Purpose: Osimertinib, established as the frontline treatment for advanced non-small cell lung cancer (NSCLC), can effectively prolong progression-free survival. However, it faces the problem of reduced treatment persistence due to acquired drug resistance. Meanwhile, tumor hypoxia is also a key driver of drug resistance. This study proposes a hybrid protein oxygen nanocarrier combined with osimertinib and ginsenoside Rg3 to address the drug resistance issue of NSCLC through multiple mechanisms. Methods: A hybrid protein-oxygen multifunctional nanoplatform (OG@HPO) was engineered by co-encapsulating OSI and GRg3 within oxygen-rich protein matrices. Initial confirmed the synthesis of OG@HPO and characterized its drug/oxygen release. Subsequent in vitro assays verified OG@HPO’s tumoricidal activity and elucidated its mechanistic. Finally, in vivo evaluations validated the nanoplatform’s tumor targeting and anticancer efficacy. Results: Preliminary experiments confirmed successful OG@HPO preparation and validated its drug/oxygen release capacities. In vitro assays demonstrated the potent cytotoxic effects of OG@HPO against H1975 OR cells. In vivo biodistribution studies revealed excellent tumor-targeting of OG@HPO in H1975 OR xenograft mice. Subsequent 18 days therapeutic monitoring showed superior antitumor efficacy accompanied and favorable biosafety profile of OG@HPO. More importantly, in vitro and in vivo studies demonstrated that OG@HPO effectively oxygenate tumor microenvironment, thereby inhibiting hypoxia-driven HIF-1α expression and simultaneously inhibiting the vascular endothelial growth factor (VEGF)/EGFR pathway. Conclusion: OG@HPO represents an innovative multifunctional nanoplatform integrating tumor-targeting, multi-drug delivery, and hypoxia modulation capabilities. By effectively alleviating tumor hypoxia, it achieves multiple inhibition of HIF-1α and EGFR/VEGF pathways. Ultimately, enhances NSCLC sensitivity to osimertinib, thereby reversing acquired resistance. Overall, OG@HPO is regarded as a promising strategy to overcome osimertinib resistance providing a clinically translatable solution.

Midnolin (MIDN) is a protein coding gene that promotes the destruction of transcription factors encoded by immediate‐early genes. Previous research has found that those immediate‐early genes are involved in tumour progression. However, the role of MIDN is still not clearly identified in human cancers. With the help of the TCGA, GTEx, and HPA databases, we revealed that the expression of MIDN was disordered in cancers. MIDN is a potential prognostic biomarker in liver cancer and bladder cancer. Prognostic analysis indicates that the expression level of MIDN gains survival benefits or promotes progression in multiple tumours. After analysing the sequencing results of TCGA via Gene Set Enrichment Analysis (GSEA), results suggested the regulative role of MIDN in cell proliferation and tumour immunity. Single cell sequencing results revealed that MIDN is highly expressed in several tumour tissues and also expressed in immune cells. With the help of the ESTIMATE, TIMER, and CIBERSORT databases, we analysed the immune score, immune cell infiltration, and anti‐cancer immunity cycle depending on the expression of MIDN. Results showed that low MIDN levels are tightly associated with high CD4 + T and NK cell infiltration. Furthermore, mutations of MIDN in cancers were significantly associated with immune cell infiltration. This study presents a robust link between the expression of MIDN and tumour progression across multiple cancer types. The MIDN/CTNNB1/MMP9 axis promotes liver cancer progression via inducing a suppressive tumour immune microenvironment.

