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.

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.

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.

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.

Photoacoustic microscopy for real-time monitoring of near-infrared optical absorbers inside biological tissue.

Significance: We developed a high-speed optical-resolution photoacoustic microscopy (OR-PAM) system using a high-repetition-rate supercontinuum (SC) light source and a two-axes Galvano scanner. The OR-PAM system enabled real-time imaging of optical absorbers inside biological tissues with excellent excitation wavelength tunability. Aim: In the near-infrared (NIR) wavelength range, high-speed OR-PAM faces limitations due to the lack of wavelength-tunable light sources. Our study aimed to enable high-speed OR-PAM imaging of various optical absorbers, including NIR contrast agents, and validate the performance of high-speed OR-PAM in the detection of circulating tumor cells (CTCs). Approach: A high-repetition nanosecond pulsed SC light source was used for OR-PAM. The excitation wavelength was adjusted by bandpass filtering of broadband light pulses produced by an SC light source. Phantom and in vivo experiments were performed to detect tumor cells stained with an NIR contrast agent within flowing blood samples. Results: The newly developed high-speed OR-PAM successfully detected stained cells both in the phantom and in vivo. The phantom experiment confirmed the correlation between the tumor cell detection rate and tumor cell concentration in the blood sample. Conclusions: The high-speed OR-PAM effectively detected stained tumor cells. Combining high-speed OR-PAM with molecular probes that stain tumor cells in vivo enables in vivo CTC detection.

EARLY STAGES OF COLORECTAL CANCER CHARACTERIZATION BY AUTOFLUORESCENCE 3D MICROSCOPY: A PRELIMINARY STUDY.

BACKGROUND: Colorectal cancer is one of the most prevalent pathologies worldwide whose prognosis is linked to early detection. Colonoscopy is the gold standard for screening, and diagnosis is usually made histologically from biopsies. Aiming to reduce the inspection and diagnostic time as well as the biopsies and resources involved, other techniques are being promoted to conduct accurate in vivo colonoscopy assessments. Optical biopsy aims to detect normal and neoplastic tissues analysing the autofluorescence spectrum based on the changes in the distribution and concentration of autofluorescent molecules caused by colorectal cancer. Therefore, the autofluorescence contribution analysed by image processing techniques could be an approach to a faster characterization of the target tissue. OBJECTIVE: Quantify intensity parameters through digital processing of two data sets of three-dimensional widefield autofluorescence microscopy images, acquired by fresh colon tissue samples from a colorectal cancer murine model. Additionally, analyse the autofluorescence data to provide a characterization over a volume of approximately 50 µm of the colon mucosa for each image, at second (2nd), fourth (4th) and eighth (8th) weeks after colorectal cancer induction. METHODS: Development of a colorectal cancer murine model using azoxymethane/dextran sodium sulphate induction, and data sets acquisition of Z-stack images by widefield autofluorescence microscopy, from control and colorectal cancer induced animals. Pre-processing steps of intensity value adjustments followed by quantification and characterization procedures using image processing workflow automation by Fiji's macros, and statistical data analysis. RESULTS: The effectiveness of the colorectal cancer induction model was corroborated by a histological assessment to correlate and validate the link between histological and autofluorescence changes. The image digital processing methodology proposed was then performed on the three-dimensional images from control mice and from the 2nd, 4th, and 8th weeks after colorectal cancer chemical induction, for each data set. Statistical analyses found significant differences in the mean, standard deviation, and minimum parameters between control samples and those of the 2nd week after induction with respect to the 4th week of the first experimental study. This suggests that the characteristics of colorectal cancer can be detected after the 2nd week post-induction. CONCLUSION: The use of autofluorescence still exhibits levels of variability that prevent greater systematization of the data obtained during the progression of colorectal cancer. However, these preliminary outcomes could be considered an approach to the three-dimensional characterization of the autofluorescence of colorectal tissue, describing the autofluorescence features of samples coming from dysplasia to colorectal cancer. BACKGROUND: • A new digital image processing method was developed to measure intensity in 3D autofluorescence images of colorectal samples using a CRC mouse model. BACKGROUND: • This method showed that autofluorescence intensity in colon mucosa is similar in healthy tissue but changes significantly in tumor development. BACKGROUND: • Statistical analysis revealed CRC traits detectable from the second week post-induction, aiding in early CRC detection. BACKGROUND: • The study provides a basis for 3D autofluorescence characterization in colorectal tissue from dysplasia to cancer, although variability in autofluorescence limits data systematization during cancer progression.

