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.

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.

Two cases with discrepancy in the quantitative cytological assessment of cerebrospinal fluid in neonatal samples using light microscopy in comparison with Sysmex XN-1000.

We present two cases from the neonatal department with cerebrospinal fluid examination. We revealed a striking discrepancy in polymorphonuclear (PMN) and mononuclear (MN) cell counts using conventional light microscopy in comparison with automated analyzer Sysmex XN-1000 (PMNs - 13 vs. 173x106/L, MNs - 200 vs. 67x106/L in case 1 and PMNs - 13 vs. 372x106/L, MNs - 411 vs. 179x106/L in case 2). We revealed the dominant presence of hemosiderophages in both cases in cytospin slide. Even though Sysmex XN-1000 offers fast examination with a low sample volume, there is possibility of misdiagnosis, with negative impact on the patient.

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.

Light-Sheet Imaging to Reveal Cardiac Structure in Rodent Hearts.

Light-sheet microscopy (LSM) plays a pivotal role in comprehending the intricate three-dimensional (3D) structure of the heart, providing crucial insights into fundamental cardiac physiology and pathologic responses. We hereby delve into the development and implementation of the LSM technique to elucidate the micro-architecture of the heart in mouse models. The methodology integrates a customized LSM system with tissue clearing techniques, mitigating light scattering within cardiac tissues for volumetric imaging. The combination of conventional LSM with image stitching and multiview deconvolution approaches allows for the capture of the entire heart. To address the inherent trade-off between axial resolution and field of view (FOV), we further introduce an axially swept light-sheet microscopy (ASLM) method to minimize out-of-focus light and uniformly illuminate the heart across the propagation direction. In the meanwhile, tissue clearing methods such as iDISCO enhance light penetration, facilitating the visualization of deep structures and ensuring a comprehensive examination of the myocardium throughout the entire heart. The combination of the proposed LSM and tissue clearing methods presents a promising platform for researchers in resolving cardiac structures in rodent hearts, holding great potential for the understanding of cardiac morphogenesis and remodeling.

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.

Speckle Variance Photoacoustic Microscopy for Microhemodynamic Imaging.

Relying on the strong optical absorption of hemoglobin to pulsed laser energy, photoacoustic microscopy provides morphological and functional information on microvasculature label-freely. Here, we propose speckle variance photoacoustic microscopy (SV-PAM), which harnesses intrinsic imaging contrast from temporal-varied photoacoustic signals of moving red blood cells in blood vessels, for recovering three-dimension hemodynamic images down to capillary-level resolution within the microcirculatory tissue beds in vivo. Calculating the speckle variance of consecutive photoacoustic B-scan frames acquired at the same lateral position enables accurate identification of blood perfusion and occlusion, which provides interpretations of dynamic blood flow in the microvasculature, in addition to the microvascular anatomic structures. We demonstrate high-resolution hemodynamic imaging of vascular occlusion and reperfusion in the microvasculature of mice ears in vivo. The results suggest that our SV-PAM is potentially invaluable for biomedical hemodynamic investigations, for example, imaging ischemic stroke and hemorrhagic stroke.

Plasmonic Imaging of Single DNA with Charge Sensitive Monolayer WS2.

Imaging the surface charge of biomolecules such as proteins and DNA, is crucial for comprehending their structure and function. Unfortunately, current methods for label-free, sensitive, and rapid imaging of the surface charge of single DNA molecules are limited. Here, we propose a plasmonic microscopy strategy that utilizes charge-sensitive single-crystal monolayer WS2 materials to image the local charge density of a single λ-DNA molecule. Our study reveals that WS2 is a highly sensitive charge-sensitive material that can accurately measure the local charge density of λ-DNA with high spatial resolution and sensitivity. The consistency of the surface charge density values obtained from the single-crystal monolayer WS2 materials with theoretical simulations demonstrates the reliability of our approach. Our findings suggest that this class of materials has significant implications for the development of label-free, scanning-free, and rapid optical detection and charge imaging of biomolecules.

