Medicine and Pharmacology

Abstract: SARS-CoV-2 infection is linked to systemic symptoms beyond the respiratory tract, including muscle weakness, muscle pain, and fatigue (1). The underlying histopathological reasons for the involvement of skeletal muscle in coronavirus disease 2019 (COVID-19) remain incompletely understood. In the present study, we examined skeletal muscle obtained at autopsy from a subgroup of people who tested positive for SARS-CoV-2 and assessed the degree of myofiber necrosis, inflammation, and the immunohistochemical reactivity for the SARS-CoV-2 nucleocapsid protein. The main morphological finding was degeneration and necrosis of myofibers often in a focal or discontinuous manner affecting single fibers or a group of fibers, while neighboring fibers were fairly well preserved. The inflammatory infiltrates were generally scarce. The immunoreactivity for the SARS-CoV-2 nucleocapsid protein varied. There was no clear correlation between the intensity of the staining and the severity of the myofiber necrosis. Necrotic changes were found in both the groups that had been hospitalized for a long time and those that had been hospitalized for a short time or not at all, which suggests that critical illness myopathy cannot account for all the lesions observed. These results point to an atypical pattern of skeletal muscle damage in individuals who are positive for SARS-CoV-2 at the time of autopsy, a pattern that is mostly free from inflammation, and thus calls for further investigation into neurogenic, vascular, and other indirect mechanisms of muscle damage during both the acute and the post-acute phases of COVID-19.

Abstract: Acute organ failure can be lethal yet often reversible and relatively stereotyped despite diverse triggers. Cells facing resource limitations should direct failure toward fault-tolerant or repairable components. As importantly, the many components and pathways that can fail in different sequences create an underappreciated cybernetic problem: high failure variety, unpredictability and branching. Simplifying the failure process could promote controllability. Specialized organ function imposes load on cell-intrinsic systems, but this dependency is asymmetric: organ function can be reduced and later restored, whereas loss of ion gradients is often irreversible. Continued high performance may couple specialized work to maintenance processes through shared energy, redox, ion and proton systems. Suppressing organ function earlier than necessary could thus be a control action that avoids resource-limitation coupling, reduces failure variety and preserves controllability. Suppression of organ function could occur through regulatory systems or heightened stress-mediator sensitivity.In a sacrificial system, organ function responding to multiple stressors may convert complex failure to a simple output. An embedded sacrificial control system could arise from mediator-controlled failure sequences. Differential sensitivities of cellular processes to stress-mediators would induce sequencing that can be self-similar failure across cells if it has high ordering-probability, reducing tissue-level complexity. Acute organ dysfunction may therefore be an act of control: a simple response pattern to avoid cybernetic chaos of the failure process.

Abstract: Small leucine-rich proteoglycans (SLRPs) are an important group of molecules in the extracellular matrix (ECM) that are involved in regulating collagen assembly, tissue homeostasis, and cell signalling pathways. Among them, Decorin represents the proto-type member and plays a central role in maintaining ECM integrity, regulating fibrosis, and controlling tumor progression. This review examines the structural and functional biology of SLRPs, with a special focus on Decorin, highlighting its involvement in fibrotic diseases, degenerative disorders and the tumor microenvironment. Decorin acts as a multifunctional regulator through its interactions with TGF-β, various tyrosine kinase receptors, and multiple ECM components, carrying out anti-fibrotic, anti-angiogenic, anti-cancer, and tumour-suppressive functions. Additionally, factors such as the contribution of SLRPs to the desmoplastic response of tumors, their potential use as biomarkers for extracellular matrix remodelling, and the emerging therapeutic prospects based on administering recombinant Decorin, gene therapies, mimetic molecules, and strategies targeting the ECM. Overall, SLRPs, especially Decorin, stand out as key molecules in integrating structural and molecular signals and as promising diagnostic and therapeutic targets in fibrotic and neoplastic diseases.

