Journal of Histotechnology最新文献

{"title":"USP34 modulates mitochondrial function in triple-negative breast cancer cells through the eIf3m/MTCH2 axis.","authors":"Peng-Fei Qian, Yi Zeng, Wang-Jing Zhong","doi":"10.1080/01478885.2026.2648740","DOIUrl":"https://doi.org/10.1080/01478885.2026.2648740","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":15966,"journal":{"name":"Journal of Histotechnology","volume":" ","pages":"1-13"},"PeriodicalIF":1.8,"publicationDate":"2026-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147773500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A look at scanner introduced variation in contrast, resolution, and colour across nine different models of whole slide imaging (WSI) scanner.","authors":"Hayley Pye, David S Brettle, Danny Kaye, Catriona M Dunn, Matthew P Humphries, Darren Treanor","doi":"10.1080/01478885.2026.2643973","DOIUrl":"https://doi.org/10.1080/01478885.2026.2643973","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":15966,"journal":{"name":"Journal of Histotechnology","volume":" ","pages":"1-12"},"PeriodicalIF":1.8,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147729154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TissuStamp: a novel high-throughput tissue transfer workflow for FFPE spatial biology assays.","authors":"Albert Velasco Abadia, Gina Benedetto, Zhenmin Hong, Jaekyung Koh, Sarthak Duggal, Sandor Kovacs, Mohammad Vatankhah Varnosfaderani, Mark Kalaj, Bandele Jeffrey-Coker, Anthony Facchini, McKenzie Pavlich, Wijendra Jude Senarathne, Digvijay Singh, Patricia Aurelina, Michael Lawson, Sabrina Shore, Kevin Marshall, Yuji Ishitsuka, Eli Glezer, Daan Witters","doi":"10.1080/01478885.2026.2648709","DOIUrl":"https://doi.org/10.1080/01478885.2026.2648709","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":15966,"journal":{"name":"Journal of Histotechnology","volume":" ","pages":"1-14"},"PeriodicalIF":1.8,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147729139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of an open-source AI tool for quantitative quality control in whole slide images of prostate needle core biopsies - a retrospective study.","authors":"Gonçalo Borrecho, Luís Rato, Pedro Salgueiro, Inês Ferreira, Catarina Madeira, Rui Caetano de Oliveira","doi":"10.1080/01478885.2026.2657106","DOIUrl":"https://doi.org/10.1080/01478885.2026.2657106","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":15966,"journal":{"name":"Journal of Histotechnology","volume":" ","pages":"1-14"},"PeriodicalIF":1.8,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147698783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An optimized method for monitoring blood-brain barrier penetration of small-molecule fluorescent probes.","authors":"Wenyi He, Xue Yu, Yinuo Li, Xiaojuan Su, Ruqiu Zhang, Ning Zhu, Yuxun Lu, Sihao Li, Zhenyang Wei, Gui Zhang, Ying Zhou, Beiyan Wu, Genfeng Wu, Fan Li","doi":"10.1080/01478885.2026.2631226","DOIUrl":"https://doi.org/10.1080/01478885.2026.2631226","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":15966,"journal":{"name":"Journal of Histotechnology","volume":" ","pages":"1-15"},"PeriodicalIF":1.8,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147512613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Color standardization in whole slide imaging: a method to reduce color variability.","authors":"Louise Collins, Richard Heale, Richard M Salmon","doi":"10.1080/01478885.2026.2636401","DOIUrl":"https://doi.org/10.1080/01478885.2026.2636401","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":15966,"journal":{"name":"Journal of Histotechnology","volume":" ","pages":"1-9"},"PeriodicalIF":1.8,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147433342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond algorithmic performance: translational gaps in implementing artificial intelligence for clinical digital pathology.","authors":"Rong Xia, Nickolas Littlefield, Riyue Bao, Qiangqiang Gu","doi":"10.1080/01478885.2026.2630525","DOIUrl":"10.1080/01478885.2026.2630525","url":null,"abstract":"","PeriodicalId":15966,"journal":{"name":"Journal of Histotechnology","volume":" ","pages":"1-3"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147271074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing digital pathology workflows: computational blur detection for H&E image quality control in preclinical toxicology.","authors":"Cyrus Manuel, Andy Cheon, Trung Nguyen, Sertan Kaya, Fangyao Hu, Ruth Sullivan, Reina Fuji","doi":"10.1080/01478885.2025.2585615","DOIUrl":"10.1080/01478885.2025.2585615","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":15966,"journal":{"name":"Journal of Histotechnology","volume":" ","pages":"44-52"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145668757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Morphometric analysis and its application in lupus nephritis: a systematic review.","authors":"Lucia Mercedes Niño-Hernandez, Liria Terradez Mas, Amparo Ruiz Sauri","doi":"10.1080/01478885.2025.2611623","DOIUrl":"10.1080/01478885.2025.2611623","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":15966,"journal":{"name":"Journal of Histotechnology","volume":" ","pages":"53-71"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146003594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel liquid immunocytochemistry with machine learning analysis for bladder cancer detection.","authors":"Ankush U Patel, Samir Atiya, Yi Song, Wenjiang Chu, Anil V Parwani","doi":"10.1080/01478885.2025.2546655","DOIUrl":"10.1080/01478885.2025.2546655","url":null,"abstract":"<p><p>Bladder cancer diagnosis is challenged by invasive monitoring and workflow inefficiencies impacting diagnostic reliability. This prospective study enrolled 150 patients (January 2020-December 2022) and evaluated a novel liquid-based immunocytochemistry platform, coupled with integrated machine learning, for detecting urothelial carcinoma in voided urine. All 150 cytology slides met the adequacy threshold of ≥2,644 urothelial cells and showed preserved cytomorphology. Eight cases of papillary urothelial neoplasm of low malignant potential (PUNLMP) were set aside a-priori, yielding an analytic cohort of 142 patients (115 urothelial-carcinoma, 27 benign) for performance analysis. hTERT (sensitivity 92.2%, specificity 66.7%), GATA-3 (67.0%, 88.9%), and CK17 (89.6%, 66.7%). In multi-marker analysis, sensitivity reached 100% (95% CI 96.8-100) when any marker was positive, whereas specificity reached 100% (95% CI 87.3-100) when all three markers were positive. The workflow-optimized platform standardizes specimen preparation and multi-marker interpretation, offering a robust foundation for urine-based bladder-cancer diagnostics. Larger, multi-center validation studies are warranted to refine specificity estimates and facilitate laboratory integration. This study demonstrates that addressing fundamental workflow challenges in bladder cancer diagnostics before implementing artificial intelligence creates more effective diagnostic tools. By prioritizing specimen integrity and standardization through a novel liquid immunocytochemistry platform, exceptional diagnostic performance was achieved with 100% sensitivity and specificity under defined marker parameters across various cancer stages. This workflow-first approach to integrating machine learning with advanced biomarker analysis offers a model for developing clinically practical diagnostic innovations that can reduce reliance on invasive monitoring procedures while improving detection accuracy.</p>","PeriodicalId":15966,"journal":{"name":"Journal of Histotechnology","volume":" ","pages":"4-12"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144859193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}