Search Results (2,259)

A miniaturized variant of the artificial luciferase (ALuc), named picALuc, has been generated through the deletion of N- and C-terminal residues in ALuc. Although picALuc is small and active, questions remain regarding its the structural organization and inter-residue interactions in the protein. Here, combining computational analysis and mutational studies, we show that the E50A mutation in picALuc results in an increased bioluminescence activity of the protein. Specifically, we generated a structural model of picALuc using the available structure of the Gaussia luciferase (GLuc) that revealed a ‘hole’ in the structure due to the deletion of N-terminal α-helices. Gaussian-accelerated molecular dynamics (GaMD) simulation revealed a rapid ‘compaction’ of the picALuc structure during the initial phase of the simulation and a number of residues such as E10, E50, and D94 showed salt bridge interactions. Mutation of the residues E10, E50, and D94 individually to an A revealed increased bioluminescence activity of the E50A mutant, while E10A and D94A mutants showed activities similar to the WT protein in living cells. In vitro assays revealed an increase in the V_max of the E50A mutant, while K_half and thermal stability of the mutant remained unchanged. Further, dynamic cross-correlation and principal component analyses of the GaMD simulation trajectories of the WT and the E50A mutant picALuc revealed altered collective dynamics in the protein. Finally, we developed a protein fragment complementation assay using picALuc that allows for the monitoring protein–protein interactions (PPIs) in live cells. We envisage that the brighter picALuc reported here will find broad applicability in developing bioluminescence-based assays. Full article

Background: Metabolic dysfunction-associated fatty liver disease (MAFLD) is a highly prevalent chronic liver disorder driven by complex metabolic, inflammatory, and oxidative mechanisms with no effective pharmacological therapy currently available. Although the multi-target natural product Proliverenol, derived from Phaleria macrocarpa pericarp, has shown hepatoprotective potential in preclinical and early clinical studies, its molecular mechanisms in MAFLD remain unclear. Objective: This study aimed to elucidate the multi-target hepatoprotective mechanisms of Proliverenol in MAFLD by integrating untargeted phytochemical profiling, network pharmacology, and molecular docking approaches. Methods: Untargeted LC–HRMS/MS analysis was performed to characterize the phytochemical composition of Proliverenol (Veprolin™). Identified compounds were subjected to target fishing, followed by protein–protein interaction (PPI) network construction, cluster analysis, and functional enrichment (GO and KEGG). Key MAFLD-related targets were further validated using molecular docking against major signaling proteins implicated in inflammation, apoptosis, and metabolic regulation. Results: Fourteen bioactive compounds were annotated, dominated by flavonoids and organic acids, including several phenolic acid derivatives, with phalerin as the most abundant constituent. Network pharmacology identified overlapping targets between Proliverenol, MAFLD, and hepatotoxicity, forming a highly interconnected PPI network. Functional enrichment revealed significant involvement in apoptosis regulation, inflammatory signaling, oxidative stress response, lipid metabolism, and insulin resistance pathways. Molecular docking demonstrated strong binding affinities of several Proliverenol constituents—particularly cucumerin B, artoindonesianin P, and vitexin 2″-p-hydroxybenzoate—toward key targets including PTGS2, SIRT1, GSK3B, RELA, and MCL1, with affinities comparable to or exceeding those of reference drugs. Conclusions: Proliverenol exerts hepatoprotective effects through coordinated multi-target modulation of inflammatory, metabolic, and apoptotic pathways relevant to MAFLD. While these findings provide mechanistic insights based on integrative metabolomics and computational analyses, the absence of direct experimental validation represents an important limitation. Therefore, further in vitro, in vivo, and clinical investigations are warranted to confirm the predicted molecular interactions and therapeutic relevance. Full article

