Metallic nanoparticle dimers have been used to enhance the excitation rate of single-quantum emitters. The interparticle distance (d) of the dimers has a crucial influence on the signal enhancement. Therefore, precise control of d is desired for optimal performance. However, statistical analysis of d has been often restricted to a small number of dimers due to the lack of reliable automatic software tools. For this reason, we developed a novel analysis tool for automatic dimer analysis. Our approach combines particle detection by circle Hough transformation (CHT) with custom classification routines optimised for distinct types of particles. We applied our tool to scanning electron microscopy (SEM) images and achieved great agreement in dimer detection, reaching an agreement of around 97% between automatic analysis and manual inspection for more than 3000 metallic nanoparticle dimers on DNA origami controlled by a combination of multiple DNA strands. Our study revealed the effects of the strand length (L) on the distribution of d. Based on geometric consideration, we expected a strong correlation between L and the standard deviation (σ) of d. We could verify this correlation by characterising four dimer designs with different L while analysing more than 1000 dimers per specimen.

Scalp hair is a key feature of humans and its variability has been the subject of a broad range of studies. A small subset of these studies has focused on geometric quantification of human scalp hair fibres, however the use of race- and ethnicity-based classification systems makes it challenging to draw objective conclusions about fibre variability. Furthermore, sample preparation techniques for micro-imaging studies often alter the original form of hair fibres. This study sought to determine which of the commonly reported descriptors could be resolved using micro-computed tomography (micro-CT) for fibres of varying curl. Images obtained from micro-CT were used to reconstruct three-dimensional images that were then analysed. The study also explored the capabilities and limitations of micro-CT as an imaging modality by comparing and cross-validating findings with those obtained from scanning electron microscopy (SEM) and laser micrometry. The former deals with surface imaging while the latter deals with cross-sectional measurements. Micro-CT was found to be highly effective at resolving cross-sectional ellipsoidal parameters, but performed more poorly than SEM in reconstructing surface level details at a 2 resolution. The technique was, however, able to reveal the presence of the medulla in type VI (high curl) hair fibres. When compared with high curl fibres, greater intra-fibre variability was observed for the low and medium curl fibres, highlighting the importance more objective classification systems.

Sidestream dark field (SDF) imaging is a tool for assessing microcirculation, commonly used for early diagnosis and monitoring of sepsis. In this study, we used SDF imaging to observe and assess the microcirculation of the intestinal mucosa during bowel surgery. We also compared different performance between normal mucosa and diseased mucosa using SDF imaging. SDF imaging was conducted in 13 patients to evaluate microcirculation parameters. All patients were assessed at distances of 0, 1, 2, 3 and 4 centimeters (cm) from the edge of the mesentery, respectively. Microcirculatory parameters such as microvascular flow index (MFI), proportion of perfused vessels (PPV), vascular density (VD), total vessel density (TVD), perfused vessel density (PVD) and heterogeneity index (HI) were measured in these patients. Compared to normal intestinal mucosa, the diseased intestinal mucosa exhibited higher values for VD (p = 0.044), TVD (p = 0.006) and PVD (p = 0.007). No significant differences in PPV, MFI and HI were observed between the two groups. The microcirculation parameters (MFI, PPV and PVD) of the intestine at the distal distance of 3 cm were significantly lower than those at a distance of 2 cm (MFI 1.5 (0.75) vs. 3 (0.5), PPV 57.6 (9.1) vs. 97.1 (8.6)% and PVD 11.395 (3.082) vs. 20.726 (4.115) mm/mm). In conclusion, SDF imaging is an advanced technique that provide real-time visualization of intestinal mucosal microcirculation. It has the potential to assess the blood perfusion of the intestine during surgery.

The evaluation of large experimental datasets is a fundamental aspect of research in every scientific field. Streamlining this process can improve the reliability of results while making data analysis more efficient and faster to execute. In biomedical research it is often very important to determine the type of cell death after various treatments. Thus, differentiating between viable, apoptotic, and necrotic cells provide critical insights into the treatment efficacy, a key aspect in the field of drug development. Fluorescent microscopy is perceived as a widely used technique for cell metabolism assessment and can therefore be used to investigate treatment outcomes after staining samples with cell death detection kit. However, accurate evaluation of therapeutic results requires quantitative analysis, often necessitating extensive postprocessing of imaging data. In this study, we introduce a complementary tool designed as a macro for the Fiji platform, enabling the automated postprocessing of fluorescent microscopy images to accurately distinguish and quantify viable, apoptotic, and necrotic cells.