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.

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.

[Preliminary Study on the Identification of Aerobic Vaginitis by Artificial Intelligence Analysis System]. / 人工智能分析系统对需氧菌性阴道炎的判读方法初探.

Objective: To develop an artificial intelligence vaginal secretion analysis system based on deep learning and to evaluate the accuracy of automated microscopy in the clinical diagnosis of aerobic vaginitis (AV). Methods: In this study, the vaginal secretion samples of 3769 patients receiving treatment at the Department of Obstetrics and Gynecology, West China Second Hospital, Sichuan University between January 2020 and December 2021 were selected. Using the results of manual microscopy as the control, we developed the linear kernel SVM algorithm, an artificial intelligence (AI) automated analysis software, with Python Scikit-learn script. The AI automated analysis software could identify leucocytes with toxic appearance and parabasal epitheliocytes (PBC). The bacterial grading parameters were reset using standard strains of lactobacillus and AV common isolates. The receiver operating characteristic (ROC) curve analysis was used to determine the cut-off value of AV evaluation results for different scoring items were obtained by using the results of manual microscopy as the control. Then, the parameters of automatic AV identification were determined and the automatic AV analysis scoring method was initially established. Results: A total of 3769 vaginal secretion samples were collected. The AI automated analysis system incorporated five parameters and each parameter incorporated three severity scoring levels. We selected 1.5 µm as the cut-off value for the diameter between Lactobacillus and common AV bacterial isolates. The automated identification parameter of Lactobacillus was the ratio of bacteria ≥1.5 µm to those <1.5 µm. The cut-off scores were 2.5 and 0.5, In the parameter of white blood cells (WBC), the cut-off value of the absolute number of WBC was 103 µL－1 and the cut-off value of WBC-to-epithelial cell ratio was 10. The automated identification parameter of toxic WBC was the ratio of toxic WBC toWBC and the cut-off values were 1% and 15%. The parameter of background flora was bacteria<1.5 µm and the cut-off values were 5×103 µL－1 and 3×104 µL－1. The parameter of the parabasal epitheliocytes was the ratio of PBC to epithelial cells and the cut-off values were 1% and 10%. The agreement rate between the results of automated microscopy and those of manual microscopy was 92.5%. Out of 200 samples, automated microscopy and manual microscopy produced consistent scores for 185 samples, while the results for 15 samples were inconsistent. Conclusion: We developed an AI recognition software for AV and established an automated vaginal secretion microscopy scoring system for AV. There was good overall concordance between automated microscopy and manual microscopy. The AI identification software for AV can complete clinical lab examination with rather high objectivity, sensitivity, and efficiency, markedly reducing the workload of manual microscopy.

Controllable Fabrication of Sub-10 nm Graphene Nanopores via Helium Ion Microscopy and DNA Detection.

Solid-state nanopores have become a prominent tool in the field of single-molecule detection. Conventional solid-state nanopores are thick, which affects the spatial resolution of the detection results. Graphene is the thinnest 2D material and has the highest spatial detection resolution. In this study, a graphene membrane chip was fabricated by combining a MEMS process with a 2D material wet transfer process. Raman spectroscopy was used to assess the quality of graphene after the transfer. The mechanism behind the influence of the processing dose and residence time of the helium ion beam on the processed pore size was investigated. Subsequently, graphene nanopores with diameters less than 10 nm were fabricated via helium ion microscopy. DNA was detected using a 5.8 nm graphene nanopore chip, and the appearance of double-peak signals on the surface of 20 mer DNA was successfully detected. These results serve as a valuable reference for nanopore fabrication using 2D material for DNA analysis.

An Extracellular Matrix Overlay Model for Bioluminescence Microscopy to Measure Single-Cell Heterogeneous Responses to Antiandrogens in Prostate Cancer Cells.

