GPT-4 can pass the Korean National Licensing Examination for Korean Medicine Doctors.

Traditional Korean medicine (TKM) emphasizes individualized diagnosis and treatment. This uniqueness makes AI modeling difficult due to limited data and implicit processes. Large language models (LLMs) have demonstrated impressive medical inference, even without advanced training in medical texts. This study assessed the capabilities of GPT-4 in TKM, using the Korean National Licensing Examination for Korean Medicine Doctors (K-NLEKMD) as a benchmark. The K-NLEKMD, administered by a national organization, encompasses 12 major subjects in TKM. GPT-4 answered 340 questions from the 2022 K-NLEKMD. We optimized prompts with Chinese-term annotation, English translation for questions and instruction, exam-optimized instruction, and self-consistency. GPT-4 with optimized prompts achieved 66.18% accuracy, surpassing both the examination's average pass mark of 60% and the 40% minimum for each subject. The gradual introduction of language-related prompts and prompting techniques enhanced the accuracy from 51.82% to its maximum accuracy. GPT-4 showed low accuracy in subjects including public health & medicine-related law, internal medicine (2), and acupuncture medicine which are highly localized in Korea and TKM. The model's accuracy was lower for questions requiring TKM-specialized knowledge than those that did not. It exhibited higher accuracy in diagnosis-based and recall-based questions than in intervention-based questions. A significant positive correlation was observed between the consistency and accuracy of GPT-4's responses. This study unveils both the potential and challenges of applying LLMs to TKM. These findings underline the potential of LLMs like GPT-4 in culturally adapted medicine, especially TKM, for tasks such as clinical assistance, medical education, and research. But they also point towards the necessity for the development of methods to mitigate cultural bias inherent in large language models and validate their efficacy in real-world clinical settings.

Compound-level identification of sasang constitution type-specific personalized herbal medicine using data science approach.

Introduction: Sasang Constitutional Medicine (SCM) is a type of traditional Korean medicine where patients are classified as one of four Sasang constitution types (Sasang type) and medications consisting of medicinal herbs are prescribed according to the Sasang type. Despite the importance of personalized medicine, the operation mechanism is largely unknown. To gain a better understanding, we investigated the compound information that composes Sasang type-specific personalized herbal medicines on both multivariate and univariate levels. Methods: Five machine learning classifiers including extremely randomized trees (ERT) were trained to investigate whether the Sasang type can be explained by compound information at the multivariate level. Hierarchical clustering was conducted to determine whether compounds are processed distributedly or specifically. Taxonomic and biosynthetic analyses were conducted on these compounds. A univariate level statistical test was conducted to provide more robust Sasang type-specific compound information. Results: Using the trained ERT classifier, sixty important compounds were extracted. The sixty compounds were clustered into three groups, corresponding to each Sasang type-prominent compounds, suggesting that most compounds have specific preference for the Sasang type. Structural and biosynthetic characteristics of these Sasang type-prominent compounds were determined based on taxonomy and pathway analyses. Fourteen compounds showed statistically significant relevance with the Sasang type. Additionally, we predicted the Sasang type of unknown herbs, which were confirmed by their biological effects in functional assays. Conclusion: This study investigated the personalized herbal medicines of the SCM using compound information. This study provided information on the chemical characteristics of the compounds that are essential for classifying the Sasang type of medicinal herbs, as well as predictions regarding the Sasang type of the commonly used but unidentified medicinal herbs.

Network Pharmacological Analysis on the Herbal Combinations for Mitigating Inflammation in Respiratory Tracts and Experimental Evaluation.

