AGE-RAGE Signaling Pathway Research Articles

Protective Effect and Related Mechanism of Modified Danggui Buxue Decoction on Retinal Oxidative Damage in Mice based on Network Pharmacology.

Age-related macular degeneration (AMD) is one of the common diseases that cause vision loss in the elderly, and oxidative stress has been considered a major pathogenic factor for AMD. Modified Danggui Buxue Decoction (RRP) has a good therapeutic effect on non-proliferatic diabetic retinopathy and can improve the clinical symptoms of patients. This study aimed to predict and verify the protective effect and mechanism of RRP on retinal oxidative damage in mice based on network pharmacology and animal experiments. A total of 15 key active components included in RRP interacted with 57 core targets related to retinal oxidative damage (such as AKT1, NFE2L2, HMOX1), mainly involved in the AGE-RAGE signaling pathway in diabetic complications, PI3K-AKT signaling pathway and so on. Further studies in vivo found that RRP improved the retinal oxidative damage, increased the content of SOD and GSH, decreased the content of MDA in mouse serum, promoted the expression of p-PI3K, p-AKT, Nrf2, HO-1 and NQO1 proteins in the mouse retina, and inhibited the expression of Nrf2 in the cytoplasm. This study revealed that RRP had a protective effect on oxidative damage of the retina in mice, and might exert anti-oxidative effect by activating the PI3K/Akt/Nrf2 signal pathway. This study provided scientific data for the further development of hospital preparations of RRP, and a good theoretical basis for the clinical application of RRP.

Luteolin Alleviates Diabetic Nephropathy Fibrosis Involving AMPK/NLRP3/TGF-β Pathway.

Luteolin is a promising candidate for diabetic nephropathy due to its potential anti-inflammatory and anti-fibrotic properties. This study explored the molecular mechanisms through which luteolin combats fibrosis in DN. Potential targets affected by luteolin and genes associated with DN were collected from databases. Overlapping targets between luteolin and diabetic nephropathy were identified through Venn analysis. A protein-protein interaction network was constructed using these common targets, and critical pathways and targets were elucidated through GO and KEGG analysis. These pathways and targets were confirmed using a streptozotocin-induced mouse model. Luteolin was administered at 45 mg/kg and 90 mg/kg. Various parameters were evaluated, including body weight, blood glucose levels, and histopathological examinations. Protein levels related to energy metabolism, inflammation, and fibrosis were quantified. Fifty-three targets associated with luteolin and 36 genes related to diabetic nephropathy were extracted. The AGE-RAGE signaling pathway was the key pathway impacted by luteolin in diabetic nephropathy. Key molecular targets include TGF-β, IL-1β, and PPARG. Luteolin reduced body weight and blood glucose levels, lowered the left kidney index, and improved insulin and glucose tolerance. Furthermore, luteolin mitigated inflammatory cell infiltration, basement membrane thickening, and collagen deposition in the kidney. Luteolin up-regulated the protein expression of p-AMPKα (Th172) while simultaneously down-regulated the protein expression of p-NF-ĸB (p65), NLRP3, TGF-β1, α-SMA, and Collagen I. Luteolin mitigated renal fibrosis by alleviating energy metabolism disruptions and inflammation by modulating the AMPK/NLRP3/TGF-β signaling pathway.

Mechanism of baicalein in treatment of castration-resistant prostate cancer based on network pharmacology and cell experiments.

Baicalein, one of the most abundant flavonoids found in Chinese herb Scutellaria baicalensis Georgi, exhibits pharmacological activities against various cancers. However, the precise pharmacological mechanism of baicalein in treating castration-resistant prostate cancer (CRPC) remains elusive. This study aimed to elucidate the potential mechanism of baicalein against CRPC through a combination of network pharmacology and experimental approaches, thereby providing new avenues for research in CRPC treatment. The pharmacological and molecular properties of baicalein were obtained using the TCMSP database. Baicalein-related targets were collected from multiple sources including SwissTargetPrediction, PharmMapper and CTD. Targets related to CRPC were acquired from DisGeNET, GeneCards, and CTD. The protein-protein interaction (PPI) was analyzed using STRING 11.5, and Cytoscape 3.7.2 software was utilized to explore the core targets of baicalein on CRPC. GO and KEGG pathway enrichment analysis were performed using DAVID database. Cell experiments were carried out to confirm the validity of the targets. A total of 131 potential targets of baicalein for the treatment of CRPC were obtained. Among them, TP53, AKT1, ALB, CASP3, and HSP90AA1, etc., were recognized as core targets by Cytoscape 3.7.2. GO function enrichment analysis yielded 926 entries, including 703 biological process (BP) terms, 84 cellular component (CC) terms and 139 molecular function (MF) terms. The KEGG pathway enrichment analysis unveiled 159 signaling pathways, mainly involved in Pathways in cancer, prostate cancer, AGE-RAGE signaling pathway in diabetic complications, TP53 signaling pathway, and PI3K-Akt signaling pathway, etc. Cell experiments confirmed that baicalein may inhibit the proliferation of CRPC cells and induce cell cycle arrest in the G1 phase. This effect could be associated with the TP53/CDK2/cyclin E1 pathway. In addition, the results of CETSA suggest that baicalein may directly bind to TP53. Based on network pharmacology analysis and cell experiments, we have predicted and validated the potential targets and related pathways of baicalein for CRPC treatment. This comprehensive approach provides a scientific basis for elucidating the molecular mechanism underlying the action of baicalein in CRPC treatment. Furthermore, these findings offer valuable insights and serve as a reference for the research and development of novel anti-CRPC drugs.

