Search Results (1,890)

Glypican-3 (GPC3)-targeted chimeric antigen receptor T (CAR-T) cell therapy is a promising approach for hepatocellular carcinoma (HCC), but marked interpatient variability and antigen heterogeneity limit its broader application. Here, we established a patient-derived organoid (PDO)-based platform to functionally evaluate autologous GPC3-targeted CAR-T cell activity in HCC. HCC PDOs preserved key histologic features and heterogeneous GPC3 expression patterns of the original tumors. In co-culture assays, CAR-T cell cytotoxicity was associated with GPC3 expression levels and was accompanied by IFN-γ and IL-2 release, supporting the feasibility of using PDOs for functional assessment of CAR-T cell sensitivity. We further found that matrix conditions strongly influenced organoid architecture, viral transduction, CAR-T cell infiltration, and killing efficiency, with lower Matrigel concentrations providing a more permissive setting for functional assessment. Importantly, in GPC3-low PDOs, pretreatment with the DNA methyltransferase inhibitor 5-azacytidine (5-AZA) increased surface GPC3 expression, reduced DNA methyltransferase 3 alpha (DNMT3A) expression, and significantly enhanced CAR-T-mediated cytotoxicity. Together, these findings provide proof-of-concept evidence supporting the use of HCC PDOs as a patient-derived platform for modeling selected determinants of GPC3-targeted CAR-T cell activity and for exploring combination strategies to improve therapeutic efficacy. Full article

Background: Trichosporon japonicum is a rare but highly lethal pathogen causing fungemia in immunocompromised patients. With the expanding use of chimeric antigen receptor T (CAR-T) cell therapy, the spectrum of opportunistic fungal infections is changing, yet data on T. japonicum infections in this setting remain scarce. Case Presentation: A 69-year-old man with diffuse large B-cell lymphoma developed catheter-associated fungemia after CAR-T cell reinfusion. He initially presented with neck pain and white oral mucosal patches, followed by fever four days later. T. japonicum was isolated from both peripheral blood and central venous catheter tip cultures, identified by microscopic examination, mass spectrometry, and molecular sequencing. Antifungal prophylaxis was initiated before fever onset based on close monitoring of white blood cell count, procalcitonin, interleukin-6, and C-reactive protein; treatment was subsequently adjusted according to species identification and antifungal susceptibility results. Infection was controlled within two weeks after catheter removal and immune recovery. The patient remained well at six-month follow-up. Conclusion: This case adds to the limited literature on T. japonicum fungemia in patients receiving CAR-T therapy. Our experience, together with a review of the literature, underscores that successful management requires prompt catheter removal, immune restoration, and combination therapy with voriconazole and amphotericin B, as echinocandin monotherapy should be avoided. Awareness of this pathogen in immunocompromised patients is critical. Full article

Despite prolonged viral inhibition with combination antiretroviral therapy (ART), HIV-1 survives as genetically intact, replication-capable proviruses within durable CD4+ T-cell fractions, involving central memory, transitional memory, and stem cell-like memory populations, as well as within tissue-resident compartments including lymphoid follicles and gut-associated lymphoid tissue. Reservoir stability is preserved via clonal growth of infected cells and epigenetic processes that impose proviral transcriptional silencing. As a result, current therapeutic approaches seek to either directly alter proviral survival or to improve immune-driven elimination of infected cells. At the molecular level, investigational strategies such as CRISPR–Cas9 and CRISPR–Cas12 gene-editing systems are intended to remove or induce inactivating mutations inside embedded proviral DNA, as well as alter host entrance co-receptors such as CCR5 to provide cellular resistance to infection. In addition, pharmacologic latency regulation is being studied via histone deacetylase inhibitors, protein kinase C agonists, and bromodomain inhibitors to reverse latency, along with Tat inhibitors and other transcriptional repressors aimed to persistently silence proviral expression. Moreover, immunological techniques aim to counteract inefficient endogenous antiviral defenses. Broadly neutralizing antibodies with tailored Fc-driven effector functions are under examination for both neutralization and antibody-dependent cellular cytotoxicity. Therapeutic vaccine approaches seek to elevate polyfunctional HIV-specific CD8+ T-cell responses, while adoptive cellular approaches, involving CAR-T cells aiming HIV envelope epitopes, remain in early clinical research. Immune checkpoint blockade is also being investigated to reverse T-cell depletion inside reservoir-rich tissues. Nevertheless, the key obstacles continue to be the diverse reservoir composition, restricted tissue penetration, viral escape, and safety limitations. The molecular and translational obstacles that characterize attempts toward an HIV cure must be addressed through ongoing multidisciplinary research. Full article

