Currently, risk stratification for pediatric Hodgkin lymphoma is based on clinical factors such as stage, bulk, and systemic symptoms. Novel minimally invasive biomarkers could enhance both prognosis and treatment strategies. Therefore, the plasma extracellular vesicles’ microRNA profile was characterized by small RNA sequencing in 36 classical Hodgkin lymphoma cases and these findings were confirmed in an extended cohort of 86 patients by RT-qPCR. It was found that the levels of miR-122-5p at diagnosis were significantly higher (p-value: 0.0002) in patients who relapsed compared to patients in remission. The 5-year event-free survival of cases with high and low levels of miR-122-5p was 65 ± 7% and 93 ± 4%, respectively. MiR-122-5p levels were significantly associated with clinical events in both univariate (p-value: 0.0009) and multivariate (p-value: 0.0037) analysis (hazard ratio 5.8). Target prediction analysis suggests an involvement in the polarization of immune cells. The phenotypic characterization of peripheral blood mononuclear cells in 12 patients showed significantly increased levels of CD4+ T-cells in cases with high miR-122-5p levels as compared to low levels (p-value: 0.048). Moreover, CCL17 (TARC) and IL-6 plasma levels at diagnosis were significantly higher as compared to healthy donors (p-value: ≤0.0001). MiR-122-5p could complement current prognostic assays to identify patients at high risk of relapse.

Background: The level of type-I interferons (IFNs) in primary sclerosing cholangitis (PSC) was investigated to evaluate its association with disease activity and progression. Methods: Bioactive type-I IFNs were evaluated in a murine model of PSC and human patients’ sera using a cell-based reporter assay and ELISA techniques. In total, 57 healthy participants, 71 PSC, and 38 patients with primary biliary cholangitis were enrolled in this study. Results: Bioactive type-I IFNs were elevated in the liver and serum of multidrug resistance protein 2–deficient animals and showed a correlation with the presence of CD45⁺ immune cells and serum alanine transaminase levels. Concordantly, bioactive type-I IFNs were elevated in the sera of patients with PSC as compared to healthy controls (sensitivity of 84.51%, specificity of 63.16%, and AUROC value of 0.8267). Bioactive IFNs highly correlated with alkaline phosphatase (r=0.4179, p<0.001), alanine transaminase (r=0.4704, p<0.0001), and gamma-glutamyl transpeptidase activities (r=0.6629, p<0.0001) but not with serum bilirubin. In addition, patients with PSC with advanced fibrosis demonstrated significantly higher type-I IFN values. Among the type-I IFN subtypes IFNα, β and IFNω could be detected in patients with PSC with IFNω showing the highest concentration among the subtypes and being the most abundant among patients with PSC. Conclusions: The selectively elevated bioactive type-I IFNs specifically the dominating IFNω could suggest a novel inflammatory pathway that might also have a hitherto unrecognized role in the pathomechanism of PSC.

Human-derived biomaterials offer several advantages over animal-derived or synthetic alternatives, including improved biocompatibility, ethical acceptability, sustainability, and clinical translatability. Here we present new applications of human placenta-derived materials – specifically HUMAN PLACENTA substrate, collagen type-I, and Laminin-111 – as 2D coating materials and 3D matrices for the cultivation of spheroids and adherent cells. Collagen type-I coatings supported colorectal cancer spheroid formation without the need for growth-factor supplementation. Lm-111 significantly enhanced NIH3T3 fibroblast adhesion compared with poly-L-lysine and rat-tail collagen type-I, performing comparably to bovine fibronectin. In a transwell blood–brain barrier model, HUMAN PLACENTA substrate coatings enabled confluent endothelial monolayers with transendothelial electrical resistance values not significantly different from the conventional human collagen type-IV/bovine fibronectin mixture. Across these in vitro models, placenta-derived materials performed comparably or better than conventional animal-derived and synthetic coatings, supporting robust cell viability, adhesion, and barrier formation. Due to their human origin, these biomaterials exhibit reduced biological complexity while enhancing biocompatibility and translational relevance. Therefore, they provide a sustainable, ethically acceptable alternative for advanced cell culture systems.

Within the Liver Imaging Reporting and Data System (LI-RADS), LI-RADS Malignant (LR-M) lesions remain diagnostically challenging: imaging indicates malignancy, but often fails to distinguish hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (iCCA). Established serum-based tools, such as GALAD, are optimized for HCC, but are not designed to resolve entity ambiguity within LR-M. In this pilot proof of concept study, we investigated whether small extracellular vesicles (EVs) integrated with routine serological markers could resolve LR-M lesion situation. A rare LR-M cohort (HCC = 25, iCCA = 25) was evaluated using least absolute shrinkage and selection operator (LASSO) logistic regression and PCA to prioritize informative biomarkers. Hybrid models combined CD9⁺CD133/2⁺ and CD81⁺CD133/2⁺ EVs with alkaline phosphatase, serum C-reactive protein, CA19-9, and optional alpha-fetoprotein (AFP). Models were internally validated using an 80:20 train-test split and assessed with bootstrap and Monte Carlo perturbation (±5-20%). Individual markers demonstrated limited discrimination (AUROC ≤0.82). Hybrid logistic regression models showed moderate internal discrimination (AUROC 0.86 with AFP; 0.91 without AFP). Translation into additive scoring systems using ROC-Youden-derived cut-offs yielded high internal AUROC estimates (e.g. 0.95-0.96), although these remain internally validated. A simplified 5-point PRISM score retained comparable discriminatory performance (AUROC ∼0.91). In an exploratory survival analysis among patients with iCCA (n = 25), those with above-median CD9⁺CD133/2⁺ EV levels (n = 13) had shorter overall survival (median 91 vs. 389 days; HR: 2.80, 95% CI: 1.16-6.74; p = 0.005). Integrated EV and serological profiling could enable minimally invasive differentiation between HCC and iCCA within LR-M lesions. By transforming machine learning (ML)-guided model discovery into a clinically interpretable paper-and-pencil additive score, we illustrate a translational pathway from computational discovery to practical application. This study provides a scientific rationale for integrating small EV phenotyping with conventional serum biomarkers to improve minimally invasive differentiation between HCC and iCCA in LR-M lesions. By translating a machine learning (ML)-derived hybrid model into a simple additive scoring system, we demonstrate how ML can yield clinically interpretable tools that bridge computational discovery and bedside application. The findings are particularly relevant for hepatologists, oncologists, and radiologists managing patients in whom imaging remains indeterminate and biopsy carries procedural risk. The 5-point model can be applied using routine laboratory values, providing a paper-and-pencil diagnostic aid that requires no specialized software or hardware. Although external multicenter validation is necessary given the cohort size, this approach illustrates how transparent, interpretable ML can support precision diagnostics in primary liver cancer.