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Results for “Experimental validation”

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At least 19 recordsLinked to original sources

PubMed2026

PCSK9 as a Key Gene of Metastasis in Lung Adenocarcinoma: A Multi-omics and Experimental Validation Study.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common form of lung cancer. Proprotein convertase subtilisin/kexin type 9 (PCSK9) is abnormally expressed in various tumor tissues and is associated with malignant phenotypes. However, the clinical significance, function, and mechanism of LUAD invasion and metastasis remain unclear. METHODS: We retrospectively enrolled 100 patients with LUAD in this study. Initially, qRT-PCR was performed to detect PCSK9 levels in clinical tissues. Subsequently, bioinformatics analysis of scRNA-seq and The Cancer Genome Atlas Program (TCGA) datasets was performed to predict the role of PCSK9 in tumor cell malignancy and its potential downstream pathways. These predictions were validated experimentally using the CCK-8 assay, TUNEL staining, wound healing, transwell invasion assay, and an in vivo lung metastasis model. Finally, Western blotting and an AKT inhibitor (MK2206) were used to verify the underlying mechanism. RESULTS: PCSK9 was significantly upregulated in LUAD tissues compared to paracancerous tissues and was associated with poorer OS and DFS. Bioinformatics analysis of scRNA-seq data and TCGA analysis predicted that PCSK9 is highly enriched in tumor cells and is involved in EMT, and that the PI3K/AKT pathway plays a significant role in LUAD development. Experiments confirmed that PCSK9 markedly promoted LUAD cell proliferation, migration, and invasion in vitro and lung metastasis in vivo. PCSK9 overexpression significantly upregulated p-AKT, p-PI3K, and p-mTOR levels. Furthermore, the AKT inhibitor, MK2206, reversed the promoting effects of PCSK9. CONCLUSIONS: PCSK9 expression is associated with the prognosis and diagnosis of LUAD. This molecule activates the PI3K/AKT signaling pathway, thereby driving invasion, metastasis, and proliferation in LUAD.

Humans↗

PubMed2026

Proteome-wide curation of experimentally validated HPV T-cell epitopes identifies key gaps in our understanding of cellular immunity to HPV and informs vaccine design.

BACKGROUND: Human papillomavirus (HPV) drives both malignant and benign tumours. Current prophylactic vaccines are type-restricted, not optimised for T-cell induction, and lack therapeutic efficacy. Although T-cells are critical for both preventing and clearing HPV infection, experimentally validated HPV T-cell epitopes remain fragmented across the literature, limiting systematic evaluation of cellular immune targets. METHODS: We curated experimentally validated HPV T-cell epitopes from the Immune Epitope Database (IEDB). Epitopes were mapped across HPV proteins and genotypes, and analysed for response rate, sequence conservation across 454 representative HPV genomes, and HLA restriction patterns. RESULTS: 485 unique experimentally validated HPV epitopes have been described (133 studies; 1,494 functional assays). Consistent with research focus and viral biology, E6 and E7 proteins account for >60% of known HPV epitopes despite accounting for ~10% of the viral proteome. High-risk HPV types, especially HPV16 and HPV18, were the most studied (p <.001) and were enriched for CD8+ epitopes (p <.001). We identified major knowledge gaps, including: underrepresentation of structural proteins such as L2; limited epitope coverage for low-prevalence HPV genotypes; a bias towards common HLA alleles. In silico analysis indicated greater conservation of epitopes in L1/L2 and across high-risk HPV types. Conserved, commonly detected, and HLA-promiscuous epitopes were highlighted and we provide panels of candidate epitopes for consideration in immune monitoring, broad-spectrum prophylactic vaccines, and high-risk targeted therapeutic vaccines. CONCLUSION: This study provides the first comprehensive atlas of experimentally validated HPV T-cell epitopes and ranked epitope candidates for translational application. We demonstrate that our understanding of HPV T-cell immunity is constrained by biases in antigen, genotype and HLA focus and by incomplete epitope mapping. Addressing these gaps will be essential for a comprehensive assessment of cellular immunity and for utilising T-cells in next-generation vaccines.