The regulation of inflammatory mediators, such as TNF-α, IL-6, IL-1ß, and leukotriene B4, could play a crucial role in suppressing inflammatory diseases such as COVID-19. In this study, we investigated the potential mechanisms of drug combinations comprising Ephedrae Herba, Schisandra Fructus, Platycodonis Radix, and Ginseng Radix; validated the anti-inflammatory effects of these drugs; and determined the optimal dose of the drug combinations. By constructing a herb-compound-target network, associations were identified between the herbs and tissues (such as bronchial epithelial cells and lung) and pathways (such as the TNF, NF-κB, and calcium signaling pathways). The drug combinations exerted anti-inflammatory effects in the RAW264.7 cell line treated with lipopolysaccharide by inhibiting the production of nitric oxide and inflammatory mediators, including TNF-α, IL-6, IL-1ß, and leukotriene B4. Notably, the drug combinations inhibited PMA-induced MUC5AC mRNA expression in NCI-H292 cells. A design space analysis was carried out to determine the optimal herbal medicine combinations using the design of experiments and synergy score calculation. Consequently, a combination study of the herbal preparations confirmed their mitigating effect on inflammation in COVID-19.

Individualized Diagnosis and Prescription in Traditional Medicine: Decision-Making Process Analysis and Machine Learning-Based Analysis Tool Development.

While pattern identification (PI) is an essential process in traditional medicine (TM), it is difficult to objectify since it relies heavily on implicit knowledge. Therefore, this study aimed to propose a machine learning (ML)-based analysis tool to evaluate the clinical decision-making process of PI in terms of explicit and implicit knowledge, and to observe the actual process by which this knowledge affects the choice of diagnosis and treatment in individual TM doctors. Clinical data for the development of the analysis tool were collected using a questionnaire administered to allergic rhinitis (AR) patients and the diagnosis and prescription results of TM doctors based on the completed AR questionnaires. Explicit knowledge and implicit knowledge were defined based on the doctors' explicit scoring and feature evaluations of ML models, respectively. There were many differences between the explicit and implicit importance scores in this study. Implicit importance is more closely related to explicit importance in prescription than in diagnosis. The analysis results for eight doctors showed that our tool could successfully identify explicit and implicit knowledge in the PI process. This is the first study to evaluate the actual process by which explicit and implicit knowledge affect the choice of individual TM doctors and to identify assessment tools for the definition of the decision-making process in diagnosing PI and prescribing herbal treatments by TM clinicians. The assessment tool suggested in this study could be broadly used for the standardization of precision medicine, including TM therapeutics.

Regulation of appetite-related neuropeptides by Panax ginseng: A novel approach for obesity treatment.

Obesity is a primary factor provoking various chronic disorders, including cardiovascular disease, diabetes, and cancer, and causes the death of 2.8 million individuals each year. Diet, physical activity, medications, and surgery are the main therapies for overweightness and obesity. During weight loss therapy, a decrease in energy stores activates appetite signaling pathways under the regulation of neuropeptides, including anorexigenic [corticotropin-releasing hormone, proopiomelanocortin (POMC), cholecystokinin (CCK), and cocaine- and amphetamine-regulated transcript] and orexigenic [agouti-related protein (AgRP), neuropeptide Y (NPY), and melanin-concentrating hormone] neuropeptides, which increase food intake and lead to failure in attaining weight loss goals. Ginseng and ginsenosides reverse these signaling pathways by suppressing orexigenic neuropeptides (NPY and AgRP) and provoking anorexigenic neuropeptides (CCK and POMC), which prevent the increase in food intake. Moreover, the results of network pharmacology analysis have revealed that constituents of ginseng radix, including campesterol, beta-elemene, ginsenoside Rb1, biotin, and pantothenic acid, are highly correlated with neuropeptide genes that regulate energy balance and food intake, including ADIPOQ, NAMPT, UBL5, NUCB2, LEP, CCK, GAST, IGF1, RLN1, PENK, PDYN, and POMC. Based on previous studies and network pharmacology analysis data, ginseng and its compounds may be a potent source for obesity treatment by regulating neuropeptides associated with appetite.

System-level investigation of anti-obesity effects and the potential pathways of Cordyceps militaris in ovariectomized rats.

