Perspectives on label-free microscopy of heterogeneous and dynamic biological systems

Significance

Advancements in label-free microscopy could provide real-time, non-invasive imaging with unique sources of contrast and automated standardized analysis to characterize heterogeneous and dynamic biological processes. These tools would overcome challenges with widely used methods that are destructive (e.g., histology, flow cytometry) or lack cellular resolution (e.g., plate-based assays, whole animal bioluminescence imaging).

Aim

This perspective aims to (1) justify the need for label-free microscopy to track heterogeneous cellular functions over time and space within unperturbed systems and (2) recommend improvements regarding instrumentation, image analysis, and image interpretation to address these needs.

Approach

Three key research areas (cancer research, autoimmune disease, and tissue and cell engineering) are considered to support the need for label-free microscopy to characterize heterogeneity and dynamics within biological systems. Based on the strengths (e.g., multiple sources of molecular contrast, non-invasive monitoring) and weaknesses (e.g., imaging depth, image interpretation) of several label-free microscopy modalities, improvements for future imaging systems are recommended.

Conclusion

Improvements in instrumentation including strategies that increase resolution and imaging speed, standardization and centralization of image analysis tools, and robust data validation and interpretation will expand the applications of label-free microscopy to study heterogeneous and dynamic biological systems.

Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI

PURPOSE

This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approach and a T2-based pore size estimation technique.

THEORY AND METHODS

A general diffusion-relaxation theoretical model for the spherical mean signal from water molecules within a distribution of cylinders with varying radii was introduced, encompassing the evaluated models as particular cases. Additionally, a new numerical approach was presented for estimating effective radii (i.e., MRI-visible mean radii) from the ground truth radii distributions, not reliant on previous theoretical approximations and adaptable to various acquisition sequences. The ground truth radii were obtained from scanning electron microscope images.

RESULTS

Both methods show a linear relationship between effective radii estimated from MRI data and ground-truth radii distributions, although some discrepancies were observed. The spherical mean power-law method overestimated fiber radii. Conversely, the T2-based method exhibited higher sensitivity to smaller fiber radii, but faced limitations in accurately estimating the radius in one particular phantom, possibly because of material-specific relaxation changes.

CONCLUSION

The study demonstrates the feasibility of both techniques to predict pore sizes of hollow microfibers. The T2-based technique, unlike the spherical mean power-law method, does not demand ultra-high diffusion gradients, but requires calibration with known radius distributions. This research contributes to the ongoing development and evaluation of neuroimaging techniques for fiber radius estimation, highlights the advantages and limitations of both methods, and provides datasets for reproducible research.

Taxonomic significance of morphological and elemental characteristics of achenes of Artemisia genus from Turkey

In the study, the achene macromorphological and micromorphological characters of the genus Artemisia distributed in Turkey have been researched with the target of knowing systematically important carpological structures for the examined species. Macro-morphological structures of the achenes including color, shape, dimension, and carpopodium diameter were studied with 100 achenes of 10 specimens per taxa with a Light Microscope. Micro-morphological features of the achenes containing surface ornamentation, anticlinal and periclinal cell walls, epidermal cells, and the presence of secondary structures were examined with a Scanning Electron Microscope. EDS analyses were performed with a SEM. EDS analyses were carried out by selecting the same spot on the sample surface at 80 sec under 30 μm aperture size, with 20 kV acceleration voltage, 8 mm operating distance, high current, and processing time conditions. The color, shape, and dimension of achene have macro-morphologically shown variations. The examined achenes are separated into four shapes; fusiform-oblong, oblong, oblong-ovate, and ovate. Oblong-ovate is the most common type. Achene dimensions range from 0.62 to 2.48 mm in length, and from 0.30 to 1.21 mm in width. Also, carpopodium diameter varies between 0.10 and 0.19 mm. Achene surfaces of the examined taxa are micro-morphologically assessed, and substantial differences are noticeably detected on behalf of the surface structures for instance, surface ornamentation, anticlinal and periclinal cell walls, epidermal cells, and the presence of secondary structures of the achenes. Surface ornamentation is separated into 10 types: irregularly sulcate, regularly sulcate, ruminate, sulcate-scalariform, rugose, favulariate, slightly sulcate, alveolate, tuberculate, and reticulate. A percentage comparison of the elements in the achene pericarp of the studied taxa has been performed with SEM-EDS. Accordingly, pericarps in taxa include C, Ca, K, Mg, Cl, Si, Na, and S elements. In the taxonomy of the genus Artemisia, the achene morphological characters are very significant characteristics that disclose inter-specific relations among the examined taxa. Moreover, a dichotomous key is offered for the identification of the studied taxa based on achene characters. RESEARCH HIGHLIGHTS: The achenes of Turkish Artemisia taxa have been examined in depth. The morphological characteristics of achenes of Turkish Artemisia taxa have been studied using SEM and LM for the first time and debated the systematic practice of these characters. The elemental content of the achene pericarp has been systematically evaluated for the first time.

3D Acoustic Wave Sparsely Activated Localization Microscopy With Phase Change Contrast Agents

OBJECTIVE

The aim of this study is to demonstrate 3-dimensional (3D) acoustic wave sparsely activated localization microscopy (AWSALM) of microvascular flow in vivo using phase change contrast agents (PCCAs).

MATERIALS AND METHODS

Three-dimensional AWSALM using acoustically activable PCCAs was evaluated on a crossed tube microflow phantom, the kidney of New Zealand White rabbits, and the brain of C57BL/6J mice through intact skull. A mixture of C 3 F 8 and C 4 F 10 low-boiling-point fluorocarbon gas was used to generate PCCAs with an appropriate activation pressure. A multiplexed 8-MHz matrix array connected to a 256-channel ultrasound research platform was used for transmitting activation and imaging ultrasound pulses and recording echoes. The in vitro and in vivo echo data were subsequently beamformed and processed using a set of customized algorithms for generating 3D super-resolution ultrasound images through localizing and tracking activated contrast agents.

RESULTS

With 3D AWSALM, the acoustic activation of PCCAs can be controlled both spatially and temporally, enabling contrast on demand and capable of revealing 3D microvascular connectivity. The spatial resolution of the 3D AWSALM images measured using Fourier shell correlation is 64 μm, presenting a 9-time improvement compared with the point spread function and 1.5 times compared with half the wavelength. Compared with the microbubble-based approach, more signals were localized in the microvasculature at similar concentrations while retaining sparsity and longer tracks in larger vessels. Transcranial imaging was demonstrated as a proof of principle of PCCA activation in the mouse brain with 3D AWSALM.

CONCLUSIONS

Three-dimensional AWSALM generates volumetric ultrasound super-resolution microvascular images in vivo with spatiotemporal selectivity and enhanced microvascular penetration.

Features in Backgrounds of Microscopy Images Introduce Biases in Machine Learning Analyses

Subvisible particles may be encountered throughout the processing of therapeutic protein formulations. Flow imaging microscopy (FIM) and backgrounded membrane imaging (BMI) are techniques commonly used to record digital images of these particles, which may be analyzed to provide particle size distributions, concentrations, and identities. Although both techniques record digital images of particles within a sample, FIM analyzes particles suspended in flowing liquids, whereas BMI records images of dry particles after collection by filtration onto a membrane. This study compared the performance of convolutional neural networks (CNNs) in classifying images of subvisible particles recorded by both imaging techniques. Initially, CNNs trained on BMI images appeared to provide higher classification accuracies than those trained on FIM images. However, attribution analyses showed that classification predictions from CNNs trained on BMI images relied on features contributed by the membrane background, whereas predictions from CNNs trained on FIM features were based largely on features of the particles. Segmenting images to minimize the contributions from image backgrounds reduced the apparent accuracy of CNNs trained on BMI images but caused minimal reduction in the accuracy of CNNs trained on FIM images. Thus, the seemingly superior classification accuracy of CNNs trained on BMI images compared to FIM images was an artifact caused by subtle features in the backgrounds of BMI images. Our findings emphasize the importance of examining machine learning algorithms for image analysis with attribution methods to ensure the robustness of trained models and to mitigate potential influence of artifacts within training data sets.

Comparison of endoscope-assisted and microscope-assisted type I tympanoplasty; a systematic review and meta-analysis

OBJECTIVES

To analyze and compare the available data about the outcomes of endoscopic and microscopic type I tympanoplasty.

DATA SOURCES

PubMed, Cochrane library Ovid, Scopus, Google scholar, and ClinicalTrials.