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.

Efficient Assessment of Tumor Vascular Shutdown by Photodynamic Therapy on Orthotopic Pancreatic Cancer Using High-Speed Wide-Field Waterproof Galvanometer Scanner Photoacoustic Microscopy.

To identify the vascular alteration by photodynamic therapy (PDT), the utilization of high-resolution, high-speed, and wide-field photoacoustic microscopy (PAM) has gained enormous interest. The rapid changes in vasculature during PDT treatment and monitoring of tumor tissue activation in the orthotopic pancreatic cancer model have received limited attention in previous studies. Here, a fully two-axes waterproof galvanometer scanner-based photoacoustic microscopy (WGS-PAM) system was developed for in vivo monitoring of dynamic variations in micro blood vessels due to PDT in an orthotopic pancreatic cancer mouse model. The photosensitizer (PS), Chlorin e6 (Ce6), was utilized to activate antitumor reactions in response to the irradiation of a 660 nm light source. Microvasculatures of angiogenesis tissue were visualized on a 40 mm2 area using the WGS-PAM system at 30 min intervals for 3 h after the PDT treatment. The decline in vascular intensity was observed at 24.5% along with a 32.4% reduction of the vascular density at 3 h post-PDT by the analysis of PAM images. The anti-vascularization effect was also identified with fluorescent imaging. Moreover, Ce6-PDT increased apoptotic and necrotic markers while decreasing vascular endothelial growth factor (VEGF) expression in MIA PaCa-2 and BxPC-3 pancreatic cancer cell lines. The approach of the WGS-PAM system shows the potential to investigate PDT effects on the mechanism of angiographic dynamics with high-resolution wide-field imaging modalities.

On-the-fly Raman microscopy guaranteeing the accuracy of discrimination.

Accelerating the measurement for discrimination of samples, such as classification of cell phenotype, is crucial when faced with significant time and cost constraints. Spontaneous Raman microscopy offers label-free, rich chemical information but suffers from long acquisition time due to extremely small scattering cross-sections. One possible approach to accelerate the measurement is by measuring necessary parts with a suitable number of illumination points. However, how to design these points during measurement remains a challenge. To address this, we developed an imaging technique based on a reinforcement learning in machine learning (ML). This ML approach adaptively feeds back "optimal" illumination pattern during the measurement to detect the existence of specific characteristics of interest, allowing faster measurements while guaranteeing discrimination accuracy. Using a set of Raman images of human follicular thyroid and follicular thyroid carcinoma cells, we showed that our technique requires 3,333 to 31,683 times smaller number of illuminations for discriminating the phenotypes than raster scanning. To quantitatively evaluate the number of illuminations depending on the requisite discrimination accuracy, we prepared a set of polymer bead mixture samples to model anomalous and normal tissues. We then applied a home-built programmable-illumination microscope equipped with our algorithm, and confirmed that the system can discriminate the sample conditions with 104 to 4,350 times smaller number of illuminations compared to standard point illumination Raman microscopy. The proposed algorithm can be applied to other types of microscopy that can control measurement condition on the fly, offering an approach for the acceleration of accurate measurements in various applications including medical diagnosis.

Open-top Bessel beam two-photon light sheet microscopy for three-dimensional pathology.

Nondestructive pathology based on three-dimensional (3D) optical microscopy holds promise as a complement to traditional destructive hematoxylin and eosin (H&E) stained slide-based pathology by providing cellular information in high throughput manner. However, conventional techniques provided superficial information only due to shallow imaging depths. Herein, we developed open-top two-photon light sheet microscopy (OT-TP-LSM) for intraoperative 3D pathology. An extended depth of field two-photon excitation light sheet was generated by scanning a nondiffractive Bessel beam, and selective planar imaging was conducted with cameras at 400 frames/s max during the lateral translation of tissue specimens. Intrinsic second harmonic generation was collected for additional extracellular matrix (ECM) visualization. OT-TP-LSM was tested in various human cancer specimens including skin, pancreas, and prostate. High imaging depths were achieved owing to long excitation wavelengths and long wavelength fluorophores. 3D visualization of both cells and ECM enhanced the ability of cancer detection. Furthermore, an unsupervised deep learning network was employed for the style transfer of OT-TP-LSM images to virtual H&E images. The virtual H&E images exhibited comparable histological characteristics to real ones. OT-TP-LSM may have the potential for histopathological examination in surgical and biopsy applications by rapidly providing 3D information.