Epitopes, T-Lymphocyte↗

PubMed2026

Network pharmacological and experimental validation of the mechanism of Chaihu Guizhi Ganjiang decoction regulating T helper cell 17/regulatory T cell balance to improve autoimmune hepatitis.

OBJECTIVE: To elucidate the therapeutic efficacy and mechanism of action of Chaihu Guizhi Ganjiang decoction (, CGGD) in autoimmune hepatitis. METHODS: CGGD components and potential target genes were extracted from previously published databases. The autoimmune hepatitis (AIH)-related regulatory genes were obtained from the DisGeNET database. Intersections were taken, and enrichment analyses were performed on the extracted data. Concanavalin A (ConA)-induced AIH model mice were treated with CGGD via gavage. The results of network pharmacological analysis were experimentally validated. RESULTS: Network pharmacology revealed 228 genes at the intersection of AIH and CGGD. Kyoto Encyclopedia of Genes and Genomes analysis revealed that CGGD primarily regulates the phosphoinositide 3-kinase (PI3K)/ protein kinase B (AKT) signaling pathway and cellular metabolism in AIH. Gene Ontology enrichment analysis revealed that CGGD modulates inflammation through transcription factor-mediated signaling pathways. As predicted, CGGD attenuated ConA-induced AIH in a dose-dependent manner by activating the PI3K/AKT signaling pathway. Histopathological assessment confirmed the protective effects of CGGD against ConA-induced AIH. Further investigation revealed that CGGD regulated the T helper cell 17 (Th17)/regulatory T cell (Treg) balance by modulating the PI3K/Akt/ nuclear factor kappa-B (NF-κB) pathway. CONCLUSIONS: This study demonstrated the therapeutic effect of CGGD on AIH through a combination of network pharmacological prediction and experimental validation. Its mechanism of action involves PI3K/Akt/ NF-κB-mediated regulation of Th17/Treg cells.

Animals↗

PubMed2025

Integrated network pharmacology, molecular docking and experimental validation to investigate the mechanism of tannic acid in nasopharyngeal cancer.

Tannic acid (TA) is the primary bioactive component in the gallnut (Galla chinensis) and has exhibited the anticancer effects. However, the mechanism of its anti-cancer activity in nasopharyngeal carcinoma (NPC) remains unclear. This research aims to explore the underlying mechanism of TA in the treatment of nasopharyngeal cancer using network pharmacology, molecular docking and experimental validation. Firstly, the targets of TA and NPC were predicted and collected through databases, and the intersection targets were identified. Subsequently, protein-protein interaction (PPI) network analysis, Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes Genomes (KEGG) pathway enrichment analysis, molecular docking and molecular dynamics (MD) simulation were conducted to uncover the potential mechanisms of TA in treatment of NPC. Finally, in vitro experiments were utilized to verify the mechanism of TA with anticancer activity in NPC. The results of network pharmacology revealed 42 intersection targets between NPC-related targets and TA-related targets. The phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signaling was identified as the main target pathway of TA against NPC. Additionally, molecular docking and MD simulation confirmed the closely binding affinities of TA with AKT1. Furthermore, the results of in vitro experiments demonstrated that TA exerts anticancer activity against NPC by targeting the PI3K/AKT signaling pathway, leading to the suppression of cell proliferation. TA is a promising therapeutic candidate for NPC through PI3K/AKT signaling pathway. These results provide insights into the clinical application of TA, particularly when considered in combination with other therapeutic modalities.

Molecular Docking Simulation↗

PubMed2025

Experimental Validation of Genome-Environment Associations in Arabidopsis.