The idea that disease is caused at the cellular level is so fundamental to us that we might forget the critical role microscopy played in generating and developing this insight. Visually identifying diseased or infected cells lays the foundation for any effort to curb human pathology. Since the discovery of the Plasmodium-infected red blood cells, which cause malaria, microscopy has undergone an impressive development now literally resolving individual molecules. This review explores the expansive field of light microscopy, focusing on its application to malaria research. Imaging technologies have transformed our understanding of biological systems, yet navigating the complex and ever-growing landscape of techniques can be daunting. This review offers a guide for researchers, especially those working on malaria, by providing historical context as well as practical advice on selecting the right imaging approach. The review advocates an integrated methodology that prioritises the research question while considering key factors like sample preparation, fluorophore choice, imaging modality, and data analysis. In addition to presenting seminal studies and innovative applications of microscopy, the review highlights a broad range of topics, from traditional techniques like white light microscopy to advanced methods such as superresolution microscopy and time-lapse imaging. It addresses the emerging challenges of microscopy, including phototoxicity and trade-offs in resolution and speed, and offers insights into future technologies that might impact malaria research. This review offers a mix of historical perspective, technological progress, and practical guidance that appeal to novice and advanced microscopists alike. It aims to inspire malaria researchers to explore imaging techniques that could enrich their studies, thus advancing the field through enhanced visual exploration of the parasite across scales and time.

Electron backscatter diffraction (EBSD) has developed over the last few decades into a valuable crystallographic characterisation method for a wide range of sample types. Despite these advances, issues such as the complexity of sample preparation, relatively slow acquisition, and damage in beam-sensitive samples, still limit the quantity and quality of interpretable data that can be obtained. To mitigate these issues, here we propose a method based on the subsampling of probe positions and subsequent reconstruction of an incomplete data set. The missing probe locations (or pixels in the image) are recovered via an inpainting process using a dictionary-learning based method called beta-process factor analysis (BPFA). To investigate the robustness of both our inpainting method and Hough-based indexing, we simulate subsampled and noisy EBSD data sets from a real fully sampled Ni-superalloy data set for different subsampling ratios of probe positions using both Gaussian and Poisson noise models. We find that zero solution pixel detection (inpainting un-indexed pixels) enables higher-quality reconstructions to be obtained. Numerical tests confirm high-quality reconstruction of band contrast and inverse pole figure maps from only 10% of the probe positions, with the potential to reduce this to 5% if only inverse pole figure maps are needed. These results show the potential application of this method in EBSD, allowing for faster analysis and extending the use of this technique to beam sensitive materials.

Magnaporthe oryzae is the causal agent of rice blast, one of the most serious diseases affecting rice cultivation around the world. During plant infection, M. oryzae forms a specialised infection structure called an appressorium. The appressorium forms in response to the hydrophobic leaf surface and relies on multiple signalling pathways, including a MAP kinase phosphorelay and cAMP-dependent signalling, integrated with cell cycle control and autophagic cell death of the conidium. Together, these pathways regulate appressorium morphogenesis.The appressorium generates enormous turgor, applied as mechanical force to breach the rice cuticle. Re-polarisation of the appressorium requires a turgor-dependent sensor kinase which senses when a critical threshold of turgor has been reached to initiate septin-dependent re-polarisation of the appressorium and plant infection. Invasive growth then requires differential expression and secretion of a large repertoire of effector proteins secreted by distinct secretory pathways depending on their destination, which is also governed by codon usage and tRNA thiolation. Cytoplasmic effectors require an unconventional Golgi-independent secretory pathway and evidence suggests that clathrin-mediated endocytosis is necessary for their delivery into plant cells. The blast fungus then develops a transpressorium, a specific invasion structure used to move from cell-to-cell using pit field sites containing plasmodesmata, to facilitate its spread in plant tissue. This is controlled by the same MAP kinase signalling pathway as appressorium development and requires septin-dependent hyphal constriction. Recent progress in understanding the mechanisms of rice infection by this devastating pathogen using live cell imaging procedures are presented.

