Citations

Abstract Pulmonary fibrosis is increasingly understood to involve dysfunction within and across multiple cellular compartments, with recent attention highlighting the involvement of pulmonary vascular dysfunction in failed repair and progression of fibrosis. Formulation and delivery of lung-targeting lipid nanoparticles (LNPs) may provide a means to selectively target the lung but not systemic vasculature. However, the feasibility and efficacy of such approaches in the fibrotic lung are unknown. We sought to test whether intravenously administered lung-targeting LNPs can safely deliver mRNA to the healthy and fibrotic lung vasculature in young and aged mice and whether delivery of mRNA encoding a matricellular protein could promote fibrosis resolution. We used a selective organ targeting LNP formulation and characterized cell-specificity of delivery after bleomycin-induced lung fibrosis. We then delivered Ccn3 mRNA (encoding cellular communication network factor 3) to aged mice in the setting of established lung fibrosis and evaluated fibrotic regression and vascular repair. The matricellular protein encoded by Ccn3 was previously identified by our group as an important regulator of lung endothelial function. We found that LNP delivery was lung specific and predominantly endothelial targeting in the setting of lung fibrosis. Delivery of Ccn3 mRNA to aged mice via LNPs modestly reduced fibrosis and improved microvascular density in the lungs. Our results support the concept that cell-specific and repair-promoting cargos delivered via lung-targeting LNPs may have utility for treatment of established fibrosis.

ABSTRACT Background Atrial fibrillation (AF) is a prevalent arrhythmia that frequently coexists with cardiomyopathy, leading to deteriorated cardiovascular outcomes. Analyzing the trends associated with these conditions is essential for improving prevention strategies and management practices. Methods CDC WONDER (1999–2023) data were analyzed to assess AF with cardiomyopathy‐related mortality in patients aged ≥ 25. Using Joinpoint regression analysis, we calculated age‐adjusted mortality rates (AAMRs) per 100,000 patients and average annual percentage changes (AAPCs) to analyze mortality trends. Results AF with cardiomyopathy is responsible for 126,377 deaths among adults aged 25 and older. Alarmingly, AAMRs have surged from 1.8 per 100,000 in 1999 to 3.0 in 2023 (AAPC: 2.11, p < 0.001). The upward trend remains pronounced, particularly between 2016 and 2021, with an annual percentage change of 6.17 ( p = 0.02). Disparities in mortality rates are striking. Men face a higher AAMR than women (3.1 vs. 1.5), and Black individuals bear the heaviest burden at 2.4, closely followed by Whites at 2.3. Regionally, Vermont stands out with the highest AAMR at 3.6, while New York reports the lowest at 1.3. Both rural and urban areas maintain equal AAMRs of 2.1, yet the increase in rural regions is particularly concerning, reflecting an AAPC of 2.44 compared to 1.78 in urban settings. Conclusion The rising mortality rates from AF with cardiomyopathy in patients, particularly among men, Black individuals, and rural residents, demand urgent action. These concerning trends underscore a public health crisis that must be addressed.

Abstract Pneumocystis jirovecii pneumonia remains a significant cause of mortality and morbidity in immunocompromised populations worldwide. Mortality rates range from 5% to 30% in HIV-positive individuals and 4% to 76% in those without HIV. Recognizing its public health impact, the World Health Organization (WHO) included Pneumocystis jirovecii in its 2022 “Fungal Priority Pathogens” list. In this review, we will summarize published findings over the last 14 years on the immunopathogenic mechanisms underlying Pneumocystis pneumonia–related lung injury and examine the potential for targeting these pathways in adjunctive immune modulation therapy. Notably, recent studies have identified promising immune-based interventions, including PD-1/PD-L1 blockade and IL-7 therapy, which may enhance pathogen clearance while controlling damaging inflammation. Additionally, small molecule inhibitors such as BRD5529 and ALW-II-41-27 have shown potential in reducing lung injury by modulating proinflammatory signaling pathways in Pneumocystis pneumonia.

