Pseudotargeted metabolomics-based random forest model for tracking plant species from herbal products.

BACKGROUND: The "one-to-multiple" phenomenon is prevalent in medicinal herbs. Accurate species identification is critical to ensure the safety and efficacy of herbal products but is extremely challenging due to their complex matrices and diverse compositions. PURPOSE: This study aimed to identify the determinable chemicalome of herbs and develop a reasonable strategy to track their relevant species from herbal products. METHODS: Take Astragali Radix-the typical "one to multiple" herb, as a case. An in-house database-driven identification of the potentially bioactive chemicalome (saponins and flavonoids) in AR was performed. Furthermore, a pseudotargeted metabolomics method was first developed and validated to obtain high-quality semi-quantitative data. Then based on the data matrix, the random forest algorithm was trained to predict Astragali Radix species from commercial products. RESULTS: The pseudotargeted metabolomics method was first developed and validated to obtain high-quality semi-quantitative data (including 56 saponins and 49 flavonoids) from 26 batches of AR. Then the random forest algorithm was well-trained by importing the valid data matrix and showed high performance in predicting Astragalus species from ten commercial products. CONCLUSION: This strategy could learn species-special combination features for accurate herbal species tracing and could be expected to promote the traceability of herbal materials in herbal products, contributing to manufacturing standardization.

Effect of Plant-Derived n-3 Polyunsaturated Fatty Acids on Blood Lipids and Gut Microbiota: A Double-Blind Randomized Controlled Trial.

BACKGROUND: Several cardioprotective mechanisms attributed to n-3 polyunsaturated fatty acids (PUFAs) have been widely documented. Significant interest has recently focused on the role of human gut microbiota in metabolic disorders. However, the role of plant-derived n-3 PUFAs on blood lipid profiles is controversial and the effect on gut microbiota is still unclear. OBJECTIVES: We aimed to perform a double-blind randomized controlled trial to test the effect of plant-derived n-3 PUFAs on the blood lipids and gut microbiota of patients with marginal hyperlipidemia. METHODS: According to the inclusion and exclusion criteria, 75 participants with marginal hyperlipidemia were randomly assigned to the intervention group (supplied with n-3 PUFA-enriched plant oil) or control group (supplied with corn oil), respectively, for a 3-month treatment. Participants and assessors were blinded to the allocation. The primary outcomes of the trial were the changes in serum lipid levels. Secondary outcomes were changes in gut microbiota and metabolites. For the primary outcomes, we conducted both an intent-to-treat (ITT) analysis and a per protocol (PP) analysis. For the secondary outcomes, we only conducted the PP analysis among the participants who provided fecal sample. RESULTS: Fifty-one participants completed the trial. Relative to the control group, the n-3 PUFA supplementation resulted in significant reduction in total cholesterol (TC) levels (-0.43 mmol/L, 95% CI-0.84 to-0.01 mmol/L, P < 0.05). The n-3 PUFA supplementation was also associated with significantly increased relative abundance of Bacteroidetes in phylum level (P < 0.01; false discovery rate (FDR) corrected p = 0.11), and decreased the ratio between Firmicutes and Bacteroidetes (P < 0.05; FDR corrected p = 0.16). At genus level, the intervention of plant derived n-3 PUFAs resulted in a significant decrease in relative abundance of Phascolarctobacterium (P < 0.01; FDR corrected p = 0.18) and Veillonella (P < 0.01; FDR corrected p = 0.18) after the intervention. CONCLUSIONS: Our results demonstrated that plant-derived n-3 PUFAs beneficially affected the serum levels of TC and decreased the ratio between Firmicutes and Bacteroidetes during the 12-week intervention period, which might confer advantageous consequences for lipid metabolism and intestinal health.

Ablation Therapy Combined with EGFR TKIs in the Treatment of Advanced Non-Small Cell Lung Cancer: A Meta-Analysis of Randomized Controlled Trials.