Until recently, the lack of three-dimensional visualisation of whole cells at the electron microscopic (EM) level has led to a significant gap in our understanding of the interaction of cellular organelles and their interconnection. This is particularly true with regard to the role of the endoplasmic reticulum (ER). In this study, we perform three-dimensional reconstructions of serial FIB/SEM stacks and anaglyphs derived from volume rendering, cryo-scanning electron microscopy (cryo-SEM) and state-of-the-art electron microscopy immobilisation and imaging techniques. The results show that glyoxysomes are formed de novo in large numbers and in characteristic clusters on the ER upon germination in mesophyll cells of Arabidopsis cotyledons. The degradation of lipid bodies during germination occurs not only via the ER, which enlarges by taking up polar lipids resulting from enzymatic degradation by lipases, but also via glyoxysomes, which engulf lipid bodies. Dictyosomal (Golgi-derived) vesicles, which fuse with glyoxysomes or their precursors, also appear to be involved in the differentiation of glyoxysomes from segments of the ER. The formation of the central vacuole is the result of the fusion of protein storage vacuoles (protein bodies), which become complex three-dimensional structures during germination. Our observations also suggest that the vacuole plays a role in the degradation of glyoxysomes. The evidence provided in three dimensions shows that the endoplasmic reticulum plays a central role in the biogenesis and degradation of lipid bodies, the ontogeny of glyoxysomes and the development of plastids in the mesophyll cells of Arabidopsis cotyledons.

Ribosomes, discovered in 1955 by George Palade, were initially described as small cytoplasmic particles preferentially associated with the endoplasmic reticulum (ER). Over the years, extensive research has focused on both the structure and function of ribosomes. However, a fundamental question - how many ribosomes are present within whole cells - has remained largely unaddressed. In this study, we developed a microscopic method to quantify the total number of ribosomes in hTERT-RPE-1 cells and in nematode cells from various tissues of Caenorhabditis elegans hermaphrodites. Using electron tomography of high-pressure frozen, freeze-substituted and resin-embedded samples, we determined that the ribosome number in hTERT-RPE-1 cells is in the same order of magnitude as biochemical measurements obtained via RNA capillary electrophoresis. As expected, control worms exhibited a higher number of ribosomes compared to RNA polymerase I A subunit (RPOA-1)-depleted worms in two out of three analysed tissue types. Our imaging-based approach complements established biochemical methods by enabling direct quantification of ribosome numbers in specific samples. This method offers a powerful tool for advancing our understanding of ribosome localisation and distribution in cells and tissues across diverse model systems.

The types and quantities of microorganisms in activated sludge are directly related to the stability and efficiency of sewage treatment systems. This paper proposes a sludge microorganism detection method based on microscopic phase contrast image optimisation and deep learning. Firstly, a dataset containing eight types of microorganisms is constructed, and an augmentation strategy based on single and multisamples processing is designed to address the issues of sample deficiency and uneven distribution. Secondly, a phase contrast image quality optimisation algorithm based on fused variance is proposed, which can effectively improve the standard deviation, entropy, and detection performance. Thirdly, a lightweight YOLOv8n-SimAM model is designed, which introduces a SimAM attention module to suppress the complex background interference and enhance attentions to the target objects. The lightweight of the network is realised using a detection head based on multiscale information fusion convolutional module. In addition, a new loss function IW-IoU is proposed to improve the generalisation ability and overall performance. Comparative and ablative experiments are conducted, demonstrating the great application potential for rapid and accurate detection of microbial targets. Compared to the baseline model, the proposed method improves the detection accuracy by 12.35% and hastens the running speed by 37.9 frames per second while evidently reducing the model size.