BACKGROUND: Cordyceps species have been used as tonics to enhance energy, stamina, and libido in traditional Asian medicine for more than 1600 years, indicating their potential for improving reproductive hormone disorders and energy metabolic diseases. Among Cordyceps, Cordyceps militaris has been reported to prevent metabolic syndromes including obesity and benefit the reproductive hormone system, suggesting that Cordyceps militaris can also regulate obesity induced by the menopause. We investigated the effectiveness of Cordyceps militaris extraction (CME) on menopausal obesity and its mechanisms. METHODS: We applied an approach combining in vivo, in vitro, and in silico methods. Ovariectomized rats were administrated CME, and their body weight, area of adipocytes, liver and uterus weight, and lipid levels were measured. Next, after the exposure of MCF-7 human breast cancer cells to CME, cell proliferation and the phosphorylation of estrogen receptor and mitogen-activated protein kinases (MAPK) were measured. Finally, network pharmacological methods were applied to predict the anti-obesity mechanisms of CME. RESULTS: CME prevented overweight, fat accumulation, liver hypertrophy, and lowered triglyceride levels, some of which were improved in a dose-dependent manner. In MCF-7 cell lines, CME showed not only estrogen receptor agonistic activity through an increase in cell proliferation and the phosphorylation of estrogen receptors, but also phosphorylation of extracellular-signal-regulated kinase and p38. In the network pharmacological analysis, bioactive compounds of CME such as cordycepin, adenine, and guanosine were predicted to interact with non-overlapping genes. The targeted genes were related to the insulin signaling pathway, insulin resistance, the MARK signaling pathway, the PI3K-Akt signaling pathway, and the estrogen signaling pathway. CONCLUSIONS: These results suggest that CME has anti-obesity effects in menopause and estrogenic agonistic activity. Compounds in CME have the potential to regulate obesity-related and menopause-related pathways. This study will contribute to developing the understanding of anti-obesity effects and mechanisms of Cordyceps militaris.

A System-Level Mechanism of Anmyungambi Decoction for Obesity: A Network Pharmacological Approach.

Obesity is a low-grade systemic inflammatory disease involving adipocytokines. As though Anmyungambi decoction (AMGB) showed significant improvement on obesity in a clinical trial, the molecular mechanism of AMGB in obesity remains unknown. Therefore, we explored the potential mechanisms of action of AMGB on obesity through network pharmacological approaches. We revealed that targets of AMGB are significantly associated with obesity-related and adipocyte-elevated genes. Evodiamine, berberine, genipin, palmitic acid, genistein, and quercetin were shown to regulate adipocytokine signaling pathway proteins which mainly involved tumor necrosis factor receptor 1, leptin receptor. In terms of the regulatory pathway of lipolysis in adipocytes, norephedrine, pseudoephedrine, quercetin, and limonin were shown to affect adrenergic receptor-beta, protein kinase A, etc. We also found that AMGB has the potentials to enhance the insulin signaling pathway thereby preventing type II diabetes mellitus. Additionally, AMGB was discovered to be able to control not only insulin-related proteins but also inflammatory mediators and apoptotic regulators and caspases, hence reducing hepatocyte injury in nonalcoholic fatty liver disease. Our findings help develop a better understanding of how AMGB controls obesity.

Hair Growth Stimulation Effect of Centipeda minima Extract: Identification of Active Compounds and Anagen-Activating Signaling Pathways.

Centipeda minima (L.) A. Braun & Asch is a well-studied plant in Chinese medicine that is used for the treatment of several diseases. A recent study has revealed the effects of extract of Cetipeda minima (CMX) standardized by brevilin A in inducing hair growth. However, the mechanism of action of CMX in human hair follicle dermal papilla cells (HFDPCs) has not yet been identified. We aimed to investigate the molecular basis underlying the effect of CMX on hair growth in HFDPCs. CMX induced the proliferation of HFDPCs, and the transcript-level expression of Wnt family member 5a (Wnt5a), frizzled receptor (FZDR), and vascular endothelial growth factor (VEGF) was upregulated. These results correlated with an increase in the expression of growth-related factors, such as VEGF and IGF-1. Immunoblotting and immunocytochemistry further revealed that the phosphorylation of ERK and JNK was enhanced by CMX in HFDPCs, and ß-catenin accumulated significantly in a dose-dependent manner. Therefore, CMX substantially induced the expression of Wnt signaling-related proteins, such as GSK phosphorylation and ß-catenin. This study supports the hypothesis that CMX promotes hair growth and secretion of growth factors via the Wnt/ß-catenin, ERK, and JNK signaling pathways. In addition, computational predictions of drug-likeness, together with ADME property predictions, revealed the satisfactory bioavailability score of CMX compounds, exhibiting high gastrointestinal absorption. We suggest that CMX could be used as a promising treatment for hair regeneration and minimization of hair loss.