Elucidating the mechanisms of Buyang Huanwu Decoction in treating chronic cerebral ischemia: A combined approach using network pharmacology, molecular docking, and in vivo validation

ObjectiveThis study aimed to explore the potential mechanisms of Buyang Huanwu Decoction (BHD) in regulating the AKT/TP53 pathway and reducing inflammatory responses for the treatment of chronic cerebral ischemia (CCI) using UHPLC-QE-MS combined with network pharmacology, molecular docking techniques, and animal experiment validation. MethodsTargets of seven herbal components in BHD, such as Astragalus membranaceus, Paeoniae Rubra Radix, and Ligusticum chuanxiong, were identified through TCMSP and HERB databases. CCI-related targets were obtained from DisGeNET and Genecards, with an intersection analysis conducted to determine shared targets between the disease and the herbal components. Functional enrichment analysis of these intersecting targets was performed. Networks of gene ontology and pathway associations with these targets were constructed and visualized. A pharmacological network involving intersecting genes and active components was delineated. A protein-protein interaction network was established for these intersecting targets and visualized using Cytoscape 3.9.1. The top five genes from the PPI network and their corresponding active components underwent molecular docking. Finally, the 2-vessel occlusion (2-VO) induced CCI rat model was treated with BHD, and the network pharmacology findings were validated using Western blot, RT-PCR, behavioral tests, laser speckle imaging, ELISA, HE staining, Nissl staining, LFB staining, and immunohistochemistry and immunofluorescence. ResultsAfter filtration and deduplication, 150 intersecting genes were obtained, with the top five active components by Degree value identified as Quercetin, Beta-Sitosterol, Oleic Acid, Kaempferol, and Succinic Acid. KEGG pathway enrichment analysis linked key target genes significantly with Lipid and atherosclerosis, AGE-RAGE signaling pathway, IL-17 signaling pathway, and TNF signaling pathway. The PPI network highlighted ALB, IL-6, AKT1, TP53, and IL-1β as key protein targets. Molecular docking results showed the strongest binding affinity between ALB and Beta-Sitosterol. Behavioral tests using the Morris water maze indicated that both medium and high doses of BHD could enhance spatial memory in 2-VO model rats, with high-dose BHD being more effective. Laser speckle results showed that BHD at medium and high doses could facilitate CBF recovery in CCI rats, demonstrating a dose-response relationship. HE staining indicated that all doses of BHD could reduce neuronal damage in the cortex and hippocampal CA1 region to varying extents, with the highest dose being the most efficacious. Nissl staining showed that nimodipine and medium and high doses of BHD could alleviate Nissl body damage. LFB staining indicated that nimodipine and medium and high doses of BHD could reduce the pathological damage to fiber bundles and myelin sheaths in the internal capsule and corpus callosum of CCI rats. ELISA results showed that nimodipine and BHD at medium and high doses could decrease the levels of TNF-α, IL-6, IL-17, and IL-1β in the serum of CCI rats (p < 0.05). Immunohistochemistry and immunofluorescence demonstrated that BHD could activate the AKT signaling pathway and inhibit TP53 in treating CCI. Western blot and RT-PCR results indicated that nimodipine and all doses of BHD could upregulate Akt1 expression and downregulate Alb, Tp53, Il-1β, and Il-6 expression in the hippocampus of CCI rats to varying degrees (p < 0.05). ConclusionBHD exerts therapeutic effects in the treatment of CCI by regulating targets, such as AKT1, ALB, TP53, IL-1β, and IL-6, and reducing inflammatory responses.

