Chronic urticaria (CU), a prevalent and often debilitating allergic skin disorder, is primarily triggered by mast cell degranulation. Danggui Yinzi (DGYZ), a traditional Chinese medicine formula, has been employed to treat pruritic conditions. However, the molecular mechanisms underlying its effects in CU remain unclear. This study aimed to investigate the immunopharmacological mechanisms of DGYZ in CU, hypothesizing that it modulates immune responses through its bioactive components, which is critical for the development of novel therapeutic agents.

Ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS) was used to identify the active compounds in DGYZ. In vivo, BALB/c mouse models of DNP-IgE/DNFB-induced CU were established and grouped into Normal Control (NC), Model, various-dose DGYZ, and Loratadine groups. Post-treatment, immunopharmacological parameters were assessed, and skin tissue was collected for histopathological analysis, mast cell quantification, and immunohistochemistry to evaluate the impact on immune cells and molecules. Serum levels of inflammatory cytokines (TNF-α, IL-6) were quantified using ELISA kits. In vitro, the human mast cell line LAD2 was pretreated with key active components of DGYZ (Quercetin and Paeoniflorin) at different concentrations before mast cell degranulation was induced. Degranulation markers (β-HEX, HIS) and the expression of proteins in immune-related signaling pathways (PI3K-Akt, TLR4) were then measured.

A total of 38 active components were identified in DGYZ. In vivo, DGYZ inhibited mast cell degranulation, blue spot reactions, and skin damage in mice. It also decreased the levels of inflammatory cytokines (TNF-α, IL-6) and suppressed the activation of associated signaling pathways. In vitro, both Quercetin and Paeoniflorin reduced mast cell degranulation and the activation of TLR4 and PI3K-Akt pathways.

This study, employing UPLC-Q-TOF-MS and both in vivo and in vitro experiments, provides a comprehensive analysis of the mechanism of DGYZ in CU. The findings indicate that DGYZ exerts therapeutic effects in CU by modulating immune responses. This research lays the foundation for a deeper understanding of its immunopharmacological mechanisms, potentially aiding the development of novel drugs and therapeutic strategies for CU management.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. Targeted therapies hold promise for HCC treatment, and understanding the molecular mechanisms of action is crucial for developing novel therapeutic strategies. Polyphyllin I, a natural compound with known antitumor activity, represents a potential therapeutic candidate.

This study employed a network pharmacology approach to investigate the anti-HCC effects of Polyphyllin I and its underlying mechanisms. Drug and disease related targets were identified and intersected to construct Components-Gene Symbols-Disease and Protein-Protein Interaction networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Molecular docking simulations were conducted to explore the interactions between Polyphyllin I and key pathway proteins (VEGF-C and β-catenin). Finally, in vitro and in vivo experiments validated the anti-HCC effects and underlying mechanisms of Polyphyllin I.

Network pharmacology analysis revealed that Polyphyllin I targets multiple genes and pathways implicated in HCC development and progression. GO and KEGG analyses identified significant enrichment of pathways related to cell proliferation, apoptosis and angiogenesis, including VEGF and the Wnt/β-catenin signaling pathways. Molecular docking simulations demonstrated strong binding affinities between Polyphyllin I and VEGF-C and β-catenin. In vitro and in vivo experiments confirmed that Polyphyllin I effectively inhibits HCC cell proliferation, induces apoptosis, and suppresses angiogenesis, potentially by modulating the VEGF-C and Wnt/β-catenin signaling pathways.

The study provides compelling evidence for the antitumor activity of Polyphyllin I in HCC and elucidates its possible molecular mechanisms, suggesting that Polyphyllin I holds great potential as a therapeutic agent for HCC.

Huatanhuoxue Decoction (HTHX) is a traditional Chinese formula consisting of nine herbs. It is used to improve obesity-related asthma symptoms and reduce airway inflammation.

To study HTHX effects on airway inflammation in obese asthmatic mice via the IL-17 A signaling pathway.

Network pharmacology was used to predict the bioactive ingredients in HTHX. Subsequently, an obese asthma model was established by high-fat diet feeding and exposure to house dust mite. The effects of HTHX on obesity-related asthma progression were investigated using histopathological examinations, airway hyperresponsiveness determinations, and enzyme-linked immunosorbent assays. The mechanism of action of HTHX was confirmed by Western blots, flow cytometry, immunohistochemistry, and immunofluorescence analyses.

HTHX alleviated the development in obese asthma mice by improving the pathological condition of lung tissue, airway hyperresponsiveness, and inflammatory factors. Network pharmacology identified the involvement of the IL-17 signaling pathway. HTHX decreased the production of neutrophils and the expression of NETs in lung tissue. HTHX also reduced group 3 innate lymphoid cells and Th17 cells, which are responsible for producing IL-17 A. The production of IL-17 A-related protein was also suppressed. The results indicate that HTHX inhibited the excessive activation of the IL-17 A signaling pathway.

HTHX alleviated airway inflammation by regulating the IL-17 A signaling pathway in obese asthmatic mice.

Fatigue is a widespread condition associated with various health issues, yet identifying specific bioactive compounds for its management remains challenging. This study integrates network pharmacology and molecular docking to uncover essential oil-derived compounds with potential antifatigue properties by targeting key genes and molecular pathways. A comprehensive analysis of 872 essential oil compounds was conducted using PubChem, with target prediction via SwissTargetPrediction. The protein-protein interaction (PPI) network and KEGG pathway analysis identified core fatigue-related targets, including ALB, BCL2, EGFR, IL-6, and STAT3, in metabolic dysregulation and inflammatory responses linked to fatigue. Molecular docking exhibits strong binding affinity between key compounds such as Calamenene, T-cadinol, and Bornyl acetate and core targets, suggesting their potential antifatigue effects. However, ADMET analysis confirmed T-cadinol's drug-likeness, suggesting good bioavailability and minimal toxicity risks. Thus, molecular docking revealed high binding affinity, which was further validated through a 100 ns MD simulation and demonstrated stable interactions with low root mean square deviation (RMSD). Additionally, hydrogen bond analysis confirmed that T-cadinol maintained consistent interactions with key residues such as Thr-790 in EGFR, Arg-222 in ALB, and Arg-104 in IL-6, indicating strong binding stability. While this study provides valuable computational insights, further in vitro and in vivo validation is necessary to confirm these findings and explore potential therapeutic applications.