OBJECTIVE: Systematically evaluate the efficacy of physical ablation combined with TKI in the treatment of advanced non-small cell lung cancer (NSCLC). METHODS: We performed a comprehensive search of databases including OVID, PubMed, EMBASE, the Cochrane Library, and three Chinese databases (China National Knowledge Infrastructure, Wanfang Database, and Chongqing Weipu Database). The aim was to identify randomized controlled trials (RCT) investigating physical ablation as the treatment for advanced NSCLC. We also evaluated the methodological quality of the included studies and summarized the data extracted for meta-analysis with Review Manager 5.3. RESULTS: A total of 9 studies, including 752 patients, were evaluable. The meta-analysis results show that the complete response rate (CRR) (RR: 2.23, 95% CI: 1. 46 to 3.40, P 0.01), partial response rate (PRR) (RR: -2.25, 95% CI: 1.41 to 3.59, P 0.01), and disease control rate (DCR) (RR: -2.80, 95% CI: 1.64 to 4.80, P< 0.01) of patients with advanced NSCLC who received physical ablation combined with TKI therapy were higher than those who did not receive physical ablation therapy. The control groups from seven of the studies had a total of 606 patients with targeted therapies and chemotherapy. The complete response rate was (CRR) (RR: 2.48, 2.4895% CI: 1.55 to 2.47, P 0.01), partial response rate (PRR) (RR: -1.66, 95% CI: 1.20 to 2.31, P< 0.01), and disease control rate (DCR) (RR: -2.68, 95% CI: 1.41 to 5.06, P< 0.01) for patients with advanced NSCLC who had received physical ablation combined with targeted therapies and chemotherapy, compared to patients who had not received physical ablation therapy. This difference was statistically significant. Above all, these results showed that the clinical efficacy of physical ablation combined EGFR-TKIs therapy (regardless of whether it was combined with chemotherapy) was better than that of EGFR-TKIs therapy alone. CONCLUSION: Physical ablation combined with TKI treatment in patients with advanced NSCLC can improve efficacy.

Bioactivity-guided discovery of quality control markers in rhizomes of Curcuma wenyujin based on spectrum-effect relationship against human lung cancer cells.

BACKGROUND: Due to the diversity of the ingredients, the complexity of the mechanism of action, the uncertainty of the effective ingredients, coupled with the multiple species and multiple growing areas, the quality control (QC) of Traditional Chinese Medicines (TCMs) is challenging. Discovering and identifying effective compounds from the complex extracts of TCMs and then establishing a scientific QC method is the key to the holistic QC of TCMs. PURPOSE: To develop an anti-lung-cancer-guided spectrum-effect relationship approach for the discovery of QC markers of the rhizome of Curcuma wenyujin (WEZ) and establish a bioactive compounds-based holistic QC method. METHODS: The chemical profiling of the volatile oil (WVO) from 42 batches of WEZ collected from different growing areas was performed by GC-MS. The anti-lung cancer activity of different WVO samples was determined by CCK-8 assay against human lung cancer cells (A549). The apoptosis and cell cycle analysis under different concentrations of WVO were detected by flow cytometry. SIMCA-P software was used to perform multivariate statistical analysis on the chemical composition of different WVO samples and to find the different components. Active compounds were screened using a PLSR model of the spectrum-effect relationship. Bioactive compounds-based fingerprint and quantification of the leading bioactive compounds were developed by GC-MS and GC-FID, respectively. RESULTS: Seventy-eight compounds were detected in WVO and 54 were successfully identified. The multivariate statistical analysis uncovered that WVO components and the anti-A549 activity of WVO at the concentration of 60 nl/ml differ greatly according to the origin of the plant. The WVO at the concentration of 60 nl/ml (IC50) increased A549 cells apoptosis significantly with late and early apoptosis of 15.61% and 7.80%, and the number of cells in the G2/M phase were also increased significantly under this concentration. The spectrum-effect relationship analysis revealed that 44 compounds were positively correlated with their activities, and the result was verified by A549 cell viability assay. Sixteen positively correlated compounds were further selected as QC markers according to their relative amount > 0.5% and anticancer activity. Finally, the 16 QC markers-based GC-MS fingerprint was established to holistically control the quality of WEZ, and a GC-FID method was developed for the quantification of leading bioactive compounds, ß-elemene and ß-caryophyllene. CONCLUSION: Based on an anti-lung-cancer-guided spectrum-effect relationship approach, the bioactive compounds-based holistic QC method was successfully developed for WEZ, which could provide a valuable reference for the QC of TCMs.

A combination index and glycoproteomics-based approach revealed synergistic anticancer effects of curcuminoids of turmeric against prostate cancer PC3 cells.