Effects of gut microbiota-derived short-chain fatty acids on cognitive impairment: An in-silico study

Increasing evidence suggests that gut microbiota-derived metabolites affect cognitive function, but the underlying molecular mechanisms remain unclear. In this study, mechanisms of cognitive dysfunction that can be targeted by acetic acid and butyric acid were analyzed using literature review, Metascape, Mienturnent, Passonline, and WissADME. We found that acetic acid and butyric acid may regulate important genes (PPARG, CASP3, IL1B, SOD2, and TNF) that protect against cognitive decline. We also found microRNAs (hsa-miR-17-5p and hsa-miR-20a-5p) and transcription factors (RELA and NFKB1) that play a critical role in this protective mechanism. The AGE-RAGE signaling pathway and apoptosis pathways also emerged as crucial to understanding the underlying pathophysiological mechanisms. Our findings are further supported by the physicochemical properties and pharmacokinetic profiles of acetic acid and butyric acid, which demonstrate remarkable intestinal absorption, ability to penetrate the blood-brain barrier, and non-inhibition of CYP450 enzymes. Our study provides further evidence of the therapeutic potential of butyric acid in managing cognitive impairment, including its anti-inflammatory properties, stimulation of insulin synthesis, and regulation of lipid metabolism. We also identified several promising treatments for cognitive impairment, including miRNA sponges, mesalazine, omega-3 fatty acids, pomalidomide, and andrographolide. Focused investigations into the apoptosis and AGE-RAGE signaling pathways, miRNA sponges, promising drugs, and the role of gut microbiota in cognitive function are warranted.

Ge-Gen-Qin-Lian decoction alleviates the symptoms of type 2 diabetes mellitus with inflammatory bowel disease via regulating the AGE-RAGE pathway

BackgroundThis study aimed to explore the mechanism of Ge-Gen-Qin-Lian decoction (GGQLD) in the alleviation of symptoms of type 2 diabetes mellitus (T2DM) with inflammatory bowel disease (IBD) by network pharmacology and experimental validation.MethodsThe active components and targets of GGQLD were identified from the TCMSP database. The potential therapeutic targets of T2DM and IBD were identified from the GEO database and 4 online disease target databases. The PPI network and KEGG/GO analyses were performed with the common targets among GGQLD, T2DM and IBD. Molecular docking was carried out between the core compounds and hub targets. To verify the above results, UHPLC-MS technology was used to identify the chemical compounds in GGQLD, and a T2DM with IBD rat model was used to explore the mechanism by which GGQLD treats T2DM with IBD.ResultsTotally, 70 potential therapeutic targets were identified among GGQLD, T2DM and IBD. Ten hub genes were selected from the PPI network. KEGG analysis revealed that GGQLD is tightly involved in the AGE-RAGE signaling pathway. Berberine, baicalein, wogonin, and quercitrin are the main active compounds of GGQLD. Animal experiments showed that GGQLD could decrease blood glucose and alleviate intestinal inflammation. Notably, the concentrations of AGEs, the expression of RAGE, c-JUN and NF-κB and the expression of inflammatory cytokines were decreased by GGQLD.ConclusionsOur study initially demonstrated that GGQLD has favorable anti-hyperglycemic and anti-intestinal inflammation effects in a T2DM with IBD rat model, and the AGE-RAGE pathway plays a vital role in this process.

Mechanism of network pharmacology of Erzhi Pill and Erxian Decoction in treating climacteric syndrome with "treating the same disease with different methods": A review.

Network pharmacology and molecular docking methods were used in the present study to clarify the molecular mechanism of two traditional Chinese medicine prescriptions of climacteric syndrome. Based on oral availability and drug similarity, the main active components of Erzhi Pill and Erxian Decoction were screened through the platform of traditional Chinese medicine system pharmacology. The target database of climacteric syndrome was established by using GENECARD, OMIM, PharmGKB, Targets and Drugbank. The "component - target" network diagram was constructed using Cytoscape software (version 3.8.2). Topology analysis, module analysis, and GO and KEGG enrichment analyses were used to explore the core target and action pathway of Erzhi Pill-Erxian Decoction for treating climacteric syndrome of same disease with different treatments. There were 16 active components and 103 corresponding targets found in Erzhi Pill; 69 active components and 121 corresponding targets were found in Erxian Decoction; and 100 potential targets were found in Erzhi Pill and Erxian Decoction. Through network analysis, topology and module analysis, TP53, AKT1, Jun, ESR1, IL1B, CASP3, MMP9, PTGS2, HIF1A, MYC and EGFR could be considered as potential targets of the 2 prescriptions for alleviating climacteric syndrome. The effects of Erzhi pill and Erxian Decoction on climacteric syndrome are mainly in the pathway of lipid and atherosclerosis, AGE-RAGE signaling pathway and PI3K-Akt signaling pathway in diabetic complications. The active components in Erzhi Pill - Erxian Decoction, such as quercetin, show considerable potential as a candidate drug for the treatment of climacteric syndrome.

Identification of potential shared gene signatures between gastric cancer and type 2 diabetes: a data-driven analysis.

