Exploring the anti-hepatocellular carcinoma effects of Xianglian Pill: Integrating network pharmacology and RNA sequencing via in silico and in vitro studies.

BACKGROUND: Liver cancer represents a most common and fatal cancer worldwide. Xianglian Pill (XLP) is an herbal formula holding great promise in clearing heat for treating diseases in an integrative and holistic way. However, due to the complex constituents and multiple targets, the exact molecular mechanisms of action of XLP are still unclear. PURPOSE: This study is focused on hepatocellular carcinoma (HCC), the most common type of liver cancer. The aim of this study is to develop a fast and efficient model to investigate the anti-HCC effects of XLP, and its underlying mechanisms. MATERIALS AND METHODS: HepG2, Hep3B, Mahlavu, HuH-7, or Li-7 cells were employed in the studies. The ingredients were analyzed using liquid chromatography tandem mass spectrometry (LC-MS). RNA sequencing combined with network pharmacology was used to elucidate the therapeutic mechanism of XLP in HCC via in silico and in vitro studies. An approach was constructed to improve the accuracy of prediction in network pharmacology by combining big data and omics. RESULTS: First, we identified 13 potential ingredients in the serum of XLP-administered rats using LC-MS. Then the network pharmacology was performed to predict that XLP demonstrates anti-HCC effects via targeting 94 genes involving in 13 components. Modifying the database thresholds might impact the accuracy of network pharmacology analysis based on RNA sequencing data. For instance, when the matching rate peak is 0.43, the correctness rate peak is 0.85. Moreover, 9 components of XLP and 6 relevant genes have been verified with CCK-8 and RT-qPCR assay, respectively. CONCLUSION: Based on the crossing studies of RNA sequencing and network pharmacology, XLP was found to improve HCC through multiple targets and pathways. Additionally, the study provides a way to optimize network pharmacology analysis in herbal medicine research.

[Overview of the application of knowledge graphs in the medical field].

With the booming development of medical information technology and computer science, the medical services industry is gradually transiting from information technology to intelligence. The medical knowledge graph plays an important role in intelligent medical applications such as knowledge questions and answers and intelligent diagnosis, and is a key technology for promoting wise medical care and the basis for intelligent management of medical information. In order to fully exploit the great potential of knowledge graphs in the medical field, this paper focuses on five aspects: inter-drug relationship discovery, assisted diagnosis, personalized recommendation, decision support and intelligent prediction. The latest research progress on medical knowledge graphs is introduced, and relevant suggestions are made in light of the current challenges and problems faced by medical knowledge graphs to provide reference for promoting the wide application of medical knowledge graphs.

Discovery and Validation of Traditional Chinese and Western Medicine Combination Antirheumatoid Arthritis Drugs Based on Machine Learning (Random Forest Model).

The combination of traditional Chinese medicine (TCM) and Western medicine is a promising method for treating rheumatoid arthritis (RA). Combining the two fully exploits the advantages of Western and TCM to treat RA and has the potential to greatly improve the therapeutic effect on RA. In this study, we developed a combination drug training set by using 16 characteristic variables based on the characteristics of small molecules of TCM ingredients and Food and Drug Administration-certified combination drug data downloaded from the DrugCombDB database. Furthermore, we compared the prediction and classification abilities of five models: the k-nearest neighbors, naive Bayes, support vector machine, random forest, and AdaBoost algorithms. The random forest model was selected as the classification and prediction model for Western and TCM and Western combination drugs. We collected data for 41 small molecules of TCM ingredients from the Traditional Chinese Medicine Systems Pharmacology database and 10 small molecule drugs commonly used in anti-RA treatment from the DrugBank database. Combinations of Western and TCM for anti-RA treatment were screened. Finally, the CellTiter-Glo method was used to determine the synergy of these combinations, and the 15 most predicted drug combinations were carried out experimental verification. Myricetin, rhein, nobiletin, and fisetin had high synergy with celecoxib, and rhein had high synergy with hydroxychloroquine. The preliminary findings of this study can be further applied for practical clinical anti-RA combined treatment strategies and serve as a reference for clinical treatment of RA with integrated Western and TCM.

Efficacy of Lianhua Qingwen for children with SARS-CoV-2 Omicron infection: A propensity score-matched retrospective cohort study.