The IARC classified betel nut as Group 1 carcinogen (2004) and arecoline as Group 2B carcinogen (2020), with approximately one-third of global oral cancer cases attributed to smokeless tobacco or betel nut consumption. While current evidence establishes an association between arecoline and oral cancer, the underlying molecular mechanisms remain complex and poorly elucidated. This study employs network toxicology integrated with molecular docking techniques to systematically investigate the potential molecular pathogenesis of arecoline-induced oral cancer, aiming to provide novel insights for targeted therapeutic strategies. The SMILES structure of arecoline was retrieved from PubChem for foundational data preparation. Toxicity profiling was conducted using ProTox-3.0 and ADMETlab databases. Potential targets of arecoline were identified via STITCH and SwissTargetPrediction. Oral cancer-related targets were collated from GeneCards, OMIM, and TTD. Intersection analysis between arecoline targets and oral cancer-associated targets was performed to identify shared targets, which were further utilized to construct compound-target regulatory network and subjected to PPI, GO, and KEGG analyses. Core targets driving oral cancer were screened using the cytoHubba plugin. Then, the correlation between core targets and immune cell infiltration in oral cancer was explored, and molecular docking validated the binding affinity of arecoline to core targets. Finally, Gromacs 2022.3 software was used to simulate the molecular dynamics of the complexes obtained by molecular docking for 100 ns. Using the STITCH and SwissTargetPrediction databases, a total of 46 potential targets of arecoline were identified. Concurrently, 2,375 oral cancer-related targets were retrieved from GeneCards, OMIM, and TTD. Intersection analysis of these two target sets yielded 26 overlapping targets. PPI analysis revealed that TP53, IL6, SNAI1, and CASP3 occupied central positions in the network, exhibiting extensive interactions with other target proteins. Enrichment analysis comprehensively elucidated the molecular functions, biological processes, cellular components, and associated pathways of these overlapping targets. Further screening using Cytoscape software identified four core targets: TP53, TNF, IL6, and CASP3. Immune infiltration analysis indicated that the expression levels of TP53, TNF, IL6, and CASP3 in oral cancer tissues were positively correlated with the infiltration levels of immune cells, including CD8 + T cells, Th1 cells, NK cells, and macrophages. Molecular docking experiments demonstrated strong binding activities between arecoline and TP53, IL6, and CASP3, while TNF also exhibited moderate binding affinity. Dynamic simulation further verified the stable binding of arecoline to TP53, TNF, IL6 and CASP3. Arecoline may induce oral cancer by acting on core targets including TP53, TNF, IL6, and CASP3, which interfere with normal cellular growth regulation, inflammatory responses, and apoptotic mechanisms. Therapeutic strategies targeting TP53, TNF, IL6, and CASP3 may represent novel research directions for clinical diagnosis and treatment of oral cancer.

Phthalates, as a class of known endocrine disruptors, have been controversial because of their potential carcinogenicity and toxicity. Diisononyl cyclohexane-1,2-dicarboxylate (DINCH) is considered to be less toxic and more prone to environmental degradation, and is widely used as a substitute for phthalate. With the increasing use of DINCH in consumer products and industrial materials, the frequency of its detection in the air and human urine has also increased, which has aroused concern about its potential toxicity in food safety. Despite the increasing popularity of DINCH, toxicological studies on this topic are still limited. This study first predicted the hepatotoxicity and carcinogenicity of DINCH via the ADMETlab 3.0 platform. Next, the potential hepatotoxic genes associated with DINCH were collected through multiple databases, and a gene network was constructed. Through proteinprotein interaction, GO enrichment and KEGG pathway analyses, we elucidated the primary mechanism by which DINCH may induce hepatotoxicity. The expression of the selected key genes in related diseases was subsequently validated via the liver cancer database of TCGA and the NASH dataset of GEO. In addition, molecular docking technology and dynamics simulation were used to simulate the interaction and binding ability between DINCH and the core target. Cell experiments verified that DINCH increases hepatotoxicity primarily by upregulating TNF, TP53, and PPARG. In summary, this study elucidates the potential biological mechanisms of DINCH-induced hepatotoxicity, providing new scientific insights for the prevention and management of related toxicities.

Phthalates (PAEs) are one of the most commonly used plasticizers. Due to their good performance, they are widely used in daily production, such as food packaging, paints, adhesives, children's toys, lubricants and building materials. However, PAEs usually have weak interactions with polymers, which can easily cause environmental pollution in use. These plasticizers have been linked to various health conditions, including inflammatory disorders. They are less intensively studied in the occurrence of inflammation, especially inflammatory bowel disease (IBD), and the necessity to evaluate their pathogenic molecular toxicity is particularly urgent. In this study, network toxicology and molecular docking methods were used to study the toxicological mechanism of IBD induced by four common plasticizers (DBP, DEHP, DEP, DNOP). Potential related targets were predicted using the PharmMapper, SwissStargetPrediction, GeneCards, DisGeNET, OMIM and TTD databases, and 286 related targets were identified. Using Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, binding protein-Protein Interaction (PPI) networks and cytoHubba plug-ins, ten relevant signaling pathways (PI3K-Akt signaling pathway, lipid and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, Proteoglycans in cancer, and so on.) and ten hub genes were identified. Four plasticizers (DBP, DEHP, DEP, DNOP) and the top 10 selected Hub gene targets (SRC, KRAS, PIK3CA, PIK3R1, JAK2, PTPN11, PIK3CD, HRAS, PIK3CG, EGFR) were analyzed by molecular docking. This study provides valuable insights into the molecular mechanisms of plasticizer-induced IBD and highlights the practicality of network toxicology in assessing the toxicity of emerging environmental pollutants. It enhances our understanding of the health risks posed by plasticizers and offers new strategies for mitigating their impact on inflammatory diseases.

The pharmacodynamics, molecular biology, network pharmacology, and molecular docking mechanisms of the Ligusticum wallichii and borneol medication pair (CXBP) were investigated for ischemic stroke treatment. Effective chemical components and targets of CXBP were identified using TCMSP, ETCM, and SymMap databases, whereas ischemic stroke targets were sourced from OMIM, GeneCards, TTD, PubMed, Web of Science, CNKI, Wanfang Data, and VIP databases. Protein-protein interaction (PPI) networks were generated using the STRING database, and GO and KEGG enrichment analyses were conducted using Metascape. A "disease-pathway-target-component-drug" network was created in Cytoscape, and molecular docking was confirmed with PyMOL and AutoDock tools. Rat models of MCAO were established to evaluate neurological scores, triphenyltetrazolium chloride (TTC) staining, and Nissl staining. Key components were validated through enzyme-linked immunosorbent assay (ELISA), real-time polymerase chain reaction (PCR), and immunohistochemistry. Thirty-three active ingredients and 419 potential targets for CXBP, with key compounds including Z-6,8',7,3'-diligustilide, cedrene, (+)-alpha-funebrene, POL, dipterocarpol, oleanolic acid, 1-acetyl-beta-carboline, and erythrodiol. Critical targets included ESR1, PRKCA, and PTPN6. KEGG pathway analysis revealed 179 signaling pathways, primarily neuroactive ligand-receptor interactions, whereas GO enrichment analysis identified 2911 biological processes, 398 molecular activities, and 203 cellular components. The neurological function scores and TTC staining of the infarcted brain regions were significantly improved following CXBP intervention compared to the MCAO group. These findings were supported by Nissl staining, which demonstrated better preserved cellular morphology and a significantly higher number of Nissl vesicles in the CXBP group. ELISA analysis revealed substantial modulation in gene expression: levels of PRKCA, PTPN6, ESR1, and TNF-α changed significantly, whereas IL-1β, IL-6, and TNF-α were notably downregulated compared to the MCAO group. PCR results corroborated these findings, showing a significant decrease in PRKCA expression and marked downregulation of IL-1β, IL-6, and TNF-α, whereas ESR1 and PTPN6 levels increased significantly. Immunohistochemical analysis further confirmed these results, with the CXBP and nimodipine groups exhibiting higher ESR1 and PTPN6 expression and lower PRKCA expression compared to the MCAO group. To improve cerebral ischemia and reperfusion injury, CXBP improves ischemic stroke outcomes through key active ingredients (e.g., Z-6,8',7,3'-diligustilide, cedrene, and oleanolic acid) and targets ESR1, PRKCA, and PTPN6, modulating multiple signaling pathways to alleviate cerebral ischemia-reperfusion injury.