Background/Objectives: CD19-directed chimeric antigen receptor T (CAR-T) cell therapy induces profound immune remodeling. Nonetheless, biomarkers predicting complete remission (CR) remain poorly defined. We characterized longitudinal cytokine and immune-cell dynamics after CAR-T infusion and identified early immunological features associated with CR. Methods: Longitudinal immune profiling was performed in 18 patients with non-Hodgkin lymphoma, including 14 with relapsed/refractory diffuse large B-cell lymphoma treated with anti-CD19 CAR-T cells. Peripheral blood was collected at the baseline and days 7, 14, 21, 28, and 60 post-infusion. Multiparameter flow cytometry quantified lymphoid and myeloid subsets and Toll-like receptor (TLR)2 and TLR4 expression. Serum cytokines were measured by multiplex assays. Machine-learning-based feature selection identified variables associated with CR. Results: Two inflammatory waves were observed. The first, at day 7, featured elevated IL-6, IL-10, IFN-α, IFN-γ, and TNF-α, accompanied by increased CD4⁺ T cells, HLA-DR^high classical monocytes, and non-classical monocytes. The second, at days 21–28, showed increased IL-5, IL-6, IL-12, IFN-γ, and GM-CSF, with expansion of CD4⁺ and CD8⁺ T cells, regulatory T cells, NK-T cells, and non-classical monocytes. TLR2 expression was significantly upregulated at day 7 on T-cell subsets and on classical and intermediate monocytes. An exploratory feature-selection analysis identified baseline and day-7 TLR2 and TLR4 expression on lymphoid and myeloid cells, early IFN-γ levels, and monocyte frequencies as variables associated with CR. Conclusions: Together, these data show that anti-CD19 CAR-T therapy induces two coordinated waves of cytokine release and immune-cell activation. Moreover, the findings suggest that early modulation of innate immune features, particularly TLR2 expression, is associated with complete remission, although these biomarker relationships remain exploratory and require validation in larger cohorts. Full article

Background/Objectives: B-cell maturation antigen (BCMA)-directed immunotherapies, including chimeric antigen receptor T-cell (CAR-T) therapies and bispecific antibodies (BsAbs), have improved clinical outcomes in multiple myeloma. However, cytokine release syndrome (CRS) remains a major safety concern, and comparative real-world evidence across BCMA-directed agents remains limited. This study aimed to evaluate and compare CRS reporting patterns associated with BCMA-targeted CAR-T and BsAb therapies using the FDA Adverse Event Reporting System (FAERS) data and to identify predictors of CRS reporting using machine learning-based approaches. Methods: A pharmacovigilance analysis was conducted using FAERS reports from 2021 Q1 to 2025 Q3. Disproportionality analyses were performed using the reporting odds ratio (ROR), proportional reporting ratio (PRR), and information component (IC), and signals were considered present when predefined thresholds were met. Multivariable logistic regression was applied to estimate adjusted odds ratios (aORs) for CRS reporting while adjusting for demographic and reporting characteristics. Machine learning models, including XGBoost, LightGBM, and random forest were developed to predict CRS reporting. Model interpretability was assessed using SHapley Additive exPlanations (SHAP). Results: Among 4046 reports included in the final dataset, CAR-T therapies showed higher CRS reporting odds than BsAbs (aOR: 2.55, 95% CI: 2.16–3.01). Disproportionality analyses identified significant CRS signals for CAR-T therapies across all indices, whereas BsAbs did not meet signal detection thresholds. At the agent level, idecabtagene vicleucel was the only agent meeting all predefined signal detection criteria and exhibited the strongest reporting pattern in multivariable analysis (aOR: 6.96, 95% CI: 5.53–8.75). Among the evaluated models, LightGBM achieved the highest predictive test AUROC (0.762). SHAP analysis identified idecabtagene vicleucel, United States region, and reporting year as the most influential predictors of CRS reporting. Conclusions: CAR-T therapies, particularly idecabtagene vicleucel, exhibited higher CRS reporting odds than BsAbs, with substantial agent-level heterogeneity observed across BCMA-directed immunotherapies. Integrating pharmacovigilance and machine learning approaches may facilitate more individualized safety monitoring by identifying agent-specific differences in CRS risk among BCMA-targeted therapies. Full article

