Liver cancer is a major public health issue in five East Asian countries, with metabolic factors becoming primary drivers. Based on the Global Burden of Disease (GBD) 2023 database, we extracted the total number and age-standardized mortality rates, years lived with disability (YLDs), years of life lost (YLLs) and disability-adjusted life years (DALYs) related to liver cancer attributable to metabolic risks (LC-MR). We analyzed the disease burden of LC-MR and trends across five East Asian countries from 1990 to 2023, examining patterns by sex and age as well as key drivers across different nations, and projected future trends through 2053. In 2023, Mongolia exhibited the highest age-standardized rates for LC-MR, while China ranked first in the total absolute number of cases. From 1990 to 2023, the overall disease burden showed a downward trend in Japan and Republic of Korea, whereas an upward trend was observed in Mongolia, Democratic People's Republic of Korea, and China. Significant sex and age disparities were observed across all countries in that males bore a higher burden and the burden generally shifted towards the elderly population. Decomposition analysis revealed that the changes in disease burden in Japan and Republic of Korea were primarily driven by population ageing, whereas the main drivering factors were epidemiological changes and population growth in Mongolia and Democratic People's Republic of Korea. Projections of disease burden for 2053 indicate that the disparities among countries would further widen. Therefore, strengthening metabolic risk interventions and implementing targeted prevention strategies for high-risk populations, especially the aging population, is crucial for reducing the regional burden of LC-MR, given the risk disparities across different countries.

To engage health care providers in Canada to identify the roles, tasks, processes, assessments, and triaging decisions for a Physiotherapist (PT) Navigator role that will be implemented and evaluated in a future trial.

A two-round, online, modified reactive Delphi study was used. Any licensed health care practitioner in Canada who works with individuals with or beyond cancer was eligible to participate. Round 1 identified qualitative feedback on role domains to guide role improvement. Qualitative feedback was examined in duplicate using content analysis. Round 2 identified quantitative feedback to gather numerical data to establish consensus. Quantitative survey feedback was analysed using descriptive statistics including mean and standard deviation. Items were added to the role description if identified by ≥10% of respondents, and 75% was the threshold to define consensus. Lastly, a consensus meeting including end users was held to consider priority items and utility of role translation into clinical practice.

Consensus on the PT Navigator role description was achieved following the two survey rounds (Round One; n = 34, Round Two; n = 18). Four domains were identified to define the role: process, assessment, triaging decisions, and duties and responsibilities. A figure visualizing the PT Navigator role was generated. Changes to the role after survey feedback included increasing appointment times with the PT Navigator, longer duration between follow-ups, patient self-referral, and additional objective testing. Consensus meeting feedback considered the variability in follow-up depending on different treatment timelines and an emphasis on promoting self-management strategies. Perceived usefulness of the role was high (mean 9.19/10; SD 2.12).

This modified Delphi study identified key domains that would inform development of a comprehensive PT Navigator role working with cancer patients. The role offers a novel approach to promote routine assessment and early intervention, with the aim towards integrating PTs meaningfully within cancer care settings in Canada.

Deep learning has shown promising performance in cervical cytology; however, many studies have relied on presegmented single-cell images rather than the more complex morphologic patterns encountered in routine practice. Here, scattered cells were defined as isolated or dissociated, nonoverlapping single cells. This study quantified the performance loss when artificial intelligence (AI) models trained on these cells were applied to hyperchromatic crowded cell groups (HCGs).

Binary convolutional neural network models were developed to differentiate between negative for intraepithelial lesion or malignancy cases and high-grade squamous intraepithelial lesion cases via a scattered cell data set composed of institutional and public liquid-based cytology images. The scattered cell data set comprised 101 cases, with 1062 images; the independent HCG data set comprised 48 cases, with 330 images. ResNet-50, ResNeXt-50, ConvNeXt-Tiny, EfficientNet-B3, VGG-19, and GoogLeNet were trained on scattered cell images, and then directly applied to HCGs without retraining or threshold recalibration.

All models showed high performance on the scattered cell data set, with the area under the receiver operating characteristic curve (AUC) ranging from 0.950 to 0.996. When directly applied to HCGs, performance declined across all architectures, with the AUC ranging from 0.385 to 0.683. ConvNeXt-Tiny showed the highest AUC on HCGs (0.683); however, this remained substantially lower than its performance on scattered cells (0.996). For all architectures, the AUC was significantly lower on HCGs than on the scattered cell data set.

Binary AI models trained on scattered cell images achieved excellent discrimination in the original setting but their performance was not preserved when directly applied to HCGs. These findings underscore the need for direct validation and HCG-aware model design in cervical cytology AI.

