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.

Mouse Brain Tissue Preparation for Scanning Electron Microscopy.

Scanning electron microscopy (SEM) is used to observe the surface structure of an object by irradiating an electron beam onto the sample and detecting the reflected and emitted electrons. Because of its large depth of focus, SEM can provide the three-dimensional structure of small surfaces that cannot be observed using an optical microscope. Furthermore, the cross-sectional structure of the tissue can be observed by freeze-cracking. Observing the ultrastructure of organisms that contain large amounts of water in their bodies while maintaining high resolution is challenging; however, this has recently become possible. Here, we explain the fixation and freeze-cracking method for mouse brain samples.

Dual-space disentangled-multimodal network (DDM-net) for glioma diagnosis and prognosis with incomplete pathology and genomic data.

Objective. Effective fusion of histology slides and molecular profiles from genomic data has shown great potential in the diagnosis and prognosis of gliomas. However, it remains challenging to explicitly utilize the consistent-complementary information among different modalities and create comprehensive representations of patients. Additionally, existing researches mainly focus on complete multi-modality data and usually fail to construct robust models for incomplete samples.Approach. In this paper, we propose adual-space disentangled-multimodal network (DDM-net)for glioma diagnosis and prognosis. DDM-net disentangles the latent features generated by two separate variational autoencoders (VAEs) into common and specific components through a dual-space disentangled approach, facilitating the construction of comprehensive representations of patients. More importantly, DDM-net imputes the unavailable modality in the latent feature space, making it robust to incomplete samples.Main results. We evaluated our approach on the TCGA-GBMLGG dataset for glioma grading and survival analysis tasks. Experimental results demonstrate that the proposed method achieves superior performance compared to state-of-the-art methods, with a competitive AUC of 0.952 and a C-index of 0.768.Significance. The proposed model may help the clinical understanding of gliomas and can serve as an effective fusion model with multimodal data. Additionally, it is capable of handling incomplete samples, making it less constrained by clinical limitations.

Registered multi-device/staining histology image dataset for domain-agnostic machine learning models.

Variations in color and texture of histopathology images are caused by differences in staining conditions and imaging devices between hospitals. These biases decrease the robustness of machine learning models exposed to out-of-domain data. To address this issue, we introduce a comprehensive histopathology image dataset named PathoLogy Images of Scanners and Mobile phones (PLISM). The dataset consisted of 46 human tissue types stained using 13 hematoxylin and eosin conditions and captured using 13 imaging devices. Precisely aligned image patches from different domains allowed for an accurate evaluation of color and texture properties in each domain. Variation in PLISM was assessed and found to be significantly diverse across various domains, particularly between whole-slide images and smartphones. Furthermore, we assessed the improvement in domain shift using a convolutional neural network pre-trained on PLISM. PLISM is a valuable resource that facilitates the precise evaluation of domain shifts in digital pathology and makes significant contributions towards the development of robust machine learning models that can effectively address challenges of domain shift in histological image analysis.

Mitosis detection, fast and slow: Robust and efficient detection of mitotic figures.

Counting of mitotic figures is a fundamental step in grading and prognostication of several cancers. However, manual mitosis counting is tedious and time-consuming. In addition, variation in the appearance of mitotic figures causes a high degree of discordance among pathologists. With advances in deep learning models, several automatic mitosis detection algorithms have been proposed but they are sensitive to domain shift often seen in histology images. We propose a robust and efficient two-stage mitosis detection framework, which comprises mitosis candidate segmentation (Detecting Fast) and candidate refinement (Detecting Slow) stages. The proposed candidate segmentation model, termed EUNet, is fast and accurate due to its architectural design. EUNet can precisely segment candidates at a lower resolution to considerably speed up candidate detection. Candidates are then refined using a deeper classifier network, EfficientNet-B7, in the second stage. We make sure both stages are robust against domain shift by incorporating domain generalization methods. We demonstrate state-of-the-art performance and generalizability of the proposed model on the three largest publicly available mitosis datasets, winning the two mitosis domain generalization challenge contests (MIDOG21 and MIDOG22). Finally, we showcase the utility of the proposed algorithm by processing the TCGA breast cancer cohort (1,124 whole-slide images) to generate and release a repository of more than 620K potential mitotic figures (not exhaustively validated).

3D polarization-interference holographic histology for wavelet-based differentiation of the polycrystalline component of biological tissues with different necrotic states. Forensic applications.

