameters and aspect ratios of vaterite microspheres with their hollow internal structures at the nanoscale. This work demonstrates the opportunity to use automated transmission electron microscopy to characterize nanoscale 3D morphologies of many biomaterials and validate the chemical and biological functionality of these materials.

The yeast vacuole membrane can phase separate into ordered and disordered domains, a phenomenon that is required for micro-lipophagy under nutrient limitation. Despite its importance as a biophysical model and physiological significance, it is not yet resolved if specific lipidome changes drive vacuole phase separation. Here we report that the metabolism of sphingolipids (SLs) and their sorting into the vacuole membrane can control this process. We first developed a vacuole isolation method to identify lipidome changes during the onset of phase separation in early stationary stage cells. We found that early stationary stage vacuoles are defined by an increased abundance of putative raft components, including 40% higher ergosterol content and a nearly 3-fold enrichment in complex SLs (CSLs). These changes were not found in the corresponding whole cell lipidomes, indicating that lipid sorting is associated with domain formation. Several facets of SL composition-headgroup stoichiometry, longer chain lengths, and increased hydroxylations-were also markers of phase-separated vacuole lipidomes. To test SL function in vacuole phase separation, we carried out a systematic genetic dissection of their biosynthetic pathway. The abundance of CSLs controlled the extent of domain formation and associated micro-lipophagy processes, while their headgroup composition altered domain morphology. These results suggest that lipid trafficking can drive membrane phase separation in vivo and identify SLs as key mediators of this process in yeast.

The inner mitochondrial membrane (IMM) generates power to drive cell function, and its dynamics control mitochondrial health and cellular homeostasis. Here, we describe the cell-permeant, lipid-like small molecule MAO-N3 and use it to assemble high-density environmentally sensitive (HIDE) probes that selectively label and image the IMM in live cells and multiple cell states. MAO-N3 pairs with strain-promoted azide-alkyne click chemistry-reactive fluorophores to support HIDE imaging using confocal, structured illumination, single-molecule localization and stimulated emission depletion microscopy, all with significantly improved resistance to photobleaching. These probes generate images with excellent spatial and temporal resolution, require no genetic manipulations, are non-toxic in model cell lines and primary cardiomyocytes (even under conditions that amplify the effects of mitochondrial toxins) and can visualize mitochondrial dynamics for 12.5 h. This probe will enable comprehensive studies of IMM dynamics with high temporal and spatial resolution.

Lipids, and cationic lipids in particular are of interest as delivery vectors for hydrophobic drugs such as the cancer therapeutic paclitaxel, and the structures of lipid assemblies affect their efficacy. We investigated the effect of incorporating the multivalent cationic lipid MVL5 (+5e) and poly(ethylene glycol)-lipids (PEG-lipids), alone and in combination, on the structure of fluid-phase lipid assemblies of the charge-neutral lipid 1,2-dioleoyl-sn-glycero-phosphocholine (DOPC). This allowed us to elucidate lipid-assembly structure correlations in sonicated formulations with high charge density, which are not accessible with univalent lipids such as the well-studied DOTAP (+1e). Cryogenic transmission electron microscopy (cryo-TEM) allowed us to determine the structure of the lipid assemblies, revealing diverse combinations of vesicles and disc-shaped, worm-like, and spherical micelles. Remarkably, MVL5 forms an essentially pure phase of disc micelles at 50 mol % MVL5. At a higher (75 mol %) content of MVL5, short- and intermediate-length worm-like micellar rods were observed, and in ternary mixtures with PEG-lipid, longer and highly flexible worm-like micelles formed. Independent of their length, the worm-like micelles coexisted with spherical micelles. In stark contrast, DOTAP forms mixtures of vesicles, disc micelles, and spherical micelles at all studied compositions, even when combined with PEG-lipids. The observed similarities and differences in the effects of charge (multivalent versus univalent) and high curvature (multivalent charge versus PEG-lipid) on the assembly structure provide insights into parameters that control the size of fluid lipid nanodiscs, relevant for future applications.

