Microscopy Image Analysis Research Articles

Pore scale investigation of chelating agents flooding for enhanced oil recovery

Recently, laboratory tests have shown a positive response to chelating agent brines in sandstone and carbonate reservoirs as a new enhanced oil recovery technique. There is little research on direct and visual evidence of underlying mechanisms behind the chelating agent effects. In this study, a microfluidic method was established using glass micromodel to investigate the micro-mechanisms of displacement under ethylenediaminetetraacetic acid (EDTA) and diethylenetriaminepentaacetic acid (DTPA) chelating agent at the pore-scale level. Furthermore, for the study of fluid/fluid interactions, EDTA brine and DTPA brine were brought into contact with two different crude oils to examine the possible compositional changes. For this purpose, sample tests, Fourier Transform Infrared Spectroscopy (FTIR), microscopic image analysis, and dynamic interfacial tension (IFT) measurements were conducted. The FTIR data showed EDTA brine and DTPA brine induced changes in the oil sample composition compared to seawater, which can be related to the formation of water-in-oil micro-dispersions. Microscopic image analysis on samples confirmed the formation of these micro-dispersions. The visual study by the micromodel demonstrated the micro-dispersion formation in the tertiary injection of EDTA and DTPA brine. Based on the observation made, the pore-scale mechanisms of chelating agent flooding involve the chelating agent brine penetrating the crude oil, resulting in micro-dispersion formation. These micro-dispersions tend to alter wettability to a more water-wet state, facilitate oil detachment from the surface, redistribution of oil saturation, and thus leading to improved oil recovery. The observed IFT reduction aids the penetration of EDTA and DTPA brine into the crude oil to form micro-dispersions.

Image‐based hybrid model incorporating initial spatial distribution for mesenchymal stem cell cultivation process design

AbstractThis work presents an image‐based hybrid model incorporating the initial spatial distribution for mesenchymal stem cell (MSC) cultivation process design. First, three levels of seeding bias in static MSC cultivation were experimentally investigated, and the resulting initial distribution was quantified using phase contrast microscopy image analysis. Second, the observed spatial heterogeneity was defined as a new parameter by calculating the standard deviation of the seeded cell number fraction among numerical 8 × 8 tiles on two‐dimensional plates. Third, the parameter was incorporated into kinetic models to consider spatial growth limitation. The model was then applied to simulate MSC cultivation processes with experimental data. Using dynamic and stochastic simulation outputs, feasible ranges of cell‐harvesting time could be determined to satisfy a given requirement for the minimum cell number and acceptable confluency level. The developed hybrid model could serve as a basis for quantitative decision‐making in the design of MSC cultivation processes.

Effect of asphaltene flocculation size on deposition using a modified quartz crystal microbalance in-house setup and microscopic image analysis: Model oil, inhibitory and nanoparticle solutions case studies

Asphaltene deposition phenomenon is a challenging event that may occur during the oil production process, causing difficulties such as formation damage and wettability alteration. To overcome these challenges, inhibitors and nanoparticles are commonly used as treatments. The size of asphaltene flocculation is a critical factor in the deposition process. In this study, we investigated the effect of asphaltene flocculation size on deposition using the quartz crystal microbalance (QCM) method in both model oil and inhibitory solutions containing Linear alkylbenzene (LABs), Sodium laureth sulfate (SLES), and 4-Dodecylbenzenesulfonic (DBSA), as well as solutions with nanoparticles such as TiO2 and SiO2. A novel in-house setup was designed to overcome experimental challenges and microscopic images were used as a visual approach for better interpretation of results. Our findings showed that TiO2 and SLES had the greatest performance in postponing flocculation points among nanoparticles and inhibitory solutions, respectively. We also observed that inhibitors were more effective in delaying the flocculation point as the concentration of heptane in the model oil decreased, with a weakened effect at higher heptane concentrations. Based on the interaction of forces, we obtained an average surface area of 17.5 square micrometres as the required value for aggregate deposition. Furthermore, inhibitory solutions showed a much lower growth rate and smaller aggregates compared to normal solutions.

