Background:Pulmonary rehabilitation (PR) is a cornerstone of chronic obstructive pulmonary disease (COPD) management; however, access to traditional center-based PR (CBPR) remains limited. Digital and remote models, collectively termed pulmonary telerehabilitation (Tele-PR), have increasingly been used, but their heterogeneity in technology use, supervision, and interaction mode may influence effectiveness and sustainability. Objective:This systematic review and meta-analysis aimed to compare the effectiveness and adherence of Tele-PR with those of CBPR in adults with COPD while systematically evaluating the impacts of supervision intensity and delivery models on key clinical outcomes. Methods:This review followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 and PRISMA-S (Preferred Reporting Items for Systematic reviews and Meta-Analyses literature search extension) guidelines. PubMed, Embase, the Cochrane Library, and the Web of Science were searched from inception to December 10, 2025, to identify randomized controlled trials comparing Tele-PR or home-based PR (HBPR) with CBPR in adults with COPD. Random effects meta-analyses were conducted using the Hartung-Knapp-Sidik-Jonkman method. Between-study heterogeneity was assessed using τ², I², and 95% prediction intervals. Risk of bias was evaluated with the Cochrane Risk of Bias 2 tool, and certainty of evidence was graded using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach. Results:Seventeen randomized controlled trials involving 1658 participants were included. After intervention, Tele-PR and CBPR showed comparable average effects on exercise capacity by 6-minute walk distance (k=9; n=950, 57.3%; mean difference -5.37 m, 95% CI -15.68 to 4.95; P=.26; τ²=103.97; I²=28.2%; 95% prediction intervals=-32.73 to 22.27). Although pooled effects were not statistically significant, substantial heterogeneity was observed across remote delivery models. Subgroup analyses linked digitally supported, synchronously supervised Tele-PR to less between-study variance across several outcomes, indicating greater consistency in treatment effects across different settings while revealing that low-technology HBPR yielded more variable outcomes, particularly in symptom burden. At long-term follow-up (≥6 mo), between-group differences in functional and symptom outcomes diminished, and short-term gains in exercise capacity did not consistently translate into increased daily physical activity. Certainty of evidence ranged from moderate to very low, mainly downgraded for performance bias, inconsistency across intervention models, and imprecision. Conclusions:Tele-PR may achieve short-term clinical outcomes comparable to CBPR. Distinct from prior reviews, we stratified remote programs by delivery models and supervision, identifying digitally supported Tele-PR and low-technology HBPR as 2 clinically distinct paradigms with differing consistency of effects. We further propose a structured "supervision gradient" to interpret model-dependent variability in effects across Tele-PR approaches, providing a context-sensitive framework for evidence-informed, model-specific implementation. Future remote rehabilitation should integrate real-time professional supervision and long-term behavioral maintenance to sustain benefits. Tele-PR may be particularly valuable for expanding PR access, while CBPR remains essential for patients requiring close in-person supervision or complex multidisciplinary care.

Background:Asthma affects approximately 334 million people worldwide. Accumulating evidence indicates that gut dysbiosis exacerbates airway inflammation through the gut-lung axis. In the present study, using an OVA-induced murine model of asthma, we investigated whether Huanglong Zhixiao Formula (HLZXF) restores gut lung homeostasis by reshaping the gut microbiota and enhancing intestinal barrier function, thereby attenuating pulmonary pathological changes. Methods:Female BALB/c mice were randomly assigned to three groups (n = 15 per group): Control (C), Asthma Model (MX), and HLZXF-treated (ZG) groups. Asthma was induced by OVA sensitization and challenge over a 6-week period. The ZG group received daily oral gavage of HLZXF, 1 h prior to each OVA challenge. Fecal samples were collected for metagenomic sequencing. Lung and intestinal tissues were excised for HE and IHC staining of tight junction proteins, including Claudin, Occludin, and ZO-1. Alpha and beta diversity analyses were conducted to evaluate the composition and structure of the gut microbiota. Results:We analyzed the structure of the gut microbiota, detected the expression levels of intestinal barrier-related proteins, and assessed inflammatory injury in the lungs and intestines. Results demonstrated that HLZXF significantly ameliorated gut microbiota dysbiosis in asthmatic mice, as evidenced by the significant enrichment of Heminiphilus faecis and Paramuribaculum intestinale. Additionally, certain fungal taxa, such as Piromyces finnis and Rhizopus arrhizus, were significantly enriched in the ZG group. HLZXF also significantly upregulated the expression levels of the tight junction proteins Claudin, Occludin, and ZO-1 in intestinal tissues, thereby promoting the repair of the intestinal mucosal barrier. Furthermore, HLZXF significantly attenuated inflammatory cell infiltration and tissue injury in the lungs and intestines, alleviated alveolar septal thickening, and enhanced the integrity of the intestinal mucosal barrier. Conclusion:This study elucidates the potential therapeutic mechanisms of HLZXF in the treatment of asthma from the perspective of gut microbiota and intestinal barrier function. It highlights that HLZXF can attenuate pulmonary inflammation by regulating the balance of gut microbiota and enhancing intestinal barrier function.