Protein–protein interactions (PPIs) are fundamental to biological processes, yet experimental identification of PPIs remains time-consuming and costly, particularly for crop species with limited data. Grape (Vitis vinifera) is a globally important fruit crop that would benefit from improved computational tools for PPI prediction to support functional genomics and molecular breeding. Here, we present GrapePPI, a deep learning framework specifically designed for grape PPI prediction that leverages pre-trained ESM (Evolutionary Scale Modeling) protein embeddings. GrapePPI employs a four-component architecture: ESM embedding extraction, sequence encoding, feature combination, and multi-layer interaction prediction. We evaluated GrapePPI on grape-specific datasets with balanced and imbalanced class distributions, as well as benchmark datasets from yeast and Arabidopsis. On grape data, GrapePPI significantly outperformed state-of-the-art methods including DeepFE-PPI, PIPR, and ESMAraPPI, achieving F1 scores of 89.34% and 85.43% on balanced and imbalanced datasets, respectively, with PR AUC values of 95.29% and 90.87%. GrapePPI also demonstrated strong cross-species generalization, outperforming competing methods on yeast datasets and achieving performance comparable to specialized plant models on Arabidopsis data. Our results establish GrapePPI as an effective and robust tool for grape PPI prediction, with practical applications in functional genomics research and crop improvement programs. Full article

Background: Shenqi granule (SQG) was used clinically to strengthen the spleen and boost energy, alleviating physical weakness and limb fatigue caused by energy deficiency. However, the specific effects and potential molecular mechanisms of SQG in myocardial infarction (MI) treatment remain to be clarified. Methods: This study thoroughly evaluates SQG’s role in improving MIRI in rats using a biological approach. Network pharmacology, weighted gene co-expression network analysis (WGCNA), receiver operating characteristic (ROC), and immune landscape analysis were used to analyze components and key molecular targets. The therapeutic targets of SQG were then validated through molecular docking, molecular dynamics simulation, and experiments. Results: SQG reduced myocardial infarct size and improved myocardial function in rats. Network pharmacology analysis found that six bioactive compounds in SQG could target four proteins. Using WGCNA and ROC, two key targets of SQG were identified, MMP9 and ADH1C. Importantly, integrating PPI network prediction, molecular docking, and expression correlation analyses, MMP9 and ADH1C demonstrate strong physical binding potential and expression association, suggesting their possible involvement in MIRI-related pathways through the immune microenvironment. Molecular experiments and other methods confirmed that the five active ingredients in SQG (luteolin, quercetin, hederagenin, 7-O-methylisomucronulatol, and stigmasterol) can exert cardioprotective effects by stably binding to MMP9/ADH1C. Conclusions: SQG reduces myocardial infarct volume and enhances myocardial function in MIRI rats, likely via inhibiting MMP9 and ADH1C expression. This suggests SQG’s potential as a therapeutic agent for MI, with findings offering strong scientific support for SQG’s use in cardiovascular disease research. Full article

Childhood obesity is a complex pathology that triggers early vascular damage through endoplasmic reticulum (ER) stress and fibrinolytic imbalance; however, the role of the ATF6/PLAT regulatory axis in this process has not yet been fully elucidated. This study aims to investigate the molecular basis of vascular risk by determining the expression levels of these genes and the potential regulatory hsa-miR-340-5p in children with obesity. Gene expression analyses were performed using the RT-qPCR method on blood samples obtained from 55 children with obesity and 40 healthy controls, while in silico protein–protein interaction (PPI) networks were mapped using the STRING database. The findings revealed that ATF6 expression was significantly downregulated (p < 0.001) and PLAT expression was significantly upregulated (p = 0.005) in the obese group compared to controls. No significant difference was detected in hsa-miR-340-5p levels (p = 0.447). PPI analysis confirmed the strong functional clustering of ATF6 with metabolic stress pathways and PLAT with coagulation cascades. In conclusion, the suppression of ATF6 in obesity indicates the “exhaustion” of adaptive cellular defense mechanisms, while the upregulation of PLAT points to a compensatory response to the chronic prothrombotic environment. These molecular alterations demonstrate that vascular risk in childhood obesity begins at the transcriptomic level long before clinical symptoms emerge, highlighting the ATF6/PLAT axis as a potential biomarker for early risk assessment. Full article

