Objective: This study investigates the prognostic value and clinical utility of the neutrophil percentage-to-albumin ratio (NPAR) in patients with resected non-small-cell lung cancer (NSCLC). Methods: We retrospectively included 335 patients with NSCLC who underwent lung resection at our institution between January 2017 and October 2018. Optimal cutoffs for preoperative and postoperative day 1 (D1) NPAR were determined using X-tile (version 3.6.1; Yale University, New Haven, CT, USA) to define high and low groups. Overall survival (OS) was evaluated using Kaplan-Meier analysis and Cox proportional hazards models. A perioperative NPAR trajectory (low-low, low-high, high-low, high-high) was constructed to characterize dynamic risk patterns. To mitigate potential bias associated with postoperative measurements, a D1 landmark analysis was performed. A nomogram was developed based on the multivariable model and assessed by calibration at 1, 3, and 5 years. Incremental clinical value beyond TNM stage and surgical approach was evaluated using decision curve analysis (DCA), as well as by 5-year continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Results: The optimal cutoffs for preoperative and postoperative D1 NPAR were 14.5 and 23.1, respectively. In univariate analyses, sex, smoking history, preoperative NPAR, postoperative D1 NPAR, pathologic type, TNM stage, surgical approach, and adjuvant therapy were associated with OS (all p < 0.01). In multivariable Cox regression, high preoperative NPAR (HR 1.896, 95% CI 1.135-3.168; p = 0.014) and high postoperative D1 NPAR (HR 1.905, 95% CI 1.097-3.305; p = 0.014) were independent risk factors, along with TNM stage (Stage II: HR 2.824, 95% CI 1.209-6.595; p = 0.016; Stage III: HR 9.470, 95% CI 4.935-18.171; p < 0.001) and open surgery (HR 2.350, 95% CI 1.341-4.117; p = 0.003). Trajectory analysis further stratified risk, with the high-high group showing the poorest survival (adjusted HR 3.48, 95% CI 1.43-8.47; p = 0.006). The association of postoperative NPAR persisted in the D1 landmark analysis (HR 1.836, 95% CI 1.071-3.148; p = 0.027). Adding NPAR to TNM stage and surgical approach improved 5-year risk reclassification (continuous NRI 0.377, 95% CI 0.094-0.659; IDI 0.028, 95% CI -0.002-0.054) and increased net benefit on DCA. The nomogram demonstrated acceptable calibration at 1, 3, and 5 years. Conclusions: This study demonstrates that NPAR serves as an independent prognostic marker for long-term outcomes in patients with NSCLC. The use of NPAR offers clinicians a comprehensive and precise tool for assessing patient prognosis.

MSL3P1 regulates the invasion through CUL3 in LUAD.