Prostate cancer (PCa) displays diverse intra-tumoral traits, impacting its progression and treatment outcomes. This study aimed to refine PCa cell culture conditions for dynamic monitoring of androgen receptor (AR) activity at the single-cell level. We introduced an extracellular matrix-Matrigel (ECM-M) culture model, enhancing cellular tracking during bioluminescence single-cell imaging while improving cell viability. ECM-M notably tripled the traceability of poorly adherent PCa cells, facilitating robust single-cell tracking, without impeding substrate permeability or AR response. This model effectively monitored AR modulation by antiandrogens across various PCa cell lines. Single-cell imaging unveiled heterogeneous antiandrogen responses within populations, correlating non-responsive cell proportions with drug IC50 values. Integrating ECM-M culture with the PSEBC-TSTA biosensor enabled precise characterization of ARi responsiveness within diverse cell populations. Our ECM-M model stands as a promising tool to assess heterogeneous single-cell treatment responses in cancer, offering insights to link drug responses to intracellular signaling dynamics. This approach enhances our comprehension of the nuanced and dynamic nature of PCa treatment responses.

Molecular tools are crucial for malaria elimination.

The eradication of Plasmodium parasites, responsible for malaria, is a daunting global public health task. It requires a comprehensive approach that addresses symptomatic, asymptomatic, and submicroscopic cases. Overcoming this challenge relies on harnessing the power of molecular diagnostic tools, as traditional methods like microscopy and rapid diagnostic tests fall short in detecting low parasitaemia, contributing to the persistence of malaria transmission. By precisely identifying patients of all types and effectively characterizing malaria parasites, molecular tools may emerge as indispensable allies in the pursuit of malaria elimination. Furthermore, molecular tools can also provide valuable insights into parasite diversity, drug resistance patterns, and transmission dynamics, aiding in the implementation of targeted interventions and surveillance strategies. In this review, we explore the significance of molecular tools in the pursuit of malaria elimination, shedding light on their key contributions and potential impact on public health.

Thermal-tagging photoacoustic remote sensing flowmetry.

Ultrasound coupling is one of the critical challenges for traditional photoacoustic (or optoacoustic) microscopy (PAM) techniques transferred to the clinical examination of chronic wounds and open tissues. A promising alternative potential solution for breaking the limitation of ultrasound coupling in PAM is photoacoustic remote sensing (PARS), which implements all-optical non-interferometric photoacoustic measurements. Functional imaging of PARS microscopy was demonstrated from the aspects of histopathology and oxygen metabolism, while its performance in hemodynamic quantification remains unexplored. In this Letter, we present an all-optical thermal-tagging flowmetry approach for PARS microscopy and demonstrate it with comprehensive mathematical modeling and ex vivo and in vivo experimental validations. Experimental results demonstrated that the detectable range of the blood flow rate was from 0 to 12 mm/s with a high accuracy (measurement error:±1.2%) at 10-kHz laser pulse repetition rate. The proposed all-optical thermal-tagging flowmetry offers an effective alternative approach for PARS microscopy realizing non-contact dye-free hemodynamic imaging.

Context-aware deep learning enables high-efficacy localization of high concentration microbubbles for super-resolution ultrasound localization microscopy.

Ultrasound localization microscopy (ULM) enables deep tissue microvascular imaging by localizing and tracking intravenously injected microbubbles circulating in the bloodstream. However, conventional localization techniques require spatially isolated microbubbles, resulting in prolonged imaging time to obtain detailed microvascular maps. Here, we introduce LOcalization with Context Awareness (LOCA)-ULM, a deep learning-based microbubble simulation and localization pipeline designed to enhance localization performance in high microbubble concentrations. In silico, LOCA-ULM enhanced microbubble detection accuracy to 97.8% and reduced the missing rate to 23.8%, outperforming conventional and deep learning-based localization methods up to 17.4% in accuracy and 37.6% in missing rate reduction. In in vivo rat brain imaging, LOCA-ULM revealed dense cerebrovascular networks and spatially adjacent microvessels undetected by conventional ULM. We further demonstrate the superior localization performance of LOCA-ULM in functional ULM (fULM) where LOCA-ULM significantly increased the functional imaging sensitivity of fULM to hemodynamic responses invoked by whisker stimulations in the rat brain.