Copyright: © 2026 dos Santos et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Ewing sarcoma (ES) is an aggressive childhood tumor. We have previously shown that tropomyosin receptor kinase (Trk) neurotrophin receptors regulate viability, and the Trk and multi-kinase inhibitor K252a restores sensitivity to chemotherapy, in ES cells. Here, we show that administration of K252a in mice transiently delays ES tumor growth and reduces expression and phosphorylation of multiple targets. BALB/c nu/nu nude mice inoculated with SK-ES-1 ES cells were given daily intraperitoneal (i.p.) injections of K252a for 18 days. Immunohistochemical analysis of tumors was performed to quantify the expression and phosphorylation of Trk receptors, phosphoinositide 3-kinase (PI3K), and insulin-like growth factor 1 receptor (IGF1R). Treatment with K252a led to a partial and transient delay in ES tumor growth and reduced the expression and phosphorylation of TrkA, TrkB, PI3K, and IGF1R. Combined treatment with K252a and the IGF1R inhibitor NVP-ADW742 was more effective in reducing ES cell viability than each compound alone. Associations between genes encoding Trks, PI3K, and IGF1R and overall survival (OS) in patients with ES was examined. Significant associations between expression of NTRK genes and patient OS were found, indicating that NTRK genes should be further evaluated as biomarkers for prognosis in patients with ES.

Myelodysplastic syndromes (MDS) and acute myeloid leukemias (AML) harboring TP53 mutations are defined by extreme genomic instability, complex karyotypes (CK), and poor prognosis. While large-scale chromosomal imbalances are common in CK-MDS/AML, the synergy between focal amplifications of signaling drivers and the disruption of transcriptional regulators remains poorly elucidated.

We performed a comprehensive clinical, cytogenetic (GTG-banding, M-FISH, M-Band), and molecular (targeted FISH, NGS) analysis of seven patients with MDS and AML characterized by a recurrent and distinct genomic signature.

All cases exhibited highly complex karyotypes on a TP53-mutated background. We identified high-level focal amplifications of EPOR (19p13.2) and JAK2 (9p24.1), predominantly manifesting as homogeneously staining regions (HSRs) or complex "sandwich-like" derivative chromosomes. Notably, these signaling alterations consistently co-occurred with monoallelic deletions of the TCF3 (E2A) tumor suppressor (19p13.3) and copy number gains of the ERG transcription factor (21q22). Detailed structural analysis indicates that TCF3 loss likely arises as a structural consequence of chromosome 19 rearrangements driving EPOR amplification. Based on this data, we propose a conceptual model of leukemogenesis where EPOR/JAK2 co-amplification potentially drives constitutive JAK2/STAT5 signaling, while concurrent ERG gain and TCF3 haploinsufficiency contribute to maturation delay. TP53 deficiency appears to be the primary permissive factor enabling the stabilization of these massive structural rearrangements.

Our findings outline a recurrent and biologically coherent genomic pattern within the spectrum of TP53-mutated myeloid neoplasms, demonstrating significant phenotypic overlap with erythroid leukemia features in a subset of cases. Given the small cohort size, these findings are hypothesis-generating. However, this convergence of predicted JAK2/STAT5 pathway hyperactivation and transcriptional disinhibition points to a theoretical therapeutic vulnerability that warrants prospective validation in larger collaborative studies.

A 57-year-old male from Guinea presented with 6 months of progressive shortness of breath, productive cough, and occasional night sweats. A lung biopsy revealed an angiocentric pulmonary infiltrate of small bland lymphocytes and lymphoepithelial lesions mimicking a MALT lymphoma. The infiltrate expressed CD3, CD56, and Epstein-Barr virus-encoded RNA with little Ki-67 staining. Blood EBV copies were 519 IU/mL. FDG-PET scan showed no uptake outside the thorax. A diagnosis of small-cell variant pulmonary NK/T-cell lymphoma was made. Following asparaginase/cisplatin-based treatment, the patient developed recurrent cough, and nasal biopsy suggested lymphoma relapse. Following transplant conditioning, the patient developed symptoms of fever and cough, with rising blood EBV load. Lymphoma progression was suspected. A flow RNA assay demonstrated a small population of EBER + CD8 + T-cells in blood. NK/T-cell lymphoma usually present with sino-nasal symptoms. The small-cell variant is rare. The diagnosis is challenging when the clinical presentation and cytological features are atypical. POT1 variants have not been reported in ENKTL to our knowledge, but germline variants have been associated with lymphomas. A multicolour EBER hybridisation flow assay can help identify the cellular origin of EBV reactivation.

Artificial chemical synapses, which specifically identify, transmit, and process molecular information, find promising applications in precision medical diagnosis, neural-electronic interface, and in-memory computing. However, to implement biomarker-triggered neuronal excitability modulation with artificial iontronic devices remains a significant challenge. Herein, we demonstrate a capture DNA integrated angstrom-fluidic chemical synapse in which the intramembrane ionic conductance can be switched between excitatory and inhibitory states by specific DNA-target interactions on the outer membrane surface. Experimental results and theoretical calculations unveil that capture of specific biomarker results in a bidirectional space charge polarization, and establishes opposite local concentration gradient at the membrane surface. Driven by this reversible concentration gradient, cation influx or efflux modulate the number density of ionic charge carriers inside the membrane, analogy to the hyperpolarization and depolarization modes of biological chemical synapses. Using a convolutional neural network algorithm to process the ionic conductance enhancement and depletion signals, we develop a diagnostic approach for early prostate cancer with 100% accuracy for both retrospective analysis of 105 clinical specimens, and prospective double-blind trials (n = 10). This work sheds light on artificial chemical synapses based medical diagnosis, and provides a blueprint for neural-like iontronic network for chemical information processing.

