BackgroundsThe COVID-19 pandemic and subsequent non-pharmaceutical interventions (NPIs) altered the epidemiological patterns of Mycoplasma pneumoniae (M. pneumoniae) infections. This study aimed to analyze the long-term trends of M. pneumoniae pneumonia (MPP) in children after NPI discontinuation, focusing on epidemiological, clinical and macrolide-resistant characteristics.MethodsA retrospective analysis was conducted on 1342 hospitalized children with MPP from January 2023 to December 2024 in Shenzhen Hospital of Southern Medical University, China. MPP, macrolide-unresponsive MPP (MUMPP), and severe MPP (SMPP) were diagnosed according to predefined criteria. Differences between mutated MPP and MUMPP were investigated, and risk factors for MUMPP, SMPP and mixed infection were assessed.ResultsMPP exhibits a bimodal temporal distribution in 2023-2024, with the first peak occurring in November 2023, and the second smaller peak in August 2024. The macrolide resistance gene positive rate was 86.43% (121/140), but only 64.29% (90/140) were clinically unresponsive to macrolides (P < 0.0001). Risk factors for MUMPP included older age, longer hospital stay, and severe cough. Approximately 25% of MPP cases progressed to SMPP, with younger age, prolonged cough, and higher inflammatory markers being associated with severity. Co-pathogen infections were common, and patients with mixed infections had distinct clinical and laboratory profiles compared to those with pure MPP.ConclusionsThis study highlights the complex epidemiological and clinical landscape of MPP in the post-pandemic era. The discordance between macrolide resistance genes and clinical treatment suggests that macrolides may still be effective in some cases. The identified risk factors and clinical features provide valuable insights for optimizing treatment strategies and managing pediatric MPP in the post-pandemic context.
Immune checkpoint blockade (ICB) therapy continues to face limitations due to tumor resistance linked to suppressed interferon (IFN) signaling. This suppression can be attributed to multiple mechanisms, among which viral pathogens represent a compelling though not yet fully elucidated factor. Here, we demonstrate that exogenous Epstein-Barr virus-encoded EBNA1 drives immunosuppression via enhanced RNA-editing enzyme ADAR1-mediated RNA editing. Comparative tumor model analyses revealed that EBNA1 overexpression reduced CD8+ T-cell infiltration, inhibited IFN responses, polarized macrophages toward the M2 phenotype, and accelerated tumor growth. Mechanistically, EBNA1 forms a trimeric complex with insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) and eukaryotic translation initiation factor 4G1 (EIF4G1), enhancing ADAR1 translation. Elevated ADAR1 further increased A-to-I editing of dsRNA, particularly within SINE elements near IFN-associated genes. This editing masked immunostimulatory signals, impairing RNA sensor activation and blunting IFN pathways. Notably, combining the EBNA1-targeting PROTAC degrader EP-1215 with anti-PD-1 effectively restored IFN signaling, enhanced T-cell infiltration, and suppressed EBNA1+ tumors in humanized mice. This viral exploitation of RNA editing suggests that targeting EBNA1 could be a strategy to convert "cold" tumors into "hot" targets amenable to ICB therapy.
BackgroundPredicting isocitrate dehydrogenase (IDH) status is crucial in glioma management. Conventional MRI (cMRI) has limitations, but the clinical translation of radiomics and machine learning (ML) is often limited by single-center datasets and poor model interpretability.PurposeTo develop and validate an interpretable, multicenter ML model integrating cMRI with functional sequences (DWI and PWI) for predicting IDH status in gliomas.Material and MethodsThis retrospective study included 180 patients from four institutions (150 training, 30 external test). Radiomics features were extracted from cMRI (T1WI, T2WI, FLAIR, T1CE), DWI, and DSC-PWI (CBV maps). After feature selection, multiparametric MRI-based fusion radiomics models were built and compared using three ML algorithms across four segmentation strategies. The optimal model was explained using SHapley Additive exPlanation (SHAP).ResultsThe full-modality model (cMRI + DWI + PWI) with 3Dmodified segmentation achieved the best performance, with area under the curve of 0.840 (training) and 0.810 (external test). Incorporating functional sequences significantly improved prediction over cMRI alone. SHAP analysis identified key predictive features and provided individualized visual explanations for model decisions.ConclusionThe developed ML-SHAP model, integrating conventional and functional MRI, reliably predicts IDH status and demonstrates generalizability across multiple centers. This interpretable tool shows potential for supporting preoperative molecular diagnosis in glioma.
Introduction Diffuse large B-cell lymphoma (DLBCL) is one of the most prevalent hematological malignancies with high mortality. G1 to S phase transition 1 (GSPT1), a key translation termination factor involved in protein synthesis, has been implicated in tumor progression. This study aimed to investigate the effectiveness and underlying mechanisms of the GSPT1 degrader SJ6986 in DLBCL.Methods The TCGA and GTEx datasets were utilized to assess the expression of GSPT1 in DLBCL. The viability and proliferation of DLBCL cells were detected using the Cell Counting Kit-8 (CCK-8) assay. Cell apoptosis was detected via flow cytometry. The expression of GSPT1 was evaluated using qRT-PCR and Western blot. Xenograft mouse models were employed to explore the in vivo therapeutic potential of SJ6986. RNA sequencing was used to explore the potential mechanism of SJ6986 in DLBCL.Results This study first identified that GSPT1 is highly expressed in DLBCL and demonstrated that its genetic knockdown significantly suppressed the activity of DLBCL cells. Furthermore, it was found that SJ6986 effectively reduced the proliferation of DLBCL cells, induced cell apoptosis, and inhibited tumor growth in vivo without significant toxicity. Mechanistically, RNA sequencing analysis showed that the endoplasmic reticulum (ER) stress was significantly triggered following SJ6986 treatment, and SJ6986 was found to activate the ER stress-related apoptosis in DLBCL cells.Discussion Our findings suggested that SJ6986 exerts its anti-tumor effects in DLBCL and activates the ER stress-related apoptotic signaling. These results supported SJ6986 as a viable anticancer drug for treating DLBCL. Future studies should further investigate its mechanism and evaluate its clinical application value.Conclusions This study validated the efficacy and safety of SJ6986 in treating DLBCL and discovered its role in inducing ER stress and subsequent apoptosis, offering a promising therapeutic option for DLBCL patients.
A standardized static-guided framework integrating CBCT and intraoral scanning provides predictable, minimally invasive management for diverse intracanal obstructions. This unified digital workflow ensures precise root canal localisation in severe obliteration and conservative retrieval of fractured fiber or ultra-hard posterior zirconia posts without iatrogenic complications.