Gastric cancer (GC) and type 2 diabetes (T2D) contribute to each other, but the interaction mechanisms remain undiscovered. The goal of this research was to explore shared genes as well as crosstalk mechanisms between GC and T2D. The Gene Expression Omnibus (GEO) database served as the source of the GC and T2D datasets. The differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) were utilized to identify representative genes. In addition, overlapping genes between the representative genes of the two diseases were used for functional enrichment analysis and protein-protein interaction (PPI) network. Next, hub genes were filtered through two machine learning algorithms. Finally, external validation was undertaken with data from the Cancer Genome Atlas (TCGA) database. A total of 292 and 541 DEGs were obtained from the GC (GSE29272) and T2D (GSE164416) datasets, respectively. In addition, 2,704 and 336 module genes were identified in GC and T2D. Following their intersection, 104 crosstalk genes were identified. Enrichment analysis indicated that "ECM-receptor interaction," "AGE-RAGE signaling pathway in diabetic complications," "aging," and "cellular response to copper ion" were mutual pathways. Through the PPI network, 10 genes were identified as candidate hub genes. Machine learning further selected BGN, VCAN, FN1, FBLN1, COL4A5, COL1A1, and COL6A3 as hub genes. "ECM-receptor interaction," "AGE-RAGE signaling pathway in diabetic complications," "aging," and "cellular response to copper ion" were revealed as possible crosstalk mechanisms. BGN, VCAN, FN1, FBLN1, COL4A5, COL1A1, and COL6A3 were identified as shared genes and potential therapeutic targets for people suffering from GC and T2D.

Network pharmacology and experimental verification to explore the effect of Hedyotis diffusa on Alzheimer's disease.

This study aimed to explore the active components and the effect of Hedyotis diffusa (HD) against Alzheimer's disease (AD) via network pharmacology, molecular docking, and experimental evaluations. We conducted a comprehensive screening process using the TCMSP, Swiss Target Prediction, and PharmMapper databases to identify the active components and their related targets in HD. In addition, we collected potential therapeutic targets of AD from the Gene Cards, Drugbank, and OMIM databases. Afterward, we utilized Cytoscape to establish both protein-protein interaction (PPI) networks and compound-target (C-T) networks. To gain further insights into the functional aspect, we performed GO and KEGG pathway analyses using the David database. Next, we employed Autodock vina to estimate the binding force between the components and the hub genes. To validate our network pharmacology findings, we conducted relevant experiments on Caenorhabditis elegans, further confirming the reliability of our results. Then a total of six active compounds and 149 therapeutic targets were detected. Through the analysis of the association between active compounds, therapeutic targets, and signaling pathways, it was observed that the therapeutic effect of HD primarily encompassed the inhibition of Aβ, suppression of AChE activity, and mitigating oxidative stress. Additionally, our investigation revealed that the key active compounds in HD primarily consisted of iridoids, which exhibited resistance against AD by acting on the Alzheimer's disease pathway and the AGE-RAGE signaling pathway in diabetic complications.

Exploration of the Potential and Mechanisms of Diabetic Cognitive Disorder Modulation by Daehwangmokdanpi-tang through a Network Pharmacological Approach

Objectives: This study utilized a network pharmacology approach to investigate the potential therapeutic effects and underlying mechanisms of Daehwangmokdanpi-tang (DHMDPT) in diabetic cognitive disorder (DCD).Methods: The compounds of DHMDPT and their target genes were obtained from the OASIS and PubChem databases. These putative target genes were compared with known targets of DCD to identify potential correlations. Using Cytoscape 3.10.2, a network was constructed to highlight key target genes. To further elucidate the underlying mechanisms, functional enrichment analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Finally, CB-DOCK was used to assess binding affinities and confirm the interactions.Results: The results showed that a total of 27 compounds and 439 related genes were identified from DHMDPT. Among these, 373 genes interacted with the DCD gene set, indicating a close relationship between the effects of DHMDPT and DCD. Through GO enrichment analysis and KEGG pathways, ‘Regulation of Apoptotic Process’, ‘Cytokine-Mediated signaling pathway’, and ‘AGE-RAGE signaling pathway in diabetic complications’ were identified as the functional pathways of the 18 key target genes of DHMDPT on DCD. Additionally, molecular docking was performed to assess the binding affinities of the six most highly associated key target genes of DCD with active compounds.Conclusions: Using a network pharmacology approach, which included molecular docking, DHMDPT was found to be highly relevant to DCD. This study could serve as a foundation for further research on the cognitive enhancement effects of DHMDPT in DCD.

Integrative Bioinformatics Approaches to Uncover Hub Genes and Pathways Involved in Cardiovascular Diseases.