Background and Aims: The rising global incidence of cholangiocarcinoma (CCA) coincides with epidemics of type 2 diabetes (T2D) and chronic hepatitis B virus (HBV) infection. Although both are established independent risk factors, the shared molecular mechanisms by which they contribute to cholangiocarcinogenesis remain poorly understood. We hypothesized that T2D and HBV converge on a state of chronic metabolic inflammation (“metaflammation”) that drives CCA progression through a conserved transcriptomic network. Methods: We performed an integrative bioinformatics analysis of transcriptomic data from public repositories, including samples of CCA (TCGA-CHOL, n = 45; GSE107943, n = 163), T2D-affected liver (GSE23343, n = 20), and HBV-infected liver (GSE58208, n = 102). Acknowledging that the T2D and HBV datasets were derived from whole-liver tissue, whereas CCA originates in the biliary epithelium, we identified differentially expressed genes (DEGs) across conditions and defined a core gene set shared among them. Subsequent analyses included functional enrichment, construction of protein–protein interaction (PPI) networks, survival analysis, and protein validation. Results: We identified a core metaflammation signature comprising 156 genes that were consistently dysregulated across T2D, HBV, and CCA. Pathway analysis revealed significant enrichment in PPAR signaling, cytokine–cytokine receptor interaction, PI3K-Akt, and TNF signaling pathways. Protein–protein interaction (PPI) network analysis identified IL6, TNF, AKT1, STAT3, and PPARG as the top hub genes. These hubs were functionally modularized into clusters associated with inflammatory signaling, metabolic regulation, and cell growth and survival. In the TCGA CCA cohort, high expression of IL6, TNF, AKT1, and STAT3 and low expression of PPARG correlated with advanced tumor stage and poorer overall survival (e.g., IL6: ρ = 0.42, p = 0.01). A metaflammation score derived from these hubs (weighted combination of the five genes) emerged as an independent prognostic factor (HR = 2.8, p < 0.001). Protein-level dysregulation of these hubs was confirmed via immunohistochemistry. Conclusions: This study defines a conserved metaflammation network that links T2D and HBV to CCA, identifying key hub genes and pathways. This signature provides a mechanistic explanation for epidemiological risks, serves as a novel prognostic tool, and offers a rationale for targeting metaflammation in prevention and therapy for high-risk populations. Full article

Background: Hilar cholangiocarcinoma (HC) is a highly aggressive malignancy with a poor prognosis, highlighting the urgent need to elucidate its molecular drivers. This study aimed to systematically identify and functionally validate key genes and pathways driving HC pathogenesis. Methods: RNA sequencing (RNA-seq) was performed on paired primary HC tumors and matched adjacent non-tumorous tissues to identify differentially expressed genes (DEGs). Subsequent bioinformatic analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein–protein interaction (PPI) network construction, were conducted to characterize the functional landscape and identify hub genes. Transwell assays and orthotopic metastatic models were used to investigate the functions of Contactin-1 (CNTN1) in HC invasion in vitro and metastasis in vivo. Results: RNA-seq analysis identified 35 DEGs in HC, mainly involved in cell adhesion, cytoskeletal regulation, and axon development. PPI network analysis identified six hub genes, including CNTN1, NCAM1, PLP1, GPM6B, SLC1A3, and PMP2. Furthermore, we demonstrated that CNTN1, a neuronal membrane glycoprotein, was markedly up-regulated in HC at both mRNA and protein levels, and its elevated expression correlated with poor prognosis. Gain- and loss-of-function studies demonstrated that CNTN1 promotes HC cell invasion in vitro and metastasis in vivo. Mechanistically, CNTN1 exerts its pro-invasive effects by activating the PI3K-AKT signaling pathway and inducing epithelial–mesenchymal transition (EMT). Conclusions: Our integrated analysis identifies CNTN1 as a critical oncogenic driver in HC, promoting metastasis through PI3K-AKT-mediated EMT. These findings nominate CNTN1 as a potential prognostic biomarker and therapeutic target in HC. Full article

Background/Objectives: Hepatocellular carcinoma (HCC) is a primary malignancy often driven by metabolic syndrome, fatty liver disease, and chronic hepatitis. These conditions foster a pro-inflammatory microenvironment that promotes tumor progression. Viniferin, a natural oligostilbene, has gained attention for its potential bioactivity. This study utilized an in silico network pharmacology approach to elucidate the pharmacokinetic properties and molecular mechanisms of ε- and δ-viniferin against HCC within the context of metabolic and inflammatory liver pathologies. Methods: ADMET profiles were characterized using SwissADME and pkCSM. Therapeutic targets were identified by intersecting viniferin-associated molecules with disease genes from GeneCards. A protein–protein interaction (PPI) network was constructed, supplemented by GO and KEGG enrichment analyses. Molecular docking and 200 ns of molecular dynamics (MD) simulations evaluated the binding affinity and structural stability between viniferin isomers and identified hub proteins. Results: Both ε- and δ-viniferin showed favorable drug-like properties, including high gastrointestinal absorption and low hepatotoxicity. We identified 247 overlapping targets, with network analysis highlighting ten essential hub genes, including AKT1, HSP90AA1, ESR1, HIF1A, NFKB1, GSK3B, PTGS2, APP, MTOR, and PIK3CA. Enrichment analysis confirmed their involvement in critical oncogenic pathways. Molecular docking showed strong interactions with APP, HSP90AA1, and AKT1, while MD simulations validated the long-term stability of ε-viniferin within the APP binding pocket. Conclusions: These findings provide mechanistic insights into viniferin as a multi-target agent for HCC, justifying further experimental validation in pre-clinical models. Full article

