An improved association-mining research for exploring Chinese herbal property theory: based on data of the Shennong's Classic of Materia Medica

Modulating the inflammatory microenvironment can inhibit the process of inflammatory diseases (IDs). A tri-cross-linked inflammatory microenvironment-responsive hydrogel with ideal mechanical properties achieves triggerable and sustained drug delivery and regulates the inflammatory microenvironment. Here, this study develops an inflammatory microenvironment-responsive hydrogel (OD-PP@SeNPs) composed of phenylboronic acid grafted polylysine (PP), oxidized dextran (OD), and selenium nanoparticles (SeNPs). The introduction of SeNPs as initiators and nano-fillers into the hydrogel results in extra cross-linking of the polymer network through hydrogen bonding. Based on Schiff base bonds, Phenylboronate ester bonds, and hydrogen bonds, a reactive oxygen species (ROS)/pH dual responsive hydrogel with a triple-network is achieved. The hydrogel has injectable, self-healing, adhesion, outstanding flexibility, suitable swelling capacity, optimal biodegradability, excellent stimuli-responsive active substance release performance, and prominent biocompatibility. Most importantly, the hydrogel with ROS scavenging and pH-regulating ability protects cells from oxidative stress and induces macrophages into M2 polarization to reduce inflammatory cytokines through PI3K/AKT/NF-κB and MAPK pathways, exerting anti-inflammatory effects and reshaping the inflammatory microenvironment, thereby effectively treating typical IDs, including S. aureus infected wound and rheumatoid arthritis in rats. In conclusion, this dynamically responsive injectable hydrogel with a triple-network structure provides an effective strategy to treat IDs, holding great promise in clinical application.

Triple Cross-linked Dynamic Responsive Hydrogel Loaded with Selenium Nanoparticles for Modulating the Inflammatory Microenvironment via PI3K/Akt/NF-κB and MAPK Signaling Pathways.

Action (“gongxiao” in Chinese) of traditional Chinese medicine (TCM) is the high recapitulation for therapeutic and health-preserving effects under the guidance of TCM theory. TCM-defined herbal properties (“yaoxing” in Chinese) had been used in this research. TCM herbal property (TCM-HP) is the high generalization and summary for actions, both of which come from long-term effective clinical practice in two thousands of years in China. However, the specific relationship between TCM-HP and action of TCM is complex and unclear from a scientific perspective. The research about this is conducive to expound the connotation of TCM-HP theory and is of important significance for the development of the TCM-HP theory. One hundred and thirty-three herbs including 88 heat-clearing herbs (HCHs) and 45 blood-activating stasis-resolving herbs (BAHRHs) were collected from reputable TCM literatures, and their corresponding TCM-HPs/actions information were collected from Chinese pharmacopoeia (2015 edition). The Kennard–Stone (K–S) algorithm was used to split 133 herbs into 100 calibration samples and 33 validation samples. Then, machine learning methods including supported vector machine (SVM), k-nearest neighbor (kNN) and deep learning methods including deep belief network (DBN), convolutional neutral network (CNN) were adopted to develop action classification models based on TCM-HP theory, respectively. In order to ensure robustness, these four classification methods were evaluated by using the method of tenfold cross validation and 20 external validation samples for prediction. As results, 72.7–100% of 33 validation samples including 17 HCHs and 16 BASRHs were correctly predicted by these four types of methods. Both of the DBN and CNN methods gave out the best results and their sensitivity, specificity, precision, accuracy were all 100.00%. Especially, the predicted results of external validation set showed that the performance of deep learning methods (DBN, CNN) were better than traditional machine learning methods (kNN, SVM) in terms of their sensitivity, specificity, precision, accuracy. Moreover, the distribution patterns of TCM-HPs of HCHs and BASRHs were also analyzed to detect the featured TCM-HPs of these two types of herbs. The result showed that the featured TCM-HPs of HCHs were cold, bitter, liver and stomach meridians entered, while those of BASRHs were warm, bitter and pungent, liver meridian entered. The performance on validation set and external validation set of deep learning methods (DBN, CNN) were better than machine learning models (kNN, SVM) in sensitivity, specificity, precision, accuracy when predicting the actions of heat-clearing and blood-activating stasis-resolving based on TCM-HP theory. The deep learning classification methods owned better generalization ability and accuracy when predicting the actions of heat-clearing and blood-activating stasis-resolving based on TCM-HP theory. Besides, the methods of deep learning would help us to improve our understanding about the relationship between herbal property and action, as well as to enrich and develop the theory of TCM-HP scientifically.