Jute Fiber Reinforced Biocomposite: Towards Developing Composite Bone Plate

Bone fractures are often treated with metallic bone plates which are inherited some fundamental issues such as stress shielding, bone atrophy, heavyweight, corrosion, and so on. This work aims to develop a jute epoxy composite to investigate its feasibility to use as a composite bone plate. In this work, the natural fiber-based composite made of jute extracted from the jute plant and epoxy resin obtained from LAPOX® METALAM - B is studied experimentally. The mechanical properties such as tensile, compressive, and bending strength of jute/epoxy composite were measured using the universal testing machine (UTM). Moisture absorption test and scanning electron microscope (SEM) image analysis were also performed. The preliminary results suggest that the jute/epoxy composite could be a potential material for a composite bone plate. However, further detailed studies are required to confirm its applicability as a composite bone plate.

Enhanced dielectric, ferroelectric and piezoelectric properties of lead-free (Ba,Ca)(Sn,Ti)O3 ceramics by optimisation of sintering temperature

Lead-zirconate-titanate [Pb(Zr,Ti)O3 PZT] crystals possess superior ferroelectric, dielectric and piezoelectric properties. However, due to the toxicity of lead there is a demand for lead-free alternatives. In the present work, we focus on the production of the lead-free (Ba,Ca)(Sn,Ti)O3 (BCST) ceramics via solid-state synthesis method. BCST ceramics calcined at 1050°C, 1100°C, 1150°C, 1200°C and 1250°C were characterized using XRD analysis which showed that at temperatures above 1150°C the structure was free from impurities. Rietveld refinements confirmed a tetragonal structure with P4mm space group for the material calcined at 1150°C. Scanning electron microscopy image analysis of samples sintered at 1200°C, 1250°C and 1300°C showed an increase in grain size and density with temperature. The material sintered at 1300°C had a higher dielectric constant compared to other ceramics. A larger grain size facilitated high ferroelectric polarisation (3.38 μC/cm2), dielectric constant (6100) and d33 piezoelectric coefficient (236 pC/N) for the ceramics. This study demonstrates the potential for using lead-free BCST ceramics for device applications, such as piezoelectric actuators, transducers and ultrasonic motors.

ADVANCED ELECTRON MICROSCOPY IMAGE PROCESSING FOR ANALYZING AMORPHOUS ALLOYS: ELECTRON MICROSCOPY IMAGE CLUSTER ANALYZER (EMICA). TOOL AND RESULTS

This article unveils EMICA, a Python-based software tool revolutionizing electron microscopy image processing for amorphous alloys. EMICA addresses the unique challenges posed by these materials, which lack long-range order, by providing specialized capabilities for cluster analysis and spatial pattern recognition. This research explored software tool development and application through illustrative examples, answering the key question of how they enhance amorphous alloy analysis. By integrating advanced image processing techniques and algorithms, EMICA uncovers hidden patterns, offering quantitative insights into cluster distributions. The key message emphasizes the application's transformative impact on material science research, providing a specialized solution for electron microscopy image analysis in the amorphous alloy domain. Our key findings, presented through real-world examples and case studies, attest to the efficacy of the software in revealing nuanced details of amorphous alloy structures. From identifying subtle variations in atomic configurations to quantifying cluster distributions, EMICA represents a significant leap forward in the field of advanced electron microscopy image processing, contributing significantly to the advancement of this domain.

SC-Track: a robust cell-tracking algorithm for generating accurate single-cell lineages from diverse cell segmentations.

Computational analysis of fluorescent timelapse microscopy images at the single-cell level is a powerful approach to study cellular changes that dictate important cell fate decisions. Core to this approach is the need to generate reliable cell segmentations and classifications necessary for accurate quantitative analysis. Deep learning-based convolutional neural networks (CNNs) have emerged as a promising solution to these challenges. However, current CNNs are prone to produce noisy cell segmentations and classifications, which is a significant barrier to constructing accurate single-cell lineages. To address this, we developed a novel algorithm called Single Cell Track (SC-Track), which employs a hierarchical probabilistic cache cascade model based on biological observations of cell division and movement dynamics. Our results show that SC-Track performs better than a panel of publicly available cell trackers on a diverse set of cell segmentation types. This cell-tracking performance was achieved without any parameter adjustments, making SC-Track an excellent generalized algorithm that can maintain robust cell-tracking performance in varying cell segmentation qualities, cell morphological appearances and imaging conditions. Furthermore, SC-Track is equipped with a cell class correction function to improve the accuracy of cell classifications in multiclass cell segmentation time series. These features together make SC-Track a robust cell-tracking algorithm that works well with noisy cell instance segmentation and classification predictions from CNNs to generate accurate single-cell lineages and classifications.