Vibrational sum-frequency generation (VSFG), a second-order nonlinear optical signal, has traditionally been used to study molecules at interfaces as a spectroscopy technique with a spatial resolution of ~100 µm. However, the spectroscopy is not sensitive to the heterogeneity of a sample. To study mesoscopically heterogeneous samples, we, along with others, pushed the resolution limit of VSFG spectroscopy down to ~1 µm level and constructed the VSFG microscope. This imaging technique not only can resolve sample morphologies through imaging, but also record a broadband VSFG spectrum at every pixel of the images. Being a second-order nonlinear optical technique, its selection rule enables the visualization of non-centrosymmetric or chiral self-assembled structures commonly found in biology, materials science, and bioengineering, among others. In this article, the audience will be guided through an inverted transmission design that allows for imaging unfixed samples. This work also showcases that VSFG microscopy can resolve chemical-specific geometric information of individual self-assembled sheets by combining it with a neural network function solver. Lastly, the images obtained under brightfield, SHG, and VSFG configurations of various samples briefly discuss the unique information revealed by VSFG imaging.

BACKGROUND AND AIMS: Data on how to teach endosonographers needle-based confocal laser endomicroscopy (nCLE)-guided histologic diagnosis of pancreatic cystic lesions (PCLs) are limited. Hence, we developed and tested a structured educational program to train early-career endosonographers in nCLE-guided diagnosis of PCLs. METHODS: Twenty-one early-career nCLE-naïve endosonographers watched a teaching module outlining nCLE criteria for diagnosing PCLs. Participants then reviewed 80 high-yield nCLE videos, recorded diagnoses, and received expert feedback (phase 1). Observers were then randomized to a refresher feedback session or self-learning at 4 weeks. Eight weeks after training, participants independently assessed the same 80 nCLE videos without feedback and provided histologic predictions (phase 2). Diagnostic performance of nCLE to differentiate mucinous versus nonmucinous PCLs and to diagnose specific subtypes were analyzed using histopathology as the criterion standard. Learning curves were determined using cumulative sum analysis. RESULTS: Accuracy and diagnostic confidence for differentiating mucinous versus nonmucinous PCLs improved as endosonographers progressed through nCLE videos in phase 1 (P < .001). Similar trends were observed with the diagnosis of PCL subtypes. Most participants achieved competency interpreting nCLE, requiring a median of 38 assessments (range, 9-67). During phase 2, participants independently differentiated PCLs with high accuracy (89%), high confidence (83%), and substantial interobserver agreement (κ = .63). Accuracy for nCLE-guided PCL subtype diagnoses ranged from 82% to 96%. The learned nCLE skills did not deteriorate at 8 weeks and were not impacted by a refresher session. CONCLUSIONS: We developed a practical, effective, and durable educational intervention to train early-career endosonographers in nCLE-guided diagnosis of PCLs.

Ambient air pollutants, including PM2.5 (aerodynamic diameter d ~2.5 μm), PM10 (d ~10 μm), and ultrafine particles (UFP: d

Arterial wall active mechanics are driven by resident smooth muscle cells, which respond to biological, chemical, and mechanical stimuli and activate their cytoskeletal machinery to generate contractile stresses. The cellular mechanoresponse is sensitive to environmental perturbations, often leading to maladaptation and disease progression. When investigated at the single cell scale, however, these perturbations do not consistently result in phenotypes observed at the tissue scale. Here, a multiscale model is introduced that translates microscale contractility signaling into a macroscale, tissue-level response. The microscale framework incorporates a biochemical signaling network along with characterization of fiber networks that govern the anisotropic mechanics of vascular tissue. By incorporating both biochemical and mechanical components, the model is more flexible and more broadly applicable to physiological and pathological conditions. The model can be applied to both cell and tissue scale systems, allowing for the analysis of in vitro, traction force microscopy and ex vivo, isometric contraction experiments in parallel. When applied to aortic explant rings and isolated smooth muscle cells, the model predicts that active contractility is not a function of stretch at intermediate strain. The model also successfully predicts cell-scale and tissue-scale contractility and matches experimentally observed behaviors, including the hypercontractile phenotype caused by chronic hyperglycemia. The connection of the microscale framework to the macroscale through the multiscale model presents a framework that can translate the wealth of information already collected at the cell scale to tissue scale phenotypes, potentially easing the development of smooth muscle cell-targeting therapeutics. [ABSTRACT FROM AUTHOR]

Electric force microscopy probes the statistics of electric field fluctuations from a sample surface, both through measurement of the noncontact friction exerted on the oscillating charged probe and by determination of the power spectrum of stochastic probe frequency fluctuations, referred to as "jitter." Here we calculate the frequency jitter power spectrum determined over a conducting sample of finite thickness, whose response is characterized by a dielectric function that is wavevector-dependent. These calculations complement previous predictions of the coefficient of noncontact friction in an electric force microscopy measurement for the same model, and also previous predictions of the jitter power spectrum for a dielectric continuum. The inclusion both of a finite sample thickness and a wavevector-dependent dielectric response can significantly enhance the magnitude of the predicted jitter spectrum for a conductor, relative to a simpler model of an infinitely thick dielectric continuum. These calculations provide a baseline prediction of the jitter power spectrum generated by the dynamics of conduction electrons in a metal sample. [ABSTRACT FROM AUTHOR]