Significance: The interference-holographic method of phase scanning of fields of scattered laser radiation is proposed. The effectiveness of this method for the selection of variously dispersed components is demonstrated. This method made it possible to obtain polarization maps of biological tissues at a high level of depolarized background. The scale-selective analysis of such maps was used to determine necrotic changes in the optically anisotropic architectonics of biological tissues. Objective: Development and experimental approbation of layered phase polarimetry of repeatedly scattered fields in diffuse layers of biological tissues. Application of scale-selective processing of the found coordinate distributions of polarization states in various phase sections of object fields. Determination of criteria (markers) for histological differential diagnosis of the causes of necrotic changes in optical anisotropy of biological tissues. Approach: We used a synthesis of three instrumental and analytical methods. Polarization-interference registration of laser radiation scattered by a sample of biological tissue. Digital holographic reconstruction and layered phase scanning of distributions of complex amplitudes of the object field. Analytical determination of polarization maps of various phase cross-sections of repeatedly scattered radiation. Application of wavelet analysis of the distributions of polarization states in the phase plane of a single scattered component of an object field. Determination of criteria (markers) for differential diagnosis of necrotic changes in biological tissues with different morphological structure. Two cases are considered. The first case is the myocardium of those who died as a result of coronary heart disease and acute coronary insufficiency. The second case is lung tissue samples of deceased with bronchial asthma and fibrosis. Results: A method of polarization-interference mapping of diffuse object fields of biological tissues has been developed and experimentally implemented. With the help of digital holographic reconstruction of the distributions of complex amplitudes, polarization maps in various phase sections of a diffuse object field are found. The wavelet analysis of azimuth and ellipticity distributions of polarization in the phase plane of a single scattered component of laser radiation is used. Scenarios for changing the amplitude of the wavelet coefficients for different scales of the scanning salt-like MHAT function are determined. Statistical moments of the first to fourth orders are determined for the distributions of the amplitudes of the wavelet coefficients of the azimuth maps and the ellipticity of polarization. As a result, diagnostic markers of necrotic changes in the myocardium and lung tissue were determined. The statistical criteria found are the basis for determining the accuracy of their differential diagnosis of various necrotic states of biological tissues. Conclusions: Necrotic changes caused by "coronary artery disease-acute coronary insufficiency" and "asthma-pulmonary fibrosis" were demonstrated by the method of wavelet differentiation with polarization interference with excellent accuracy.

Integrating X-ray phase-contrast imaging and histology for comparative evaluation of breast tissue malignancies in virtual histology analysis.

Detecting breast tissue alterations is essential for cancer diagnosis. However, inherent bidimensionality limits histological procedures' effectiveness in identifying these changes. Our study applies a 3D virtual histology method based on X-ray phase-contrast microtomography (PhC µ CT), performed at a synchrotron facility, to investigate breast tissue samples including different types of lesions, namely intraductal papilloma, micropapillary intracystic carcinoma, and invasive lobular carcinoma. One-to-one comparisons of X-ray and histological images explore the clinical potential of 3D X-ray virtual histology. Results show that PhC µ CT technique provides high spatial resolution and soft tissue sensitivity, while being non-destructive, not requiring a dedicated sample processing and being compatible with conventional histology. PhC µ CT can enhance the visualization of morphological characteristics such as stromal tissue, fibrovascular core, terminal duct lobular unit, stromal/epithelium interface, basement membrane, and adipocytes. Despite not reaching the (sub) cellular level, the three-dimensionality of PhC µ CT images allows to depict in-depth alterations of the breast tissues, potentially revealing pathologically relevant details missed by a single histological section. Compared to serial sectioning, PhC µ CT allows the virtual investigation of the sample volume along any orientation, possibly guiding the pathologist in the choice of the most suitable cutting plane. Overall, PhC µ CT virtual histology holds great promise as a tool adding to conventional histology for improving efficiency, accessibility, and diagnostic accuracy of pathological evaluation.

[Intraoperative stimulated Raman histology for personalized brain tumor surgery]. / Personalisierte Hirntumorchirurgie mittels intraoperativer stimulierter Raman-Histologie.

BACKGROUND: In brain tumor surgery a personalized surgical approach is crucial to achieve a maximum safe tumor resection. The extent of resection decisively depends on the histological diagnosis. Stimulated Raman histology (SRH), a fiber laser-based optical imaging method, offers the possibility for evaluation of an intraoperative diagnosis in a few minutes. OBJECTIVE: To provide an overview on the applications of SRH in neurosurgery and transference of the technique to other surgical disciplines. METHODS: Description of the technique and review of the current literature on SRH. RESULTS: The SRH technique was successfully used in multiple neuro-oncological tumor entities. Initial pilot projects showed the potential for analysis of extracranial tumors. CONCLUSION: The use of SRH provides a near real-time diagnosis with high diagnostic accuracy and provides further developmental potential to improve personalized tumor surgery.

