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Aims/hypothesisWe aimed to characterise and quantify the expression of HLA class II (HLA-II) in human pancreatic tissue sections and to analyse its induction in human islets.MethodsWe immunostained human pancreatic tissue sections from non-diabetic (n = 5), autoantibody positive (Aab+; n = 5), and type 1 diabetic (n = 5) donors, obtained from the Network of Pancreatic Organ Donors (nPOD), with HLA-II, CD68 and insulin. Each tissue section was acquired with a widefield slide scanner and then analysed with QuPath software. In total, we analysed 7415 islets that contained 338,480 cells. Widefield microscopy was further complemented by high resolution imaging of 301 randomly selected islets, acquired using a Zeiss laser scanning confocal (LSM880) to confirm our findings. Selected beta cells were acquired in enhanced resolution using LSM880 with an Airyscan detector. Further, we cultured healthy isolated human islets and reaggregated human islet microtissues with varying concentrations of proinflammatory cytokines (IFN-γ, TNF-α and IL-1β). After proinflammatory cytokine culture, islet function was measured by glucose-stimulated insulin secretion, and HLA-I and HLA-II expression was subsequently evaluated with immunostaining or RNA sequencing.ResultsInsulin-containing islets (ICIs) of donors with type 1 diabetes had a higher percentage of HLA-II positive area (24.31%) compared with type 1 diabetic insulin-deficient islets (IDIs, 0.67%), non-diabetic (3.80%), and Aab+ (2.31%) donors. In ICIs of type 1 diabetic donors, 45.89% of the total insulin signal co-localised with HLA-II, and 27.65% of the islet beta cells expressed both HLA-II and insulin, while in non-diabetic and Aab+ donors 0.96% and 0.59% of the islet beta cells, respectively, expressed both markers. In the beta cells of donors with type 1 diabetes, HLA-II was mostly present in the cell cytoplasm, co-localising with insulin. In the experiments with human isolated islets and reaggregated human islets, we observed changes in insulin secretion upon stimulation with proinflammatory cytokines, as well as higher expression of HLA-II and HLA-I when compared with controls cultured with media, and an upregulation of HLA-I and HLA-II RNA transcripts.Conclusions/interpretationAfter a long-standing controversy, we provide definitive evidence that HLA-II can be expressed by pancreatic beta cells from patients with type 1 diabetes. Furthermore, this upregulation can be induced in vitro in healthy isolated human islets or reaggregated human islets by treatment with proinflammatory cytokines. Our findings support a role for HLA-II in type 1 diabetes pathogenesis since HLA-II expressing beta cells can potentially become a direct target of autoreactive CD4+ lymphocytes.

Background With growing insights into the tumor immune microenvironment, tumor-infiltrating lymphocytes (TILs) have emerged as key indicators of anti-tumor immunity. Numerous studies highlight their prognostic value in gastric cancer (GC). However, manual or semi-quantitative TIL assessment is time-consuming and poorly reproducible. Methods A total of 388 patients with gastric adenocarcinoma were randomly stratified into training and validation cohorts based on TNM stage. QuPath was used to establish an automated workflow for identifying tumor cells, TILs, and other stromal cells in brightfield hematoxylin-eosin (H&E)-stained tissue microarrays (TMAs). TIL-related variables were derived from these classifications. Prognostic significance was assessed using Kaplan-Meier analysis, log-rank tests, and univariable and multivariable Cox proportional hazards models. A nomogram incorporating age, T stage, lymph node metastasis and the proportion of TILs among all cells (pTILs) was built to predict 1- and 3-year overall survival (OS). Results Higher levels of TILs were associated with improved OS in both cohorts. Multivariate analysis confirmed that pTILs was an important prognostic factor for OS. The nomogram effectively predicted 1-year and 3-year OS. Notably, the nomogram-based risk stratification demonstrated better discriminative ability than TNM stage in distinguishing between low- and middle-risk patients. Conclusions This study established a quantitative workflow for TIL assessment in GC. Integrating TIL-related parameters with clinical characteristics enhances risk stratification and may improve individualized prognosis prediction.