Mono-antibiotic therapy for Helicobacter pylori (H. pylori) infection minimizes unnecessary antibiotic exposure, reduces disruption of the gut microbiota, and lowers the risk of multidrug resistance. Although resistance of H. pylori to amoxicillin remains extremely low (<3%) worldwide, regular-dose amoxicillin monotherapy achieves eradication rates of less than 30%. Strategies to improve the efficacy of amoxicillin-based mono-antibiotic therapy include elevating intragastric pH with potent acid suppression, increasing the amoxicillin dose, and adding bismuth salts to the treatment regimen. This review evaluates the safety and effectiveness of six amoxicillin-based treatments for H. pylori. All regimens lasted 14 days and were studied in clinical trials published between 1 October 2014, and 1 October 2025. The pooled intention-to-treat and per-protocol eradication rates for each regimen were as follows: Regimen 1: Regular-dose amoxicillin + high-dose proton pump inhibitor (PPI): 84.7% (83/98) and 84.7% (83/98); Regimen 2: High-dose amoxicillin + high-dose PPI: 85.3% (3709/4347) and 89.9% (3692/4109); Regimen 3: Regular-dose amoxicillin + high-dose potassium-competitive acid blocker (PCAB): 86.0% (901/1048) and 91.2% (888/974); Regimen 4: High-dose amoxicillin + high-dose PCAB: 88.2% (1771/2009) and 93.5% (1720/1839); Regimen 5: Regular-dose amoxicillin + high-dose PCAB + bismuth: 84.9% (327/385) and 91.3% (327/358); Regimen 6: High-dose amoxicillin + high-dose PCAB + bismuth: 95.8% (115/120) and 98.4% (115/117). In conclusion, potent acid inhibition, escalation of amoxicillin dosage, and incorporation of bismuth can transform amoxicillin mono-antibiotic therapy from an ineffective approach into a highly effective eradication regimen for H. pylori infection. Full article

Objectives: This study aimed to describe the epidemiological and clinical characteristics and the potential risk factors associated with Clostridioides difficile infection (CDI) in a high-complexity healthcare center. Methods: This was a retrospective case–control study conducted from 2020 to 2022 with a cohort of participants aged ≥18 years with diarrhea (more than three liquid stools per day), which included a molecular testing request (the FilmArray Gastrointestinal [GI] PCR Panel) in a high-complexity clinic in Santiago de Cali, Colombia. Controls were randomly selected from the same institutional laboratory database at a 2:1 ratio, matched by age and sex, and required to test negative for C. difficile. Patients from other institutions were excluded to avoid exposure misclassification. Results: Our study included 147 participants (49 cases and 98 controls) and found a 22% infection prevalence among those who underwent molecular testing. When comparing CDI cases with controls, significant differences were observed in the univariate analysis: cases showed longer time to symptom resolution, longer post-diagnosis hospital stay, and greater exposure to in-hospital antibiotics for more than 7 days prior to symptom onset (p < 0.05). Among CDI cases, 55% were healthcare-associated and 18% were classified as severe, with an overall 30-day mortality of 15%. In the multivariate logistic regression model, three variables remained significantly associated with CDI: hospital stay longer than 10 days before symptom onset, antibiotic exposure in the previous 90 days, and in-hospital proton pump inhibitor use. Conclusions: CDI can present a wide range of clinical manifestations, so underdiagnosis should be avoided. Identifying risk factors, particularly in patients with hospital-acquired diarrhea, is crucial. Factors such as a hospital stay longer than 10 days before symptom onset and in-hospital exposure to PPIs or antibiotics in the last 90 days were significant in our study. Early recognition of these risk factors may reduce hospital stay, lower the risk of complications, and optimize healthcare resources. Full article