Abstract 5226: A 3D ECM embedded tumoroid platform for testing antibody drugs and engineered TCRs for immune oncology

Abstract We developed a screening platform for immune oncology using an assay based on automated image guided injection of tumoroids in wells of multi-well plates preloaded with a collagen-rich ECM. The identical x-y-z position and size of the ECM-embedded tumoroids in each well facilitates automated real time confocal microscopy and quantitative image analysis algorithms. The model is used to generate quantitative data for T cell recruitment to tumoroids and killing of tumoroids by T cells. We have applied this to screening a panel of CD3:Her2 bispecific antibodies (BsAb) binding with different affinities to CD3 or Her2 or displaying high affinity interactions with different epitopes on Her2. Exposure to fresh, non-activated peripheral blood mononuclear cell (PBMC) derived T cells shows an initial phase of random T cell movement throughout the ECM followed by a BsAb-dependent phase of active T cell recruitment to tumoroids (day 2-4) and a subsequent phase of tumoroid killing (day 4-6). We show that the wave of T cell recruitment following initial T cell-tumoroid contact involves chemotactic signaling. Decreased affinity at the Her2 or CD3 arm can be compensated for by increasing BsAb concentrations. However, we detect major differences in efficacy for different high affinity epitopes. I.e., of two BsAbs interacting with high affinity with distinct Her2 epitopes and each causing effective tumor cell killing in 2D co-culture, only one was able to trigger a wave of T cell recruitment and subsequent tumoroid killing in 3D. We have applied the same setup to testing the efficacy of T cells expressing engineered TCRs aimed at application in adoptive T-cell therapy. Kinetics of experiments using these activated engineered T cells are considerably shorter (24 hours instead of ~6 days) but show a similar pattern of T cell recruitment and subsequent tumoroid killing. We demonstrate successful generation of quantitative data for T cell recruitment and tumoroid killing for engineered T cells targeting tumor antigens expressed on TNBC and uveal melanoma tumoroids. Citation Format: Erik H. J. Danen. A 3D ECM embedded tumoroid platform for testing antibody drugs and engineered TCRs for immune oncology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5226.

Abstract 737: Arrays of 3D ECM-embedded fibroblast clusters for characterization of ECM remodeling by primary cancer associated fibroblasts and for evaluation of drugs attenuating fibrotic ECM remodeling

Abstract Chronic fibrosis can lead to organ failure and is also associated with cancer, where the tumor is interpreted as a chronic wound, and the fibrotic tumor environment drives disease progression. Fibrosis occurs in an inflammatory environment where macrophages are activated, and fibroblasts transdifferentiate into myofibroblasts. Activated macrophages stimulate the myofibroblasts to produce excessive amounts of collagen-rich ECM. Changes in proteolytic activity and high contractile forces that myofibroblasts apply onto their tissue environment, further lead to extensive remodeling of the healthy tissue matrix into a scar matrix. Similar activity is displayed by cancer-associated fibroblasts (CAFs) in tumors. Intervening with the excessive ECM remodeling by activated fibroblasts represents a candidate therapeutic strategy to normalize the architecture of fibrotic and malignant tissues. We developed a screening platform using an assay based on automated image guided injection of clusters of fibroblasts in wells of multi-well plates preloaded with a collagen-rich ECM network. The identical x-y-z position, spacing, and size of the ECM-embedded fibroblast clusters in each well facilitates automated real time confocal microscopy and quantitative image analysis algorithms. We use this setup for automated quantitative analysis of ECM remodeling activity of CAFs obtained from early-stage colorectal cancer patients. We find that CAFs from these early-stage lesions display increased ECM remodeling capacity as compared to patient matched normal fibroblasts. We then use the same setup to screen a series of compounds for their ability to attenuate ECM remodeling triggered by TGFb-activated primary human fibroblasts. We detect known and novel pathways, and we identify small molecule inhibitors with a promising efficacy versus toxicity profile. Lastly, we detect a previously unknown concentration-dependent side effect of ALK5 inhibitors that leads to the identification of a novel profibrotic pathway and indicates that caution is warranted for the clinical application of ALK5 inhibitors. Citation Format: Erik H. J. Danen. Arrays of 3D ECM-embedded fibroblast clusters for characterization of ECM remodeling by primary cancer associated fibroblasts and for evaluation of drugs attenuating fibrotic ECM remodeling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 737.