Abstract: Background/Objectives: Dietary mineral deficiencies rarely occur singly, yet most experimental work on the testis has used single-nutrient designs and endpoints, such as sperm number, that cannot tell where spermatogenesis fails. We asked whether isolated deficiency of magnesium, iron, selenium and zinc interrupts spermatogenesis at different stages and whether combined deficiency exceeds the effect of any single element. Methods: Outbred male rats were fed certified purified diets on a common base for twelve weeks from the age of three months: control, magnesium-, iron-, selenium-, zinc- and combined-deficient (six groups, n = 15 each). Testes were examined at six months by morphometry, a stage-resolved census of germ cells per tubule profile with three transition ratios, Johnsen scoring, van Gieson histochemistry and imprint cytology. Results: Every deficiency thinned the spermatogenic epithelium and reduced luminal spermatozoa, but the step affected differed. Selenium restriction lowered the spermatid-to-spermatocyte ratio to 4.05 against 4.98 in controls while sparing the adjacent transitions, a block at meiotic exit. Zinc restriction left that ratio unchanged (5.00) but reduced the spermatozoa-to-spermatid ratio to 1.45 against 1.68, a post-meiotic block, and spared spermatogonia. Magnesium and iron restriction suppressed all germ cell classes in proportion. Combined deficiency lowered two transitions at once and produced the steepest losses: spermatids fell 40.4%, the Johnsen score fell from 10 to 7.4 and Leydig cell density fell 24.5%, against at most 9.0% for any single element. Conclusions: The four deficiencies leave distinguishable structural signatures that sperm number alone does not reveal. Combined deficiency exceeds every single element, markedly so in the Leydig cell compartment, which argues for correcting concurrent deficiencies together rather than one at a time.

Abstract: Determining the mammary origin of a metastatic or poorly differentiated carcinoma is a frequent challenge in surgical pathology. Conventional breast markers (GATA3, GCDFP-15 and mammaglobin) lose sensitivity in triple-negative and metaplastic breast carcinoma. TRPS1 (trichorhinophalangeal syndrome type 1), an atypical GATA-family transcription factor, was proposed in 2020–2021 as an immunohistochemical marker of breast lineage. This narrative review summarizes the literature up to October 2026 on TRPS1 biology, its diagnostic performance across breast carcinoma subtypes, its expression in non-mammary neoplasms and its place in current diagnostic panels. TRPS1 shows nuclear positivity in 86–99% of breast carcinomas, including triple-negative and metaplastic tumors, in which it outperforms GATA3. It is almost always negative in urothelial carcinoma, a GATA3-positive mimic of breast carcinoma. However, large studies have demonstrated expression in squamous cell carcinomas, salivary gland tumors, gynecologic carcinomas, cutaneous adnexal neoplasms and sarcomas, with overall specificities of 58–74% in recent series. Apocrine, triple-negative neuroendocrine and acinic cell carcinomas are usually negative. TRPS1 is the most sensitive breast-lineage marker currently available, particularly in triple-negative breast cancer, but it is not specific. It should be interpreted together with morphology, clinical history and a panel that includes GATA3 and markers relevant to the differential diagnosis.

Abstract: Pulmonary alveolar microlithiasis (PAM) is a rare autosomal recessive lung disease in which calcium phosphate microliths fill the alveoli. Although the cause of it remained unknown for some time, more recently loss-of-function variants in SLC34A2, which encodes the sodium-phosphate cotransporter NPT2b, explain nearly all genetically tested cases; failure to clear phosphate from the alveolar lining fluid leads to microlith formation, and an epithelial Npt2b-knockout mouse reproduces the human phenotype. Diagnosis now rests mainly on characteristic high-resolution CT and, increasingly, on genotyping rather than lung biopsy. The protracted course has been described in some series of cases, with death from respiratory failure. No drug has proven efficacy; lung transplantation is the only established therapy, and no allograft recurrence has been documented. Preclinical data support phosphate restriction, EDTA lavage and gene-directed approaches. However, controlled trials with more genotype-phenotype correlation and prospective natural-history data are still needed.

