Citations

Abstract Introduction Multiple pulmonary nodules (MPNs) are commonly encountered in patients at elevated risk for thoracic malignancy and represent a spectrum of disease states and stages. We evaluated the safety, and procedural outcomes of a combined robotic assisted bronchoscopy (RaB) and linear endobronchial ultrasound (EBUS) approach to patients with MPNs during a single bronchoscopic procedure. Methods This multicenter observational registry included patients who underwent RaB for evaluation of MPNs. Data were prospectively collected from six centers between 2019 and 2025. Demographics, imaging characteristics, safety events, and procedural outcomes were analyzed and associated with final diagnosis. Results A total of 191 patients underwent RaB with biopsy of MPN during a single procedure; 167 patients also underwent linear EBUS lymph node sampling. The strict per nodule diagnostic yield was 71.5% overall (first nodule 70.7%, second 74.3%, third 71.4%). At least one malignant nodule was identified in 127 patients (66.8%), and 85 patients (44.5%) had two or more malignant nodules; 15 patients (17.6%) demonstrated heterogeneous histopathology between malignant nodules. Among patients with non–small cell lung cancer, adequate cellularity for next generation sequencing was achieved in 82.6% of nodules. Malignant lymph nodes were identified in 10.8% (18/167). No patients with two pure ground glass nodules (0/8) had malignant nodal involvement. Pneumothorax occurred in 7.3% of cases, with 2.1% requiring chest tube placement; unplanned admissions occurred in 3.7%. Conclusion This study provides a large multisite registry evaluation of performance of simultaneous bronchoscopic sampling of multiple pulmonary nodules with EBUS staging during a single anesthesia event demonstrating an acceptable safety profile and adequacy for molecular profiling.

ABSTRACT Background Most genomic studies of adult-type diffuse gliomas have focused on predominantly European ancestry populations, limiting the generalizability of molecular classifications and precision medicine approaches. We assembled a multi-institutional glioma cohort of diverse patients to investigate how germline ancestry, molecular subtypes, and mutational processes shape tumor biology and clinical outcomes. Methods We analyzed 1,102 adults with WHO 2021–classified diffuse gliomas (IDH-mutant, 1p/19q-codeleted oligodendroglioma; IDH-mutant astrocytoma; IDH-wildtype glioma) from seven U.S. institutions. Whole-exome sequencing (WES) of FFPE tumors identified somatic alterations and COSMIC SBS v3.2 mutational signatures. Genetic ancestry was estimated from WES using 1000 Genomes reference populations. Overall survival was assessed using Kaplan–Meier and multivariable models. Results The cohort included 66.9% European (EUR), 21.1% Admixed American/Hispanic (AMR), 10.3% Admixed African (AFR), and 1.6% Asian (AS) ancestry. Survival followed expected molecular hierarchy (median overall survival: oligodendroglioma 15.7 years, astrocytoma 10.6 years, IDH-wildtype glioma 1.9 years). Within oligodendroglioma, AMR patients showed improved survival versus EUR (HR 0.67, 95% CI 0.48–0.94; p=0.011), with similar trends across subtypes. Somatic profiling confirmed canonical subtype-defining alterations and revealed higher ATRX alterations in AFR and AMR IDH-wildtype tumors compared with EUR. ATRX alterations were associated with improved survival only in AFR (p=0.003). Mutational signature analysis identified subtype-specific signatures, including therapy-associated signatures. Chemotherapy-related signatures were more frequent in EUR and AMR than in AFR. Conclusions This ancestrally diverse glioma cohort confirms established molecular classifications and identifies ancestry-associated differences in survival, somatic alterations, and mutational processes, indicating the critical need for broad representation to inform precision neuro-oncology. Key Points A multi-institutional glioma cohort validates subtype and survival patterns across ancestries. Therapy-associated mutational signatures differ by ancestry, suggesting distinct treatment-related mutational processes. Admixed American patients show improved survival, particularly in oligodendroglioma. Importance of the Study Most genomic studies of adult-type diffuse glioma have focused on populations of predominantly European ancestry which limits the ability to examine variation in tumor biology and clinical outcomes across populations. In this study, we assembled one of the largest ancestrally diverse cohorts of molecularly characterized adult diffuse gliomas, integrating germline ancestry inference with tumor whole-exome sequencing and mutational signature analysis. We confirm that established molecular classifications and survival hierarchies remain robust across ancestry groups. However, we also identified ancestry-associated differences in survival within specific tumor subtypes, higher ATRX alteration frequencies in African American and admixed American patients with IDH-wildtype tumors, and variation in therapy-associated mutational signatures across ancestry groups. These findings highlight the importance of incorporating population differences into genomic studies of glioma and provide a resource for future multi-ancestry investigations of glioma risk, tumor evolution, and treatment response, ultimately supporting more inclusive precision neuro-oncology.

