Abstract Background Benzo[a]pyrene diol epoxide (BPDE), a key carcinogenic metabolite of the ubiquitous environmental pollutant benzo[a]pyrene, is a well-established etiological agent in lung cancer. However, a systems-level understanding of its molecular targets and pathogenic mechanisms remains incomplete. This study aimed to identify and characterize the core toxicity targets linking BPDE exposure to lung carcinogenesis using an integrative network toxicology approach. Methods Putative BPDE targets were retrieved from SwissTargetPrediction and TargetNet. Lung cancer-associated genes were compiled from GeneCards and TCGA datasets. The intersection yielded candidate genes, which were analyzed via protein–protein interaction (PPI) network construction, functional enrichment, and machine learning (LASSO, XGBoost, Random Forest, Boruta) to identify core biomarkers. A nomogram was developed for risk prediction. The key target CA2 was further validated for prognostic value, differential expression across multiple cohorts (TCGA, GEO), and associated biological pathways via gene set enrichment analysis (GSEA) and pathway activity scoring. Molecular docking was performed to simulate the BPDE-CA2 interaction. Results Thirty-one overlapping targets were identified. Enrichment analysis implicated processes like inflammation, oxidative stress response, and cancer-related pathways (e.g. p53, cell cycle). Machine learning convergence highlighted four core biomarkers: PARP1, ALOX5, CA9, and CA2. Among these, CA2 demonstrated significant prognostic value, consistent downregulation in lung tumor tissues across independent datasets, and distinct molecular phenotypes: its high expression correlated with immune activation and suppressed VEGF signaling, while low expression was linked to enhanced cell cycle activity. Molecular docking revealed a stable binding interaction between BPDE and CA2. Conclusion This integrative study identifies a set of core targets, prominently featuring CA2, that potentially mediate BPDE-induced lung carcinogenesis. CA2 downregulation is associated with poor prognosis, a pro-proliferative phenotype, and may be directly modulated by BPDE, positioning it as a critical molecular link between environmental exposure and lung cancer development. Insight Paragraph This study provides a systems-level molecular bridge connecting environmental carcinogen exposure to lung cancer pathogenesis. By integrating network toxicology, machine learning, and multi-omics validation, we move beyond single-gene associations to identify a core set of toxicity targets, most notably CA2. We demonstrate that CA2 downregulation, potentially via direct interaction with BPDE, is linked to poor prognosis and a pro-proliferative phenotype. This integrative approach offers a novel mechanistic insight, positioning CA2 as a critical node at the intersection of environmental exposure, disrupted metabolism, and tumor progression, with implications for risk prediction and targeted prevention strategies.
Abstract Background Diabetes mellitus (DM) and its cardiovascular complications represent one of the most prevalent causes of death worldwide, closely linked to chronic inflammatory states. Inflammatory Burden Index (IBI) is a composite inflammatory marker that comprehensively assesses systemic inflammation levels. Currently, the prognostic association of IBI with outcomes in individuals living with DM and prediabetes (pre-DM) remains unclear. Objective To investigate association of IBI with all-cause and cardiovascular mortalities in individuals living with DM and pre-DM. Methods Utilizing data from NHANES 1999–2010, we enrolled 8738 participants. Kaplan–Meier analysis and weighted multivariate Cox proportional hazards models were employed to examine relationship of IBI tertiles with mortality risk. RCS analysis tested for non-linear associations, while subgroup analyses evaluated effect modification. Sensitivity analysis was performed by excluding deaths occurring during the early follow-up period. Results During a median 11.7 years of follow-up, 2726 all-cause deaths (31.2%) and 893 cardiovascular deaths (10.2%) were recorded. Results demonstrated significant associations of IBI with mortality risks in individuals living with pre-DM and DM. In fully adjusted model, compared with the lowest IBI tertile (T1), the highest tertile (T3) was associated with a 42% elevated risk of all-cause mortality (HR = 1.42, 95%CI: 1.24–1.63, P < 0.001) and a 38% elevated risk of cardiovascular mortality (HR = 1.38, 95%CI: 1.08–1.76, P = 0.011). RCS analysis revealed an overall significant association of IBI with mortality risks without evidence of non-linearity (P-non-linear>0.05). No significant interaction effects were seen in subgroup analyses. After excluding deaths occurring within the first 1 and 2 years of follow-up in sensitivity analyses, the above associations remained generally consistent. Conclusion Elevated IBI was significantly associated with elevated risks of all-cause and cardiovascular mortalities in persons with DM and pre-DM, suggesting that IBI may help identify subjects at higher mortality risk within this population. Highlights Elevated inflammatory burden index was significantly associated with increased risks of all-cause and cardiovascular mortality in individuals with diabetes and prediabetes. Insight Box This study identifies the Inflammatory Burden Index as a stable, integrative biomarker linking systemic inflammation to elevated all-cause and cardiovascular mortality in prediabetic and diabetic individuals. By quantifying cumulative inflammatory burden rather than single markers, it provides a biologically coherent, clinically accessible tool for risk stratification. These findings support integrated inflammatory monitoring as a rational strategy to improve prognostic evaluation and targeted intervention in glucose metabolism disorders, bridging molecular inflammation, cardiometabolic pathophysiology, and population-level clinical outcomes.
