Ameliorative Effect of Ethanolic Echinacea purpurea against Hyperthyroidism-Induced Oxidative Stress via AMRK and PPAR Signal Pathway Using Transcriptomics and Network Pharmacology Analysis.

Echinacea purpurea (L.) Moench (EP) is a well-known botanical supplement with antioxidant characteristics. However, the effects of EP on oxidative stress induced by hyperthyroidism have not yet been studied. This study was designed to evaluate the antioxidative effect of ethanolic Echinacea Purpurea (EEP) on hyperthyroidism-induced oxidative stress mice using an integrated strategy combining transcriptomics with network pharmacology analysis. Firstly, a hyperthyroidism mice model was induced via thyroxine (160 mg/kg) and EEP (1, 2, or 4 g/kg) once daily for 2 weeks. Body weight, thyroid-stimulating hormones, and oxidative stress markers were tested. Secondly, EEP regulating the potential genes at transcript level were analyzed. Thirdly, a network pharmacology based on the constituents of EEP identified using UPLC-Q-TOF-MS analysis was adopted. Finally, a joint analysis was performed to identify the key pathway. The results showed that EEP significantly changed the thyroid-stimulating hormones and oxidative stress markers. Meanwhile, RT-qPCR and Western Blotting demonstrated that the mechanism of the antioxidant effect of EEP reversed the mRNA expression of EHHADH, HMGCR and SLC27A2 and the protein expression of FABP and HMGCR in AMPK and PPAR signaling pathways. This study integrates transcriptomics with network pharmacology to reveal the mechanism of ameliorative effect of EEP on hyperthyroidism-induced oxidative stress.

Lignans with NO inhibitory activity from Tinospora sinensis.

Two new lignan glucosides, tinsinlignans A and B (1 and 2), two new oxyneolignans, tinsinlignans C and D (3 and 4), along with one known analogue (5), were isolated from the stems of Tinospora sinensis. The structures of the new compounds were elucidated based on analysis of spectroscopic data, and the absolute configuration of 1 was determined through electronic circular dichroism (ECD) calculation based on the time-dependent density functional theory (TD-DFT). Compounds 1-4 were evaluated for their inhibitory effects on nitric oxide (NO) production induced by lipopolysaccharide (LPS) in murine RAW264.7 macrophage cells and compounds 1 and 2 exhibited moderate inhibitory activities with IC50 values of 18.5 ± 2.0 and 28.8 ± 1.2 µmol·L-1, respectively.

DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal.

Combinatorial therapies that target multiple pathways have shown great promises for treating complex diseases. DrugComb (https://drugcomb.org/) is a web-based portal for the deposition and analysis of drug combination screening datasets. Since its first release, DrugComb has received continuous updates on the coverage of data resources, as well as on the functionality of the web server to improve the analysis, visualization and interpretation of drug combination screens. Here, we report significant updates of DrugComb, including: (i) manual curation and harmonization of more comprehensive drug combination and monotherapy screening data, not only for cancers but also for other diseases such as malaria and COVID-19; (ii) enhanced algorithms for assessing the sensitivity and synergy of drug combinations; (iii) network modelling tools to visualize the mechanisms of action of drugs or drug combinations for a given cancer sample and (iv) state-of-the-art machine learning models to predict drug combination sensitivity and synergy. These improvements have been provided with more user-friendly graphical interface and faster database infrastructure, which make DrugComb the most comprehensive web-based resources for the study of drug sensitivities for multiple diseases.

Chemical constituents from Tinospora sagittata and their biological activities.

Six undescribed low-polarity compounds including three rare 14-methylergostane steroids (1-3), one euphane triterpenoid (4) and two octadecanoic acid ethyl esters (5 and 6), along with ten previously reported terpenyl cometabolites (7-16), were isolated from the stems of Tinospora sagittata. Their structures were determined by detailed spectroscopic analyses and comparison with structurally related known compounds, and all of them have been reported from T. sagittata for the first time. Compounds 4-6 and 16 showed potent in vitro inhibitory activity against the diabetes target α-glucosidase, while compounds 10 and 14 displayed promising antibacterial effect toward Staphylococcus aureus ATCC 25923.

