Taraxacum mongolicum extract inhibited malignant phenotype of triple-negative breast cancer cells in tumor-associated macrophages microenvironment through suppressing IL-10 / STAT3 / PD-L1 signaling pathways.

ETHNOPHARMACOLOGICAL RELEVANCE: Triple-negative breast cancer (TNBC) is the most aggressive and the worst prognosis breast cancer with limited treatment options. Taraxacum mongolicum (also called dandelion) is a traditional Chinese medicine has been used to treat mastitis, breast abscess, and hyperplasia of mammary glands since ancient times. In modern pharmacological research, dandelion has been proven with anti-breast cancer activities. We previously reported that dandelion extract could induce apoptosis in TNBC cells. However, its anti-tumor effects and mechanisms in the tumor microenvironment have not yet been elucidated. AIM OF THE STUDY: Tumor-associated macrophages (TAMs) play an important role in regulating the interaction between tumor cells and the immune system. The present study aimed to investigate the effects and mechanisms of dandelion extract on TNBC cells under the microenvironment of TAMs, as well as its influence on the polarization of M2 macrophages. MATERIALS AND METHODS: M2 macrophages were induced by phorbol-12-myristate 13-acetate (PMA) and interleukin 4 (IL-4), and verified by flow cytometry, quantitative RT-PCR (qRT-PCR), Western blotting, and ELISA. MDA-MB-231 and MDA-MB-468 TNBC cells were co-cultured with the supernatant of M2 macrophage which providing the TAMs microenvironment. The antitumor activity of dandelion extract in TNBC cells was evaluated by MTT assay. The invasive and migratory capacity of TNBC cells was measured by transwell assays. The expression of protein and gene was assessed by Western blotting and qRT-PCR, respectively. RESULTS: TAMs microenvironment promoted the proliferation, migration, and invasion of TNBC cells. However, dandelion extract inhibited the malignant property of MDA-MB-231 and MDA-MB-468 cells induced by TAMs. Both of TAMs and IL-10 caused STAT3 activation and PD-L1 higher expression, the immunosuppressive molecules in TNBC cells, and this effect can be attenuated by IL-10 neutralizing antibody. Dandelion extract exerted inhibition on STAT3 and PD-L1 in TNBC cells under TAMs microenvironment. Furthermore, in M2 macrophages, dandelion extract remarkably promoted the expression of M1-like marker TNF-α, IL-8, and iNOS, but reduced M2-like marker IL-10, CD206, Arginase-1, and TGF-ß. CONCLUSION: Dandelion extract inhibited the proliferation, migration and invasion of TNBC cells in TAMs microenvironment through suppressing IL-10/STAT3/PD-L1 immunosuppressive signaling pathway. Furthermore, dandelion extract promoted the polarization of macrophages from M2 to M1 phenotype. Thus, our results indicated that dandelion may serve as a promising therapeutic strategy for TNBC by modulating tumor immune microenvironment.

Differentiating Westlake Longjing tea from the first- and second-grade producing regions using ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry-based untargeted metabolomics in combination with chemometrics.

There are numerous articles published for geographical discrimination of tea. However, few research works focused on the authentication and traceability of Westlake Longjing green tea from the first- and second-grade producing regions because the tea trees are planted in a limited growing zone with identical cultivate condition. In this work, a comprehensive analytical strategy was proposed by ultrahigh performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based untargeted metabolomics coupled with chemometrics. The automatic untargeted data analysis strategy was introduced to screen metabolites that expressed significantly among different regions. Chromatographic features of metabolites can be automatically and efficiently extracted and registered. Meanwhile, those that were valuable for geographical origin discrimination were screened based on statistical analysis and contents in samples. Metabolite identification was performed based on high-resolution mass values and tandem mass spectra of screened peaks. Twenty metabolites were identified, based on which the two-way encoding partial least squares discrimination analysis was built for geographical origin prediction. Monte Caro simulation results indicated that prediction accuracy was up to 99%. Our strategy can be applicable for practical applications in the quality control of Westlake Longjing green tea.

A comprehensive automatic data analysis strategy for gas chromatography-mass spectrometry based untargeted metabolomics.

Automatic data analysis for gas chromatography-mass spectrometry (GC-MS) is a challenging task in untargeted metabolomics. In this work, we provide a novel comprehensive data analysis strategy for GC-MS-based untargeted metabolomics (autoGCMSDataAnal) by developing a new automatic strategy for performing TIC peak detection and resolution and proposing a novel time-shift correction and component registration algorithm. autoGCMSDataAnal uses original acquired GC-MS datafiles as input to automatically perform TIC peak detection, component resolution, time-shift correction and component registration, statistical analysis, and compound identification. We utilize standards and complex plant samples to comprehensively investigate the performance of autoGCMSDataAnal. The results suggest that the developed strategy is comparable with several state-of-the-art methods that are widely used in GC-MS-based untargeted metabolomics. Based on the proposed strategy, we develop a user-friendly MATLAB GUI for users who are unfamiliar with programming languages to facilitate their routine analysis, which can be freely downloaded at: http://software.tobaccodb.org/software/autogcmsdataanal.