Cardiovascular diseases (CVD) represent a significant global health challenge resulting from a complex interplay of genetic, environmental, and lifestyle factors. However, the molecular pathways and genetic factors involved in the onset and progression of CVDs remain incompletely understood. Here, we performed an integrative bioinformatic analysis to highlight specific genes and signaling pathways implicated in the pathogenesis of 80 CVDs. Differentially expressed genes (DEGs) were identified through the integrated analysis of microarray and GWAS datasets. Then, hub genes were identified after gene ontology functional annotation analysis and protein-protein internet (PPI) analysis. In addition, pathways were identified through KEGG and gene ontology enrichment analyses. A total of 821 hub genes related to 80 CVDs were identified, including 135 common and frequent CVD-associated genes. TNF, IL6, VEGFA, and TGFB.1 genes were the central core genes expressed in 50% or more of CVDs, confirming that the inflammation is a key pathological feature of CVDs. Analysis of hub genes by KEGG enrichment revealed predominant enrichment in 201 KEGG pathways, of which the AGE-RAGE signaling pathway in diabetic complications was identified as the common key KEGG implicated in 62 CVDs. In addition, the outcomes showed an overrepresentation in pathways categorized under human diseases, particularly in the subcategories of infectious diseases and cancers, which may be common risk factors for CVDs. In conclusion, this powerful approach for in silico fine-mapping of genes and pathways allowed the identification of determinant hubs genes and pathways implicated in the pathogenesis of CVDs which could be employed in developing more targeted and effective interventions for preventing, diagnosing, and treating CVDs. The function of these hub genes in CVDs needs further exploration to elucidate their biological characteristics.

Whole transcriptome analysis revealed the regulatory network and related pathways of non-coding RNA regulating ovarian atrophy in broody hens.

Poultry broodiness can cause ovarian atresia, which has a detrimental impact on egg production. Non-coding RNAs (ncRNAs) have become one of the most talked-about topics in life sciences because of the increasing evidence of their novel biological roles in regulatory systems. However, the molecular mechanisms of ncRNAs functions and processes in chicken ovarian development remain largely unknown. Whole-transcriptome RNA sequencing of the ovaries of broodiness and laying chickens was thus performed to identify the ncRNA regulatory mechanisms associated with ovarian atresia in chickens. Subsequent analysis revealed that the ovaries of laying chickens and those with broodiness had 40 differentially expressed MicroRNA (miRNAs) (15 up-regulated and 25 down-regulated), 379 differentially expressed Long Noncoding RNA (lncRNAs) (213 up-regulated and 166 down-regulated), and 129 differentially expressed circular RNA (circRNAs) (63 up-regulated and 66 down-regulated). The competing endogenous RNAs (ceRNA) network analysis further revealed the involvement of ECM-receptor interaction, AGE-RAGE signaling pathway, focal adhesion, cytokine-cytokine receptor interaction, inflammatory mediator regulation of TRP channels, renin secretion, gap junction, insulin secretion, serotonergic synapse, and IL-17 signaling pathways in broodiness. Upon further analysis, it became evident that THBS1 and MYLK are significant candidate genes implicated in the regulation of broodiness. The expression of these genes is linked to miR-155-x, miR-211-z, miR-1682-z, gga-miR-155, and gga-miR-1682, as well as to the competitive binding of novel_circ_014674 and MSTRG.3306.4. The findings of this study reveal the existence of a regulatory link between non-coding RNAs and their competing mRNAs, which provide a better comprehension of the ncRNA function and processes in chicken ovarian development.

Identification of key genes and biological pathways associated with vascular aging in diabetes based on bioinformatics and machine learning.

Vascular aging exacerbates diabetes-associated vascular damage, a major cause of microvascular and macrovascular complications. This study aimed to elucidate key genes and pathways underlying vascular aging in diabetes using integrated bioinformatics and machine learning approaches. Gene expression datasets related to vascular smooth muscle cell (VSMC) senescence and diabetic vascular aging were analyzed. Differential expression analysis identified 428 genes associated with VSMC senescence. Functional enrichment revealed their involvement in cellular senescence, ECM-receptor interaction, PI3K-Akt and AGE-RAGE signaling pathways. Further analysis of diabetic vascular aging datasets revealed 52 differentially expressed genes, enriched in AMPK signaling, AGE-RAGE signaling, cellular senescence, and VEGF signaling pathways. Machine learning algorithms, including LASSO regression and SVM-RFE, pinpointed six key genes: TFB1M, FOXRED2, LY75, DALRD3, PI4K2B, and NDOR1. Immune cell infiltration analysis demonstrated correlations between diabetic vascular aging, the identified key genes, and infiltration levels of plasma cells, M1 macrophages, CD8+ T cells, eosinophils, and regulatory T cells. In conclusion, this study identified six pivotal genes (TFB1M, FOXRED2, LY75, DALRD3, PI4K2B, and NDOR1) closely associated with diabetic vascular aging through integrative bioinformatics and machine learning approaches. These genes are linked to alterations in the immune microenvironment during diabetic vascular aging. This study provides a reference and basis for molecular mechanism research, biomarker mining, and diagnosis and treatment evaluation of diabetes-related vascular aging.