/pdf/development-of-models-for-classification-of-action-between-321yr1sity.pdf

Development of models for classification of action between heat-clearing herbs and blood-activating stasis-resolving herbs based on theory of traditional Chinese medicine

Abstract Objective To investigate the causal relationship between low bone mineral density (BMD) and osteoarthritis (OA) using Mendelian randomization (MR) design. Methods Two-sample bi-directional MR analyses were performed using summary-level information on OA traits from UK Biobank and arcOGEN. Sensitivity analyses including MR-Egger, simple median, weighted median, MR pleiotropy residual sum, and outlier approaches were utilized in conjunction with inverse variance weighting (IVW). Gene ontology (GO) enrichment analyses and expression quantitative trait locus (eQTL) colocalization analyses were used to investigate the potential mechanism and shared genes between osteoporosis (OP) and OA. Results The IVW method revealed that genetically predicted low femoral neck BMD was significantly linked with hip ( β = 0.105, 95% CI: 0.023–0.188) and knee OA ( β = 0.117, 95% CI: 0.049–0.184), but not with other site-specific OA. Genetically predicted low lumber spine BMD was significantly associated with OA at any sites ( β = 0.048, 95% CI: 0.011–0.085), knee OA ( β = 0.101, 95% CI: 0.045–0.156), and hip OA ( β = 0.150, 95% CI: 0.077–0.224). Only hip OA was significantly linked with genetically predicted reduced total bone BMD ( β = 0.092, 95% CI: 0.010–0.174). In the reverse MR analyses, no evidence for a causal effect of OA on BMD was found. GO enrichment analysis and eQTL analysis illustrated that DDN and SMAD-3 were the most prominent co-located genes. Conclusions These findings suggested that OP may be causally linked to an increased risk of OA, indicating that measures to raise BMD may be effective in preventing OA. More research is required to determine the underlying processes via which OP causes OA. 

Osteoporosis and osteoarthritis: a bi-directional Mendelian randomization study

Purpose OP and OA are chronic bone diseases with high incidence in the middle-aged and elderly populations. The latest research shows that the pathological environment of OP may be involved in the aggravation of the pathological process of OA, and the pathological state of OP plays an important role in the aggravation of OA pathology. EXD is a traditional Chinese medicine decoction that has been used to treat osteoporosis. Therefore, we further study whether OA will be aggravated in the OP environment and whether EXD can alleviate OA by intervening in the OP environment. The purpose of this study was to analyze the effect of OP on OA metabolites by using metabolomic methods and to explore the intervention mechanism of EXD on osteoporotic OA. Method Thirty-two SD rats were randomly divided into normal group, OA group, OP-OA group, and EXD group. EXD was administered by gavage. Histopathological evaluation of cartilage tissue was performed using Saffron fast green and HE staining. Western blot and qRT-PCR were used to detect the expression levels of chondrogenesis genes SOX9, COL2A1, and COMP in cartilage tissue. GC-TOFMS and LC-QTRAP-MS/MS metabolomics methods were used to analyze the changes of metabolites in serum samples of rats in each group. Result The slice results showed that the cartilage damage in the OP-OA group was more serious than that in the OA group, which was significantly relieved after EXD intervention, indicating that the cartilage damage in the OP-OA group was more severe than that in the OA group and further reduced the protein and gene expressions of cartilage markers SOX9, COL2A1, and COMP. Thirty-seven substances were identified, and gentiopicroside, emodin, quercetin, and diosmetin were analyzed as possible active components of EXD. EXD treatment significantly reduced cartilage damage and reversed the expression of these markers. Metabolomics showed that EXD attenuated cartilage destruction by modulating the expression of cystine, chenodeoxycholate, and D-Turanose, involving glycolysis/gluconeogenesis, pantothenate, and CoA biosynthesis metabolic pathways. Conclusion The OP environment may promote the progression of OA through metabolic factors. The benign intervention of EXD in osteoporotic OA involves cystine, chenodeoxycholate, and D-Turanose, and their associated glycolysis/gluconeogenesis, pantothenate, and CoA biosynthesis metabolic pathways. Therefore, we have a deep understanding of the metabolic-related intervention of EXD in osteoporotic OA and are eager to better understand the mechanism of multi-targeted intervention of EXD in bone metabolic lesions.

https://www.frontiersin.org/articles/10.3389/fendo.2022.905507/pdf

GCTOF-MS Combined LC-QTRAP-MS/MS Reveals Metabolic Difference Between Osteoarthritis and Osteoporotic Osteoarthritis and the Intervention Effect of Erxian Decoction

Overexpressed matrix metalloproteinases, hypoxia microenvironment, and metabolic abnormality are important pathological signs of rheumatoid arthritis (RA). Designing a delivery carrier according to the pathological characteristics of RA that can control drug release in response to disease severity may be a promising treatment strategy. Psoralen is the main active ingredient isolated from Psoralea corylifolia L. and possesses excellent anti-inflammatory activities as well as improving bone homeostasis. However, the specific underlying mechanisms, particularly the possible relationships between the anti-RA effects of psoralen and related metabolic network, remain largely unexplored. Furthermore, psoralen shows systemic side effects and has unsatisfactory solubility. Therefore, it is desirable to develop a novel delivery system to maximize psoralen's therapeutic effect. In this study, a self-assembled degradable hydrogel platform is developed that delivers psoralen and calcium peroxide to arthritic joints and controls the release of psoralen and oxygen according to inflammatory stimulation, to regulate homeostasis and the metabolic disorder of the anoxic arthritic microenvironment. Therefore, the hydrogel drug delivery system based on the responsiveness of the inflammatory microenvironment and regulation of metabolism provides a new therapeutic strategy for RA treatment.