Obstructive sleep apnea (OSA) is associated with excess mortality, and readily obtainable biomarkers may support pragmatic risk stratification in OSA, but their comparative and incremental value remains uncertain. We benchmarked inflammation-nutrition indices and TyG-related metabolic indices for mortality risk in adults with questionnaire-defined OSA and evaluated whether these markers improve 5-year all-cause mortality prediction beyond a basic clinical model. We analysed 3,503 adults with questionnaire-defined OSA from the NHANES 2005–2008 and 2015–2018 derivation cohorts. Seven candidate biomarkers were evaluated: TyG, TyG-BMI, TyG-WC, TyG-WHtR, TG/HDL-C, advanced lung cancer inflammation index (ALI), and neutrophil percentage-to-albumin ratio (NPAR). Survey-weighted Cox models and restricted cubic splines were used to characterise mortality associations. Two 5-year all-cause mortality prediction strategies were developed: a tertile-based model (Model 1) and a continuous-scale model (Model 2). Internal validation used bootstrap optimism correction, calibration curves, Brier scores, and decision-curve analysis. Incremental value beyond a prespecified base model was assessed using likelihood-ratio testing, change in AUC, and net reclassification improvement (NRI). External validation was performed in an independent multicenter Chinese cohort of 200 patients from six hospitals. All included patients had at least 5 years of observation time from baseline assessment, allowing complete ascertainment of the binary 5-year all-cause mortality endpoint. The externally validated object was the final Base + Combine model, and its performance was assessed alongside the base model using ROC analysis, calibration plots, calibration intercept and slope, Brier score, and decision-curve analysis. During a median follow-up of 57.0 months (IQR 33.0–150.0), 293 all-cause deaths occurred in the derivation cohort. Among individual biomarkers, ALI showed the most robust mortality-related signal across analyses, whereas NPAR showed signal in selected single-marker and nonlinear analyses but was less consistent after full multivariable adjustment. TyG-related indices were also variably associated with mortality and contributed mainly within the combined prediction model. In Model 1, the full 7-marker composite model achieved an AUC of 0.735, a bootstrap-corrected AUC of 0.721, and a Brier score of 0.039. In Model 2, the best-performing combined model incorporated TyG-BMI, TyG-WC, TyG-WHtR, TG/HDL-C, and ALI, yielding an AUC of 0.765, a bootstrap-corrected AUC of 0.761, and a Brier score of 0.038. Internal calibration was acceptable for both derivation models, with Model 2 performing better. Decision-curve analysis showed positive net benefit over treat-all and treat-none strategies, with a wider clinically useful threshold range for Model 2. Compared with the base model, the combined biomarker model improved model fit (likelihood-ratio test p < 0.001) and reclassification (NRI p < 0.001), although the increase in AUC was modest. In the external validation cohort, the prespecified final Base + Combine model achieved an AUC of 0.697 (95

Bevacizumab (Bev) resistance limits therapeutic efficacy in ovarian cancer (OC) patients. We identified ESM1 as a key gene in Bev-resistant OC. ESM1 secreted by OC-resistant cell lines activates the ITGB1/FAK axis to induce neovascularization and Bev resistance. Additionally, ESM1 overexpression promoted the growth and Bev resistance of OC, lung, intestinal, and hepatocellular carcinoma tumors. Then, we identified TRIM28 as an upstream regulator that stabilizes ESM1 by promoting SUMOylation, inhibiting its proteasomal degradation. In OC mice, TRIM28 overexpression promotes angiogenesis and Bev resistance via ESM1-mediated ITGB1/FAK activation. This work unveils a new molecular pathway underlying Bev resistance in OC and proposes TRIM28 and ESM1 as potential therapeutic targets.

MSL3P1 is upregulated in a variety of cancers.

Antiphospholipid syndrome is an autoimmune disorder of unknown etiology. The anti-inflammatory and immunomodulatory properties of Zingiber officinale Roscoe may provide a novel approach for potentially preventing obstetric antiphospholipid syndrome (OAPS). Based on several public databases, compounds and potential drug targets of Z officinale Roscoe were screened, and a compound-target network was constructed using Cytoscape. The targets of OAPS were identified from GeneCards. The common genes of the disease targets and compound targets were defined as hub genes. Protein-protein interaction, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses were performed, and the OAPS pathway was obtained. Molecular docking was used to verify the binding ability of the effective compounds and targets. In total, 298 compounds were identified as components of Z officinale Roscoe. Among these, 12 active compounds exhibited an oral bioavailability of ≥30% and drug-likeness of ≥0.14, with 99 associated targets. A total of 28 common targets were identified as hub genes. In addition, the beneficial effects of Z officinale Roscoe in OAPS management are thought to be mediated by anticoagulant, anti-inflammatory, and immunomodulatory mechanisms. These processes are regulated by 9 biological signaling pathways involved in the protection against OAPS. Molecular docking showed that the binding affinities of tumor protein 53 with beta-sitosterol, tumor protein 53 with stigmasterol, prostaglandin G/H synthase 2 with beta-sitosterol, and prostaglandin G/H synthase 2 with stigmasterol were -6.651, -6.709, -7.099, and -6.829, all of which had high binding affinities. Overall, systematic pharmacology and molecular docking provide a new theoretical basis and research insight for the prevention of OAPS.

