Intestinal fibrosis in Crohn's disease (CD) is a key determinant of stricture formation, but collagen architecture is difficult to assess on routine mucosal biopsies because of limited tissue depth and the lack of quantitative tissue-based fibrosis measures. We evaluated the feasibility of applying second harmonic generation/two-photon excitation microscopy (SHG/TPE) with qFibrosis analysis to quantify collagen microarchitecture across histologic compartments in CD biopsies. Unstained formalin-fixed paraffin-embedded endoscopic biopsies from 31 samples obtained from 20 patients with CD were analyzed using SHG/TPE imaging and qFibrosis. Regions of interest were annotated by a gastrointestinal pathologist into glands/crypts, lamina propria, muscularis mucosae, and submucosa. Quantitative morphometric parameters reflecting collagen burden, fiber/string features, and architectural organization were compared across compartments. SHG/TPE imaging with qFibrosis successfully generated compartment-level collagen morphometric data from routine FFPE biopsy tissue. Collagen content (%SHG) and aggregated collagen (%Agg) increased progressively with tissue depth, with the highest levels observed in the submucosa. In contrast, superficial compartments showed higher fiber/string-based parameters, suggesting a more dispersed collagen architecture. These findings demonstrate measurable, depth-dependent differences in collagen organization across intestinal biopsy compartments, including patterns not readily appreciable on routine histology. SHG/TPE-based qFibrosis analysis is feasible for quantitative assessment of collagen microarchitecture in routine CD biopsy specimens and identifies compartment-specific, depth-dependent collagen patterns. However, because this pilot study lacked non-IBD controls and paired histochemical validation with Sirius Red or trichrome staining, these findings should not be interpreted as disease-specific or clinically validated. These preliminary findings support further validation of SHG/TPE-based collagen morphometry as a potential tissue-level approach for studying intestinal fibrosis in larger cohorts with controls, paired histochemical validation, histologic correlation, and clinical outcomes.
The administration of biologics to the eyes of non-human primates in non-clinical studies can result in sporadic intraocular inflammation (IOI) in individual animals. When the biologic is a human (foreign) protein being administered to a non‑human primate (NHP), understanding the causes and clinical relevance of IOI can be especially challenging and represent an important data gap needed to advance the development of ocular biologic therapies. This study describes the development and validation of a multiplex immunostaining assay designed to address this need. It includes six markers that differentiate T cells (CD4+, CD8+), T regulatory cells (CD4+, FoxP3+), B cells (CD20+), macrophages (CD68+), and M2 macrophages and microglia cells (CD68+, IBA1+). Preliminary results in representative ocular samples with a biologic drug-induced IOI demonstrated the assay's ability to identify which immune cell types are present and their spatial relationships, which can significantly enhance the understanding of the immunology underlying IOI. This adds valuable interpretive information, facilitating better decision-making to develop safe and effective therapies.
Methods of processing histology tissues have undergone many positive changes over the past decades to include reduction in safety hazards, standardization of reagents/timing/temperatures of processing steps, and implementation of automation to reduce turnaround time, improve efficiency, and enhance reproducibility. A brief history, current standardized processes, and newer developments are described here.
Variation in H&E staining is often a confounder when comparing data in multi-site studies, and impacts on the generalisability of AI models. In this paper, slides containing serial sections of control liver tissue were sent out to eight clinical laboratories in England to stain over a two-week period. H&E staining optical density was quantified from the WSIs to measure the level of stain variation present within, and between, the eight laboratories. The laboratories used similar staining instruments and reagents, but their H&E stain durations varied. Intra-laboratory consistency was high (9-12% variation) but inter-laboratory variation was higher (maximum median difference of 31%) and the eight laboratories were statistically significantly different (p < 0.001). In addition, multiple colour-normalisation algorithms were applied to the image data using a range of target images. An automated nuclear count was then applied as an indicator of the impact of colour normalisation on the dataset and compared with pathologist manual 'ground truth' count. From three representative labs, the manual 'ground truth' nuclear counts ranged between 129 and 249, and the automated nuclear counts ranged between 152 and 621. Colour normalisation did improve inter-laboratory automated count variation (QCD) from 10% to 5%, but the results varied, particularly depending upon target image selection. The results from this work suggest that colour normalisation may improve consistency between slides but has the potential to be a confounder in its own right.