Early diagnosis and treatment of lung cancer are critical for improving patient survival rates and prognosis. The diagnosis of lung cancer relies on multimodal features, yet the performance of single models remains limited. Current studies have insufficiently explored multimodal feature fusion strategies and the intrinsic decision-making mechanisms of models, restricting their clinical application. To evaluate the performance improvement of a Stacking ensemble algorithm integrating radiological characteristics, clinical data, and laboratory indicators in diagnosing benign and malignant pulmonary occupying lesions, and to interpret the model's decision-making mechanism using the SHAP method, thereby providing a novel strategy for clinical intelligent auxiliary diagnosis. This study retrospectively enrolled 618 pulmonary space-occupying lesions from 595 patients with pathologically confirmed Pulmonary Space-Occupying Lesions. Participants were divided into a Training set and Test Set at a 7:3 ratio, with a separate independent External validation set (126 lesions from 118 patients) established. Employed an enhanced multi-algorithm voting integration strategy (Boruta, stability selection, and LASSO regression) to perform feature screening. Eleven fundamental classification models were constructed using selected stable features (including AdaBoost, ExtraTrees, KNN, Logistic Regression, CatBoost, RF, SVM, MLP, GBM, LightGBM, and XGBoost) and optimized through fusion with the Stacking algorithm. Model efficacy was assessed using the receiver operating characteristic curve (AUC), Brier score, and clinical decision curve (DCA), with the SHAP attribution method employed to analyze feature importance and model ensemble weights. In the test set, the Stacking-XGBoost model demonstrated optimal comprehensive diagnostic performance (AUC 0.83, 95% CI 0.76–0.89), with false-negative cases decreasing from 17 to 13 compared to its XGBoost base model (AUC = 0.80, 95% CI 0.73–0.87). The learning curve confirmed model convergence after the sample size reached 400 cases. The calibration curve demonstrated high concordance between select models predicted probabilities and actual incidence (XGBoost Brier = 0.1641; Stacking-RF Brier = 0.1504), though the Hosmer–Lemeshow test (p < 0.01) indicated some degree of calibration deviation. Decision curve analysis indicated clinical net benefit for the core model across broad threshold ranges. External validation demonstrated variable performance across models, with the base ExtraTrees model achieving the highest AUC of 0.78 (95% CI 0.69–0.86), followed by the Stacking-GBM ensemble with an AUC of 0.76 (95% CI 0.67–0.84). Ablation analysis confirmed that multimodal fusion significantly outperformed the imaging-only model (AUC 0.802 vs. 0.739, p = 0.019). SHAP interpretation was performed at three levels: model-level contribution identified KNN and XGBoost as the highest-weighted base models in the meta-model.; ensemble input contribution summarized LUNG-RADS, Pleural Contact Area, Surface Area, and Age as common core features across models, with CEA showing in specific base models (e.g., XGBoost); raw feature contribution confirmed that LUNG-RADS ranked first in global feature importance, while imaging-based high-risk indicators (e.g., Pleural Contact Area) and laboratory tumor markers (CYFRA21-1) demonstrated consistent positive decision contributions across all base models. The Stacking ensemble framework based on multi-modal features (especially Stacking-XGBoost) demonstrated a positive trend in reducing missed diagnosis risks for malignant lesions, while improving diagnostic accuracy and generalization capability. Combined with SHAP's multi-level interpretation mechanisms, this synergistic pattern integrating imaging and serum indicators provides a referable clinical paradigm for developing interpretable AI-assisted diagnostic systems.