Collaborative Optimization Design of Self-Powered Sterilizer with Highly Efficient Synergistic Antibacterial Effect.

The development of self-powered sterilizers has garnered significant attention in the scientific and engineering fields. However, there remains an urgent need to improve their sterilization efficiency. In this study, we present a self-powered sterilizer with superior antibacterial capability by maximizing the utilization of breakdown discharge generated by a soft-contact freestanding rotary triboelectric nanogenerator (FR-TENG). To achieve this, a collaborative optimization strategy is proposed, encompassing the structural design of the FR-TENG, the implementation of double voltage rectification, and manipulation of the gaseous phase. Through a comprehensive analysis of antibacterial rates and microscopic images, the effectiveness of the self-powered sterilizer against various types of bacteria, including Gram-positive and Gram-negative species, as well as mixed bacteria in natural seawater, is demonstrated. Further investigations into bacterial morphologies and solution compositions reveal that the synergistic effect between electroporation and the generation of reactive oxygen/nitrogen species contributes to efficient sterilization. Additionally, controlled trials and molecular dynamics simulations are conducted to quantitatively elucidate the synergistic antibacterial effect between electroporation and reactive oxygen/nitrogen species. This study highlights the effectiveness of the collaborative optimization strategy in enhancing the sterilization efficiency of self-powered sterilizers while providing valuable insights into the synergistic antibacterial mechanisms of physical and chemical sterilization.

Investigation of type, size, and dosage effects of superabsorbent polymers on the hydration development of high-performance cementitious materials

The low water-to-binder ratio commonly used for high-performance cementitious materials is known to limit the degree of hydration of their cement particles. This issue often cannot be resolved with conventional external curing methods, primarily because of the low permeability of such materials. Thus, internal curing methods are devised to improve the degree of hydration and maximize the use of cement particles. Focusing on superabsorbent polymers (SAPs) as one of the main internal curing agents, this study investigates the effects of various types, sizes, and dosages of SAPs on the hydration kinetics of high-performance cementitious mixtures. For this purpose, the main performance characteristics of SAPs were characterized first. Paired with monitoring the temperature development patterns in a set of SAP-contained mixtures, thermogravimetric analyses (TGA) and X-ray diffractometry (XRD) investigations were systematically performed to measure the phase consumption of cement particles. Scanning electron microscope (SEM) image analyses were then employed to assess the materials deposited in the remaining SAP voids. By providing original insights into the hydration development process, this study’s outcome guides the use of SAPs with the ultimate goal of maximizing the hydration degree of cement particles, paving the way to minimizing the carbon footprint of high-performance cementitious materials.

Selective damage induced by pigment-medium interactions in a Neoplasticist oil canvas painting: Composition dans le cône avec couleur orange by G. Vantongerloo (1929)

This research focuses on the study of pigment-medium interactions in the film forming, ageing and degradation mechanisms of modern white oil paints observed in the Neoplasticist painting Composition dans le cône avec couleur orange by G. Vantongerloo (1929), conserved in the Institut Valencià d’Art Modern (IVAM). The observation of selective vertical cracks and the significant presence of protrusions in the painting suggested that the observed degradation phenomena were specific to the coloured area. To understand the composition of pigments governing the film formation processes and later degradation phenomena in the oil paint films, a hybrid experimental approach was taken, aimed at understanding the physical, chemical and mechanical mechanisms involved. For this purpose, digital portable microscopy and multiband imaging analyses were carried out. Furthermore, the technical study involved the use of micro-invasive analysis such as μ-Raman, ATR-FTIR spectroscopy and GC–MS analysis for a more comprehensive understanding of the nature of the binding media and products resulting from the auto-oxidation, film-forming, hydrolysis, and degradation processes of the lipidic binding media. The results obtained suggest that on-going degradation phenomena are closely linked to the chemical interaction between pigment and binding medium.