Label-free Brillouin endo-microscopy for the quantitative 3D imaging of sub-micrometre biology.

This report presents an optical fibre-based endo-microscopic imaging tool that simultaneously measures the topographic profile and 3D viscoelastic properties of biological specimens through the phenomenon of time-resolved Brillouin scattering. This uses the intrinsic viscoelasticity of the specimen as a contrast mechanism without fluorescent tags or photoacoustic contrast mechanisms. We demonstrate 2 µm lateral resolution and 320 nm axial resolution for the 3D imaging of biological cells and Caenorhabditis elegans larvae. This has enabled the first ever 3D stiffness imaging and characterisation of the C. elegans larva cuticle in-situ. A label-free, subcellular resolution, and endoscopic compatible technique that reveals structural biologically-relevant material properties of tissue could pave the way toward in-vivo elasticity-based diagnostics down to the single cell level.

Label-Free Techniques for Probing Biomolecular Condensates.

Biomolecular condensates play important roles in a wide array of fundamental biological processes, such as cellular compartmentalization, cellular regulation, and other biochemical reactions. Since their discovery and first observations, an extensive and expansive library of tools has been developed to investigate various aspects and properties, encompassing structural and compositional information, material properties, and their evolution throughout the life cycle from formation to eventual dissolution. This Review presents an overview of the expanded set of tools and methods that researchers use to probe the properties of biomolecular condensates across diverse scales of length, concentration, stiffness, and time. In particular, we review recent years' exciting development of label-free techniques and methodologies. We broadly organize the set of tools into 3 categories: (1) imaging-based techniques, such as transmitted-light microscopy (TLM) and Brillouin microscopy (BM), (2) force spectroscopy techniques, such as atomic force microscopy (AFM) and the optical tweezer (OT), and (3) microfluidic platforms and emerging technologies. We point out the tools' key opportunities, challenges, and future perspectives and analyze their correlative potential as well as compatibility with other techniques. Additionally, we review emerging techniques, namely, differential dynamic microscopy (DDM) and interferometric scattering microscopy (iSCAT), that have huge potential for future applications in studying biomolecular condensates. Finally, we highlight how some of these techniques can be translated for diagnostics and therapy purposes. We hope this Review serves as a useful guide for new researchers in this field and aids in advancing the development of new biophysical tools to study biomolecular condensates.

Dynamic Mode Decomposition of Multiphoton and Stimulated Emission Depletion Microscopy Data for Analysis of Fluorescent Probes in Cellular Membranes.

An analysis of the membrane organization and intracellular trafficking of lipids often relies on multiphoton (MP) and super-resolution microscopy of fluorescent lipid probes. A disadvantage of particularly intrinsically fluorescent lipid probes, such as the cholesterol and ergosterol analogue, dehydroergosterol (DHE), is their low MP absorption cross-section, resulting in a low signal-to-noise ratio (SNR) in live-cell imaging. Stimulated emission depletion (STED) microscopy of membrane probes like Nile Red enables one to resolve membrane features beyond the diffraction limit but exposes the sample to a lot of excitation light and suffers from a low SNR and photobleaching. Here, dynamic mode decomposition (DMD) and its variant, higher-order DMD (HoDMD), are applied to efficiently reconstruct and denoise the MP and STED microscopy data of lipid probes, allowing for an improved visualization of the membranes in cells. HoDMD also allows us to decompose and reconstruct two-photon polarimetry images of TopFluor-cholesterol in model and cellular membranes. Finally, DMD is shown to not only reconstruct and denoise 3D-STED image stacks of Nile Red-labeled cells but also to predict unseen image frames, thereby allowing for interpolation images along the optical axis. This important feature of DMD can be used to reduce the number of image acquisitions, thereby minimizing the light exposure of biological samples without compromising image quality. Thus, DMD as a computational tool enables gentler live-cell imaging of fluorescent probes in cellular membranes by MP and STED microscopy.

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.