Bioluminescence imaging of MSL3P1 knockdown or overexpression on the localization of LUAD cells in the lungs of nude mice.

Intrauterine adhesion (IUA) is a significant cause of female infertility and a critical public health concern among women of childbearing age. Emerging evidence has highlighted the therapeutic potential of mesenchymal stem cell-derived extracellular vesicles (EVs) in IUA treatment. However, conventional two-dimensional (2D) culture systems impose constraints on the yield and biological activity of EVs. In this study, we employed a threedimensional (3D) culture platform based on gelatin methacrylate (GelMA) microspheres to culture human umbilical cord mesenchymal stem cells and isolate MSC-EVs. Comparative analysis demonstrated that 3D-EVs exhibited significantly superior therapeutic effects on restoring the proliferation, migration, viability, and alleviating fibrosis of mifepristone-injured human endometrial stromal cells (hESCs) compared with 2D-EVs in vitro. In IUA animal models, in situ treatment with GelMA-encapsulated 3D-EVs exhibited remarkable regenerative capabilities. The treatment effectively rejuvenated endometrial structure including mucosal thickness and glandular density, ameliorated endometrial fibrosis, and ultimately improved reproductive outcomes. Results from proteomic profiling and functional verification assays revealed that elevated expression of BECN1 in 3D-EVs contributes to the enhanced therapeutic effect of 3D-EVs on injured hESCs. This study establishes 3D culture-derived EVs as an innovative cell-free therapeutic approach for endometrial regeneration, addressing both the limitations of traditional EVs production methods and the clinical need for effective IUA treatments. Our findings provide a foundation for advanced regenerative strategies targeting endometrial pathologies.

Epigenomic regulation of MSL3P in LUAD

Bronchoscopic microwave ablation (MWA) is an emerging therapy for peripheral pulmonary lesions. Clinical cohorts evaluating the Ion robotic-assisted bronchoscopy (RAB) system for MWA remain lacking. We report our initial prospective experience with Ion RAB-guided MWA using an augmented fluoroscopy (AF) workflow, benchmarked against a historical electromagnetic navigation bronchoscopy (ENB) cohort. This prospective single-center cohort study evaluated 21 consecutive patients prospectively enrolled to undergo microwave ablation (MWA) for peripheral pulmonary lesions using the Ion RAB system (25 lesions) between January 1, 2025, and January 1, 2026, and benchmarked these outcomes against a retrospectively established historical cohort of 42 consecutive ENB-guided MWA procedures (51 lesions) performed at the same center under an augmented fluoroscopy (AF) strategy. The primary endpoint was postoperative day 1 (POD1) technical success. Secondary endpoints included 6-month treatment success, navigation/total workflow times, cone-beam CT (CBCT) acquisitions, radiation dose, and complications. POD1 technical success was 100

Small cell lung cancer (SCLC) is a heterogeneous disease with different pathogenic mechanisms. A range of molecular classification systems has been proposed based on the tumor’s molecular characteristics. However, the relationship between these various molecular subtypes and survival prognosis remains unclear and has not been incorporated into clinical practice. Therefore, we conducted a systematic review of studies investigating the relationship between molecular subtypes of SCLC and patient survival prognosis. A comprehensive search was conducted in the PubMed, Embase, Cochrane, and Web of Science databases, utilizing combinations of terms related to SCLC, molecular subtypes, and survival prognosis. Two independent reviewers were tasked with data extraction and quality assessment. Following a comprehensive review of the pertinent literature, eight studies were included. Some methodological heterogeneity across these studies contributed to frequently inconsistent conclusions. Our findings tend to suggest that the inflammatory subtype (SCLC-I), which belongs to the non-neuroendocrine (non-NE) subtype, exhibits a survival advantage in most cases, while the ASCL1-dominant subtype (SCLC-A), which belongs to the NE subtype, shows a poorer survival prognosis, except in some exceptional cases. This is one of the first comprehensive systematic reviews to explore the relationship between molecular subtypes and survival prognosis in SCLC. Future high-quality studies employing standardized subtype definitions are warranted to validate these prognostic associations and enable definitive conclusions. Furthermore, emerging multi-omics and integrated spatial analyses have revealed novel subtypes and predictors, which are significantly associated with survival prognosis.