Rationale Despite significant advances in patient care and outcomes, criteria for cardiopulmonary exercise testing (CPET) in risk stratification guidelines for lung resection have not been updated in over a decade. We hypothesised that CPET no longer holds additional predictive value for postoperative complications. Methods In this secondary analysis, we included lung resection candidates from two prospective, multicentre studies eligible for CPET and assessed with preoperative pulmonary function tests (PFTs) and arterial blood gas analysis. Postoperative pulmonary (PPCs) and cardiovascular complications (PCCs) were documented during hospitalisation. We trained five types of machine learning models applying nested cross-validation to predict complications and compared predictive performance based on four metrics, including area under the receiver operating characteristic curve (AUC-ROC). Results A total of 497 patients were included. PPCs developed in 71 (14%) patients. Adding CPET parameters to PFTs and baseline clinical data did not improve the ability of models to predict PPCs in unselected patients (AUC-ROC=0.72–0.78; p=0.47), nor in those meeting American College of Chest Physicians (ACCPs) (n=236; AUC-ROC=0.64–0.78; p=0.70) or European Respiratory Society/European Society of Thoracic Surgery (ERS/ESTS) criteria (n=168; AUC-ROC=0.59–0.76; p=0.92). PCCs developed in 90 (18%) patients. CPET parameters likewise did not improve model performance for the prediction of PCCs in unselected patients (AUC-ROC=0.65–0.73; p=0.96), nor in the ACCP (AUC-ROC=0.61–0.73; p=0.82) or ERS/ESTS subgroups (AUC-ROC=0.62–0.69; p=0.87). Conclusions In contemporary surgical practice, CPET did not improve the predictive performance of machine learning models for PPCs or PCCs in patients with an indication based on established guidelines or in those without. The role of CPET in preoperative risk stratification for lung resection should be re-evaluated. Trial registration number NCT03498352 , NCT04826575 .

Background. The spirometric response to standard-of-care (SOC) immunosuppressive therapy for the management of bronchiolitis obliterans syndrome (BOS) has been sparsely reported in the literature. Data from a Medicare-approved Registry were analyzed to characterize the effectiveness/durability of a wide range of SOC interventions to manage the decline of lung function and to validate the study spirometric criteria for initiation of rescue therapy. Methods. Lung transplant recipients with refractory BOS at 21 US collaborating centers were enrolled in the Registry. Data included both nonspirometric (eg, demographic, Immunosuppressive Regimens for management of BOS) and spirometric parameters (ie, forced expiratory volume in 1 s [FEV 1 ] measurements and derived indices). The utility of study FEV 1 criteria for treatment (ie, statistically significant rate of FEV 1 decline >30 mL/mo) was evaluated by comparing the spirometric course between participants who met or did not meet this criterion. Results. Only 21% of participants treated with SOC therapy had >50% decrease (76 ± 25% decrease) in the rate of FEV 1 decline. Although 51% of participants had a partial response (rate of FEV 1 decline decreased on average 71%), 49% of participants had a substantial increase (mean increase 224%). The FEV 1 criterion for treatment was able to identify 19% of participants (48/258) who achieved durable stabilization (ie, nonsignificant rate of FEV 1 <30 mL/mo) with SOC therapy. Conclusions. Patients with BOS have a widely variable response to SOC therapy. Our findings support the use of FEV 1 rate of decline to assess response to SOC therapy and to ensure appropriate assignment of participants with refractory BOS to rescue therapy treatment cohorts.

Background A classification system describing clinical presentation before aortic valve replacement (AVR) has recently been proposed (stable valve syndrome [SVS]), mildly symptomatic (progressive valve syndrome), or with acute and severe signs and symptoms (acute valve syndrome [AVS]). We aimed to evaluate the clinical impact, health care costs, and resource use associated with the mode of clinical presentation at the time of AVR among patients presenting with aortic stenosis. Methods Using the Market Clarity database (2017–2023), patients >18 years old with aortic stenosis and undergoing AVR (transcatheter or surgical) were included. Patients were categorized as SVS, progressive valve syndrome, or AVS based on their clinical presentation during the 1 year before AVR. All‐cause death, heart failure hospitalization, total health care costs (index hospitalization plus 1‐year follow‐up), and resource use were compared across clinical presentation groups using adjusted regression models. Results Of the 24 075 patients undergoing AVR for aortic stenosis, 270 (1.1%) had SVS, 10 195 (42.3%) progressive valve syndrome, and 13 610 (56.5%) AVS. Compared with SVS, AVS presentation was associated with increased risk of 1‐year death (adjusted hazard ratio [aHR], 2.93 [95% CI, 1.1–7.8]; P =0.03) and heart failure hospitalization (aHR, 4.15 [95% CI, 1.6–11.1]; P <0.01) after AVR. The total costs of AVR and 1‐year follow‐up were significantly higher in both the progressive valve syndrome (difference $27 410 [$13 507–$41 314]) and AVS groups (difference $36 267 [$22 302–$50 232]) compared with patients with SVS. Conclusions AVS was frequent among patients undergoing AVR and was associated with increase in death, heart failure hospitalization, health care costs, and resource use 1 year after AVR, and SVS presentation was associated with the best clinical and economic outcomes.