METHODS

We conducted a meta-analysis in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. We included comparative studies describing type I tympanoplasty, and comparing surgical outcomes of the endoscope with the microscope in terms of efficacy and safety.

RESULTS

Our systematic search yielded 22 studies meeting the inclusion criteria and eligible for analysis. The pooled graft uptake rates and audiological results of endoscopic and microscopic tympanoplasty demonstrated non-significant differences. In contrast, endoscopic type I tympanoplasty outperforms microscopic tympanoplasty regarding a highly significant decrease not only in pooled mean operative time but also in the pooled complications rate.

CONCLUSIONS

Based on our meta-analysis, the surgical outcomes of endoscope-assisted and microscope-assisted type I tympanoplasty in terms of postoperative hearing outcomes and the graft uptake rate were comparable. On the contrary, operative time and complications rate proved to be significantly reduced with endoscopy compared to microscopy. Hence, the endoscope is as efficient as the microscope in type I tympanoplasty but less invasive, fewer in complications and shorter in operative time.

Examining cut mark residue with SEM to identify metal tool use: An experimental study

In this manuscript, we explore the potential of studying metal residues in cut marks generated by copper and bronze knives. The method was developed in the forensic sciences for use with modern metals in order to identify microscopic particles of metal tools on bone surfaces. However, the study of residues in archaeological materials can be challenging due to the ways in which the bone remains may have been manipulated, both in the past and in more recent times. Using a scanning electron microscope (SEM), we detected microscopic fragments of bronze and copper knives along with contamination both inside and outside of the cut marks made by those knives. Copper and bronze residues were identified embedded in the bone inside the incisions and, in two cases, they left greenish stains caused by metal oxidation. In contrast, modern contamination of undetermined origin was found unattached to the bone and had a chemical composition not compatible with that of the knives. The amount of residue was influenced by the quantity of soft tissue between the bone and the knife during the butchering tasks. Bone cooking does not seem to influence the preservation of the residues. We anticipate that the approach used in this first exploratory study will emerge as a promising method for identifying the use of metal tools in archaeological bone remains.

Dermatopathologist accuracy in classifying angioinvasive fungal infections using virtual microscopy

BACKGROUND

Due to perceived difficulty in the categorization of angioinvasive fungal infections based on histopathology, variation exists in dermatopathology reporting.

METHODS

This study characterized the diagnosis of angioinvasive fungal infections by light microscopy at a single academic institution over an 11-year period. Subsequently, the accuracy of blinded reclassification by virtual microscopy was measured.

RESULTS

Seventy-six specimens with hematoxylin-eosin slides were obtained from 33 patients. The mean diagnostic accuracy of dermatopathologists in differentiating mucormycosis, hyalohyphomycosis, and phaeohyphomycosis based on blinded reclassification via virtual microscopy was 74%, with a range of 65%-91%.

CONCLUSIONS

While there was a range in diagnostic accuracy, the highest score of 91% and the identification of common sources of error suggest that histopathologic categorization of angioinvasive fungal infections can frequently be performed. However, accurate identification is not always possible given common pitfalls in diagnosis. In addition, standardized and clinically useful reporting should be considered.

leaves

The genus Achyranthes belong to the family Amaranthaceae which constitutes an important group of herbs and shrubs with immense medicinal value. The present research work was conducted to investigate the anticancer potential of Achyranthes aspera L. leaves by focusing on the antioxidant, aniproliferative and antimitotic activities of leaf extracts. Plant extraction was carried out by soxhelt method with different solvents. Phytochemical characterization of the plants extracts using chemical methods identified the presence of cardiac glycosides, saponins, coumarins, proteins, tannins, flavonoids and triterpenes. Alkaloid was present in methanolic and ethanolic extract. High performance liquid chromatography showed presence of different concentration of myricetin, quercetin and kaempferol in different extracts with the highest concentration of myricetin (84.53 μg/mL) in n-butanolic extract. The extracts were then tested for antioxidant activity using 2,2-diphenylpicrylhydrazyl (DPPH) radical scavenging assay by spectrophotometric method. In DPPH radical scavenging assay, antioxidant activity of A. aspera ranged between 79.78 ± 0.034% and 58.63 ± 0.069%. Highest antioxidant activity was observed for methanolic extract and lowest for acetone. Antimitotic activity was determined by using Allium cepa assay in which microscopic investigation was carried out to observe normal and abnormal phases of mitosis. In this assay, n-butanolic extract had highest antimitotic activity with minimum mitotic index at 2 mg/mL (57 ± 0.0351%). The plant extracts also caused chromosomal and mitotic aberrations which were clearly observed under 40× and 100× magnification of compound microscope. Antiproliferative activity was determined by using yeast cell model in which light microscope with hemocytometer was used for cell counting. In case of Antiproliferative activity, the ethyl acetate extract of A. aspera had highest antiproliferative activity with lowest cell viability (22.14 ± 0.076%) at highest extract concentration (2 mg/mL) while methanol extract of A. aspera had highest antiproliferative activity with lower cell viability (24.24 ± 0.057%) at lowest extract concentration (0.25 mg/mL). The results of the study indicated that the leaves extract of A. aspera have strong potential to be used as a source of anti-cancer agent. RESEARCH HIGHLIGHTS: Achyranthes aspera L. leaves have various phytochemicals which contribute to its medicinal properties Various extracts of the leaves of A. aspera L. possess antioxidant, antimitotic and antiproliferative potential The results of the study indicated that the leaves extract of A. aspera have strong potential to be used as a source of anti-cancer agent.

Evidence-based clinical practice guideline for management of urinary tract infection and primary vesicoureteric reflux

We present updated, evidence-based clinical practice guidelines from the Indian Society of Pediatric Nephrology (ISPN) for the management of urinary tract infection (UTI) and primary vesicoureteric reflux (VUR) in children. These guidelines conform to international standards; Institute of Medicine and AGREE checklists were used to ensure transparency, rigor, and thoroughness in the guideline development. In view of the robust methodology, these guidelines are applicable globally for the management of UTI and VUR. Seventeen recommendations and 18 clinical practice points have been formulated. Some of the key recommendations and practice points are as follows. Urine culture with > 104 colony forming units/mL is considered significant for the diagnosis of UTI in an infant if the clinical suspicion is strong. Urine leukocyte esterase and nitrite can be used as an alternative screening test to urine microscopy in a child with suspected UTI. Acute pyelonephritis can be treated with oral antibiotics in a non-toxic infant for 7-10 days. An acute-phase DMSA scan is not recommended in the evaluation of UTI. Micturating cystourethrography (MCU) is indicated in children with recurrent UTI, abnormal kidney ultrasound, and in patients below 2 years of age with non-E. coli UTI. Dimercaptosuccinic acid scan (DMSA scan) is indicated only in children with recurrent UTI and high-grade (3-5) VUR. Antibiotic prophylaxis is not indicated in children with a normal urinary tract after UTI. Prophylaxis is recommended to prevent UTI in children with bladder bowel dysfunction (BBD) and those with high-grade VUR. In children with VUR, prophylaxis should be stopped if the child is toilet trained, free of BBD, and has not had a UTI in the last 1 year. Surgical intervention in high-grade VUR can be considered for parental preference over antibiotic prophylaxis or in children developing recurrent breakthrough febrile UTIs on antibiotic prophylaxis.

High-Throughput Single-Cell, Single-Mitochondrial DNA Assay Using Hydrogel Droplet Microfluidics

There is growing interest in understanding the biological implications of single cell heterogeneity and heteroplasmy of mitochondrial DNA (mtDNA), but current methodologies for single-cell mtDNA analysis limit the scale of analysis to small cell populations. Although droplet microfluidics have increased the throughput of single-cell genomic, RNA, and protein analysis, their application to sub-cellular organelle analysis has remained a largely unsolved challenge. Here, we introduce an agarose-based droplet microfluidic approach for single-cell, single-mtDNA analysis, which allows simultaneous processing of hundreds of individual mtDNA molecules within >10,000 individual cells. Our microfluidic chip encapsulates individual cells in agarose beads, designed to have a sufficiently dense hydrogel network to retain mtDNA after lysis and provide a robust scaffold for subsequent multi-step processing and analysis. To mitigate the impact of the high viscosity of agarose required for mtDNA retention on the throughput of microfluidics, we developed a parallelized device, successfully achieving ~95 % mtDNA retention from single cells within our microbeads at >700,000 drops/minute. To demonstrate utility, we analyzed specific regions of the single-mtDNA using a multiplexed rolling circle amplification (RCA) assay. We demonstrated compatibility with both microscopy, for digital counting of individual RCA products, and flow cytometry for higher throughput analysis.

