Citations

Abstract Glioblastomas exhibit low immunogenicity and a highly immunosuppressive tumor microenvironment (TME) mediated by both tumor cells and tumor associated microglia/macrophages (TAMs). However, biomarkers that allow for specific detection, monitoring and therapy response assessment of the TAM phenotype in glioblastoma are still lacking. To address this gap, we characterized the dynamics of TAM clusters in the TME of experimental SB28 glioblastoma using single-cell RNA sequencing, immunofluorescence, and molecular imaging and identified Triggering Receptor Expressed on Myeloid Cells 2 (TREM2) as a dynamic TAM-specific target. Consequently, we investigated a novel 64 Cu-labeled TREM2 radiotracer with a blood-brain barrier transport vehicle for translational mapping of TAMs in the TME of glioblastoma. We found strong and highly myeloid cell-specific PET signals that followed the trajectory of TREM2 gene expression from early- towards late-stage tumors. Transient myeloid cell depletion via CSF1R inhibition showed a reduction of TREM2 PET signals compared to placebo and prolonged survival in SB28 glioblastoma mice, while TREM2 stimulation led to increased TREM2 PET signals. Translation into a pilot cohort of patients with glioblastoma revealed strong TREM2 PET signals predominantly at lesion edges and high heterogeneity across individuals, matching with immunohistochemistry. In summary, TREM2 PET imaging has strong potential as an immune cell-specific biomarker for personalized assessment of the TAM phenotype in the TME of patients with glioblastoma.

Abstract Background Immune checkpoint inhibitors can result in serious, long-lasting immune-related adverse events (irAEs). Early identification of symptoms predictive of irAEs could enhance monitoring and timely intervention. This study assessed whether symptoms within the first 8 weeks of treatment could predict subsequent development of immune-related adrenal insufficiency(AI) or hypothyroidism. Methods This retrospective cohort study analyzed prospectively collected data from the I-SPY2 trial, a phase 2 platform trial for high-risk stage II/III breast cancer across 30 U.S. sites. The cohort included 482 women treated with experimental immunotherapy agents concurrent with weekly paclitaxel neoadjuvant chemotherapy. The primary outcomes were grade ≥ 1 hypothyroidism or AI, adjudicated by an independent safety group, up to 1-year post-treatment. Symptoms and irAEs were assessed using the Common Terminology Criteria for Adverse Events. Symptom burden was quantified as area under the curve (AUC) based on symptom grade and duration. Predictive modeling was performed using logistic regression and ROC analysis; symptom enrichment between cases and controls was evaluated using Fisher’s exact tests. Results Among 482 participants, 107 (22.2%) developed irAEs, with hypothyroidism (n = 61, 12.7%) occurring more frequently than AI (n = 38, 7.9%) at medians of 99 and 105 days from treatment initiation, respectively. Symptom enrichment analysis identified early predictive symptoms. Fatigue (17.2% vs 6.8%, p = 0.011) and rash (20.7% vs 7.8%, p = 0.0037) were predictive of hypothyroidism, while diarrhea (45.9% vs 31%, p = 0.048), constipation (5.4% vs 0.2%, p = 0.018), and taste changes (5.4% vs 0.5%, p = 0.034) were associated with AI. A predictive model demonstrated moderate performance (AUC 0.65 for AI, p < 0.0001; AUC 0.61 for hypothyroidism, p = 0.012). Model accuracy in an external validation cohort was 72.8% for AI and 74.7% for hypothyroidism. Conclusions This study presents a predictive framework to identify patients at risk for adrenal insufficiency and hypothyroidism as irAEs, enabling personalized care and proactive intervention to improve treatment outcomes and safety.

Abstract This review aims to update recent advancements in the management and treatment of olfactory neuroblastoma (ONB) based on discussions and topics highlighted during the 2024 North American Skull Base Society session “Literature Review: What's New in Olfactory Neuroblastoma?” A systematic review was conducted using PubMed/MEDLINE, focusing on relevant studies published between January 2022 and June 2024. Data were organized into themes: prognostication and staging, surgical concepts, biomarkers/genomics, imaging, syndrome of inappropriate antidiuretic hormone release and hyponatremia, chemotherapy, and radiotherapy. Out of 289 initial records, 46 studies met eligibility criteria. Key findings include the proposed integration of Hyams grading and dural infiltration with traditional staging for better prognostic accuracy, a shift toward less invasive surgical techniques while maintaining clear resection margins, and the identification of biomarkers for improved diagnosis and targeted therapy. Advanced imaging modalities like DOTA-peptide tomography (positron emission tomography–computed tomography/magnetic resonance imaging) were highlighted for their diagnostic value. Variability in induction chemotherapy outcomes underscores the need for personalized treatment plans, and new radiotherapy techniques offer promising results with improving morbidity. Recent advancements in ONB management have enhanced prognostic accuracy, molecular diagnostics, imaging techniques, and treatment outcomes. Continuous research is necessary to optimize these strategies and further improve patient survival and quality of life.