Identifying the genetic basis of local adaptation is a key goal in evolutionary biology. Allele frequency clines along environmental gradients, known as genotype-environment associations (GEA), are often used to detect potential loci causing local adaptation but are rarely followed by experimental validation. Here, we tested loci identified in three moisture-related GEA studies on Arabidopsis. We studied 42 GEA-identified genes using t-DNA knockout lines under drought and tested effects on flowering time, an adaptive trait, and genotype-by-environment (GxE) interactions for performance and fitness. In total, 16/42 genes had significant effects on traits involved in local adaptation or performance responses to the environment. We found that wrky38 mutants had significant GxE effects for fitness; lsd1 plants had a significant GxE effect for flowering time, and 11 genes showed flowering time effects with no drought interaction. However, most GEA candidates did not exhibit GxE. In the follow-up experiments, wrky38 caused decreased stomatal conductance and specific leaf area under drought, indicating potentially adaptive drought avoidance. Additionally, GEA identified natural putative LoF variants of WRKY38 associated with dry environments, as well as alleles associated with variation in LSD1 expression. While only a few GEA-identified genes were validated for GxE interactions for fitness, we likely overlooked some genes because experiments might not well represent natural environments and t-DNA insertions might not well represent natural alleles. Nevertheless, GEAs apparently identified some genes contributing to local adaptation. GEA and follow-up experiments are straightforward to implement in model systems and demonstrate prospects for GEA discovery of new local adaptations.

Arabidopsis↗

PubMed2026

Integrated dual transcriptome sequencing and experimental validation reveal potential mechanisms of baicalin against pneumocystis pneumonia in immunosuppressed rats.

BACKGROUND: Pneumocystis pneumonia (PCP) remains a major cause of morbidity and mortality in immunocompromised individuals. Although baicalin (Ba), a natural bioactive flavonoid, has demonstrated protective and therapeutic effects against PCP, its molecular mechanisms remain undefined. We employed dual RNA sequencing (dual RNA-seq) to characterize host and pathogen transcriptional responses to Ba treatment in an immunosuppressed rat model of PCP. METHODS: Comparative transcriptomic analyses identified differentially expressed genes in both the host and Pneumocystis, followed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analyses. Candidate targets were further investigated using network pharmacology, protein-protein interaction analysis, molecular docking, and molecular dynamics simulations. Key findings were validated by immunohistochemistry, enzyme-linked immunosorbent assay, and quantitative PCR. RESULTS: Ba markedly remodeled host and pathogen transcriptomes. Host transcriptomic analyses showed that Ba attenuated inflammatory and oxidative stress responses by modulating immune-related pathways, including Toll-like receptor, NF-κB, cytokine-cytokine receptor interaction, chemokine signaling, Th17 cell differentiation, and antigen processing and presentation. Experimental validation demonstrated that Ba reduced pulmonary expression of indoleamine 2,3-dioxygenase 1 (IDO1), Toll-like receptor 2 (TLR2), and TLR4 while increasing nuclear factor erythroid 2-related factor 2 (Nrf2) and its downstream antioxidant enzyme heme oxygenase-1 (HO-1). Pathogen transcriptomic analysis identified Pneumocystis Rtt109 (PcRtt109), a fungal histone acetyltransferase, as a potential pathogen-specific target that was significantly downregulated after Ba treatment. Molecular docking and molecular dynamics simulations supported stable interactions between Ba and IDO1, Nrf2, TLR2, TLR4, and PcRtt109, with the strongest predicted binding observed for PcRtt109. CONCLUSION: Dual RNA-seq revealed that Ba exerts anti-PCP activity through coordinated modulation of host and pathogen molecular networks. Its therapeutic effects are associated with suppression of inflammatory signaling, enhancement of antioxidant defenses, and inhibition of a fungal virulence-associated target. These findings provide mechanistic insights into host-pathogen interactions during PCP and support Ba as a potential therapeutic candidate for PCP.

Nrf2↗

PubMed2026

Multi-omics and experimental validation identify RAPGEF2 as a protective prognostic biomarker in clear cell renal cell carcinoma.