The elastic behavior of nematics is commonly described in terms of the three so-called bulk deformation modes, i.e., splay, twist, and bend. However, the elastic free energy contains also other terms, often denoted as saddle–splay and splay–bend, which contribute, for instance, in confined systems. The role of such terms is controversial, partly because of the difficulty of their experimental determination. The saddle–splay (K24) and splay–bend (K13) elastic constants remain elusive also for theories; indeed, even the possibility of obtaining unambiguous microscopic expressions for these quantities has been questioned. Here, within the framework of Onsager theory with Parsons–Lee correction, we obtain microscopic estimates of the deformation free energy density of hard rod nematics in the presence of different director deformations. In the limit of a slowly changing director, these are directly compared with the macroscopic elastic free energy density. Within the same framework, we derive also closed microscopic expressions for all elastic coefficients of rodlike nematics. We find that the saddle–splay constant K24 is larger than both K11 and K22 over a wide range of particle lengths and densities. Moreover, the K13 contribution comes out to be crucial for the consistency of the results obtained from the analysis of the microscopic deformation free energy density calculated for variants of the splay deformation. [ABSTRACT FROM AUTHOR]

Polarization plays a crucial role in understanding the interaction of fluorescent molecules in a light field. We report the study on the effect of a field–dipole interaction under polarization light-sheet fluorescence microscopy using the vectorial theory of light. The molecule is suitably modeled as a radiating electric dipole in a polarized electric field (both linear and random), and the system point spread function (PSF) is determined for different orientations of the dipole (both fixed and random). PSF analysis and contour plots suggest distinct nature of a field distribution in each case, indicating the importance of a field–dipole interaction for high-quality fluorescence imaging. The analysis suggests that the field spreads gradually along the polarization axis at a high numerical aperture (NA) of the objective lens, whereas it is more isotropic and homogeneous at low NA. Moreover, fast changes are not observed at low NA (i.e., far from the central lobe in the field contour plots), suggesting the absence of high-frequency components. However, sidelobes are prominent for linear polarized (along x) light. On the other hand, rapid variations are evident for randomly polarized light, depicting the presence of high spatial frequencies in the system optical transfer function. The other significant observation is the distinct frequency spectrum (both k x and k y) for random and fixed dipoles, indicating the significance of dipole orientation in a light-sheet field. Compared to the point-illumination-based fluorescence microscopy, sheet based polarization technique provides a high signal-to-noise ratio, a uniform field, an order large field of view, and critical information (related to the micro-environment of a dipole and its short-range interactions). The study is expected to facilitate polarization-sensitive investigation of large biological specimens (both fixed and live). [ABSTRACT FROM AUTHOR]

COVID-19 is a serious global infectious disease impairing the quality of life of people across the world. SARS-CoV-2 may reside in nasopharyngeal and salivary secretions of COVID-19-infected patients and spreads mainly through respiratory droplets and fomites. It has presented a challenge to dentistry, as many dental procedures generate aerosols that could lead to cross-contamination. It also presents many post-infection complications that may continue to debilitate patients, even after successful management of the virus. One such complication may be osteomyelitis of the jaw. Two cases of post-COVID-19 osteomyelitis of the jaw are presented that were determined to be unrelated to mucormycosis in otherwise healthy individuals with no prior dental complaints. An attempt is made to shed light on clinical signs in post-COVID cases that may point to a diagnosis of the condition. The pathophysiology is also discussed, which may help in formulating guidelines to prevent and manage post-COVID osteomyelitis of the jaw. [ABSTRACT FROM AUTHOR]

Pollen-induced allergies affect a significant part of the population in developed countries. Current palynological analysis in Europe is a slow and laborious process which provides pollen information in a weekly-cycle basis. In this paper, we describe a system that allows to locate and classify, in a single step, the pollen grains present in standard glass microscope slides. Besides, processing the samples in the z-axis allows us to increase the probability of detecting grains compared to solutions based on one image per sample. Our system has been trained to recognise 11 pollen types, achieving 97.6 % success rate locating grains, of which 96.3 % are also correctly identified (0.956 macro–F1 score), and with a 2.4 % grains lost. Our results indicate that deep learning provides a robust framework to address automated identification of various pollen types, facilitating their daily measurement. [ABSTRACT FROM AUTHOR]