Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are severe inflammatory lung diseases with high morbidity and mortality, lacking specific treatments. Inhalation offers direct access to the damaged lung epithelium, making tracheal gene delivery a promising approach. However, challenges such as low efficiency, off-target effects, and repeated dosing limit its effectiveness. In this study, we developed an inhalable recombinant adenoviral vector (Ad-IL4/10) carrying dual reporter genes to deliver interleukin-10 (IL10) and interleukin-4 (IL4) to the lungs, enabling efficient and sustained expression of anti-inflammatory cytokines. Using a lipopolysaccharide (LPS)-induced lung injury mouse model, the anti-inflammatory effects of aerosolized Ad-IL4/10 were evaluated. The results showed that aerosolized Ad-IL4/10 significantly reduced weight loss, lung wet-to-dry weight ratio, and total protein levels in bronchoalveolar lavage fluid (BALF). Additionally, it alleviated pulmonary inflammation and alveolar damage while suppressing proinflammatory markers and LPS-induced monocyte and neutrophil infiltration. Ad-IL4/10 also restored monocyte-macrophage homeostasis. These findings indicate that an inhalable adenoviral vector effectively mitigates LPS-induced lung injury through IL4 and IL10 delivery, offering a promising therapeutic strategy for ALI.

BACKGROUND: Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is characterized by a significant worsening of respiratory symptoms. Blood eosinophil levels are a key predictor of glucocorticoid efficacy in AECOPD patients; however, their stability can present challenges. Predicting stable eosinophil levels from CT images is essential for optimal patient management. METHODS: This study utilized CT images from 482 AECOPD patients across two hospitals. Dataset 1 comprised 193 patients for model development, while Dataset 2 included 289 patients for external validation. A threshold of 2% eosinophil was used to differentiate between high and low eosinophil levels. A machine learning model was developed to predict eosinophil levels using CT radiomics and quantitative computed tomography (QCT) features. Radiomics features were extracted, and feature selection was performed using random forest (RF) algorithms. Segmentation of pulmonary lobes, airways, and blood vessels yielded 20 QCT features. A Gradient Boosting (GB) classifier was then trained on the fused features. RESULTS: The GB classifier with radiomics features demonstrated strong performance, achieving an accuracy (ACC) of 0.734 and an area under the curve (AUC) of 0.838 on the test set of Dataset 1. In external validation, the ACC and AUC were 0.624 and 0.671, respectively. After fusing QCT features, the ACC and AUC improved to 0.786 and 0.843, respectively, with external validation results of 0.673 and 0.697. CONCLUSION: The CT image-based machine learning model can predict blood eosinophil levels in AECOPD patients, providing a noninvasive and stable assessment. It has potential for future clinical application following further validation and external testing.

ABSTRACT ST‐segment elevation myocardial infarction (STEMI) remains a major cause of cardiovascular mortality and morbidity worldwide. Despite advances in reperfusion therapy, many patients still develop irreversible myocardial injury and adverse ventricular remodeling. Intracoronary mesenchymal stem cell (MSC) administration has been investigated as a potential therapeutic approach, but clinical evidence remains inconsistent. We performed a systematic review and meta‐analysis of randomized controlled trials (RCTs) comparing intracoronary MSC administration with standard care in STEMI patients. Databases were searched from inception through February 2026. Eight RCTs involving 796 patients were identified, and seven trials with 400 patients were included in the quantitative analysis after excluding one study under Expression of Concern. MSC administration significantly improved ΔLVEF (I2 = 44.6%, p = 0.108; WMD = 3.18, 95% CI: 1.52–4.83, p < 0.001). No significant differences were detected in rehospitalization for heart failure (I2 = 0.0%, p = 0.592; RR = 1.14, 95% CI: 0.36–3.61, p = 0.831), all‐cause mortality (I2 = 0.0%, p = 0.525; RR = 1.51, 95% CI: 0.24–9.31, p = 0.659), or MACE (I2 = 0.0%, p = 0.887; RR = 2.47, 95% CI: 0.55–11.05, p = 0.236). Intracoronary MSC administration after STEMI is associated with a modest improvement in left ventricular function, while no reduction in clinical events was found. No major safety signal was identified, although available safety data remain limited. Larger and well‐designed trials with longer follow‐up are still needed. Trial Registration: PROSPERO: CRD420261286620