Diversity of Acupuncture Point Selections According to the Acupuncture Styles and Their Relations to Theoretical Elements in Traditional Asian Medicine: A Data-Mining-Based Literature Study.

Acupuncture point (AP) selections can vary depending on clinicians' acupuncture style, and therefore, acupuncture style is an important factor in determining the efficacy of acupuncture treatment. However, few studies have examined the differences in AP selections according to the acupuncture styles and theoretical backgrounds causing the differences. We compared the AP prescriptions used for 14 diseases in three classical medical textbooks, Dongeuibogam (DEBG), Saamdoinchimgooyogyeol (SADI), and Chimgoogyeongheombang (CGGHB), which represent unique acupuncture styles and have affected clinicians during this time. AP prescriptions showed more diversity between textbooks than between types of diseases. Among the three textbooks, AP prescriptions of SADI were most different compared to those of DEBG and CGGHB. Importantly, we found each style can be more clearly explained by AP attributes than by the APs per se. Specifically, SADI, DEBG, and CGGHB preferred five transport points located on the limbs, APs of the extra meridians, and source points, respectively. This suggests the possibility that the theoretical diversity of acupuncture styles results in the heterogeneity of AP selections.

Investigating the Biomarkers of the Sasang Constitution via Network Pharmacology Approach.

Sasang constitutional (SC) medicine classifies people into Soeum (SE), Soyang (SY), Taeeum (TE), and Taeyang (TY) types based on psychological and physical traits. However, biomarkers of these types are still unclear. We aimed to identify biomarkers among the SC types using network pharmacology methods. Target genes associated with the SC types were identified by grouping herb targets that preserve and strengthen the requisite energy (Bomyeongjiju). The herb targets were obtained by constructing an herb-compound-target network. We identified 371, 185, 146, and 89 target genes and their unique biological processes related to SE, SY, TE, and TY types, respectively. While the targets of SE and SY types were the most similar among the target pairs of the SC types, those of TY type overlapped with only a few other SC-type targets. Moreover, SE, SY, TE, and TY were related to "diseases of the digestive system," "diseases of the nervous system," "endocrine, nutritional, and metabolic diseases," and "congenital malformations, deformations, and chromosomal abnormalities," respectively. We successfully identified the target genes, biological processes, and diseases related to each SC type. We also demonstrated that a drug-centric approach using network pharmacology analysis provides a deeper understanding of the concept of Sasang constitutional medicine at a phenotypic level.

Effects of estrogen inhibition formula herbal mixture for danazol-induced precocious puberty in female rats: an experimental study with network pharmacology.

BACKGROUND: This study aimed at determining the effect of the herbal mixture estrogen inhibition formula (EIF) and its possible mechanisms by precocious puberty animal models and network pharmacology-based analysis. METHODS: Precocious puberty animal models were established by a single injection of 300 µg danazol, then female rats were administered EIF, vaginal openings were monitored, uterus and pituitary indices were determined. The levels of ALP, E2, LH, and FSH were measured using ELISA kits. Real-time PCR was performed to evaluate the mRNA expression of GnRH, UNC5C, and netrin-1 in hypothalamic tissues. We applied network pharmacological analysis to predict potential targets and pathways of EIF. RESULTS: EIF delayed danazol-induced early vaginal opening. In the onset model, EIF reduced the increased levels of serum ALP, E2, LH, and FSH; as well as mRNA expressions of GnRH, Netrin-1, and UNC5C. Moreover, long-term administration of EIF not only diminished all impaired factors but also had no effect on the normal development of the animals. The gene set enrichment analysis showed that the targets of EIF are mainly associated with the GnRH signaling and ovarian steroidogenesis pathways. CONCLUSION: EIF could be used in preclinical research for the treatment of precocious puberty by the inhibition of HPGA pre-maturation.