Background Lactylation, as a novel type of post-translational protein modification, is closely associated with key processes such as cellular metabolism, the tumor immune microenvironment, tumor proliferation, and metastasis. However, the specific relationship between lactylation and radiation resistance in non-small cell lung cancer (NSCLC) has not yet been fully explored. This study aims to investigate the potential relationship between lactylation and radiation resistance in lung cancer using tumor databases, providing new molecular targets for individualized radiotherapy strategies for NSCLC. Methods Using the Cancer Genome Atlas (TCGA) database and the GSE197236 dataset on non-small cell lung cancer, the differential expression of lactate-associated radiation resistance genes (LARRGs) was analyzed. Based on the lactylation-radiation resistance model, relevant risk scores were calculated to identify high-lactylation and low-lactylation subtypes. A gene signature model based on LARRGs was developed and validated, and it was evaluated using training and validation cohorts. Additionally, immune cell infiltration and drug response were analyzed. Results A total of 1865 differentially expressed genes (DEGs) were identified, showing differences between radiation resistant non-small cell lung cancer (NSCLC) and normal tissues. Among these genes, 23 lactate-related differentially expressed genes (LR-DEGs) were ultimately identified through an intersection analysis of the DEGs and LARRGs. Using univariate and multivariate Cox regression analysis for further screening, three key lactate-related biomarkers were identified: RRM2B, COL4A1, and CD46. It was found that patients with high-LARRGs exhibited stronger characteristics of immune exclusion, immune exhaustion, and immunosuppression in the tumor microenvironment (TME). Additionally, in the scRNA-seq, different cell types are distinctly distributed in the reduced-dimensional space, reflecting the significant heterogeneity of the TME. Furthermore, the gene sets of fibroblasts and endothelial cells show the highest scores, suggesting that under high lactate conditions, enhanced gene expression activity in fibroblasts and endothelial cells may promote tumor radioresistance. Analysis of significantly correlated signaling pathways in the high-LARRGs indicates that metabolic reprogramming and immunosuppression may promote radioresistance through lactate-mediated inhibition of T cell function and macrophage polarization, which highlights the role of the TME in radiotherapy and suggests that targeting immune evasion mechanisms may be a key strategy to overcome radioresistance. Conclusions LARRGs are crucial in the context of radiation resistant NSCLC, as they significantly influence tumor growth, the immune microenvironment, and drug response. This signature of LARRGs has the potential to serve as a prognostic biomarker and may also represent a promising therapeutic target for patients facing radiation resistant NSCLC. Graphical abstract

Iatrogenic perforation of the left atrium and aorta during transseptal puncture (TSP) is a rare but potentially life‐threatening complication. This report presents the case of an elderly male patient with a 20‐year history of atrial fibrillation who experienced this complication during a scheduled left atrial appendage closure procedure. During the procedure, the sheath inadvertently penetrated the left atrial wall and mediastinal tissues, resulting in perforation of the descending aorta. To prevent hemorrhage and secondary injury, we successfully repaired the defects by simultaneously deploying two ductus arteriosus occluders through the original access tract. Immediate post‐procedural and 1‐month follow‐up assessments confirmed stable device position with no residual shunt, pericardial effusion, or thromboembolic complications. This case represents the first documented instance of concurrent closure of both left atrial and descending aortic perforations using ductus arteriosus occluders. It highlights the critical importance of prompt intervention for complex cardiac complications and demonstrates the feasibility of dual‐chamber repair using occluder devices.

Purpose: To prospectively investigate the association between patent foramen ovale (PFO), detected via agitated saline contrast echocardiography (ASCE), and anxiety using a deep learning approach. Materials and methods: This prospective study consecutively enrolled 161 participants between July 15, 2025 and October 31, 2025. Participants were stratified into ASCE-negative (n=58) and ASCE-positive (n=103) groups based on the examination results. All participants underwent ASCE and anxiety assessment using the Self-Rating Anxiety Scale (SAS). An artificial intelligence model was developed using a 10-fold cross-validation approach on the 103 ASCE-positive videos to predict anxiety scores. The primary endpoint was the association between PFO and anxiety, while the deep learning model was evaluated as a secondary/exploratory endpoint. Statistical analyses, including logistic regression, were performed with statistical significance set at p<0.05. Results: Compared to the ASCE-negative group, the ASCE-positive group exhibited significantly higher anxiety levels (SAS score: 45.0 vs. 38.0, p<0.001) and a higher prevalence of anxiety (32.0% vs. 5.2%, p<0.001). Logistic regression identified a strong association between ASCE-positive status and anxiety (adjusted odds ratio=8.64, p<0.001), with no clear dose-dependent relationship across shunt grades. The imaging-only deep learning model achieved a mean absolute error (MAE) of 5.76 ± 0.12 and an R² of 0.46 ± 0.03 across cross-validation folds. After incorporating clinical and sociodemographic confounders, the model’s performance improved to an MAE of 5.15 ± 0.10 and an R² of 0.59 ± 0.02. Conclusion: This prospective study confirms a significant association between PFO and anxiety and demonstrates the feasibility of using ASCE-based deep learning models to predict anxiety risk, although clinical application requires external validation.