Automatic peak detection coupled with multivariate curve resolution-alternating least squares for peak resolution in gas chromatography-mass spectrometry.

Gas chromatography-mass spectrometry (GCMS) has been extensively used in complex sample analysis for the high-throughput characterization of volatile and semivolatile compounds. However, the accurate extraction of compound information remains challenging. Here, we present a combined algorithm strategy for GCMS data analysis to accurately screen metabolites across groups. First, chromatographic peaks in a total ion chromatogram (TIC) are extracted by using a Gaussian smoothing strategy and aligned on the basis of their mass spectra by a dynamic programing algorithm. The aligned TIC peaks are then registered into a component list table by applying a nearest-neighbor clustering algorithm. Significantly expressed TIC peaks among groups are screened through statistical analysis, such as ANOVA. Second, a chemometric method of multivariate curve resolution-alternating least squares for the peak resolution of the screened TIC peaks is utilized to retrieve the chromatographic and mass spectral profiles of coeluted components. The developed strategy is employed for the analysis of standard and complex plant sample datasets. Results indicate that our methodology is comparable with several state-of-the-art methods that are widely used in GC-MS-based metabolomics.

Automatic data analysis workflow for ultra-high performance liquid chromatography-high resolution mass spectrometry-based metabolomics.

Data analysis for ultra-performance liquid chromatography high-resolution mass spectrometry-based metabolomics is a challenging task. The present work provides an automatic data analysis workflow (AntDAS2) by developing three novel algorithms, as follows: (i) a density-based ion clustering algorithm is designed for extracted-ion chromatogram extraction from high-resolution mass spectrometry; (ii) a new maximal value-based peak detection method is proposed with the aid of automatic baseline correction and instrumental noise estimation; and (iii) the strategy that clusters high-resolution m/z peaks to simultaneously align multiple components by a modified dynamic programing is designed to efficiently correct time-shift problem across samples. Standard compounds and complex datasets are used to study the performance of AntDAS2. AntDAS2 is better than several state-of-the-art methods, namely, XCMS Online, Mzmine2, and MS-DIAL, to identify underlying components and improve pattern recognition capability. Meanwhile, AntDAS2 is more efficient than XCMS Online and Mzmine2. A MATLAB GUI of AntDAS2 is designed for convenient analysis and is available at the following webpage: http://software.tobaccodb.org/software/antdas2.

Automatic untargeted metabolic profiling analysis coupled with Chemometrics for improving metabolite identification quality to enhance geographical origin discrimination capability.

Untargeted metabolic profiling analysis is employed to screen metabolites for specific purposes, such as geographical origin discrimination. However, the data analysis remains a challenging task. In this work, a new automatic untargeted metabolic profiling analysis coupled with a chemometric strategy was developed to improve the metabolite identification results and to enhance the geographical origin discrimination capability. Automatic untargeted metabolic profiling analysis with chemometrics (AuMPAC) was used to screen the total ion chromatographic (TIC) peaks that showed significant differences among the various geographical regions. Then, a chemometric peak resolution strategy is employed for the screened TIC peaks. The retrieved components were further analyzed using ANOVA, and those that showed significant differences were used to build a geographical origin discrimination model by using two-way encoding partial least squares. To demonstrate its performance, a geographical origin discrimination of flaxseed samples from six geographical regions in China was conducted, and 18 TIC peaks were screened. A total of 19 significant different metabolites were obtained after the peak resolution. The accuracy of the geographical origin discrimination was up to 98%. A comparison of the AuMPAC, AMDIS, and XCMS indicated that AuMPACobtained the best geographical origin discrimination results. In conclusion, AuMPAC provided another method for data analysis.

Cyclodextrin-Catalyzed Organic Synthesis: Reactions, Mechanisms, and Applications.

Cyclodextrins are well-known macrocyclic oligosaccharides that consist of α-(1,4) linked glucose units and have been widely used as artificial enzymes, chiral separators, chemical sensors, and drug excipients, owing to their hydrophobic and chiral interiors. Due to their remarkable inclusion capabilities with small organic molecules, more recent interests focus on organic reactions catalyzed by cyclodextrins. This contribution outlines the current progress in cyclodextrin-catalyzed organic reactions. Particular emphases are given to the organic reaction mechanisms and their applications. In the end, the future directions of research in this field are proposed.

[Progress on treatment of rheumatoid arthritis with ethnodrugs].