Network-based modeling of herb combinations in traditional Chinese medicine.

Traditional Chinese medicine (TCM) has been practiced for thousands of years for treating human diseases. In comparison to modern medicine, one of the advantages of TCM is the principle of herb compatibility, known as TCM formulae. A TCM formula usually consists of multiple herbs to achieve the maximum treatment effects, where their interactions are believed to elicit the therapeutic effects. Despite being a fundamental component of TCM, the rationale of combining specific herb combinations remains unclear. In this study, we proposed a network-based method to quantify the interactions in herb pairs. We constructed a protein-protein interaction network for a given herb pair by retrieving the associated ingredients and protein targets, and determined multiple network-based distances including the closest, shortest, center, kernel, and separation, both at the ingredient and at the target levels. We found that the frequently used herb pairs tend to have shorter distances compared to random herb pairs, suggesting that a therapeutic herb pair is more likely to affect neighboring proteins in the human interactome. Furthermore, we found that the center distance determined at the ingredient level improves the discrimination of top-frequent herb pairs from random herb pairs, suggesting the rationale of considering the topologically important ingredients for inferring the mechanisms of action of TCM. Taken together, we have provided a network pharmacology framework to quantify the degree of herb interactions, which shall help explore the space of herb combinations more effectively to identify the synergistic compound interactions based on network topology.

Bioactive aromatic butenolides from a mangrove sediment originated fungal species, Aspergillus terreus SCAU011.

Seven new compounds including five aromatic butenolide analogues (1-5), one quinazolinone alkaloid (6) and one benzoic acid derivative (7), along with eleven known co-metabolites (8-18), were isolated from Aspergillus terreus SCAU011, a fungus from the rhizosphere sediment of a mangrove plant Rhizophora stylosa. The structures of these isolates were established by a combination of MS, NMR and ECD data analyses, as well as chemical method. Compound 3 is a rare ring-open aromatic butenolide, while 6 represents the first natural ring-open benzomalvin-type quinazolinone alkaloid. Also, the previously reported structures for asperlides A-C were proposed to be revised in the present work. The COX-2 inhibitory, α-glucosidase inhibitory, antioxidant and antibacterial activities of all the compounds were assessed. While compounds 4, 6, 11 and 18 exhibited better COX-2 inhibitory activity than the positive control celecoxib, compounds 9 and 10 showed significant α-glucosidase inhibitory activity with IC50 values of 56.1 and 12.9 µM, respectively. Meanwhile, half of the tested samples (1, 8-11 and 15-17) exerted similar or better antioxidant activity compared with the reference drug curcumin, and compounds 3, 9, 17 and 18 displayed moderate antibacterial effect against Staphylococcus aureus.

Unsupervised Learning and Multipartite Network Models: A Promising Approach for Understanding Traditional Medicine.

The ultimate goal of precision medicine is to determine right treatment for right patients based on precise diagnosis. To achieve this goal, correct stratification of patients using molecular features and clinical phenotypes is crucial. During the long history of medical science, our understanding on disease classification has been improved greatly by chemistry and molecular biology. Nowadays, we gain access to large scale patient-derived data by high-throughput technologies, generating a greater need for data science including unsupervised learning and network modeling. Unsupervised learning methods such as clustering could be a better solution to stratify patients when there is a lack of predefined classifiers. In network modularity analysis, clustering methods can be also applied to elucidate the complex structure of biological and disease networks at the systems level. In this review, we went over the main points of clustering analysis and network modeling, particularly in the context of Traditional Chinese medicine (TCM). We showed that this approach can provide novel insights on the rationale of classification for TCM herbs. In a case study, using a modularity analysis of multipartite networks, we illustrated that the TCM classifications are associated with the chemical properties of the herb ingredients. We concluded that multipartite network modeling may become a suitable data integration tool for understanding the mechanisms of actions of traditional medicine.