Implementation of a portable diffraction phase microscope for digital histopathology.

Quantitative phase imaging (QPI) has a significant advantage in histopathology as it helps in differentiating biological tissue structures and cells without the need for staining. To make this capability more accessible, it is crucial to develop compact and portable systems. In this study, we introduce a portable diffraction phase microscopy (DPM) system that allows the acquisition of phase map images from various organs in mice using a low-NA objective lens. Our findings indicate that the cell and tissue structures observed in portable DPM images are similar to those seen in conventional histology microscope images. We confirmed that the developed system's performance is comparable to the benchtop DPM system. Additionally, we investigate the potential utility of digital histopathology by applying deep learning technology to create virtual staining of DPM images.

Electron Microscopy Techniques for 3D Plant ER Imaging.

The endoplasmic reticulum (ER) forms an extensive network in plant cells. In leaf cells and vacuolated root cells it is mainly restricted to the cortex, whereas in the root meristem the cortical and cytoplasmic ER takes up a large volume throughout the entire cell. Only 3D electron microscopy provides sufficient resolution to understand the spatial organization of the ER in the root. Here we present two protocols for 3D EM imaging of the ER across a range of scales. For large-scale ER structure analysis, we describe selective ER staining with ZIO that allows for automated or semi-automated ER segmentation. For smaller regions of ER, we describe high-pressure freezing, which enables almost instantaneous fixation of plant tissues but without organelle specific staining. These fixation and staining techniques are suitable for a range of imaging modalities, including serial sections, array tomography, serial block face-scanning electron microscopy (SBF-SEM), or focused ion beam (FIB) SEM.

Automated Segmentation and 3D Reconstruction of Different Membranes from Confocal Z-Stacks.

Confocal laser scanning microscopy (CLSM) is an advanced microscopy technique based on fluorescence technology which produces sharp images of a specimen in a single focal plane. The optical sectioning by CLSM allows to have z-stacks which can be further processed into 3D reconstructions. These then provide the option of variable perspectives and additional precise data evaluation on structural and anatomical alterations. Here, we used CLSM to image the thylakoids of cyanobacteria and the endoplasmic reticulum (ER) in moss protonemata as an example. Then, out of the confocal z-stacks, we create 3D constructions of the membranes and their alterations to present a holistic, structural view from different angles.

[Effects of upstream laboratory processes on the digitization of histological slides]. / Auswirkungen vorgeschalteter Laborprozesse auf die Digitalisierung histologischer Schnittpräparate.

BACKGROUND: Several factors in glass slide (GS) preparation affect the quality and data volume of a digitized histological slide. In particular, reducing contamination and selecting the appropriate coverslip have the potential to significantly reduce scan time and data volume. GOALS: To objectify observations from our institute's digitization process to determine the impact of laboratory processes on the quality of digital histology slides. MATERIALS AND METHODS: Experiment 1: Scanning the GS before and after installation of a central console in the microtomy area to reduce dirt and statistical analysis of the determined parameters. Experiment 2: Re-coverslipping the GS (post diagnostics) with glass and film. Scanning the GS and statistical analysis of the collected parameters. CONCLUSION: The targeted restructuring in the laboratory process leads to a reduction of GS contamination. This causes a significant reduction in the amount of data generated and scanning time required for the digitized sections. Film as a coverslip material minimizes processing errors in contrast to glass. According to our estimation, all the above-mentioned points lead to considerable cost savings.

The use of scanning electron microscopy and fixation methods to evaluate the interaction of blood with the surfaces of medical devices.

Testing the hemocompatibility of medical devices after their interaction with blood entails the need to evaluate the activation of blood elements and the degree of their coagulation and adhesion to the device surface. One possible way to achieve this is to use scanning electron microscopy (SEM). The aim was to develop a novel SEM-based method to assess the thrombogenic potential of medical devices and their adhesiveness to blood cells. As a part of this task, also find a convenient procedure of efficient and non-destructive sample fixation for SEM while reducing the use of highly toxic substances and shortening the fixation time. A polymeric surgical mesh was exposed to blood so that blood elements adhered to its surface. Such prepared samples were then chemically fixed for a subsequent SEM measurement; a number of fixation procedures were tested to find the optimal one. The fixation results were evaluated from SEM images, and the degree of blood elements' adhesion was determined from the images using ImageJ software. The best fixation was achieved with the May-Grünwald solution, which is less toxic than chemicals traditionally used. Moreover, manipulation with highly toxic osmium tetroxide can be avoided in the proposed procedure. A convenient methodology for SEM image analysis has been developed too, enabling to quantitatively evaluate the interaction of blood with the surfaces of various medical devices. Our method replaces the subjective assessment of surface coverage with a better-defined procedure, thus offering more precise and reliable results.

