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Structural materials used in nuclear reactor environments are subjected to coupled extremes such as high temperature, irradiation, and corrosion which act in concert to degrade their functional performance. Connecting alloy microstructure such as grain boundaries, and accumulating point defects with corrosion attack and pore morphology is critical to understanding underlying mechanisms. We uncover the compositional variations and morphology at multiple length scales in corrosion-damaged Ni-Cr alloy after exposure to oxidants in molten fluoride salts. A complex network of dense corrosion pores is detected by surface-level SEM observations. The corrosion pores take on a 1-dimensional morphology and are enriched with Ni and depleted of Cr 1–5 µm from the pore surface. STEM-EDS and 4D-STEM strain maps acquired simultaneously highlight the local variations in composition and structure of a ≤ 200 nm Cr-rich layer identified from a cross-section taken at the bottom of an isolated corrosion pore between the Ni-Cr alloy matrix and the embedded salt. However, the absence of an observed interface between the Ni-Cr alloy matrix and the FCC-structured Cr-rich layer suggests that Cr plating from the salt did not transpire. These findings support a proposed Cr lattice diffusion mechanism rather than Cr-precipitation from the salt to accommodate temperature transient conditions during sample cooling. Through the development of a 1D phase field model, these results are rationalized by formation energies for the Ni- and Cr-oxidation into the molten salt. This study reveals the locally altered microstructure caused by high temperature corrosion in non-steady-state molten salt nuclear reactor environments.

Many animals use visual information to navigate1-4, but how such information is encoded and integrated by the navigation system remains incompletely understood. In Drosophila melanogaster, EPG neurons in the central complex compute the heading direction5 by integrating visual input from ER neurons6-12, which are part of the anterior visual pathway (AVP)10,13-16. Here we densely reconstruct all neurons in the AVP using electron-microscopy data17. The AVP comprises four neuropils, sequentially linked by three major classes of neurons: MeTu neurons10,14,15, which connect the medulla in the optic lobe to the small unit of the anterior optic tubercle (AOTUsu) in the central brain; TuBu neurons9,16, which connect the AOTUsu to the bulb neuropil; and ER neurons6-12, which connect the bulb to the EPG neurons. On the basis of morphologies, connectivity between neural classes and the locations of synapses, we identify distinct information channels that originate from four types of MeTu neurons, and we further divide these into ten subtypes according to the presynaptic connections in the medulla and the postsynaptic connections in the AOTUsu. Using the connectivity of the entire AVP and the dendritic fields of the MeTu neurons in the optic lobes, we infer potential visual features and the visual area from which any ER neuron receives input. We confirm some of these predictions physiologically. These results provide a strong foundation for understanding how distinct sensory features can be extracted and transformed across multiple processing stages to construct higher-order cognitive representations.

IntroductionThe physical modification of cartilage grafts during rhinoplasty risks chondrocyte death at the margins where the tissue is cut. This study compares chondrocyte viability between diced, scaled, and pate samples in human models, and further computes percent chondrocyte viability as a function of sequential dicing size in a computational model.MethodsSeptal cartilage from 11 individuals was prepared as follows: diced (1 mm cubic), scaled (shaved to  0.05). Conversely, pate samples had significantly less viability compared to positive controls, diced samples, and scaled samples (all p

Tumor-associated T cells orchestrate cancer rejection after checkpoint blockade immunotherapy. T cell function depends on dynamic antigen recognition through the T cell receptor (TCR) resulting in T cell activation. Here, we present an approach to quantify the dynamics and magnitude of tumor-associated T cell activation at multiple time points in living mice using the genetically encoded calcium reporter Salsa6f and functional intravital microscopy (F-IVM). Our protocol allows researchers to measure the activation dynamics of various immune cells in vivo. For complete details on the use and execution of this protocol, please refer to Geels et al.1.

We describe the development, operation, and application of the 4D Camera-a 576 by 576 pixel active pixel sensor for scanning/transmission electron microscopy which operates at 87,000 Hz. The detector generates data at ∼480 Gbit/s which is captured by dedicated receiver computers with a parallelized software infrastructure that has been implemented to process the resulting 10-700 Gigabyte-sized raw datasets. The back illuminated detector provides the ability to detect single electron events at accelerating voltages from 30 to 300 kV. Through electron counting, the resulting sparse data sets are reduced in size by 10--300× compared to the raw data, and open-source sparsity-based processing algorithms offer rapid data analysis. The high frame rate allows for large and complex scanning diffraction experiments to be accomplished with typical scanning transmission electron microscopy scanning parameters.