Ischemia-reperfusion damage to cardiomyocytes is one of the main directions of cardiovascular disease research, and Bawei Chenxiang powder (BWCX) is a traditional ethnomedicinal compound preparation mainly used in the treatment of cardiovascular diseases. On the basis of serum pharmacology, the present study aimed to explore the potential mechanism of BWCX against myocardial ischemia-reperfusion damage to cardiomyocytes. We prepared BWCX-serum containing. Using serum pharmacology and bioinformatics approaches, we explored its protective effects on H9C2 cells in a hypoxia/reoxygenation (H/R) model. Additionally, we investigated the underlying mechanisms. BWCX-containing serum can increase the survival rate of H9C2 cells and reduce oxidative stress levels in an H/R model. Specifically, it decreases the release of malondialdehyde (MDA), lactate dehydrogenase (LDH), creatine kinase (CK), and reactive oxygen species (ROS), while increasing the levels of catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GSH-PX), and Complex I. Additionally, it downregulates the expression of NADH dehydrogenase (ubiquinone) 1 alpha sub-Complex 10 (NDUFA-10), thioredoxin (Trx), heme oxygenase 1 (HO-1), and kelch-like ECH-associated protein 1 (Keap1), and it upregulates the expression of nuclear factor erythroid 2-related factor 2 (Nrf2). These effects are potentially mediated through the PI3K-AKT pathway. In the present study, we found that BWCX powder exhibited significant ameliorative and reparative effects on H/R-induced cardiomyocyte injury by alleviating the level of oxidative stress during H/R and acting on the PI3K-AKT pathway.

Fatigue is commonly marked by reduced endurance and impaired function, often linked to overexertion and chronic conditions. Quinoa (Chenopodium quinoa Willd.), with its rich amino acids and resilience to harsh conditions, offers a novel strategy for combating fatigue. This study explored the antifatigue effects of quinoa protein (QPro) and its hydrolysate (QPH) in weight-loaded swimming mice. After 4 weeks of oral administration, QPro and QPH significantly prolonged swimming duration, reduced serum fatigue biomarkers (lactic acid, urea nitrogen, lactate dehydrogenase, creatine kinase), and elevated glycogen reserves in the liver and muscle. RT-qPCR analysis indicated that QPH activated hepatic gluconeogenesis via G6Pase and PEPCK signaling and enhanced mitochondrial function through PGC-1α/NRF1/TFAM signaling in muscle. Additionally, QPro and QPH boosted antioxidant defenses by improving antioxidant enzyme activity, reducing malondialdehyde through the Nrf2/HO-1 pathway, and suppressing inflammation by reducing TNF-α and IL-6 levels. Network pharmacology identified 31 key targets involved in energy metabolism and inflammation, providing novel insights into the molecular mechanisms underlying the antifatigue properties of quinoa peptides. These findings highlight the potential of QPro and QPH as natural and bioactive ingredients in functional foods for enhancing endurance and mitigating fatigue.

Type 2 diabetes mellitus (T2DM) is characterized by pancreatic β-cell dysfunction and insulin resistance, with pyroptosis emerging as a key contributor to β-cell loss. Jiedu Tongluo Tiaogan Formula (JTTF), a traditional Chinese medicine (TCM), has shown clinical efficacy in T2DM management, but its mechanism linking pyroptosis remains unexplored. This study integrates UPLC-MS/MS, network pharmacology, and in vivo experiments to elucidate JTTF's anti-diabetic mechanisms. UPLC-MS/MS identified 441 compounds in JTTF, predominantly alkaloids, flavonoids, phenols, and terpenoids. Network pharmacology revealed JTTF's multi-target effects on T2DM-associated pyroptosis, particularly via the NLRP3/Caspase-1/GSDMD pathway. In diabetic mice, JTTF dose-dependently reduced fasting blood glucose, insulin resistance, and dyslipidemia, while restoring pancreatic β-cell morphology. Mechanistically, JTTF suppressed NLRP3 inflammasome activation, downregulated Caspase-1 and GSDMD expression, and attenuated IL-1β/IL-18 release. Notably, this study provides the first evidence of JTTF's anti-pyroptotic effects in T2DM, highlighting its unique ability to modulate glycolipid metabolism and inflammatory cell death concurrently. These findings underscore JTTF's translational promise for preserving β-cell function and suggest future exploration of non-classical pyroptosis pathways. Our work bridges traditional medicine and molecular pharmacology, paving the way for clinical trials and integrative T2DM therapies.

The content of terpenoids in tobacco can alter its resistance to TMV. NtSPS1, a pivotal structural gene in tobacco, is capable to regulate the terpenoid content. In this study, we investigated the effect of NtSPS1 knockout in HD on the content of terpenoids and the anti-TMV activity of this mutant using gene editing, widely targeted metabolomics, network pharmacology, and molecular docking. 48 terpenoids (six up-regulated and five down-regulated) in NtSPS1 knockout tobacco compared with WT leaves. Notably, solanesol was remarkable downregulation which was lowered by fourfold and compounds 1 (log2FC = 18.2), 8 (log2FC = 16.7) were significant upregulation between the mutants and wild-type line leaves. The 46 terpenoid's target network encompassed 150 nodes, 509 edges and their underlying mechanisms in the therapeutic management of TMV are discussed. Furthermore, the network pharmacology and molecular docking revealed that compounds 16, 18, 23, 27, and 36 exhibited significant affinity in their respective interactions. Ultimately, five compounds were assayed for their anti-TMV effects, noteworthily, compounds 36 showed potential anti-TMV activity. Above all, we adopted a multifaceted approach to gain a comprehensive understanding of the terpenoid content and anti-TMV properties in NtSPS1 knockout HD. It enlightens the therapeutic potential of NtSPS1 knockout tobacco and it is helpful to find undescribed anti-TMV activity inhibitors, as well as searching for new anti-TMV candidates from the mutants.