Acute exacerbation of chronic obstructive pulmonary disease(AECOPD) constitutes the acute deterioration phase of chronic obstructive pulmonary disease(COPD), typified by an abrupt intensification of respiratory symptomatology, encompassing exacerbated dyspnea, heightened cough severity, augmented sputum volume, and pronounced respiratory insufficiency. Systemic inflammatory cascades serve as a cardinal etiological driver of AECOPD, emanating from multifaceted host-pathogen interactions involving viral, bacterial, or polymicrobial infections, superimposed upon environmental modulators that collectively precipitate accelerated pathological progression. These contributory elements markedly escalate the inflammatory milieu within the small airways, surmounting endogenous anti-inflammatory safeguards, thereby precipitating airway epithelial barrier disruption, microvascular dilation, edema, and prolific immune cell infiltration, which in turn perpetuate an inflammatory amplification loop. Such mechanisms converge to synergistically impair pulmonary function and extend durations of inpatient care. Current therapeutic paradigms for AECOPD predominantly incorporate bronchodilators, anti-inflammatory pharmacotherapies, supplemental oxygen administration, and mechanical ventilatory support. Notwithstanding these interventions, persistent limitations include the adverse sequelae of protracted systemic glucocorticoid therapy, escalating antimicrobial resistance profiles, and ventilator-associated morbidities. Ergo, there exists an imperative to investigate novel therapeutic modalities that confer enhanced safety and efficacy. TCM proffers salient therapeutic merits via its multi-target and multi-pathway pharmacodynamics, facilitating regulation of pivotal signaling pathways, including the Toll-like receptor 4(TLR4)/nuclear factor-κB(NF-κB), NF-κB/NOD-like receptor pyrin domain containing 3(NLRP3), phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt), Janus kinase(JAK)/signal transducer and activator of transcription(STAT), and neutrophil elastase(NE)/mucin 5AC(MUC5AC) pathways. Through such regulatory interventions, TCM efficaciously attenuates inflammatory response, ameliorates symptomatic burden, and diminishes the incidence of AECOPD. The present investigation endeavors to delineate systematically the extant advancements in TCM-mediated regulation of inflammation-related signaling pathways within the context of AECOPD, thereby furnishing a robust theoretical framework and empirical guidance for optimized clinical interventions and pharmaceutical innovations in AECOPD management.

Drug-resistant bacterial infections have emerged as a critical global public health challenge, characterized by high mortality rates, substantial healthcare costs, and rapid transmission characteristics that pose a severe test to modern medical practice. Traditional Chinese medicine(TCM), with its comprehensive theoretical framework and extensive clinical experience, demonstrates unique advantages in infectious disease management. Particularly in addressing drug-resistant bacterial infections, TCM has achieved remarkable progress by integrating its fundamental principle of &quot;strengthening vital Qi while eliminating pathogens&quot; with contemporary research methodologies. This review systematically examines the current epidemiological landscape of antimicrobial resistance, elucidates the theoretical foundations of TCM intervention, and analyzes its therapeutic advantages and mechanistic actions. By synthesizing these perspectives, we aim to provide novel insights and approaches for combating drug-resistant bacterial infections.

Objective: This study aims to investigate the potential of Bu-Fei Yi-Shen Formula (BYF) in ameliorating airway epithelial barrier dysfunction in chronic obstructive pulmonary disease (COPD) and to elucidate the underlying mechanisms. Methods: By establishing both in vivo and in vitro models of COPD, this study examined lung function, lung tissue pathology, inflammatory cytokines levels, cellular apoptosis rate, oxidative stress intensity, and TEER. Concurrently, it quantified the expression levels of proteins relevant to apical junctions, apoptosis, and the Nrf2 signaling pathway. These exhaustive analyses were undertaken to decipher the intricate mechanisms by which BYF ameliorates the disruption of airway epithelial barrier integrity in COPD. Results: BYF significantly improved lung function, attenuated lung tissue pathological damage, reduced inflammatory cytokines levels, inhibited cellular apoptosis, upregulated the expression of apical junctional proteins, and alleviated oxidative stress injury in a COPD rat model. In vitro, BYF restored the CSE-induced decreases in TEER values and apical junctional protein expression in BEAS-2B cells, while reducing airway epithelial cell apoptosis apoptosis and oxidative stress injury. Furthermore, BYF counteracted the inhibitory effects of CSE on Nrf2, facilitating the expression of HO-1, a downstream protein of Nrf2. The addition of ML385 exacerbated the apoptosis, oxidative stress, and barrier dysfunction induced by CSE; however, the co-administration of ML385 and BYF reversed the inhibitory effects of ML385. Conclusion: These findings underscore that BYF ameliorates airway epithelial barrier dysfunction in COPD by activating the Nrf2/ HO-1 signaling pathway.

PM2.5 exposure is harmful to health. The related mechanisms by which PM2.5 induced acute lung injury remain to be investigated. Herein, we found PM2.5 compromised lung function, disrupted lung tissue histology, and elevated inflammatory cytokines. Transcriptome sequencing data showed that ferroptosis-mediated oxidative stress plays a critical role in both cellular and murine models. In airway epithelial cells, a dose-dependent decrease in junction proteins was observed following PM2.5 induction, which was subsequently ameliorated by the ferroptosis inhibitor Fer-1 treatment. In alveolar macrophages, continuous exposure to PM2.5 for 6 h resulted in diminished phagocytic capacity, which was also reversed upon the addition of Fer-1. Moreover, network analysis identified FTH1 as a central node in regulating PM2.5-induced lung injury. These findings suggest that enhanced pulmonary uptake and retention of PM2.5 correlate with more severe lung injuries, with the number of barriers encountered by PM2.5 during its transit potentially playing a crucial role. The underlying mechanism is partially through disrupting pulmonary barriers via promoting FTH1-mediated ferroptosis.