BACKGROUND:Venous thromboembolism (VTE) represents a potentially fatal but preventable postoperative complication. We sought to establish and validate an explainable prediction model based on the machine learning (ML) approach for VTE, and assess its prognostic implications in thoracic oncology patients undergoing VATS Segmentectomy. MATERIALS AND METHODS:We prospectively developed and validated a predictive model for postoperative VTE following VATS segmentectomy. Patients were sequentially enrolled into training (n = 557, Apr.2017-Jan.2021) and validation cohorts (n = 239, Feb.2021-Oct.2022). 49 clinicopathological variables, including the novel biomarker von Willebrand factor A2 (vWF-A2), were evaluated. 11 ML algorithms were compared based on several evaluation indexes including AUC. SHapley Additive exPlanations (SHAP) analysis was utilized for feature ranking and interpretability. The final model was benchmarked against the traditional Caprini score, and the prognostic impact of postoperative VTE on long-term survival was further assessed. RESULTS:In this prospective study, eXtreme gradient boosting (XGBoost) demonstrated superior discriminative performance among 11 evaluated ML-models. After feature reduction based on ranked feature importance, a final interpretable XGBoost model comprising 11 variables was established. This model accurately predicted postoperative VTE in both training (AUC = 0.903) and validation (AUC = 0.856) cohorts, significantly outperforming the conventional Caprini score RAM. Additionally, comparison of oncologic outcomes revealed no significant difference in overall survival (P = 0.068), whereas disease-free survival was significantly shorter in patients experiencing postoperative VTE (P = 0.017). CONCLUSION:Our explainable risk-stratification ML model not only accurately predicts the risk of VTE following VATS segmentectomy in early-stage NSCLC patients, but also exhibits substantial clinical relevance to adverse prognostic outcomes in this patient cohort.

Functional tissue repair is often constrained by inflammation and fibrosis. Alternatively activated M2 macrophages have emerged as promising therapeutic targets for optimizing graft-to-host interactions; however, efficient induction methods are required. Presumably, the outcome of regenerative wound healing or scar formation/fibrosis might be dependent on the balance between M2a and M2c sub-phenotypes. This study utilized dual-functionalized graphene oxide (GO) as a DNA delivery agent to induce M2a and M2c macrophage polarization. Mechanistically, molecular characteristics were analyzed using RNA sequencing. We designed GO with polyethyleneimine (PEI) modification and subsequently conjugated it with polyethylene glycol (PEG)-folate (FA) to target human THP-1-derived macrophage activation. Specifically, the resulting GO-PEI-PEG-FA (GPPF) compound effectively activated CD206+CD209+M2a and CD163+MerTK+M2c phenotype polarization. The efficient delivery of IL4 or IL10 plasmid DNA using GPPF (GPPF/pIL4 or GPPF/pIL10) significantly enhanced macrophage cellular elongation and reduced MHC-II-associated antigen presentation. M2a(GPPF/pIL4) and M2c(GPPF/pIL10) were validated as negative regulators of the immune response and positive regulators of Th2 effectors. Up-regulated genes in M2a(GPPF/pIL4) even inhibited type I interferon production and restricted the innate immune response. Supplemental to the established data, M2a(GPPF/pIL4) behaved similar to IFN-responsive macrophages, restricting viral life cycles and promoting myogenesis and osteogenesis. Meanwhile, M2c(GPPF/pIL10) was characterized using IL10 signaling, anti-fibrosis, and neutrophil-mediated suppression of the LPS-bacterial response. Regarding the tissue remodeling process, the two subsets attenuated negative-regulated BMP signaling to facilitate osteoinduction and up-regulated NAMPT to establish a transient stem cell-activating niche for tissue regeneration. This study underscored the potential of functionalized GO-induced M2 sub-phenotypes as modulators in regenerative medicine.