Classification and counting of cells in brightfield microscopy images: an application of convolutional neural networks

Microscopy is integral to medical research, facilitating the exploration of various biological questions, notably cell quantification. However, this process's time-consuming and error-prone nature, attributed to human intervention or automated methods usually applied to fluorescent images, presents challenges. In response, machine learning algorithms have been integrated into microscopy, automating tasks and constructing predictive models from vast datasets. These models adeptly learn representations for object detection, image segmentation, and target classification. An advantageous strategy involves utilizing unstained images, preserving cell integrity and enabling morphology-based classification-something hindered when fluorescent markers are used. The aim is to introduce a model proficient in classifying distinct cell lineages in digital contrast microscopy images. Additionally, the goal is to create a predictive model identifying lineage and determining optimal quantification of cell numbers. Employing a CNN machine learning algorithm, a classification model predicting cellular lineage achieved a remarkable accuracy of 93%, with ROC curve results nearing 1.0, showcasing robust performance. However, some lineages, namely SH-SY5Y (78%), HUH7_mayv (85%), and A549 (88%), exhibited slightly lower accuracies. These outcomes not only underscore the model's quality but also emphasize CNNs' potential in addressing the inherent complexities of microscopic images.

Near-infrared PAINT localization microscopy via chromophore replenishment of phytochrome-derived fluorescent tag

Bacterial phytochromes are attractive molecular templates for engineering fluorescent proteins (FPs) because their near-infrared (NIR) emission significantly extends the spectral coverage of GFP-like FPs. Existing phytochrome-based FPs covalently bind heme-derived tetrapyrrole chromophores and exhibit constitutive fluorescence. Here we introduce Rep-miRFP, an NIR imaging probe derived from bacterial phytochrome, which interacts non-covalently and reversibly with biliverdin chromophore. In Rep-miRFP, the photobleached non-covalent adduct can be replenished with fresh biliverdin, restoring fluorescence. By exploiting this chromophore renewal capability, we demonstrate NIR PAINT nanoscopy in mammalian cells using Rep-miRFP.

Tools and methods for high-throughput single-cell imaging with the mother machine

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.

Clinical Characteristics and Pathogen Spectrum of Male Genital Fungal Infections in Nanchang Area, South China

The cutaneous fungal infections in male genitalia are relatively rare, and often present with various atypical clinical symptoms. It was mainly reported in a small number of case reports, while data with large number of patients were rarely reported. In this study, we reported 79 male patients with cutaneous fungal infections on scrotum or penis. The fungal infections were confirmed by microscopic examination directly and fungus culture. Clinical characteristics and predisposing factors were also collected. Of these 79 patients, 72 has lesions on scrotum, 5 on penis and 2 on both scrotum and penis. Trichophyton (T.) rubrum is the most common pathogen, found in 50 (67.6%) patients, which presented diverse clinical manifestation such as majorly erythematous, dry diffused scaly lesions without a clear border, slightly powdery and scutular scalings. Candida (C.) albicans is the secondly common pathogen, found in 21 (28.4%) patients, which also presented diverse lesions such as erythematous with dry whitish scaly lesions and erythematous erosion. The predisposing factors mainly included concomitant fungal infections on sites other than genitalia, especially inguinal region (tinea cruris), application of corticosteroid and high moisture. In conclusion, cutaneous fungal infections in male genitalia could be caused by different fungi, showed atypical or mild clinical appearances in most cases and might be a fungus reservoir, emphasizing the necessity to timely perform the fungi examinations and corresponding therapy.

Functional Plasmonic Microscope: Characterizing the Metabolic Activity of Single Cells via Sub-nm Membrane Fluctuations

Metabolic abnormalities are at the center of many diseases, and the capability to film and quantify the metabolic activities of a single cell is important for understanding the heterogeneities in these abnormalities. In this paper, a functional plasmonic microscope (FPM) is used to image and measure metabolic activities without fluorescent labels at a single-cell level. The FPM can accurately image and quantify the subnanometer membrane fluctuations with a spatial resolution of 0.5 μm in real time. These active cell membrane fluctuations are caused by metabolic activities across the cell membrane. A three-dimensional (3D) morphology of the bottom cell membrane was imaged and reconstructed with FPM to illustrate the capability of the microscope for cell membrane characterization. Then, the subnanometer cell membrane fluctuations of single cells were imaged and quantified with the FPM using HeLa cells. Cell metabolic heterogeneity is analyzed based on membrane fluctuations of each individual cell that is exposed to similar environmental conditions. In addition, we demonstrated that the FPM could be used to evaluate the therapeutic responses of metabolic inhibitors (glycolysis pathway inhibitor STF 31) on a single-cell level. The result showed that the metabolic activities significantly decrease over time, but the nature of this response varies, depicting cell heterogeneity. A low-concentration dose showed a reduced fluctuation frequency with consistent fluctuation amplitudes, while the high-concentration dose showcased a decreasing trend in both cases. These results have demonstrated the capabilities of the functional plasmonic microscope to measure and quantify metabolic activities for drug discovery.

Label-free quantification of gold nanoparticles at the single-cell level using a multi-column convolutional neural network (MC-CNN)

Gold nanoparticles (AuNPs) are extensively used in cellular imaging, single-particle tracking, disease diagnosis, studying membrane protein interaction, and drug delivery. Understanding the dynamics of AuNP uptake in live cells is crucial for optimizing their efficacy and safety. Traditional manual methods for quantifying AuNP uptake are time-consuming and subjective, limiting their scalability and accuracy. The available fluorescence-based techniques are limited to photobleaching and photoblinking. Optical microscopy techniques are limited by diffraction limits. Electron microscopy-based imaging techniques are destructive and unsuitable for live cell imaging. Furthermore, the resulting images may contain hundreds of particles with varied intensities, blurring, and substantial occlusion, making it difficult to manually quantify AuNP uptake. To overcome this issue and measure AuNP uptake by live cells, we annotated a dataset of dark-field images of 50 nanometer-radius AuNPs at different incubation durations. Then, to count the number of particles present in a cell, we created a customized multi-column convolutional neural network (MC-CNN). The customized MC-CNN outperformed typical particle counting architectures when compared to spectroscopy-based counting. This will allow researchers to gain a better understanding of AuNP behavior and interactions with cells, paving the way for advancements in nanomedicine, drug delivery, and biomedical research. The code for this paper is available at the following link: https://github.com/Namerlight/LabelFree_AuNP_Quantification.

Multi-scale fractal Fourier Ptychographic microscopy to assess the dose-dependent impact of copper pollution on living diatoms

Accumulation of bioavailable heavy metals in aquatic environment poses a serious threat to marine communities and human health due to possible trophic transfers through the food chain of toxic, non-degradable, exogenous pollutants. Copper (Cu) is one of the most spread heavy metals in water, and can severely affect primary producers at high doses. Here we show a novel imaging test to assay the dose-dependent effects of Cu on live microalgae identifying stress conditions when they are still capable of sustaining a positive growth. The method relies on Fourier Ptychographic Microscopy (FPM), capable to image large field of view in label-free phase-contrast mode attaining submicron lateral resolution. We uniquely combine FPM with a new multi-scale analysis method based on fractal geometry. The system is able to provide ensemble measurements of thousands of diatoms in the liquid sample simultaneously, while ensuring at same time single-cell imaging and analysis for each diatom. Through new image descriptors, we demonstrate that fractal analysis is suitable for handling the complexity and informative power of such multiscale FPM modality. We successfully tested this new approach by measuring how different concentrations of Cu impact on Skeletonema pseudocostatum diatom populations isolated from the Sarno River mouth.

Towards developing a matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) compatible tissue expansion protocol

Mass spectrometry imaging (MSI) visualizes spatial distribution of molecules in a biological tissue. However, compared with traditional microscopy-based imaging, conventional MSI is limited to its spatial resolution, resulting in difficulties in identifying detailed tissue morphological characters, such as lesion boundary or nanoscale structures. On the other hand, expansion microscopy, a tissue expansion method widely used in optical imaging to improve morphological details, has great potential to solve insufficient spatial resolution in mass spectrometry imaging (MSI). However, expansion microscopy was not originally designed for MSI, resulting in problems while combining expansion microscopy and MSI such as expanded sample fragility, vacuum stability and molecule loss during sample preparation. In this research we developed a MALDI MSI compatible expansion protocol by adjusting sample preparation methods during tissue expansion, successfully combining expansion microscopy with MSI. After tissue expansion the expanded sample can be readily applied to MALDI MSI sample preparation and further data acquisition. The MALDI MSI compatible expansion protocol has great potential to be widely applied in MALDI MSI sample preparation to facilitate improvement of MSI spatial resolution.