Apicomplexans, a large phylum of protozoan intracellular parasites, well known for their ability to invade and proliferate within host cells, cause diseases with major health and economic impacts worldwide. These parasites are responsible for conditions such as malaria, cryptosporidiosis, and toxoplasmosis, which affect humans and other animals. Apicomplexans exhibit complex life cycles, marked by diverse modes of cell division, which are closely associated with their pathogenesis. All the unique structural and evolutionary characteristics of apicomplexan parasites, the biology underlying life stage transitions, and the singular mechanisms of cell division alongside their associated biomedical relevance have captured the attention of parasitologists of all times. Traditional light and electron microscopy have set the fundamental foundations of our understanding of these parasites, including the distinction among their modes of cell division. This has been more recently complemented by microscopy advances through the implementation of superresolution fluorescence microscopy, and variants of electron microscopy, such as cryo-EM and tomography, revealing intricate details of organelles and cell division. Ultrastructure Expansion Microscopy has emerged as a transformative, accessible approach that enhances resolution by physically expanding samples isometrically, allowing nanoscale visualisation on standard light microscopes. In this work, we review the most recent contributions of U-ExM and its recent improvements and innovations, in providing unprecedented insights into apicomplexan ultrastructure and its associated mechanisms, focusing particularly on cell division. We highlight the power of U-ExM in combination with protein-specific labelling, in aiding the visualisation of long oversighted organelles and detailed insights into the assembly of parasite-specific structures, such as the conoid in Plasmodia, and the apical-basal axis in Toxoplasma, respectively, during new parasite assembly. Altogether, the contributions of U-ExM reveal conserved and unique structural features across species while nearing super resolution. The development of these methodologies and their combination with different technologies are crucial for advancing our mechanistic understanding of apicomplexan biology, offering new perspectives that may facilitate novel therapeutic strategies against apicomplexan-caused diseases.

This article presents a qualitative, quantitative, and experimental analysis of optical coherence tomography (OCT) volumes obtained using different families of non-raster trajectories. We propose a multicriteria analysis to be used in the assessment of scan trajectories used in obtaining OCT volumetric point cloud data. The novel criteria includes exploitation/exploration ratio of the OCT data obtained, smoothness of the scan trajectory and fast preview of the acquired OCT data in addition to conventional criteria; time and quality (expressed as volume similarity rather than slice-by-slice image quality). The set of criteria proposed will be useful in assessing OCT scan trajectories for optimisation in various applications including robot assisted in vivo optical biopsy. We show in this paper that the rate of data acquisition is improved without degrading the OCT volume quality by scanning using non-raster trajectories (they are fast, smooth, and make the galvanometer scanners have less wear and tear). In particular, the rosette scan trajectory, which was the preferred non-raster trajectory, provided a balanced performance in having better clarity at the centre and periphery of the scanned object.

This short review discusses the recent developments in low-cost, high-resolution optoacoustic microscopy systems, integrating laser diodes for signal excitation, which are 20-40 times cheaper than the typically employed Q-switched nanosecond laser sources. The development of laser diode-based microscopes can substantially improve not only cost efficiency, but also multispectral capabilities, robustness, portability and overall imaging performance of the optoacoustic technique. To this end, we demonstrate relevant implementations in both time and frequency domain, highlighting their representative applications in biomedical research such as microvasculature imaging, oxygen saturation assessments, hybrid and multiview microscopy of model organisms and tissues and Doppler flow speed measurements. Finally, we analyse the benefits and limitations of each approach, identifying the respective application contexts where they achieve optimum performance.

Conventional optical microscopy imaging of obligate intracellular bacteria is hampered by the small size of bacterial cells, tight clustering exhibited by some bacterial species and challenges relating to labelling such as background from host cells, a lack of validated reagents, and a lack of tools for genetic manipulation. In this study, we imaged intracellular bacteria from the species Orientia tsutsugamushi (Ot) using five different fluorescence microscopy techniques: standard confocal, Airyscan confocal, instant Structured Illumination Microscopy (iSIM), three-dimensional Structured Illumination Microscopy (3D-SIM) and Stimulated Emission Depletion Microscopy (STED). We compared the ability of each to resolve bacterial cells in intracellular clumps in the lateral (xy) axis, using full width half-maximum (FWHM) measurements of a labelled outer membrane protein (ScaA) and the ability to detect small, outer membrane vesicles external to the cells. Comparing the techniques readily available to us (above), 3D-SIM microscopy, in combination with the shortest-wavelength dyes, was found overall to give the best lateral resolution. We next compared the ability of each technique to sufficiently resolve bacteria in the axial (z) direction and found 3D-STED to be the most successful method for this. We then combined this 3D-STED approach with a custom 3D cell segmentation and analysis pipeline using the open-source, deep learning software, Cellpose to segment the cells and subsequently the commercial software Imaris to analyse their 3D shape and size. Using this combination, we demonstrated differences in bacterial shape, but not their size, when grown in different mammalian cell lines. Overall, we compare the advantages and disadvantages of different super-resolution microscopy techniques for imaging this cytoplasmic obligate intracellular bacterium based on the specific research question being addressed.