Chimeric antigen receptor (CAR) T-cell therapy is an effective treatment for hematologic malignancies. However, it is limited by high costs, risk of severe toxicities such as cytokine release syndrome and neurotoxicity, and heterogeneous patient responses. The current therapy monitoring depends largely on subjective symptom assessment, routine laboratory tests, and basic vital signs, without real-time, quantitative evaluation of CAR T-cell expansion or activation in clinical practice. This lack of timely immune monitoring hampers individualized care and contributes to increased treatment costs. To address this need, we present a proof-of-concept, label-free rapid optical imaging (ROI) biosensor with automated machine learning analysis for direct quantification of CAR T-cells from whole blood. This microfluidic platform integrates red blood cell (RBC) removal, CAR T-cell capture, and imaging-based quantification on a single chip, eliminating the need for centrifugation, staining, and operator-dependent interpretation. For validation, 50 μL whole blood samples spiked with Jurkat cells expressing CD19 CARs underwent RBC depletion by agglutination and microfiltration. The remaining blood components were then incubated on a sensor chip functionalized with recombinant CD19 protein. Captured CAR T-cells were imaged by brightfield microscopy and automatically enumerated using a machine learning algorithm trained on fluorescence-validated cells. The CD-19 cells’ capture performance was validated by flow cytometry and fluorescence imaging. The trained machine learning model validated at 88% sensitivity and 96% specificity. Buffer and whole blood calibration curves were established across clinically relevant concentrations (1–1000 cells/µL) with triple replicates. The results showed high correlation (0.975 and 0.990 R²) between the spiked concentration and the detected CAR T-cells, with a 95% certainty limit of detection (LOD) and quantification (LOQ) of 0.6 and 1.1 cells/µL for spiked buffer, and 14 and 67 cells/µL for spiked whole-blood, respectively. Full article

Natural killer/T-cell lymphoma (NKTCL) is a rare and aggressive Epstein–Barr virus (EBV)-associated lymphoma characterized by intrinsic chemoresistance and an immunosuppressive tumor immune microenvironment (TIME). EBV-driven immune dysregulation provides a biological rationale for immunotherapy. This review summarizes current advances in immunotherapeutic strategies for NKTCL, integrating molecular mechanisms, clinical evidence, and resistance mechanisms within the context of TIME remodeling and immune reprogramming. We synthesize evidence from clinical trials, translational studies, and preclinical investigations evaluating immune checkpoint inhibitors, antibody-based therapies, adoptive cellular therapies, immune engagers, EBV-directed immunotherapies, and multimodal combination strategies in NKTCL. Among these strategies, PD-1/PD-L1 inhibitors are the most extensively studied immunotherapies in NKTCL and demonstrate clinically meaningful activity across different clinical settings. However, therapeutic responses remain heterogeneous, and primary or acquired resistance is common, driven by EBV-associated immune suppression, defective antigen presentation, metabolic reprogramming, and multi-checkpoint co-expression. Beyond immune checkpoint blockade, emerging approaches—including dual-checkpoint inhibition, epigenetic and metabolic combinations, antibody–drug conjugates, EBV-specific cytotoxic T lymphocytes, chimeric antigen receptor (CAR)-based platforms, immune engagers, and EBV vaccines—have shown encouraging signals in early-phase studies. Increasing evidence also supports multimodal strategies integrating immunotherapy with radiotherapy and other immune-modulatory interventions to enhance immune reprogramming and improve response durability. Overall, immunotherapy has substantially expanded the therapeutic landscape of NKTCL but remains constrained by complex EBV–TIME interactions and interpatient heterogeneity. Future progress will rely on biologically informed patient stratification, rational multimodal combination strategies, and integration of innovative immune platforms to establish a durable, immune-reprogramming-centered treatment paradigm for EBV-driven NKTCL. Full article