Myoepithelial cells (MECs) are integral to mammary gland physiology, classically serving a structural and tumor-suppressive role. While their function in normal breast tissue and ductal carcinoma in situ is well characterized, their behavior in human invasive breast cancer has not been previously examined. In this study, we performed a comprehensive transcriptomic analysis of MECs isolated from seven archived human breast cancer specimens, directly comparing them with MECs from adjacent normal tissue to define gene expression changes associated with invasive progression. The analysis revealed marked transcriptomic reprogramming across three key domains: extracellular matrix (ECM) interactions, epithelial-mesenchymal transition (EMT), and cellular signaling. Notable findings include stromal remodeling characterized by overexpression of 17 distinct collagen genes; compromise of the basement membrane through upregulation of matrix metalloproteinases (MMPs 2, 9, 11, and 14); and dysregulation of epithelial markers (KRT5, KRT7, KRT14), consistent with a phenotypic shift toward a cancer-associated fibroblast (CAF)-like state. In addition, increased expression of pro-tumorigenic mediators such as SPARC, POSTN, and integrin subunits was observed. Despite the limited sample size, these results indicate substantial molecular plasticity in MECs, suggesting a transition from a tumor-suppressive to a tumor-promoting phenotype during invasive disease. Overall, this study identifies a fundamental shift in myoepithelial identity and provides a critical framework for future investigations into the role of MEC plasticity in driving breast cancer progression.
Accurate assessment of blood-brain barrier (BBB) penetration is essential for validating small-molecule fluorescent probes. Conventional methods often suffer from signal attenuation, tissue damage, or fluorescence distortion during chemical fixation. We present an optimized histological workflow: 'intraperitoneal administration → fresh brain sampling → unfixed cryosectioning → confocal imaging.' By utilizing fresh-frozen tissue without chemical fixation, this method preserves intrinsic probe fluorescence and provides a high-resolution, accurate representation of BBB penetration. The workflow was validated across three murine models: neonatal hypoxic-ischemic injury, neuroinflammation, and neurodegenerative disease. In all models, fluorescence intensity showed a strong positive trend correlated with pathological severity, demonstrating that the method is exceptionally sensitive for detecting pathology-associated BBB penetration changes. While the workflow preserves baseline signals in control groups, its primary advantage lies in providing a high-resolution, accurate representation of probe engagement in compromised CNS environments. Notably, this standardized approach avoids invasive cranial procedures and minimizes fixation-induced quenching. The primary advantage of this optimized workflow over conventional fixation-based methods is the superior preservation of intrinsic small-molecule fluorescence in fresh-frozen sections, ensuring a more reliable evaluation of BBB penetration in preclinical research.
Triple-negative breast cancer (TNBC) represents a particularly aggressive form of breast tumors. Mitochondrial dysfunction represses the proliferation of TNBC cells. Ubiquitin-specific proteases 34 (USP34) has been predicted to be abnormally overexpressed in TNBC. This research examined the role of USP34 in the mitochondrial function modulation of TNBC. Herein, cell proliferation was evaluated by the 5-ethynyl-2'-deoxyuridine assay. Mitochondrial membrane potential was detected employing the JC-1 assay. Mitochondrial superoxide was measured utilizing MitoSOX Red assay. Mito‑Tracker Red CMXRos staining was selected to monitor mitochondrial network structure. The relationship among USP34, eukaryotic translation initiation factor 3 m (eIF3m), and mitochondrial carrier homolog 2 (MTCH2) was validated by co-immunoprecipitation, GST-pull down, RNA immunoprecipitation and RNA-pull down analysis. We found that USP34 silencing inhibited cell proliferation by inducing mitochondrial dysfunction in TNBC cells. USP34 maintained the stability of the eIF3m protein through deubiquitination. Overexpression of eIF3m countered the mitochondrial dysfunction induced by USP34 silencing. Furthermore, eIF3m upregulated the MTCH2 level by directly binding to its 5'UTR region. MTCH2 overexpression reversed the damaging effect of eIF3m silencing on mitochondrial function. Collectively, USP34 maintained the stability of eIF3m protein through deubiquitination; the upregulated eIF3m bound to the 5'UTR of MTCH2 mRNA to promote MTCH2 expression, thereby maintaining mitochondrial function and promoting the malignant progression of TNBC.