A Novel Framework for Understanding the Pattern Identification of Traditional Asian Medicine From the Machine Learning Perspective.

Pattern identification (PI), a unique diagnostic system of traditional Asian medicine, is the process of inferring the pathological nature or location of lesions based on observed symptoms. Despite its critical role in theory and practice, the information processing principles underlying PI systems are generally unclear. We present a novel framework for comprehending the PI system from a machine learning perspective. After a brief introduction to the dimensionality of the data, we propose that the PI system can be modeled as a dimensionality reduction process and discuss analytical issues that can be addressed using our framework. Our framework promotes a new approach in understanding the underlying mechanisms of the PI process with strong mathematical tools, thereby enriching the explanatory theories of traditional Asian medicine.

Effect of Herbal Formulation on Immune Response Enhancement in RAW 264.7 Macrophages.

Immune response is a necessary self-defense mechanism that protects the host from infectious organisms. Many medicinal plants are popularly used in Asian folk medicine to increase body resistance. An herbal formulation named KM1608 was prepared from three medicinal plants: Saussurea lappa, Terminalia chebula, and Zingiber officinale. In this study, we evaluated the immune stimulatory effect of KM1608 on RAW 264.7 murine macrophages. Network pharmacological analyses were used to predict potential immune response pathways of major compounds from KM1608. The cytotoxicity and immuno-stimulating effect of KM1608 were determined using cell viability and nitric oxide assays. The underlying mechanism of immunomodulatory activity was evaluated by quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) of pro-inflammatory cytokines. The results of network pharmacological analysis suggested that major compounds from KM1608 possess anticancer potential via immune signaling pathways. After treatment with KM1608 at 25-100 µg/mL for 24 h, the level of nitric oxide was increased in the dose-dependent manner. The results of quantitative real-time PCR showed that KM1608 stimulates the expression of immune cytokines (interferon (IFN)-α, -ß, IL-1ß, -6, IL-10, inducible nitric oxide synthase (iNOS), and cyclooxygenase-2 (COX-2)) in macrophages. KM1608 extract is a potential agent for immune response enhancement.

Investigating the Systems-Level Effect of Pueraria lobata for Menopause-Related Metabolic Diseases Using an Ovariectomized Rat Model and Network Pharmacological Analysis.

This study was conducted to evaluate the biological activities of Pueraria lobata (PL) on menopause-related metabolic diseases and to explore the underlying mechanism of PL by network pharmacological analyses. We used ovariectomized (OVX) rats as a postmenopausal model and administered PL at different doses (50, 100, and 200 mg/kg). In OVX rats, decreased uterine weights and PPAR-γ (peroxisome proliferator-activated receptor-gamma) mRNA expression in the thigh muscle were significantly recovered after PL administration. PL also significantly alleviated OVX-induced increases in total cholesterol, triglyceride, alanine aminotransferase (ALT/GPT), and aspartate aminotransferase (AST/GOT) levels. To identify the systems-level mechanism of PL, we performed network pharmacological analyses by predicting the targets of the potential bioactive compounds and their associated pathways. We identified 61 targets from four potential active compounds of PL: formononetin, beta-sitosterol, 3'-methoxydaidzein, and daidzein-4,7-diglucoside. Pathway enrichment analysis revealed that among female sex hormone-related pathways, the estrogen signaling pathways, progesterone-mediated oocyte maturation, oxytocin signaling pathways, and prolactin signaling pathways were associated with multiple targets of PL. In conclusion, we found that PL improved various indicators associated with lipid metabolism in the postmenopausal animal model, and we also identified that its therapeutic effects are exerted via multiple female sex hormone-related pathways.