Systemic amyloidosis involves the deposition of misfolded proteins in organs/tissues, leading to progressive organ dysfunction and failure. Congo red is the gold-standard chemical stain for visualizing amyloid deposits in tissue, showing birefringence under polarization microscopy. However, Congo red staining is tedious and costly to perform, and prone to false diagnoses due to variations in amyloid amount, staining quality and manual examination of tissue under a polarization microscope. We report virtual birefringence imaging and virtual Congo red staining of label-free human tissue to show that a single neural network can transform autofluorescence images of label-free tissue into brightfield and polarized microscopy images, matching their histochemically stained versions. Blind testing with quantitative metrics and pathologist evaluations on cardiac tissue showed that our virtually stained polarization and brightfield images highlight amyloid patterns in a consistent manner, mitigating challenges due to variations in chemical staining quality and manual imaging processes in the clinical workflow.

Determining the label to target ratio, also known as the degree of labeling (DOL), is crucial for quantitative fluorescence microscopy and a high DOL with minimal unspecific labeling is beneficial for fluorescence microscopy in general. Yet robust, versatile and easy-to-use tools for measuring cell-specific labeling efficiencies are not available. Here we present a DOL determination technique named protein-tag DOL (ProDOL), which enables fast quantification and optimization of protein-tag labeling. With ProDOL various factors affecting labeling efficiency, including substrate type, incubation time and concentration, as well as sample fixation and cell type can be easily assessed. We applied ProDOL to investigate how human immunodeficiency virus-1 pathogenesis factor Nef modulates CD4 T cell activation measuring total and activated copy numbers of the adapter protein SLP-76 in signaling microclusters. ProDOL proved to be a versatile and robust tool for labeling calibration, enabling determination of labeling efficiencies, optimization of strategies and quantification of protein stoichiometry.

Drosophila border cell clusters model collective cell migration. Airyscan super-resolution microscopy enables fine-scale description of cluster shape and texture. Here we describe how to convert Airyscan images of border cell clusters into 3D models of the surface and detect regions of convex and concave curvature. We use spectral decomposition analysis to compare surface textures across genotypes to determine how genes of interest impact cluster surface geometry. This protocol applies to border cells and could generalize to additional cell types. For complete details on the use and execution of this protocol, please refer to Gabbert et al.1.

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.

Signal theory predicts organisms should evolve signals that are conspicuous to intended receivers in natural signalling environments. Cleaner shrimps remove ectoparasites from reef fish clients and many signal their intent to clean by whipping long, white antennae. As white is a reliably conspicuous colour in aquatic environments, we hypothesized that selection has acted to increase broad-spectrum antennal reflectance in cleaners. Using scanning electron microscopy, optical models and reflectance measurements, we found that the antennae in three obligate cleaner species from two families (Palaemonidae and Lysmatidae) had thick (∼6 µm) chitinous layers or densely packed high refractive index spheres (300-400 nm diameter), which models show increase reflectance (400-700 nm). Two facultative and non-cleaning species had no visible antennae ultrastructure beyond the chitinous exoskeleton. Antennae reflectance was significantly higher in obligate cleaners than in facultative and non-cleaning species. Our results suggest that some obligate cleaners may have evolved ultrastructures that increase the conspicuousness of their antennae as signals.

Mapping neuronal networks is a central focus in neuroscience. While volume electron microscopy (vEM) can reveal the fine structure of neuronal networks (connectomics), it does not provide molecular information to identify cell types or functions. We developed an approach that uses fluorescent single-chain variable fragments (scFvs) to perform multiplexed detergent-free immunolabeling and volumetric-correlated-light-and-electron-microscopy on the same sample. We generated eight fluorescent scFvs targeting brain markers. Six fluorescent probes were imaged in the cerebellum of a female mouse, using confocal microscopy with spectral unmixing, followed by vEM of the same sample. The results provide excellent ultrastructure superimposed with multiple fluorescence channels. Using this approach, we documented a poorly described cell type, two types of mossy fiber terminals, and the subcellular localization of one type of ion channel. Because scFvs can be derived from existing monoclonal antibodies, hundreds of such probes can be generated to enable molecular overlays for connectomic studies.