Spatial biology is shifting from single-sample studies to cohort-scale analyses required for translational research, AI model development, and clinical deployment, yet tissue preparation methods have remained largely unchanged for decades, creating a critical throughput bottleneck. Existing approaches face a trade-off: traditional processing accommodates only a few samples per slide, while tissue microarrays increase sample count by restricting analysis to small cores that limit spatial context. This technical note describes TissuStamp™, a tissue transfer system that enables high-throughput FFPE tissue preparation for spatial multiomics. FFPE sections are first mounted on gel pads, then specific regions of interest are punched using square blades and 'stamped' onto surface-functionalized TissuGrip™ slides using a pusher block. This enables the transfer of up to 32 millimeter-scale tissue regions or 10 larger regions (totaling up to ~1,000 mm2 of tissue area) onto a single standard 75 mm × 25 mm slide in a tightly packed, multi-lane array format. TissuStamp allows tissue cutting, storage and transfer to occur at different times and locations, facilitating multi-institutional studies and biobank initiatives. While TissuStamp was developed for the G4X™ platform, which performs integrated spatial transcriptomic, proteomic, and fluorescent H&E (fH&E™) profiling on up to 128 samples per run at subcellular resolution, its capabilities are transferable to other tissue analysis workflows. Comparative analysis demonstrated that TissuStamp preserved tissue morphology and delivered equivalent multiomic assay performance compared to conventional direct mounting onto slides. This method provides a practical solution for scaling spatial multiomics to cohort-scale research and clinical applications.
Variation in digital whole slide images can be introduced across entire the digital pathology pathway, but one source of variation is the WSI scanner itself. We measured the range of variation across 9 different makes and models of WSI scanner using commercial and bespoke test objects. Slides were prepared representing a range of contrast, colour and resolution test signals. Differences in contrast were seen in both a shift of the maximum and minimum contrast levels and the introduction of non-linearity in some scanners. These contrast differences were also reflected in H&E images with additional shifts seen within the eosin colour space for some of the scanners. The resolution test pattern showed a wide variation in the ability of scanners to accurately reproduce the smaller details. This study describes the image variability of nine WSI scanners and highlights the importance of independent quality assessment and control.
The quality of Whole Slide Images (WSI) is a determining factor for proper diagnosis and prognosis, and for enhanced performance of Digital and Computational Pathology. In a context where diagnoses are increasingly quantitative, an automated, precise, effective, and rapid quality control is of paramount importance. PathProfiler is a deep learning-based software trained on prostatic tissue that provides a 'usability score' of WSI, evaluating its suitability for diagnosis. The Centro de Anatomia Patológica Germano de Sousa receives around 2500 prostate biopsies a year, distributed to Pathologists remotely. Hence, it becomes crucial to investigate PathProfiler's viability for automated and quantitative WSI quality control and its monitoring for diagnostic purposes. Thus, in the last 3 months of 2024, 226 H&E WSI from prostate needle core biopsies were retrospectively analysed by PathProfiler. Usability score, focus, and H&E quality were registered numerically. WSIs had a usability score mean of 0.6, focus score of 9.6, and H&E quality score of 9.1. A usability score of 0.5 or higher was obtained for 70% of the WSIs, while 30% required revision. Artefacts such as mounting media, dust, and folded tissue were the major artifacts detected; extra-prostatic tissue was also recognised as 'other artifacts,' since the algorithm provides a lower rating in our cohort. PathProfiler is a valuable tool in the automatic quality control of prostate biopsies, allowing quick evaluation and identification of cases requiring review before being handed over to the pathologist, and promotes recognition of opportunities to improve laboratory and clinical quality.
