Journal of Histotechnology最新文献

The incidence of lymphoma, a cancer that affects both humans and animals, has witnessed a significant increase. In response, immunohistochemistry (IHC) has become an essential tool for its classification. This prompted us to develop an innovative mathematical methodology for the precise quantification of immunopositive and immunonegative cells, along with their spatial analysis, in CD3-stained lymphoma IHC images. Our approach involves integrating an algorithm based on a mathematical color model for cell differentiation, employing the distinctive morphological erosion, algorithmic transformations, and customized histogram equalization to enhance features. Refined local thresholding enhances classification precision. Additionally, a customized circular Hough transform quantifies cell counts and assesses their spatial data. The algorithms accurately enumerate cell types, reducing human intervention and providing total numbers and spatial information on detected cells within tissue specimens. Evaluation of IHC image samples revealed an overall accuracy of 93.98% for automatic cell counts. The automatic counts and location information were cross-validated by three pathology specialists, highlighting the effectiveness and reliability of our automated approach. Our innovative framework enhances lymphoma cell counting accuracy in IHC images by combining physics-based color understanding with machine learning, thereby improving diagnosis and reducing the risks of human error.

Stains frequently performed to exclude infectious etiologies in esophagitis include Grocott methenamine silver (GMS) and periodic acid-Schiff (PAS) as well as immunohistochemistry (IHC) assays for cytomegalovirus (CMV) and herpes simplex virus (HSV). The diagnostic yield of these tests, in this situation, has not been well studied. We retrospectively reviewed 261 esophageal biopsies, which had one or more of the above tests performed. The diagnostic yield for GMS and PAS was 8%, while CMV and HSV immunohistochemistry had a diagnostic yield of 1% and 0%, respectively. Our study suggests that routine use of ancillary labeling techniques in esophagitis biopsies may be of limited utility and have low diagnostic yield.

Gliomas are malignant tumors of neuronal support cells within the central nervous system (CNS) and are characterized by poor overall prognoses and limited treatment options due to their infiltrative growth patterns. The neural tumor microenvironment, composed of benign neurons, neuroglia, endothelial cells, and intravascular white blood cells, is a target-rich site for potential chemotherapeutic agents. This study assessed cell proliferation rates, white blood cell components, and a limited number of nuclear, cytoplasmic, and membrane markers using immunohistochemistry (IHC) assays on formalin-fixed and paraffin-embedded benign and glial tumor tissue samples from the CNS. It was observed that glioma tissues had increased rates of glial cell proliferation and significant increases in the number of observed T-lymphocytes and granulocytes but decreased expression of markers Somatostatin receptor 2 (SSTR2), L1 cell adhesion molecule (L1CAM), and GATA binding protein 3 (GATA3) when compared to benign tissue samples. Understanding the lack of protein expression and population expansion potential of the glioma microenvironment in greater detail could help identify valuable therapeutic target combinations for future treatments.

High glucose-induced dysfunction of endothelial cells is a critical and initiating factor in the genesis of diabetic vascular complications. Low-magnitude high-frequency vibration (LMHFV) is a non-invasive biophysical intervention. It has been reported that it exhibits protective effects on high glucose-induced osteoblast dysfunction, but little was known on diabetic vascular complications. In this work, we aim to clarify the role of LMHFV on high glucose-induced endothelial dysfunction and hypothesized that the protective effects functioned through adenosine monophosphate-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR) pathway. We cultured primary murine aortic endothelial cells (MAECs) in normal or HG medium, respectively, before exposing to LMHFV. The tube formation, paracellular permeability assay, and aortic ring sprouting assay showed that the high glucose injured-function of MAECs was improved after LMHFV treatment. The intracellular ROS generation analysis, mitochondrial complex I activities measurement, ATP measurement and mitochondrial membrane potential (MMP), and mitochondrial ROS generation analysis of MAECs indicated that mitochondrial function was restored by LMHFV loading in a high glucose environment. Mechanically, western blot assays showed that AMPK phosphorylation was promoted and mTOR was inhibited in LMHFV-induced endothelial function restoration. After the administration of the AMPK inhibitor, Compound C, these protective effects resulting from LMHFV are reversed. These findings suggest that LMHFV plays a significant role in protecting endothelial cells' function and mitochondrial function in high glucose-induced injured MAECs via AMPK/mTOR signalling.

The HistoEnder, an inexpensive open-source 3D printer published as an automated histological slide stainer, has been adapted for conventional biological transmission electron microscopy (TEM) batch grid staining. Details are presented of the 3D printed apparatus, assembly, G-code programming, and operation on the 3D printer to post-section stains up to 20 grids through aqueous uranyl acetate, distilled water rinses, and lead stains. TEM Results are identical to manual staining with the advantages of automation using the low cost HistoEnder, apparatus, and equipment.