Abstract: Celiac disease is a common immune-mediate inflammatory disease of the small intestine triggered by an environmental agent (gluten) in genetically predisposed individuals. It affects approximately 1% of the population and is characterized by diarrhea, malabsorption, and villous atrophy of the intestinal mucosa. In the context of dynamics systems, entropy is a measure of uncertainty. In computer vision, entropy is a statistical measure of randomness that can be used to characterize the texture and complexity of the input image. The hypothesis of this proof-of-concept study was that the loss of physiological structural balance could be measured by entropy. Entropy was measured in 16 patients with celiac disease (57 biopsies, 7294 image patches) and compared with 20 cases of small intestine control (54 biopsies/whole-tissue sections, 15810 image patches). The series was expanded with 18 cases of unspecific duodenal inflammation (5966 image patches) and 5 cases of duodenal adenocarcinoma (3723 image patches). Analysis was performed using 224×224×3 input non overlapping image patches and Matlab 2026a entropy function. In comparison with control, celiac disease was characterized by lower histological entropy (6.04 ± 0.39 vs. 6.59 ± 0.40, respectively, P < 0.001). In conclusion, the histological evaluation of entropy as a topological analysis is useful for the differential diagnosis between normal intestinal mucosa control and celiac disease. Loss of randomness characterized celiac disease.

Abstract: Colon histology computer-aided diagnosis (CAD) papers often lead with pooled grading accuracy. That number mixes easy majority-class hits with minority-class misses and treats a Grade 1↔Grade 2 swap as interchangeable with calling poorly differentiated cancer well differentiated. This preprint recomputes stratified five-fold support-vector grading on 560 public colorectal cancer patches with frozen ResNet50 embeddings (Grade 1 n=251, Grade 2 n=210, Grade 3 n=99). Cross-validated accuracy is 73.6% ± 2.9% and macro-F1 is 0.705, but Grade 3 recall is only 0.475. Of 148 residual mistakes, 119 (80.4%) are adjacent-grade swaps; 29 (19.6%) jump from Grade 3 to Grade 1. A published soft-voting ensemble confusion matrix shows the same structure: 86.0% of errors remain adjacent. We treat that adjacent share as the checkable claim—not a new leaderboard—and argue that Grade 3 recall and adjacent versus non-adjacent error counts should be reported before pooled accuracy is read as a deployment summary. Embedding protocol and ensemble confusion-matrix anchors follow a published two-stage colon pipeline; no new patients were enrolled.

Abstract: Pathology laboratories are a critical dependency across almost every diagnostic and treatment pathway. Pathology laboratories support healthcare delivery through analysing blood, urine, faecal and tissue samples, informing clinical diagnosis and tailoring patient treatment. However, laboratories have unique vulnerabilities to extreme weather events. To analyse samples and provide timely results, laboratories need highly-controlled environments and timelines. EWE can disrupt these and, when pathology laboratories fail or slow down during EWE, many healthcare services are disrupted simultaneously. In this study we have reviewed the impacts of heatwaves and flooding on pathology laboratories in G20 and European Union countries and any adaptation strategies that laboratories have put in place to mitigate those impacts. The PRISMA guidance was followed for a systematic search strategy that identified 1,133 articles for screening. Seven of these were included after full-text screening. Together with an additional two articles from backward citation searches, a total of nine articles were included in this review. Three reviewers were involved in this process. We found reports of widespread impacts of heatwaves and flooding on pathology laboratory staff, equipment, operations and internal and external supply chains. The perspectives of patients were mostly absent. While there were examples of adaptations deployed, we found little evidence of systematic evaluation to determine the cost-benefit of these adaptations, their health consequences or their impacts on health inequalities. Climate change will lead to more intense, frequent, volatile and unpredictable extreme weather events in most countries, which will increase pathology laboratory disruptions and subsequent impacts on healthcare pathways and patients. This should be a call for further action and the development of frameworks to enable pathology laboratories to implement and evaluate adaptations to extreme weather events-related disruptions that minimise disruption and deliver resilient pathology service provision to support patient care.

