Background. Pulmonary alveolar proteinosis (PAP) is a rare disorder which is characterized by the accumulation of excessive surfactant lipids and proteins in alveolar macrophages and alveoli. Oral statin therapy has been reported to be a novel therapy for PAP with hypercholesterolemia. We aimed to evaluate the safety and efficacy of oral statin therapy for PAP without hypercholesterolemia. Methods. In a prospective real‐world observational study, 47 PAP patients without hypercholesterolemia were screened. Oral statin was initiated as therapy for these PAP patients with 12 months of follow‐up. Results. Forty PAP patients completed the study. 26 (65%) of 40 PAP patients responded to statin therapy according to the study criteria. Partial pressure of arterial oxygen (PaO2) and percentage of diffusion capacity predicted (DLCO%) significantly increased while disease severity score (DSS) and radiographic abnormalities decreased after 12 months of statin therapy (all p < 0.05). The factors associated with response were higher levels of granulocyte‐macrophage colony‐stimulating factor (GM‐CSF) antibody and baseline total cholesterol/high‐density lipoprotein cholesterol (TC/HDL) (p = 0.015 and p = 0.035, respectively). The area under the receiver operating characteristic curve (AUROC) of dose of atorvastatin for predicting the response to statin therapy for PAP was 0.859 (95% CI: 0.738‐0.979, p < 0.001). The cutoff dose of atorvastatin was 67.5 mg daily with their corresponding specificity (64.3%) and sensitivity (96.2%). No severe side effects were observed during the study. Conclusions. In PAP patients without hypercholesterolemia, statin therapy resulted in improvements in arterial blood gas (ABG) measurement, pulmonary function, and radiographic assessment.

Ferroptosis is a newly form of regulated cell death, which has attracted great attention for tumor therapy. Herein, we prepared nanoscale coordination polymer Fe-NQA particles to deliver iron and NQA (vitamin K₃ derivative) into tumor cells, which synergistically promoted ferroptotic therapy for inhibiting tumor growth, preventing metastasis, and overcoming radioresistance.

Background: Extracellular volume (ECV) fraction has been used in cardiovascular diseases, pancreatic fibrosis, and hepatic fibrosis. The diagnostic value of ECV for focal lung lesions remains to be explored. The aim of this study was to evaluate the feasibility of ECV derived from a dual-layer detector computed tomography (DLCT) to differentiate lung cancer (LC) from benign lung lesions (BLLs). Methods: Retrospectively, 128 consecutive patients with pathologically confirmed LC (n=86) or BLLs (n=42) were included. Conventional computed tomography (CT) characteristics and spectral CT parameters were assessed. All patients’ hematocrits were measured to correct contrast volume distributions in blood while calculating ECV. After performing logistic regression analysis, a conventional CT-based model (Model A), DLCT-based model (Model B), combined diagnostic models (Model C), and an ECV-based model (Model D) were developed. The diagnostic effectiveness of each model was examined using the receiver operating characteristic (ROC) curve and their corresponding 95% confidence intervals (CIs). The area under the curve (AUC) of each model was compared using the DeLong test. Results: Certain conventional CT features (such as lesion size, lobulation, spiculation, pleural indentation, and enlarged lymph nodes) differed significantly between the LC and BLL groups (all P<0.05). Statistical differences were found in the following DLCT parameters (all P0.05). Conclusions: The ECV derived from DLCT may be a potential new method to differentiate LC from BLLs, broadening the scope of ECV in clinical research.

Objectives Risk prediction for patients with polymyositis/dermatomyositis-associated interstitial lung disease (PM/DM-ILD) is challenging due to heterogeneity in the disease course. We aimed to develop a mortality risk prediction model for PM/DM-ILD. Methods This prognostic study analysed patients with PM/DM-ILD admitted to Nanjing Drum Hospital from 2016 to 2021. The primary outcome was mortality within 1 year. We used a least absolute shrinkage and selection operator (LASSO) logistic regression model to identify predictive laboratory indicators. These indicators were used to create a laboratory risk score, and we developed a mortality risk prediction model by incorporating clinical factors. The evaluation of model performance encompassed discrimination, calibration, clinical utility and practical application for risk prediction and prognosis. Results Overall, 418 patients with PM/DM-ILD were enrolled and randomly divided into development (n=282) and validation (n=136) cohorts. LASSO logistic regression identified four optimal features in the development cohort, forming a laboratory risk score: C reactive protein, lactate dehydrogenase, CD3+CD4+ T cell counts and PO2/FiO2. The final prediction model integrated age, arthralgia, anti-melanoma differentiation-associated gene 5 antibody status, high-resolution CT pattern and the laboratory risk score. The prediction model exhibited robust discrimination (area under the receiver operating characteristic: 0.869, 95% CI 0.811 to 0.910), excellent calibration and valuable clinical utility. Patients were categorised into three risk groups with distinct mortality rates. The internal validation, sensitivity analyses and comparative assessments against previous models further confirmed the robustness of the prediction model. Conclusions We developed and validated an evidence-based mortality risk prediction model with simple, readily accessible clinical variables in patients with PM/DM-ILD, which may inform clinical decision-making.

Background: The necessity of localization of pulmonary nodules lies in ensuring the ability to locate the nodule quickly and accurately during surgery, thereby improving the success rate of the operation. The accuracy and risk of preoperative localization of pulmonary nodules need further exploration. Therefore, the purpose of this study was to investigate the factors of accuracy and safety of computed tomography (CT)-guided localization of pulmonary nodules using a flexible wire hook positioner. Methods: In this retrospective cross-sectional analysis, 281 patients with a single pulmonary nodule underwent video-assisted thoracoscopic surgery (VATS) following localization with a soft hook-wire guided by CT scan from January 2021 to July 2022 at Nanjing Drum Tower Hospital. The patients underwent VATS to remove pulmonary nodules within 24 hours after localization. The demographic, pulmonary nodule, and technical factors were analyzed retrospectively. Univariate and multivariate analysis were used to analyze the identified factors that influence pulmonary nodule localization accuracy and complications. Results: Localization was successfully performed in 280 patients, with only 1 patient being excluded due to a displaced positioner and the hook wire failing to enter the lung parenchyma as a result of pneumothorax. Out of the total cases, 191 (68.2%) were accurately positioned in group G0, whereas 89 cases (31.7%) were inaccurately positioned in group G1. Hemorrhage and self-limited hemoptysis were observed in 64 patients (22.8%), whereas pneumothorax was observed in 84 patients (29.9%). There were no serious complications such as air embolism or death. The accuracy of localization was found to be influenced by both the depth of pulmonary nodules [odds ratio (OR) =22.610, 95% confidence interval (CI): 10.351–49.391, P=0.001] and the depth of the needle used (OR =0.322, 95% CI: 0.136–0.765, P=0.010). Additionally, postoperative hemorrhage was found to be affected by several important factors, including the diameter (P=0.036) and depth of the nodule (P=0.011), as well as the thickness of the chest wall (P=0.043) and the depth of the needle used (P=0.005). Conclusions: The CT-guided flexible wire hook positioner has been found to be a safe and effective device for locating pulmonary nodules. The depth of pulmonary nodules and needle penetration are key factors affecting the accuracy of lung nodule localization under CT guidance and are important factors affecting postoperative bleeding.