Exploration of Potential Targets and Molecular Mechanisms of the Yiqi Jianpi Tongqiao Formula in Treating Allergic Rhinitis Mouse Model based on Network Pharmacology and Molecular Docking.

To investigate the therapeutic effect of Yiqi Jianpi Tongqiao (YJT) formula (Hedysarum Multijugum Maxim, Magnoliae Flos, Xanthii Fructus, Notopterygii Rhizoma Et Radix, Kaempferiae Rhizoma, Acoritataninowii Rhizoma, Saposhnikoviae Radix) on an allergic rhinitis mouse model, and to explore the active ingredients, key targets, and molecular mechanisms of this formula using network pharmacology and molecular docking methods. An allergic rhinitis mouse model was established to observe changes in rhinitis symptoms, nasal mucosal morphology, and serum indicators after administering the YJT formula. The TCMSP, GeneCards, OMIM, and DisGeNET databases were used to screen for the active ingredients, action targets, and disease targets of the YJT formula. The Cytoscape software was used to construct a network of the active ingredients and action targets. The protein-protein interaction (PPI) network was used to predict hub genes. The corresponding active compounds with the hub genes' highest oral bioavailability (OB) values were identified, followed by molecular docking analysis. Animal experiments demonstrated that the YJT formula reduced rhinitis symptoms (nasal itching, runny nose, and face scratching) in allergic rhinitis mice, as well as decreased nasal mucosal inflammatory reactions and serum inflammatory indicators (histamine, OVAspecific IgE, IL-1β levels). Furthermore, 63 active components and 101 potential indicator targets of the YJT formula were identified, along with 5 hub genes (IL6, AKT1, IL1B, VEGFA, and PTGS2), and the corresponding active compounds with the highest OB values were quercetin, aloe-emodin, and denudanolide b. Molecular docking results revealed the binding energy between quercetin, aloe-emodin, denudanolide b and 5 hub genes (IL6, AKT1, IL1B, VEGFA, and PTGS2) were -5.78 to -10.22 kcal/mol, the binding energy between dexamethasone and 5 hub genes were -6.3 to -9.7 kcal/mol. In addition, GO and KEGG analysis suggested significant enrichment of these genes in biological processes such as response to lipopolysaccharide, response to molecule of bacterial origin, and response to reactive oxygen species, as well as signaling pathways like AGE-RAGE signaling pathway in diabetic complications, Lipid and atherosclerosis, and IL-17 signaling pathway. The YJT formula has therapeutic effects in an allergic rhinitis mouse model, with the main active components being quercetin, aloe-emodin, and denudanolide b, and the key targets being IL6, AKT1, IL1B, VEGFA, and PTGS2, involving multiple signaling pathways.

Study on the bioactive ingredients and mechanism of Huangqi against diabetic retinopathy based on network pharmacology and experimental verification.

Diabetic retinopathy (DR) is one of the most well-known microvascular complications of diabetes mellitus. As a traditional Chinese medicine, Huangqi (HQ), has been used for treating DR for a long time. However, its anti-DR active ingredients and mechanism are still unknown. Therefore, we designed this study to explore the active components and mechanism of HQ against DR via network pharmacology analysis. The ingredients of HQ, and potential targets of HQ and DR were obtained from public databases. We used the protein-protein interaction (PPI) network, Kyoto Encyclopedia of Genes and Genomes (KEGGs) pathway enrichment, and Gene Ontology (GO) analysis to identify core targets and pathways of HQ against DR. Finally, molecular docking and vitro experiments were applied to validate our results. A total of 34 potential targets of HQ against DR were obtained. Based on PPI network, VEGFA, PTGS2, Interleukin-6 (IL-6), and CCL2 were considered as core targets. GO analysis involved 692 biological processes, 21 cellular components, and 35 molecular functions. KEGG enrichment analysis manifested that the anti-DR effect of HQ was mainly mediated via the AGE-RAGE signaling pathway in diabetic complications. The molecular docking results indicated that kaempferol had higher affinity with CCL2, IL-6, VEGFA, and PTGS2. The vitro experiments showed that the mRNA expressions of CCL2, IL-6, VEGFA, and PTGS2 in ARPE-19 cells were differentially decreased after kaempferol treatment. This study preliminarily unveiled that the therapeutic efficacy of HQ against DR might be attributed to the reduced expression of CCL2, IL-6, VEGFA, and PTGS2.

The Mechanism of "Treating Different Diseases with the Same Treatment" by Qiangji Jianpi Decoction in Ankylosing Spondylitis Combined with Inflammatory Bowel Disease: A Comprehensive Analysis of Multiple Methods.