Organoids are in vitro tissue models derived from human or animal primary tissues or stem cells that allow for studying three-dimensional (3D) tissue biology, toxicity testing, biomarker evaluation, and assessment of compound efficacy, supplementing or potentially minimizing use of animal models. Organoids are typically cultured in a 3D format within an extracellular matrix and, at the end of an experiment, can be further processed for various cellular or molecular readouts. Analysis often relies on whole mount immunolabeling for markers of interest, which consumes the entire sample/well, thereby limiting sample availability for downstream assays. In addition, 3D cultures become more friable after fixation and are susceptible to sample loss during washing steps. In contrast, by fixing and processing organoids to a paraffin block, dozens or hundreds of unstained slides can be generated, enabling robust characterization via multiple assays, including histologic evaluation and (immuno)histochemical stains, thus maximizing the yield of these time- and labor-intensive cultures. Here we describe three methods to process 3D Matrigel cultures into paraffin blocks using Histogel as an embedding agent. The three techniques all yield high-quality sections but vary in complexity of implementation at different steps, and their application for different use cases is discussed.

Although many of the structures and organelles of vegetative cells are comparable to those of animal tissues, significant differences between the two kingdoms require modifications in histological techniques for both tissue processing steps and histochemical staining techniques. The authors investigated the challenges of working with plant tissues by collecting various flora to represent the four main plant organs: leaf, stem, root, and flower/fruit. Triplicate samples for each specimen were placed into formalin for paraffin embedding, placed into formalin for later frozen sections, and used fresh to undergo immediate frozen sectioning. Frozen sections of plant tissues were more difficult to obtain than formalin-fixed paraffin-embedded (FFPE) sections, exhibited tissue loss during staining, and were inferior morphologically to FFPE sections. Although, historically, plant tissue fixation and processing has employed several different reagents compared with those used in animal tissue processing and took significantly longer times, the current investigation determined reagents and protocols from a modern histology laboratory which processes mammalian tissues can be applied to plant tissue processing with only slight modifications in respect to reagent timing. Additionally, staining techniques were compared and while it is well known that plant cell walls stain well with safranin O, the current investigation determined the uptake of safranin O can be accelerated by incubating at 60°C.

Bone tissue poses critical roadblocks for spatial transcriptomics and molecular pathology due to a combination of its dense, calcified matrix and inadequate preservation of biomolecules in conventional decalcification. Decalcification is a complex and nuanced histological process to concomitantly preserve nucleic acids, proteins, and tissue architecture, ensuring molecular integrity for downstream assays. However, commonly used agents like formic and hydrochloric acids, while efficient, can degrade biomolecules to varying extents, complicating assays such as PCR, sequencing, immunohistochemistry, and in situ hybridization. Advances in spatial transcriptomics, both sequencing- and imaging-based, emphasize the importance of optimizing decalcification protocols to improve research outcomes. This synoptic and perspective article explores traditional and modern decalcification methods, offering recommendations on technical and methodological refinements for achieving molecularly robust processing of bone and calcified tissues in spatial transcriptomics and molecular pathology.

The discovery of biomarkers, essential for successful drug development, is often hindered by the limited availability of tissue samples, typically obtained through core needle biopsies. Standard 'omics platforms can consume significant amounts of tissue, forcing scientist to trade off spatial context for high-plex assays, such as genome-wide assays. While bulk gene expression approaches and standard single-cell transcriptomics have been valuable in defining various molecular and cellular mechanisms, they do not retain spatial context. As such, they have limited power in resolving tissue heterogeneity and cell-cell interactions. Current spatial transcriptomics platforms offer limited transcriptome coverage and have low throughput, restricting the number of samples that can be analyzed daily or even weekly. While the Digital Spatial Profiling (DSP) method does not provide single-cell resolution, it presents a significant advancement by enabling scalable whole transcriptome and ultrahigh-plex protein analysis from distinct tissue compartments and structures using a single tissue slide. These capabilities overcome significant constraints in biomarker analysis in solid tissue specimens. These advancements in tissue profiling play a crucial role in deepening our understanding of disease biology and in identifying potential therapeutic targets and biomarkers. To enhance the use of spatial biology tools in drug discovery and development, the DSP Scientific Consortium has created best practices guidelines. These guidelines, built on digital spatial profiling data and expertise, offer a practical framework for designing spatial studies and using current and future spatial biology platforms. The aim is to improve tissue analysis in all research areas supporting drug discovery and development.