Traffic accident detection is a critical component of intelligent transportation systems (ITS), enabling timely incident response and traffic management. While most existing approaches rely on temporal information from video sequences, such methods are not always applicable in resource-constrained surveillance environments. This study investigates the feasibility of detecting traffic accidents from single static images by formulating the task as a binary classification problem. Representative architectures, including Vision Transformer (ViT), Swin Transformer, and ResNet-50, are systematically evaluated on the Car Crash Dataset (CCD) under multiple training configurations. To assess generalization capability, cross-domain evaluation is conducted using an external crash video dataset (ECVD) constructed to approximate real-world deployment conditions. Experimental results show that all models achieve strong performance under in-domain evaluation. However, cross-domain testing reveals substantial performance degradation, particularly in recall, indicating limited generalization capability under domain shift. Qualitative analysis further shows that missed detections are associated with weak visual cues, occlusion, and complex traffic environments, while false positives are caused by visually ambiguous patterns resembling accident scenarios. Unlike prior studies that primarily report performance improvements, this work provides empirical evidence that model behavior in static-image-based accident detection is governed by dataset composition rather than architectural design. Therefore, static-image-based accident detection should be interpreted as a coarse-level screening tool rather than a fully reliable decision-making system. This study highlights the importance of data-centric design and cross-domain evaluation for improving real-world applicability. Full article

The treatment of chronic lymphocytic leukemia (CLL) has significantly shifted from chemoimmunotherapy to targeted therapies like Bruton’s tyrosine kinase and BCL2 inhibitors. Despite these advancements, CLL remains an incurable disease characterized by immune dysregulation, therapeutic resistance, and cumulative toxicities. To overcome these challenges, novel immunotherapeutic strategies are emerging as fundamentally different approaches that target immune–tumor interactions. These innovations include novel monoclonal antibodies, bispecific antibodies that redirect T cell cytotoxicity, chimeric antigen receptor (CAR) T-cell therapies, and natural killer (NK) cell-based platforms. By actively engaging cellular cytotoxicity, these approaches show promise in high-risk and treatment-resistant scenarios where standard pathway inhibition is inadequate. Establishing optimal use, toxicity management, and combination strategies for these cell-engaging immunotherapies is now a critical priority in contemporary CLL research. Full article

Introduction: Chimeric antigen receptor (CAR) T-cell therapies have revolutionized treatment for relapsed/refractory hematologic malignancies, targeting CD19 in B-cell neoplasms and BCMA in multiple myeloma, with response rates exceeding 80%. However, long-term risks, including therapy-related myeloid neoplasms, such as myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML), are emerging 6–24 months post infusion, potentially linked to lymphodepleting chemotherapy, clonal hematopoiesis expansion, and inflammatory milieus. This FAERS pharmacovigilance analysis quantified MDS/AML reporting across seven FDA-approved CAR-T products to detect antigen-specific signals unattainable in pivotal trials with limited follow-up. Methods: Adverse event reports from FAERS (1 January 2013–10 February 2025) were queried for tisagenlecleucel, axicabtagene ciloleucel, brexucabtagene autoleucel, lisocabtagene maraleucel, obecabtagene autoleucel, idecabtagene vicleucel, and ciltacabtagene autoleucel, focusing on MedDRA terms for MDS/AML. Duplicates and ambiguous cases were excluded. Disproportionality was assessed using reporting odds ratios (RORs; lower 95% CI >1 signaling significance), comparing CAR-T-event pairs to database background, with subgroup analyses by antigen target. Results: Among 14,093,557 reports, CAR-T products linked to 303 MDS (brexucabtagene autoleucel ROR 97.93 [72.18–132.87], n = 44; axicabtagene ciloleucel ROR 58.70 [50.34–68.44], n = 172) and 129 AML cases (axicabtagene ciloleucel ROR 22.89 [18.23–28.73], n = 76). Signals were consistent across CD19- and BCMA-directed agents, absent only for recently approved obecabtagene autoleucel. Conclusions: CAR-T therapies exhibit disproportionate MDS/AML reporting in FAERS, supporting class-wide late hematologic toxicity in pretreated patients with clonal hematopoiesis. Enhanced surveillance, baseline profiling, and marrow evaluation for cytopenias are warranted, balancing curative benefits. Full article