Background: Lung cancer remains the leading cause of cancer-related mortality globally, largely due to delayed diagnosis in its early stages. While conventional diagnostic tools like low-dose CT and tissue biopsy are routinely used, they suffer from limitations including invasiveness, radiation exposure, cost, and limited sensitivity for early-stage detection. Liquid biopsy, a minimally invasive alternative that captures circulating tumor-derived biomarkers such as ctDNA, cfRNA, and exosomes from body fluids, offers promising diagnostic potential—yet its sensitivity in early disease remains suboptimal. Recent advances in Artificial Intelligence (AI) and radiomics are poised to bridge this gap. Objective: This review aims to explore how AI, in combination with radiomics, enhances the diagnostic capabilities of liquid biopsy for early detection of lung cancer and facilitates personalized monitoring strategies. Content Overview: We begin by outlining the molecular heterogeneity of lung cancer, emphasizing the need for earlier, more accurate detection strategies. The discussion then transitions into liquid biopsy and its key analytes, followed by an in-depth overview of AI techniques—including machine learning (e.g., SVMs, Random Forest) and deep learning models (e.g., CNNs, RNNs, GANs)—that enable robust pattern recognition across multi-omics datasets. The role of radiomics, which quantitatively extracts spatial and morphological features from imaging modalities such as CT and PET, is explored in conjunction with AI to provide an integrative, multimodal approach. This convergence supports the broader vision of precision medicine by integrating omics data, imaging, and electronic health records. Discussion: The synergy between AI, liquid biopsy, and radiomics signifies a shift from traditional diagnostics toward dynamic, patient-specific decision-making. Radiomics contributes spatial information, while AI improves pattern detection and predictive modeling. Despite these advancements, challenges remain—including data standardization, limited annotated datasets, the interpretability of deep learning models, and ethical considerations. A push toward rigorous validation and multimodal AI frameworks is necessary to facilitate clinical adoption. Conclusion: The integration of AI with liquid biopsy and radiomics holds transformative potential for early lung cancer detection. This non-invasive, scalable, and individualized diagnostic paradigm could significantly reduce lung cancer mortality through timely and targeted interventions. As technology and regulatory pathways mature, collaborative research is crucial to standardize methodologies and translate this innovation into routine clinical practice.

AbstractInterstitial lung disease (ILD) encompasses pulmonary disorders characterized by chronic inflammation and fibrosis that disrupt pulmonary gas exchange. While ILD‐related changes in the lung parenchyma are well‐documented, less is known about how ILD affects luminal area within the large conducting airways. This retrospective, case–control study tested the hypothesis that patients with ILD would have greater large conducting airway luminal areas than healthy matched controls. Three‐dimensional reconstructions of computed tomography images were used to quantify airway luminal areas in patients with ILD (n = 82; 54% female) and healthy controls matched for age, sex, and height. Patients with ILD had 16%–22% greater airway luminal areas across all seven measured large conducting airways compared to controls (all p < 0.001). Among patients with ILD, males had 17%–34% greater height‐normalized airway luminal areas than females (all p < 0.05). These data provide evidence that ILD is associated with greater large conducting airway luminal area, even when matched for key demographic factors. Consistent with observations in health, males with ILD exhibited greater height‐normalized airway size than females. These findings offer new insight into airway remodeling in ILD and highlight potential sex differences in airway luminal area.