To evaluate the protective effect of Bufei Yishen Formula (BYF) against cigarette smoke extract (CSE)-induced injuries in human bronchial epithelial BEAS-2B cells and explore the underlying mechanism. BEAS-2B cells exposed to CSE were treated with normal rat serum, BYF-medicated rat serum at low or high doses, pyrrolidine dithiocarbamate (PDTC, a NF-κB inhibitor), PDTC combined with high-dose BYF-medicated serum, or S-carbomethyloysteine (S-CMC, as the positive control). CCK-8 assay was used to determine the optimal concentration and treatment time of CSE, BYF-medicated serum and S-CMC. The treated cells were examined for inflammatory factor levels in the supernatant and cellular expressions of MUC5AC and MUC5B using ELISA, cell ultrastructural changes with transmission electron microscopy, and cell apoptosis rate using flow cytometry. The expression levels of TLR4/NF‑κB pathway-associated mRNAs and proteins were determined by qRT-PCR and Western blotting. CSE exposure significantly increased secretions of IL-1β, IL-6 and TNF-α, mRNA and protein expressions of MUC5AC and MUC5B, and early and total apoptosis rates in BEAS-2B cells, where the presence of apoptotic bodies was detected. CSE also significantly enhanced the mRNA and protein expressions of TLR4, I-κB, and NF-κB and reduced mRNA and protein expressions of AQP5. Treatments of the CSE-exposed cells with BYF-medicated serum, PDTC and S-CMC all significantly lowered inflammatory factor levels, MUC5AC and MUC5B expressions, and early and total cell apoptosis rates, and partly reversed the changes in cellular ultrastructure and mRNA and protein expressions of the TLR4/NF-κB pathway, and the effects were the most conspicuous following the combined treatment with high-dose BYF-medicated serum and PDTC. BYF can inhibit cell apoptosis, inflammation and mucus hypersecretion in CSE-induced BEAS-2B cells by inhibiting the TLR4/NF-κB signaling pathway.

Objective This study was aimed to explore the prolonged therapeutic profile and underlying mechanisms of Yiqi Zishen Formula(YZF)in chronic obstructive pulmonary disease(COPD)management. Methods A COPD rat model was established through exposure to tobacco smoke and Klebsiella pneumoniae infections from weeks 1 to 8,followed by treatment with YZF from weeks 9 to 20.No treatment was administered from weeks 21 to 31.At week 32,all rats were euthanized,and lung tissue samples and blood specimens were collected for subsequent analyses.Then,comprehensive multiomics profiling-encompassing transcrip-tomics,proteomics,and metabolomics-was conducted to identify differentially expressed molecules in lung tissues and elucidate the underlying molecular mechanisms. Results By week 32,sustained therapeutic efficacy became apparent,characterized by diminished inflammatory cytokine expression,mitigation of protease-antiprotease dysre-gulation,and reduced collagen deposition.These differentially expressed molecules were predominantly enriched in pathways related to oxidoreductase activity,antioxidant homeostasis,focal adhesion,tight junction formation,adherens junction dynamics,and lipid metabolism regulation.Integrative analysis of predicted targets,transcriptomic,proteomic,and metabolomic datasets revealed that differentially expressed molecules in YZF-treated rats and YZF-targeted proteins collectively participated in lipid metabolism,inflammatory responses,oxidative stress,and focal adhesion pathways. Conclusion YZF provides sustained therapeutic benefits in COPD rat models,poten-tially through systemic regulation of lipid metabolism,inflammatory responses,oxidative stress,and focal adhesion pathways.

Gleditsia sinensis Fructus (GSF) exhibits anti-cancer activity and is effective against lung adenocarcinoma (LUAD). However, its underlying mechanisms remain unclear. In this study, the potential chemical components, targets, and pathways of GSF in treating LUAD were investigated using UHPLC-HRMS combined with network pharmacology analysis. These findings were subsequently verified via molecular docking, molecular dynamics simulation, and in vitro cell experiments. The results showed that a total of 61 components targeting 192 LUAD-related genes were identified, and 177 candidate targets of GSF against LUAD were obtained, among which AKT1, SRC, EGFR, IL6, and TNF may be the core targets. Enrichment analysis revealed that the mechanisms were related to various cancer-related pathways, particularly the PI3K-AKT signaling pathway. Molecular docking demonstrated that the active components of GSF, particularly luteolin, exhibited excellent binding affinity to the top five core targets. Molecular dynamics simulation results showed a similar trend. Therefore, we identified luteolin as the primary active component of GSF. The cell experiments revealed that luteolin significantly inhibited cell growth and proliferation and promoted the apoptosis of A549 cells, exhibiting effects similar to those of cisplatin. In addition, luteolin significantly upregulated the expression of Bax and cleaved-caspase3 and decreased the expression of P-AKT and BCL2. Our results demonstrate that GSF can exert anti-LUAD effects through multi-components, multi-targets, and multi-pathways. Luteolin, one of the main active components of GSF, suppressed proliferation and induced apoptosis in A549 cells, possibly through inhibiting the AKT signaling pathway.