Background/Objectives: This article employs both in vivo and in vitro experiments. Methods: The core targets and key pathways of Paeoniflorin were predicted using a PPI network analysis, GO analysis, and KEGG analysis. Subsequently, molecular docking analysis and molecular simulation dynamics were performed on the core effector. In vitro experiments employed a UVB-irradiated B16F10 cell model. The effects of Paeoniflorin on melanin content and tyrosinase activity were evaluated. Apoptosis and inflammatory cytokine levels were also assessed in vitro. In vivo experiments used a model combining progesterone injection with UV irradiation. Histopathological skin changes and melanin granule distribution were examined using HE staining. Skin melanin content, tyrosinase activity, and expression levels of related proteins were measured. Additionally, ELISA assays measured serum IL-6 and TNF-α inflammatory cytokines in mice. Results: Rese screening identified 69 targets involved in Paeoniflorin’s effects on melanogenesis, including TNF-α, IL-6, TP53, MAPK3, HIF1A and BCL2. Molecular docking and molecular dynamics simulations indicate that Paeoniflorin exhibits strong affinity for tumor necrosis factor-α. In in vitro experiments, Paeoniflorin significantly reduced UVB-induced melanin content and tyrosinase activity in B16F10 cells. It also promoted melanocyte apoptosis and a dose-dependent decrease in IL-6 and TNF-α levels. In vivo, Paeoniflorin significantly reduced epidermal and dermal thickness and inhibited inflammatory infiltration. It decreased melanin granules, melanin content, tyrosinase activity, and IL-6 and TNF-α levels in mouse skin tissue. Conclusions: This research indicates that Paeoniflorin can significantly suppress UVB-induced cellular inflammatory responses by inhibiting the TNF signaling pathway, thereby reducing hyperpigmentation. Full article

Zinc-L-selenomethionine (Zn-L-SeMet), a novel organic selenium (Se) source, shows great potential in alleviating oxidative stress. This study first evaluated the potential of Zn-L-SeMet to improve the health of weaned piglets and investigated underlying molecular mechanisms. In vivo, 240 weaned piglets were assigned to five dietary groups, namely, a control group (basal diet without Se) and four groups supplemented with Zn-L-SeMet (0.1, 0.2, 0.3, or 0.4 mg Se/kg in basal diet) for 42 days. In vitro, an oxidative stress model was established using hydrogen peroxide (H₂O₂) in porcine intestinal epithelial cells (IPEC-J2) to investigate the mechanisms of Zn-L-SeMet against oxidative damage. The results showed that Zn-L-SeMet improved growth performance, enhanced antioxidant and immune function, stimulated thyroid hormone secretion, and upregulated expression of selenoprotein genes. In vitro, Zn-L-SeMet reduced H₂O₂-induced apoptosis, promoted IPEC-J2 viability, and enhanced activities of antioxidant enzymes, while reducing lactate dehydrogenase release, malondialdehyde and reactive oxygen species levels. Furthermore, Zn-L-SeMet significantly increased the expression levels of Keap1, NQO1, HO-1, ARE, p-Nrf2, p-PI3K, and p-AKT, and protein ratio of p-Nrf2/Nrf2, PI3K/PI3K, and p-AKT/AKT compared to the H₂O₂ group (p < 0.05). In conclusion, Zn-L-SeMet improves health status with antioxidant potential in weaned piglets, and the mechanism is associated with activation of PI3K/AKT and Nrf2/Keap1 pathways. Full article

To enhance the accuracy of wind shear identification by coherent Doppler wind lidar (CDWL), it is necessary to clarify the variation characteristics of CDWL detection results under typical airflow disturbance conditions. This study first numerically simulated typical wind shear fields and generated the Plane Position Indication (PPI) results of CDWL through coordinate projection. Then, it compared the performance of the double-slope algorithm and the least squares algorithm on wind shear identification from the PPI data. The results showed that for wind fields with significant peak characteristics, the double-slope algorithm can more sensitively identify wind shear near the peak, compared with the least square algorithm. In contrast, for wind fields with stable, continuous and linear gradient characteristics, the least squares algorithm can better suppress noise and fit the wind speed gradient changes. Finally, a self-developed long-range CDWL was used to conduct wind shear detection experiments at a plateau airport. After the CDWL beam position was calibrated, its data were compared with those from the anemometer. The “least square + double-slope” scheme was adopted to analyze the typical wind shear case, and the effectiveness and reliability of the identification scheme were verified in combination with an aircraft crew report. Full article