Folic acid (FA)-modified gadolinium nanoparticles are promising candidates for magnetic resonance imaging (MRI) contrast agents due to their high cancer specificity. Therefore, this study aims to modify nanoparticles with polyethylene glycol (PEG)-FA to enhance their biocompatibility and specificity toward cervical cancer target via folate receptor (FR)-mediated endocytosis. Spherical nanoparticles less than 20 nm were characterized by dynamic light scattering and transmission electron microscopy, with UV absorbance peaks at 282 and 362 nm confirming the successful attachment of FA. Additionally, the zeta potential at - 51.23 mV indicated good colloidal stability. Subsequently, an in vitro investigation was performed using three different FA-expressing cancer cell lines: HEK-293 (-), HeLa ( +), and KB (+ +), demonstrating that the cancer cells remained > 90% viable after 24 h incubation with the nanoparticles. There was enhanced FA-nanoparticle uptake in HeLa and KB, with minimal uptake in HEK-293 cells. In addition, FA pretreatment reduced uptake, confirming the receptor specificity. Compared to nanoparticles without modification, modified nanoparticles showed a significant increase in uptake in cancer cells expressing the FA receptor (p < 0.0001). These results support the potential of FA-modified gadolinium nanoparticles as a receptor-targeted contrast agent for further cervical cancer MR imaging applications.

Peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS), is a heterogeneous nodal T- and natural killer (NK)-cell lymphoma with limited prognostic biomarkers. A subset of PTCL-NOS characterized by Epstein-Barr virus (EBV) involvement in tumour cells has recently been recognized as EBV-positive nodal T- and NK-cell lymphoma (EBV+ nPTCL), a distinct entity in the fifth edition of the World Health Organization classification of haematolymphoid neoplasms (WHO-HAEM5). However, the clinical significance of circulating EBV deoxyribonucleic acid (DNA) in PTCL-NOS remains unclear. Patients initially diagnosed with PTCL-NOS who received first-line systemic chemotherapy at a single-centre between 2007 and 2025 were retrospectively analysed. Cases were reclassified according to WHO-HAEM5 using EBV-encoded small ribonucleic acid (EBER) in situ hybridization and pathological review. Among 101 patients, 4 were reclassified as EBV+ nPTCL using a ≥50% tumour cell EBER positivity cut-off and excluded, yielding a cohort of 97 patients with WHO-HAEM5-defined PTCL-NOS. Baseline blood EBV-DNA positivity was observed in 42.3%. EBV-DNA-positive patients demonstrated significantly shorter progression-free and overall survival (OS) compared with EBV-DNA-negative patients. In multivariate analyses, EBV-DNA positivity independently predicted poorer survival outcomes. Exploratory analyses indicated that EBV-DNA clearance during chemotherapy was associated with improved OS. These findings suggest that blood EBV-DNA may serve as a prognostic biomarker in patients with PTCL-NOS.

Liver cancer (LC) is one of the most prevalent and deadly malignancies worldwide, and early diagnosis together with accurate staging is critical for improving patient prognosis. Although surface-enhanced Raman spectroscopy (SERS) has shown strong potential for minimally invasive tumor detection, its broader clinical application remains limited by insufficient substrate stability, incomplete spectral coverage, and inadequate discriminative ability in complex classification and staging tasks.

In this study, we developed a silver nanoparticle-composited three-dimensional porous SERS substrate (Ag@BTM) by combining the breath-figure method with a Marangoni effect-driven liquid-liquid interfacial self-assembly strategy, enabling uniform AgNP distribution within the porous scaffold and improving SERS sensitivity, uniformity, and reproducibility. To further expand biochemical information, we proposed a dual-substrate SERS detection strategy using two Ag@BTM substrates with complementary localized surface plasmon resonance characteristics, namely S-Ag@BTM and L-Ag@BTM, and fused their spectra into a dual-substrate SERS super-fingerprint. Combined with the AutoGluon automated machine learning framework and SHAP analysis, this strategy achieved 98.6% accuracy for classifying Normal, HBV, and LC samples and 80.4% accuracy for LC staging, representing improvements of 12.6 and 14.7 percentage points over the corresponding single-substrate models.

This dual-substrate fusion framework provides a sensitive, low-cost, and scalable route for minimally invasive LC screening and precise staging, and highlights the potential of substrate-complementary SERS analysis for complex clinical classification tasks.