BACKGROUND:Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) significantly accelerate disease progression and substantially increase mortality risk. The risk window of AECOPD (AECOPDRW) represents a time between acute exacerbation and recovery to a stable stage. Chinese medicine (CM) has shown significant therapeutic efficacy in COPD but CM treatment for AECOPDRW has not been validated by high-quality clinical studies. PURPOSE:To assess the clinical effect of CM syndrome differentiation treatment for patients with AECOPDRW. STUDY DESIGN:A multicenter, randomized, double-blind, placebo-controlled parallel trial. METHODS:336 eligible participants were included to the study. Both groups were based on the conventional treatment as the baseline therapy. The experimental group was administered Chinese herbal medicine granules based on CM syndrome differentiation, whereas the control group received a placebo in the form of Chinese herbal medicine granules. The intervention course lasted for 8-week, while the follow-up for 26-week. Primary outcomes were incidences of acute exacerbation and COPD Assessment Test (CAT) scores recorded during AECOPDRW. Secondary outcomes were the timing of the first acute exacerbation, incidence of exacerbations, acute exacerbation readmission rate, severity of exacerbation, and CAT scores during follow-up, pulmonary function, mMRC scale, clinical symptom scale, and the quality of life assessment tools. RESULTS:At 8-week, the risk of acute exacerbations and CAT score were significantly reduced in the experimental group between-group analysis with a risk ratio (RR) of 0.375(95 % confidence interval [CI]: 0.150 to 0.935; p = 0.027), and a mean difference (MD) of -2.476 score (95 % CI: -3.281 to -1.671; p < 0.001). At 26-week, experimental group showed statistically lower risk of acute exacerbation between-group analysis (RR: 0.519; 95 % CI: 0.282 to 0.953; p = 0.030). The first exacerbation time in the experimental group (97.63 ± 35.90) was statistically longer than in the control group (66.11 ± 25.25) (MD: 31.517 (95 % CI: 14.720 to 48.314; p < 0.001). The rates of acute exacerbation readmission were similar for both the groups during the risk window and follow-up period. After 26 weeks of follow-up, experimental group CAT score was reduced by 2.046 between-group analysis (p < 0.001). Furthermore, during the whole study, the experimental group showed significantly reduced in mMRC score, as well as FEV1 and FVC values (all p < 0.05). During study period, the experimental group had a significant reduce in clinical symptom scores, including cough, expectoration, and fatigue, than the control group (p < 0.05). Regarding to SGRQ, mCOPD-PRO and mESQ-COPD, our results demonstrated that CM had better advantages in many aspects. CONCLUSION:Treatment of AECOPDRW with CM showed high efficacy and safety in significantly reducing further incidences of acute exacerbation, prolonging the interval to the initial acute exacerbation, alleviating the clinical symptoms, and improving the quality of life.

Lung adenocarcinoma (LUAD) is the most common type of lung cancer, accounting for approximately 35-40% of lung cancers, and the overall survival time of patients with LUAD is still very poor. B cells are important effector cells of adaptive immunity, and B-cell infiltration increases in various tumors. The role of B cells in LUAD is still largely unknown. Therefore, it is particularly important to clarify the role of B cells in LUAD. GSE164983, GSE50081, GSE37745 and GSE30219 were obtained from the GEO database. The TCGA-LUAD dataset was obtained from the TCGA database. UMAP was used to perform clustering descending and subgroup identification on single-cell RNA-sequencing (scRNA-seq) data to obtain B-cell markers. The TCGA cohort was used to obtain differentially expressed genes (DEGs). B-cell-related differentially expressed genes (BRGs) were identified through the intersection of B-cell markers and DEGs. The LASSO method was used to identify characteristic genes of BRGs and construct a prognostic risk model. LUAD patients were divided into high-risk and low-risk groups based on risk scores, and the immune landscape of the two groups was evaluated. We also analyzed the differences in clinical characteristics, mutations, immunotherapy, and drug sensitivity between the two groups. Thirty BRGs were obtained, and 6 characteristic genes were identified. Based on the characteristic genes, a prognostic risk model was constructed. According to the prognostic risk model, LUAD patients were divided into two groups: high-risk group and low-risk group. Patients in the high-risk group had worse outcomes and shorter survival times. Low-risk patients had better survival, while patients with high TNM stage accounted for a greater proportion of patients in the high-risk group. In addition, high-risk patients had a greater probability of mutation and worse immunotherapy response. Finally, we found different susceptibility profiles between the high-risk and low-risk groups. The prognostic risk model built based on the BRGs had good predictive performance, providing a new perspective on the prognosis and immunotherapy of LUAD patients and a new reference for LUAD research.