New antibacterial thiophenes from Eclipta prostrata.

Three new thiophene derivatives, ecliprostins A-C (1-3), have been isolated from the aerial parts of a Compositae medicinal plant Eclipta prostrata, and structures of them have been elucidated by comprehensive spectroscopic analyses. Both ecliprostins A (1) and B (2) feature an acetylenic bithiophenyl backbone and also incorporate an isovalerate moiety, while ecliprostin C (3) is a symmetrical dimer of compound 1 and represents the first example bonded via an ether bridge among the very limited natural dimers. All three compounds show antibacterial activity against Staphylococcus aureus.

Fast-Acting Black-Phosphorus-Assisted Depression Therapy with Low Toxicity.

A black phosphorus (BP)-nanosheet-based drug-delivery system containing a therapeutic drug (Fluoxetine, Flu) is synthesized. According to subsequent behavioral, biochemical, and electrophysiological analysis, BP-Flu, after irradiated with near-infrared light (808 nm), can significantly reduce the therapy time of depression. Meanwhile, the inherent biotoxicity of Flu is also alleviated.

Mesenchymal stem cells combined with traditional Chinese medicine (qi-fang-bi-min-tang) alleviates rodent allergic rhinitis.

Mesenchymal stem cells (MSCs) have been proved to exert anti-inflammatory effects and regulate immune reactions. Traditional Chinese medicine (TCM), qi-fang-bi-min-tang, is effective for some patients with allergic diseases. However, it remains unclear whether MSCs combined with TCM could benefit the treatment of allergic rhinitis (AR). In this study, we reported an additional effect of TCM (qi-fang-bi-min-tang) on the therapy of AR under MSCs treatment. Intriguingly, we observed that TCM-treated MSCs significantly inhibited the symptoms of AR and reduced the pathological changes of nasal mucosa in ovalbumin (OVA)-induced rats. The expression levels of interferon Î³ (IFN-γ), interleukin-17 (IL-17), and IL-4 were significantly decreased in the plasma of AR rats after injection of TCM-treated MSCs. TCM-treated MSCs reduced the levels of histamine secreted by mast cells and immunoglobulin E (IgE) secreted by plasma cells. In addition, we found that MSCs combined with TCM had a better therapeutic effect than TCM alone on AR in an OVA-induced mouse model. After OVA induction, MSCs combined with TCM significantly reduced the ratio of T helper type 1 (Th1), Th2, and Th17, but increased the proportion of Treg in the spleen of mice. Consistently, the expression levels of IFN-γ, IL-4, and IL-17 were significantly decreased, but transforming growth factor-ß1 was significantly increased in the plasma of AR mice after treated with TCM and MSCs. Our results from both rats and mice indicated that the effects of TCM combined with MSCs on the AR might be through regulating the secretion of Th1, Th2, and Th17 cytokines. This study suggested that TCM (qi-fang-bi-min-tang)-treated MSCs could be used in the clinical therapy of AR.

Predicting Meridian in Chinese traditional medicine using machine learning approaches.

Plant-derived nature products, known as herb formulas, have been commonly used in Traditional Chinese Medicine (TCM) for disease prevention and treatment. The herbs have been traditionally classified into different categories according to the TCM Organ systems known as Meridians. Despite the increasing knowledge on the active components of the herbs, the rationale of Meridian classification remains poorly understood. In this study, we took a machine learning approach to explore the classification of Meridian. We determined the molecule features for 646 herbs and their active components including structure-based fingerprints and ADME properties (absorption, distribution, metabolism and excretion), and found that the Meridian can be predicted by machine learning approaches with a top accuracy of 0.83. We also identified the top compound features that were important for the Meridian prediction. To the best of our knowledge, this is the first time that molecular properties of the herb compounds are associated with the TCM Meridians. Taken together, the machine learning approach may provide novel insights for the understanding of molecular evidence of Meridians in TCM.