The Methodological Trends of Traditional Herbal Medicine Employing Network Pharmacology.

Natural products, including traditional herbal medicine (THM), are known to exert their therapeutic effects by acting on multiple targets, so researchers have employed network pharmacology methods to decipher the potential mechanisms of THM. To conduct THM-network pharmacology (THM-NP) studies, researchers have employed different tools and databases for constructing and analyzing herb-compound-target networks. In this study, we attempted to capture the methodological trends in THM-NP research. We identified the tools and databases employed to conduct THM-NP studies and visualized their combinatorial patterns. We also constructed co-author and affiliation networks to further understand how the methodologies are employed among researchers. The results showed that the number of THM-NP studies and employed databases/tools have been dramatically increased in the last decade, and there are characteristic patterns in combining methods of each analysis step in THM-NP studies. Overall, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was the most frequently employed network pharmacology database in THM-NP studies. Among the processes involved in THM-NP research, the methodology for constructing a compound-target network has shown the greatest change over time. In summary, our analysis describes comprehensive methodological trends and current ideas in research design for network pharmacology researchers.

Characterization of hidden rules linking symptoms and selection of acupoint using an artificial neural network model.

Comprehension of the medical diagnoses of doctors and treatment of diseases is important to understand the underlying principle in selecting appropriate acupoints. The pattern recognition process that pertains to symptoms and diseases and informs acupuncture treatment in a clinical setting was explored. A total of 232 clinical records were collected using a Charting Language program. The relationship between symptom information and selected acupoints was trained using an artificial neural network (ANN). A total of 11 hidden nodes with the highest average precision score were selected through a tenfold cross-validation. Our ANN model could predict the selected acupoints based on symptom and disease information with an average precision score of 0.865 (precision, 0.911; recall, 0.811). This model is a useful tool for diagnostic classification or pattern recognition and for the prediction and modeling of acupuncture treatment based on clinical data obtained in a real-world setting. The relationship between symptoms and selected acupoints could be systematically characterized through knowledge discovery processes, such as pattern identification.

A Systems-Level Analysis of Mechanisms of Platycodon grandiflorum Based on A Network Pharmacological Approach.

Platycodon grandiflorum (PG) is widely used in Asia for its various beneficial effects. Although many studies were conducted to understand the molecular mechanisms of PG, it is still unclear how the combinations of multiple ingredients work together to exert its therapeutic effects. The aim of the present study was to provide a comprehensive review of the systems-level mechanisms of PG by adopting network pharmacological analysis. We constructed a compound⁻target⁻disease network for PG using experimentally validated and machine-leaning-based prediction results. Each target of the network was analyzed based on previously known pharmacological activities of PG. Gene ontology analysis revealed that the majority of targets were related to cellular and metabolic processes, responses to stimuli, and biological regulation. In pathway enrichment analyses of targets, the terms related to cancer showed the most significant enrichment and formed distinct clusters. Degree matrix analysis for target⁻disease associations of PG suggested the therapeutic potential of PG in various cancers including hepatocellular carcinoma, gastric cancer, prostate cancer, small-cell lung cancer, and renal cell carcinoma. We expect that network pharmacological approaches will provide an understanding of the systems-level mechanisms of medicinal herbs and further develop their therapeutic potentials.

Beneficial effects of Panax ginseng for the treatment and prevention of neurodegenerative diseases: past findings and future directions.