Supramolecular Hydrogels and Water Channels of Differing Diameters from Dipeptide Isomers

Dipeptides stereoisomers and regioisomers composed of norleucine (Nle) and phenylalanine (Phe) self-assemble into hydrogels under physiological conditions that are suitable for cell culture. The supramolecular behavior, however, differs as the packing modes comprise amphipathic layers or water channels, whose diameter is defined by either four or six dipeptide molecules. A variety of spectroscopy, microscopy, and synchrotron-radiation-based techniques unveil fine details of intermolecular interactions that pinpoint the relationship between the chemical structure and ability to form supramolecular architectures that define soft biomaterials.

Quantitative and qualitative analysis of cell culture media powders for mammalian cells by Raman microscopy

Cell culture media are essential for large-scale recombinant protein production using mammalian cell cultures. The composition and quality of media significantly impact cell growth and product formation. Analyzing media poses challenges due to complex compositions and undisclosed exact compositions. Traditional methods like NMR and chromatography offer sensitivity but require time-consuming sample preparation and lack spatial information. Raman chemical mapping characterizes solids, but its use in cell culture media analysis is limited so far. We present a chemometric evaluation for Raman maps to qualify and quantify media components, evaluate powder homogeneity, and perform lot-to-lot comparisons. Three lots of a marketed cell culture media powder were measured with Raman mapping technique. Chemometrics techniques have outlined a strategy to extract information from complex data. First, a spectral library has been structured. In addition to the 23 spectra for presumed ingredients, we obtained another 9 pure components with Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS). Then the Spectral Angle Mapper-Orthogonal Projection (SAM-OP) algorithm revealed whether references actually occur in the mapped media powders. Finally, a quantification was provided by Classical Least Squares (CLS) modelling. Quantities of 18 significant amino acids mostly correlated with the reference method. The proposed method can be generally applied even for such complicated samples. Leveraging Raman mapping and innovative chemometric methods enhance recombinant protein production by improving the understanding of the spatial distribution and composition of cell culture media in mammalian cell cultivations.

DeepDOF-SE: affordable deep-learning microscopy platform for slide-free histology

Histopathology plays a critical role in the diagnosis and surgical management of cancer. However, access to histopathology services, especially frozen section pathology during surgery, is limited in resource-constrained settings because preparing slides from resected tissue is time-consuming, labor-intensive, and requires expensive infrastructure. Here, we report a deep-learning-enabled microscope, named DeepDOF-SE, to rapidly scan intact tissue at cellular resolution without the need for physical sectioning. Three key features jointly make DeepDOF-SE practical. First, tissue specimens are stained directly with inexpensive vital fluorescent dyes and optically sectioned with ultra-violet excitation that localizes fluorescent emission to a thin surface layer. Second, a deep-learning algorithm extends the depth-of-field, allowing rapid acquisition of in-focus images from large areas of tissue even when the tissue surface is highly irregular. Finally, a semi-supervised generative adversarial network virtually stains DeepDOF-SE fluorescence images with hematoxylin-and-eosin appearance, facilitating image interpretation by pathologists without significant additional training. We developed the DeepDOF-SE platform using a data-driven approach and validated its performance by imaging surgical resections of suspected oral tumors. Our results show that DeepDOF-SE provides histological information of diagnostic importance, offering a rapid and affordable slide-free histology platform for intraoperative tumor margin assessment and in low-resource settings.

Microscopy detection and molecular characterisation of Giardia duodenalis infection in outpatients seeking medical care in Egypt

Introduction

Giardiosis remains one of the most prevalent enteric parasitic infections globally. Earlier molecular-based studies conducted in Egypt have primarily focused on paediatric clinical populations and most were based on single genotyping markers. As a result, there is limited information on the frequency and genetic diversity of G. duodenalis infections in individuals of all age groups.

Methods

Individual stool samples (n = 460) from outpatients seeking medical care were collected during January-December 2021 in Kafr El-Sheikh governorate, northern Egypt. Initial screening for the presence of G. duodenalis was conducted by coprological examination. Microscopy-positive samples were further confirmed by real-time PCR. A multilocus sequence typing approach targeted amplification of the glutamate dehydrogenase (gdh), beta-giardin (bg), and triose phosphate isomerase (tpi) genes was used for genotyping purposes. A standardised epidemiological questionnaire was used to gather basic sociodemographic and clinical features of the recruited patients.

Results

Giardia duodenalis cysts were observed in 5.4% (25/460, 95% CI: 3.6-7.9) of the stool samples examined by conventional microscopy. The infection was more frequent in children under the age of 10 years and in individuals presenting with diarrhoea but without reaching statistical significance. Stool samples collected during the winter period were more likely to harbour G. duodenalis. All 25 microscopy-positive samples were confirmed by real-time PCR, but genotyping data was only available for 56.0% (14/25) of the isolates. Sequence analyses revealed the presence of assemblages A (78.6%, 11/14) and B (21.4%, 3/14). All assemblage A isolates were identified as sub-assemblage AII, whereas the three assemblage B sequences belonged to the sub-assemblage BIII. Patients with giardiosis presenting with diarrhoea were more frequently infected by the assemblage A of the parasite.

Conclusion

This is one of the largest epidemiological studies evaluating G. duodenalis infection in individuals of all age groups in Egypt. Our molecular data suggest that G. duodenalis infections in the surveyed population are primarily of anthropic origin. However, because assemblages A and B are zoonotic, some of the infections identified can have an animal origin. Additional investigations targeting animal (domestic and free-living) and environmental (water) samples are warranted to better understand the epidemiology of giardiosis in Egypt.

A hybrid topological quantum state in an elemental solid

Topology1-3 and interactions are foundational concepts in the modern understanding of quantum matter. Their nexus yields three important research directions: (1) the competition between distinct interactions, as in several intertwined phases, (2) the interplay between interactions and topology that drives the phenomena in twisted layered materials and topological magnets, and (3) the coalescence of several topological orders to generate distinct novel phases. The first two examples have grown into major areas of research, although the last example remains mostly unexplored, mainly because of the lack of a material platform for experimental studies. Here, using tunnelling microscopy, photoemission spectroscopy and a theoretical analysis, we unveil a 'hybrid' topological phase of matter in the simple elemental-solid arsenic. Through a unique bulk-surface-edge correspondence, we uncover that arsenic features a conjoined strong and higher-order topology that stabilizes a hybrid topological phase. Although momentum-space spectroscopy measurements show signs of topological surface states, real-space microscopy measurements unravel a unique geometry of topologically induced step-edge conduction channels revealed on various natural nanostructures on the surface. Using theoretical models, we show that the existence of gapless step-edge states in arsenic relies on the simultaneous presence of both a non-trivial strong Z2 invariant and a non-trivial higher-order topological invariant, which provide experimental evidence for hybrid topology. Our study highlights pathways for exploring the interplay of different band topologies and harnessing the associated topological conduction channels in engineered quantum or nano-devices.

Expansion microscopy of apicomplexan parasites

Apicomplexan parasites comprise significant pathogens of humans, livestock and wildlife, but also represent a diverse group of eukaryotes with interesting and unique cell biology. The study of cell biology in apicomplexan parasites is complicated by their small size, and historically this has required the application of cutting-edge microscopy techniques to investigate fundamental processes like mitosis or cell division in these organisms. Recently, a technique called expansion microscopy has been developed, which rather than increasing instrument resolution like most imaging modalities, physically expands a biological sample. In only a few years since its development, a derivative of expansion microscopy known as ultrastructure-expansion microscopy (U-ExM) has been widely adopted and proven extremely useful for studying cell biology of Apicomplexa. Here, we review the insights into apicomplexan cell biology that have been enabled through the use of U-ExM, with a specific focus on Plasmodium, Toxoplasma and Cryptosporidium. Further, we summarize emerging expansion microscopy modifications and modalities and forecast how these may influence the field of parasite cell biology in future.