BACKGROUND: Lianhua Qingwen Granules or Capsules (LHQW) has accumulated much research evidence in the fight against the coronavirus disease 2019 (COVID-19) epidemic. However, there are still few data on its efficacy and safety in children with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. PURPOSE: To evaluate the efficacy and safety of LHQW in children with SARS-CoV-2 Omicron infection. METHODS: We conducted a single-center, propensity-score matched retrospective cohort study of children with SARS-CoV-2 Omicron infection in Shanghai New International Expo Center mobile cabin hospital between April 1st and June 1st, 2022. Eligible patients received either LHQW granules/capsules plus supportive care (LHQW group) or supportive care alone (control group). The primary outcome was the negative conversion time of nucleic acid. Secondary outcomes included the negative conversion rate of nucleic acid, the length of hospital stay, clinical disease progression, and cycle threshold [Ct] values for SARS-CoV-2 open reading frame [ORF1ab] or nucleocapsid [N] genes. RESULTS: Overall, 2808 patients were enrolled, and 346 patients in each group were included in the analysis. Among the propensity-score matched groups, LHQW treatment was associated with an accelerated negative conversion time of nucleic acid (median: 5 d vs. 6 d, Hazard ratio: 1.25, 95% CI: 1.08 - 1.46, Log-rank p < 0.001), a higher negative conversion rate of nucleic acid (Day 2 - 6: 2.9% vs. 0.6%, p = 0.036; 29.8% vs. 5.5%, p < 0.001; 42.5% vs. 24.3%, p < 0.001; 51.4% vs. 31.5%, p < 0.001; 63.3% vs. 55.2%, p = 0.030), shorter hospital stay (median: 10 d vs. 11 d, Hazard ratio: 1.50, 95% CI: 1.29 - 1.74, Log-rank p < 0.001), and lower rates of asymptomatic infection progressing to mild (37.9% vs. 46.5%, p = 0.021). CONCLUSION: Our study suggested that LHQW treatment was associated with faster clinical recovery in children with SARS-CoV-2 Omicron infection.

A review of research on eligibility criteria for clinical trials.

The purpose of this paper is to systematically sort out and analyze the cutting-edge research on the eligibility criteria of clinical trials. Eligibility criteria are important prerequisites for the success of clinical trials. It directly affects the final results of the clinical trials. Inappropriate eligibility criteria will lead to insufficient recruitment, which is an important reason for the eventual failure of many clinical trials. We have investigated the research status of eligibility criteria for clinical trials on academic platforms such as arXiv and NIH. We have classified and sorted out all the papers we found, so that readers can understand the frontier research in this field. Eligibility criteria are the most important part of a clinical trial study. The ultimate goal of research in this field is to formulate more scientific and reasonable eligibility criteria and speed up the clinical trial process. The global research on the eligibility criteria of clinical trials is mainly divided into four main aspects: natural language processing, patient pre-screening, standard evaluation, and clinical trial query. Compared with the past, people are now using new technologies to study eligibility criteria from a new perspective (big data). In the research process, complex disease concepts, how to choose a suitable dataset, how to prove the validity and scientific of the research results, are challenges faced by researchers (especially for computer-related researchers). Future research will focus on the selection and improvement of artificial intelligence algorithms related to clinical trials and related practical applications such as databases, knowledge graphs, and dictionaries.

Characteristic analysis of clinical trials for new traditional Chinese medicines in mainland China from 2013 to 2021.

Objective: Based on the clinical trials registered on the platform for the registry and publicity of clinical drug trials of the National Medical Products Administration (NMPA), the registration and approval of clinical trials of traditional Chinese medicines (TCMs) in mainland China from 2013 to 2021 were reviewed. Methods: Clinical trials of new TCMs published in Chinese were retrieved from the platform for the registry and publicity of clinical drug trials. The number of registered trials and approved trials, status of clinical trials, therapeutic area of clinical trials for the treatment of diseases, type of trial design, sample size, sponsors, and leading clinical trial centers were evaluated. Results: From 2013 to 2021, a total of 965 clinical trials of new drugs applied in TCM were registered on the aforementioned NMPA platform, comprising 117 phase I trials, 586 phase II trials, 174 phase III trials, 40 phase IV trials, and 48 other clinical trials. The treatment fields included the respiratory system, alimentary tract and metabolism, genetic system and reproductive hormones, and cardiovascular system. Among the 760 phase II and phase III trials, 98.9% were randomized, 95.4% were double-blind, and 98.2% were parallel controlled trials, and the proportion of placebo-controlled trials increased year by year from 2013 to 2021. From 2013 to 2021, 123 new TCMs were approved in mainland China. Conclusion: From 2015 to 2021, the number of registered clinical trials of new TCMs remained low. The approval rate was also low, but the clinical trial design was greatly improved.