Background:Lung cancer is the most common cancer and the leading cause of cancer-related death worldwide. In pulmonary fibrosis (PF), the incidence of lung cancer is elevated, and its prognosis is worse compared to the general population. With the development of related research, the relationship between lung cancer and pulmonary fibrosis has received close attention. However, comprehensive and objective reports on this topic remain scarce. Therefore, this study aims to identify research hotspots and visualize evolving trends and collaboration networks in the field of pulmonary fibrosis and lung cancer using bibliometric and knowledge mapping tools. Methods:Articles in the field of pulmonary fibrosis and lung cancer were retrieved using the Web of Science core collection subject search, and bibliometric analysis was performed in CiteSpace, VOSviewer, ChiPlot (https://www.chiplot.online/) and Bibliometrix (R-Tool of R-Studio). Results:This bibliometric analysis included 1,830 publications from 2000 to 2024, showing a steady increase over time. Collaborative network analysis identifies Japan, the United States, and China as the most influential countries, contributing the highest publications and citations. Respiratory Research is the leading journal. Bade BC is a key author, with Lung Cancer 2020: Epidemiology, Etiology, and Prevention as the most cited work. Literature and keyword analyses indicate a primary focus on diagnosis and survival, with recent shifts toward gene regulation and pulmonary inflammation. Emerging research highlights epithelial-mesenchymal transition (EMT) and chronic inflammation in lung cancer development among IPF patients. Notably, studies on immune checkpoint inhibitors (e.g., PD-1/PD-L1) have surged, reflecting a growing interest in immunotherapy. Conclusion:This study is the first to employ bibliometric methods to visualize research trends and frontiers in pulmonary fibrosis and lung cancer. Our analysis reveals a shift from early studies on diagnosis and prognosis toward a growing focus on molecular mechanisms and immunotherapy. These findings offer valuable insights into emerging research directions and may serve as a reference for researchers seeking to identify key topics and potential collaborators.

Background Butyrate may inhibit SARS-CoV-2 replication and affect the development of COVID-19. However, there have been no systematic comprehensive analyses of the role of butyrate metabolism-related genes (BMRGs) in COVID-19.Methods We performed differential expression analysis of BMRGs in the brain, liver and pancreas of COVID-19 patients and controls in GSE157852 and GSE151803. The differentially expressed genes (DEGs) and module genes between COVID-19 patients and healthy controls in GSE171110 were screened through ‘limma’ and ‘WGANA’ R package, respectively, followed by an intersection with BMRGs via ‘ggvenn’ R package. Six machine learning algorithms were employed to determine the best model for identifying biomarkers, and receiver operating characteristic (ROC) curves were plotted to evaluate the diagnostic value of the biomarkers in COVID-19. Moreover, the differences in immune-infiltrating cells between the COVID-19 and control groups were compared using CIBERSORT. The differences in immune cells and expression levels of biomarkers in immune cells among different tissues were analysed using GSE171668.Results The BMRGs were the most different in the brain between the COVID-19 and control groups, including 21 upregulated and 16 downregulated genes. Five important common BMRGs were screened as biomarkers for COVID-19 using XGBoost, namely CCNB1, CCNA2, BRCA1, HBB and HSPA5, with increased diagnostic performance. Enrichment analysis revealed that these five genes were related to the cell cycle, cell proliferation and cell senescence. The infiltrating abundance of 12 immune cells was different between the COVID-19 and control groups. Finally, the expression levels of HSPA5, BRCA1 and HBB were higher in annotated cells than in CCNB1 and CCNA2, and there were four different types of immune cells in the liver, heart, lungs and kidneys.Conclusions These five genes may be potential biomarkers of butyrate metabolism in COVID-19 patients. These findings provide a direction for further studies on the molecular mechanisms underlying COVID-19.