Rheumatoid arthritis(RA) is a chronic autoimmune disease, belonging to the "Arthromyodynia (Bi Zheng)" category in traditional Chinese medicine. However, the ethnomedicine has a unique understanding of RA, with a long-term clinical experience accumulation and significant efficacy in the treatment of RA, and it has now become one of the important means in treatment of RA. On the basis of literature research, the understanding of RA and commonly used Tibetan medicine, Mongolian medicine, Hui medicine and other herbs and preparations were reviewed in this paper, with the aim of providing a reference for its clinical treatment of RA and research and development of innovative drugs.

[Advances on chemical constituents and bioactivities of genus Stellera].

Advance on chemical constituents and pharmacological activities of Stellera plants have been conducted. The chemical constituents include terpenes, coumarins, flavonoids, lignans, volatile oils, and other compounds. Pharmacological studies showed that diterpenoids and biflavones showed strong activities, such as antitumor, anti-HIV, and immune regulations. This review hopes to provide a scientific basis for further research and explorations of the medicinal values of the genus.

Component analysis and free radical-scavenging potential of Panax notoginseng and Carthamus tinctorius extracts.

Panax notoginseng and Carthamus tinctorius are known as traditional medicinal plants, and they also have edible values. To better understand their pharmacological mechanism, the present study assessed the in vitro antioxidant activities of extracts of P. notoginseng (EPN) and C. tinctorius (ECT). In addition, the main components of EPN and ECT were determined by HPLC. The results show that EPN mainly contained saponins, which were effective in scavenging (.)OH and O(.)(2-), while showing a low activity in the DPPH(.) assay. Flavonoids were the main components of ECT and were active in scavenging all three radicals in a dose-dependent manner. In brief, the antioxidant properties of EPN and ECT are distinct and might be complementary, their combined use tending to be more effective in scavenging (.)OH (P<0.05 vs. EPN or ECT).

Three new acylated glycosides from the stems of Casearia velutina and their protective effect against H2O2-induced impairment in PC12 cells.

Chemical investigation of the stems of Casearia velutina led to the isolation and structural elucidation of three new acylated glycosides, casearicosides A-C (1-3), together with 13 known compounds. The structures of the new compounds were established by spectroscopic and chemical methods. These isolates were evaluated for protective effects against H(2)O(2)-induced impairment in PC12 cells and inhibitory activity against snake venom phosphodiesterase I. A brief chemotaxonomy of the genus Casearia is also discussed.

A new seco-friedelolactone acid from the bark and twigs of Itoa orientalis.

A new seco-friedelolactone, named itoaic acid, together with 5 known compounds was isolated from the bark and twigs of Itoa orientalis. The structure was elucidated by means of MS, 1D and 2D NMR techniques. Anti-inflammatory activity against COX-2 was evaluated for several compounds from I. orientalis and another Flacourtiaceae plant Xylosma controversum.

Investigation of two Flacourtiaceae plants: Bennettiodendron leprosipes and Flacourtia ramontchi.

Investigations of two Flacourtiaceae plants, Bennettiodendron leprosipes and Flacourtia ramontchi, resulted in the isolation and structural elucidation of six new constituents including two phenolic glycosides ( 1 and 2), one lignan ( 3), two lignan glycosides ( 4 and 5), and a monoterpene glycoside ( 6), together with 22 known compounds ( 7- 28). The structures of the new compounds were elucidated by spectroscopic analysis and chemical methods. The selected isolates 1, 2, 8- 10, 22- 26, and some phenolic glycosides 29- 42 previously isolated from another Flacourtiaceae plant, Itoa orientalis, were tested against snake venom phosphodiesterase I (PDE I) activity. The result indicated that 22, 30, 32, 34, and 40 exhibited moderate inhibitory activities against PDE I with the values ranging from 13.15 to 20.86 %, and 1, 8, 10, 25, 31, 33, 35, 38, 39, and 41 showed weak inhibitory activity.

Itosides J-N from Itoa orientalis and structure - anti-COX-2 activity relationship of phenolic glycosides.

Two new phenolic glycosides, itosides J (1) and K (2), two new cylcohexenoyl glycosides, itosides L (3) and M (4), a new flavone glycoside, itoside N (5), and echitin (6) were isolated from the extract of the bark, twigs, and leaves of Itoa orientalis, together with 22 known compounds. The structures were elucidated by means of UV, IR, MS, and NMR techniques, and the relative configuration of compound 3 was confirmed by X-ray crystallography. NMR data for 6 are reported for the first time. Compounds 1, 3, 5, and phenolic glycosides 7- 22 were also assayed for anti-inflammatory activity against COX-2. Compounds 8, 10, 12- 14, 16, 19, 24, 26, and 27 showed significant inhibitory effects, with inhibitory rates of 49.7-85.3% at 10 microM.