Naoxintong Capsule for Secondary Prevention of Ischemic Stroke: A Multicenter, Randomized, and Placebo-Controlled Trial.

OBJECTIVE: To examine whether the combination of Naoxintong Capsule with standard care could further reduce the recurrence of ischemic stroke without increasing the risk of severe bleeding. METHODS: A total of 23 Chinese medical centers participated in this trial. Adult patients with a history of ischemic stroke were randomly assigned in a 1:1 ratio using a block design to receive either Naoxintong Capsule (1.2 g orally, twice a day) or placebo in addition to standard care. The primary endpoint was recurrence of ischemic stroke within 2 years. Secondary outcomes included myocardial infarction, death due to recurrent ischemic stroke, and all-cause mortality. The safety of drugs was monitored. Results were analyzed using the intention-to-treat principle. RESULTS: A total of 2,200 patients were enrolled from March 2015 to March 2016, of whom 143 and 158 in the Naoxintong and placebo groups were lost to follow-up, respectively. Compared with the placebo group, the recurrence rate of ischemic stroke within 2 years was significantly lower in the Naoxintong group [6.5% vs. 9.5%, hazard ratio (HR): 0.665, 95% confidence interval (CI): 0.492-0.899, P=0.008]. The two groups showed no significant differences in the secondary outcomes and safety, including rates of severe hemorrhage, cerebral hemorrhage and subarachnoid hemorrhage (P>0.05). CONCLUSION: The combination of Naoxintong Capsule with standard care reduced the 2-year stroke recurrence rate in patients with ischemic stroke without increasing the risk of severe hemorrhage in high-risk patients. (Trial registration No. NCT02334969).

Whether Immunostimulants Are Effective in Susceptible Children Suffering From Recurrent Respiratory Tract Infections: A Modeling Analysis Based on Literature Aggregate Data.

Immunostimulants are gradually being used in the prevention and treatment of recurrent respiratory tract infections in susceptible children, but their drug effects have not been quantified. The purpose of this study was to confirm the efficacy of immunostimulants in the prevention and treatment of recurrent respiratory tract infections in susceptible children. A model-based meta-analysis was used to describe the time course of placebo and immunostimulants in the prevention of respiratory tract infections in children. The cumulative number of respiratory tract infections was used as an indicator of efficacy. A meta-analysis was used to analyze the incidence of drug-related adverse events. Fourteen articles with 2400 pediatric subjects were finally included in the analysis. The results showed that the cumulative number of respiratory tract infections increased linearly with time, with the incidence of respiratory tract infections in the placebo group being 0.65 (95% confidence interval [CI], 0.55-0.75) per month. OM-85 BV and pidotimod reduced the incidence of respiratory tract infections by 0.21 (95%CI, 0.16-0.26) and 0.19 (95%CI, 0.17-0.21) compared to placebo per month, respectively. Pidotimod and OM-85 BV can effectively reduce the incidence of respiratory tract infections in susceptible children, with no significant increase in the incidence of drug-related adverse events when compared with placebo (risk ratio values were 1.07 [95%CI, 0.66-1.71] and 1.31 [95%CI, 0.54-3.19], respectively). This study provides quantitative support for the application of immunostimulants for the prevention of recurrent respiratory tract infections in children.

Network Pharmacology-Based Analysis and Experimental Exploration of Antidiabetic Mechanisms of Gegen Qinlian Decoction.