Colorectal cancer (CRC) ranks among the top three most prevalent malignancies globally and is a leading cause of cancer-related mortality. Traditional therapeutic approaches usually cause significant adverse effects, highlighting the urgent demand for alternative, more effective treatments. Probiotics have gained attentions as potential cancer therapy due to their beneficial impacts on host health. Clostridium butyricum (Cl. butyricum) has shown anticancer properties in recent studies, though the underlying mechanisms remain inadequately understood. This study presents an integrative analysis of network pharmacology and proteomics to elucidate the key targets of Cl. butyricum in CRC treatment. The network pharmacology analysis identified 72 overlapping genes, and functional analysis of these genes indicated that most pathways were related to pathways in cancer and inflammation, and butyrate emerging as the pivotal product of Cl. butyricum due to its strong associations with the identified hub genes. In parallel, proteomics analysis revealed 168 differential expressed proteins (DEPs) in Cl. butyricum-treated HCT-116 cells, comprising 78 upregulated and 90 downregulated proteins. These DEPs were primarily enriched in apoptosis and inflammatory pathways. PPI analysis further highlighted NFKB1 as key contributors to the anticancer effects of Cl. butyricum. The integrative analysis revealed a significant convergence of pathways enrichment patterns, particularly in inflammatory and immune-related pathways. Computational and experimental validation identified NFKB1 as a pivotal molecular target in CRC intervention. These collective findings elucidate the mechanistic basis of the antitumor properties of Cl. butyricum, highlighting its regulatory effects on NFKB1 through both inflammatory and, to a lesser extent, immunoregulatory pathways.

The immune system is vital for maintaining homeostasis, defending against external threats, and regulating inflammation, forming the cornerstone of human health. Sanghuangporus, a natural medicinal mushroom, contains flavonoids that may increase immune cell activity, potentially improving human health. This study investigated the immunomodulatory effects of Sanghuangporus flavonoids (PBF) via network pharmacology and in vitro and in vivo experiments. Network pharmacology identified PBF compounds targeting 46 immunosuppression-related targets, with rutin emerging as a key component. Molecular docking confirmed the strong binding affinity of rutin for the core targets IL6, TNF, and IL1B. In vitro, PBF activated mouse macrophages, promoting their proliferation, phagocytic activity, NO production, and cytokine regulation. In vivo, PBF enhanced immune function in normal mice by promoting thymus and spleen growth, increasing cellular and humoral immunity, and restoring immune function in immunosuppressed mice. These findings highlight the potential of PBFs in increasing immunity and treating immunosuppressive diseases.

Amisulpride, a unique atypical antipsychotic, significantly increases prolactin secretion during schizophrenia treatment, resulting in adverse effects that reduce patient quality of life and treatment adherence. Aripiprazole, a partial dopamine D2 receptor agonist, reduces prolactin elevation induced by antipsychotic drugs used for schizophrenia treatment. The molecular targets and mechanisms underlying the contrasting effects of these two drugs on prolactin regulation are unclear. The objective of this study was to systematically explore the molecular mechanisms of prolactin regulation by aripiprazole and amisulpride using network pharmacology and molecular docking techniques.

Relevant targets of amisulpride and aripiprazole and for schizophrenia and elevated prolactin treatment were obtained from online databases and screened for significance. A protein-protein interaction network was constructed. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses of the core targets were performed to identify key biological processes and signaling pathways, and a target-pathway-drug integrated network was established. The binding affinities of amisulpride and aripiprazole with core targets were predicted using molecular docking analyses.

Screening and matching drug and disease targets combined with GO and KEGG pathway enrichment analyses revealed several key signaling pathways involved in prolactin regulation, including MAPK, PI3K/AKT, and dopamine receptor pathways. The core targets of aripiprazole include MAPK3, PPARG, DRD2, and ESR1, and amisulpride primarily targets MMP9, CDC42, mTOR, and AKT1. Molecular docking analysis demonstrated that aripiprazole and amisulpride have high binding affinities for their respective targets, supporting the hypothesis that these drugs regulate prolactin levels through target-ligand interactions.

These findings highlight the distinct signaling pathways and molecular networks involved in prolactin regulation by aripiprazole and amisulpride and provide new insights into the mechanisms of these drugs in schizophrenia treatment. Further pharmacological and clinical research is needed to validate the complex regulatory networks and in vivo effects.

Wenweishu (WWS) is a traditional Chinese medicine compound formulated for chronic atrophic gastritis (CAG) treatment by warming the stomach and alleviating pain. However, its pharmacological mechanisms remain underexplored.

This study investigated the therapeutic effects and potential mechanisms of WWS on CAG with spleen-stomach cold deficiency syndrome (SSCDS).

To achieve this, an SSCDS-CAG rat model and a human gastric mucosal epithelial cells (GES-1) cell model were established using multi-factor modeling and N-Methyl-N'-nitro-N-nitrosoguanidine (MNNG) induction, respectively. WWS's effects on gastric injury were evaluated through pathology, inflammation, serum biomarkers, and apoptosis. Additionally, MNNG's effects on GES-1 cells were analyzed. Network pharmacology, involving protein-protein interaction networks, GO/KEGG enrichment, and molecular docking, was employed to predict WWS's potential targets and mechanisms in SSCDS-CAG. Mechanistic insights were further validated using immunohistochemistry, quantitative reverse transcription polymerase chain reaction, and western blotting.

In vivo results showed that WWS alleviated symptoms in SSCDS-CAG rats, lowering symptom scores and improving gastric histopathology. It modulated serum biomarkers and reduced inflammation and apoptosis in both in vivo and in vitro studies. Network pharmacology results revealed 263 overlapping targets between WWS and SSCDS-CAG, associated with apoptosis, inflammation, and the PI3K/AKT pathway. Molecular docking revealed strong binding affinity between the core target and active WWS components. In SSCDS-CAG rats and GES-1 cells, WWS inhibited PI3K/AKT phosphorylation, increased PTEN expression, and regulated Bcl-2, Bax, and cleaved caspase-3 levels.

WWS reduces inflammation and apoptosis in multi-factor CAG rats and MNNG-induced GES-1 cells by modulating the PTEN/PI3K/AKT signaling pathway and apoptosis-related proteins.

Bufalin is a potent bioactive compound extracted from the venom of toads such as Bufo gargarizans. It has rich pharmacological effects, and its traditional applications mainly include anti-cancer, anti-inflammatory and analgesic, especially in cancer treatment, which has been a hot topic of research. Prior research has suggested that bufalin may have anti-tumor angiogenic effects. However, the efficacy and mechanism of bufalin inhibiting hepatocellular carcinoma (HCC) angiogenesis have yet to be further investigated.

An extensive detailed strategy via network pharmacology, proteomics, histopathological analysis, molecular docking, in vitro experiments, and in vivo magnetic resonance imaging (MRI) examinations were adopted to investigate the efficacy and mechanisms of bufalin against HCC angiogenesis.