Evaluation of Rock Burstability with Mechanical Property Testing and Microscopic Image Analysis

Evaluation of Rock Burstability with Mechanical Property Testing and Microscopic Image Analysis

The rise of data-driven microscopy powered by machine learning.

Optical microscopy is an indispensable tool in life sciences research, but conventional techniques require compromises between imaging parameters like speed, resolution, field of view and phototoxicity. To overcome these limitations, data-driven microscopes incorporate feedback loops between data acquisition and analysis. This review overviews how machine learning enables automated image analysis to optimise microscopy in real time. We first introduce key data-driven microscopy concepts and machine learning methods relevant to microscopy image analysis. Subsequently, we highlight pioneering works and recent advances in integrating machine learning into microscopy acquisition workflows, including optimising illumination, switching modalities and acquisition rates, and triggering targeted experiments. We then discuss the remaining challenges and future outlook. Overall, intelligent microscopes that can sense, analyse and adapt promise to transform optical imaging by opening new experimental possibilities.

Deep learning for three-dimensional segmentation of electron microscopy images of complex ceramic materials

The microstructure is a critical factor governing the functionality of ceramic materials. Meanwhile, microstructural analysis of electron microscopy images of polycrystalline ceramics, which are geometrically complex and composed of countless crystal grains with porosity and secondary phases, has generally been performed manually by human experts. Objective pixel-based analysis (semantic segmentation) with high accuracy is a simple but critical step for quantifying microstructures. In this study, we apply neural network-based semantic segmentation to secondary electron images of polycrystalline ceramics obtained by three-dimensional (3D) imaging. The deep-learning-based models (e.g., fully convolutional network and U-Net) by employing a dataset based on a 3D scanning electron microscopy with a focused ion beam is found to be able to recognize defect structures characteristic of polycrystalline materials in some cases due to artifacts in electron microscopy imaging. Owing to the training images with improved depth accuracy, the accuracy evaluation function, intersection over union (IoU) values, reaches 94.6% for U-Net. These IoU values are among the highest for complex ceramics, where the 3D spatial distribution of phases is difficult to locate from a 2D image. Moreover, we employ the learned model to successfully reconstruct a 3D microstructure consisting of giga-scale voxel data in a few minutes. The resolution of a single voxel is 20 nm, which is higher than that obtained using a typical X-ray computed tomography. These results suggest that deep learning with datasets that learn depth information is essential in 3D microstructural quantifying polycrystalline ceramic materials. Additionally, developing improved segmentation models and datasets will pave the way for data assimilation into operando analysis and numerical simulations of in situ microstructures obtained experimentally and for application to process informatics.

Effects of Multi-Walled Carbon Nanotubes and Recycled Fine Aggregates on the Multi-Generational Cycle Properties of Reactive Powder Concrete

In order to investigate the effect of multi-walled carbon nanotubes (MWCNTs) on the recyclable properties of multi-generation recycled concrete, the physical properties of multi-generation recycled fine aggregate and the mechanical properties of multi-generation recycled concrete with different dosages of MWCNTs were tested, and the enhancement mechanism was analyzed by scanning electron microscopy (SEM). The results showed that the apparent density of multi-generation recycled fine aggregate with 0.05 wt% MWCNTs was increased by 1.04~2.03%, the crushing value was decreased by 38.21~49.45%, the compressive strength of the concrete prepared by it was increased by 11.11~18.96%, the splitting tensile strength was increased by 10~43.94%, the flexural strength was increased by 13.62~22.23%, and the mechanical properties were analyzed by scanning electron microscopy (SEM). Combined with the scanning electron microscope image analysis, the MWCNTs can fill the pores inside the specimen, bridge the cracks, and retard the decrease in concrete strength after multi-generation recycling.

Piperine, a phytochemical prevents the biofilm city of methicillin-resistant Staphylococcus aureus: A biochemical approach to understand the underlying mechanism