Type-2 diabetes mellitus (T2DM) and therapy options have been studied increasingly due to their rising incidence and prevalence. The trend of applying traditional Chinese medicine (TCM) to treat T2DM is increasing as a crucial medical care for metabolic dysfunctions. Gegen Qinlian decoction (GQL), a well-known classical TCM formula used in China, has been clinically applied to treat various types of chronic metabolic diseases. However, antidiabetic effects of GQL administration during T2DM have never been studied systematically. We assessed physiological and molecular targets associated with therapeutic effects of GQL by evaluating network topological characteristics. The GQL-related biological pathways are closely associated with antidiabetic effects, including the TNF and PI3K-AKT signaling pathways. Associated primary biological processes such as RNA polymerase II promoter transcription participate in the inflammatory response, oxidative stress reduction, and glucose metabolic process, thereby exerting multiple biological effects on the antidiabetic mechanism. Furthermore, our results showed that GQL can affect blood glycemic levels and ameliorate inflammatory symptoms, and liver and pancreas tissue injury in high-fat diet plus streptozotocin-induced diabetic mice. In vivo and in vitro experiments confirmed that antidiabetic effects of GQL were associated with a modulation of the TNF and PI3K-AKT-MTOR pathways.

Interpreting the Molecular Mechanisms of Yinchenhao Decoction on Hepatocellular Carcinoma through Absorbed Components Based on Network Pharmacology.

To investigate the mechanisms through which Yinchenhao decoction (YCHD) inhibits hepatocellular carcinoma (HCC), we analyzed YCHD ingredients absorbed into the bloodstream by using network pharmacology. We conducted a weighted gene coexpression network analysis on gene expression data collected from the Gene Expression Omnibus and The Cancer Genome Atlas databases to derive an HCC gene set; moreover, we used four online prediction system databases to predict the potential targets of YCHD ingredients absorbed into the bloodstream. We discovered that YCHD directly interfered with 17 HCC-related disease targets. Subsequent gene ontology enrichment analyses of these 17 disease targets revealed that YCHD exhibited effects through 17 biological processes, 7 molecular functions, and 9 cellular components. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated 14 pathways through which YCHD inhibits HCC. We observed similar trends in how the 17 small molecules interfered with the key target set. We surmised that YCHD inhibits HCC by regulating inflammatory and metabolic pathways. Network pharmacological analysis of YCHD ingredients absorbed into the bloodstream may provide new insights and serve as a new method for discovering the molecular mechanisms through which YCHD inhibits HCC.

The impacts of race and regimens on the efficacy and safety of paclitaxel and platinum combination treatment for patients with advanced non-small cell lung cancer.

PURPOSE: Paclitaxel-platinum chemotherapy is the first-line treatment for advanced non-small cell lung cancer (NSCLC) patients. This study quantitatively evaluated the factors influencing the efficacy and safety of the paclitaxel-platinum regimen to provide the necessary reference for the development of clinical practice and clinical trials. METHODS: A literature search was performed using public databases. The parametric survival function was used to analyze the overall survival (OS) time course of patients treated with the paclitaxel-platinum regimen. The random effects model in the single-arm meta-analysis was used to analyze the objective response rate (ORR) and the incidence of grade 3-4 adverse events (AEs) under the predefined subgroups according to race and the regimen. RESULTS: A total of 31 studies consisting of 3365 participants were included in the analysis. Race was the most important determinant of efficacy and safety in the paclitaxel-platinum regimen, with the median survival time and ORR in East Asians and non-East Asians being 12.2 months (95% CI: 10.5-14.4 months) and 37% (95% CI: 32-41%) and 8.4 months (95% CI: 6.5-11.0 months) and 28% (95% CI: 25-32%), respectively. The incidence of grade 3-4 AEs such as leukopenia and neutropenia was about three times higher in East Asians compared to non-East Asians. CONCLUSIONS: The efficacy and safety of the paclitaxel-platinum regimen can vary between East Asian and non-East Asian populations and between different treatment schedules. The results of this study can provide a reliable and precise external control for the future evaluation of new treatment options for advanced NSCLC.

Association between physical activity and digestive-system cancer: An updated systematic review and meta-analysis.