Digital pathology can efficiently assess immunohistochemistry (IHC) data on tissue microarrays (TMAs). Yet, it remains important to evaluate the comparability of the data acquired by different software applications and validate it against pathologist manual interpretation. In this study, we compared the IHC quantification of 5 clinical breast cancer biomarkers—estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), epidermal growth factor receptor (EGFR), and cytokeratin 5/6 (CK5/6)—across 3 software applications (Definiens Tissue Studio, inForm, and QuPath) and benchmarked the results to pathologist manual scores. IHC expression for each marker was evaluated across 4 TMAs consisting of 935 breast tumor tissue cores from 367 women within the Nurses’ Health Studies; each women contributing three 0.6-mm cores. The correlation and agreement between manual and software-derived results were primarily assessed using Spearman’s ρ, percentage agreement, and area under the curve (AUC). At the TMA core-level, the correlations between manual and software-derived scores were the highest for HER2 (ρ ranging from 0.75 to 0.79), followed by ER (0.69–0.71), PR (0.67–0.72), CK5/6 (0.43–0.47), and EGFR (0.38–0.45). At the case-level, there were good correlations between manual and software-derived scores for all 5 markers (ρ ranging from 0.43 to 0.82), where QuPath had the highest correlations. Software-derived scores were highly comparable to each other (ρ ranging from 0.80 to 0.99). The average percentage agreements between manual and software-derived scores were excellent for ER (90.8%–94.5%) and PR (78.2%–85.2%), moderate for HER2 (65.4%–77.0%), highly variable for EGFR (48.2%–82.8%), and poor for CK5/6 (22.4%–45.0%). All AUCs across markers and software applications were ≥0.83. The 3 software applications were highly comparable to each other and to manual scores in quantifying these 5 markers. QuPath consistently produced the best performance, indicating this open-source software is an excellent alternative for future use. •It is important to evaluate the comparability of the data acquired by different software applications and validate it against pathologist manual interpretation.•Definiens Tissue Studio®, inForm®, and QuPath were highly comparable to each other and to pathologist manual scores in quantifying 5 clinical breast cancer biomarkers—ER, PR, HER2, EGFR, and CK5/6—in tissue microarrays.•QuPath had the highest correlation and %agreement with manual scores.•QuPath is a reliable open-source tool to automate IHC expression quantification of breast tumor biomarkers.

Early neuroimmune remodeling is a critical yet understudied component of Alzheimer’s disease (AD) pathogenesis. To investigate microglial contributions to AD development prior to overt plaque deposition, we developed an open-source morphometric pipeline to systematically quantify hippocampal microglial structure and activation states in pre-plaque 5xFAD mice. Across ∼11,000 cells, we extracted multidimensional parameters including area, circularity, convex hull, branch points, nearest-neighbor distance, and nuclear features, alongside Iba1 and CD68 intensity measurements. While no significant overt gliosis was observed at this early stage, microglia from 5xFAD mice exhibited subtle trends toward increased structural complexity compared to wild-type controls. Importantly, significant sex-specific differences were detected within the CA1 subregion: male 5xFAD microglia displayed hyper-ramified morphologies consistent with enhanced surveillance states, whereas female microglia demonstrated greater density and a more reactive phenotype. Correlation analyses revealed a conserved association between microglial complexity and Iba1/CD68 expression, independent of sex or genotype, underscoring a fundamental link between cytoskeletal remodeling and phagolysosomal activity. These findings highlight the capacity of morphometric profiling to sensitively detect early, region-specific, and sex-dependent shifts in microglial phenotype before amyloid deposition. By integrating quantitative morphology with canonical molecular markers, this framework provides a robust and unbiased approach for characterizing microglial activation trajectories. Such early readouts may inform biomarker discovery and therapeutic strategies aimed at modulating microglial responses to delay or prevent AD progression.