Investigating the effect of volatility on the hygroscopicities of acetate nanoparticle aerosols by surface plasmon resonance microscopy

Under high relative humidity (RH) conditions, the release of volatile components (such as acetate) has a significant impact on the aerosol hygroscopicity. In this work, one surface plasmon resonance microscopy (SPRM) measurement system was introduced to determine the hygroscopic growth factors (GFs) of three acetate aerosols separately or mixed with glucose at different RHs. For Ca(CH3COO)2 or Mg(CH3COO)2 aerosols, the hygroscopic growth trend of each time was lower than that of the previous time in three cyclic humidification from 70% RH to 90% RH, which may be due to the volatility of acetic acid leading to the formation of insoluble hydroxide (Ca(OH)2 or Mg(OH)2) under high RH conditions. Then the third calculated GF (using the Zdanovskii-Stokes-Robinson method) for Ca(CH3COO)2 or Mg(CH3COO)2 in bicomponent aerosols with 1:1 mass ratio were 3.20% or 5.33% lower than that of the first calculated GF at 90% RH. The calculated results also showed that the hygroscopicity change of bicomponent aerosol was negatively correlated with glucose content, especially when the mass ratio of Mg(CH3COO)2 to glucose was 1:2, the GF at 90% RH only decreased by 4.67% after three cyclic humidification. Inductively coupled plasma atomic emission spectrum (ICP-AES) based measurements also indicated that the changes of Mg2+concentration in bicomponent was lower than that of the single-component. The results of this study reveal thatduring the efflorescence transitions of atmospheric nanoparticles, the organic acids diffusion rate may be inhibited by the coating effect of neutral organic components, and the particles aging cycle will be prolonged.

Dual-channel neural network for instance segmentation of synapse

Detection and segmentation of neural synapses in electron microscopy images are the committed steps for analyzing neural ultrastructure. To date, manual annotation of the structure in synapses has been the primary method, which is time-consuming and restricts the throughput of data acquisition. Recent studies have utilized a series of deformations based on a segmentation model for the detection and segmentation of transmission electron microscope images. However, the analysis of synaptic segmentation and statistics still lacks sufficient automation and high-throughput. Therefore, we developed a dual-channel neural network instance segmentation model with weighted top-down and multi-scale bottom-up schemes, which aid in accurately detecting and segmenting synaptic vesicles and their active zones within presynaptic membranes in complex environments. In addition, we proposed a masked self-supervised pre-training model based on the latest convolutional architecture to improve performance in downstream segmentation tasks. By comparing our model to other state-of-the-art methods, we determined its viability and accuracy. The applicability of our model is thoroughly demonstrated by distinct application scenarios for neurobiological research. These findings indicate that the dual-channel neural network could facilitate the analysis of synaptic structures for the advancement of biomedical research and electron microscope reconstruction techniques.

Efficient Supervised Pretraining of Swin-Transformer for Virtual Staining of Microscopy Images

Fluorescence staining is an important technique in life science for labeling cellular constituents. However, it also suffers from being time-consuming, having difficulty in simultaneous labeling, etc. Thus, virtual staining, which does not rely on chemical labeling, has been introduced. Recently, deep learning models such as transformers have been applied to virtual staining tasks. However, their performance relies on large-scale pretraining, hindering their development in the field. To reduce the reliance on large amounts of computation and data, we construct a Swin-transformer model and propose an efficient supervised pretraining method based on the masked autoencoder (MAE). Specifically, we adopt downsampling and grid sampling to mask 75% of pixels and reduce the number of tokens. The pretraining time of our method is only 1/16 compared with the original MAE. We also design a supervised proxy task to predict stained images with multiple styles instead of masked pixels. Additionally, most virtual staining approaches are based on private datasets and evaluated by different metrics, making a fair comparison difficult. Therefore, we develop a standard benchmark based on three public datasets and build a baseline for the convenience of future researchers. We conduct extensive experiments on three benchmark datasets, and the experimental results show the proposed method achieves the best performance both quantitatively and qualitatively. In addition, ablation studies are conducted, and experimental results illustrate the effectiveness of the proposed pretraining method. The benchmark and code are available at https://github.com/birkhoffkiki/CAS-Transformer.

The InSciEdRS View: A User-Friendly and Accessible Microscope with Easy-to-Follow Companion Curricula

Microscopes are essential for research and education in science. Unlike computers and online learning tools, however, microscopes are not currently a fixed element in K-12 classrooms, due to steep cost, needless complexity, and often requiring a prohibitive level of staff training to effectively deploy. In a collaboration with Area 10 Labs, Integrated Science Education Outreach (InSciEd Out) developed a state-of-the-art alternative microscope, the InSciEdRS View, to reduce the financial barrier, prohibitive per-student cost, unnecessary complexity, and extensive staff training. Utilizing a 1080p camera and a lunchbox-style case, this Wi-Fi- and USB-connectable microscope comes with all necessary components for visualization of microscopic specimens (10 × -50 × magnification). While built to handle the rigors of classroom use, its imaging capability and battery-operation can make it flexible for a laboratory or fieldwork as well. We further highlight here K-12 curricula that we have developed using larval zebrafish to enable teachers, science outreach leaders, and parents to support active hands-on science observations. The InSciEdRS View microscope and the InSciEd Out curricula are readily scalable, translatable, and accessible for traditional and neurodiverse students and integrating these in various settings can be an efficient way to achieve better outcomes in science education.

Recent advances in label-free imaging and quantification techniques for the study of lipid droplets in cells

Lipid droplets (LDs), once considered mere storage depots for lipids, have gained recognition for their intricate roles in cellular processes, including metabolism, membrane trafficking, and disease states like obesity and cancer. This review explores label-free imaging techniques' applications in LD research. We discuss holotomography and vibrational spectroscopic microscopy, emphasizing their potential for studying LDs without molecular labels, and we highlight the growing integration of artificial intelligence. Clinical applications in disease diagnosis and therapy are also considered.

Toward a comprehensive view of gene architecture during transcription

The activation of genes within the nucleus of eukaryotic cells is a tightly regulated process, orchestrated by a complex interplay of various physical properties and interacting factors. Studying the multitude of components and features that collectively contribute to gene activation has proven challenging due to the complexities of simultaneously visualizing the dynamic and transiently interacting elements that coalesce within the small space occupied by each individual gene. However, various labeling and imaging advances are now starting to overcome this challenge, enabling visualization of gene activation at different lengths and timescales. In this review, we aim to highlight these microscopy-based advances and suggest how they can be combined to provide a comprehensive view of the mechanisms regulating gene activation.

ChatGPT's innovative application in blood morphology recognition

BACKGROUND

Recently, the rapid advancement in generative artificial intelligence (AI) technology, such as ChatGPT-4, has sparked discussions, particularly in image recognition. Accurate results are critical for hematological diagnosis, particularly for blood morphology identification. Despite advanced hematology analyzers, reliance on professional hematopathologists for manual identification remains in cases of abnormal or rare conditions, a process prone to human subjectivity and potential errors. Consequently, this study aimed to investigate the potential of ChatGPT-4 to assist with blood morphology identification.

METHODS

We conducted a retrospective study using blood images obtained from the American Society of Hematology (ASH). These images comprised a range of normal and abnormal morphologies. Each sample was analyzed by expert technicians (control group) and classified using ChatGPT-4 (test group).

RESULTS

Preliminary results showed that ChatGPT-4 could identify normal blood cells with an accuracy of 88%, exceeding the accuracy of identifying abnormal blood cells at a rate of 54%. Regarding identifying abnormal cells, the accuracy of ChatGPT-4 was slightly higher than that of the manual method, which was 49.5%.

CONCLUSION

This study shows that although generative AI shows the potential for blood type identification, it has not yet reached the point where it can replace the professional judgment of medical staff. The results showed that ChatGPT-4 is excellent for identifying red blood cell morphology, particularly inclusion bodies. It can be used as an auxiliary tool for clinical diagnosis. However, the overall recognition accuracy must be further improved. Our study produced innovative results in this field, establishing a foundation for future studies and highlighting the potential of generative AI in aiding blood morphology recognition. Future research should focus on enhancing the effectiveness of AI to improve overall standards of medical care.

Rapid and robust bacterial species identification using hyperspectral microscopy and gram staining techniques

Gram staining can classify bacterial species into two large groups based on cell wall differences. Our study revealed that within the same gram group (gram-positive or gram-negative), subtle cell wall variations can alter staining outcomes, with the peptidoglycan layer and lipid content significantly influencing this effect. Thus, bacteria within the same group can also be differentiated by their spectra. Using hyperspectral microscopy, we identified six species of intestinal bacteria with 98.1% accuracy. Our study also demonstrated that selecting the right spectral band and background calibration can enhance the model's robustness and facilitate precise identification of varying sample batches. This method is suitable for analyzing bacterial community pathologies.