Kidney Renal Clear Cell Carcinoma (KIRC) is characterized by marked molecular heterogeneity and metabolic reprogramming, underscoring the need for reliable biomarkers for prognostic assessment and individualized treatment. RAPGEF2, a guanine nucleotide exchange factor has been implicated in cell adhesion and differentiation, but its role in KIRC remains unclear. In this study, we systematically evaluated the expression pattern, prognostic significance, genomic associations, biological function, and therapeutic relevance of RAPGEF2 in KIRC through integrated multi-omics analyses and experimental validation. Pan-cancer single-cell and Spatial transcriptomic analysis revealed heterogeneous RAPGEF2 expression across tumor types, with a relatively prominent signal in KIRC, where RAPGEF2 was mainly enriched in endothelial cells. Survival analyses in the TCGA-KIRC showed that high RAPGEF2 expression was significantly associated with favorable overall survival, disease-specific survival, and progression-free interval, and these findings were validated in independent ICGC_RECA-EU and E-MTAB-1980 cohorts. Multivariate Cox regression further confirmed RAPGEF2 as an independent protective prognostic factor. Immunohistochemistry in a tissue microarray cohort demonstrated that higher RAPGEF2 protein expression was associated with improved overall survival. Genomic analyses showed that low RAPGEF2 expression was related to higher mutational burden. Functional assays demonstrated that RAPGEF2 knockdown promoted KIRC progression. Enrichment analyses indicated that RAPGEF2 may be associated with metabolic pathway remodeling, while immunotherapy cohort analyses suggested its potential association with therapeutic benefit. Collectively, RAPGEF2 is identified as a protective prognostic biomarker and potential functional regulator in KIRC.

Biomarker↗

PubMed2026

HNRNPC as a Novel Therapeutic Target for Ischemic Heart Disease: Evidence From Mendelian Randomization and Experimental Validation.

BACKGROUND: Several studies have suggested that N6-methyladenosine (m6A) plays an essential role in cardiovascular disease, but the causality of m6A on ischemic heart disease (IHD) remains unknown. Therefore, this study investigated the potential relationship between m6A and IHD using a 2-sample Mendelian randomization method. METHODS: The publicly available genome-wide association study data for m6A-related proteins were obtained from the INTERVAL study, a large population-based cohort of healthy blood donors in the United Kingdom, whereas the genome-wide association study database (including 30 952 cases and 187 840 healthy controls) provided the IHD data. We performed a 2-sample Mendelian randomization analysis to evaluate the potential causal association between HNRNPC (heterogeneous nuclear ribonucleoprotein C) and IHD, followed by experimental validation in vitro and in vivo to confirm the role of HNRNPC in IHD pathogenesis. RESULTS: There was no indication of pleiotropy or heterogeneity among the 6 m6A-associated proteins, but Mendelian randomization analysis revealed that HNRNPC (odds ratio [OR], 0.93 [95% CI, 0.88-0.97]; P=0.002) was associated with IHD. When IHD developed, there was a significant upregulation of HNRNPC expression in both animal and cellular tests. HNRNPC knockdown prevented oxidative stress, mitochondrial dysfunction, and cell death. CONCLUSIONS: The Mendelian randomization study suggests a potential causal association of the m6A-related protein HNRNPC in the cause of IHD and verified the accuracy of the results through a series of experiments, which will help us understand the pathogenesis of IHD and identify potential therapeutic targets in the future.

Humans↗

PubMed2025

Mechanism of Qigu capsule as a treatment for sarcopenia based on network pharmacology and experimental validation.

OBJECTIVE: To explore the potential molecular mechanism of Qigu capsule (，QGC) in the treatment of sarcopenia through network pharmacology and to verify it experimentally. METHODS: The active compounds of QGC and common targets between QGC and sarcopenia were screened from databases. Then the herbs-compounds-targets network, and protein-protein interaction (PPI) network was constructed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed by R software. Next, we used a dexamethasone-induced sarcopenia mouse model to evaluate the anti-sarcopenic mechanism of QGC. RESULTS: A total of 57 common targets of QGC and sarcopenia were obtained. Based on the enrichment analysis of GO and KEGG, we took the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt) signaling pathway as a key target to explore the mechanism of QGC on sarcopenia. Animal experiments showed that QGC could increase muscle strength and inhibit muscle fiber atrophy. In the model group, the expression of muscle ring finger-1 and Atrogin-1 were increased, while myosin heavy chain was decreased, QGC treatment reversed these changes. Moreover, compared with the model group, the expressions of p-PI3K, p-Akt, p-mammalian target of rapamycin and p-Forkhead box O3 in the QGC group were all upregulated. CONCLUSION: QGC exerts an anti-sarcopenic effect by activating PI3K/Akt signaling pathway to regulate skeletal muscle protein metabolism.