New e:b-Friedo-Hopane Type Triterpenoids from Euphorbia peplus with Simiarendiol Possessing Significant Cytostatic Activity against HeLa Cells by Induction of Apoptosis and S/G2 Cell Cycle Arrest.

Seven rare e:b-friedo-hopane-type triterpenoids including four new (1-4) and three known (5-7) ones with 5 being first reported as a natural product, together with five other known triterpenoids (8-12), were isolated from the nonpolar fractions of the ethanolic extract of Euphorbia peplus. Structural assignments for these compounds were based on spectroscopic analyses and quantum chemical computation method. The structural variations for the C-21 isopropyl group, including dehydrogenation (1 and 3) and hydroxylation at C-22 (simiarendiol, 2), were the first cases among e:b-friedo-hopane-type triterpenoids. Simiarendiol (2) bearing a 22-OH showed significant cytostatic activity against HeLa and A549 human tumor cell lines with IC50 values of 3.93 ± 0.10 and 7.90 ± 0.31 µM, respectively. The DAPI staining and flow cytometric analysis revealed that simiarendiol (2) effectively induced cell apoptosis and arrested cell cycle at the S/G2 phases in a dose-dependent manner in HeLa cells.

Secondary metabolites from the mangrove sediment-derived fungus Penicillium pinophilum SCAU037.

Five new funicone derivatives, pinophilones A-E (1a/1b and 2-4), along with 18 biosynthetically related known analogues (5-22), were obtained from the culture of a mangrove sediment-derived fungus Penicillium pinophilum SCAU037. Their structures were established by analysis of 1D/2D NMR and MS data, while the absolute configurations of the new compounds were determined by ECD calculation based on time-dependent density functional theory (TD-DFT). The dihydrofuran moiety in 1a and 1b was first reported for funicone derivatives. Compound 22 exhibited antibacterial activity against Mycobacterium smegmatis and Staphylococcus aureus with IC50 of 23.5 and 2.6 µM, respectively, while 16, 18 and 22 showed significant α-glucosidase inhibitory activity with IC50 of 51.9, 78.4 and 33.8 µM, respectively.

DrugComb: an integrative cancer drug combination data portal.

Drug combination therapy has the potential to enhance efficacy, reduce dose-dependent toxicity and prevent the emergence of drug resistance. However, discovery of synergistic and effective drug combinations has been a laborious and often serendipitous process. In recent years, identification of combination therapies has been accelerated due to the advances in high-throughput drug screening, but informatics approaches for systems-level data management and analysis are needed. To contribute toward this goal, we created an open-access data portal called DrugComb (https://drugcomb.fimm.fi) where the results of drug combination screening studies are accumulated, standardized and harmonized. Through the data portal, we provided a web server to analyze and visualize users' own drug combination screening data. The users can also effectively participate a crowdsourcing data curation effect by depositing their data at DrugComb. To initiate the data repository, we collected 437 932 drug combinations tested on a variety of cancer cell lines. We showed that linear regression approaches, when considering chemical fingerprints as predictors, have the potential to achieve high accuracy of predicting the sensitivity of drug combinations. All the data and informatics tools are freely available in DrugComb to enable a more efficient utilization of data resources for future drug combination discovery.

Absolute structure assignment of an iridoid-monoterpenoid indole alkaloid hybrid from Dipsacus asper.

Iridoid-monoterpenoid indole alkaloid hybrids (IMIAHs) represent a rare class of natural products reported from only several plants of Rubiaceae and Dipsacaceae families, while their structural assignments remain a very challenging work due to complexity and flexibility. In the current study, a new IMIAH (1) was isolated from the roots of Dipsacus asper and its structure with absolute configuration was unambiguously established by a combination of spectroscopic analyses, chemical degradation and ECD calculation. A new oleanane-type triterpenoid saponin (2) and 15 known co-metabolites were also obtained and structurally characterized. Our biological evaluations showed that compound 2 exhibited moderate inhibition against acetylcholine esterase (AChE) with an IC50 value of 15.8 ±â€¯0.56 µM, and compound 15 displayed potent cytotoxicity selectively against human A549 and H157 lung cancer cells with IC50 values of 6.94 ±â€¯0.24 and 9.06 ±â€¯0.12 µM, respectively.