Ankylosing spondylitis (AS) and inflammatory bowel disease (IBD) are prevalent autoimmune disorders that often co-occur, posing significant treatment challenges. This investigation adopts a multidisciplinary strategy, integrating bioinformatics, network pharmacology, molecular docking, and Mendelian randomization, to elucidate the relationship between AS and IBD and to investigate the potential mechanisms of traditional Chinese medicine formulations, represented by Qiangji Jianpi (QJJP) decoction, in treating these comorbid conditions. We utilized databases to pinpoint common targets among AS, IBD, and QJJP decoction's active compounds through intersection analysis. Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, we mapped a network in Cytoscape, isolating critical targets. Molecular docking with AutoDock validated the affinity between targets and compounds. ROC analysis and dataset validation assessed diagnostic performance, while Gene Set Enrichment Analysis (GSEA) offered pathway insights. Mendelian randomization explored the AS-IBD causal relationship. Screening identified 105 targets for QJJP decoction, 414 for AS, and 2420 for IBD, with 85 overlapping. These targets predominantly participate in organismal responses and DNA transcription factor binding, with a significant cellular presence in the endoplasmic reticulum and vesicle lumen. Molecular docking, facilitated by Cytoscape, confirmed IL1A, IFNG, TGFB1, and EDN1 as critical targets, with IFNG demonstrating diagnostic potential through GEO dataset validation. The integration of GSEA with network pharmacology highlighted the therapeutic significance of the relaxin, osteoclast differentiation, HIF-1, and AGE-RAGE signaling pathways in QJJP decoction's action. Mendelian randomization analysis indicated a positive causal relationship between IBD and AS, pinpointing rs2193041 as a key SNP influencing IFNG. Based on the principle of "treating different diseases with the same method" in traditional Chinese medicine theory, we explored the intricate mechanisms through which QJJP decoction addresses AS and IBD comorbidity. Our research spotlighted the pivotal role of the IFNG gene. IFNG emerges not only as a key therapeutic target but also assumes significance as a potential diagnostic biomarker through its genetic underpinnings. This investigation establishes a solid base for subsequent experimental inquiries. Our findings introduce novel approaches for incorporating traditional Chinese medicine into the treatment of AS-IBD comorbidity, setting the stage for groundbreaking research directions.

Preliminary Exploration of Potential Active Ingredients and Molecular Mechanisms of Yanggan Yishui Granules for Treating Hypertensive Nephropathy Using UPLC-Q-TOF/MS Coupled with Network Pharmacology and Molecular Docking Strategy.

Hypertensive nephropathy (HN) is a prevalent complication of hypertension and stands as the second primary reason for end-stage renal disease. Research in clinical settings has revealed that Yanggan Yishui Granule (YGYSG) has significant therapeutic effects on HN. However, the material basis and action mechanisms of YGYSG against HN remain unclear. Consequently, this study utilized a comprehensive method integrating ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS), network pharmacology, and molecular docking to delineate the active ingredients and potential therapeutic mechanisms of YGYSG for treating HN. Firstly, sixty distinct components were recognized in total as potential active ingredients in YGYSG by UPLC-Q-TOF/MS. Subsequently, the mechanisms of YGYSG against HN were revealed for the first time using network pharmacology. 23 ingredients played key roles in the complete network and were the key active ingredients, which could affect the renin-angiotensin system, fluid shear stress and atherosclerosis, HIF-1 signaling pathway, and AGE-RAGE signaling pathway in diabetic complications by regulating 29 key targets such as TNF, IL6, ALB, EGFR, ACE, and MMP2. YGYSG could treat HN through the suppression of inflammatory response and oxidative stress, attenuating the proliferation of renal vascular smooth muscle cells, lessening glomerular capillary systolic pressure, and ameliorating renal dysfunction and vascular damage through the aforementioned targets and pathways. Molecular docking results revealed that most key active ingredients exhibited a high affinity for binding to the key targets. This study pioneers in clarifying the bioactive compounds and molecular mechanisms of YGYSG against HN and offers scientific reference into the clinical application.

Identification of key genes affecting ventilator-induced diaphragmatic dysfunction in diabetic mice.