BACKGROUND: Physical activity (PA) may have an impact on digestive-system cancer (DSC) by improving insulin sensitivity and anticancer immune function and by reducing the exposure of the digestive tract to carcinogens by stimulating gastrointestinal motility, thus reducing transit time. The current study aimed to determine the effect of PA on different types of DSC via a systematic review and meta-analysis. METHODS: In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched for relevant studies in PubMed, Embase, Web of Science, Cochrane Library, and China National Knowledge Infrastructure. Using a random effects model, the relationship between PA and different types of DSC was analyzed. RESULTS: The data used for meta-analysis were derived from 161 risk estimates in 47 studies involving 5,797,768 participants and 55,162 cases. We assessed the pooled associations between high vs. low PA levels and the risk of DSC (risk ratio (RR)  = 0.82, 95% confidence interval (95%CI): 0.79-0.85), colon cancer (RR = 0.81, 95%CI: 0.76-0.87), rectal cancer (RR = 0.88, 95%CI: 0.80-0.98), colorectal cancer (RR = 0.77, 95%CI: 0.69-0.85), gallbladder cancer (RR = 0.79, 95%CI: 0.64-0.98), gastric cancer (RR = 0.83, 95%CI: 0.76-0.91), liver cancer (RR = 0.73, 0.60-0.89), oropharyngeal cancer (RR = 0.79, 95%CI: 0.72-0.87), and pancreatic cancer (RR = 0.85, 95%CI: 0.78-0.93). The findings were comparable between case-control studies (RR = 0.73, 95%CI: 0.68-0.78) and prospective cohort studies (RR = 0.88, 95%CI: 0.80-0.91). The meta-analysis of 9 studies reporting low, moderate, and high PA levels, with 17 risk estimates, showed that compared to low PA, moderate PA may also reduce the risk of DSC (RR = 0.89, 95%CI: 0.80-1.00), while compared to moderate PA, high PA seemed to slightly increase the risk of DSC, although the results were not statistically significant (RR = 1.11, 95%CI: 0.94-1.32). In addition, limited evidence from 5 studies suggested that meeting the international PA guidelines might not significantly reduce the risk of DSC (RR = 0.96, 95%CI: 0.91-1.02). CONCLUSION: Compared to previous research, this systematic review has provided more comprehensive information about the inverse relationship between PA and DSC risk. The updated evidence from the current meta-analysis indicates that a moderate-to-high PA level is a common protective factor that can significantly lower the overall risk of DSC. However, the reduction rate for specific cancers may vary. In addition, limited evidence suggests that meeting the international PA guidelines might not significantly reduce the risk of DSC. Thus, future studies must be conducted to determine the optimal dosage, frequency, intensity, and duration of PA required to reduce DSC risk effectively.

Study Design Characteristics and Pharmacological Mechanisms in International Clinical Trials Registry Platform: Registered Clinical Trials on Antiviral Drugs for COVID-19.

OBJECTIVE: This study aimed to evaluate the pharmacological mechanisms of antiviral drugs against the novel coronavirus disease (COVID-19) and the study designs in clinical trials registered with the International Clinical Trials Registry Platform (ICTRP). METHODS: Clinical trials involving antiviral drugs for treating COVID-19 were retrieved from the ICTRP database. For each trial, the study design, number of participants, primary endpoints, source register, antiviral mechanism, and results were evaluated. RESULTS: On June 10, 2020, 145 eligible clinical trials were retrieved from the ICTRP, of which 99 (68.3%) were randomized trials, 109 (75.2%) were parallel assignment trials, 38 (26.2%) were double or single blinded, 130 (89.7%) involved two groups, and 75 (51.6%) included more than 100 participants; and clinical improvement or recovery and virus-negative conversion were the two most common endpoints, accounting for 40.7% and 18.6%, respectively. The drugs were divided according to the antiviral mechanism into HIV reverse transcriptase inhibitors, RNA-dependent RNA polymerase inhibitors, HIV protease inhibitors (PIs), hepatitis C virus NS3 PIs, and anti-influenza drugs. CONCLUSION: The design characteristics of clinical trials of antiviral drugs for treating COVID-19 as well as the mechanism of action and antiviral efficacy of the drugs were evaluated in this study. The results of these trials could constitute a reference for future clinical trials to be executed on COVID-19 treatment and prevention.

Relationship between antofloxacin concentration and QT prolongation and estimation of the possible false-positive rate.