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disorder characterized by persistent airflow limitation and is a leading cause of morbidity and mortality worldwide. While cigarette smoking is the primary environmental risk factor, only a subset of smokers develops clinically significant COPD, indicating roles for genetic susceptibility and dysregulated cellular responses. Although traditionally viewed as an immune-driven inflammatory disease, recent evidence underscores the active contribution of structural cells—particularly alveolar type II epithelial cells (AT2 cells)—to immune regulation and tissue remodeling. This study integrated single-cell transcriptomics, conditional gene knockout mouse models, organoid culture, multiplex immunofluorescence validation, and flow cytometry to investigate the role of the RS1 gene in chronic obstructive pulmonary disease (COPD). Single-cell sequencing technology revealed RS1 as a signature gene of AT2 cells. Using cigarette smoke (CS)-exposed AT2 cell-specific RS1 knockout mice and organoids as models, we elucidated the mechanisms by which RS1 regulates AT2 cells and its associated role in COPD pathogenesis through molecular experiments. Single-cell RNA sequencing analysis revealed that RS1 is specifically expressed in AT2 cells in COPD models, and its expression exhibits interactions with immune cells. By constructing a COPD mouse model with AT2 cell-specific RS1 knockout (Sftpccre;RS1fl/fl) and organoid models, we demonstrated that RS1-deficient AT2 cells display enhanced proliferative capacity and suppress macrophage infiltration. Mechanistically, RS1 mediates the interaction between NEDD4 and YAP1 through serine 105, while the RS1-NEDD4 interaction facilitates YAP1 dephosphorylation and nuclear translocation. Treatment with the selective NEDD4 inhibitor I3C further suppressed TGFB1 expression and macrophage infiltration. RS1 suppresses AT2 cell proliferative capacity and promotes macrophage infiltration. RS1 interacts with NEDD4 to mediate YAP1 dephosphorylation and nuclear translocation, and treatment with the selective NEDD4 inhibitor I3C further suppresses TGFB1 expression and macrophage infiltration.

Chronic Obstructive Pulmonary Disease (COPD) is one of the leading causes of death worldwide, and current treatments fail to significantly halt its progression. Exosomes derived from mesenchymal stem cells (MSCs-Exos) have demonstrated promising potential in treating COPD due to their anti-inflammatory and regenerative biological properties. In this study, we investigated the potential anti-inflammatory effects of bone marrow mesenchymal stem cell-derived exosomes (BMSCs-Exos) in a COPD rat model and the possible mechanisms by which they inhibit airway remodeling, as well as identifying the optimal dosage and administration route. Our results show that nebulized BMSC-Exos significantly improve lung function in COPD rats while reducing pulmonary inflammatory infiltration, bronchial mucus secretion, and collagen deposition. Moreover, BMSC-Exos treatment notably decreased the expression of pro-inflammatory cytokines such as TNF-alpha, IL-6 and IL-1(3, and the pro-fibrotic factor TGF-(31 in serum, bronchoalveolar lavage fluid (BALF), and lung tissue. The most pronounced therapeutic effect was observed at a low dose of exosomes. Furthermore, quantitative real-time PCR and immunohistochemical analyses revealed that nebulized BMSC-Exos significantly inhibited airway remodeling and epithelial-mesenchymal transition (EMT) by suppressing the Wnt/(3-catenin signaling pathway. In conclusion, these findings indicate that nebulized BMSC-Exos offer a noninvasive therapeutic strategy for COPD by mitigating lung inflammation and airway remodeling through the suppression of abnormal Wnt/(3-catenin pathway activation induced by cigarette smoke (CS) and lipopolysaccharide (LPS) in rats.