Color standardization in digital pathology is essential for ensuring consistency across Whole Slide Imaging (WSI) scanners. This study utilizes color data from multiple WSI scanners captured from a slide containing 55 color patches with histology stain spectral characteristics alongside a proprietary algorithm to generate International Color Consortium (ICC) profiles. By transforming scanner-derived color values to align with their true spectral counterparts, the method enables effective color standardization. The color gamut of various scanner models was compared to the true spectral values both before and after standardization, as well as to the standard Red, Green and Blue (sRGB) gamut commonly used in display technologies. Results show that WSI scanners apply significantly different linear and tone curve profiles, as well as introducing variability in white and black point calibration. The proposed ICC-based standardization method substantially reduced discrepancies between scanned color values and their true spectral equivalents. This approach demonstrates the potential to mitigate scanner-induced color variability within digital pathology workflows. As artificial intelligence becomes increasingly integrated into pathology, addressing color presentation discrepancies between human observers and machine learning algorithms is critical. Application of standardized calibration would ensure consistency of data used for accurate diagnostic methods leading to reliable use for scaling of digital pathology. The uniquely large dataset presented here reveals how different image sources can generate significantly different outputs. Industry best practice would be to have all scanners calibrated by the same standard method and quantifiable accuracy, leading to real standardization rather than the variety of approaches this paper has revealed.
Annotated pathology datasets are the cornerstone for developing computational pathology. However, the intrinsic complexity of pathology data often results in a scarcity of large, manually annotated datasets. To address this challenge, a rapid, accurate, and automatic method for annotating tumor cells is essential for advancing the field of computational pathology. Here, we introduce a novel annotation technology. In our approach, Hematoxylin-eosin (H&E) slides were first digitized and preserved. These H&E slides were then faded and re-stained using multiple biological technologies (MBT) to identify specific biomarkers. The re-stained MBT slides were subsequently scanned again to create new digital images. The original and re-stained digital images underwent a registration and segmentation process to ensure that all minute structures in both images aligned perfectly. The staining results from the MBT slides, referred to as2 label maps, were extracted and transferred back onto the H&E slides, and the data were merged. This method allows for precise and efficient annotation of all tumor cells, including those expressing specific biomarkers, as well as the components of the tumor microenvironment. By rapidly generating high-quality, high-volume datasets, this innovative method significantly enhances the ability of AI approaches to analyze and interpret pathology data. Consequently, it supports the development of highly accurate diagnostic, prognostic, and predictive decision-making systems in the field of computational pathology.
Lupus nephritis (LN) is a severe manifestation of systemic lupus erythematosus (SLE), characterized by marked histological heterogeneity and high interobserver variability in the evaluation of renal biopsies. Digital morphometry has emerged as an objective and reproducible tool that enables precise quantification of tissuelesions, thereby enhancing diagnostic accuracy and prognostic assessment. To explore its application in LN, a systematic review was conducted following PRISMA guidelines, including observational studies in adults, children, and animal models with biopsy-proven LN in which digital morphometry was applied. Searches were performed inPubMed, Embase, Scopus, Web of Science, Cochrane, and Google Scholar. From 376 identified records, 46 studies fulfilled inclusion criteria. Among these, 30 analyzed the glomerularcompartment, 22 the tubulointerstitial, and the vascular. Both manual techniques and image analysis software such as ImageJ, ImagePro-Plus, and QuPath were used. In the glomerular compartment, parameters including cellularity, mesangial expansion, proliferation, and immune deposits were assessed. Tubulointerstitial studies measured fibrosis, tubular atrophy, and immune Infiltrates, while vascular analyses examined intimal thickening and complementactivation. Across compartments, morphometry consistently outperformed conventional visual evaluation, particularly in fibrosis quantification and prediction of renal prognosis. Overall, digital morphometry represents a valuable method for the comprehensive assessment of LN renal biopsies. Its application provides greater precision in characterizing renal damage and offers advantages interms of objectivity, reproducibility, and prognostic value. Standardization of morphometric approaches, together with integration into artificial intelligence-based tools, could optimize diagnostic accuracy and therapeutic strategies in LN.