In recent years, several therapeutic drugs have been rationally designed and synthesized based on the novel knowledge gained from investigating the actions of biologically active chemicals derived from foods, plants, and medicinal herbs. One of the major advantages of these naturalistic chemicals is their ability to interact with multiple targets in the body resulting in a combined beneficial effect. Ginseng is a perennial herb (Araliaceae family), a species within the genus Panax, and a highly valued and popular medicinal plant. Evidence for the medicinal and health benefits of Panax ginseng and its components in preventing neurodegeneration has increased significantly in the past decade. The beneficial effects of P. ginseng on neurodegenerative diseases have been attributed primarily to the antioxidative and immunomodulatory activities of its ginsenoside components. Mechanistic studies on the neuroprotective effects of ginsenosides revealed that they act not only as antioxidants but also as modulators of intracellular neuronal signaling and metabolism, cell survival/death genes, and mitochondrial function. The goal of the present paper is to provide a brief review of recent knowledge and developments concerning the beneficial effects as well as the mechanism of action of P. ginseng and its components in the treatment and prevention of neurodegenerative diseases.

Protective Effect of Artemisia argyi and Its Flavonoid Constituents against Contrast-Induced Cytotoxicity by Iodixanol in LLC-PK1 Cells.

Preventive effects and corresponding molecular mechanisms of mugwort (Artemisia argyi) extract and its flavonoid constituents on contrast-induced nephrotoxicity were explored in the present study. We treated cultured LLC-PK1 cells with iodixanol to induce contrast-induced nephrotoxicity, and found that A. argyi extracts ameliorated the reduction in cellular viability following iodixanol treatment. The anti-apoptotic effect of A. argyi extracts on contrast-induced nephrotoxicity was mediated by the inhibition of mitogen-activated protein kinase (MAPK) phosphorylation and the activation of caspases. The flavonoid compounds isolated from A. argyi improved the viability of iodixanol-treated cells against contrast-induced nephrotoxicity. Seven compounds (1, 2, 3, 15, 16, 18, and 19) from 19 flavonoids exerted a significant protective effect. Based on the in silico oral-bioavailability and drug-likeness assessment, which evaluate the drug potential of these compounds, compound 2 (artemetin) showed the highest oral bioavailability (49.55%) and drug-likeness (0.48) values. We further investigated the compound⁻target⁻disease network of compound 2, and proliferator-activated receptor gamma (PPAR-γ) emerged as a predicted key marker for the treatment of contrast-induced nephrotoxicity. Consequently, compound 2 was the preferred candidate, and its protective effect was mediated by inhibiting the contrast-induced inflammatory response through activation of PPAR-γ and inhibition of MAPK phosphorylation and activation of caspases.

Oxyresveratrol ameliorates nonalcoholic fatty liver disease by regulating hepatic lipogenesis and fatty acid oxidation through liver kinase B1 and AMP-activated protein kinase.

Oxyresveratrol (OXY) is a naturally occurring polyhydroxylated stilbene that is abundant in mulberry wood (Morus alba L.), which has frequently been supplied as a herbal medicine. It has been shown that OXY has regulatory effects on inflammation and oxidative stress, and may have potential in preventing or curing nonalcoholic fatty liver disease (NAFLD). This study examined the effects of OXY on in vitro model of NAFLD in hepatocyte by the liver X receptor α (LXRα)-mediated induction of lipogenic genes and in vivo model in mice along with its molecular mechanism. OXY inhibited the LXRα agonists-mediated sterol regulatory element binding protein-1c (SREBP-1c) induction and expression of the lipogenic genes and upregulated the mRNA of fatty acid ß-oxidation-related genes in hepatocytes, which is more potent than genistein and daidzein. OXY also induced AMP-activated protein kinase (AMPK) activation in a time-dependent manner. Moreover, AMPK activation by the OXY treatment helped inhibit SREBP-1c using compound C as an AMPK antagonist. Oral administration of OXY decreased the Oil Red O stained-positive areas significantly, indicating lipid droplets and hepatic steatosis regions, as well as the serum parameters, such as fasting glucose, total cholesterol, and low density lipoprotein-cholesterol in high fat diet fed-mice, as similar with orally treatment of atorvastatin. Overall, this result suggests that OXY has the potency to inhibit hepatic lipogenesis through the AMPK/SREBP-1c pathway and can be used in the development of pharmaceuticals to prevent a fatty liver.