A study of collagen refractility in dermatofibroma and dermatofibrosarcoma protuberans using diffractive microscopy

BACKGROUND

Diffractive microscopy creates contrast within samples that are otherwise uniform under bright light. This technique can highlight subtle differences in refractive indices within birefringent samples containing varying amounts of mature collagen. Dermatofibroma (DF) and dermatofibrosarcoma protuberans (DFSP) possess differences in their mature collagen content and, therefore, may be distinguishable using diffractive microscopy.

METHODS

Two hundred forty-two DF and 85 DFSP hematoxylin-eosin (H&E)-stained specimens were analyzed using diffractive microscopy. Data regarding the distribution pattern and strength of refractility was recorded.

RESULTS

DFSP was more frequently found to be focally, weakly, or non-refractile (82.9%; n = 68) under diffractive microscopy, while DF more often showed diffusely bright refractility (52.9%; n = 128). DFSP samples with diffuse refractility in portions of the lesion (17.1%; n = 14) also exhibited a unique checkerboard pattern distinct from that which was seen in DF samples.

CONCLUSIONS

The absence of diffuse refractility was more closely associated with DFSP, as was the presence of a unique checkerboard diffraction pattern. Despite high sensitivity (Sn = 82.9%), absent refractility was not a specific test (Sp = 52.9%), with 47.1% (n = 114) of DF samples sharing this feature. The distinction between DF and DFSP is often diagnosed using H&E alone. In difficult cases, examination of collagen under diffractive microscopy may be useful in distinguishing DFSP from DF and provide an alternative cost-effective tool to immunohistochemical staining.

Bright and stable monomeric green fluorescent protein derived from StayGold

The high brightness and photostability of the green fluorescent protein StayGold make it a particularly attractive probe for long-term live-cell imaging; however, its dimeric nature precludes its application as a fluorescent tag for some proteins. Here, we report the development and crystal structures of a monomeric variant of StayGold, named mBaoJin, which preserves the beneficial properties of its precursor, while serving as a tag for structural proteins and membranes. Systematic benchmarking of mBaoJin against popular green fluorescent proteins and other recently introduced monomeric and pseudomonomeric derivatives of StayGold established mBaoJin as a bright and photostable fluorescent protein, exhibiting rapid maturation and high pH/chemical stability. mBaoJin was also demonstrated for super-resolution, long-term live-cell imaging and expansion microscopy. We further showed the applicability of mBaoJin for neuronal labeling in model organisms, including Caenorhabditis elegans and mice.

Evaluation of MV140 in preventing recurrent urinary tract infections: a multicentre double-blind randomized controlled trial protocol

OBJECTIVES

To determine, firstly, whether MV140 reduces rates of recurrent urinary tract infections (rUTIs) in patients older than 65 years, measured as the number of urinary tract infections (UTIs) detected over 12 months following the completion of a 3-month treatment course and, additionally, to assess the number of re-admissions to the emergency department, the rate of antibiotic use for UTIs, the safety profile of MV140, and quality of life.

MATERIALS AND METHODS

This is a multicentre, double-blind, randomized controlled trial with two arms. Patients will be randomized and allocated to receive either a 3-month course of MV140 or placebo (two sublingual sprays daily). Participants will have 3-monthly consultations with the investigator for 12 months to assess differences in rates of rUTIs between the two groups. Study candidates will be identified and recruited from inpatient and outpatient clinics across Sydney via referral to the investigation team. After obtaining consent, participants will undergo initial study consultations including urine microscopy and culture, uroflowmetry, and bladder scan to assess postvoid residual urine volume. Participants will be randomized and provided with a unique trial number. Electronic medical records will be reviewed to collect relevant information. Participants will be provided with a study diary to record relevant data.

RESULTS

Follow-up consultations will be conducted every 3 months for a 12-month duration, during which the study diary will be reviewed. These follow-up consultations will primarily occur via telephone review, however, there will be flexibility for in-person reviews for participants who find telephone consultation prohibitively difficult.

CONCLUSION

This is a multicentre, double-blinded, randomised control trial, the first in Australia to assess the safety and efficacy of MV140 Uromune vaccine in prevention of recurrent UTIs. Results have been promissing in the global literatures.

Thermoplastic clear dental aligners under cyclic compression loading: A mechanical performance analysis using acoustic emission technique

The objective of this work is to analyse the performance of clear aligners made of thermoplastic materials. Within this framework, the damage evolution stages and damage states of the aligners at different cycles of the compressive loading are evaluated using the Acoustic Emission (AE) technique. Three different clear aligner systems were prepared: thermoformed PET-g (polyethylene terephthalate glycol) and PU (polyurethane), and additively manufactured PU. Cyclic compression tests are performed to simulate 22500 swallows. The mechanical results show that the energy absorbed by the thermoformed PET-g aligner remains stable around 4 Nmm throughout the test. Although the PU-based aligners show a higher energy absorption of about 7 Nmm during the initial phase of the cyclic loading, this gradually decreases after 12500 cycles. The time-domain based, and frequency-based parameters of the stress wave acoustic signals generated by the aligners under compression loading are used to identify the damage evolution stages. The machine learning-based AE results reveal the initiation and termination of the different damage states in the aligners and the frequency-based results distinguish the different damage sources. Finally, the microscopy results validated the damage occurrences in the aligners identified by the AE results. The mechanical test results indicate that the thermoformed PET-g has the potential to match the performance and requirements of the dentistry of the popular Invisalign (additively manufactured PU). The AE results have the potential to identify at which cycles the aligners may start losing their functionality.

Exoscope Use in Spine Surgery: A Systematic Review of Applications, Benefits, and Limitations

BACKGROUND

Exoscopes were recently developed as an alternative to the operative microscope (OM) and endoscope for intraoperative visualization during neurosurgery. Prior reviews studying mixed cranial and spinal surgical cohorts reported advantages with exoscope use, including improved ergonomics and teaching. In recent years, there has been an increase in exoscope research, with no updated systematic review focused exclusively on the benefits and limitations of exoscope use in spine surgery. Thus, we sought to systematically synthesize the literature related to exoscope-assisted spine surgery.

METHODS

A literature search was conducted using the PubMed, Embase, Scopus, Cochrane, and Web of Science databases to identify relevant studies reported between 2010 and September 2023. Data, such as the exoscope model used, procedure types performed, and user observations, were then collected.

RESULTS

A total of 31 studies met our inclusion criteria, including 481 patients with spine pathologies who underwent a surgical procedure using 1 of 9 exoscope models. The lumbar region was the most frequently operated area (n = 234; 48.6%), and discectomies comprised the most overall procedures (n = 273; 56.8%). All patients benefited clinically. The reported advantages of exoscopes compared with OMs or endoscopes were improved focal distance, surgeon posture, trainee education, compactness, and assistant participation. Other aspects such as stereopsis, illumination, and cost had various observations.

CONCLUSIONS

Exoscopes have advantages compared with OMs or endoscopes during spine surgery. The user learning curve is minimal, and no negative patient outcomes have been reported. However, some aspects of exoscope use necessitate longer term prospective research before exoscopes can be considered a standard tool in the armamentarium of intraoperative visualization strategies.

An approach of separating the overlapped cells or nuclei based on the outer Canny edges and morphological erosion

In biomedicine, the automatic processing of medical microscope images plays a key role in the subsequent analysis and diagnosis. Cell or nucleus segmentation is one of the most challenging tasks for microscope image processing. Due to the frequently occurred overlapping, few segmentation methods can achieve satisfactory segmentation accuracy yet. In this paper, we propose an approach to separate the overlapped cells or nuclei based on the outer Canny edges and morphological erosion. The threshold selection is first used to segment the foreground and background of cell or nucleus images. For each binary connected domain in the segmentation image, an intersection based edge selection method is proposed to choose the outer Canny edges of the overlapped cells or nuclei. The outer Canny edges are used to generate a binary cell or nucleus image that is then used to compute the cell or nucleus seeds by the proposed morphological erosion method. The nuclei of the Human U2OS cells, the mouse NIH3T3 cells and the synthetic cells are used for evaluating our proposed approach. The quantitative quantification accuracy is computed by the Dice score and 95.53% is achieved by the proposed approach. Both the quantitative and the qualitative comparisons show that the accuracy of the proposed approach is better than those of the area constrained morphological erosion (ACME) method, the iterative erosion (IE) method, the morphology and watershed (MW) method, the Generalized Laplacian of Gaussian filters (GLGF) method and ellipse fitting (EF) method in separating the cells or nuclei in three publicly available datasets.