Non-invasive methods of monitoring Fe3O4 magnetic nanoparticle toxicity in human liver HepaRG cells using impedance biosensing and Coherent anti-Stokes Raman spectroscopic (CARS) microscopy.

Functionalized nanoparticles have been developed for use in nanomedicines for treating life threatening diseases including various cancers. To ensure safe use of these new nanoscale reagents, various assays for biocompatibility or cytotoxicity in vitro using cell lines often serve as preliminary assessments prior to in vivo animal testing. However, many of these assays were designed for soluble, colourless materials and may not be suitable for coloured, non-transparent nanoparticles. Moreover, cell lines are not always representative of mammalian organs in vivo. In this work, we use non-invasive impedance sensing methods with organotypic human liver HepaRG cells as a model to test the toxicity of PEG-Fe3O4 magnetic nanoparticles. We also use Coherent anti-Stokes Raman Spectroscopic (CARS) microscopy to monitor the formation of lipid droplets as a parameter to the adverse effect on the HepaRG cell model. The results were also compared with two commercial testing kits (PrestoBlue and ATP) for cytotoxicity. The results suggested that the HepaRG cell model can be a more realistic model than commercial cell lines while use of impedance monitoring of Fe3O4 nanoparticles circumventing the uncertainties due to colour assays. These methods can play important roles for scientists driving towards the 3Rs principle - Replacement, Reduction and Refinement.

Digital Microscopy Augmented by Artificial Intelligence to Interpret Bone Marrow Samples for Hematological Diseases.

Analysis of bone marrow aspirates (BMAs) is an essential step in the diagnosis of hematological disorders. This analysis is usually performed based on a visual examination of samples under a conventional optical microscope, which involves a labor-intensive process, limited by clinical experience and subject to high observer variability. In this work, we present a comprehensive digital microscopy system that enables BMA analysis for cell type counting and differentiation in an efficient and objective manner. This system not only provides an accessible and simple method to digitize, store, and analyze BMA samples remotely but is also supported by an Artificial Intelligence (AI) pipeline that accelerates the differential cell counting process and reduces interobserver variability. It has been designed to integrate AI algorithms with the daily clinical routine and can be used in any regular hospital workflow.

A Mouse Model of the Associating Liver Partition and Portal Vein Ligation for Staged Hepatectomy Procedure Aided by Microscopy.

Hepatectomy is widely regarded as the primary treatment for hepatic malignancies; yet, postoperative liver failure remains a major cause of perioperative mortality, severely impacting patient outcomes. In a robust hepatic environment, the future liver remnant (FLR) must exceed 25%, and in cases of cirrhosis, this requirement increases to over 40%. The inadequacy of FLR is currently a major obstacle in the progression of hepatic surgery. Traditional methods to enhance FLR hypertrophy mainly focus on portal vein embolization (PVE), but its effectiveness is considerably limited. In recent years, there have been numerous reports on a novel biphasic hepatectomy method involving hepatic partitioning and portal vein ligation, known as associating liver partition and portal vein ligation for staged hepatectomy (ALPPS). ALPPS surpasses PVE in efficiently and considerably inducing FLR hypertrophy. However, the detailed mechanisms driving ALPPS-facilitated hepatic regeneration are not fully understood. Thus, replicating ALPPS in animal models is crucial to thoroughly investigate the molecular mechanisms of hepatic regeneration, offering valuable theoretical and practical insights.

Prevalence and associated factors for asymptomatic microscopic hematuria in adults in the PERSIAN Guilan cohort study (PGCS).

Although hematuria is not life-threatening, some could be the result of a more severe condition. Our objectives are to report on the prevalence and risk factors of asymptomatic microscopic hematuria (AMH) in the prospective epidemiological research studies of the Iranian adults (PERSIAN) Guilan cohort study (PGCS) population. This cross-sectional study was conducted from 2014 to 2017 and consisted of 10,520 individuals aged 35-70. Data collection was conducted using a questionnaire during a face-to-face interview. The urine analyses (UA) were done up to 2 h after sample collection. Based on a urine microscopy evaluation, AMH is defined as 3 or more red blood cells per high power field (HPF). Simple and multiple logistic regression analysis was conducted to explore factors associated with AMH. The prevalence of AMH in this study was 34.1% and was more prevalent in participants of older ages and female gender as well as those with low educational level, underweight-body mass index (BMI), high physical activity, smoking, alcohol consumption, and kidney stone disease. On the other hand, obesity, opium, and diabetes decreased the likelihood of AMH. The results of the present study shed light on the prevalence and risk factors of AMH and suggested that a significant portion of the study population is affected by AMH. Considering the lack of consensus on a definite clinical guideline for AMH in our country, the results of the present study could be used to design a unit algorithm for screening and therapy of AMH.