Objective Data on cardiac index (CI) in patients undergoing coronary angiography (CAG) can enhance decision-making and improve clinical outcomes. However, this necessitates an additional invasive procedure, and therefore, it is frequently omitted. This study explores the novel application of convolutional neural networks (CNNs) to predict CI from routine CAGs. Methods and analysis Patients who underwent CAG and simultaneous right heart catheterisation at Mayo Clinic between 2002 and 2023 were included. A three-dimensional (3D)-CNN model (X3D architecture) was developed to predict binary CI categories (normal: CI≥2.2 vs abnormal: CI<2.2 L/min/m²) from CAG videos. CAGs were randomly split into training (70%), validation (15%) and test (15%) sets. All available videos from each study were entered into the model. The model’s performance was evaluated using the area under the curve (AUC), sensitivity, specificity and F1 score. Results A total of 15 297 CAG studies were considered. After applying a quality-check algorithm to exclude low-quality or irrelevant CAGs, 11 475 studies from 9103 patients were included. CI was abnormal in 25.2% of studies. The model achieved an AUC of 0.83 (95% CI 0.81 to 0.85), sensitivity of 0.72 (95% CI 0.68 to 0.77), specificity of 0.78 (95% CI 0.75 to 0.80) and F1 score of 0.62 (95% CI 0.58 to 0.65) on the test dataset. Limiting the input to 4, 3 or 2 prespecified CAG videos representing standard views did not significantly affect the model’s performance, supporting its applicability in varied clinical workflows. Conclusions This study demonstrates the feasibility of leveraging deep learning models to predict CI from CAG videos. The proposed 3D-CNN model shows promise as a tool for providing physicians with real-time data to aid decision-making during CAG procedures.

Ex vivo liver perfusion (EVLP) sustains human or large animal livers outside the body under near-physiological conditions, enabling functional monitoring for lactate clearance, bile production, and oxygen consumption and allowing targeted therapeutic interventions. Originally developed to optimize donor grafts for transplantation, EVLP has evolved into a powerful translational research platform bridging preclinical discovery and early clinical translation. This review discusses EVLP as a platform for gene therapy, immunotherapy, pharmacology, and personalized medicine, with particular emphasis on gene- and immune-based interventions as mechanistically mature exemplars. We consolidate advances in pharmacological testing and toxicity modeling, viral and non-viral gene delivery, genome engineering, and immunomodulation using perfused livers. We further describe emerging applications, including autologous EVLP pathways for organ-confined therapy, ex vivo liver surgery, and bioengineering strategies such as biliary organoid repair, RNA interference, and mitochondrial transfer. We highlight how these applications align with a paradigm shift in biomedical research, including the NIH’s recent initiative to prioritize human-based experimental models over animal-only studies. By leveraging transplant-declined or surgically resected organs that would otherwise be unused, ex vivo perfusion bridges the gap between pre-clinical testing and clinical practice, enabling real-time evaluation of interventions in functional human tissue. We discuss both the scientific opportunities afforded by EVLP and the technical, biosafety, and ethical challenges that must be addressed to enable responsible clinical translation.

Abstract The trabecular meshwork (TM) and ciliary body (CB) regulate aqueous humor dynamics and intraocular pressure (IOP), and TM/Schlemm’s canal (SC) dysfunction underlies glaucoma. Here, we present a spatially resolved multi-omics atlas of human TM and CB, integrating snRNA-seq, scRNA-seq, and snATAC-seq from over one million cells and nuclei across 112 donors with Xenium spatial transcriptomics. We identified 9 major cell classes and 21 cell types, revealing heterogeneity, including undercharacterized fibroblast and epithelial subpopulations. Spatial mapping supported TM fibroblast zonation and CB epithelial organization. Regulatory analyses identified cell type–specific programs, including OTX/PAX networks in CB epithelium and SMAD3/TGF-β signaling in fibroblasts. Integration with glaucoma loci showed enrichment of non-coding variants in regulatory elements associated with POAG and PACG. Age- and ancestry-associated remodeling revealed divergent fibroblast aging with increased PIEZO1 , suggesting impaired outflow and elevated IOP. Together, this high-resolution atlas links cellular, regulatory, and genetic variation to anterior segment function and glaucoma susceptibility.

ABSTRACT Glioblastoma (GBM) is universally lethal despite decades of research to find effective treatments. This highlights the need to identify druggable targets essential for sustaining the malignant phenotype but dispensable for normal tissue. We propose that the enzyme α-tubulin acetyl transferase ( ATAT1 ) meets these criteria. ATAT1 acetylates α-tubulin at lysine 40, which increases microtubule stability and promotes microtubule-based transport. While ATAT1 knockout mice have only a very mild phenotype, ATAT1 suppression in GBM has multiple therapeutic effects by reducing tumor invasion, proliferation, and therapeutic resistance. These translate not only into improved survival with ATAT1 targeting by itself, but also into synergy when ATAT1 deletion is combined with FDA approved therapies. This study strongly supports our conclusion that ATAT1 is a promising therapeutic target in GBM.