Abstract: Human forensic biobanks preserve biological materials and associated information for forensic investigation, evidence retention, research, quality assurance, method development, and training, yet the terminology, purposes, governance, and operating models of these resources remain heterogeneous across forensic disciplines. This scoping review will map how human forensic biobanks and related forensic imaging or data repositories are defined, established, operated, governed, and used. The review will follow the Arksey and O’Malley framework with refinements by Levac and colleagues and will be reported in accordance with PRISMA-ScR. PubMed, Scopus, CINAHL, PsycINFO, and Embase will be searched without date, geographic, or search-language restrictions, supplemented by reference-list and forward-citation searching. Eligible evidence will describe established human biological collections, retained biological evidence repositories, or qualifying forensic digital repositories with documented forensic purposes. Two reviewers will independently screen records; data will be charted using a piloted form and verified by a second reviewer. Findings will be synthesized descriptively and narratively, with publications distinguished from unique resources and physical, digital, and hybrid models mapped separately. The review is expected to characterize resource purposes, populations, specimens, and data types, governance, access, quality management, sustainability, and reported applications, while identifying implementation challenges and reporting gaps. By organizing a fragmented literature around the underlying resources rather than individual analytical findings, the review will provide a structured evidence base for future forensic biobank development, governance, and research.

Abstract:

Introduction: Continuing professional education in forensic practice requires curricula that address disciplinary expertise, interpretation, documentation, and communication while remaining responsive to changing professional needs. This scoping review aims to map how continuing professional education curricula are designed, delivered, assessed, evaluated, and quality-assured across forensic disciplines, including their relationship to ongoing professional competence. Accreditation, certification, and governance will be examined in relation to how they shape educational arrangements. Methods: The review will follow Arksey and O’Malley’s five-stage framework, incorporating Levac and colleagues’ refinements and JBI guidance. Reporting will follow PRISMA-ScR and PRISMA-S. PubMed, Embase, Scopus, CINAHL, and APA PsycINFO will be searched from inception to the final search date, with reference-list searching providing additional sources. Inclusion will be restricted to English-language publications without geographical restrictions. Eligible sources will address continuing professional education or competence maintenance among qualified or practicing forensic professionals and provide substantive information on curriculum design or educational assurance. Sources concerning only undergraduate, pre-licensure, entry-to-practice, or initial specialist education will be excluded unless a separable continuing-development component is reported. Two reviewers will independently screen titles, abstracts, and full texts using Covidence, with disagreements resolved through discussion or a third reviewer. A standardized charting form will be piloted on at least five eligible sources; one reviewer will chart each source, and a second will verify all entries. Results and Analysis: Data will be summarized descriptively and synthesized narratively across the following: learning needs assessment; competencies and objectives; curriculum content and structure; teaching and implementation; assessment and feedback; evaluation and revision; and educational quality assurance. Reported outcomes will be mapped to the four Kirkpatrick levels: reaction, learning, behavior, and results. Measurement methods and follow-up periods will be retained to distinguish immediate learning outcomes from retained competence and workplace application. The synthesis will identify shared educational elements, disciplinary variations, accessibility barriers, and reporting or evaluation gaps to inform subsequent curriculum development. Ethics and Dissemination: Ethical approval is not anticipated because the review will analyze published literature without collecting identifiable participant data. Findings will be disseminated through peer-reviewed publications, relevant professional meetings, and curriculum design summaries for educators, practitioners, professional associations, accrediting organizations, and forensic service leaders.

