Citations

Abstract Metabolic reprogramming is a fundamental determinant of immune cell fate and effector function during inflammation, yet how distinct metabolic pathways regulate pathogenic lung macrophage activity and contribute to fibrotic remodeling remains incompletely understood. Here, we integrated single-cell RNA sequencing, lineage-specific genetic mouse models, and fate-mapping approaches to define the metabolic pathways that regulate the pro-fibrotic activity of lung macrophages. We found that such cells undergo pronounced aerobic glycolysis in the bleomycin-induced mouse model of pulmonary fibrosis. Myeloid cell-specific depletion of lactate dehydrogenase A (Ldha), but not of mitochondrial pyruvate carrier (Mpc), markedly attenuated lung fibrosis and improved survival. Mechanistically, enhanced glycolytic flux increased lactate production, which promoted histone lysine lactylation and facilitated Arginase 1 (Arg1) expression in lung macrophages, thereby driving fibrotic progression. Using monocyte fate-mapping, we further demonstrated that Arg1 expression is largely restricted to recruited monocyte-derived macrophages rather than lung-resident macrophages. Notably, selective deletion of Ldha in granulocyte-monocyte progenitors and their progeny was sufficient to suppress Arg1 expression and reduce fibrosis severity. In human lung samples, we observed significantly elevated expression of ARG1 and key glycolytic enzymes in patients with idiopathic pulmonary fibrosis, despite species-specific differences in the immune cell types expressing ARG1. Together, these findings identify an aerobic glycolysis–lactate–histone lactylation axis that regulates pro-fibrotic myeloid cell function and represents a potential therapeutic target in pulmonary fibrosis.

GGGGCC (G 4 C 2 ) repeat expansion in C9ORF72 is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Toxicity is thought to result from the accumulation of either repeat RNAs and/or dipeptide repeat proteins (DPRs) translated from repeat-containing transcripts through repeat-associated non-AUG (RAN) translation. To disentangle RNA from DPR toxicity, we mutated a CUG codon predominantly used to initiate DPR translation from all three reading frames. This mutation disrupted DPR synthesis while preserving the expression of repeat-containing RNAs. Despite the accumulation of RNA foci, behavioral deficits and pathological abnormalities, including p-TDP-43 inclusions, STING activation, motor neuron loss, neuroinflammation, and increased plasma neurofilament concentration, were alleviated in C9ORF72 mice. Base editing of the CUG codon also improved molecular phenotypes and survival in patient induced pluripotent stem cell–derived neurons, which highlights the potential of therapeutically targeting DPR production rather than repeat RNAs.

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.

ABSTRACT Tumorigenesis and metastasis are frequently attributed to the intricate interplay between cancer cells and the tumor microenvironment (TME). Comprehending the mechanisms and key regulators of cancer‐immune crosstalk in the TME is imperative for developing efficacious immunotherapy. Through a series of in vivo CRISPR screens, we identified tumor‐intrinsic ITGB1 as a critical regulator of triple‐negative breast cancer (TNBC) development and deciphered its underlying mechanisms. Tumoral ITGB1 facilitated the establishment of pro‐tumorigenic TME by orchestrating tumor‐associated myeloid populations. Suppressing ITGB1 favored the enrichment of anti‐tumorigenic myeloid cells and enhanced infiltration of CD4 and CD8 T cells, culminating in superior antitumor effects. CRISPR scanning pinpointed a previously unrecognized functional domain essential for ITGB1's pro‐tumorigenic activity. This domain is distinct from all known ligand‐binding sites in ITGB1. An antibody capable of sterically blocking this domain significantly impaired TNBC progression. These findings position tumoral ITGB1 as a promising therapeutic target for reprogramming the TME from a pro‐ to an anti‐tumorigenic state, thereby effectively inhibiting TNBC development. Our study uncovers a novel mechanism of TNBC development and provides a unique therapeutic strategy for targeting ITGB1 in TNBC treatment.