A new emissive guanosine analog CF3thG, constructed by a single trifluoromethylation step from the previously reported thG, displays red-shifted absorption and emission spectra compared to its precursor. The impact of solvent type and polarity on the photophysical properties of CF3thG suggests that the electronic effects of the trifluoromethyl group dominate its behavior and demonstrates its susceptibility to microenvironmental polarity changes. In vitro transcription initiations using T7 RNA polymerase, initiated with CF3thG, result in highly emissive 5'-labeled RNA transcripts, demonstrating the tolerance of the enzyme toward the analog. Viability assays with HEK293T cells displayed no detrimental effects at tested concentrations, indicating the safety of the analog for cellular applications. Live cell imaging of the free emissive guanosine analog using confocal microscopy was facilitated by its red-shifted absorption and emission and adequate brightness. Real-time live cell imaging demonstrated the release of the guanosine analog from HEK293T cells at concentration-gradient conditions, which was suppressed by the addition of guanosine.

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.

Refractive errors remain a global health concern, as a large proportion of the world's population is myopic. Current ablative approaches are costly, not without risks, and not all patients are candidates for these procedures. Electromechanical reshaping (EMR) has been explored as a viable cost-effective modality to directly shape tissues, including cartilage. In this study, stromal collagen structure and fibril orientation was examined before and after EMR with second-harmonic generation microscopy (SHG), a nonlinear multiphoton imaging method that has previously been used to study native corneal collagen with high spatial resolution. EMR, using a milled metal contact lens and potentiostat, was performed on the corneas of five extracted rabbit globes. SHG was performed using a confocal microscopy system and all images underwent collagen fibril orientation analysis. The collagen SHG signal in controls is uniform and is similarly seen in samples treated with pulsed potential, while continuous EMR specimens have reduced, nonhomogeneous signal. Collagen fibril orientation in native tissue demonstrates a broad distribution with suggestion of another peak evolving, while with EMR treated eyes a bimodal characteristic becomes readily evident. Pulsed EMR may be a means to correct refractive errors, as when comparing its SHG signal to negative control, preservation of collagen structures with little to no damage is observed. From collagen fiber orientation analysis, it can be inferred that simple DC application alters the structure of collagen. Future studies will involve histological assessment of these layers and multi-modal imaging analysis of dosimetry.

The dry mass and the orientation of biomolecules can be imaged without a label by measuring their permittivity tensor (PT), which describes how biomolecules affect the phase and polarization of light. Three-dimensional (3D) imaging of PT has been challenging. We present a label-free computational microscopy technique, PT imaging (PTI), for the 3D measurement of PT. PTI encodes the invisible PT into images using oblique illumination, polarization-sensitive detection and volumetric sampling. PT is decoded from the data with a vectorial imaging model and a multi-channel inverse algorithm, assuming uniaxial symmetry in each voxel. We demonstrate high-resolution imaging of PT of isotropic beads, anisotropic glass targets, mouse brain tissue, infected cells and histology slides. PTI outperforms previous label-free imaging techniques such as vector tomography, ptychography and light-field imaging in resolving the 3D orientation and symmetry of organelles, cells and tissue. We provide open-source software and modular hardware to enable the adoption of the method.

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.

Polymerization of nucleotides under prebiotic conditions simulating the early Earth has been extensively studied. Several independent methods have been used to verify that RNA-like polymers can be produced by hot wet-dry cycling of nucleotides. However, it has not been shown that these RNA-like polymers are similar to biological RNA with 3'-5' phosphodiester bonds. In the results described here, RNA-like polymers were generated from 5'-monophosphate nucleosides AMP and UMP. To confirm that the polymers resemble biological RNA, ribonuclease A should catalyze hydrolysis of the 3'-5' phosphodiester bonds between pyrimidine nucleotides to each other or to purine nucleotides, but not purine-purine nucleotide bonds. Here we show AFM images of specific polymers produced by hot wet-dry cycling of AMP, UMP and AMP/UMP (1:1) solutions on mica surfaces, before and after exposure to ribonuclease A. AMP polymers were unaffected by ribonuclease A but UMP polymers disappeared. This indicates that a major fraction of the bonds in the UMP polymers is indeed 3'-5' phosphodiester bonds. Some of the polymers generated from the AMP/UMP mixture also showed clear signs of cleavage. Because ribonuclease A recognizes the ester bonds in the polymers, we show for the first time that these prebiotically produced polymers are in fact similar to biological RNA but are likely to be linked by a mixture of 3'-5' and 2'-5' phosphodiester bonds.