Prevalence of drifting osteons distinguishes human bone.

The histological, or microscopic, appearance of bone tissue has long been studied to identify species-specific traits. There are several known histological characteristics to discriminate animal bone from human, but currently no histological characteristic that has been consistently identified in human bone exclusive to other mammals. The drifting osteon is a rare morphotype found in human long bones and observationally is typically absent from common mammalian domesticates. We surveyed previously prepared undecalcified histological sections from 25 species (human n = 221; nonhuman primate n = 24; nonprimate n = 169) to see if 1) drifting osteons were indeed more common in humans and 2) this could be a discriminating factor to identify human bone histologically. We conclude that drifting osteons are indeed more prevalent in human and nonhuman primate bone relative to nonprimate mammalian bone. Two criteria identify a rib or long bone fragment as human, assuming the fragment is unlikely to be from a nonhuman primate given the archaeological context: 1) at least two drifting osteons are present in the cross-section and 2) a drifting osteon prevalence (or as a percentage of total secondary osteons) of ≥ 1%. We present a quantitative histological method that can positively discriminate human bone from nonprimate mammalian bone in archaeological contexts.

Compartments in medulloblastoma with extensive nodularity are connected through differentiation along the granular precursor lineage.

Medulloblastomas with extensive nodularity are cerebellar tumors characterized by two distinct compartments and variable disease progression. The mechanisms governing the balance between proliferation and differentiation in MBEN remain poorly understood. Here, we employ a multi-modal single cell transcriptome analysis to dissect this process. In the internodular compartment, we identify proliferating cerebellar granular neuronal precursor-like malignant cells, along with stromal, vascular, and immune cells. In contrast, the nodular compartment comprises postmitotic, neuronally differentiated malignant cells. Both compartments are connected through an intermediate cell stage resembling actively migrating CGNPs. Notably, we also discover astrocytic-like malignant cells, found in proximity to migrating and differentiated cells at the transition zone between the two compartments. Our study sheds light on the spatial tissue organization and its link to the developmental trajectory, resulting in a more benign tumor phenotype. This integrative approach holds promise to explore intercompartmental interactions in other cancers with varying histology.

Protocol to study immunodynamics in the tumor microenvironment using a tyramide signal amplification-based immunofluorescent multiplex panel.

Immunodynamics in the tumor microenvironment can be precisely examined by using multiple antigen identification approaches. Here, we present a protocol for capturing expression levels of multiple target proteins in the same specimen at single-cell resolution using a tyramide signal amplification-based immunofluorescent multiplexing system. We describe steps for tumor tissue microarray preparation, multiplex immunohistochemistry staining, image acquisition, and quantification. This protocol can quantify immune cells in tissues from patients or experimental disease models at a protein level. For complete details on the use and execution of this protocol, please refer to Chung et al. (2023),1 Tang et al. (2022),2 and Tang et al. (2022).3.

A twin convolutional neural network with hybrid binary optimizer for multimodal breast cancer digital image classification.

There is a wide application of deep learning technique to unimodal medical image analysis with significant classification accuracy performance observed. However, real-world diagnosis of some chronic diseases such as breast cancer often require multimodal data streams with different modalities of visual and textual content. Mammography, magnetic resonance imaging (MRI) and image-guided breast biopsy represent a few of multimodal visual streams considered by physicians in isolating cases of breast cancer. Unfortunately, most studies applying deep learning techniques to solving classification problems in digital breast images have often narrowed their study to unimodal samples. This is understood considering the challenging nature of multimodal image abnormality classification where the fusion of high dimension heterogeneous features learned needs to be projected into a common representation space. This paper presents a novel deep learning approach combining a dual/twin convolutional neural network (TwinCNN) framework to address the challenge of breast cancer image classification from multi-modalities. First, modality-based feature learning was achieved by extracting both low and high levels features using the networks embedded with TwinCNN. Secondly, to address the notorious problem of high dimensionality associated with the extracted features, binary optimization method is adapted to effectively eliminate non-discriminant features in the search space. Furthermore, a novel method for feature fusion is applied to computationally leverage the ground-truth and predicted labels for each sample to enable multimodality classification. To evaluate the proposed method, digital mammography images and digital histopathology breast biopsy samples from benchmark datasets namely MIAS and BreakHis respectively. Experimental results obtained showed that the classification accuracy and area under the curve (AUC) for the single modalities yielded 0.755 and 0.861871 for histology, and 0.791 and 0.638 for mammography. Furthermore, the study investigated classification accuracy resulting from the fused feature method, and the result obtained showed that 0.977, 0.913, and 0.667 for histology, mammography, and multimodality respectively. The findings from the study confirmed that multimodal image classification based on combination of image features and predicted label improves performance. In addition, the contribution of the study shows that feature dimensionality reduction based on binary optimizer supports the elimination of non-discriminant features capable of bottle-necking the classifier.