BACKGROUND: Myocardial flow reserve (MFR), measured by positron emission tomography (PET) myocardial perfusion imaging, provides valuable information on epicardial coronary disease, diffuse atherosclerosis, and microvascular function. Despite its routine use, the prognostic efficacy of 13 N-ammonia PET MFR remains unconfirmed in larger multicenter cohorts of patients with suspected or known coronary artery disease. METHODS: We considered patients from 5 sites in the REFINE PET (Registry of Flow and Perfusion Imaging for Artificial Intelligence with PET) registry who underwent 13 N-ammonia PET myocardial perfusion imaging for coronary artery disease. Clinical and imaging data were collected at the time of myocardial perfusion imaging. MFR was quantified as the ratio of stress to rest myocardial blood flow, using QPET software (Cedars-Sinai Medical Center, Los Angeles, CA). The primary outcome was all-cause mortality. Survival analyses were performed using Kaplan-Meier and Cox regression models adjusted for clinical and imaging covariates. RESULTS: In total, 6277 patients were included (median age of 65 years, 56% male). Median follow-up time was 3.8 years. There were 1895 patients with MFR ≤2 and 4382 with MFR >2. Patients with MFR ≤2 had significantly higher mortality than those with MFR >2 (n=701 [37.0%] versus n=537 [12.3%], respectively; P <0.001). Annualized all-cause mortality rates by MFR and summed stress score ranged from 1.7 to 15.8. In multivariable analysis, MFR ≤2 was independently associated with increased all-cause mortality in the overall population (hazard ratio, 2.70 [95% CI, 2.41–3.03]; P <0.001), even among patients with no perfusion defects (hazard ratio, 2.36 [95% CI, 1.93–2.89]; P <0.001). Mortality risk decreased across increasing MFR deciles, ranging from hazard ratio, 2.73 (95% CI, 2.39–3.11) to hazard ratio, 0.35 (95% CI, 0.25–0.49). CONCLUSIONS: In this large multicenter cohort, MFR derived from 13 N-ammonia PET myocardial perfusion imaging is a strong, independent predictor of all-cause mortality, even in patients with normal perfusion. An MFR of ≤2 identifies elevated risk, while higher values are associated with improved survival. These findings support the routine integration of MFR to enhance risk stratification in patients with suspected or known coronary artery disease.

Objective: To assess the link between retinal vascular health and cognitive performance in a diverse population, using a novel mobile laboratory platform and portable color fundus photography. Background: The retina is an accessible window into brain health. Studies that had highlighted the link between retinal vasculature and cognition included clinical populations or narrowly defined research cohorts, with limited generalizability. To address the need to expand this research to demographic and geographic diverse communities, we launched a mobile laboratory platform across rural and urban Arizona zip codes. Methods: 240 subjects were recruited in our prospective community-based study. We assessed cognition using the MindCrowd web-based testing platform and analyzed verbal paired associates (VPA) task, a validated measure of verbal associative memory sensitive to age-related cognitive decline. Non-mydriatic color fundus photographs were obtained using the portable hand-held Aurora camera (Optomed), two images per eye (disc- and macula-centered). Image processing and vascular feature quantification were automatically conducted using Automorph software. Linear regression models examined the associations between retinal vascular metrics and VPA, adjusting for age, sex, education attainment, and risk factors. Results: Our cohort’s mean age was 45 +/-16.7 years, 32.9% were male and 39.5% had a college degree. In disc-centered fundus images, fractal dimension strongly associated with chronological age (p = 1.04E-10). Greater artery tortuosity in the retinal zones B and C was associated with lower VPA (p = 0.02 and p = 0.004, respectively). In macula-centered images, fractal dimension showed the strongest association with age (p = 4.31E-11), reinforcing its utility as a robust biomarker of vascular aging. Males had wider average artery caliber in zone B (p=0.02). Zone B vein fractal dimension (p=0.002) and vein vessel density (p=0.006) were the strongest predictors of VPA. Conclusions: This study demonstrates the safety, feasibility, and utility of a mobile laboratory to collect high-quality non-mydriatic color photos and cognitive data across a geographically diverse cohort. Arterial tortuosity and venous fractal dimension and density, particularly in retinal zone B, were predictive of cognitive performance, after adjusting for vascular health covariates. Retina may become a scalable and accessible platform for studying brain aging in the general population.