Sarcopenia↗

PubMed2026

Multi-Omics Integration Identifies a Five-Gene Metabolic Signature With Experimental Validation in Clear Cell Renal Cell Carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is hallmarked by profound metabolic reprogramming; however, its intricate crosstalk with the tumor immune microenvironment (TIME) and its clinical ramifications remain inadequately elucidated. This study aims to systematically decipher the metabolic-immune interplay in ccRCC through multi-omics integration, with the goal of identifying robust prognostic biomarkers and actionable therapeutic vulnerabilities. AIMS: This study aims to systematically decipher the metabolic-immune interplay in clear cell renal cell carcinoma (ccRCC) through multi‑omics integration, and to identify robust prognostic biomarkers and actionable therapeutic vulnerabilities that can inform precision risk stratification and individualized treatment strategies. METHODS: We integrated bulk transcriptomic, genomic, and clinical data from multiple ccRCC cohorts. Differential expression and functional enrichment analyses were performed to characterize metabolic pathway alterations. Mendelian randomization (MR) was employed to infer causal relationships between metabolic disorders and ccRCC risk. A machine learning-based prognostic framework, incorporating SHAP (SHapley Additive exPlanations) for feature interpretability, was constructed and rigorously validated. TIME heterogeneity was dissected using deconvolution algorithms, while drug sensitivity, tumor mutation burden (TMB), and TIDE scores were utilized to assess therapeutic responses and immune evasion. Candidate gene function was evaluated through in vitro gain- and loss-of-function assays, with expression validated via TCGA, HPA, western blot, and qRT-PCR. RESULTS: Enrichment analysis identified coordinated dysregulation in lipid metabolism, energy homeostasis, and hypoxia response pathways. MR analysis confirmed lipid metabolism disorders as a causal risk factor for ccRCC. Our machine-learning model, centered on five core SHAP-identified features (SUCLA2, ACAT1, PC, SUCLG1, and HMGCS2), demonstrated superior predictive accuracy over conventional clinical staging. Immune profiling unveiled dichotomous TIME states: the low-risk group retained active immune surveillance, whereas the high-risk group was enriched with immunosuppressive subsets. Drug sensitivity screening pinpointed LY2109761 and carmustine as high-risk-specific candidate agents. Furthermore, TMB and TIDE analyses stratified high-risk patients displaying genomic instability and immune evasion phenotypes. Functionally, SUCLA2 knockdown significantly enhanced ccRCC cell proliferation and invasion, while its overexpression suppressed these malignant phenotypes, corroborating its tumor-suppressive role. Expression patterns of the hub genes were consistently validated across multi-level datasets and experimental assays. CONCLUSION: This study establishes a precision oncology framework for ccRCC by functionally linking metabolic biomarkers, immunophenotypes, and stratified therapeutic strategies. Importantly, we identify SUCLA2 as a potential functional tumor suppressor and a promising target for further mechanistic and translational investigation.

Humans↗

PubMed2026

Network pharmacology-based prediction and experimental validation of the anti-hyperuricemic effects of oolong tea polyphenols.