PURPOSE: To elucidate the relationship between antofloxacin (AT) plasma concentration and QT interval prolongation, compare the effects of different correction and analytical methods on conclusions, and estimate the possible false-positive rate in thorough QT (TQT) studies. METHODS: Twenty-four healthy Chinese volunteers from a four-period crossover TQT study orally received 200 mg/d AT, 400 mg/d AT, 400 mg/d moxifloxacin, and a placebo in a random order for 5 d for each. QT interval samples were collected on d 1 and d 5. Population models were established describing the relationship between QT and AT concentration. The yardstick from ICH E14 guidelines was used to measure the effect of drugs on QT prolongation both in biostatistical and modeling analyses. A possible false-positive rate was estimated by constructing a 1000-time bootstrap to obtain the rate-of-difference values between d 1 and d 5 over 5 ms in the placebo period. RESULTS: In the modeling analysis, the QT prolongation estimate at the mean maximal concentration of AT (4.51 µg/mL) was 3.84 ms, and its upper bound of the one-sided 95 % CI was 7.04 ms, which showed a negative effect on QT interval prolongation. The estimation for the false-positive rate was 31 % in this study. CONCLUSION: The effect of AT on QT interval prolongation may not have been significant at the dosage of 400 mg. Baseline and placebo adjustments were necessary in TQT studies. Population modeling has demonstrated clear superiority in making full use of data to accurately analyze the relationship between drugs and QT intervals.

Characteristics of COVID-19 Clinical Trials in China Based on the Registration Data on ChiCTR and ClinicalTrials.gov.

OBJECTIVE: This study aimed to evaluate the fundamental characteristics of coronavirus disease (COVID-19) clinical trials registered in China. METHODS: COVID-19 clinical trials registered in China were analyzed from databases on ChiCTR and ClinicalTrials.gov. The study designs, samples, primary end points, and intervention measures were evaluated. RESULTS: In total, 262 intervention clinical trials were retrieved on March 10, 2020. Overall, 181 (69.1%) trials involved two groups, 200 (76.3%) trials were randomized parallel trials, 24 (9.2%) trials were double blind, and 60.3% of trials included ≤100 participants. Sixty (22.9%) trials considered symptom improvement as the primary endpoint and 43 (16.4%) trials considered the rate or time at which the subjects became virus-free as the primary endpoint. Of 262 intervention studies, chemical drugs and biological products were studied in 105 (40.1%) intervention studies, of which antiviral drugs accounted for 15.3% and malaria drugs accounted for 8.4% of the studies. Among all trials, 27.9% of the studies used traditional Chinese medicine (TCM), 10.3% used cell therapy, and 5.0% used plasma therapy. CONCLUSION: This study is the first snapshot of the landscape of COVID-19 clinical trials registered in China and provided the basic features of clinical trial designs for the treatment and prevention of COVID-19 to offer useful information to guide future clinical trials on COVID-19 in other countries.

Interpreting the Pharmacological Mechanisms of Huachansu Capsules on Hepatocellular Carcinoma Through Combining Network Pharmacology and Experimental Evaluation.

Hepatocellular carcinoma (HCC) is one of the most fatal cancers across the world. Chinese medicine has been used as adjunctive or complementary therapy for the management of HCC. Huachansu belongs to a class of toxic steroids isolated from toad venom that has important anti-cancer property. This study was aimed to identify the bioactive constituents and molecular targets of Huachansu capsules (HCSCs) for treating HCC using network pharmacology analysis and experimental assays. The major bioactive components of HCSCs were determined using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). A series of network pharmacology methods including target prediction, pathway identification, and network establishment were applied to identify the modes of action of HCSCs against HCC. Furthermore, a series of experiments, including MTT, clonogenic assay, 3-D transwell, wound healing assay, as well as flow cytometry, were conducted to verify the inhibitory ability of HCSCs on HCC in vitro. The results showed that 11 chemical components were identified from HCSCs. The network pharmacological analysis showed that there were 82 related anti-HCC targets and 14 potential pathways for these 11 components. Moreover, experimental assays confirmed the inhibitory effects of HCSCs against HCC in vitro. Taken together, our study revealed the synergistic effects of HCSCs on a systematic level, and suggested that HCSCs exhibited anti-HCC effects in a multi-component, multi-target, and multi-pathway manner.

Integrating Network Pharmacology and Experimental Models to Investigate the Efficacy of Coptidis and Scutellaria Containing Huanglian Jiedu Decoction on Hepatocellular Carcinoma.