Abstract: Tumor budding, defined as single tumor cells or clusters of up to four cells at the invasive front, is a morphological marker of tumor-cell dissociation and stromal invasion in colorectal cancer. Standardization by the International Tumor Budding Consensus Conference (ITBCC) established a reproducible hematoxylin-and-eosin-based method and enabled broader incorporation of budding into pathology reporting and clinical risk assessment. Intermediate- and high-grade budding are associated with lymph node metastasis in pT1 colorectal cancer, while high-grade budding identifies a subgroup of stage II colon cancers with increased recurrence risk. Adverse prognostic associations have also been reported in stage III disease and in rectal cancer after neoadjuvant therapy, although evidence that budding predicts benefit from a specific treatment is still insufficient. At the biological level, budding is linked to partial epithelial-mesenchymal transition, altered cell adhesion, cytoskeletal remodeling, and interactions with fibroblasts, extracellular matrix, and immune cells. Digital pathology and artificial intelligence may improve hotspot selection, quantification, and spatial characterization, but their clinical use depends on external validation, control of domain shift, and continued pathologist oversight. Tumor budding is therefore best interpreted as a complementary morphological biomarker alongside TNM stage, established histopathological risk factors, molecular features, and clinical context.

Abstract: Serum protein electrophoresis (SPE) remains a central laboratory method for the detection and characterization of monoclonal gammopathies and other dysproteinemic patterns. Despite substantial analytical automation, interpretation still relies largely on graphical representation and expert visual assessment, making low-amplitude or borderline abnormalities particularly challenging. Artificial intelligence (AI), including machine-learning (ML) and deep-learning (DL) approaches, has increasingly been applied to SPE, with high performance reported for automated recognition of established abnormalities, particularly M-proteins, i.e., monoclonal immunoglobulins or immunoglobulin fragments produced by clonal plasma cells. However, most models have been developed against predefined diagnostic targets and evaluated using expert interpretation, immunofixation, or immunotyping as reference standards. Improved recognition of known abnormalities should therefore not be equated with discovery of additional clinically meaningful information. Modern electrophoretic platforms generate machine-readable numerical signals that may preserve features not explicitly considered during routine graphical interpretation. This creates the possibility of extending AI-assisted SPE from conventional pattern recognition toward detection of low-amplitude, distributed, or sub-visual signal characteristics. Yet current literature has focused predominantly on algorithmic performance, while the validation pathway required to determine whether additional AI-detected features are biologically meaningful and clinically actionable remains insufficiently defined. Evidence is strongest for automated M-protein recognition, including low-amplitude abnormalities, whereas non-canonical systemic patterns, longitudinal signal analysis, and AI-assisted decomposition of therapeutic monoclonal antibody interference remain exploratory. This critical review addresses this translational gap by evaluating AI applications according to the nature of detected information, strength of supporting evidence, and proximity to clinical implementation. We propose a translational framework in which additional AI-detected electrophoretic features progress through analytical validity, biological validity, clinical validity, and clinical utility before being considered actionable laboratory information.

Abstract: Tumor budding is a prognostic marker associated with epithelial-mesenchymal transition and tumor microenvironment in various tumors. The programmed cell death protein 1 (PD-1) pathway functions as a crucial immune checkpoint that regulates lymphocyte activity within the tumor microenvironment. The expression patterns of PD-1 ligands may significantly influence the potential success of therapeutic blockade of this pathway. This study aims to compare the expression of programmed cell death ligand 1 (PD-L1) with clinical-pathological features using different scoring systems and to evaluate its prognostic value in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors. A total of 361 cases of NSCLC were included in the study. A statistically significant association was found between patients with a negative combined positive score (CPS) or immune cell score (ICS) and those with an advanced clinical stage and poor tumor differentiation. A high tumor budding score correlated with positive PD-L1 expression across all three scoring systems. Overall survey (OS) revealed that PD-L1 positivity with ICS is a significant independent factor associated with a favorable prognosis. Kaplan-Meier analysis showed that CPS+ or ICS+ cases had significantly longer OS compared to CPS- or ICS- patients. In the immune checkpoint inhibitor group, no significant OS difference was found between positive and negative cases in TPS, CPS, and ICS. In conclusion, our study demonstrated a significant correlation between high tumor budding in NSCLC and PD-L1 expression in tumor and immune cells. We showed that CPS or ICS is a better predictor of prognosis in NSCLC.