Convergent framework for future POC cancer diagnostics aligning clinical needs (why), enabling technologies (how), and translational bridges. It integrates lab-on-chip biosensing and analytics for decentralized, early, longitudinal care.

Neutrophils and neutrophil extracellular traps (NETs) contribute to early neuromyelitis optica (NMO) histopathology initiated by IgG targeting astrocytic aquaporin-4 (AQP4) water channels. Yet, the mechanisms underlying neutrophil recruitment and their pathogenic roles in disease progression remain unclear. To investigate molecular-cellular events preceding classical complement cascade activation in a mouse NMO model, we continuously infused, via spinal subarachnoid route, a non-complement-activating mouse monoclonal AQP4-IgG. Parenchymal infiltration of netting neutrophils containing C5a ensued with microglial activation and motor impairment but no blood-brain barrier leakage. Motor impairment and neuronal dysfunction both reversed when AQP4-IgG infusion stopped. Two-photon microscopy and electron microscopy–based reconstructions revealed physical interaction of infiltrating neutrophils with microglia. Ablation of either peripheral neutrophils or microglia attenuated the motor deficit, highlighting their synergistic pathogenic roles. Of note, mice lacking complement receptor C5aR1 exhibited reduction in neutrophil infiltration, microglial lysosomal activation, neuronal lipid droplet burden, and motor impairment. Pharmacological inhibition of C5aR1 recapitulated this protection. Immunohistochemical analysis of an NMO patient’s spinal cord revealed disease-associated microglia surrounding motor neurons in nondestructive lesions. Our study identifies neutrophil-derived C5a signaling through microglial C5aR1 as a key early driver of reversible motor neuron dysfunction in the precytolytic phase of NMO.

Abstract Generative artificial intelligence (AI) is rapidly populating medical records with synthetic or partially AI-generated content, creating a feedback loop where future models are increasingly at risk of training on uncurated AI-generated data. However, the clinical consequences of this AI-generated data contamination remain unexplored. Here, we show that in the absence of mandatory human verification, this self-referential cycle drives a rapid erosion of pathological variability and diagnostic reliability of medical data at population scale. By analysing more than 800,000 synthetic data points across clinical text generation, vision–language reporting, and medical image synthesis, we find that models progressively converge toward generic phenotypes regardless of the model architectures. Specifically, rare but critical findings, including pneumothorax and effusions, vanish from the synthetic content generated by AI models, while demographic representations skew heavily toward middle-aged male phenotypes. Crucially, this degradation is masked by false diagnostic confidence. Models continue to issue reassuring reports while failing to detect life-threatening pathology, with false reassurance rates tripling to 40%. Blinded physician evaluation confirms that this decoupling of confidence and accuracy renders AI-generated documentation clinically useless after just two generations. We systematically evaluate three mitigation strategies that can be easily integrated into existing clinical workflows, finding that while synthetic volume scaling fails to prevent collapse, mixing real data with quality-aware filtering effectively preserves diversity. Ultimately, our results suggest that without policy-mandated human oversight, the deployment of generative AI threatens to degrade the very healthcare data ecosystems it relies upon.

ABSTRACT Objectives While maxillary sinus fungal balls (MSFB) can be associated with odontogenic conditions (MSFBO), MSFBO clinical and dental features have not been compared to odontogenic sinusitis (ODS). This multicenter study aimed to compare characteristics of MSFB, MSFBO, and ODS. Methods A multicenter international retrospective cohort study was conducted on adults with MSFBs and ODS who underwent sinus surgery. First in MSFBs, it was determined whether different dental conditions were more likely in FB versus non‐FB sides. Second, clinical features and dental pathologies were compared between MSFBO and ODS. For analyses, dental conditions were considered individually and as two groups: infectious pathologies and dental/oral procedures with indwelling metallic materials. Results After exclusions, there were 203 MSFBs and 163 ODS. Among MSFBs, 141 were MSFBOs. FB sides were associated with sinus protrusion of root canal treatment (RCT) materials ( p = 0.040) and dental implants ( p = 0.040). Compared to MSFBO, ODS patients were younger, more likely to have MS purulence (OR = 40.9, p < 0.010), more likely associated with apical periodontitis (OR = 2.59, p = 0.010) and oroantral fistulas (OR = 6.94, p = 0.020), and less likely associated with extruded RCT materials (OR = 0.01, p = 0.010) and protruded midface screws (OR < 0.01, p = 0.010). Comparing purulent MSFBO and ODS, ODS was more associated with infectious dental pathologies ( p < 0.009). Conclusion Compared to MSFBs, MSFBOs were associated with RCT extrusion and implant protrusion. Compared to MSFBOs, ODS was more likely purulent and associated with infectious dental pathologies. While ODS is often distinct from MSFBO, the two conditions can coexist, and surgeons must determine whether patients have infectious dental pathology requiring treatment with both conditions. Level of Evidence 4.