CS is an environmental pollutant everywhere, but we still do not fully know how it hurts our skin. This study integrates LC-MS, network toxicology, molecular docking, and experimental validation in order to understand how CS causes skin involvement at the molecular level. By searching a database, constructing a PPI network and analyzing GO/KEGG, we found 57 candidate targets related to CS-induced skin damage. We found that STAT3, AKT1, TP53, CASP3 and IL-6 play the core roles, and PI3K-Akt, p53, JAK-STAT and apoptosis pathways may be crucial. Molecular docking analysis confirmed strong interactions between components of CS and these key targets. In vitro validation using HaCaT cells showed that CS exposure decreased expressions of STAT3 and AKT, but increased p53, CASP3 and IL-6. The inhibition of PI3K-AKT- and JAK-STAT-related responses, coupled with the initiation of p53-driven apoptosis, led to the observed cytotoxicity, functional impairment, oxidative stress and inflammation, which induced and aggravated skin damage. These findings provide a new perspective on the harmful effects of CS on the skin, providing both a theoretical basis for strengthening regulatory measures to limit exposure and opening new avenues for exploring relevant prevention strategies. Full article

Background: Chrysopogon zizanioides (L.) Roberty (vetiver) is a perennial medicinal grass with deep aromatic roots traditionally used for several ailments. Its root essential oil (CZEO) is rich in phytochemicals with documented antimicrobial, anti-inflammatory, and antioxidant activities. Although its anticancer potential remains underexplored, the complex phytochemical profile of CZEO positions it as a promising multi-target therapy, particularly for colorectal (CRC) and lung cancers where resistance and pathway redundancy often limit conventional treatments. Therefore, this study aimed to investigate the phytochemical composition and antiproliferative activity of CZEO from Qatar against colorectal (HCT-116) and lung (A549) cancer cells and to elucidate its molecular targets and mechanisms of action in CRC and lung cancer using network pharmacology and in silico approaches. Methods: CZEO was extracted by steam distillation and characterized using GC–MS. In vitro proliferation assays with HCT-116 colorectal and A549 lung cancer cells were conducted using the Alamar Blue assay. The ten most abundant phytochemicals identified by GC–MS were assessed for drug-likeness and ADMET properties and further analyzed through network pharmacology, molecular docking, and molecular dynamics (MD) simulations to elucidate the molecular targets and mechanisms underlying CZEO’s anticancer activity. Results: GC-MS profiling identified 40 compounds, predominantly sesquiterpenoids (93%), including khusimol, β-eudesmol, α-vetivone, and rosifoliol. CZEO inhibited cancer cell viability in a dose-dependent manner, with IC₅₀ values of 62.95 ± 2.19 µg/mL for HCT-116 and 167.82 ± 6.51 µg/mL for A549 cells, demonstrating greater potency against colorectal cancer. CZEO did not affect the growth of normal human neonatal fibroblasts (HDFn), suggesting potential selectivity for cancerous cells. ADMET predictions indicated favorable pharmacokinetics and low toxicity of CZEO’s top 10 abundant compounds (TACs). Network pharmacology revealed 373 and 394 overlapping gene targets between TACs and lung and colorectal cancer, respectively. The overlapping genes were used to construct a protein–protein interaction (PPI) network to identify hub genes. STAT3 and AKT1 consistently emerged as common top-scoring hub genes in both cancers. Molecular docking of TACs showed strong binding affinities of rosifoliol and α-vetivone to AKT1 (−6.20 and −5.93 kcal/mol, respectively) and STAT3 (−5.19 and −5.09 kcal/mol, respectively), surpassing reference inhibitors. MD simulations confirmed stable ligand–protein interactions and structural stabilization, particularly with α-vetivone. Conclusions: CZEO from Qatar exhibits potent antiproliferative activity against colorectal and lung cancer cells, supported by a sesquiterpenoid-rich phytochemical profile. Integrative computational analyses highlight AKT1 and STAT3 as key molecular targets, with rosifoliol and α-vetivone emerging as promising lead compounds. These findings support CZEO as a natural, multi-target anticancer agent, warranting further mechanistic and in vitro and in vivo validation. Full article