Abstract: Chronic exposure to ethanol (ETH) and e-cigarette vapor activates the P2X7 receptor (P2X7R) in human pulmonary alveolar epithelial cells (hPAEpiCs), promoting extracellular vesicle (EV) release. Proteomic analysis of this EVs identified enrichment of urokinase-type plasminogen activator (uPA), a key extracellular matrix remodeling enzyme. Treatment of hPAEpiCs with ETH, acetaldehyde (ALD), and e-cigarette vapor, with or without nicotine, induced NLRP3 inflammasome activation, IL-1β secretion, and increased incorporation of uPA into EVs. Exposure of human brain microvascular endothelial cells (hBMVECs) to this EVs enhanced plasmin conversion, activated MMP-9 and TGF-β1, resulting in reduced transendothelial electrical resistance (TEER), indicating blood-brain barrier (BBB) dysfunction. Pharmacological inhibition of P2X7R using ‘A804598’ significantly reduced EV-associated uPA release and attenuated endothelial injury. In vivo, chronic ETH vapor exposure increased expression of uPA, uPAR, MMP-2, and MMP-9 while decreasing SERPIN1 and TIMP1 in murine brain microvessels, changes associated with BBB disruption and IgG leakage into brain parenchyma. P2X7R inhibition normalized these effects. Collectively, these findings identify EV-associated uPA as a mediator of lung-to-brain signaling and BBB injury following ETH and e-cigarette exposure.

Abstract: Bladder cancer surveillance remains challenging due to the limited sensitivity of con-ventional diagnostic methods for detecting biologically aggressive disease, particularly in low-grade urothelial carcinomas (LGUC). This study evaluated the diagnostic per-formance and biological significance of the urinary DNA methylation assay Bladder EpiCheck™ in patients undergoing histopathological evaluation for suspected urothe-lial carcinoma. A retrospective cohort of 134 patients with paired histopathology, urine cytology and Bladder EpiCheck™ results was analyzed. Bladder EpiCheck™ showed excellent performance for high-grade urothelial carcinoma (HGUC) detection, with 91.5% sensitivity, 81.6% specificity and an AUC of 0.876. Methylation scores in-creased with tumor grade and identified two molecular subgroups within LGUC. Methylation-positive LGUCs displayed HGUC-like epigenetic profiles, increased pro-liferation, more frequent MTAP loss and higher recurrence/progression risk, whereas methylation-negative LGUCs resembled benign urothelium and had more favorable outcomes. These findings indicate that urinary DNA methylation provides clinically relevant biological information beyond histological grading and may improve LGUC risk stratification and personalized surveillance.