Diffuse midline gliomas (DMGs) are rare but highly aggressive central nervous system (CNS) tumors that can present in both pediatric and adult populations. These tumors were redefined in the 2016 WHO classification of CNS tumors based on integrated histopathological and molecular features, and were initially designated as “DMG, H3 K27M-mutant”. In the 2021 WHO update, DMGs were incorporated into the newly defined category of primarily pediatric-type diffuse high-grade gliomas, and nomenclature was changed to “DMG, H3 K27-altered” to encompass additional molecular drivers beyond the canonical H3 K27M mutation. Clinically, DMGs arise as expansile, infiltrating tumors within midline structures and may present as non-enhancing or enhancing lesions on imaging. Diagnosis is based on neuroimaging and molecular confirmation by immunohistochemistry or sequencing when tissue is available. DMGs are categorized as WHO grade 4 malignant tumors due to their aggressive biology leading to rapid and infiltrative growth. Owing to their deep and midline location, surgical resection is typically not feasible. Radiation therapy is the backbone of treatment, but there is no standard regimen of chemotherapy that has demonstrated durable efficacy. Recent progress in therapeutic approaches has led to a major breakthrough on 6 August 2025 when the U.S. Food and Drug Administration granted the accelerated approval of dordaviprone (ONC201), marking it as the first systemic therapy for progressive DMG harboring H3 K27M mutation. Other novel approaches, including chimeric antigen receptor (CAR) T-cell directed therapies and convection-enhanced delivery, are actively under investigation. We aim to comprehensively review DMGs, including the recent insights into their biology, the evolving therapeutic landscape, and the opportunities to fuel this new momentum against one of the most formidable gliomas. Full article

Under growing urbanization and environmental challenges, sustainable urban mobility has become a critical priority for cities worldwide. Public Transport (PT) systems play a central role in reducing car dependency, lowering emissions, increasing network capacity, and promoting more equitable and efficient access to urban spaces for all users. Hence, the present paper aims to investigate PT preferences in the city of Larissa, Greece. Larissa is a medium-sized city currently serviced only by buses, and is currently focusing on the potential introduction of a new tram system to operate in parallel with existing bus services. To this end, a SP survey was designed and implemented, resulting in 972 observations that were collected for further statistical analysis. Survey results show a slight preference for trams over buses, with 54.63% selecting the tram and 45.37% favoring the buses. Moreover, a context-based segmentation pipeline was established using PCA, DBSCAN and t-SNE algorithms, aiding the visualization of existing clusters for transport choice approaches. Afterwards, a series of mixed logit models was applied, and statistically significant variables influencing mode choice were determined. The study also examines Value of Time (VoT) metrics and finds that respondents assign lower VoTs to trams than to buses, especially in out-of-vehicle segments of the journey, such as waiting and walking, and therefore consider trams as more pleasant and less burdensome. The findings also indicate that passengers place a high value on the quality of infrastructure related to access and waiting times, underlining the need to improve the overall user experience beyond the vehicle itself. In summary, the present research offers valuable insights into how the introduction of a tram system could possibly reshape PT usage patterns when compared with the legacy existing bus services. Full article