OBJECTIVE: This study aimed to identify candidate therapeutic targets of oolong tea polyphenols (TP) against hyperuricemia (HUA) using network pharmacology and bioinformatics, and to validate the predicted molecular mechanism through in vivo experimentation. METHODS: Drug and disease targets were retrieved from public databases, and overlapping targets were identified by Venn diagram analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on the shared targets, and a protein-protein interaction (PPI) network was constructed to identify hub genes. For in vivo validation, an HUA mouse model was established by 15 days of oral potassium oxonate (PO) administration. Model mice then received TP by gavage at low (0.5 g⋅kg-1⋅d-1), medium (1 g⋅kg-1⋅d-1), or high (2 g⋅kg-1⋅d-1) doses for an additional 15 days. Serum biochemical markers, histopathological changes, and pathway-related protein expression were assessed by enzyme-linked immunosorbent assay (ELISA), hematoxylin and eosin (HE) staining, and western blot analysis, respectively. RESULTS: Network pharmacology analysis identified 59 overlapping targets between TP and HUA; GO and KEGG enrichment analyses revealed that these targets were primarily associated with hormone metabolism and the PI3K-AKT signaling pathway. In the animal experiment, TP dose-dependently reduced serum uric acid (SUA) levels in hyperuricemic mice. At the molecular level, low and medium doses of TP suppressed phosphorylation of phosphatidylinositol 3-kinase (PI3K), protein kinase B (AKT), and mammalian target of rapamycin (mTOR), whereas the high dose paradoxically activated this pathway and concomitantly elevated interleukin-1β levels. These findings indicate that TP modulates uric acid metabolism through a non-monotonic, dose-dependent mechanism. CONCLUSION: By combining network pharmacology with animal experiments, this study identified the PI3K/AKT/mTOR signaling pathway as a likely mediator of the anti-hyperuricemic action of oolong tea polyphenols (TP). A medium dose of TP achieved the most balanced outcome, attenuating inflammation and preserving hepatic and renal architecture; the high dose, by contrast, paradoxically elevated interleukin-1β (IL-1β) and overactivated PI3K/AKT/mTOR signaling, underscoring the importance of dose calibration. These data suggest that a medium dose of TP may represent a feasible dietary strategy against hyperuricemia. Further work-including monomer identification, direct target validation, and clinical evaluation-is warranted to confirm and extend these preclinical findings.

PI3K/Akt/mTOR signaling pathway↗

PubMed2026

Targeting EGFR in cancer using Terminalia arjuna: An integrated In Silico, molecular dynamics, experimental validation, and network pharmacology study.

The Epidermal Growth Factor Receptor (EGFR) plays a pivotal role in 20-60% of cancer cases, including glioblastoma, lung adenocarcinoma, and head and neck squamous cell carcinoma, as reported in The Cancer Genome Atlas (TCGA) dataset. The present study employed an integrated in silico and experimental workflow to evaluate EGFR-targeted compounds from Terminalia arjuna. Drug-likeness and ADMET screening were performed, followed by molecular docking and 1000 ns molecular dynamics simulations. In vitro validation was conducted using cancer cell-based assays and network pharmacology to explore the molecular mechanisms associated with the identified compound. Screening shortlisted eight compounds from T. arjuna. Molecular docking identified Arjunaside C (-8.2 kcal/mol), Arjunapthanoloside (-7.7 kcal/mol), and Beta-sitosterol (-7.4 kcal/mol) as potential EGFR inhibitors compared to Erlotinib (-6.6 kcal/mol). Arjunapthanoloside formed more H-bonds and exhibited most stable interactions with EGFR. MD simulations at 1000 ns revealed lower RMSD, RMSF, SASA, and Rg values for the Arjunapthanoloside-EGFR complex, indicating enhanced stability. Direct binding validation was limited by the unavailability of purified Arjunapthanoloside; therefore, Arjuna extract was evaluated, which demonstrated potent cytotoxicity with an IC₅₀ of 9 µg/mL in H357 oral cancer cells. Flow cytometry confirmed apoptosis-mediated cell death by increased early- and late-apoptotic cell populations. Network pharmacology analysis further identified additional targets (MMP3, MMP7, MMP9, and HRAS) that are directly involved in various cancers. Overall, the findings provide new insights into the therapeutic potential of Arjunapthanoloside as a stable compound that interacts with EGFR from T. arjuna, highlighting its significance in EGFR-targeted anticancer research.

ErbB Receptors↗

PubMed2026

Effects and mechanisms of Stauntonia brachyanthera Hand.-Mazz against Alzheimer's disease through network pharmacology and experimental validation.