Micro-vessel density (MVD) and intravoxel incoherent motion (IVIM) perfusion-related parameters based on magnetic resonance diffusion-weighted imaging were used to identify the effect of bufalin against HCC angiogenesis. Potential bufalin and HCC targets were gathered from appropriate databases. The STRING database was used to construct the target protein interaction networks. The "clusterprofiler" package (version 4.2.2) in R was applied to conduct the target-related Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) analysis. Network pharmacology and proteomics were integrated to identify key targets and pathways related to bufalin against HCC angiogenesis. Molecular docking and Western Blot were utilized to validate the findings.

Analysis through IVIM and MVD showed that bufalin could inhibit HCC angiogenesis in nude mice models. A total of 159 common targets of bufalin and HCC were identified by network pharmacology. GO analysis revealed that these targets focused on multiple angiogenesis-related biological processes, including endothelial cell proliferation and migration, sprouting angiogenesis, and regulation of angiogenesis. The KEGG enrichment results suggested that bufalin could regulate multiple signaling pathways to inhibit HCC angiogenesis, including VEGF, MAPK, PI3K-Akt, mTOR, and HIF-1 signaling pathways. MAPK1, MAPK14, PRKCA, EIF4E, and APEX1 might be critical targets in regulating the above pathways. The molecular docking and Western blot analysis verified the effects of bufalin on target proteins.

This study demonstrated that bufalin might inhibit HCC angiogenesis by regulating multiple targets and pathways. These findings offer theoretical insights and experimental foundations for the clinical application and commercial development of bufalin in the treatment of HCC.

It is well established that certain carboxylic acid compounds can effectively inhibit tyrosinase activity. This study investigated the mechanisms by which four carboxylic acid compounds-3-phenyllactic acid, lactic acid, L-pyroglutamic acid, and malic acid-inhibit tyrosinase and melanogenesis. IC50 values for mushroom tyrosinase inhibition ranged from 3.38 to 5.42 mM, with 3-phenyllactic acid (3.50 mM), lactic acid (5.42 mM), and malic acid (3.91 mM) exhibiting mixed-type inhibition, while L-pyroglutamic acid (3.38 mM) showed competitive inhibition, as determined by enzymatic kinetic analysis. Additionally, the acidification effects of lactic acid, L-pyroglutamic acid, and malic acid contributed to the reduction in tyrosinase activity. Furthermore, all four carboxylic acid compounds effectively inhibited DOPA auto-oxidation (IC50 = 0.38-0.66 mM), ranking in potency as follows: malic acid (0.38 mM) > lactic acid (0.57 mM) > 3-phenyllactic acid (0.63 mM) > L-pyroglutamic acid (0.66 mM). These compounds also demonstrated a dose-dependent reduction in melanin production in B16-F10 cells. Proteomic analysis further revealed that these compounds not only inhibit key proteins involved in melanin synthesis, such as tyrosinase, tyrosinase-related protein 1, and tyrosinase-related protein 2, but also potentially modulate other genes associated with melanogenesis and metabolism, including Pmel, Slc45a2, Ctns, Oca2, and Bace2. Network toxicology analysis indicated that these four compounds exhibit a low risk of inducing dermatitis. These findings suggest that these compounds may indirectly regulate melanin-related pathways through multiple mechanisms, highlighting their potential for further applications in cosmetics and pharmaceuticals.

Metabolic-associated fatty liver disease (MAFLD) is a prevalent global health issue closely tied to dietary habits, impacting a significant portion of the adult population. MAFLD is linked to various metabolic disorders, elevating risks of cirrhosis and hepatocellular carcinoma and severely impacting patients' quality of life. While therapeutic research has progressed, effective food-based interventions remain scarce. Natural products, rich in bioactive compounds and offering health benefits, have gained attention for their potential in managing MAFLD. This study employed network pharmacology and lipidomics to investigate the therapeutic effects of Food and Medicine Homology (FMH) on MAFLD using a high-fat-diet-induced HepG2 cell model. We identified 169 potential bioactive components from Radix Puerariae, Hericium erinaceus, Rhizoma Curcumae longae, Camellia oleifera, and Hoveniae Dulcis Semen, constructing a drug-component-target network that highlighted 34 key targets. The characteristic components of this FMH compound solution (HSD) were identified using UPLC-QTOF-MS/MS. In vitro, HSD significantly reduced intracellular lipid accumulation, decreased inflammatory markers, and mitigated hepatocyte damage. Lipidomics analysis revealed significant alterations in lipid metabolites, suggesting HSD's potential to modulate sphingolipid and glycerophospholipid metabolism, thus improving MAFLD outcomes. This research underscores the critical role of the FMH complex in modulating lipid metabolism and inflammatory pathways, offering valuable insights for developing FMH-based dietary supplements and functional foods to alleviate MAFLD. By leveraging the synergistic effects of natural compounds, our findings hold significant implications for innovative nutritional strategies in managing this prevalent metabolic disorder.

BackgroundPrior studies examined variants within presenilin-2 (PSEN2), presenilin-1 (PSEN1), and amyloid precursor protein (APP) genes. However, previously-reported clinically-relevant variants and other predicted damaging missense (DM) variants have not been characterized in a newer release of the Alzheimer's Disease Sequencing Project (ADSP).ObjectiveTo characterize previously-reported clinically-relevant variants and DM variants in PSEN2, PSEN1, APP within the participants from the ADSP.MethodsWe identified rare variants (MAF < 1%) in PSEN2, PSEN1, and APP in 14,641 individuals with whole genome sequencing and 16,849 individuals with whole exome sequencing available (Ntotal = 31,490). We additionally curated variants from ClinVar, OMIM, and Alzforum and report carriers of variants in clinical databases as well as predicted DM variants in these genes.ResultsWe detected 31 previously-reported clinically-relevant variants with alternate alleles observed within the ADSP: 4 variants in PSEN2, 25 in PSEN1, and 2 in APP. The overall variant carrier rate for the 31 clinically-relevant variants in the ADSP was 0.3%. We observed that 79.5% of the variant carriers were cases compared to 3.9% were controls. In those with AD, the mean age of onset of AD among carriers of these clinically-relevant variants was 19.6 ± 1.4 years earlier compared with noncarriers (p = 7.8 × 10-57). Additionally, we identified 197 rare variants (MAF < 1%) within ADSP participants not reported in known clinical databases.ConclusionsA small proportion of individuals in the ADSP are carriers of a previously-reported clinically-relevant variant allele for AD and these participants have significantly earlier age of AD onset compared to noncarriers.