Abstract: Purpose: Some sudden infant death syndrome (SIDS) and sudden unexpected infant death (SUID) cases remain unexplained after medicolegal investigation. The Metabolic Vulnerability Index (MVI) was proposed as a specimen-aware framework in which the total score summarizes measured multidomain findings and archetype classification organizes patterns of domain involvement. This review proposes a post-MVI framework for organizing candidate non-metabolic vulnerabilities after Stage 1 MVI classification. Methods: Literature on molecular autopsy, cardiac conduction-system pathology, concealed cardiomyopathy, epilepsy/SUDEP, autonomic or respiratory developmental disorders, and postmortem specimen constraints was synthesized into a staged eligibility framework, tiered escalation pathway, and pilot-implementation elements. Results: The framework distinguishes MVI-positive, confirmed low-MVI, and specimen-limited evaluations before routing eligible cases into a tiered pathway. Tier 1 prioritizes targeted cardiac channelopathy testing because of DNA robustness, family actionability, and relevance to autopsy-negative sudden death. Conditional Tier 2 addresses cardiac, neurologic, autonomic/respiratory-control, and structural mechanisms when supported by history, autopsy context, specimen readiness, or predefined triggers. Tier 3 is reserved for unresolved cases when research-level genomic expansion or specialized assessment is feasible and authorized. Stage 1 classification preserves indeterminate or not-evaluable results rather than treating missing findings as normal and separates exposure-context abstraction from score-eligible analytic findings and research-only measurements. Conclusions: The staged MVI/post-MVI model organizes unexplained SIDS/SUID cases into specimen-aware research profiles that integrate abnormal domain patterns, domain evaluability, exposure context, and post-MVI findings. These profiles can generate testable hypotheses about the biologic or physiologic pathways underlying candidate vulnerability. Pilot studies can establish the feasibility and reproducibility of domain collection; subsequent adequately powered studies can determine whether recurring patterns distinguish biologically meaningful subgroups within heterogeneous SIDS/SUID. The resulting classifications remain research constructs and do not constitute diagnoses or individual cause-of-death determinations.

Abstract: As a common benign bone tumor, the pathological diagnosis of chondrogenic tumors needs to accurately analyze the calcification pattern of the cartilage matrix, key spatial topology information, and other important indicators. However, chondrogenic tumors is a rare disease, doctors lack sufficient reference data and experience in diagnosis. At the same time, complex spatial structural information also increases the difficulty of diagnosis, which leads to inconsistencies in the diagnosis’s results of different doctors. In contrast, with the development of technology, artificial intelligence (AI) with its fast, accurate, and robust characteristics can effectively improve the efficiency and accuracy of diagnosis. However, the application of AI in this field is still unrecognized, so it is urgent to develop a model that can help doctors in diagnosis to improve accuracy and efficiency. In this study, we propose XChondNet, an explainable spatial-context-aware synergistic deep feature fusion model for WSI-based chondrogenic tumor classification. The model proposes a fusion mechanism of pathological and positional features so that the model can effectively perceive spatial structural information and a parallel classifier mechanism based on potential coding, which can effectively solve the problem of class imbalance in chondrogenic tumors data. We evaluated the XChondNet model on our chondrogenic tumors dataset and the experimental results verified its effectiveness in the classification of the chondrogenic tumors subtype. In the test phase, compared to the other advanced models, the XChondNet model achieved state-of-the-art accuracy (ACC), area under the curve (AUC), F1 score and Recall rate. And the XChondNet model explicitly reflects the consistency with pathologists’ concerns, which improves the interpretability of AI.