Background and objective Chronic obstructive pulmonary disease (COPD) has high heterogeneity in etiologies and clinical manifestations. Expiratory Computed tomography (CT) can effectively assess air trapping, aiding in disease diagnosis. However, due to concerns about radiation exposure and cost, expiratory CT is not routinely performed. Recent work on synthesizing expiratory CT has primarily focused on imaging features while neglecting patient-specific pulmonary function. Methods To address these issues, we developed a novel model named BreathVisionNet that incorporates pulmonary function data to guide the synthesis of expiratory CT from inspiratory CT. An architecture combining a convolutional neural network and transformer is introduced to leverage the irregular phenotypic distribution in COPD patients. The model can better understand the long-range and global contexts by incorporating global information into the encoder. The utilization of edge information and multi-view data further enhances the quality of the synthesized CT. Parametric response mapping (PRM) can be estimated by using synthesized expiratory CT and inspiratory CT to quantify COPD phenotypes of the normal, emphysema, and functional small airway disease (fSAD), including their percentages, spatial distributions, and voxel distribution maps. Results BreathVisionNet outperforms other generative models in terms of synthesized image quality. It achieves a mean absolute error, normalized mean square error, structural similarity index and peak signal-to-noise ratio of 78.207 HU, 0.643, 0.847 and 25.828 dB, respectively. Comparing the predicted and real PRM, the Dice coefficient can reach 0.732 (emphysema) and 0.560 (fSAD). The mean of differences between true and predicted fSAD percentage is 4.42 for the development dataset (low radiation dose CT scans), and 9.05 for an independent external validation dataset (routine dose), indicating that model has great generalizability. A classifier trained on voxel distribution maps can achieve an accuracy of 0.891 in predicting the presence of COPD. Conclusions BreathVisionNet can accurately synthesize expiratory CT images from inspiratory CT and predict their voxel distribution. The estimated PRM can help to quantify COPD phenotypes of the normal, emphysema, and fSAD. This capability provides additional insights into COPD diversity while only inspiratory CT images are available.

Studies have indicated a complex association between chronic obstructive pulmonary disease (COPD) and lung adenocarcinoma (LUAD). However, the underlying mechanisms of their coexistence are still not fully understood. Thus, this study evaluated the possible mechanisms and biomarkers of COPD and LUAD by analyzing public RNA sequencing databases via bioinformatics analysis. This study obtained the LUAD datasets (TCGA-LUAD, GSE118370, and GSE30219) and the COPD dataset (GSE11784 and GSE39874) from TCGA and GEO databases, respectively. The differentially expressed genes (DEGs) were analyzed using the DESeq2 and limma packages. These DEGs were then intersected with pyroptosis-related genes (PRGs) to produce PRDEGs, which were examined via GO analysis and KEGG enrichment analyses. Simultaneously, a prognostic model was developed using PRDEGs by the TCGA-LUAD dataset to generate diagnostic PRDEGs (DPRDEGs). The STING database was employed to develop a protein-protein interaction (PPI) network for DPRDEGs. Transcription factors-associated with DPRDEGs were also identified in the ChIPBase and hTFtarget databases. The comparative toxicogenomics database (CTD) was employed to detect possible drugs or small molecules that interacted with DPRDEGs, and results were illustrated using Cytoscape. Moreover, this study developed a prognostic model using multivariate analysis and simultaneously conducted a prognostic analysis. The results were further validated by immunohistochemistry (IHC), western blotting (WB), and qPCR of clinical specimens. A total of 273 DEGs were identified, and 12 PRDEGs were detected after intersecting with PRGs. Inflammation and infectious diseases were the primary enriched regions for these PRDEGs, as indicated by GO and KEGG enrichment analyses. The study identified six DPRDEGs (BNIP3, FTO, NEK7, POLR2H, S100A12, and TLR4) via prognosis modeling of PRDEGs. The expression of these DPRDEGs in COPD and LUAD was verified through IHC, WB, and qPCR examinations. Based on multifactorial prognosis modeling, among six, FTO, POLR2H, S100A12, and TLR4 revealed enhanced prognostic predictive effects. This study demonstrated that COPD and LUAD have common pathogenic mechanisms. The identified DPRDEGs and predictive models offer new perspectives for understanding and addressing COPD and LUAD.