Toxicologic pathology is undergoing a digital transformation, with advances in imaging and computational methods enabling automation of traditionally manual workflows. Central to these digital workflows is the generation of high-quality whole slide images (WSIs), where one key determinant of image quality is focus sharpness. To address this, we have integrated a pair of productionalized computational models - 'MiQC' (Microscopic Quality Control) - into our routine image QC workflows. MiQC combines Local Binary Patterns (LBP) and DeepFocus-based deep learning algorithms to detect and quantify out-of-focus regions in WSIs. Subsequent to scanner-based focus metric assessment, MiQC further screens WSIs and supports technician review by generating heatmaps that highlight problematic areas. Even WSIs with scanner focus scores of 98-99% can contain unacceptable blur, which MiQC helps identify. Using this system, 85-95% of WSIs are approved without further intervention, and technician review time is reduced by nearly 50%. Compared to fully manual review, MiQC has doubled our throughput of QC'd slides per hour. This efficiency gain has accelerated the expansion of our high-quality WSI repository and provides a scalable, reproducible framework for enhancing image QC in toxicologic and broader digital pathology applications. MiQC supports higher throughput and integration of automated image analysis pipelines, laying the groundwork for robust downstream computational pathology workflows.
Spatial transcriptomics has transformed the study of gene expression in tissue samples, yet its application to non-standard sample preservation formats beyond fresh frozen and FFPE remains underexplored. PAXgene fixation offers advantages for genomic studies by preserving DNA and RNA without crosslinking but poses challenges for high-quality spatial transcriptomics. Here, we present an optimised workflow for applying Xenium, an automated in situ sequencing platform, to PAXgene-fixed paraffin-embedded (PFPE) tissues. Using our newly developed Xenium Tissue Optimisation (XTO) protocol, we systematically tested permeabilisation conditions across multiple mouse and human tissues. We show that pepsin digestion effectively enhances RNA accessibility in PFPE samples, with tuneable digestion times for tissue-specific optimisation, though a compromise may need to be reached between transcript detection rates and maintaining tissue integrity and morphological staining. Our results indicate that, under optimal conditions, PFPE samples can yield comparable spatial RNA transcript detection to formalin-fixed paraffin-embedded (FFPE) and fresh frozen samples. This study provides a framework for adapting in situ sequencing to PFPE tissues, broadening the applicability of spatial transcriptomics to archival and prospective sample collections.
Decalcification is an important step in histology laboratories to allow mineralized tissue samples to be trimmed and sectioned easily. Many decalcifying solutions have a rapid onset of action in softening tissues but alter protein structure and morphology, while others preserve protein integrity but are less efficient. The ideal decalcification protocol allows for rapid and cost-effective processing and precise evaluation of microscopy and antigen-based immunostaining such as immunohistochemistry. In our study, mouse tissues were decalcified with three commercially available solutions to identify the product that best meets those criteria. ImmunocalTM (StatLab), EprediaTM, and Rapid-CalTM (StatLab) decalcification agents were tested on formalin-fixed, paraffin-embedded CD-1 mouse femur, skull, and sternum samples. Multiple metrics including ammonium oxalate turbidity and radiography were used to assess stages of bone demineralization. Tissues were routinely processed, embedded in paraffin, and sectioned at 5 µm for H&E staining and CD3, CD31, and Iba1 immunostaining. Each tested sample represented a decalcification product and time (4, 6, 12, 24, 30, 48, 73 h). Samples were assessed by radiolucency on X-ray and gross bone pliability prior to histologic processing, followed by histopathologic scoring for completeness of demineralization, preservation of tissue architecture, and antigenicity of tissue. All three commercially available decalcifying solutions are sufficient for rapid decalcification with preservation of tissue integrity, cellular detail, and immunogenicity.
