Hepatitis B virus (HBV) vertical transmission remains a major health challenge, and the characteristics of the placental immune microenvironment in chronic infection remain unclear. This study aimed to use mass cytometry to comprehensively analyze phenotypic changes in placental immune cell subsets.

We collected placental tissues from 20 pregnant women (6 healthy controls and 14 with chronic HBV infection). CD45+ leukocytes were detected using a 35-marker antibody panel. Unsupervised clustering identified 14 clusters, of which 13 immune clusters were analyzed.

HBV mainly caused functional remodeling of placental immune cells rather than changes in cell composition (P > 0.05 for all subsets). In natural killer (NK) cells, CD38 (P = 0.015) and CD16 (P = 0.0020) were notably upregulated and strongly correlated (ρ = 0.872, P < 0.001), suggesting potentially enhanced antibody-dependent cellular cytotoxicity (ADCC) function. T cells showed upregulation of CD27, CD38, and CXCR5. Basophils exhibited the most pronounced changes: 9 differential markers (including chemokine receptors CCR4 and CCR7) were consistently downregulated. Classical monocytes showed an M1 polarization tendency (CD38↑, CD163↓). All P-values were raw; no markers remained significant after false discovery rate (FDR) correction at an FDR threshold of < 0.1, indicating nominal significance. In addition, the coordinated expression patterns of markers within multiple cell subsets were weakened after infection.

These exploratory findings suggest that HBV may reshape placental immunity through enhanced NK cell activation, broad basophil suppression, and disrupted marker coordination. The sample size was limited (n = 20), so the results need to be validated in larger cohorts. These findings provide new perspectives for understanding the mechanisms of mother-to-child transmission.

EWSR1 fusions are recurrent genetic alterations in a wide spectrum of mesenchymal tumors and are often associated with specific clinicopathologic entities. However, the presence of an EWSR1 rearrangement does not always indicate a functional or disease-defining fusion.

We report a case of undifferentiated pleomorphic sarcoma with high-grade morphologic features harboring an EWSR1 rearrangement detected by fluorescence in situ hybridization. It was subsequently characterized by RNA sequencing as a likely nonfunctional fusion of EWSR1 exon 1 and NF2 intron 1. Histologically, the tumor was composed of pleomorphic spindle cells with brisk mitotic activity and lacked a specific line of differentiation. Immunohistochemically, the tumor showed diffuse cytoplasmic S100 positivity, with nuclear staining in a subset of tumor cells, while the overall immunophenotype did not support a specific line of differentiation. The EWSR1::NF2 fusion was inferred to have a tail-to-tail configuration, and additional KRAS and TP53 alterations were detected.

This case highlights that an EWSR1 rearrangement detected by fluorescence in situ hybridization should be interpreted cautiously and does not necessarily represent a functional or disease-defining fusion. Comprehensive molecular evaluation is important for the accurate interpretation and classification of sarcomas with atypical EWSR1 rearrangements.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly prevalent worldwide and is frequently encountered in patients undergoing liver transplantation and hepatic surgery. Although hepatic steatosis was once considered a relatively benign condition, accumulating evidence indicates that MASLD is associated with reduced tolerance to ischemic stress and increased susceptibility to ischemia–reperfusion injury, which may contribute to graft dysfunction and postoperative liver injury. In this mini review, we used the concept of hepatic resilience, referring to the ability of the liver to maintain homeostasis during stress and recover after injury. We discussed how MASLD may reduce hepatic resilience through mechanisms involving lipotoxicity, mitochondrial dysfunction, oxidative stress, inflammatory activation, regulated cell death, and impaired regeneration. MASLD represents a heterogeneous disease spectrum, and susceptibility to ischemia–reperfusion injury may differ according to disease stage and phenotype, particularly in the presence of progressive inflammation and fibrosis. We further summarized strategies aimed at improving hepatic resilience, including metabolic optimization, mitochondrial protection, modulation of reperfusion-associated inflammation, and enhancement of tissue repair. However, current evidence remains limited by the paucity of human studies and validated approaches for assessing hepatic resilience. Further investigation of these mechanisms may help develop individualized strategies to protect the liver in patients with MASLD during hepatic surgery and transplantation.

CXC chemokine receptor 2 (CXCR2) expression has been observed in normal neuroendocrine cells, but its role in neuroendocrine neoplasms is less well established. We aimed to evaluate CXCR2 expression with somatostatin receptor type 2 (SSTR2) expression in pancreatic neuroendocrine tumors (PanNETs) and small intestinal neuroendocrine tumors (SI-NETs).

This was a cross-sectional study. Pathology archives were searched for PanNETs with ≥2 resected liver metastases and SI-NETs with resected liver metastases, mesenteric tumor deposits (MTDs), and/or peritoneal metastases. Immunohistochemistry for CXCR2 was performed on de-identified tissue microarrays containing PanNETs and SI-NETs. SSTR2 and CXCR2 immunohistochemistry was also performed on tumor blocks from primary and metastatic PanNETs and SI-NETs. Based on H-scores, expression was scored as negative (<50), weak (50–100), moderate (>100–200), or strong (>200). Marker expression was descriptively reported among primary tumors, liver metastases, MTDs, and peritoneal metastases.