BACKGROUND:Sodium-glucose cotransporter 2 (SGLT2) inhibitors have shown neuroprotective potential. This meta-analysis aimed to compare the effects of SGLT2 inhibitors and dipeptidyl peptidase-4 (DPP-4) inhibitors on dementia risk in patients with type 2 diabetes mellitus (T2DM). METHODS:A systematic search of PubMed, EMBASE, Cochrane Library, and Web of Science was conducted from inception through May 2025. Cohort studies comparing dementia incidence in T2DM patients treated with SGLT2 inhibitors versus DPP-4 inhibitors were included. Study quality was assessed using the Newcastle-Ottawa Scale (NOS). Data were pooled using a random-effects model in STATA 12.0, with incidence rate ratios (IRRs) and 95 % confidence intervals (CIs) calculated for dementia outcomes. RESULTS:Eight cohort studies (1275,257 participants) were analyzed. SGLT2 inhibitor use was associated with a 33 % lower risk of all-cause dementia compared to DPP-4 inhibitors (I² = 0.0 %, P = 0.816; IRR = 0.666; 95 % CI: 0.484-0.918; P < 0.05). Subgroup analyses indicated non-significant risk reductions for Alzheimer's disease (I² = 0.0 %, P = 0.994; IRR = 0.654; 95 % CI: 0.352-1.212; P = 0.177) and vascular dementia (I² = 0.0 %, P = 0.971; IRR = 0.573; 95 % CI: 0.204-1.605; P = 0.289). CONCLUSIONS:SGLT2 inhibitors are associated with a significantly reduced risk of all-cause dementia in T2DM patients compared to DPP-4 inhibitors. While trends favoring SGLT2 inhibitors were observed for dementia subtypes, further long-term studies are needed to confirm these associations.

High-flow nasal cannula (HFNC) has recently emerged as a promising alternative to non-invasive ventilation (NIV) for patients with chronic obstructive pulmonary disease (COPD). However, direct comparative evidence on the clinical efficacy of HFNC versus NIV in acute exacerbations of COPD (AECOPD) remains limited and inconclusive. A systematic search of PubMed, EMBASE, Cochrane Library, and Web of Science was conducted up to January 2025 for randomized controlled trials (RCTs) comparing HFNC and NIV in AECOPD patients. Outcomes included mortality, treatment failure, intubation rates, and treatment intolerance. Nine RCTs involving 786 patients were included in the meta-analysis. No significant differences were observed in mortality (I2 = 0.0

BACKGROUND:Non-cystic fibrosis bronchiectasis (NCFB) is often complicated by chronic Pseudomonas aeruginosa infection. Inhaled antibiotics, such as tobramycin, have been explored for their efficacy in managing these infections, but their efficacy and safety in NCFB remains uncertain. METHODS:We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) to assess the efficacy and safety of inhaled tobramycin in NCFB patients. PubMed, EMBASE, Cochrane Library, and ISI Web of Science databases were searched up to June 2024 using predefined keywords. Studies comparing inhaled tobramycin versus placebo were included if they reported outcomes related to P. aeruginosa eradication, sputum density, exacerbations, hospital admissions, and adverse events. RESULTS:Nine RCTs involving 772 patients met the inclusion criteria. Inhaled tobramycin significantly increased P. aeruginosa eradication rates compared to placebo (I2 = 22.0 %, P = 0.255; RR 2.422, 95 % CI 1.570 to 3.738, P < 0.001). There was a marked reduction in hospital admissions (I2 = 27.9 %, P = 0.250; WMD -0.523, 95 % CI -0.879 to -0.167, P = 0.004) but no significant difference in exacerbation rates (I2 = 31.9 %, P = 0.196; RR 0.837, 95 % CI 0.519 to 1.349, P = 0.464). Adverse events leading to trial discontinuation were higher in the tobramycin group (I2 = 0.0 %, P = 0.634; RR 1.968, 95 % CI 1.197 to 3.236, P = 0.008). CONCLUSIONS:Inhaled tobramycin therapy demonstrated efficacy in eradicating P. aeruginosa and reducing hospital admissions in patients with NCFB. However, no significant impact on exacerbation rates was observed, and the higher incidence of adverse events necessitates careful consideration in clinical practice.

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous disease with various phenotypes. Registered inspiratory and expiratory CT images can generate the parametric response map (PRM) that characterizes phenotypes' spatial distribution and proportions. However, increased radiation dosage, scan time, quality control, and patient cooperation requirements limit the utility of PRM. This study aims to synthesize a PRM using only inspiratory CT scans. First, a CycleGAN with perceptual loss and a multiscale discriminator (MPCycleGAN) is proposed and trained to synthesize registered expiratory CT images from inspiratory images. Next, a strategy named InspirationOnly is introduced, where synthesized images replace actual expiratory CT images. The image synthesizer outperformed state-of-the-art models, achieving a mean absolute error of 105.66 ± 36.64 HU, a peak signal-to-noise ratio of 21.43 ± 1.87 dB, and a structural similarity of 0.84 ± 0.02. The intraclass correlation coefficients of emphysema, fSAD, and normal proportions between the InspirationOnly and ground truth were 0.995, 0.829, and 0.914, respectively. The proposed MPCycleGAN enables the InspirationOnly strategy to yield PRM using only inspiratory CT. The estimated COPD phenotypes are consistent with those from dual-phase CT and correlated with the spirometry parameters. This offers a potential tool for characterizing phenotypes of COPD, particularly when expiratory CT images are unavailable.