Introduction Large-scale production of mammalian cells is pivotal for applications in biotechnology, regenerative medicine, and therapeutic manufacturing. However, current bioreactor technologies face significant technical and economic challenges, including excessive cell aggregation, shear stress-induced cell death, batch-to-batch inconsistencies, and limited scalability. We propose that engineering a cell-friendly microenvironment can enhance culture efficiency. Previously, we developed alginate hydrogel microtubes (AlgTubes) that significantly improved cell density and growth rates; however, AlgTubes lack adhesion sites essential for anchorage-dependent cells and frequently break, causing cell leakage and production inconsistencies. Methods To address these limitations, we reinforced AlgTubes with collagen nanofibers, creating collagen-alginate hybrid hydrogel microtubes (ColAlgTubes). Collagen was integrated to form a dense nanofiber network interwoven with the alginate mesh, with the dual aim of enhancing mechanical properties and providing cell adhesion sites. ColAlgTubes were fabricated to maintain cell mass within a 400 μm diameter to ensure efficient nutrient exchange and waste removal. Results ColAlgTubes successfully formed a reinforced hybrid hydrogel structure in which the collagen nanofiber network improved the mechanical integrity of the alginate matrix while supplying adhesion sites for anchorage-dependent cells. The optimized 400 μm diameter microenvironment supported high cell viability, rapid proliferation, and exceptional yields of 5 × 10 8 cells/mL. Discussion These results demonstrate that ColAlgTubes overcome the key limitations of AlgTubes by combining structural reinforcement with biological functionality. The improved mechanical properties reduce tube breakage and cell leakage, while collagen-derived adhesion sites broaden compatibility to anchorage-dependent cell types. With their scalability, cost-effectiveness, and high efficiency, ColAlgTubes represent a transformative solution for large-scale mammalian cell production across biotechnology, regenerative medicine, and therapeutic manufacturing.

Abstract Large Language Models (LLMs) demonstrate strong capabilities in healthcare applications. However, recruiting human evaluators to assess usability and effectiveness becomes challenging in the large-scale LLM-generated outcomes. Existing metrics are often outdated for evaluating LLM-based healthcare technologies. This paper proposes a Research through Evaluation (RtE) approach that can refine metrics and improve assessments of LLM-generated outputs. We deploy RtE in a retrospective comparative study of prostate cancer patient inquiries, comparing responses from human clinical care teams with those generated by a GPT-4-based in-basket bot. Through three rounds of co-evaluations with clinical professionals and an LLM-as-graders study with four LLMs, the RtE method shows that starting with small, iterative evaluations helps human graders adjust metrics to suit their daily practices better. Additionally, in the LLM-as-graders study, LLMs exhibit similar behavior, preferring the in-basket bot's responses over the clinical care team. Our methodology and findings demonstrate that the RtE method can enhance the transparency and robustness of evaluation metrics for LLM-generated content, with the potential to generalize to evaluations in other clinical practices.

Deep brain stimulation (DBS), a cornerstone neurosurgical intervention for advanced Parkinson’s disease, exerts modulatory effects on aberrant basal ganglia circuitry through continuous high-frequency electrical stimulation. This approach yields sustained amelioration of motor symptoms while concurrently reducing the requisite dosage of dopaminergic pharmacotherapy. Nonetheless, DBS still has its limitations: its efficacy on non-motor symptoms remains limited, electrode implantation leads to biological reactions, and it cannot alter the trajectory of disease progression. Embryonic stem cells and induced pluripotent stem cells can be directed to differentiate into functionally mature nigrostriatal dopaminergic neurons, demonstrating the potential for neuronal replacement and neuroprotective effects in preclinical models and early-phase clinical trials. Mesenchymal stem cells and their derived exosomes mitigate neuroinflammation and impede α-synuclein aggregation through neurotrophic support and immunomodulatory mechanisms. This article reviews two core domains that have achieved breakthroughs in the treatment of Parkinson’s disease—DBS and stem cells—and covers their current status and future prospects. First, this review elucidates the therapeutic mechanisms of DBS, including neurotransmitter release regulation and neuroinflammation suppression, while evaluating its long-term efficacy (e.g., the sustainability of motor improvement and advancements in directional stimulation technology) and safety challenges (e.g., cognitive impairment, mood disturbances, and glial scar formation induced by electrode implantation). Second, it provides an in-depth analysis of the differentiation mechanisms of stem cells from different sources (embryonic stem cells, induced pluripotent stem cells, mesenchymal stem cells, etc.), preclinical efficacy validation, and early-phase clinical trial outcomes (e.g., the long-term safety and motor function enhancement observed in the transplantation of induced pluripotent stem cell-derived nigrostriatal dopaminergic progenitor cells). Third, the article addresses the standardization of stem cell therapy protocols, strategies for managing immune rejection, and current international regulatory and ethical frameworks. The core challenges of current Parkinson’s disease treatment paradigms are as follows: DBS shows limited efficacy in improving axial symptoms (e.g., freezing of gait), whereas stem cell transplantation faces issues such as low long-term graft survival and insufficient functional integration. Looking ahead, multidisciplinary integration is essential to promote the synergistic application of DBS and stem cell therapy, develop personalized treatment protocols under the guidance of precision medicine, and translate novel neural interface materials and genetic engineering technologies into clinical practice. Ultimately, such integrated strategies hold the promise of advancing Parkinson’s disease therapy from mere symptom control to true disease modification.