Viola philippica (VP), a traditional Chinese medicinal herb widely used for its antibacterial and antioxidant properties, has recently garnered attention for its potential in skin photoprotection. VP was extracted using glycerol (GLY), 1,3-propanediol (PDO), and 1,3-butanediol (BDO) at concentrations of 30%, 60%, and 90% (w/w) to evaluate its antioxidant and UV-protective properties. The total phenolic content (TPC) and total flavonoid content (TFC) of the nine extracts ranged from 34.73 to 71.45 mg GAEs/g and from 26.68 to 46.68 mg REs/g, respectively, with the highest TPC observed in 90% PDO and the highest TFC in 60% GLY. Antioxidant assays revealed IC50 values of 0.49–1.26 mg/mL (DPPH), 0.10–0.19 mg/mL (ABTS), and 1.58–460.95 mg/mL (OH). Notably, the 60% GLY, 30% PDO, and 90% PDO extracts demonstrated notable protective effects against UVB-induced cell damage, reducing intracellular ROS levels and preventing DNA damage. RNA-seq analysis revealed that the protective effects were associated with the modulation of key molecular pathways, including neutrophil extracellular trap formation and TNF, IL-17, and HIF-1 signaling. These findings suggest that Viola philippica polyol extracts, particularly those using 60% GLY, 30% PDO, and 90% PDO, have promising potential for skin photoprotection and could be utilized as natural antioxidants in cosmetic formulations.

OBJECTIVES:To evaluate the protective effect of Bufei Yishen Formula (BYF) against cigarette smoke extract (CSE)-induced injuries in human bronchial epithelial BEAS-2B cells and explore the underlying mechanism. METHODS:BEAS-2B cells exposed to CSE were treated with normal rat serum, BYF-medicated rat serum at low or high doses, pyrrolidine dithiocarbamate (PDTC, a NF-κB inhibitor), PDTC combined with high-dose BYF-medicated serum, or S-carbomethyloysteine (S-CMC, as the positive control). CCK-8 assay was used to determine the optimal concentration and treatment time of CSE, BYF-medicated serum and S-CMC. The treated cells were examined for inflammatory factor levels in the supernatant and cellular expressions of MUC5AC and MUC5B using ELISA, cell ultrastructural changes with transmission electron microscopy, and cell apoptosis rate using flow cytometry. The expression levels of TLR4/NF‑κB pathway-associated mRNAs and proteins were determined by qRT-PCR and Western blotting. RESULTS:CSE exposure significantly increased secretions of IL-1β, IL-6 and TNF-α, mRNA and protein expressions of MUC5AC and MUC5B, and early and total apoptosis rates in BEAS-2B cells, where the presence of apoptotic bodies was detected. CSE also significantly enhanced the mRNA and protein expressions of TLR4, I-κB, and NF-κB and reduced mRNA and protein expressions of AQP5. Treatments of the CSE-exposed cells with BYF-medicated serum, PDTC and S-CMC all significantly lowered inflammatory factor levels, MUC5AC and MUC5B expressions, and early and total cell apoptosis rates, and partly reversed the changes in cellular ultrastructure and mRNA and protein expressions of the TLR4/NF-κB pathway, and the effects were the most conspicuous following the combined treatment with high-dose BYF-medicated serum and PDTC. CONCLUSIONS:BYF can inhibit cell apoptosis, inflammation and mucus hypersecretion in CSE-induced BEAS-2B cells by inhibiting the TLR4/NF-κB signaling pathway.

Idiopathic pulmonary fibrosis (IPF) is associated with high mortality, heavy economic burden, limited treatment options and poor prognosis, and seriously affects the health-related quality of life (HRQoL) and life expectancy of patients. This systematic review and meta-analysis of HRQoL and health state utility value (HSUV) in IPF patients and the instruments used in this assessment aimed to provide information sources and data support for the future research on IPF HRQoL and HSUV. We searched the PubMed, EMBASE, Web of Science and Cochrane Library databases for studies reporting the HRQoL or HSUV of IPF patients, with the retrieval time from the establishment of each database to April 2024. After two researchers independently screened the literature, extracted the data, and evaluated the risk of bias in the included studies, pooled analysis was performed on the measurement tools adopted in more than two studies. Subgroup analysis was employed to explore the source of heterogeneity, and sensitivity analysis was used to assess the robustness of the results. Funnel-plot directed evaluation combined with Egger’s test quantitative evaluation was conducted to detect publication bias. Sixty-nine studies were ultimately included, covering eighteen measurement tools. The literature quality was generally excellent. The St. George’s Respiratory Questionnaire (SGRQ), EuroQoL Five Dimensions Questionnaire (EQ-5D), Short Form-36 (SF-36) and the King’s Brief Interstitial Lung Disease (KBILD) were the most common instruments, among which the EQ-5D included the HSUV and the visual analog scale (VAS). The results of the meta-analysis revealed that the pooled SGRQ total score was 45.28 (95