Abstract Purpose This study used scRNA-seq to explore the underlying mechanisms of decidual natural killer cells affecting recurrent miscarriage (RM). Methods We obtained the GSE214607 scRNA-seq dataset from Gene Expression Omnibus (GEO) database, containing data from 5 normal and 3 RM pregnancy samples. The ‘Seurat’ and ‘Harmony’ R package was used for the scRNA-seq analysis. Differentially expressed genes among cell subpopulations were identified using FindAllMarkers function, and the ‘Monocle2’ package was employed to construct pseudo-time trajectories. Finally, the ‘CellChat’ package was used to analyze ligand-receptor interactions between cells. Results Our analysis revealed altered immune cell composition in RM, with reduced decidual NK (dNK), decidual stromal, and epithelial glandular cells but increased Mono/Macro proportions. Two dNK subclusters were identified: PAEP-high (linked to growth factor signaling) and LGALS1-high (involved in glycolysis and platelet function). Despite similar subcluster frequencies, RM samples showed elevated interferon response genes (e.g. IFITM1, ISG15) and diminished migration/activation signals. Pseudo-time analysis highlighted progressive gene expression changes during RM. CellChat revealed reduced Vascular Endothelial Growth Factor (VEGF) signaling, indicating impaired angiogenesis, and enhanced TNF, MHC-II, and FAS/FASL interactions, suggesting increased inflammation and trophoblast apoptosis. These findings implicate dNK dysfunction in RM and suggest potential therapeutic targets. Conclusions Our findings demonstrate dNK cell dysfunction in RM, marked by heightened interferon signaling and aberrant crosstalk with trophoblasts. Integrative analysis of public transcriptomic data suggests that dNK cell-directed interventions represent a putative therapeutic avenue for RM. Insight RM linked to decidual immune imbalance with reduced dNK and increased monocytes/macrophages. Two dNK subclusters (PAEP-high, LGALS1-high) with specific gene expression pattern in RM. RM shows impaired angiogenesis, inflammation, and trophoblast apoptosis in dNK cell-mediated signaling pathways. Dysfunctional dNK cells drive RM, revealing potential therapeutic targets for treatment.
Thrips are the only insect order in which every winged representative has bristled wings. Their size range is greater than in any other group of bristle-winged insects, and they include the largest representatives of bristle-winged insects. Available publications lack comparative morphological data on the scaling of wings in thrips, hindering the study of their flight mechanics. We analyze here the functional wing morphology of thrips across different taxonomic and size groups. Using light microscopy and scanning electron microscopy, we describe the wing morphology of several species. A second row of setae on the trailing edge of the forewing is found only in Thysanoptera. It appears as a short additional row in Tubulifera, where it reduces wing permeability, and as a long row in Terebrantia, where it presumably increases the rigidity and stability of the spread fringe of bristles in combination with the wavy shape of the bristles, found in Thripinae. The microsculpture of the bristles consists of reinforcing ridges in the suborder Terebrantia and small secondary outgrowths in the suborder Tubulifera, possibly increasing the surface area of the bristles. Scaling analysis was performed separately for representatives of each of the two suborders and the results were compared with the available data on other insects with bristled wings. Phlaeothripidae (Tubulifera) demonstrate trends similar to those of feather-wing beetles (Ptiliidae): as body size decreases, the number and diameter of wing setae, relative length and area of the wing blade decrease, whereas the gap between setae increases. The scaling of wing parameters in Thripidae (Terebrantia) is ambiguous for most characteristics. High-speed video recording of flight was conducted and basic kinematic characteristics were obtained. Mechanical analysis based on morphological and kinematic data confirmed that the wings of thrips have minimal inertia while maintaining aerodynamic functionality. The data provided here can be used to construct accurate scaling and numerical models of thrips wings and open the way for studying the aerodynamics of flight in both the smallest thrips and the largest thrips.
Methicillin-resistant Staphylococcus aureus (MRSA) infections pose a critical threat in healthcare and community settings. Meanwhile, the effectiveness of treatment is limited by vancomycin, which remains the only frontline drug against MRSA. The emergence of new strains of MRSA, along with the development of vancomycin-resistant S. aureus (VRSA), emphasises the need for alternative therapies. This study explores the use of natural compounds as a sustainable alternative to treat MRSA. The inhibition potential of natural compounds against D-alanine-d-alanine ligase, a key enzyme in the peptidoglycan synthesis, which belongs to the ATP Grasp Protein family. The ATP binding is responsible for the formation of the intermediate through enzyme catalysis. The 1252 molecules selected from the COCONUT database, with high predicted potency, low toxicity, and bioavailability, were subjected to virtual high-throughput screening (vHTS) against the ATP-binding site of the target protein. The two promising molecules were identified based on their orientations and interactions with ATP-binding residues. The selected protein-drug complexes were further evaluated by MD simulation to comprehend their effects under physiological conditions, followed by calculation of binding affinity using the MM-PBSA approach. The essential dynamics studies and MM-PBSA results suggested that CNP0475353 (ΔG = -98.78 kcal/mol) and CNP0263347 (ΔG = -10.63 kcal/mol) could act as potential inhibitors of Ddl by interacting with key ATP-binding residues. The study proposes that CNP0475353 and CNP0263347 may be explored for therapeutic potential against MRSA.
