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.

Biliary atresia (BA) is a severe pediatric cholangiopathy characterized by rapidly progressive liver fibrosis. This study aimed to characterize scar-associated macrophages and investigate the role of plasminogen (PLG)–plasminogen receptor with a C-terminal lysine (PLGRKT) signaling in BA-associated fibrogenesis.

Single-cell RNA sequencing and spatial transcriptomics were applied to liver tissues from patients with BA and non-BA controls. Key findings were validated in an independent cohort using quantitative polymerase chain reaction and multiplex immunohistochemistry. The functional role of the PLGRKT pathway was further examined using primary human peripheral blood mononuclear cell-derived macrophages with small interfering RNA (siRNA)-mediated PLGRKT knockdown, together with co-culture systems involving LX-2 hepatic stellate cells and human liver organoids. In vivo therapeutic potential was evaluated in a murine bile duct ligation model of cholestatic liver fibrosis using macrophage-targeted Plgrkt–Trem2 antibody–siRNA conjugates.

In BA, scar-associated macrophages (SAMs) increased with fibrosis progression and co-localized with hepatic stellate cells in fibrotic areas. PLGRKT was upregulated in BA liver tissue and increased during monocyte-to-macrophage differentiation. In primary human macrophages, PLG induced a PLGRKT-dependent pro-fibrotic phenotype, and conditioned medium from these cells increased COL1A1 deposition in hepatic stellate cells and human liver organoids. In vivo, macrophage-targeted Plgrkt–Trem2 antibody–siRNA conjugates reduced SAM accumulation and attenuated bile duct ligation-induced liver fibrosis.

These findings support a role for SAMs and the PLGRKT–SAM axis in BA-associated liver fibrosis and suggest that PLGRKT warrants further investigation as a potential macrophage-directed anti-fibrotic target.

Metabolic dysfunction-associated steatotic liver disease affects roughly 38% of adults, yet approved agents do not correct the upstream redox-metabolic perturbations—a depressed nicotinamide adenine dinucleotide (NAD+/NADH) ratio, saturated lipid excess, and endoplasmic reticulum (ER) stress—that drive hepatocyte injury. Cytochrome b5 reductase 3 (CYB5R3) couples NADH oxidation to fatty acid desaturation, nuclear factor erythroid 2-related factor 2 (NRF2)-linked antioxidant and cholesterol-handling pathways, NAD+/sirtuin signaling, and ER-phagy, and is the sole electron input to mitochondrial amidoxime-reducing component 1 (mARC1). This review grades every link in the axis across the steatosis–cirrhosis–hepatocellular carcinoma spectrum, reporting effect estimates with sample sizes and test statistics alongside a study-level appraisal of clinical relevance. The common MTARC1 p.A165T variant protects against all-cause cirrhosis (odds ratio, 0.91; 95% CI, 0.89–0.94; P = 2.3 × 10−11; 12,361 cases, 790,095 controls), with lower hepatic fat, liver enzyme levels, and low-density lipoprotein cholesterol levels. Germline mARC1 deletion reduces picrosirius red fibrosis area by 24%–50% depending on diet, without altering histological disease activity, whereas partial protein reduction confers no protection. Critically, therapeutic hepatocyte-directed knockdown loses its anti-fibrotic effect when started at higher disease burden and in the choline-deficient model: efficacy depends on the depth, compartment, and timing of inhibition. Deep, hepatocyte-restricted mARC1 inhibition by GalNAc-conjugated oligonucleotides—which also avoids a male-predominant cardiac liability—is therefore the most credible near-term strategy, only in pre-cirrhotic F2–F3 disease. CYB5R3 activation, and its combination with mARC1 inhibition, remain unproven, and no clinical trial of this axis has been reported. Falsifiable in vivo and pharmacodynamic biomarker roadmaps are proposed, together with the efficacy, delivery, and safety uncertainties specific to advanced cirrhosis and a non-invasive pharmacodynamic framework.

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.

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.

Balloon-occluded transarterial chemoembolization (B-TACE) has emerged as a significant advancement in the locoregional treatment of hepatocellular carcinoma. This technique utilizes a balloon microcatheter selectively placed in target hepatic arteries to occlude blood flow and enhance drug accumulation within tumors while minimizing systemic exposure. The feasibility, safety, and effectiveness of the balloon occlusion technique have been verified. Recent studies have demonstrated that B-TACE achieves superior tumor response rates and potentially improves survival outcomes compared with conventional transarterial chemoembolization (C-TACE) techniques, particularly in cases with complex tumor vasculature or C-TACE-refractory disease. However, determining which patients would benefit from B-TACE requires comprehensive assessment. It remains to be determined in clinical practice whether this technique increases the risk of liver function impairment or is associated with specific complications. Further research is needed to better understand the technical conditions required for its clinical application, prognostic factors, and how it can be combined with other interventional techniques. This review summarizes the current literature on B-TACE, focusing on its technical principles, clinical efficacy, safety profile, and evolving role within the contemporary treatment landscape for advanced hepatocellular carcinoma, including its integration with systemic therapies.

Estrogen receptor alpha, encoded by the ESR1 gene, is a major oncogenic driver in hormone receptor-positive/HER2-negative breast cancers. While endocrine therapies are effective in treating this subgroup, patients with advanced or metastatic disease may develop resistance associated with acquired somatic ESR1 mutations. This mini review summarizes recent clinical and technological advances in understanding ESR1 mutations, newly approved targeted therapies, and the use of liquid biopsy companion diagnostics, with a focus on their implications for pathologists.

We conducted a narrative review of PubMed-indexed literature and relevant regulatory and guideline sources related to ESR1 in breast cancer, with an emphasis on recent peer-reviewed studies of ESR1 mutations and clinical trials of emerging therapies.

This review describes the molecular features of ESR1 alterations and estrogen receptor pathway biology, the mechanisms and key trial data for recently approved ER-targeted therapies for ESR1-mutated breast cancer. Additionally, it evaluates liquid biopsy testing platforms for detecting ESR1 mutations, discusses the advantages and limitations of liquid biopsy in detection of treatment resistance, and considers the evolving role of pathologists in breast cancer care.

Acquired ESR1 mutations are major drivers of endocrine therapy resistance. Next-generation sequencing and liquid biopsy have increasingly informed the clinical management of breast cancer in the past decade. Pathologists can play an important role in implementing molecular testing, interpreting complex biomolecular data, and helping to guide timely treatment decisions in the era of precision oncology.