Mechanical ventilation (MV) is often required in critically ill patients. However, prolonged mechanical ventilation can lead to Ventilator-induced diaphragmatic dysfunction (VIDD), resulting in difficulty in extubation after tracheal intubation, prolonged ICU stay, and increased mortality. At present, the incidence of diabetes is high in the world, and the prognosis of diabetic patients with mechanical ventilation is generally poor. Therefore, the role of diabetes in the development of VIDD needs to be discovered. MV modeling was performed on C57 mice and DB mice, and the control group was set up in each group. After 12h of mechanical ventilation, the muscle strength of the diaphragm was measured, and the muscle fiber immunofluorescence staining was used to verify the successful establishment of the MV model. RNA sequencing (RNA-seq) method was used to detect mRNA expression levels of the diaphragms of each group, and then differential expressed gene analysis, Heatmap analysis, WGCNA analysis, Venn analysis, GO and KEGG enrichment analysis were performed. qRT-PCR was used to verify the expression of the selected mRNAs. Our results showed that, compared with C57 control mice, the muscle strength and muscle fiber cross-sectional area of mice after mechanical ventilation decreased, and DB mice showed more obvious in this respect. RNA-seq showed that these differential expressed (DE) mRNAs were mainly related to genes such as extracellular matrix, collagen, elastic fiber and Fbxo32. GO and KEGG enrichment analysis showed that the signaling pathways associated with diabetes were mainly as follows: extracellular matrix (ECM), protein digestion and absorption, PI3K-Akt signaling pathway, calcium signaling pathway, MAPK signaling pathway and AGE-RAGE signaling pathway in diabetic complications, etc. ECM has the closest relationship with VIDD in diabetic mice. The key genes determined by WGCNA and Venn analysis were validated by quantitative real-time polymerase chain reaction (qRT-PCR), which exhibited trends similar to those observed by RNA-seq. VIDD can be aggravated in diabetic environment. This study provides new evidence for mRNA changes after mechanical ventilation in diabetic mice, suggesting that ECM and collagen may play an important role in the pathophysiological mechanism and progression of VIDD in diabetic mice, and provides some clues for the research, diagnosis, and treatment of VIDD in diabetic context.

Targeting Metabolic Syndrome Pathways: Carrot microRNAs As Potential Modulators.

Metabolic syndrome is a condition characterized by metabolic alterations that culminate in chronic noncommunicable diseases of high morbidity and mortality, such as cardiovascular diseases, type 2 diabetes, nonalcoholic fatty liver disease, and colon cancer. Developing new therapeutic strategies with a multifactorial approach is important since current therapies focus on only one or two components of the metabolic syndrome. In this sense, plant-based gene regulation represents an innovative strategy to prevent or modulate human metabolic pathologies, including metabolic syndrome. Here, using a computational and systems biology approach, it was found that carrot microRNAs can modulate key BMPs/SMAD signaling members, C/EBPs, and KLFs involved in several aspects associated with metabolic syndrome, including the hsa04350:TGF-beta signaling pathway, hsa04931:insulin resistance, hsa04152:AMPK signaling pathway, hsa04933:AGE-RAGE signaling pathway in diabetic complications, hsa04010:MAPK signaling pathway, hsa04350:TGF-beta signaling pathway, hsa01522:endocrine resistance, and hsa04910:insulin signaling pathway. These data demonstrated the potential applications of carrot microRNAs as effective food-based therapeutics for obesity and associated metabolic diseases.

Exploring the mechanism of Jinlida granules against type 2 diabetes mellitus by an integrative pharmacology strategy

Jinlida granule (JLD) is a Traditional Chinese Medicine (TCM) formula used for the treatment of type 2 diabetes mellitus (T2DM). However, the mechanism of JLD treatment for T2DM is not fully revealed. In this study, we explored the mechanism of JLD against T2DM by an integrative pharmacology strategy. Active components and corresponding targets were retrieved from Traditional Chinese Medicine System Pharmacology (TCMSP), SwissADME and Bioinformatics Analysis Tool for Molecular Mechanisms of Traditional Chinese Medicine Database (BATMAN-TCM) database. T2DM-related targets were obtained from Drugbank and Genecards databases. The protein–protein interaction (PPI) network was constructed and analyzed with STRING (Search Toll for the Retrieval of Interacting Genes/proteins) and Cytoscape to get the key targets. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) enrichment analyses were performed with the Database for Annotation, Visualization and Integrated Discovery (DAVID). Lastly, the binding capacities and reliability between potential active components and the targets were verified with molecular docking and molecular dynamics simulation. In total, 185 active components and 337 targets of JLD were obtained. 317 targets overlapped with T2DM-related targets. RAC-alpha serine/threonine-protein kinase (AKT1), tumor necrosis factor (TNF), interleukin-6 (IL-6), cellular tumor antigen p53 (TP53), prostaglandin G/H synthase 2 (PTGS2), Caspase-3 (CASP3) and signal transducer and activator of transcription 3 (STAT3) were identified as seven key targets by the topological analysis of the PPI network. GO and KEGG enrichment analyses showed that the effects were primarily associated with gene expression, signal transduction, apoptosis and inflammation. The pathways were mainly enriched in PI3K-AKT signaling pathway and AGE-RAGE signaling pathway in diabetic complications. Molecular docking and molecular dynamics simulation verified the good binding affinity between the key components and targets. The predicted results may provide a theoretical basis for drug screening of JLD and a new insight for the therapeutic effect of JLD on T2DM.