Osteoblasts are the functional cells capable of bone formation in the bone microenvironment and play an important role in bone growth, development, and the maintenance of bone mass. The cells cultured in vitro are derived from preosteoblasts in tissues and possess the ability to divide and proliferate. Osteoblasts form the bone matrix by secreting collagen and other matrix proteins, which provides a foundation for the deposition of minerals such as calcium and phosphorus, ultimately resulting in the formation of hard bone tissue. Bone diseases affect the quality of life and the aging of the population. Bone diseases such as osteoporosis, fractures, bone tumours, and arthritis have a significant impact on quality of life, especially among the elderly population. These realities remind us that we should pay more attention to bone and joint health. Therefore, it is particularly important to study the imaging and characterisation of mechanical properties of bone cells, which provides a basis for the research of bone diseases in human beings.

Interference Reflection Microscopy (IRM) is an optical technique that relies on the interference between the reflected light from an incident beam as it passes through materials of different refractive indices. This technique has been successfully used to image microtubules, biologically important biofilaments with a diameter of 25 nm. However, it is often desirable to image both the microtubule and microtubule interacting proteins simultaneously. Here we present a simple modification to a standard multicolour total internal reflection fluorescence (TIRF) microscope that enables simultaneous high-speed IRM and single molecule TIRF imaging. Our design utilises a camera for each channel (IRM and TIRF) allowing independent optimisation of camera parameters for the two different modalities. We illustrate its application by imaging unlabelled microtubules and GFP-labelled end-binding protein EB1, which forms comets on the tips of polymerising microtubules. Our design is easily implemented, and with minimal cost, making it accessible to any laboratory with an existing fluorescence microscope.

The endoplasmic reticulum (ER) forms contact sites with the chloroplast. Exposing contact sites that contain both the chloroplast and the ER to localised high-fluence, wavelength specific, 405 nm violet light, hereinafter referred to as photostimulation, induces multiple, potentially interacting intra- and intercellular responses. The responses vary depending on the tissue type of the cell and the chloroplast. Photostimulating the ER-chloroplast contact sites in growing epidermal cells of the hypocotyl of Arabidopsis thaliana, produces a wave of cytoplasmic ionic calcium that traverses the cell, spreading radially to other cells around the circumference of the hypocotyl. A transient ER stress accompanies the calcium wave. These responses occur in older epidermal cells (5-8 days post-germination) with nonmotile chloroplasts tethered to the ER and the cell cortex but do not occur with motile or dividing chloroplasts. Dividing chloroplasts show a markedly different association with the ER, which forms a ring around the fission plane, similar to that of dividing mitochondria. Inhibition of calcium channels with lanthanum has no effect. Photostimulation of only the ER results in no ER stress and a calcium wave with a different spatiotemporal signature: delayed release and lower magnitude, with no accompanying ER stress response. Likewise, photostimulation of the chloroplast only, without the ER, produces no calcium wave or ER stress. General chloroplast photobleaching or restructuring caused by photostimulation is not the cause of this response; photostimulation with 488 nm of the same intensity and power as 405 nm photostimulation produces no change in cytosolic calcium levels. The pH of the ER decreases, indicating the involvement of ER ion transporters in the response. A wave of increased reactive oxygen species (ROS) in mitochondria and nuclei accompanies photostimulation. Together, these data support a model by which tethered ER-chloroplast contact sites constitute a unique subcellular photosensitive region and are part of an ER-mediated signalling network. Lay Abstract: The endoplasmic reticulum (ER) forms contact sites with the chloroplast. Shining violet (405 nm) light on the chloroplast with its associated ER produces a calcium wave through the cell that is communicated to other cells. This is correlated with a wave of transient denaturation of the luminal proteins of the ER (ER stress) and increased reactive oxygen species (ROS) in mitochondria. The wavelength dependence and precise cellular location of the light stimulation implies a novel way for plants to sense light. The movement of the response through the cell is consistent with the mediation of the response by a subcellular network, such as that formed by the ER.