Objective. Intrathoracic airway segmentation in computed tomography is important for quantitative and qualitative analysis of various chronic respiratory diseases and bronchial surgery navigation. However, the airway tree's morphological complexity, incomplete labels resulting from annotation difficulty, and intra-class imbalance between main and terminal airways limit the segmentation performance. Approach. Three methodological improvements are proposed to deal with the challenges. Firstly, we design a dilated contextual transformer-UNet to collect better information on neighboring voxels and ones within a larger spatial region. Secondly, an airway label self-updating strategy is proposed to iteratively update the reference labels to conquer the problem of incomplete labels. Thirdly, a deep learning-based terminal region growing is adopted to extract terminal airways. Extensive experiments were conducted on two internal datasets and three public datasets. Main Results. Compared to the counterparts, the proposed method can achieve a higher branch detected, tree-length detected, branch ratio, and tree-length ratio (ISICDM2021 dataset, 95.19%, 94.89%, 166.45%, and 172.29%; binary airway segmentation dataset, 96.03%, 95.11%, 129.35%, and 137.00%). Ablation experiments show the effectiveness of three proposed solutions. Our method is applied to an in-house chronic obstructive pulmonary disease (COPD) dataset. The measures of branch count, tree length, endpoint count, airway volume, and airway surface area are significantly different between COPD severity stages. Significance. The proposed methods can segment more terminal bronchi and larger length of airway, even some bronchi which are real but missed in the manual annotation can be detected. Potential application significance has been presented in characterizing COPD airway lesions and severity stages.

Background:Chronic obstructive pulmonary disease (COPD) is characterized by a persistent, progressive, and irreversible decline in lung function, primarily driven by persistent airway obstruction and pulmonary inflammation. Cigarette smoking is a major risk factor, as tobacco smoke harms pulmonary epithelial cells, frequently inducing chronic inflammation and ultimately resulting in structural lung lesions. Although pyroptosis is a well-recognized mechanism implicated in cigarette smoke extract (CSE)-induced lung epithelial damage, the specific regulatory roles of early growth response 1 (EGR1) and ubiquitin-specific peptidase 44 (USP44) in this process remain to be fully elucidated. Since inhibiting pyroptosis represents a promising therapeutic strategy for COPD, clarification of the roles of these factors is critically important. Methods:We used a well-established cigarette smoke exposure protocol to establish COPD cellular and animal models. We assessed the extent of pyroptosis in the cellular model using techniques including propidium iodide (PI) staining, Annexin V/PI flow cytometry, and Western blot analysis for cleaved caspase-1 and gasdermin D (GSDMD), identified the pivotal downstream gene EGR1 through transcriptome sequencing, and validated the function of the EGR1/USP44/TNF receptor-associated factor 6 (TRAF6) axis in the model. In the animal model, we observed the therapeutic effect of USP44 knockdown on COPD progression. Results:EGR1 was identified as a key response gene in CSE-stimulated lung epithelial cells. Moreover, our findings indicated that EGR1 plays a crucial role in facilitating CSE-induced pyroptosis. EGR1 transcriptionally enhances the expression of USP44, which subsequently facilitates the deubiquitination and stabilization of TRAF6, thus promoting pyroptosis in lung epithelial cells. The inhibition of either EGR1 or USP44 markedly reduced CSE-induced pyroptosis, underscoring their critical roles in this pathological process. Knocking down USP44 in animal models effectively alleviated COPD-like pathological changes caused by cigarette smoke exposure. Conclusion:We identified the EGR1/USP44/TRAF6 signaling axis implicated in the pyroptosis of lung epithelial cells induced by CSE, indicating that this axis has the potential to serve as a therapeutic target for the treatment of smoking-induced COPD.

