Introduction: Rheological properties, as critical material attributes (CMAs) of solid dispersion drugs such as dripping pills, affect the melting, dispersion, and solidification. Therefore, characterization and assessments of rheological properties in the pharmaceutical process are important in enhancing drug stability and bioavailability.
Objectives: The study aimed to develop a method for analyzing the rheology of molten materials, assessing their consistency and how rheological properties affect the dripping process and pills quality.
Materials and methods: The rheological behavior of molten materials composed of Ginkgo biloba leaf extract (GBE) and polyethylene glycol (PEG) 4000 was characterized. Batch consistency of molten materials was evaluated. Image monitoring technology was utilized to capture and process images of the droplet formation process. We established the relationship between the rheological properties of molten materials and various attributes.
Results: The quality consistency of molten materials was evaluated, with 12 batches showing similarity above 0.8. The MLR models showed strong correlations (R2 > 0.80) between rheological properties and evaluation attributes. The rheological properties, including consistency coefficient, flow index, and viscosity at 80°C, were identified as critical rheological properties of the molten materials. Rheological property differences of molten materials have an impact on the morphology of droplet and quality performance.
Conclusion: A rheological method was established, enabling quality consistency evaluation of molten materials in dripping pills. This study revealed the influence of rheological properties on droplet formation process and dripping pills quality, providing a reference for researches on material attributes control of other traditional Chinese medicine dripping pills.
Introduction: Secondary metabolites in plants play a crucial role in defense mechanisms against insects, pests, and pathogens. These metabolites exhibit varying distributions within and among plant parts under different biotic and abiotic conditions. Understanding the intricate relationships between secondary metabolites and insect populations can be helpful for elucidating plant defense mechanisms and enhancing agricultural managing efficiencies.
Objective: To investigate the influence of the glucosinolate profile in the leaves of three cabbage (Brassica oleracea var. capitata L.) varieties on insect loads.
Methods: Glucosinolate profiles across different leaf positions (such as bottom, middle, and center) and leaf shapes (such as curly and non-curly leaf) of three cabbage varieties (Xiagan [XGA], Xiaguang [XGU], and Qiangxia [QIX]) were analyzed by using high-performance liquid chromatography-mass spectrometry (LC-MS). The insect loads were recorded by visually inspecting the upper and lower layers of each target leaf.
Results: Increasing concentrations of four glucosinolates, namely, glucoiberin, progoitrin, glucoraphanin, and glucobrassicin, were positively related to insect loads. While increasing concentrations of the other four glucosinolates, such as neoglucobrassicin, 4-methoxyglucobrassicin, sinigrin, and gluconapin, were negatively related to insect loads. Furthermore, both glucosinolate synthesis and insect loads were significantly higher in the curly-shaped and middle-position leaves than in the non-curly-shaped and bottom- and central-position leaves across the cabbage varieties.
Conclusion: Differences in glucosinolate profiles across leaf positions and shapes strongly influenced the insect loads of the three Brassica varieties. This link may further extend our understanding of the real defense power of a particular variety against herbivore damage.
Introduction: Qi-Fu-Yin has been used to treat Alzheimer's disease (AD) in China. Oxidative stress has been recognized as a factor in AD progress. To date, there is no quality control method to ensure batch-to-batch consistency of Qi-Fu-Yin, and the potential antioxidant compounds in Qi-Fu-Yin remain uncertain.
Objectives: The aim of this study is to identify the potential antioxidant compounds of Qi-Fu-Yin and establish quality control standards for Qi-Fu-Yin.
Methods: High-performance liquid chromatography was used to establish and quantify the fingerprints of Qi-Fu-Yin from various batches. Ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UHPLC-Q-TOF/MS) was used to identify the common peaks. Bivariate correlation analysis, partial least squares regression analysis, and gray correlation analysis were used to establish the spectrum-effect relationship.