Stauntonia brachyanthera Hand.-Mazz. (SB), a traditional medicinal plant of the Dong ethnic group with nutraceutical applications, exhibits broad-spectrum pharmacological activity. However, the therapeutic effects and mechanisms of SB on Alzheimer's disease (AD) remain unclear. This study aims to investigate the neuroprotective potential and underlying mechanisms of SB against AD. We utilized network pharmacology and molecular docking to predict the active components, targets, and pathways of SB associated with AD treatment. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were further used to identify potential therapeutic targets and underlying mechanisms of SB in relation to AD. Then, the neuroprotective effects, neuronal differentiation-promoting activity and potential mechanism of key active components of SB on the main therapeutic targets were verified by in vitro experiments. The network pharmacological prediction results showed that the treatment of AD with SB was closely related to MAPK and PI3K/Akt pathways. Further experiments showed that the SB active component kaempferol (KMF) alleviated Aβ1-42-induced injury and promoted neuronal differentiation. Additionally, we found that KMF-mediated promotion of neuronal differentiation in N2a cells was dependent on the PI3K/Akt and MAPK pathways. In this study, we employed a combined computational-experimental approach to elucidate the neuroprotective mechanisms of SB against Alzheimer's disease. We further validated KMF as a key active component of SB that alleviates Aβ1-42-induced injury and promotes neuronal differentiation through the PI3K/Akt and MAPK pathways.

Alzheimer's disease↗

PubMed2026

Integrated network pharmacology, molecular docking, and experimental validation to reveal the potential mechanism of Ginsenoside Rg1 on chronic obstructive pulmonary disease.

Ginsenoside Rg1 (GS Rg1), a natural flavonoid exhibiting anti-inflammatory and antioxidant properties, holds significant potential for treatment chronic obstructive pulmonary disease (COPD). Nevertheless, the precise mechanisms underlying its therapeutic effects remain to be fully elucidated. This study aimed to explore the role and potential mechanism of GS Rg1 in the treatment of COPD using network pharmacology, molecular docking, and experimental validation.Targets related to GS Rg1 and COPD were screened from public databases, and the potential common targets were then imported into the STRING database to construct a protein-protein interaction (PPI) network. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis were performed to identify key signaling pathways. Molecular docking was employed to predict the binding interactions between GS Rg1 and core targets. A BEAS-2B cell model induced by lipopolysaccharide(LPS) and cigarette smoke extract(CSE) was used to explore the protective mechanisms of GS Rg1. Western blot analysis was conducted to validate the critical targets and pathways involved in the anti-COPD effects of GS Rg1. Network pharmacology analysis revealed 105 common targets between GS Rg1 and COPD. The EGFR/PI3K/AKT and EGFR/STAT3 signaling pathways were selected for further validation. GS Rg1 was demonstrated to effectively inhibit inflammation and mucus hypersecretion in vitro models of COPD. Western blot results showed that GS Rg1 treatment significantly downregulated the expression of proteins involved in the EGFR/PI3K/AKT and EGFR/STAT3 signaling pathway, consistent with the network pharmacology findings. CSE/LPS exposure induces inflammation and oxidative stress in COPD by disrupting the EGFR/PI3K/AKT and EGFR/STAT3 signaling pathways, and GS Rg1 significantly alleviates these effects, which may be partially through regulating the EGFR/PI3K/AKT and EGFR/STAT3 signaling pathway.

Ginsenosides↗

PubMed2026

Experimental validation of an AI-driven digital healthcare platform for oral health behavior and plaque assessment among vietnamese children.

BACKGROUND: Oral health among children in developing countries, including Vietnam, remains a significant public health concern. Innovative approaches leveraging artificial intelligence AI-based digital health platforms may offer effective strategies for managing dental plaque and promoting better oral hygiene behaviors among school-aged children. This study aimed to evaluate the effectiveness of an AI-driven oral healthcare platform (Denti-i Vietnam) in improving oral hygiene and behavioral outcomes among Vietnamese primary school students. METHODS: A total of 204 primary school students aged 8-10 years in Hanoi, Vietnam, participated in this experimental study. Participants were randomly assigned to an intervention group (n = 107), which used the AI-driven oral healthcare platform, and a comparison group (n = 97), which received traditional oral health education via pamphlets. Oral health behaviors, dental plaque levels (Simplified Oral Hygiene Index; OHI-S), and caries indices (dft/DMFT) were assessed at baseline and after the intervention period. RESULTS: The intervention group demonstrated a significant reduction in the OHI-S score compared to baseline (2.49 ± 0.60 to 1.70 ± 0.76, p < 0.001), particularly in the debris component, indicating enhanced plaque control. Notable improvements were also observed in oral hygiene behaviors, including increased frequency of toothbrushing before and after breakfast (p < 0.01) and more frequent parental assistance during brushing (p = 0.03). Furthermore, parental awareness of dental caries significantly increased in the intervention group (p = 0.001). CONCLUSIONS: The AI-driven oral healthcare platform significantly improved both oral hygiene behaviors and plaque control among Vietnamese primary school children. These findings suggest that AI-driven digital health tools can serve as practical and scalable solutions for promoting oral health in developing countries.