Characterization of the collagen network of human cheek skin using ultrasonic microscopy

Dermal collagen is the most abundant component of human skin and has a network structure that regulates the mechanical properties of the skin. Therefore, non-invasive characterization of the collagen network would be beneficial for the evaluation of skin conditions. The microscopic substructures of the network, which are individual bundles and fibers, have been optically investigated. However, the macroscopic structure of the collagen network has not been assessed. To evaluate the dermal collagen network, we developed two new indicators, volume filling factor (VFF) and collagen fiber texture (CFT), to analyze three-dimensional echo intensity maps of high-frequency ultrasonic microscopy. By identifying the difference in the elastic modulus components of the dermal layer of facial skin, the density and texture of the collagen network were characterized using VFF and CFT, respectively. These new indicators revealed that the density decreased and the texture became fine with facial age. This study demonstrates that ultrasonic microscopy is useful for investigating skin conditions, paving the way for diagnostic applications in dermatology and aesthetic medicine.

Efficacy of endoscopic ultrasound-guided tissue acquisition using stereo-microscopic on-site evaluation for possible comprehensive genome profile in patients with advanced pancreatic cancer

BACKGROUND AND AIM

Stereomicroscopic on-site evaluation (SOSE) is a rapid evaluation method for endoscopic ultrasound-guided tissue acquisition (EUS-TA) with a high diagnostic sensitivity when the stereomicroscopically visible white core (SVWC) cut-off value (≥ 11 mm) is met. We prospectively examined the association between SVWCs and the adequacy of tissue specimens, assuming subsequent comprehensive genome profiling (CGP).

METHODS

This study included 66 consecutive patients with suspected unresectable pancreatic cancer who underwent EUS-TA. The primary endpoint was the frequency of combined samples with ≥ 20% tumor cell content that met over twice the SVWC (T-SVWC) cut-off value, achieved through multiple punctures. The secondary endpoints were the number of punctures, the percentage of SVWC cut-off values, adverse events, the positive diagnosis rate, and the tissue section area.

RESULTS

The median number of EUS-TA punctures for suspected unresectable pancreatic cancer was 3 (range, 3-4); SVWC and T-SVWC cut-off values were obtained in 171/206 specimens and 65/66 patients, respectively. There were no EUS-TA-related adverse events. The positive diagnosis rate of EUS-TA was 95.5%. Among the 63 patients meeting the T-SVWC cut-off value in pathological diagnoses, the median tumor cell content was 40% (range, 5-80%), with 57 patients having tumor cell content ≥ 20%. The median tissue section area was 15 (range, 3-40) mm2.

CONCLUSIONS

When performing EUS-TA for unresectable pancreatic cancer with the intention of subsequent CGP, obtaining a high tumor cell content (≥ 20%) by assessing the T-SVWC cut-off value via SOSE may serve as a novel indicator for on-site estimation of CGP suitability for EUS-TA specimens.

Alternative Strategies to Provide Actionable Results When a Supply of Urinalysis Strips Is Unavailable

CONTEXT.—

Urinalysis instrument-specific dip strips offer physicians qualitative results for actionable analytes (protein, glucose, leukocyte esterase, nitrates, hemoglobin, and ketones).

OBJECTIVE.—

To explain a strategy implemented to support clinical decision-making by providing urine quantification of protein, glucose, white blood cells (WBCs), and red blood cells because of urine strip shortages.

DESIGN.—

During shortages, we implemented an automated algorithm that triggered sending urine samples to the automation line for quantification of protein and glucose and ensured that urine microscopy was performed to obtain WBC and red blood cell counts. The algorithm printed 2 labels so nursing staff would collect 2 specimens. We monitored the turnaround time from the specimen being received in the laboratory to result verification, ensured that the culture reflex order was triggered, and tracked complaints by physicians regarding not having usual urinalysis results. Prior to implementation, correlation between sample types for protein and glucose measurement was found acceptable.

RESULTS.—

The algorithm was put in place twice during 2022. The turnaround time of urine microscopic study was identical to that obtained when the urinalysis was done with the strips; however, the quantification of glucose and protein took approximately 30 minutes more. Urine reflex cultures were triggered correctly with the algorithm, as they were derived entirely from a WBC count higher than 10 per high-power field. During the shortage period we had only 1 complaint, by a physician wanting to have results of nitrates.

CONCLUSIONS.—

During urine strip shortages, we successfully implemented a diversion algorithm that provided actionable urinalysis analytes in a timely manner with minimal provider complaints.

Accuracy of the tuberculosis molecular bacterial load assay to diagnose and monitor response to anti-tuberculosis therapy: a longitudinal comparative study with standard-of-care smear microscopy, Xpert MTB/RIF Ultra, and culture in Uganda

BACKGROUND

In 2018, the tuberculosis molecular bacterial load assay (TB-MBLA), a ribosomal RNA-based test, was acknowledged by WHO as a molecular assay that could replace smear microscopy and culture for monitoring tuberculosis treatment response. In this study, we evaluated the accuracy of TB-MBLA for diagnosis and monitoring of treatment response in comparison with standard-of-care tests.

METHODS

For this longitudinal prospective study, patients aged 18 years or older with presumptive tuberculosis (coughing for at least 2 weeks, night sweats, and weight loss) were enrolled at China-Uganda Friendship Hospital Naguru (Kampala, Uganda). Participants were evaluated for tuberculosis by TB-MBLA in comparison with Xpert MTB/RIF Ultra (Xpert-Ultra) and smear microscopy, with Mycobacteria Growth Indicator Tube (MGIT) culture as a reference test. Participants who were positive on Xpert-Ultra were enrolled on a standard 6-month anti-tuberculosis regimen, and monitored for treatment response at weeks 2, 8, 17, and 26 after initiation of treatment and then 3 months after treatment.

FINDINGS

Between Nov 15, 2019, and June 15, 2022, 210 participants (median age 35 years [IQR 27-44]) were enrolled. 135 (64%) participants were male and 72 (34%) were HIV positive. The pretreatment diagnostic sensitivities of TB-MBLA and Xpert-Ultra were similar (both 99% [95% CI 95-100]) but the specificity was higher for TB-MBLA (90% [83-96]) than for Xpert-Ultra (78% [68-86]). Ten participants were Xpert-Ultra trace positive, eight (80%) of whom were negative by TB-MBLA and MGIT culture. Smear microscopy had lower diagnostic sensitivity (75% [65-83]) but higher specificity (98% [93-100]) than TB-MBLA and Xpert-Ultra. Among participants who were smear microscopy negative, the sensitivity of TB-MBLA was 96% (95 CI 80-100) and was 100% (95% CI 86-100) in those who were HIV positive. 129 (61%) participants were identified as tuberculosis positive by Xpert-Ultra and these individuals were enrolled in the treatment group and monitored for treatment response. According to TB-MBLA, 19 of these patients cleared bacillary load to zero by week 2 of treatment and remained negative throughout the 6-month treatment follow-up. Positivity for tuberculosis decreased with treatment as measured by all tests, but the rate was slower with Xpert-Ultra. Consequently, 31 (33%) of 95 participants were still Xpert-Ultra positive at the end of treatment but were clinically well and negative on TB-MBLA and culture at 6 months of treatment. Two patients were still Xpert-Ultra positive with a further 3 months of post-treatment follow-up. The rate of conversion to negative of the DNA-based Xpert-Ultra was 3·3-times slower than that of the rRNA-based TB-MBLA. Consequently for the same patient, it would take 13 weeks and 52 weeks to reach complete tuberculosis negativity by TB-MBLA and Xpert-Ultra, respectively. Participants who were positive on smear microscopy at 8 weeks, who received an extra month of intensive treatment, had a similar TB-MBLA-measured bacillary load at 8 weeks to those who were smear microscopy negative.

INTERPRETATION

TB-MBLA has a similar performance to Xpert-Ultra for pretreatment diagnosis of tuberculosis, but is more accurate at detecting and characterising the response to treatment than Xpert-Ultra and standard-of-care smear microscopy.

FUNDING

European and Developing Countries Clinical Trials Partnership, Makerere University Research and Innovation Fund, US National Institutes of Health.

The effect of Galilean magnification loupes on the visual acuity and working distance of dental students

OBJECTIVE

This study aimed to evaluate the visual acuity and working distance of dental students using Galilean loupes at different magnification levels.