BACKGROUND:Aging-related genes (ARGs) are prognostic markers in cancers, but their role in lung adenocarcinoma (LUAD) remains unclear. Investigating ARGs in LUAD may provide valuable insights for clinical diagnosis and treatment. METHODS:Gene expression profiles from TCGA and GEO datasets were analyzed to identify ARG-related genes. Univariate Cox regression and LASSO analysis were used to construct a prognostic risk model. Kaplan-Meier survival analysis, ROC curves, and clinicopathological features validated its predictive accuracy. Immune cell infiltration and tumor microenvironment were assessed using CIBERSORT and ESTIMATE. RT-qPCR was used to validate the differential expression of key genes in LUAD and adjacent normal tissues. RESULTS:Seven prognostic ARGs (RHPN2, BLK, PTPRO, CA4, UBE2C, METTL7A, and H2BC12) were identified. The risk model stratified patients into high- and low-risk groups, with high-risk individuals showing poorer survival, increased immune evasion, and altered immune cell infiltration. These findings were validated in independent datasets. RT-qPCR confirmed elevated RHPN2, BLK, UBE2C, and H2BC12 in tumors, while PTPRO, CA4, and METTL7A were reduced. CONCLUSION:A robust ARG-based risk model, leveraging Cox regression and LASSO, effectively predicts survival and immunotherapy responses in LUAD, offering new tools for personalized prognosis and treatment strategies.

Cisplatin chemotherapy is an important treatment for advanced ovarian cancer (OC). However, the development of cisplatin resistance greatly limits the survival time of OC patients. Endothelial cell-specific molecule 1 (ESM1) has been found to be an important proto-oncogene promoting OC, but its mediating OC cisplatin resistance remains unknown. We used quantitative polymerase chain reaction (qPCR) to measure transcription levels of ESM1, Growth arrest specific transcript 5 (GAS5), miR-23a-3p, and Phosphatase And Tensin Homolog (PTEN). A double luciferase reporter gene assay confirmed the direct binding of GAS5 to miR-23a-3p and miR-23a-3p to PTEN mRNA. The effects of ESM1, GAS5, miR-23a-3p, and PTEN on OC cisplatin resistance were tested with an Half Maximal Inhibitory Concentration (IC50) assay. Flow cytometry was used to assess the effects of ESM1, GAS5, and miR-23a-3p on cisplatin-induced OC apoptosis. Changes in apoptosis-related proteins and PI3K/AKT-related proteins were analyzed with western blot (WB). ESM1 inhibits the levels of GAS5 and PTEN but increases miR-23a-3p. ESM1 and miR-23a-3p promote OC cisplatin resistance. GAS5 and miR-23a-3p promote cisplatin sensitivity for OC cells. Moreover, the main molecular mechanism is the ESM1/GAS5/miR-23a-3p/PTEN/PI3K/Akt signaling axis. ESM1 promotes OC cisplatin resistance by activating the Phosphoinositide-3-Kinase (PI3K)/AKT Serine/Threonine Kinase (Akt) signaling pathway through the GAS5/miR-23a-3p/PTEN signaling axis. This suggests that prescriptive ESM1 regulates key downstream molecular mechanisms via non-coding RNA and can be used before neoadjuvant chemotherapy in OC is initiated.

PurposeTo analysis the correlation between EGFR mutations and clinicopathological features in lung adenocarcinomas.Methods139 lung adenocarcinoma cases from the Second Hospital of Shandong University were conducted molecular detection of EGFR mutations. Multiple clinicopathological characteristics were collected and analyzed to identify the relationship with EGFR mutations. The amplification refractory mutation system (ARMS) was performed to detect the EGFR mutations.ResultsDuring the 139 cases, 96 lung adenocarcinoma cases had EGFR mutations. EGFR mutations were associated with smoking history (P=0.0311), tumor size (P=0.0247), tumor subtype (P=0.0003), rhabdomyoid differentiation (P=0.0237) and extracellular mucus (P=0.0013).ConclusionsSmoking history, tumor size, tumor subtype, rhabdomyoid differentiation and extracellular mucus were related to EGFR mutations in lung adenocarcinoma. These histological characteristics might be meaningful to predict EGFR mutations.