ETHNOPHARMACOLOGICAL RELEVANCE: Herbal medicines (HMs) often exert integration effects, including synergistic, additive and antagonistic effects, in such ways that they act on multiple targets and multiple pathways on account of their multiple components. Turmeric, made from the rhizome of Curcuma longa L., is a well-known HM prescribed in the polyherbal formulas for cancer treatment in traditional Chinese medicines (TCMs). However, neither the multiple anticancer compounds of turmeric nor the integration effects of these components are fully known. AIM OF THE STUDY: This work aims to develop a systematic approach to reveal the integration effect mechanisms of multiple anticancer compounds in turmeric against prostate cancer PC3 cells. MATERIALS AND METHODS: Combination index and omics technologies were applied to profile the integration effect mechanisms of bioactive compounds in proportions naturally found in turmeric. PC3 cell line (a prostate cancer cell line) fishing and high resolution mass spectrometry were employed to screen and identify the anticancer compounds from turmeric. The combinations which contain different cell-bound compounds in natural proportions were prepared for further evaluation of anti-cancer activity by using cell viability assays, and assessment of cell apoptosis and cell cycle analysis. Combination index analysis was applied to study the integration effects of the anticancer compounds in their natural proportions. Finally, quantitative glycoproteomics/proteomics and Western blot were implemented to reveal the potential synergistic effect mechanisms of the anticancer compounds based on their natural proportions in turmeric. RESULTS: Three curcuminoids (curcumin, CUR; demethoxycurcumin, DMC; bisdemethoxycurcumin, BDMC) in turmeric were discovered and shown to possess significant synergistic anticancer activities. Combination index analysis revealed an additive effect of CUR combined with DMC or BDMC and a slight synergistic effect of DMC combined with BDMC in natural proportions in turmeric, while a combination of all three curcuminoids (CUR, DMC and BDMC) at a ratio of 1:1:1 yielded superior synergistic effects. Interestingly, the presence of BDMC and DMC are essential for synergistic effect. Glycoproteomics and proteomics demonstrated that different curcuminoids regulate various protein pathways, such as ribosome, glycolysis/gluconeogenesis, biosynthesis of amino acids, and combination of CUR + DMC + BDMC showed the most powerful effects on down-regulation of protein expression. CONCLUSIONS: Our analytical approach provides a systematic understanding of the holistic activity and integration effects of the anti-cancer compounds in turmeric and three curcuminoids of turmeric showed a synergistic effect on PC3 cells.

Modeling Study of Selenium Migration Behavior in Wet Flue Gas Desulfurization Spray Towers.

Wet flue gas desulfurization (WFGD) system is the core equipment for removing SO2 from coal-fired power plants, and it also has an important synergistic effect on the removal of selenium. However, the removal efficiency of Se across WFGD systems is not as expected, and it varies greatly in different coal-fired units (12.5-96%). In this study, a mathematical model was established to quantitatively describe the selenium migration behavior in WFGD spray towers, including the conversion of gaseous selenium to particulate selenium and the capture of gaseous SeO2 and particles by droplets. The calculation results show that the behavior of selenium in the spray tower can be divided into three stages: preparation, condensation, and removal. The condensation stage significantly affected the selenium distribution and its total removal efficiency. Furthermore, five factors which may affect the selenium behavior were investigated. Among them, the inlet particle size distribution and the droplet temperature had great impacts on the outlet selenium concentration, which may be the reason for the unstable selenium removal efficiencies. This study can help in understanding the migration process of selenium in WFGD spray towers and provide some guidance for the development of specific selenium control technologies.

Discovery and validation of peptide biomarkers for discrimination of Dendrobium species by label-free proteomics and chemometrics.

The stems of Dendrobium officinale, a well-known and expensive food material and herbal medicine in Asia, has recently suffered adulterants and counterfeits by using lower-price confusing Dendrobium species such as D. devonianum or D. transparens in the herbal market. However, robust methods that could authenticate D. officinale from its confusing species effectively are still lacking, especially for the dried samples. This study committed to discover specific peptides biomarkers for the authentication of D. officinale from the other two Dendrobium species using label-free proteomics by nanoLC LTQ Orbitrap mass spectrometry. Multivariate statistical analysis was applied to visualize the difference between the three Dendrobium species. As a result, 29 peptides among a total of 343 measurable peptides were selected to be potential biomarkers for the classification of these Dendrobium species. The validation of the representative peptide biomarkers was carried out by the synthesized peptides and 3 peptide biomarkers were found significant for the authentication of D. officinale. Further analysis showed that peptide ALGLELDLSER may also be a biomarker for the discrimination of the D. officinale originated from different geographical regions.