METHODS

The participants included 50 undergraduate dentistry students selected from each class in the second to fifth years (N = 200) of São Paulo State University, School of Dentistry, Araraquara. The response variables were (i) the working distance between the operator's eyes and the mouth of the dental phantom head, and (ii) visual acuity. The independent variables were the five levels of the Galilean magnification system (naked eye, Galilean loupe simulator without magnification, and Galilean loupes with 2.5×, 3.0×, or 3.5× magnification) and academic year. Visual acuity was measured using a miniature Snellen eye chart inserted into the Class I cavities of the maxillary molars. After verifying the assumptions of normality and sphericity, a mixed repeated measures analysis was performed (α = 0.05).

RESULTS

Statistical significance was found between the "magnification system" and "academic year" for visual acuity (p < 0.001). For the second-, fourth-, and fifth-year participants, there were no significant differences in visual acuity between the naked eye and different magnifications of the Galilean loupes, which were superior to and significantly different from that of the loupe simulator. For the working distance, statistical significance was observed in the interaction between "magnification system" and "academic year" (p = 0.008). For the third-, fourth-, and fifth-year participants, there was no significant difference in the working distance between the naked eye and different magnifications of the Galilean loupes, which were superior to and significantly different from that of the simulator.

CONCLUSION

It was concluded that the different magnification levels of the Galilean loupes did not influence the visual acuity or distance between the eyes of the operator and the mouth of the dental phantom head in the evaluated students.

Label-free assessment of pathological changes in pancreatic intraepithelial neoplasia by biomedical multiphoton microscopy

Pancreatic intraepithelial neoplasia (PanIN) is the most common precursor lesion that has the potential to progress to invasive pancreatic cancer, and early and rapid detection may offer patients a chance for treatment before the development of invasive carcinoma. Therefore, the identification of PanIN holds significant clinical importance. In this study, we first used multiphoton microscopy (MPM) combining two-photon excitation fluorescence and second-harmonic generation imaging to label-free detect PanIN and attempted to differentiate between normal pancreatic ducts and different grades of PanIN. Then, we also developed an automatic image processing strategy to extract eight morphological features of collagen fibers from MPM images to quantify the changes in collagen fibers surrounding the ducts. Experimental results demonstrate that the combination of MPM and quantitative information can accurately identify normal pancreatic ducts and different grades of PanIN. This study may contribute to the rapid diagnosis of pancreatic diseases and may lay the foundation for further clinical application of MPM.

Diagnostic tests for human Schistosoma mansoni and Schistosoma haematobium infection: a systematic review and meta-analysis

BACKGROUND

Accurate diagnosis is pivotal for implementing strategies for surveillance, control, and elimination of schistosomiasis. Despite their low sensitivity in low-endemicity areas, microscopy-based urine filtration and the Kato-Katz technique are considered as reference diagnostic tests for Schistosoma haematobium and Schistosoma mansoni infections, respectively. We aimed to collate all available evidence on the accuracy of other proposed diagnostic techniques.

METHODS

In this systematic review and meta-analysis, we searched PubMed, Embase, the Cochrane Library, and LILACS for studies published from database inception to Dec 31, 2022, investigating the sensitivity and specificity of diagnostic tests for S haematobium and S mansoni infections against Kato-Katz thick smears or urine microscopy (reference tests) involving adults (aged ≥18 years), school-aged children (aged 7 to 18 years), or preschool-aged children (aged 1 month to 7 years). We extracted raw data on true positives, true negatives, false positives, and false negatives for the diagnostic tests and data on the number of participants, study authors, publication year, journal, study design, participants' age and sex, prevalence of Schistosoma infection, and treatment status. To account for imperfect reference tests, we used a hierarchical Bayesian latent class meta-analysis to model test accuracy.

FINDINGS

Overall, we included 121 studies, assessing 28 different diagnostic techniques. Most studies (103 [85%] of 121) were done in Africa, 14 (12%) in South America, one (1%) in Asia, and one (1%) in an unknown country. Compared with the reference test, Kato-Katz thick smears, circulating cathodic antigen urine cassette assay version 1 (CCA1, 36 test comparisons) had excellent sensitivity (95% [95% credible interval 88-99]) and reasonable specificity (74% [63-83]) for S mansoni. ELISA-based tests had a performance comparable to circulating cathodic antigen, but there were few available test comparisons. For S haematobium, proteinuria (42 test comparisons, sensitivity 73% [62-82]; specificity 94% [89-98]) and haematuria (75 test comparisons, sensitivity 85% [80-90]; specificity 96% [92-99]) reagent strips showed high specificity, with haematuria reagent strips having better sensitivity. Despite limited data, nucleic acid amplification tests (NAATs; eg, PCR or loop-mediated isothermal amplification [LAMP]) showed promising results with sensitivity estimates above 90%. We found an unclear risk of bias of about 70% in the use of the reference or index tests and of 50% in patient selection. All analyses showed substantial heterogeneity (I2>80%).

INTERPRETATION

Although NAATs and immunological diagnostics show promise, the limited information available precludes drawing definitive conclusions. Additional research on diagnostic accuracy and cost-effectiveness is needed before the replacement of conventional tests can be considered.

FUNDING

WHO and Luxembourg Institute of Health.

Diagnosis of soil-transmitted helminth infections with digital mobile microscopy and artificial intelligence in a resource-limited setting

BACKGROUND

Infections caused by soil-transmitted helminths (STHs) are the most prevalent neglected tropical diseases and result in a major disease burden in low- and middle-income countries, especially in school-aged children. Improved diagnostic methods, especially for light intensity infections, are needed for efficient, control and elimination of STHs as a public health problem, as well as STH management. Image-based artificial intelligence (AI) has shown promise for STH detection in digitized stool samples. However, the diagnostic accuracy of AI-based analysis of entire microscope slides, so called whole-slide images (WSI), has previously not been evaluated on a sample-level in primary healthcare settings in STH endemic countries.

METHODOLOGY/PRINCIPAL FINDINGS

Stool samples (n = 1,335) were collected during 2020 from children attending primary schools in Kwale County, Kenya, prepared according to the Kato-Katz method at a local primary healthcare laboratory and digitized with a portable whole-slide microscopy scanner and uploaded via mobile networks to a cloud environment. The digital samples of adequate quality (n = 1,180) were split into a training (n = 388) and test set (n = 792) and a deep-learning system (DLS) developed for detection of STHs. The DLS findings were compared with expert manual microscopy and additional visual assessment of the digital samples in slides with discordant results between the methods. Manual microscopy detected 15 (1.9%) Ascaris lumbricoides, 172 (21.7%) Tricuris trichiura and 140 (17.7%) hookworm (Ancylostoma duodenale or Necator americanus) infections in the test set. Importantly, more than 90% of all STH positive cases represented light intensity infections. With manual microscopy as the reference standard, the sensitivity of the DLS as the index test for detection of A. lumbricoides, T. trichiura and hookworm was 80%, 92% and 76%, respectively. The corresponding specificity was 98%, 90% and 95%. Notably, in 79 samples (10%) classified as negative by manual microscopy for a specific species, STH eggs were detected by the DLS and confirmed correct by visual inspection of the digital samples.

CONCLUSIONS/SIGNIFICANCE

Analysis of digitally scanned stool samples with the DLS provided high diagnostic accuracy for detection of STHs. Importantly, a substantial number of light intensity infections were missed by manual microscopy but detected by the DLS. Thus, analysis of WSIs with image-based AI may provide a future tool for improved detection of STHs in a primary healthcare setting, which in turn could facilitate monitoring and evaluation of control programs.

Visual Prompting Based Incremental Learning for Semantic Segmentation of Multiplex Immuno-Flourescence Microscopy Imagery

Deep learning approaches are state-of-the-art for semantic segmentation of medical images, but unlike many deep learning applications, medical segmentation is characterized by small amounts of annotated training data. Thus, while mainstream deep learning approaches focus on performance in domains with large training sets, researchers in the medical imaging field must apply new methods in creative ways to meet the more constrained requirements of medical datasets. We propose a framework for incrementally fine-tuning a multi-class segmentation of a high-resolution multiplex (multi-channel) immuno-flourescence image of a rat brain section, using a minimal amount of labelling from a human expert. Our framework begins with a modified Swin-UNet architecture that treats each biomarker in the multiplex image separately and learns an initial "global" segmentation (pre-training). This is followed by incremental learning and refinement of each class using a very limited amount of additional labeled data provided by a human expert for each region and its surroundings. This incremental learning utilizes the multi-class weights as an initialization and uses the additional labels to steer the network and optimize it for each region in the image. In this way, an expert can identify errors in the multi-class segmentation and rapidly correct them by supplying the model with additional annotations hand-picked from the region. In addition to increasing the speed of annotation and reducing the amount of labelling, we show that our proposed method outperforms a traditional multi-class segmentation by a large margin.