Methicillin-resistant Staphylococcus aureus (MRSA), a drug-resistant human pathogen causes several nosocomial as well as community-acquired infections involving biofilm machinery. Hence, it has gained a wide interest within the scientific community to impede biofilm-induced MRSA-associated health complications. The current study focuses on the utilization of a natural bioactive compound called piperine to control the biofilm development of MRSA. Quantitative assessments like crystal violet, total protein recovery, and fluorescein-di-acetate (FDA) hydrolysis assays, demonstrated that piperine (8 and 16 μg/mL) could effectively compromise the biofilm formation of MRSA. Light and scanning electron microscopic image analysis confirmed the same. Further investigation revealed that piperine could reduce extracellular polysaccharide production by down-regulating the expression of icaA gene. Besides, piperine could reduce the cell-surface hydrophobicity of MRSA, a crucial factor of biofilm formation. Moreover, the introduction of piperine could interfere with microbial motility indicating the interaction of piperine with the quorum-sensing components. A molecular dynamics study showed a stable binding between piperine and AgrA protein (regulator of quorum sensing) suggesting the possible meddling of piperine in quorum-sensing of MRSA. Additionally, the exposure to piperine led to the accumulation of intracellular reactive oxygen species (ROS) and potentially heightened cell membrane permeability in inhibiting microbial biofilm formation. Besides, piperine could reduce the secretion of diverse virulence factors from MRSA. Further exploration revealed that piperine interacted with extracellular DNA (e-DNA), causing disintegration by weakening the biofilm architecture. Conclusively, this study suggests that piperine could be a potential antibiofilm molecule against MRSA-associated biofilm infections.

The spatial organization of sphingofungin biosynthesis in Aspergillus fumigatus and its cross-interaction with sphingolipid metabolism.

Sphingofungins are sphinganine analog mycotoxins acting as inhibitors of serine palmitoyl transferases, enzymes responsible for the first step in the sphingolipid biosynthesis. Eukaryotic cells are highly organized with various structures and organelles to facilitate cellular processes and chemical reactions, including the ones occurring as part of the secondary metabolism. We studied how sphingofungin biosynthesis is compartmentalized in the human-pathogenic fungus Aspergillus fumigatus, and we observed that it takes place in the endoplasmic reticulum (ER), ER-derived vesicles, and the cytosol. This implies that sphingofungin and sphingolipid biosynthesis colocalize to some extent. Automated analysis of confocal microscopy images confirmed the colocalization of the fluorescent proteins. Moreover, we demonstrated that the cluster-associated aminotransferase (SphA) and 3-ketoreductase (SphF) play a bifunctional role, supporting sphingolipid biosynthesis, and thereby antagonizing the toxic effects caused by sphingofungin production.IMPORTANCEA balanced sphingolipid homeostasis is critical for the proper functioning of eukaryotic cells. To this end, sphingolipid inhibitors have therapeutic potential against diseases related to the deregulation of sphingolipid balance. In addition, some of them have significant antifungal activity, suggesting that sphingolipid inhibitors-producing fungi have evolved mechanisms to escape self-poisoning. Here, we propose a novel self-defense mechanism, with cluster-associated genes coding for enzymes that play a dual role, being involved in both sphingofungin and sphingolipid production.

Unveiling the Radiative Electron-Hole Recombination of MoS2 Nanostructures at Extreme pH Conditions.

Nanostructures of MoS2 are in wide research for optoelectronic, energy and biological applications. Opto-electronic and biological applications requires the tuning of photoluminescence properties of MoS2 nanostructures. In this article, nanosized MoS2 is hydrothermally synthesized, and photoluminescence at extreme pH conditions (pH 1 and 13) is examined. As the photoluminescence gives a key to probe the radiative electron-hole recombination, here, photoluminescence emissions are used as an indicator to suggest the pattern of electron-hole recombination in the material at extreme pH conditions. Raman spectroscopy, dynamic light scattering, Scanning electron microscopic image and energy dispersive x-ray analysis are done for material confirmation. At pH 1 and 13 as-synthesized nanostructured MoS2 exhibited both upconversion and downconversion photoluminescence. The intensity of photoluminescence is varied with respect to pH. Excitation-dependent photoluminescence mechanisms and preliminary understanding on the ratio of quantum yields and life span of excited state of as-synthesized nanostructured MoS2 are unveiled here.

Blueprints from plane to space: outlook of next-generation three-dimensional histopathology.

Here, we summarize the literature relevant to recent advances in three-dimensional (3D) histopathology in relation to clinical oncology, highlighting serial sectioning, tissue clearing, light-sheet microscopy, and digital image analysis with artificial intelligence. We look forward to a future where 3D histopathology expands our understanding of human pathophysiology and improves patient care through cross-disciplinary collaboration and innovation.