Unlike Western medicines with single-target, the traditional Chinese medicines (TCM) always exhibit diverse curative effects against multiple diseases through its "multi-components" and "multi-targets" manifestations. However, discovery and identification of the major therapeutic diseases and the underlying molecular mechanisms of TCM remain to be challenged. In the current study, we, for the first time, applied an integrated strategy by combining network pharmacology with experimental evaluation, for exploration and demonstration of the therapeutic potentials and the underlying possible mechanisms of a classic TCM formula, Huanglian Jiedu decoction (HLJDD). First, the herb-compound, compound-protein, protein-pathway, and gene-disease networks were constructed to predict the major therapeutic diseases of HLJDD and explore the underlying molecular mechanisms. Network pharmacology analysis showed the top one predicted disease of HLJDD treatment was cancer, especially hepatocellular carcinoma (HCC) and inflammation-related genes played an important role in the treatment of HLJDD on cancer. Next, based on the prediction by network pharmacology analysis, both in vitro HCC cell and in vivo orthotopic HCC implantation mouse models were established to validate the curative role of HLJDD. HLJDD exerted its antitumor activity on HCC in vitro, as demonstrated by impaired cell proliferation and colony formation abilities, induced apoptosis and cell cycle arrest, as well as inhibited migratory and invasive properties of HCC cells. The orthotopic HCC implantation mouse model further demonstrated the remarkable antitumour effects of HLJDD on HCC in vivo. In conclusion, our study demonstrated the effectiveness of integrating network pharmacology with experimental study for discovery and identification of the major therapeutic diseases and the underlying molecular mechanisms of TCM.

Analysis of Time-Course, Dose-Effect, and Influencing Factors of Antidepressants in the Treatment of Acute Adult Patients With Major Depression.

OBJECTIVE: Model-based meta-analysis was used to describe the time-course and dose-effect relationships of antidepressants and also simultaneously investigate the impact of various factors on drug efficacy. METHODS: This study is a reanalysis of a published network meta-analysis. Only placebo-controlled trials were included in this study. The change rate in depression rating scale scores from baseline was used as an efficacy indicator because a continuous variable is more likely to reflect subtle differences in efficacy between drugs. RESULTS: A total 230 studies containing 64 346 patients were included in the analysis. The results showed that the number of study sites (single or multi-center) and the type of setting (inpatient or noninpatient) are important factors affecting the efficacy of antidepressants. After deducting the placebo effect, the maximum pure drug efficacy value of inpatients was 18.4% higher than that of noninpatients, and maximum pure drug efficacy value of single-center trials was 10.2% higher than that of multi-central trials. Amitriptyline showed the highest drug efficacy. The remaining 18 antidepressants were comparable or had little difference. Within the approved dose range, no significant dose-response relationship was observed. However, the time-course relationship is obvious for all antidepressants. In terms of safety, with the exception of amitriptyline, the dropout rate due to adverse events of other drugs was not more than 10% higher than that of the placebo group. CONCLUSION: The number of study sites and the type of setting are significant impact factors for the efficacy of antidepressants. Except for amitriptyline, the other 18 antidepressants have little difference in efficacy and safety.

Integrating Network Pharmacology and Pharmacological Evaluation for Deciphering the Action Mechanism of Herbal Formula Zuojin Pill in Suppressing Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a kind of complicated disease with an increasing incidence all over the world. A classic Chinese medicine formula, Zuojin pill (ZJP), was shown to exert therapeutic effects on HCC. However, its chemical and pharmacological profiles remain to be elucidated. In the current study, network pharmacology approach was applied to characterize the action mechanism of ZJP on HCC. All compounds were obtained from the corresponding databases, and active compounds were selected according to their oral bioavailability and drug-likeness index. The potential proteins of ZJP were obtained from the traditional Chinese medicine systems pharmacology (TCMSP) database and the traditional Chinese medicine integrated database (TCMID), whereas the potential genes of HCC were obtained from OncoDB.HCC and Liverome databases. The potential pathways related to genes were determined by gene ontology (GO) and pathway enrichment analyses. The compound-target and target-pathway networks were constructed. Subsequently, the potential underlying action mechanisms of ZJP on HCC predicted by the network pharmacology analyses were experimentally validated in HCC cellular and orthotopic HCC implantation murine models. A total of 224 components in ZJP were obtained, among which, 42 were chosen as bioactive components. The compound-target network included 32 compounds and 86 targets, whereas the target-pathway network included 70 proteins and 75 pathways. The in vitro and in vivo experiments validated that ZJP exhibited its prominent therapeutic effects on HCC mainly via the regulation of cell proliferation and survival though the EGFR/MAPK, PI3K/NF-κB, and CCND1 signaling pathways. In conclusion, our study suggested combination of network pharmacology prediction with experimental validation may offer a useful tool to characterize the molecular mechanism of traditional Chinese medicine (TCM) ZJP on HCC.