Diagnostic electron microscopy (EM) is indispensable in all cases of infectious diseases which deserve or profit from the detection of the entire pathogen (i.e. the infectious unit). The focus of its application has shifted during the last decades from routine diagnostics to diagnostics of special cases, emergencies and the investigation of disease pathogenesis. While the focus of application has changed, the methods remain more or less the same. However, since the number of cases for diagnostic EM has declined as the number of laboratories that are able to perform such investigations, the preservation of the present knowledge is important. The aim of this article is to provide a review of the methods and strategies which are useful for diagnostic EM related to infectious diseases in our days. It also addresses weaknesses as well as useful variants or extensions of established methods. The main techniques, negative staining and thin section EM, are described in detail with links to suitable protocols and more recent improvements, such as thin section EM of small volume suspensions. Sample collection, transport and conservation/inactivation are discussed. Strategies of sample examination and requirements for a proper recognition of structures are outlined. Finally, some examples for the actual application of diagnostic EM related to infectious diseases are presented. The outlook section will discuss recent trends in microscopy, such as automated object recognition by machine learning, regarding their potential in supporting diagnostic EM.

Brain surgery is a widely practised and effective treatment for brain tumours, but accurately identifying and classifying tumour boundaries is crucial to maximise resection and avoid neurological complications. This precision in classification is essential for guiding surgical decisions and subsequent treatment planning. Hyperspectral (HS) imaging (HSI) is an emerging multidimensional optical imaging method that captures detailed spectral information across multiple wavelengths, allowing for the identification of nuanced differences in tissue composition, with the potential to enhance intraoperative tissue classification. However, current frameworks often require retraining models for each HSI to extract meaningful features, resulting in long processing times and high computational costs. Additionally, most methods utilise the deep semantic features at the end of the network for classification, ignoring the spatial details contained in the shallow features. To overcome these challenges, we propose a novel approach called MedDiffHSI, which combines diffusion and transformer techniques. Our method involves training an unsupervised learning framework based on the diffusion model to extract high-level and low-level spectral-spatial features from HSI. This approach eliminates the need for retraining of spectral-spatial feature learning model, thereby reducing time complexity. We then extract intermediate multistage features from different timestamps for classification using a pretrained denoising U-Net. To fully explore and exploit the rich contextual semantics and textual information hidden in the extracted diffusion feature, we utilise a spectral-spatial attention module. This module not only learns multistage information about features at different depths, but also extracts and enhances effective information from them. Finally, we employ a supervised transformer-based classifier with weighted majority voting (WMV) to perform the HSI classification. To validate our approach, we conduct comprehensive experiments on in vivo brain database data sets and also extend the analysis to include additional HSI data sets for breast cancer to evaluate the framework performance across different types of tissue. The results demonstrate that our framework outperforms existing approaches by using minimal training samples (5%) while achieving state-of-the-art performance.

In this short and popular review, we summarise some of our findings analysing the replication cycles of large DNA viruses using scanning transmission electron tomography (STEM tomography) that we applied in the laboratory of Paul Walther. It is also a tribute to a very kind and expert scientist, who recently retired. Transmission electron microscopy (TEM), in particular cryo-EM, has benefited tremendously from recent developments in instrumentation. However, TEM imaging remains limited by the thickness of the specimen and classical thin-section TEM typically generates 2D representations of 3D volumes. Although TEM tomography can partly overcome this limitation, the thickness of the sample, the volume that can be analysed in 3D, remains limiting. STEM tomography can partly overcome this problem, as it allows for the analysis of thicker samples, up to 1 µm in thickness. As such, it is an interesting imaging technique to analyse large DNA viruses, some of which measure 1 µm or more, and which is the focus of our research interest.