Background: Tumor immune microenvironment (TIME) heterogeneity limits immunotherapy efficacy in hepatocellular carcinoma (HCC), underscoring the need for predictive biomarkers and therapeutic targets. We previously identified dual specificity phosphatase 4 (DUSP4) as a mediator of sorafenib resistance, but its immunomodulatory role remains unknown. Methods: Glypican-3 (GPC3)-specific chimeric antigen receptor (CAR) T-cell cytotoxicity assays were performed to assess the impact of DUSP4 on HCC immune susceptibility. A subcutaneous tumor model using Dusp4-overexpressing cells in female C57BL/6J mice was established to evaluate DUSP4-mediated microenvironment remodeling and anti-PD-L1 therapy efficacy. Bulk RNA sequencing of DUSP4-overexpressing HCC cells identified downstream pathways. Public datasets were interrogated to correlate DUSP4 expression with immune checkpoint blockade (ICB) response and immune infiltration in HCC. Results: DUSP4 overexpression significantly enhanced HCC cell susceptibility to CAR-T cell killing in vitro and potentiated anti-PD-L1 efficacy in vivo, accompanied by TIME remodeling. Mechanistically, RNA sequencing revealed DUSP4-mediated downregulation of the TGF-β signaling pathway, functionally confirmed using a neutralizing antibody that abrogated the enhanced CAR-T killing. Public datasets confirmed associations between DUSP4 expression and enhanced immune cytolytic activity with favorable prognostic outcomes in HCC. Conclusions: DUSP4 serves as a critical molecular nexus linking targeted therapy resistance to enhanced immunotherapy sensitivity. By attenuating the TGF-β signaling pathway, DUSP4 reprograms TIME toward an immunologically active state, thereby augmenting the efficacy of immunotherapy. These findings establish DUSP4 as a promising dynamic biomarker for guiding sequential therapy in HCC and highlight its potential as a novel therapeutic target to improve outcomes in solid tumor immunotherapy. Full article

Autoimmune diseases arise from the failure of self-tolerance. The recognition of self-antigen peptide–MHC (pMHC) complexes by the T-cell receptor (TCR) is the fundamental event triggering autoimmune pathogenesis. While traditional immunosuppressants provide broad systemic effects, they often compromise global immunity. Emerging molecular strategies aim to selectively disrupt the trimolecular complex—comprising the TCR, the antigenic peptide, and the MHC molecule—to induce antigen-specific tolerance. This review highlights the pMHC–TCR interaction as the primary molecular checkpoint for antigen-specific intervention. We discuss the structural basis of these interactions and their potential to redefine the therapeutic landscape for autoimmune diseases (ADs). We examine the molecular drivers of tolerance breakdown—including genetic susceptibility, molecular mimicry, post-translational modifications (PTMs), and ectopic MHC II expression—that shape the autoreactive T-cell landscape. This review examines current advancements in biological and pharmacological interventions, such as pMHC-decorated nanoparticles and soluble pMHC, to reprogram pathogenic T-cell response. We also explored CAR-T therapy strategies for autoimmune diseases, such as CAR-Treg, designed to precisely modulate pMHC-TCR signaling. Collectively, these precision interventions in immunological synapse assembly during autoimmune response are considered the basis for safer, antigen-specific immunotherapy capable of restoring self-tolerance without global immunosuppression. Full article

Smart cities are increasingly dependent on interconnected transportation systems; however, this connectivity exposes smart mobility networks to significant cybersecurity risks. Traditional Intrusion Detection Systems are ill-equipped for this environment, as they are designed for isolated systems or fixed network boundaries. Thus, they struggle to secure the complex and heterogeneous smart mobility networks, where various protocols and resource-constrained edge devices require more adaptive solutions. To address this limitation, we propose a novel hybrid deep learning framework that combines convolutional neural networks for spatial feature extraction, long short-term memory networks for temporal pattern recognition, and an attention mechanism for adaptive feature weighting, together forming a context-aware Intrusion Detection System. Our approach is evaluated across six benchmark datasets spanning vehicular networks, IoT ecosystems, cloud computing, and 5G environments—VeReMi Extension, CICIoV2024, Edge-IIoTset, UNSW-NB15, Car Hacking, and 5G-NIDD—a deliberately diverse selection that represents the heterogeneous nature of real-world smart mobility networks. Empirical evaluation using three different random seeds reveals the proposed framework achieves detection accuracy exceeding 98% on each dataset, a mean F1 score of 98.94%, and an inference latency of just 4.96 ms per sample. Our results show that the proposed model achieves consistently high detection performance across six heterogeneous benchmark datasets, making it a potentially robust candidate for real-time intrusion detection in smart mobility systems. Full article