BACKGROUND:Chronic obstructive pulmonary disease (COPD) is a prevalent and debilitating respiratory condition that imposes a significant healthcare burden worldwide. Accurate staging of COPD severity is crucial for patient management and treatment planning. METHODS:The retrospective study included 530 hospital patients. A lobe-based radiomics method was proposed to classify COPD severity using computed tomography (CT) images. First, we segmented the lung lobes with a convolutional neural network model. Secondly, the radiomic features of each lung lobe are extracted from CT images, the features of the five lung lobes are merged, and the selection of features is accomplished through the utilization of a variance threshold, t-Test, least absolute shrinkage and selection operator (LASSO). Finally, the COPD severity was classified by a support vector machine (SVM) classifier. RESULTS:104 features were selected for staging COPD according to the Global initiative for chronic Obstructive Lung Disease (GOLD). The SVM classifier showed remarkable performance with an accuracy of 0.63. Moreover, an additional set of 132 features were selected to distinguish between milder (GOLD I + GOLD II) and more severe instances (GOLD III + GOLD IV) of COPD. The accuracy for SVM stood at 0.87. CONCLUSIONS:The proposed method proved that the novel lobe-based radiomics method can significantly contribute to the refinement of COPD severity staging. By combining radiomic features from each lung lobe, it can obtain a more comprehensive and rich set of features and better capture the CT radiomic features of the lung than simply observing the lung as a whole.

AbstractThe efficacy of administering high doses of vitamin D to patients diagnosed with COVID‐19 remains uncertain. We conducted a comprehensive search across multiple databases (PubMed, EMBASE, Cochrane Library, and ISI Web of Science) from inception until August 2022, with no limitations on language, to locate randomized controlled trials (RCTs) that investigated the impact of high‐dose vitamin D supplementation (defined as a single dose of ≥100,000 IU or daily dose of ≥10,000 IU reaching a total dose of ≥100,000 IU) on COVID‐19 patients. Risk ratios (RR) with 95% confidence intervals (CI) and weighted mean differences (WMD) with 95% CI were calculated. Our meta‐analysis included 5 RCTs with a total of 834 patients. High‐dose vitamin D supplementation did not show any significant benefits for mortality (I2 = 0.0%, p = .670; RR 1.092, 95% CI 0.685–1.742, p = .711) or intensive care unit (ICU) admission (I2 = 0.0%, p = .519; RR 0.707, 95% CI 0.454–1.102, p = .126) in COVID‐19 patients compared to the control group. However, it was found to be safe and well‐tolerated (I2 = 0.0%, p = .887; RR 1.218, 95% CI 0.930–1.594, p = .151). Subgroup analysis also showed no benefits in overall mortality, including for patients with vitamin D deficiency (I2 = 0.0%, p = .452; RR 2.441, 95% CI 0.448–13.312, p = .303) or compared to the placebo (I2 = 0.0%, p = .673; RR 1.666, 95% CI 0.711–3.902, p = .240). Our research indicates that there is no evidence to support the efficacy of high‐dose vitamin D supplementation in improving clinical outcomes among individuals with COVID‐19, in line with previous studies focused on contexts including rickets. Considering the limitations of the study, additional research may be required.

Chronic obstructive pulmonary disease (COPD) stands as a significant global health challenge, with its intricate pathophysiological manifestations often demanding advanced diagnostic strategies. The recent applications of artificial intelligence (AI) within the realm of medical imaging, especially in computed tomography, present a promising avenue for transformative changes in COPD diagnosis and management. This review delves deep into the capabilities and advancements of AI, particularly focusing on machine learning and deep learning, and their applications in COPD identification, staging, and imaging phenotypes. Emphasis is laid on the AI-powered insights into emphysema, airway dynamics, and vascular structures. The challenges linked with data intricacies and the integration of AI in the clinical landscape are discussed. Lastly, the review casts a forward-looking perspective, highlighting emerging innovations in AI for COPD imaging and the potential of interdisciplinary collaborations, hinting at a future where AI doesn’t just support but pioneers breakthroughs in COPD care. Through this review, we aim to provide a comprehensive understanding of the current state and future potential of AI in shaping the landscape of COPD diagnosis and management.