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.

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.

In a scanning transmission electron microscope (STEM), producing a high-resolution image generally requires an electron beam focused to the smallest point possible. However, the magnetic lenses used to focus the beam are unavoidably imperfect, introducing aberrations that limit resolution. Modern STEMs overcome this by using hardware aberration correctors comprised of many multipole elements, but these devices are complex, expensive, and can be difficult to tune. We demonstrate a design for an electrostatic phase plate that can act as an aberration corrector. The corrector is comprised of annular segments, each of which is an independent two-terminal device that can apply a constant or ramped phase shift to a portion of the electron beam. We show the improvement in image resolution using an electrostatic corrector. Engineering criteria impose that much of the beam within the probe-forming aperture be blocked by support bars, leading to large probe tails for the corrected probe that sample the specimen beyond the central lobe. We also show how this device can be used to create other STEM beam profiles such as vortex beams and probes with a high degree of phase diversity, which improve information transfer in ptychographic reconstructions.

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

PURPOSE: Small-fiber neuropathy (SFN) is known to be associated with Sjögren disease (SjD), and in vivo corneal confocal microscopy can identify features compatible with SFN. Here, we performed a descriptive study to identify features of SFN of the corneal subbasal nerve plexus using in vivo confocal microscopy. METHODS: We recruited 10 participants from the Sjögrens International Collaborative Clinical Alliance (SICCA), 1 new participant (in an effort to expand the SICCA cohort), and 22 healthy controls. All participants underwent slit-lamp examination and in vivo confocal microscopy of the central corneal subbasal nerve plexus centered about the central whorl to create a 30-image montage. Each image was analyzed with automated software (ACCmetrics, Manchester, United Kingdom) to produce 7 nerve metrics. We performed t-tests and age-adjusted regressions to make comparisons of nerve metrics between participants with SjD and healthy controls. RESULTS: Most nerve metrics were significantly lower in participants with SjD compared with healthy controls. The mean corneal nerve fiber density was found to be 3.5 mm/mm 2 in participants with SjD compared with 10.6 mm/mm 2 in healthy controls (95% confidence interval, -8.4 to -0.93; P = 0.02). Within the 11 participants with SjD, 22 eyes were analyzed on confocal microscopy, and 16 of those eyes (from 9 individuals) did not have an identifiable central whorl. Within the 22 healthy controls, 22 eyes (right eye alone) were analyzed on confocal microscopy, and 21 of those eyes had an identifiable central whorl. CONCLUSIONS: SjD exhibits lower corneal nerve metrics compared with healthy controls. These findings suggest that features compatible with SFN can distinguish SjD from healthy controls and may serve as a potential novel biomarker in identifying SjD.

Previous studies have evaluated method performance for quantifying and characterizing microplastics in clean water, but little is known about the efficacy of procedures used to extract microplastics from complex matrices. Here we provided 15 laboratories with samples representing four matrices (i.e., drinking water, fish tissue, sediment, and surface water) each spiked with a known number of microplastic particles spanning a variety of polymers, morphologies, colors, and sizes. Percent recovery (i.e., accuracy) in complex matrices was particle size dependent, with ∼60-70% recovery for particles >212 μm, but as little as 2% recovery for particles

An analytical model is presented for light scattering associated with heat transport near a cell membrane that divides a complex system into two topologically distinct half-spaces. Our analysis is motivated by experiments on vibrational photothermal microscopy which have not only demonstrated remarkably high contrast and resolution, but also are capable of providing label-free local information of heat transport in complex morphologies. In the first Born approximation, the derived Greens function leads to the reconstruction of a full 3D image with photothermal contrast obtained using both amplitude and phase detection of periodic excitations. We show that important fundamental parameters including the Kapitza length and Kapitza resistance can be derived from experiments. Our goal is to spur additional experimental studies with high-frequency modulation and heterodyne detection in order to make contact with recent theoretical molecular dynamics calculations of thermal transport properties in membrane systems.