Background: QuPath is an open-source digital image analyzer notable for its user-friendly design, cross-platform compatibility, and customizable functionality. Since it was first released in 2016, at least 624 publications have reported its use, and it has been applied in a wide spectrum of settings. However, there are currently limited reports of its use in placental tissue. Here, we present the use of QuPath to quantify staining of G-protein coupled receptor 18 (GPR18), the receptor for the pro-resolving lipid mediator Resolvin D2, in placental tissue. Methods: Whole slide images of vascular smooth muscle (VSM) and extravillous trophoblast (EVT) cells stained for GPR18 were annotated for areas of interest. Visual scoring was performed on these images by trained and in-training pathologists, while QuPath scoring was performed with the methodology described herein. Results: Bland-Altman analyses showed that, for the VSM category, the two methods were comparable across all staining levels. For EVT cells, the high-intensity staining level was comparable across methods, but the medium and low staining levels were not comparable. Conclusions: Digital image analysis programs offer great potential to revolutionize pathology practice and research by increasing accuracy and decreasing the time and cost of analysis. Careful study is needed to optimize this methodology further.

Colorectal cancer (CRC) ranks as the third most common and second deadliest cancer worldwide. The immune system, particularly tertiary lymphoid structures (TLS), significantly influences CRC progression and prognosis. TLS maturation, especially in the presence of germinal centers, correlates with improved patient outcomes; however, consistent and objective TLS assessment is hindered by varying histological definitions and limitations of traditional staining methods. This study involved 656 patients with colorectal adenocarcinoma from CHU Brest, France. We employed dual immunohistochemistry staining for CD21 and CD23 to classify TLS maturation stages in whole-slide images and implemented a fivefold cross-validation. Using ResNet50 and Vision Transformer models, we compared various aggregation methods, architectures, and pretraining techniques. Our automated system, TLS-PAT, achieved high accuracy (0.845) and robustness (kappa = 0.761) in classifying TLS maturation, particularly with the Vision Transformer pretrained on ImageNet using Max Confidence aggregation. This AI-driven approach offers a standardized method for automated TLS classification, complementing existing detection techniques. Our open-source tools are designed for easy integration with current methods, paving the way for further research in external datasets and other cancer types.

PRAME (PReferentially expressed Antigen in MElanoma) was first identified as a malignant melanoma-specific antigen. Recently, a few cases of fibrosarcomatous dermatofibrosarcoma protuberans (FS-DFSP) were shown to have positivity for PRAME, while conventional dermatofibrosarcoma protuberans (C-DFSP) was negative. Because PRAME may be of diagnostic utility in FS-DFSP and is raising expectations as a new immunotherapy target, we examined the positivity of PRAME in FS-DFSP. Twenty-one cases of FS-DFSP and age/sex/location-matched cases of C-DFSP as a control group were examined by immunohistochemistry for CD34 and PRAME. The results were then evaluated by H-score, which was objectively and semi-quantitatively calculated using the open-source bioimaging analysis software QuPath. The results revealed that the PRAME H-score in FS-DFSP was significantly higher than that in C-DFSP ( p  = 0.0137). As for CD34, the H-score in FS-DFSP was significantly lower than that in C-DFSP ( p  < 0.001). Using these two immunohistochemical analyses in combination, the sensitivity and specificity for the diagnosis of FS-DFSP were 86% and 90%, respectively. Double staining of CD34 and PRAME revealed that PRAME-positive and CD34-positive areas did not overlap. This is the largest study to examine PRAME expression in FS-DFSP, and it confirmed the usefulness of PRAME in diagnosing this condition.

This study aims to retrospectively compare two resuscitation methods ( extracorporeal cardiopulmonary resuscitation (ECPR) vs. emergency preservation and resuscitation (EPR)) by pathohistologically assessing pig brains in a ventricular fibrillation cardiac arrest (VFCA) model. In prospective studies from 2004 to 2006, swine underwent VFCA for 13 ( n  = 6), 15 ( n  = 14) or 17 ( n  = 6) minutes with ECPR (ECPR13, ECPR15 and ECPR17). Another 15 min VFCA group ( n  = 8) was resuscitated with EPR and chest compressions (EPR15 + CC). Brains of animals surviving for nine days (ECPR13 n  = 4, ECPR15 n  = 2, ECPR17 n  = 1, EPR15 + CC n  = 7) were harvested. Eight different brain regions were analyzed with the image analysis software QuPath using HE-staining, GFAP- and Iba1-immunohistochemistry. Only ECPR13 and EPR15 + CC animals were included in statistical analysis, due to low survival rates in the other groups. All VFCA samples showed significantly fewer viable neurons compared to shams, but no significant differences between ECPR13 and EPR15 + CC animals were observed. ECPR13 animals showed significantly more glial activation in all cerebral cortex regions compared to shams and in occipital, temporal and parietal cortex compared to EPR15 + CC. In conclusion, EPR + CC resulted in a significantly reduced inflammatory reaction in cerebral cortex compared to ECPR but did not influence the extent of neuronal death after VFCA.