Abstract Isolated/idiopathic rapid-eye-movement (REM)-Sleep Behavior Disorder (iRBD) is characterized by dream enactment behaviors associated with loss of REM atonia. iRBD is in most cases a prodromal synucleinopathy, and emerging evidence suggests associations between RBD and other neurological and psychiatric conditions. In this study, we performed pathway-based polygenic risk score (PRS) and rare variant burden analyses to examine these potential associations. Pathway-specific PRS were constructed from genome-wide association study summary statistics of five neurodegenerative and seven psychiatric traits across 10 biologically relevant pathway categories, including a total of 279 pathways, in 1,573 iRBD cases and 16,022 controls from the International RBD Study Group and UK Biobank. Rare variant burden tests were performed in 1,264 iRBD cases and 2,581 controls. We identified multiple potential pathways indicating shared polygenic risk between RBD and both neurodegenerative and psychiatric disorders. Lewy body diseases and post-traumatic stress disorder had the most shared polygenic risk pathways in neurological and psychiatric disorders, respectively. Two pathways, the serotonin transport pathway and the chaperone-mediated autophagy pathway, showed the strongest association with iRBD, and gene-based rare variants analyses revealed five genes associated with iRBD: GBA1 , PLEKHM1 , LRP2 , P2RX1 , and HAP1. Subsequent analysis of these genes in Parkinson’s disease and dementia with Lewy bodies replicated several associations. Together, these findings provide novel insights into the shared genetic architecture underlying iRBD, neurodegenerative disorders, and psychiatric traits, with implications for early identification and mechanistic understanding.

Abstract Background Artificial intelligence (AI) models trained on 12-lead ECGs effectively detect left ventricular systolic dysfunction (LVSD; left ventricular ejection fraction [LVEF] &lt;=40%). Continuous ECG monitoring via Holter recordings provides an opportunity for opportunistic screening for structural heart disease beyond rhythm disorders. We hypothesized that a lead-invariant version of the 12-lead AI model would enable a Holter monitor to screen for both arrhythmias and ventricular dysfunction. Methods We retrospectively analyzed continuous Holter ECGs from 17,665 patients who underwent a Holter and transthoracic echocardiogram (TTE) within 30 days of each other at Mayo Clinic. From each Holter, a random 20-minute of valid (non-flatline/lead disconnect) ECG segment was extracted and analyzed for LVSD detection using the adapted lead-invariant AI model. To evaluate stability, we examined model performance across different time points of the day, presenting results as area under the receiver operating characteristic curve (AUC) over time. Moreover, we illustrated the model’s robustness to noisy data by comparing its performance on raw ECG signals with that on bandpass-filtered inputs. Results Among 17,665 patients (mean age 59 years, 48.57% female), 4.96% had an LVEF &lt;=40%. The AI model demonstrated strong predictive performance (20-minute segment AUC 0.90, mean prediction of 24-hour AUC 0.92). Analysis of results over time (Figure) revealed temporal patterns in predictive accuracy, with specific time periods showing greater stability. Despite modest variability, model performance remained consistently high throughout the day, confirming robustness across different physiological states. The predictions remained robust with noisy input. We did not observe performance improvement when the baseline wander and high frequency noise are removed by the bandpass filter. Conclusion Applying a 12-lead AI ECG model with a lead-invariant framework to a continuous Holter ECG enables effective screening for left ventricular dysfunction. This suggests that AI-based analysis of Holter-monitors can facilitate opportunistic screening of ventricular dysfunction and may enable assessment of an arrhythmia’s impact on LVEF, as well as the relationship between arrhythmia burden and LVEF.Figure 1.Mean prediction AUC of the day Figure 2.AUC for different time point

Abstract Enhancer is a critical epigenetic feature in head and neck squamous cell carcinoma (HNSCC), yet the functional roles of individual enhancers remain poorly understood. Here, we conducted an integrative multi-omics analysis based on publicly available ATAC-seq, H3K27ac ChIP-seq, transcriptomic profiling, and genetic association datasets to systematically map HNSCC-associated enhancers and their target genes. Integrating ATAC-seq and H3K27ac ChIP-seq, we identified 20,362 enhancers and 18,040 enhancer-associated genes, highlighting widespread regulatory complexity. Functional characterization of the TERT -associated enhancer GH05J001312 (GRCh38/hg38: chr5:1312099-1317743) revealed strong transcriptional activity in HNSCC. CRISPR-mediated deletion of a core sequence significantly reduced TERT expression, impaired cellular proliferation in vitro , and suppressed tumor growth in vivo , confirming its role as a key cis-regulatory element. RNA-seq analysis of enhancer-edited cells uncovered 742 differentially expressed genes enriched in cancer-related pathways, including MAPK and IL-17 signaling, indicating a broad transcriptional impact. Collectively, our findings establish GH05J001312 as a functional enhancer driving oncogenic programs in HNSCC and suggest enhancer-targeted strategies as a potential therapeutic avenue.