Hesperetin (HE), a natural flavonoid exhibiting anti-inflammatory and antioxidant properties, holds significant potential in treating chronic obstructive pulmonary disease (COPD). Nonetheless, the precise mechanisms underlying its effects are yet to be fully elucidated. In this study, we aim to explore the role and potential mechanism of HE in treating COPD using network pharmacology, molecular docking and experimental validation. We screened for HE and COPD-related targets from public databases, and then imported potential targets into a STRING database to establish a protein-protein interaction network. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes enrichment analysis were performed to obtain key signaling pathways. We then predicted the binding interactions between HE and core targets using molecular docking. The animal model of COPD was established through lipopolysaccharide and cigarette smoke induction in mice to observe lung function, inflammatory factors, pathology, and the expression of related proteins. Network pharmacology findings unveiled that HE and COPD shared 105 common targets. MAPKs and NF-κB signaling pathways were selected for further validation. In animal experiment, HE enhanced lung function and histopathological morphology, while reducing inflammation levels. The results of Western blot tests indicated that HE treatment considerably inhibited the expression of MAPKs and NF-κB. HE effectively reduced lung inflammation and improved lung function in mice. This mechanism may be achieved by inhibition of MAPKs and NF-κB signaling pathways.

Approximately one out of two patients with diabetes develops diabetic neuropathy; of these, 20% experience neuropathic pain. Risk factors for neuropathic pain are largely unknown; however, DNA methylation was recently associated with neuropathies and degeneration of nerve fibers. The aim of this work was to describe the DNA methylation signature and identify genes associated with neuropathic pain in type 2 diabetes mellitus (T2DM). We discovered distinct DNA methylation signatures that differentiate painful and painless neuropathy phenotypes associated with T2DM and identified genes with potential as therapeutic targets for neuropathic pain, such as GCH1, MYT1L, and MED16. This work can serve as reference hallmark for future studies on painful diabetic neuropathy and other chronic pain conditions.

To evaluate the therapeutic potential of the curcumin analog J7 in protecting the liver and regulating glucose and lipid metabolism in rats with type 2 diabetes.

Bioinformatics methods were used to identify signaling pathways linked to diabetic liver disease. Diabetic rats were treated with curcumin, low-dose J7, or high-dose J7, and liver function and fibrosis were assessed through biochemical analyses, histopathology, immunohistochemistry, and ELISA.

J7 administration significantly improved lisver function, reduced fibrosis, and regulated metabolic profiles in diabetic rats. J7 downregulated TGF-β1, NF-κB p65, and BAX, while upregulating BCL-2, showing superior effects to traditional curcumin in reducing TGF-β1 and inhibiting α-SMA expression.

J7 demonstrates potential as a therapeutic agent for managing liver complications in type 2 diabetes, effectively attenuating liver fibrosis and regulating metabolism through the modulation of key signaling pathways and proteins.

Scrophularia ningpoensis Hemsl. is a traditional Chinese medicine used to regulate blood sugar levels, immunity, etc. We previously isolated polysaccharides from S. ningpoensis Hemsl. (SNPS) and innovatively observed that SNPS exhibit antidepressant properties; however, the underlying mechanism is still unclear. Here, we employed network pharmacology to predict the potential targets and antidepressant mechanism of SNPS. Accordingly, we detected the effects of SNPS on monoamine neurotransmitter synthesis, metabolism, receptor expression and signal transduction in reserpine (RES)-treated mice using ELISA, HPLC-electrochemistry, metabonomics, Golgi-Cox staining and Western blotting. Finally, the mechanism of SNPS on key targets (HTR2A and HTR2C) was verified in vivo and in vitro. Results showed that SNPS ameliorated depression by restoring monoamine neurotransmitter homeostasis and hippocampal neurogenesis. SNPS reversed the depletion of 5-HT, NE and DA by activating the tryptophan (Trp)/5-HT and tyrosine (Tyr)/DA/NE metabolic pathways. SNPS decreased HTR2A and HTR2C contents, leading to the phosphorylation of AKT and GSK3β, followed by increases in β-catenin, CBP and BDNF levels. Mechanistically, SNPS reduced the levels of HTR2A and HTR2C proteins by inhibiting their mRNA transcription, rather than inducing protein degradation. In conclusion, by inhibiting the transcription of HTR2A and HTR2C, SNPS activated the AKT/GSK3β/β-catenin/CBP/BDNF pathway, thereby exerting dose-dependent antidepressant effects.

Hepatocellular carcinoma (HCC) is a malignant disease with high incidence and mortality worldwide. This study focuses on the TP53 target protein to investigate the potential therapeutic effect of tetrahydrocurcumin (THC) on HCC and its mechanism of action. The research hypothesis is that THC can inhibit the proliferation, migration, and invasion of HCC cells, and promote their apoptosis by regulating the TP53 target protein.

To explore the mechanism by which THC inhibits HCC cell proliferation via the TP53 signaling pathway.

Potential targets of THC and HCC were identified from multiple databases. The core targets were subjected to analyses using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases, and visualization processing, using the online platform Metascape to identify the key molecules and signaling pathways involved in the action of THC against HCC. The molecular mechanisms of action of THC against TP53 in the inhibition of HCC cells were verified using cell counting kit-8, Transwell, apoptosis, and western blotting assays.

Molecular docking results showed that THC had a high score for the TP53 target protein. In vitro experiments indicated that THC effectively inhibited the proliferation and migration of HCC cells, and affected the expression levels of TP53, MDM2, cyclin B, Bax, Bcl-2, caspase-9, and caspase-3.

THC induces the apoptosis of HCC cells through the TP53 signaling pathway, thereby inhibiting their proliferation and migration.

Liver cancer has a high incidence and mortality worldwide, especially in China. Herein, we investigated the therapeutic effect and mechanism of tetrahydrocurcumin against hepatocellular carcinoma (HCC), with a focus on the of phosphoinositide 3-kinases (PI3K)/AKT signaling pathway.

To investigate the effects and mechanism of tetrahydrocurcumin in HCC cell lines HepG2 and Huh7.

Using Metascape, we analyzed the potential targets of tetrahydrocurcumin in HCC. Molecular docking validation was performed using SYBYL2.0. Cell Counting Kit-8, wound healing, and transwell assays were performed to evaluate the effects of tetrahydrocurcumin on HepG2 and Huh7 cell migration, invasion, and apoptosis. The expression of PI3K/AKT signaling pathway-related proteins was detected by western blotting.

Network pharmacology and molecular docking showed that tetrahydrocurcumin has high binding affinity for phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha. In vitro experiments demonstrated that tetrahydrocurcumin suppressed the migration and invasion of liver cancer cells, promoted their apoptosis, and downregulated the expression of p-PI3K, p-AKT, and B cell leukemia/lymphoma 2, while upregulating caspase-3, p53, and B cell leukemia/lymphoma 2 associated X.

In summary, tetrahydrocurcumin suppresses PI3K/AKT signaling, promotes apoptosis, and prevents the migration and invasion of liver cancer cells.

Adverse Drug Reactions (ADRs), a widespread phenomenon in clinical drug treatment, are often associated with a high risk of morbidity and even death. Drugs and changes in gene expression are the two important factors that affect whether and how adverse reactions occur. Notably, pharmacogenomics data have recently become more available and could be used to predict ADR occurrence. However, there is a challenge in effectively analyzing the massive data lacking guidance on mutual relationship for ADRs prediction.