Phenolic bisabolane sesquiterpenoids from a Thai mangrove endophytic fungus, Aspergillus sp. xy02.

Seven new phenolic bisabolane sesquiterpenoids, (7R,10S)-7,10-epoxysydonic acid (1), (7S,10S)-7,10-epoxysydonic acid (2), (7R,11S)-7,12-epoxysydonic acid (3), (7S,11S)-7,12-epoxysydonic acid (4), 7-deoxy-7,14-didehydro-12-hydroxysydonic acid (5), (Z)-7-deoxy-7,8-didehydro-12-hydroxysydonic acid (6), and (E)-7-deoxy-7,8-didehydro-12-hydroxysydonic acid (7), along with five known analogues (8-12), were obtained from the culture of an endophytic fungus Aspergillus sp. xy02 isolated from the leaves of a Thai mangrove Xylocarpus moluccensis. All structures were assigned on the basis of detailed spectroscopic analyses. The absolute configurations of 1-4, being two pairs of epimers, were established by TDDFT-ECD calculations. Compound 12 showed mild antioxidative activity to scavenge DPPH radical with an IC50 of 72.1 µM, whereas 2, 3, 5, 7, 9, 11, and 12 displayed moderate inhibitory activities against Staphylococcus aureus ATCC 25923 with IC50 values ranging from 31.5 to 41.9 µM.

[Clinical characteristics and therapy of pan-drug resistant Acinetobacter baumannii infection].

OBJECTIVE: To analyze clinical characteristics and therapy of pan-resistant Acinetobacter baumannii (PDRAB) infection and explore the methods for effective therapy and prevention of this infection. METHODS: Nine hospitalized patients with PDRAB infection confirmed by pathogen and susceptibility testing were analyzed for the risk factors and the treatment outcomes were assessed by case analysis. RESULTS: PDRAB infections occurred mainly in patients with severe complications, most of whom had complications by diabetes or hypertension or damaged mucosal integrity due to mechanical ventilation, surgery and catheterization. The polymyxin sensitivity were 100% for these infections, but all the bacteria identified showed a antimicrobial resistance rates of 100%. The majority of the infections were acquired during hospitalization occurring mainly in the lungs; all the patients had prolonged hospitalization and received antibiotic treatments with high proportions of broad-spectrum antimicrobial agents especially third-generation cephalosporins and quinolones. Exclusive or sequential use of carbapenems and sulbactam in combination with quinolone or aminoglycoside produced favorable effects. CONCLUSIONS: The prevalence of hospital-acquired pan-resistance of PDRAB infections increased significantly in recent years, particularly in patients with high risk factors. The widespread use of broad-spectrum antibiotics may have some relevance to drug resistant occurrence. The application of carbapenems or sulbactam, or their sequential use, in combination with other agents may produce good effects.

[Establishment of high-throughput drug screening cell models based on JAK-STAT signal pathway].

AIM: To discover new drugs which may be applied to diseases of the immune system, hemogenesis system diseases and tumors, several high-throughput drug screening cell models based on JAK-STAT signal pathway have been established. METHODS: Four repeats of STAT DNA binding conserved sequences were synthesized, subcloned into pGL-Luc reporter vector and stably transfected into cell lines in vitro. Cell clones with high copy numbers of STAT binding sites and reporter genes were chosen as high-throughput drug screening cell models. The cell models were tested with known anti-allergic drugs and anti-tumor drugs by determining luciferase activity. The reaction was performed in 96 well micro-plates with a final volume of 50 microL. RESULTS: The cell models by performing rapid fluorescence assay were shown to be highly sensitive and stable after testing with cytokine and drugs. The modification of the expression plasmid simplified this method and made it more practical. It also provided good linear correlation, wide range of assay, highly sensitive and good reproducibility. CONCLUSION: The method can be performed by high-throughput drug screening for effective extraction of Chinese traditional herbs.