背景:研究表明骨髓间充质干细胞源外泌体在多种呼吸系统炎症及疾病损伤模型中表现出强大的修复和再生能力,但在慢性阻塞性肺疾病中的研究较少,且尚未有研究将外泌体雾化吸入应用于慢性阻塞性肺疾病的模型实验中.目的:探讨大鼠骨髓间充质干细胞源外泌体通过雾化吸入途径对慢性阻塞性肺疾病大鼠炎症和肺部损伤的治疗作用,并且明确最适治疗剂量.方法:体外分离培养大鼠骨髓间充质干细胞,并提取鉴定其外泌体.脂多糖联合烟熏28 d建立慢性阻塞性肺疾病大鼠模型,然后给予低剂量(0.5×108 particles/kg)、中剂量(1.0×108 particles/kg)、高剂量(1.5×108 particles/kg)外泌体雾化吸入治疗以及外泌体(1.5×108 particles/kg)尾静脉注射治疗,模型组雾化1 mL PBS,对照组不造模、雾化1 mL PBS.连续雾化或注射治疗5 d,最后一次雾化或注射治疗后的第2天开始检测,使用小动物肺功能仪测试各组肺功能指标,ELISA检测支气管肺泡灌洗液及血清中的白细胞介素1β和肿瘤坏死因子α水平,苏木精-伊红染色和Masson染色从组织学评估肺组织改变.结果 与结论:①骨髓间充质干细胞来源外泌体在透射电镜下显示为椭圆形的双层膜囊泡结构,呈典型的杯口状,粒径分析提示外泌体的峰直径为91.7 nm,占比为97.3％,颗粒浓度为3.3×109 L-1,并且外泌体表面蛋白CD9和CD63高表达;②与尾静脉注射外泌体相比,雾化吸入外泌体显著改善了慢性阻塞性肺疾病大鼠的肺功能、肺组织切片胶原沉积和肺组织病理变化,并且明显降低了支气管肺泡灌洗液和血清中白细胞介素1β和肿瘤坏死因子α水平,且低剂量外泌体治疗效果最为显著;③以上结果表明,雾化吸入骨髓间充质干细胞来源外泌体可以减轻慢性阻塞性肺疾病的炎性损伤,并且最适剂量可能为0.5×108 particles/kg.

Chronic obstructive pulmonary disease (COPD) has a high morbidity and mortality worldwide and is characterized by chronic inflammation and progressive airflow obstruction. At present, no drug treatment has been proved to improve the survival rate of COPD patients. In recent years, exosomes have become a research hotspot due to their involvement in inflammatory response, immune regulation and injury repair. At the same time, studies have found that exosomes are closely related to the occurrence and development of COPD. This review first introduced the biological characteristics components and functions of exosomes, and then lists the relevant studies on exosomes in COPD biomarkers and pathogenesis, and finally clarifies the latest progress of exosomes in clinical diagnosis and treatment of respiratory diseases.

Purpose: Although cigarette smoke exposure is the major risk factor for chronic obstructive pulmonary disease (COPD), the mechanism is not completely understood.The aim of the present study was to investigate whether ACSL4-mediated ferroptosis in lung epithelial cells plays a part in the COPD development process and its association.Patients and Methods: In this study, animal and cell models of COPD were modelled using cigarette smoke extracts (CSEs), and cell viability, lipid ROS, iron ion deposition, and ferroptosis-related markers were measured in lung tissue and lung epithelial cells following CSE exposure.Morphological changes in mitochondria were observed in lung tissue and epithelial cells of the lung by transmission electron microscope.The expression levels of ACSL4 mRNA and protein in lung tissue and epithelial cells were measured by real-time PCR and Western blotting.In addition, animal-interfering lentivirus and cell-interfering RNA against ACSL4 were constructed in this study, ferroptosis in lung tissue and lung epithelial cells after ACSL4 interference was detected, and ACSL4 mRNA and protein expression levels were detected.Results: CSE induced ferroptosis in lung tissues and lung epithelial cells, and the expression levels of ACSL4 were elevated in CSEtreated lung tissues and lung epithelial cells.After ACSL4 interference, the expression of ACSL4 decreased, mitochondrial morphology was restored, and ferroptosis in lung tissues and lung epithelial cells was alleviated.Both respiratory frequency and enhanced pause of COPD mice models decreased after ACSL4 interference.Conclusion: ACSL4-mediated ferroptosis in lung epithelial cells is associated with COPD and positively correlated with ferroptosis in epithelial cells.

阐述慢性阻塞性肺疾病急性加重所致气道菌群生态失调、肺功能陡峭下降及临床过程的级联反应,从而洞悉急性加重频发和严重程度的危害,为制定有效精准的治疗策略提供依据.