We constructed separate similarity features for drugs and ADRs using pharmacogenomics data from the Comparative Toxicogenomics Database [CTD, including Chemical-Gene Interactions (CGIs) and Gene-Disease Associations (GDAs)]. We proposed a novel deep learning architecture, DGANet, based on the constructed features for ADR prediction. The algorithm uses Convolutional Neural Networks (CNN) and cross-features to learn the latent drug-gene-ADR associations for ADRs prediction.

The performance of DGANet was compared to three state-of-the-art algorithms with different genomic features. According to the results, GDANet outperformed the benchmark algorithms (AUROC = 92.76%, AUPRC = 92.49%), demonstrating a 3.36% AUROC and 4.05% accuracy improvement over the cutting-edge algorithms. We further proposed new genomic features that improved DGANet's predictive capability. Moreover, case studies on top-ranked candidates confirmed DGANet's ability to predict new ADRs.

Allergic rhinitis is a devastating health complication that interrupts the quality of daily life and significantly affects around 40 % of the population worldwide. Despite the availability of various treatment options, many patients continue to struggle with persistent symptoms and side effects, highlighting the need for innovative therapeutic approaches. Therefore, identifying pathway and mechanism-based targeted therapies with more effective and fewer side effects could aid current therapeutics and provide novel therapeutic advantages. This study aimed to identify potential drug candidates for allergic rhinitis treatment by employing in-silico approaches, including network pharmacology, molecular docking, ADMET, similarity, pharmacophore modeling, quantum chemistry, and machine learning-based QSAR modeling. From three traditionally used medicinal plants known as allergic rhinitis curing, Xanthium strumarium, Magnolia liliiflora, and Tylophora indica, 241 compounds were obtained, and their favorable ADMET properties were analyzed. Network pharmacology revealed 203 potential therapeutic targets, with 15 hub targets identified through protein-protein interaction network analysis and most of them play key roles in inflammatory and immune pathways confirmed by KEGG pathway analysis. Molecular docking, similarity testing, and pharmacophore modeling studies identified promising compounds Quercetin, Yinyanghuo E, Uralenin, CID:90643991, CID:42607537, CID:76329670, Heracetin, and Fisetin exhibiting strong binding affinities with key regulatory targets, NFKB1, TRAF6, and key cytokines IL5, and IL6 that directly and indirectly involved in allergic reactions. Quantum chemistry calculations revealed favorable electronic properties and reactivities of these compounds. The machine learning-based QSAR model predicted IC50 < 50 nM for almost all compounds, indicating highly potent inhibitors. Hence, this in-silico study identified some novel promising drug candidates for treating allergic rhinitis by targeting crucial inflammatory and immune pathways, offering improved treatment outcomes and reduced side effects, subject to further experimental validation.

Novel thiazepine-based hybrids (9 a-d) were designed and synthesized to create lead molecules with exceptional anti-colon cancer efficacy. Analytical methods, including IR, NMR, and HR-MS, characterized the synthesized compounds. The in vitro colorectal study was carried out to compare the biological activity of newly developed compounds with the computational data. The tested compounds induced cytotoxicity in HT-29 cells for both 24 h and 48 h in a dose-dependent manner. However, compound 9 a induced cytotoxicity at much higher concentrations compared to the rest of the compounds. 9 b and 9 c caused 50 % cell death (compared to the untreated cells) at a dose of ~50 μM and 40 μM in case of 24-hour exposure, respectively. On the contrary, for 48 h exposure, both 9 b and 9 c induced 50 % cell death concerning untreated cells at a dose of around ~20 μM, whereas 9 d exhibited 50 % cell death at 5 μM in the case of 48 h exposure. In silico ADMET was also carried out to understand the pharmacokinetics and safety profiles of the drug candidates. We found some of the critical targets of these compounds, which eventually will be integral to exploring the mechanistic actions of these compounds in colon cancer.

This study aimed to investigate the potential pharmacological effects of icariin (ICA) in the treatment of spinal cord injury (SCI). Network pharmacology was used to focus on the potential targets and biological processes of ICA in SCI. Molecular docking was used to verify the ability of ICA to bind to its core targets. Finally, valuate the efficacy and potential mechanisms of ICA in treating spinal cord injury through in vitro and in vivo experiments. A total of 37 targets were screened out, and core genes were screened out from the protein‒protein interaction network. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that these targets are enriched mainly in response to hypoxia, regulation of the cellular response to stress, and the TGF-beta signaling pathway. Molecular docking analysis showed that ICA has good docking ability with core targets. In animal experiments, Basso, Beattie and Bresnahan scores, catwalk gait analysis, hematoxylin and eosin staining, and RT-qPCR showed that ICA can inhibit spinal cord inflammation and effectively improve the behavioral and histological recovery after SCI rats. Western blot and immunofluorescence showed that ICA can reduce astrocyte activation and downregulate the TGF-beta signaling pathway after SCI. In addition, ICA can promote axonal nerve elongation and promotes angiogenesis after spinal cord injury in rats. In vitro experiments revealed that ICA can inhibit TGFβ1-induced activation of the TGF-beta signaling pathway and astrocyte activation. ICA treats SCI through multiple targets and pathways. ICA plays a major role in protecting nerves, promoting angiogenesis, and inhibiting reactive astrocyte activation in the treatment of SCI.

Despite the insights that metabolite analysis can provide into the onset, development, and progression of diseases-thus offering new concepts and methodologies for prevention, diagnosis, and treatment-traditional wet lab experiments are often time-consuming and labor-intensive. Consequently, this study aimed to develop a machine learning model named COM-RAN, which is based on a knowledge graph and random forest algorithm, to identify potential associations between metabolites and diseases.

Firstly, we integrated the known associations between diseases and metabolites. Secondly, we provided a synthesis of the extant data regarding diseases and metabolites, accompanied by supplementary information pertinent to these entities. Thirdly, knowledge graph-based embedded features were used to characterize disease-metabolite associations. Finally, a random forest algorithm was employed to construct a model for identifying potential disease-metabolite associations.

The experimental results demonstrated that the proposed model achieved an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.968 in 5-fold cross-validations, while the Area Under the Precision-Recall Curve (AUPR) was 0.901, outperforming the vast majority of existing prediction methods. The case studies corroborated the majority of the novel associations identified by COM-RAN, thereby further demonstrating the reliability of the current method in predicting the potential relationship between metabolites and diseases.

The COM-RAN model demonstrated promise in predicting associations between diseases and metabolites, suggesting that integrating knowledge graphs with machine learning methodologies can significantly improve the accuracy and reliability of predictions related to disease-associated metabolites.