Bone taphonomy and diagenesis contribute to anthropological analysis in forensic investigations by attempting to reconstruct the relationship between human cadaveric remains and their postmortem depositional environment. The rare aquatic taphonomic experiments have been delivering conflicting results on the influence of time and the environment on the decay of bone and teeth, especially considering that the main diagenetic processes can lead to fragmentation, progressive dissolution or fossilization. The aim of this experimental, quantitative, randomized and controlled 2-year study was to analyse the taphonomy and diagenesis of submerged terrestrial mammalian bones to achieve a more accurate estimation of both the post-mortem interval (PMI) and the post-mortem submersion interval (PMSI) in the short term. Three parameters of bone diagenesis, the Oxford Histological Index (OHI), the total porosity and the collagen content of cortical bone were analysed by MicroCT Scan, bright-field Light Microscopy (Picrosirius Red stain), Scanning Electron Microscopy (SEM) and Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) on 75 sheep femurs and tibias placed in four distinct types of environment (natural saltwater, natural freshwater, an artificial seawater solution and exposed to the air) vs. non-exposed controls. LA-ICP-MS was soon discontinued because no measurable changes of the elemental profiles could be detected. Multivariate statistical analysis was applied to the collected data. The macroscopical preservation was consistently excellent (OHI=5). The total porosity and the degradation of collagen were greater underwater than in subaerial exposure, whereas demineralization zones and bioerosion tunnelling appeared after 12 months in the air-exposed samples only. Underwater, the continuous movement, the correlated abrasion by sand and sediment and the constant alkaline pH (≥ 8) can explain the progressive removal of the mineral component and the subsequent exposure of collagen to bioeroders and chemical hydrolysis. On land, the same process occurs at a slower rate on account of the seasonality of the water flow, however, the action of the more abundant and diversified species of bioeroding microorganisms appears more efficient. Despite some limitations, this study indicates that three parameters of bone diagenesis can predict the depositional environment of terrestrial mammalian bone characterized by a PMI and/or PMSI of at least 12 months.

This study aimed to assess the prognostic value of intratumoral CD57+ cells in head and neck squamous cell carcinoma (HNSCC) and to examine the reproducibility of these analyses using QuPath. Pretreatment biopsies of 159 patients with HPV-negative, stage III/IV HNSCC treated with chemoradiotherapy were immunohistochemically stained for CD57. The number of CD57+ cells per mm2 tumor epithelium was quantified by two independent observers and by QuPath, software for digital pathology image analysis. Concordance between the observers and QuPath was assessed by intraclass correlation coefficients (ICC). The correlation between CD57 and clinicopathological characteristics was assessed; associations with clinical outcome were estimated using Cox proportional hazard analysis and visualized using Kaplan-Meier curves. The patient cohort had a 3-year OS of 65.8% with a median follow-up of 54 months. The number of CD57+ cells/mm2 tumor tissue did not correlate to OS, DFS, or LRC. N stage predicted prognosis (OS: HR 0.43, p = 0.008; DFS: HR 0.41, p = 0.003; LRC: HR 0.24, p = 0.007), as did WHO performance state (OS: HR 0.48, p = 0.028; LRC: 0.33, p = 0.039). Quantification by QuPath showed moderate to good concordance with two human observers (ICCs 0.836, CI 0.805–0.863, and 0.741, CI 0.692–0.783, respectively). In conclusion, the presence of CD57+ TILs did not correlate to prognosis in advanced stage, HPV-negative HNSCC patients treated with chemoradiotherapy. Substantial concordance between human observers and QuPath was found, confirming a promising future role for digital, algorithm driven image analysis.