Among 12 primary PanNETs and 38 liver metastases, mean CXCR2 H-scores were 269.6 ± 36.7 and 254.6 ± 75.5, respectively, and mean SSTR2 H-scores were 261.5 ± 61.9 and 259.3 ± 70.9, respectively. All 84 SI-NET lesions showed moderate/strong CXCR2 expression, whereas 12 showed negative/weak SSTR2 expression. CXCR2 H-scores were 284.0 ± 26.5 in primary tumors, 272.5 ± 28.7 in MTDs, 269.6 ± 42.8 in liver metastases, and 265.0 ± 51.5 in peritoneal metastases. SSTR2 expression appears to be lower in MTDs than in primary tumors (182.2 ± 76.5 vs 235.9 ± 55.9).

CXCR2 is moderately/strongly expressed in most sampled PanNETs and all sampled SI-NETs. In SI-NETs, moderate/strong CXCR2 expression is less heterogeneous than SSTR2 expression.

Standardized pathologic sampling and reporting are essential for pancreatic cancer staging, prognosis assessment, and comparable clinical data. This guideline aimed to develop evidence-based recommendations for standardized pathologic sampling and diagnostic reporting of pancreatic cancer in China. Literature searches were conducted in English and Chinese databases, guideline websites, Google, and reference lists for records published before December 31, 2023. Two investigators screened and extracted the evidence; methodological quality and certainty were assessed using AMSTAR/AGREE II and GRADE, respectively; and recommendations were formulated through two rounds of modified Delphi consultations, with an agreement threshold of ≥ 75% for consensus. The final guideline includes 11 recommendations, including six strong and five weak recommendations, addressing margin and surface assessment, sampling methods, histologic classification and grading, lymphovascular and perineural invasion, TNM staging, tumor regression grading after neoadjuvant therapy, background lesions, and structured reporting. These recommendations provide a standardized framework for pathologic assessment and reporting of pancreatic cancer resection specimens and may support more consistent prognostic evaluation and clinical decision-making.

Machine-learning approaches that combine predictive performance with model interpretability may improve lung cancer status classification. This study aimed to develop and internally evaluate an Explainable Precision Screening Framework for lung cancer risk classification using demographic, behavioral, and symptom-based variables from a publicly available dataset.

This retrospective cross-sectional study analyzed a publicly available Kaggle dataset containing 309 records, including 270 labeled as lung cancer and 39 as non-cancer. Six models—logistic regression, support vector machine (SVM), random forest, LightGBM, XGBoost, and a stacking ensemble—were compared using a stratified hold-out test set and repeated stratified five-fold cross-validation. Performance was assessed using classification metrics with bootstrap 95% confidence intervals (CIs). A separate Shapley additive explanations (SHAP) analysis was applied to the standalone SVM model for exploratory feature attribution.

Across all models, accuracy ranged from 85% to 92% (ROC-AUC: 0.93–0.95). The stacking ensemble achieved 0.92 accuracy (95% CI: 0.85–0.98), 0.94 sensitivity (95% CI: 0.88–1.00), 0.75 specificity (95% CI: 0.40–1.00), 0.96 precision (95% CI: 0.89–1.00), 0.95 F1 score (95% CI: 0.91–0.99), and 0.95 ROC-AUC (95% CI: 0.89–0.99). Its PR-AUC was 0.993 (95% CI: 0.981–0.999), and its Brier score was 0.074 (95% CI: 0.037–0.121). SHAP analysis identified smoking, yellow fingers, coughing, chest pain, wheezing, shortness of breath, and age as the features contributing most strongly to its predictions.

Within this public retrospective dataset, the stacking ensemble was among the highest-performing models, whereas separate SHAP analysis of the standalone SVM model identified the features contributing most strongly to its predictions. Given the marked class imbalance, the absence of a reported clinical reference standard for the source labels, the framework requires independent validation in clinically verified multicenter cohorts before clinical use.

Non-muscle-invasive bladder cancer (NMIBC) is characterized by a high recurrence rate and a substantial long-term surveillance burden. However, current detection and surveillance strategies rely largely on invasive cystoscopy and urine cytology, which are limited by patient discomfort, suboptimal adherence, and insufficient sensitivity, particularly for low-grade disease. This mini review examines the role of liquid biopsy in the detection, risk stratification, and surveillance of NMIBC. It summarizes current evidence on circulating tumor DNA, circulating tumor cells, exosomes and extracellular vesicles, urinary tumor DNA, and DNA methylation and protein biomarkers in blood or urine. For detection, urine-based molecular assays complement cystoscopy and cytology in the noninvasive assessment of patients with suspected bladder cancer. For risk stratification, molecular detection of residual disease and longitudinal biomarker changes help identify patients at increased risk of recurrence or progression. During surveillance, urine-based assays support earlier recurrence detection and, in selected settings, help reduce the frequency of cystoscopy. Overall, liquid biopsy is a promising minimally invasive complement to conventional NMIBC management although technical standardization and prospective clinical validation are required before routine implementation.