Abstract Cancer occurs in ∼1 per 1000 pregnancies; thousands of patients may require radiation procedures for diagnosis and treatment each year in the United States alone. This rare but high-risk scenario, coupled with fear of radiation, has created ambiguity in the ideal management of pregnant patients. Without a comprehensive guide for the use of radiation in imaging and treatment for pregnant cancer patients, it is difficult for providers to offer optimal patient-centered care without introducing disparities. The goal of this paper is to provide guidance on the use of radiation for screening, diagnosis, staging, and treatment of cancer, while highlighting gaps in existing knowledge and guidelines. The intention is that physicians, medical physicists, and patients could use this document as a resource for shared decision-making, ensuring safe and effective practice. A team of physicians and medical physicists with expertise in imaging, radiotherapy, and maternal fetal medicine was assembled, along with a patient advocate and lawyer. Existing guidelines and recent literature were reviewed. Authors also drew from their experience where published guidance was lacking. The resulting document discusses best practice to guide use of radiation for cancer, as well as patient-centered care management and legal considerations. Overall, it is possible to safely and effectively deliver radiation to pregnant patients in numerous circumstances. Use of radiation or other modalities should be discussed through shared decision-making with the physician and patient, contextualizing the maternal and fetal risk from treatments. Healthcare providers should support wide access to reproductive healthcare to allow equitable, evidence-based, patient-centered healthcare.

Abstract Objectives To comprehensively evaluate the validity of International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes for both prevalent diagnoses and less common diseases, and to assess the performance of a large language model (LLM)-based system in validating these codes. Materials and Methods This retrospective study analyzed hospital admissions from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. We developed a validated LLM-based system using GPT-4o, refined through iterative prompt engineering, to assess ICD-10-CM code validity. We measured the positive predictive value (PPV) of ICD-10-CM codes, PPV of principal and secondary diagnoses, and the performance of an LLM-based system in code validation. Results Among 865 079 assigned codes, the PPV was 84.6% (95% CI, 84.5%-84.6%). Principal diagnoses had a PPV of 93.9% (95% CI, 93.7%-94.1%), while secondary diagnoses had a PPV of 83.8% (95% CI, 83.7%-83.9%). The LLM system demonstrated high performance in validating ICD codes, achieving 93.6% accuracy, 95.4% sensitivity, and 85.2% specificity. Among correctly assigned secondary diagnoses, the majority (67.9%) represented historical or baseline conditions, while 32.1% reflected active conditions that deviated from baseline status; 22.3% of these emerged after hospital admission. PPV decreases with later diagnosis positions, with the largest decline occurring between principal and secondary diagnoses. Discussion and Conclusion In this large-scale evaluation, ICD-10-CM codes exhibited generally high accuracy, though variability existed by position and condition type. A validated LLM system performed comparably to physician review and offers a scalable means to improve coding accuracy. These findings support the potential for integrating LLM-based auditing into routine workflows to strengthen the quality of administrative and research data.

ABSTRACT Objective This study aims to identify both fluid and neuroimaging biomarkers for CSF1R‐RD that can inform the optimal timing of treatment administration to maximize therapeutic benefit, while also providing sensitive quantitative measurements to monitor disease progression. Methods Our study compared neuroimaging and fluid (plasma and cerebrospinal fluid (CSF)) biomarkers across three distinct populations: asymptomatic CSF1R pathogenic variant carriers ( N = 14), symptomatic CSF1R pathogenic variant carriers ( N = 17), and healthy controls ( N = 30). We evaluated biomarker correlations with both an established (Montreal Cognitive Assessment (MoCA)) and a novel (CSF1R Clinical Severity Score (CCSS)) clinical diagnostic scale to investigate potential clinical utility. Additionally, we tested the relationship between select biomarkers and cortical thickness using 3D T1‐weighted MPRAGE scans, providing a highly valuable physiological component to our analyses. Results Our results demonstrate that while plasma glial fibrillary acidic protein (GFAP) displays a high sensitivity for distinguishing early‐stage CSF1R‐RD patients from healthy controls, plasma neurofilament light chain (NfL) is more effective for tracking disease progression following the onset of symptoms. Interpretation Overall, our study provides evidence for plasma NfL and GFAP as valuable biomarkers of earliest symptom onset and disease progression for CSF1R‐RD.