Background:Chronic obstructive pulmonary disease (COPD) is a major global cause of death, imposing substantial socioeconomic and healthcare burdens. This meta-analysis synthesizes evidence on all-cause and cause-specific mortality risks in COPD populations to identify high-risk subgroups and guide precision management strategies. Methods:We searched PubMed, Embase, Web of Science, and Cochrane Library for cohort studies reporting death risks in COPD from database inception to April 10, 2025. Study screening, data extraction, and quality assessment were independently performed by two investigators. Meta-analyses pooled risks for all-cause and cause-specific mortality. Sensitivity analyses tested robustness; publication bias was assessed via funnel plots and Egger's test. Results:Twenty-seven studies covering 286,314 showed COPD patients had significantly higher all-cause mortality versus non-COPD individuals (HR, 1.80; 95% CI: 1.40-2.30). Mortality risk exhibited a graded increase with COPD severity compared to non-COPD individuals: mild (HR, 1.32; 95% CI: 1.19-1.47), moderate (HR, 1.62; 95% CI: 1.45-1.81), severe (HR, 2.18; 95% CI: 1.59-2.99), and very severe (HR, 2.94; 95% CI: 1.78-4.85). When stratified by smoking status, COPD patients had consistently higher mortality than their non-COPD counterparts within each subgroup: never-smokers (HR, 1.41; 95% CI: 1.27-1.56), former smokers (HR, 1.37; 95% CI: 1.30-1.45), and current smokers (HR, 1.48; 95% CI: 1.25-1.76). The presence of comorbidities further amplified mortality risks in COPD patients versus non-COPD individuals, particularly in those with respiratory diseases (HR, 3.64; 95% CI: 3.10-4.27), cardiovascular diseases (HR, 1.29; 95% CI: 1.10-1.50), and all-cancers (HR, 1.69; 95% CI: 1.37-2.10), especially lung cancer (HR, 2.57; 95% CI: 2.04-3.24). Conclusion:COPD patients have significantly higher death risks than non-COPD individuals, worsening with disease severity. Independent determinants of COPD-attributable mortality risk comprise smoking, coexisting respiratory diseases, cardiovascular diseases, and cancer (particularly lung cancer). These findings provide an evidence-based foundation for developing targeted intervention strategies to mitigate COPD-related mortality.

Background and objective The discrimination between benign and malignant pulmonary space-occu-pying lesions and the classification of pathological subtypes of lung cancer are critical for clinical decision-making.However,conventional methods often suffer from insufficient utilization of multi-source clinical data and poor interpretability of deep learning models.This study investigates the performance of interpretable deep learning algorithms in diagnosing benign versus malignant pulmonary space-occupying lesions and classifying pathological subtypes of lung cancer,using a hybrid architec-ture based on Tab-Transformer-designed for tabular data and Residual Multi-Layer Perceptron(ResMLP),referred to as TT-ResMLP.Methods Data including radiological characteristics,medical history,and laboratory findings from 345 patients with pathologically confirmed pulmonary space-occupying lesions were collected.The dataset was randomly split into a develop-ment set and a test set at an 8:2 ratio.Stable features were selected using the Spearman correlation test and the Least Absolute Shrinkage and Selection Operator(LASSO).The Synthetic Minority Over-sampling Technique(SMOTE)was employed to balance the samples,and 10-fold cross-validation was used to enhance model generalizability.Models were constructed using the Tab-Transformer algorithm,the ResMLP algorithm,and the TT-ResMLP hybrid.Model performance was evaluated using receiver operating characteristic(ROC)curves,the area under the curve(AUC),accuracy,specificity,sensitivity,and micro-averaged ROC(micro-ROC).SHapley Additive exPlanations(SHAP)analysis was performed based on the optimal model.Results In the benign vs malignant diagnosis task,all three models performed well.The Tab-Transformer model demon-strated the best performance on the test set,followed by TT-ResMLP and ResMLP.SHAP analysis of the top-performing Tab-Transformer model revealed that the feature importance ranking was:age,pleural indentation,thrombin time,mean density,and ground-glass opacity.Pleural indentation contributed substantially to malignant diagnosis,and its contribution was further enhanced with increasing age and decreasing thrombin time.In the lung cancer subtype classification task,all three models exhibited excellent performance,with the TT-ResMLP hybrid showing the best overall performance.SHAP analysis further revealed that the Lung Imaging Reporting and Data System(Lung-RADS)category held high importance across all three pathological subtypes.Male gender was positively associated with the prediction of squamous cell carcinoma.Neuron-specific enolase(NSE)played a significant role in predicting small cell carcinoma.For adenocarcinoma,the diagnostic probability was positively correlated with the Lung-RADS category,a relationship more pronounced at lower prothrombin time(PT)values.In contrast,a negative correlation was observed in the squamous cell carcinoma and small cell carcinoma subgroups,although gender and NSE levels could enhance their contributory risk prediction.Analysis of feature decision boundaries indicated that the Lung-RADS grade possessed high discriminative power for identifying adenocarcinoma,whereas NSE demonstrated stronger discriminative ability for identifying small cell carcinoma.Conclusion The TT-ResMLP hybrid architecture is effec-tive for diagnosing the benign or malignant nature of pulmonary space-occupying lesions and classifying pathological subtypes of lung cancer.The model possesses good interpretability,aiding in the identification of key predictive features and unravelling their interactive mechanisms,thereby providing an effective tool for a deeper understanding of lung cancer biology and clinical decision support.