Humans↗

PubMed2026

Bioinformatics Analysis and Experimental Validation of Key Genes Associated With Hypoxia and Ischemia in Myocardial Infarction.

BACKGROUND: This study aimed to screen and identify core hypoxia-ischemia-related genes associated with myocardial infarction (MI). METHOD: Two transcriptomic datasets, GSE97320 and GSE48060, were retrieved from the Gene Expression Omnibus (GEO) database. After data integration and batch effect elimination, differential expression analysis was performed to screen differentially expressed genes (DEGs), and the corresponding visualization analysis was conducted. Hypoxia-ischemia-related genes were acquired from the GeneCards database; hypoxia-ischemia related genes (HIRGs) were subsequently identified by intersecting the retrieved genes with screened DEGs. Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were implemented to explore the biological functions and underlying signaling pathways of HIRGs. A combination of protein-protein interaction (PPI) network analysis and random forest (RF) algorithm was applied to screen hub genes from HIRGs. The external GEO dataset GSE66360 was utilized to validate the expression patterns of candidate hub genes. Furthermore, an acute myocardial infarction (AMI) mouse model was established, and quantitative real-time polymerase chain reaction (qPCR) was performed to detect the mRNA expression levels of hub genes in myocardial tissues for in vivo validation. RESULTS: A total of 633 DEGs and 308 hypoxia-ischemia-related genes were screened in the present study, among which 21 overlapping HIRGs were obtained. PLAUR and IL1B were finally identified as two hub genes from HIRGs based on PPI network and random forest algorithm. The qPCR results revealed that the expression levels of PLAUR and IL1B were significantly upregulated in the AMI group compared with the sham operation group (p < 0.05). CONCLUSION: The present findings demonstrated that PLAUR and IL1B serve as pivotal genes involved in the pathological hypoxia-ischemia process of AMI. These two genes may act as novel biomarkers and promising therapeutic targets for the recognition and clinical intervention of hypoxia-ischemia injury following AMI.

Myocardial Infarction↗

PubMedDate not supplied

Experimental validation of methods for the measurement of coronary sinus blood flow in man.

The measurement accuracy of clinically applicable methods for blood flow measurement in coronary sinus -- continuous local thermodilution (LTD), differential pressure (DP), ultrasonic Doppler (US) and the electromagnetic flow measurement method (EMF) -- was examined in 15 anaesthetized closed chest dogs with left ventricle weights between 150 and 200 g. The LTD, DP, US and the EMF were examined in each experiment in the two following arrangements. 1. In coronary sinus -- left jugular vein by-pass: This arrangement allowed four reference methods for measurement of coronary sinus blood flow (CBF). 2. In "clinical" position, without by-pass, which allowed two reference methods for CBF measurements. The results on the measurement accuracy of the LTD, DP and US are, depending on the measurement arrangement, contradictory. In the by-pass arrangement 1 there was observed a good agreement of the LTD, DP and US CBF values with the reference values. In the "clinical" position, without by-pass 2 the measurement accuracy of LTD was not sufficient for exact measurement of CBF and derived parameters. The examined velocity tip flow probes (US, DP) gave no correlation with the reference methods. US and DP are even for semiquantitative estimation of CBF unsuitable. The EMF tip flow probe was for the CBF measurement unsuitable, because of disturbance by the electrical activity of myocardium.

Animals↗

PubMed1978

Noninvasive assessment of coronary stenoses by myocardial perfusion imaging during pharmacologic coronary vasodilatation. I. Physiologic basis and experimental validation.

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Animals↗