Ischemic stroke ranks as the second leading cause of global mortality. The limited time for effective thrombolytic treatment has prompted the exploration of alternative prevention approaches. Eucommia ulmoides (E. ulmoides) Oliv. bark has shown multiple pharmacological effects, including neuroprotection, anti-inflammation and autophagy modulation. This study aims to elucidate the neuroprotective effects of water extract of E. ulmoides (WEU) supplementation in a middle cerebral artery occlusion (MCAO) mouse model and to further explore the underlying molecular mechanisms. Seven bioactive compounds in WEU-aucubin, chlorogenic acid, geniposidic acid, quercetin, protocatechuic acid, betulin and pinoresinol diglucoside-were identified using HPLC-MS. Our results showed that WEU supplementation significantly decreased infarct volume and ameliorated neurological dysfunction in mice following MCAO/reperfusion (MCAO/R) injury. Furthermore, the administration of WEU significantly attenuated microglia activation induced by cortical ischemia in mice and inhibited the production of pro-inflammatory mediators, including interleukin-1β (IL-1β), interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α). Importantly, in contrast with the vehicle group, the protein expression levels of Toll-like receptor 4 (TLR4), phospho-p38 (p-p38) and nuclear factor kappa B (NF-κB) were reduced in the WEU group. Therefore, this present study provides evidence that E. ulmoides improves neurological behaviors by suppressing neuroinflammation and inhibiting the activation of the TLR4/ p38 MAPK and NF-κB pathways in mice after ischemia, which indicates that E.ulmoides is a promising candidate for alleviating gray matter ischemic change.

Chronic atrophic gastritis (CAG) is a global disease of the digestive system and is an important precancerous lesion in the development of gastric cancer. Yang Wei Shu granule (YWSG), which evolved from the formula "Warm Stomach Soup" of the Jin and Yuan Dynasties in China, is frequently used as a classic herbal compound in the treatment of CAG. However, the active ingredients and mechanisms by which it works are not clear.

To elucidate the chemical composition of YWSG and investigate the potential mechanisms of YWSG on CAG by composition analysis, network pharmacology and cellular experimental studies.

The chemical and blood-entry constituents of YWSG were analyzed by ultra-high performance liquid chromatography-Quadrupole tandem time-of-flight mass spectrometry (UPLC-QTOF-MS/MS). Subsequently, potential targets of YWSG for CAG treatment were identified through utilization of publicly available online resources. The YWSG-component-target-pathway network and protein-protein interaction (PPI) network were constructed using Cytoscape software. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of potential targets was performed using the DAVID database. Finally, a cellular model of lipopolysaccharide (LPS)-activated RAW 264.7 macrophages was established and validated by in vitro experiments.

A total of 150 compounds in YWSG and 47 blood-entry constituents were identified by using UPLC-QTOF-MS/MS. Based on network pharmacology, a total of 132 target genes were identified as being involved in the therapeutic effect of YWSG on CAG. Network pharmacology and molecular docking results suggest that AKT1, PIK3CA, PTPN11, SRC and STAT3 may be potential targets of YWSG for the treatment of CAG. Cellular experiments showed that the YWSG-containing serum had no cytotoxic effect on RAW264.7 cells and could inhibit nitric oxide (NO) production and the expression of pro-inflammatory factors TNF-α, IL-6, and IL-1β. Additionally, it was observed to promote the expression of the anti-inflammatory factor IL-10 in LPS-stimulated RAW264.7 cells. The immunofluorescence results showed that YWSG treated CAG by inhibiting the PI3K-Akt pathway.

The application of UPLC-Q-TOF-MS/MS, network pharmacology and cellular experiments provided elucidation to understand the components and mechanisms of the therapeutic effects of YWSG on CAG, providing useful directions for further research.

Background:Astragali radix is a traditional Chinese medicine with potential therapeutic effects on periodontitis; however, its underlying mechanisms require further investigation. Methods: We employed network pharmacology, molecular docking, molecular dynamics simulations, and in vitro experiments to explore the potential actions and mechanisms of Astragali radix in treating periodontitis. Results: A total of 17 compounds (including the most prevalent one, Kaempferol) from Astragali radix and 464 corresponding targets were identified, from which five major active ingredients were selected based on the drug-active ingredient and periodontitis gene network. Protein-protein interaction (PPI) network analysis identified the top ten core potential targets, seven of which possess suitable crystal structures for molecular docking. These include interleukin-6 (IL6), tumor necrosis factor (TNF), AKT serine/threonine kinase 1 (AKT1), interleukin-1β (IL1β), prostaglandin G/H synthase-2 (PTGS2), matrix metalloproteinase-9 (MMP9), and caspase-3 (CASP3). Additionally, 58 Gene Ontology (GO) terms and 146 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were identified. The five major active ingredients and seven core targets mentioned above were subjected to molecular docking analysis using Discovery Studio 2019 software. Molecular dynamic simulations confirmed a stable interaction between the CASP3 and the Kaempferol ligand system. In vitro experiments indicated that Kaempferol significantly inhibited lipopolysaccharide (LPS)-induced apoptosis in human periodontal ligament stem cells and reduced the expression levels of IL6, CASP3 and MMP9. Conclusions: This study systematically elucidates that the primary active ingredients derived from Astragali radix exert their pharmacological effects (including anti-inflammation and anti-apoptosis) primarily by interacting with multiple targets. These findings establish a promising foundation for the targeted application of Astragali radix in the treatment of periodontitis.

Prostate cancer (PCa) is one of the prevalent malignant tumors among men. It can progress to castration-resistant prostate cancer (CRPC), which is significantly more challenging to treat. Saikosaponin A (SSA), a triterpenoid saponin extracted from the genus Bupleurum, exerts numerous pharmacological effects, including anti-inflammatory and anti-tumorigenic effects. However, the mechanism underlying the effects of SSA in prostate cancer treatment remains elusive.

In this study, a network pharmacology approach was applied to identify relevant targets from drug- and disease-related databases, and intersections were analyzed using Venny2.1 to construct a Protein-Protein interaction (PPI) interaction network. Next, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to elucidate associated biological functions and signaling pathways. Meanwhile, molecular docking between core targets and SSA was performed using Autodock software. Lastly, in vitro experiments were performed for validation.

A least of four key targets, namely BCL2 apoptosis regulator (BCL2), estrogen receptor 1 (ESR1), hypoxia-inducible factor 1 subunit alpha (HIF1A), and signal transducer and activator of transcription 3 (STAT3) were identified in this study, and molecular docking analyses revealed that SSA stably binds to these targets. Moreover, the results of in vitro experiments revealed that SSA significantly inhibited the proliferative and migratory abilities of PC3 cells in a dose-dependent manner. Finally, SSA also induced G1-phase blockade and apoptosis in PC3 cells, further highlighting its potential role in prostate cancer treatment.

The present study revealed that SSA exerts anti-tumorigenic effects in prostate cancer by targeting multiple pathways, laying a theoretical reference for its use as a therapeutic candidate for prostate cancer.