ETHNOPHARMACOLOGICAL RELEVANCE:Severe pneumonia (SP) represents an acute, critical condition characterized by high morbidity and mortality rates, along with numerous complications. The Qingfei Jiedu Huatan Formula (QJHF), a traditional Chinese medicine (TCM) formulation, is indicated for the treatment of severe pneumonia. However, its underlying therapeutic mechanisms remain uncertain. AIM OF THE STUDY:This study aimed to investigate the beneficial effects and molecular mechanisms of QJHF in the treatment of severe pneumonia. MATERIALS AND METHODS:The anti-inflammatory properties of QJHF were assessed using a Klebsiella pneumoniae-induced rat model of SP and LPS-induced MH-S cells. Network pharmacology and transcriptomics were employed to identify potential targets and elucidate the molecular mechanisms underlying QJHF's action against SP. Pyroptosis in lung tissue and MH-S cells was examined via immunofluorescence and scanning electron microscopy. The expression of the NLRP3 inflammasome and its upstream regulatory pathways was measured through Western blot analysis. RESULTS:QJHF was found to alleviate pulmonary edema, enhance lung pathology, and improve the blood oxygenation index, while reducing inflammatory cell infiltration, expression of inflammatory factors, and lactic acidosis in SP rats. Serum containing QJHF-containing serum significantly reduced the secretion and transcription of inflammatory factors in MH-S cells. Network pharmacology and RNA-Seq analysis revealed potential targets modulated by QJHF against SP, showing a significant association between these targets and NLRP3 within the PPI network. Pathway enrichment analysis suggested that the NOD-like receptor, TNF, NF-κB, and JAK/STAT signaling pathways might regulate the NLRP3 inflammasome and coordinate the inflammatory response. Additionally, QJHF was shown to suppress NLRP3 inflammasome activation in rats with SP and in MH-S cells, which corresponded with markedly reduced levels of TNFR1, TRAF2, TAK1, phosphorylated p65, IκBα, JAK2, and STAT3. CONCLUSIONS:QJHF effectively attenuated the inflammatory response in severe pneumonia by inhibiting macrophage-mediated inflammation and NLRP3 inflammasome activation through TNF, NF-κB, and JAK/STAT signaling pathways.

Background In China, the incidence and mortality rates of cancer have shown a significant upward trajectory from 1980/1990 to 2021, resulting in an escalating public health burden. Identifying key risk factors is critical for improving cancer prevention and management strategies. This study primarily analyzes cancer incidence and mortality data, with a particular focus on understanding the patterns and underlying factors that contribute to these trends. Methods Data from the Global Burden of Disease 2021 study were utilized. A combination of statistical analyses, decomposition analysis, Joinpoint regression analysis, and Bayesian Age-Period-Cohort modeling were employed to examine temporal trends of various cancer types across different sexes and age groups. Additionally, risk factors were identified and projected trends for the five leading cancer types were analyzed. Results In 2021, cancer accounted for 24.07% of all deaths in China. Lung, stomach, esophageal, colorectal, and liver cancers collectively accounted for 71.08% of cancer-related mortality. While age-standardized death rates (ASDR) for most cancers decreased from 1980 to 2021, age-standardized incidence rates (ASIR) significantly increased. Male cancer mortality was nearly 1.8 times higher than that of females, though both sexes shared similar leading cancer types. Notably, breast cancer ranked among the top five causes of cancer-related deaths in women. Mortality peaked in the 70–74 age group for both sexes. The incidence of breast cancer was higher in females at younger ages, while males surpassed females in incidence from age 60 onward. Behavioral and environmental risk factors, particularly tobacco use and air pollution, have the greatest impact on lung cancer. Decomposition analysis revealed that the increase in cancer mortality was predominantly driven by population aging. By 2050, colorectal cancer incidence is expected to rise, while liver cancer is projected to continue its downward trend. Conclusion The cancer profile of China has shifted over the past 30 years. The decline in ASDR indicates improvements in treatment and management, while the rise in ASIR reflects both increased risk exposure and enhanced detection capabilities. In light of aging demographics, economic development, and environmental changes, identifying predominant cancer types and their associated risk factors is essential for developing effective control strategies and targeted interventions.