Fibroblastic reticular cell tumor of eyelid: Rare case report and review of literature.

Fibroblastic reticular cell tumours (FRCT) originate from the fibroblastic reticular cells (FBRC) which are histiocytic cells, belonging to the dendritic cell family. These tumours are extremely rare, with only a few cases reported in literature. Histomorphologically, they resemble follicular dendritic cell sarcoma (FDCS); however, they differ immunophenotypically. Extranodal presentations are rare. We report a case of malignant FBRC tumour of the left eyelid, in a 23-year-old woman, who had presented with a recurrent swelling over left lower eyelid. Microscopy revealed an ill circumbscribed tumour composed of oval to spindle cells in storiform pattern, sprinkled with lymphocytes. Immunohistochemistry was performed and diagnosis of FRCT was offered. To the best of our knowledge, this is the first report of malignant FBRC tumour arising in the eyelid region. Here we present this extremely rare case with review of the available literature.

Stochastic Optical Reconstruction Microscopy Imaging of Multiple System Atrophy Inclusions Suggests Stepwise α-Synuclein Aggregation.

BACKGROUND: The architecture and composition of glial (GCI) and neuronal (NCI) α-synuclein inclusions observed in multiple system atrophy (MSA) remain to be precisely defined to better understand the disease. METHODS: Here, we used stochastic optical reconstruction microscopy (STORM) to characterize the nanoscale organization of glial (GCI) and neuronal (NCI) α-synuclein inclusions in cryopreserved brain sections from MSA patients. RESULTS: STORM revealed a dense cross-linked internal structure of α-synuclein in all GCI and NCI. The internal architecture of hyperphosphorylated α-synuclein (p-αSyn) inclusions was similar in glial and neuronal cells, suggesting a common aggregation mechanism. A similar sequence of p-αSyn stepwise intracellular aggregation was defined in oligodendrocytes and neurons, starting from the perinuclear area and growing inside the cells. Consistent with this hypothesis, we found a higher mitochondrial density in GCI and NCI compared to oligodendrocytes and neurons from unaffected donors (P < 0.01), suggesting an active recruitment of the organelles during the aggregation process. CONCLUSIONS: These first STORM images of GCI and NCI suggest stepwise α-synuclein aggregation in MSA. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Digital morphology compared to the optical microscope: A validation study on reporting bone marrow aspirates.

INTRODUCTION: This study aims to evaluate the effectiveness and reliability of the utilization for clinical reporting of the evaluation of digital images of bone marrow aspirates by morphologists and their comparability with the classic microscopic morphological evaluation. METHODS: We scanned 180 consecutive bone marrow needle aspirates smears using the "Metafer4 VSlide" whole slide imaging (WSI) digital scanning system. We evaluated the statistical comparability and the risk of bias of the microscopic readings with those performed on the screen on the digitized medullary images. RESULTS: The evaluation of cellularity on the screen was equivalent, with a higher frequency of "normal" than the analysis of digital preparations. The means and medians of the percentage values obtained on the different cell populations with the microscopic and digital reading were comparable as the main categories are concerned, with an average difference equal to 0 for the neutrophilic and eosinophilic granulocytic series, at -0.2% for the total myeloid cells, at 1.2% for the erythroid series, at -0.4% for the lymphocytes and at -0.4% for the blasts. Dysplastic features were consistently identified in 69/71 cell lineages. CONCLUSION: Our study demonstrated that screen evaluation of digitized bone marrow needle aspirates provides quantitative and qualitative results comparable to traditional microscopic analysis of the corresponding slide smears. Digital images offer significant benefits in reducing the workload of experienced operators, reproducibility and sharing of observations, and image preservation. Even in routine diagnostic activities, their use does not alter the quality of the results obtained in evaluating bone marrow needle aspirates.