Abstract: Background: Esophageal squamous cell carcinoma (ESCC) accounts for over 80% of esophageal cancer cases globally. Accurate preoperative prediction of lymph node metastasis (LNM) is critical for treatment decision-making, yet current clinical staging frequently underestimates nodal disease burden. Pathomics — the high-throughput quantitative analysis of histopathological images — offers an opportunity to capture tumor microenvironmental patterns invisible to routine microscopy. We aimed to develop and validate a pathomics-clinical integrated model for predicting LNM in resectable ESCC. Methods: A total of 477 consecutive ESCC patients who underwent radical esophagectomy were retrospectively enrolled. After excluding 61 patients with missing data, 416 patients were included in the final analysis (LNM-positive: 217, 52.2%). H&E-stained whole-slide images were acquired using a KFBIO KF-PRO-400-HI scanner at 20× magnification (pixel size 0.5 μm/px). Nuclear morphological features were extracted via QuPath hematoxylin optical density (OD)-based detection, yielding 17 pathomic features selected by LASSO-logistic regression. A combined clinical-pathomics nomogram was constructed and internally validated via 10-fold cross-validation (out-of-fold, OOF), with apparent (resubstitution) performance reported alongside to quantify optimism. Secondary analyses examined survival stratification within node-negative (pN0) patients and across whole-cohort risk groups. The final nomogram was additionally applied, without refitting, to an independent external cohort of 101 ESCC patients from a separate institution to assess transportability. Results: The combined nomogram achieved an out-of-fold (cross-validated) AUC of 0.821 (95% CI 0.779–0.858), compared with 0.791 for the clinical model and 0.762 for the pathomics-alone model. In multivariable analysis, the pathomics score remained an independent predictor of LNM (adjusted OR 2.47, 95% CI 1.80–3.39; P < 0.001), with significant incremental value over clinical variables alone (likelihood-ratio χ² = 35.5, P = 2.56e-09). Risk stratification by nomogram score tertiles showed a clear gradient of LNM prevalence: 15.8% (low-risk), 55.1% (intermediate-risk), and 85.6% (high-risk) (Cochran-Armitage trend P < 0.001). In the pN0 subgroup (n = 199), patients with high pathomics risk had significantly worse overall survival (3-year OS: 77.2% vs. 94.3%; log-rank P = 0.005) and progression-free survival (3-year PFS: 75.5% vs. 88.9%; log-rank P = 0.007). Externally, in an independent cohort of 101 patients from a separate institution (LNM+ = 25, 24.8%), the combined model achieved an AUC of 0.774 (95% CI 0.663–0.870), the clinical model 0.801, and the pathomics-alone model 0.685, confirming partial transportability of the clinical component while the pathomics signature showed limited generalizability across centers. Conclusions: The integration of quantitative pathomic features with conventional clinicopathological variables provides robust predictive power for LNM in ESCC and identifies a subset of node-negative patients at elevated risk of poor outcomes. These findings support the potential utility of pathomics as a complementary tool for preoperative risk stratification in ESCC. External validation in an independent cohort confirmed partial transportability of the clinical component but highlighted limited generalizability of the pathomics signature, underscoring the need for multi-center harmonization before clinical deployment.

Abstract: Background: Programmed death-ligand 1 (PD-L1) contributes to immune escape and is a therapeutically relevant target in aggressive B-cell lymphomas. However, its distribution and clinicopathologic significance across primary mediastinal aggressive large B-cell lymphomas remain incompletely defined. Methods: We retrospectively reviewed 53 cases diagnosed between 2010 and 2025, including diffuse large B-cell lymphoma (DLBCL), primary mediastinal large B-cell lymphoma (PMBCL), mediastinal gray zone lymphoma (MGZL), and T-cell/histiocyte-rich large B-cell lymphoma (THRLBCL). PD-L1 immunohistochemistry (clone 22C3) was performed on formalin-fixed, paraffin-embedded tissue. Tumor cells and intratumoral inflammatory cells were assessed together. Membranous staining was scored as 0, 1+, 2+, or 3+, and the proportion of cells in each category was recorded. Results: PD-L1 staining was present in 40/53 cases (75.5%). Mean PD-L1-positive percentages were similar in DLBCL, PMBCL, and MGZL (38%, 36%, and 44%, respectively; p = 0.939), and no tested cutoff separated the diagnostic groups. In contrast, MGZL showed a higher mean 3+ component (31.11%) and more cases with 3+ staining in at least 50% of evaluated cells (44% vs. 4.3% in DLBCL and 4.7% in PMBCL; p = 0.007). PD-L1 extent was not associated with age, tumor size, LDH, beta-2 microglobulin, Ann Arbor stage, SUVmax, treatment response, or overall survival. Conclusions: PD-L1 expression is common in mediastinal aggressive large B-cell lymphomas. MGZL is distinguished by a strong-staining pattern, whereas combined PD-L1 extent was not prognostic in this cohort.