Oculomotor inhibition markers of working memory load.

Involuntary eye movements occur constantly even during fixation and were shown to convey information about cognitive processes. They are inhibited momentarily in response to external stimuli (oculomotor inhibition, OMI), with a time and magnitude that depend on stimulus saliency, attention, and expectations. It was recently shown that the working memory load for numbers modulates the microsaccade rate; however, the generality of the effect and its temporal properties remain unclear. Our goal was to investigate the relationship between OMI and the working memory load for simple colored shapes. Participants (N = 26) maintained their fixation while their eyes were tracked; they viewed briefly flashed colored shapes accompanied by small arrows indicating the shapes to be memorized (1/2/3). After a retention period, a probe shape appeared for matching. The microsaccade rate modulation and temporal properties were analyzed for the memory encoding, maintenance, and retrieval phases. Microsaccade inhibition was stronger when more shapes were memorized, and performance improved when microsaccades were suppressed during maintenance and retrieval. This occurred even though the physical stimuli were identical in number under all conditions. Thus, oculomotor inhibition may play a role in silencing the visual input while processing current stimuli and is generally related to processing time and load.

Idiopathic Slow Transit Constipation: Pathophysiology, Diagnosis, and Management.

Slow transit constipation (STC) has an estimated prevalence of 2-4% of the general population, and although it is the least prevalent of the chronic constipation phenotypes, it more commonly causes refractory symptoms and is associated with significant psychosocial stress, poor quality of life, and high healthcare costs. This review provides an overview of the pathophysiology, diagnosis, and management options in STC. STC occurs due to colonic dysmotility and is thought to be a neuromuscular disorder of the colon. Several pathophysiologic features have been observed in STC, including reduced contractions on manometry, delayed emptying on transit studies, reduced numbers of interstitial cells of Cajal on histology, and reduced amounts of excitatory neurotransmitters within myenteric plexuses. The underlying aetiology is uncertain, but autoimmune and hormonal mechanisms have been hypothesised. Diagnosing STC may be challenging, and there is substantial overlap with the other clinical constipation phenotypes. Prior to making a diagnosis of STC, other primary constipation phenotypes and secondary causes of constipation need to be ruled out. An assessment of colonic transit time is required for the diagnosis and can be performed by a number of different methods. There are several different management options for constipation, including lifestyle, dietary, pharmacologic, interventional, and surgical. The effectiveness of the available therapies in STC differs from that of the other constipation phenotypes, and prokinetics often make up the mainstay for those who fail standard laxatives. There are few available management options for patients with medically refractory STC, but patients may respond well to surgical intervention. STC is a common condition associated with a significant burden of disease. It can present a clinical challenge, but a structured approach to the diagnosis and management can be of great value to the clinician. There are many therapeutic options available, with some having more benefits than others.

Bioadhesive behaviors of HPMC E5: comparative analysis of various techniques, histological and human radiological evidence.

Enhancing drug residence duration within the stomach offers distinct advantages for both localized and systemic effects. Numerous strategies have been proposed to extend drug residence time, with mucoadhesive polymers being a notable avenue. In this context, hydroxypropyl methylcellulose E5 has been employed as both a binding agent for granulating contrast metal powder and a mucoadhesive polymer, spanning various concentrations. The in vitro bioadhesion strength of the formulated tablets was gauged against the stomach lining of rabbits, for the quantification of bioadhesive forces. The temporal aspect of bioadhesion was evaluated through two approaches: one centered on gastric fluid dynamics and another proffered by the researchers, focusing on gastric wall kinetics. The results divulged a decline in bioadhesion force concomitant with high polymer concentrations. Histological examination of stained stomach sections revealed mucosal perturbations within the rabbit stomach. These disruptions exhibited an escalating trend in conjunction with elevated polymer concentrations, culminating in extensive disturbance at a 7.5% polymer concentration. The outcomes unveiled a direct relationship between polymer concentration increments and extended contact time. Subsequent radiological tracking of contrast metal behavior within a mature human stomach indicated a residence time of 6 h due to the entrapment of displaced components at disparate locations.