A Metabolic Driven Bio-Responsive Hydrogel Loading Psoralen for Therapy of Rheumatoid Arthritis.

Methodology for Modeling on Chinese Herbal Property Theory

Chronic heart failure (CHF) is the primary cause of death among patients with cardiovascular diseases, representing the advanced stage in the development of several cardiovascular conditions. Zhenwu decoction (ZWD) has gained widespread recognition as an efficacious remedy for CHF due to its potent therapeutic properties and absence of adverse effects. Nevertheless, the precise molecular mechanisms underlying its actions remain elusive. This study endeavors to unravel the intricate pharmacological underpinnings of five herbs within ZWD concerning CHF through an integrated approach. Initially, pertinent data regarding ZWD and CHF were compiled from established databases, forming the foundation for constructing an intricate network of active component-target interactions. Subsequently, a pioneering method for evaluating node significance was formulated, culminating in the creation of core functional association space (CFAS). To discern vital components, a novel dynamic programming algorithm was devised and used to determine the core component group (CCG) within the CFAS. Enrichment analysis of the CCG targets unveiled the potential coordinated molecular mechanisms of ZWD, illuminating its capacity to ameliorate CHF by modulating genes and related signaling pathways involved in pathological remodeling. Notable pathways encompass PI3K-Akt, diabetic cardiomyopathy, cAMP and MAPK signaling. Concluding the computational analyses, in vitro experiments were executed to assess the effects of vanillic acid, paradol, 10-gingerol and methyl cinnamate. Remarkably, these compounds demonstrated efficacy in reducing the production of ANP and BNP within isoprenaline-induced AC 16 cells, further validating their potential therapeutic utility. This investigation underscores the efficacy of the proposed model in enhancing the precision and reliability of CCG selection within ZWD, thereby presenting a novel avenue for mechanistic inquiries, compound refinement and the secondary development of TCM herbs. 

System pharmacology-based determination of the functional components and mechanisms in chronic heart failure treatment: an example of Zhenwu decoction.

Osteoporosis (OP) is a systemic disease susceptible to fracture due to the decline of bone mineral density and bone mass, the destruction of bone tissue microstructure, and increased bone fragility. At present, the treatments of OP mainly include bisphosphonates, hormone therapy, and RANKL antibody therapy. However, these treatments have observable side effects and cannot fundamentally improve bone metabolism. Currently, the prescription of herbal medicine and their derived proprietary Chinese medicines are playing increasingly important roles in the treatment of OP due to their significant curative effects and few side effects. Among these prescriptions, Gushukang Granules (GSK), Xianling Gubao Capsules (XLGB), and Er-xian Decoction (EXD) are widely employed at the clinic on therapy of OP, which also is in line with the compatibility principle of “different treatments for the same disease” in herbal medicine. However, at present, the functional interpretation of “different treatments for the same disease” in herbal medicine still lacks systematic quantitative research, especially on the detection of key component groups and mechanisms. To solve this problem, we designed a new bioinformatics model based on random walk, optimized programming, and information gain to analyze the components and targets to figure out the Functional Response Motifs (FRMs) of different prescriptions for the therapy of OP. The distribution of high relevance score, the number of reported evidence, and coverage of enriched pathways were performed to verify the precision and reliability of FRMs. At the same time, the information gain and target influence of each component was calculated, and the key component groups in all FRMs of each prescription were screened to speculate the potential action mode of different prescriptions on the same disease. Results show that the relevance score and the number of reported evidence of high reliable genes in FRMs were higher than those of the pathogenic genes of OP. Furthermore, the gene enrichment pathways in FRMs could cover 79.6, 81, and 79.5% of the gene enrichment pathways in the component-target (C-T) network. Functional pathway enrichment analysis showed that GSK, XLGB, and EXD all treat OP through osteoclast differentiation (hsa04380), calcium signaling pathway (hsa04020), MAPK signaling pathway (hsa04010), and PI3K-Akt signaling pathway (hsa04151). Combined with experiments, the key component groups and the mechanism of “different treatments for the same disease” in the three prescriptions and proprietary Chinese medicines were verified. This study provides methodological references for the optimization and mechanism speculation of Chinese medicine prescriptions and proprietary Chinese medicines.

/pdf/uncovering-hidden-mechanisms-of-different-prescriptions-176u76j3.pdf

Uncovering Hidden Mechanisms of Different Prescriptions Treatment for Osteoporosis via Novel Bioinformatics Model and Experiment Validation

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A Metabolic Driven Bio-Responsive Hydrogel Loading Psoralen for Therapy of Rheumatoid Arthritis.

Methodology for Modeling on Chinese Herbal Property Theory

System pharmacology-based determination of the functional components and mechanisms in chronic heart failure treatment: an example of Zhenwu decoction.

Uncovering Hidden Mechanisms of Different Prescriptions Treatment for Osteoporosis via Novel Bioinformatics Model and Experiment Validation