Results: Forty-nine common peaks were determined through the establishment of fingerprints. Among them, 35 common peaks were preliminarily characterized. The multiple statistical correlation analysis methods identified six compounds as potential antioxidant constituents of Qi-Fu-Yin, and their antioxidant activities were validated in vitro. All six antioxidant compounds derived from two herbs. Therefore, three chemical index compounds derived from other three herbs were added to the quantitative analysis, while for two herbs, no peaks could be included. Eventually, six antioxidant constituents and three index compounds were quantitatively determined to provide a relatively comprehensive quality control for Qi-Fu-Yin.
Conclusions: The study elucidated the antioxidant substance basis of Qi-Fu-Yin and provided a relatively comprehensive approach for the assay of Qi-Fu-Yin, which is a promising advance in the quality control of Qi-Fu-Yin.
Introduction: The fruit wastes, in particular agricultural wastes, are considered potential and inexpensive sources of bioactive compounds.
Objective: The current study was aimed at the preparation of an optimized extract of sugarcane bagasse using microwave-assisted extraction (MAE) technology and comparative evaluation of chemical composition, antioxidant, and antidiabetic activities with extract prepared through maceration technique.
Methodology: Box-Behnken Design (BDD) with response surface methodology was applied to observe interactions of three independent variables (ethanol concentrations [%], microwave power [W], and extraction time [min]) on the dependent variables (total phenolic content [TPC] and antioxidant status via 2,2-diphenyl-1-picrylhydrazyl [DPPH] to establish optimal extraction conditions. The ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) analysis was applied for untargeted metabolite profiling, and in vitro assays were used for evaluation of the antidiabetic and antioxidant potential of the extract. Moreover, an in silico study was used to predict the interaction of five dominant compounds from the UHPLC-Q-TOF-MS profile against the dipeptidyl peptidase-IV (DPP-IV) enzyme.
Results: The optimal conditions for the extraction were established at 60% (v/v) ethanol, 500 W microwave power, and 5 min time with TPC 12.83 ± 0.66 mg GAE/g d.w. and DPPH 45.09 ± 0.07%. The UHPLC-Q-TOF-MS analysis revealed the presence of a total of 106 compounds in the extract. Moreover, the extract prepared through MAE technology presented higher TPC and DPPH findings than the extract prepared through maceration. Similarly, the extract was also found with good antidiabetic activity by inhibiting the DPP-IV enzyme which was also rectified theoretically by a molecular docking study.
Conclusion: The current study presents a sustainable and an optimized approach for the preparation of sugarcane bagasse extract with functional phytoconstituents and higher antidiabetic and antioxidant activities.
Introduction: Taxus media (Taxus × media Rehder) is renowned for its high paclitaxel content, serving as a major source for industrial paclitaxel production. In addition to paclitaxel, T. media contains a diverse range of metabolites, including flavonoids, alkaloids, and terpenoids, which have been shown to possess antioxidant, antibacterial, anti-inflammatory, and immunomodulatory effects. However, these compounds have not been thoroughly studied as key metabolites in T. media.
Objective: The untargeted metabolomics analysis of six T. media tissues provides new insights into the development and utilization of T. media metabolites.
Method: The extracts from six tissues of T. media were analyzed and subjected to analysis using high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (HPLC-Q-TOF-MS/MS) and chemometric techniques.
Results: Using a reliable HPLC-Q-TOF-MS/MS method, we identified 312 compounds in six T. media tissues, including 214 previously unreported in T. media. To identify characteristic compounds across different tissues, 34 metabolites were further screened. KEGG metabolic pathway analysis revealed that these compounds primarily occur in the metabolic pathways of terpene glycosides, flavans, and O-methylated flavonoids.
Conclusion: This study initially utilized an HPLC-QTOF-MS/MS-based metabolomics approach to assess the metabolites in different tissues of T. media, providing a basis for their utilization and management.
Introduction: Catnip (Nepeta cataria, L.) has well-documented applications in arthropod repellency because of its bioactive iridoids. Long-term stability of nepetalactones and other iridoids in N. cataria are needed to develop as effective pest repellents.
Objectives: The present work intends to measure iridoid concentration over time in biomass, plant extracts, and extract solution while identifying degradative byproducts under different storage conditions.
Methodology: Samples of desiccated biomass, ethanol extract, and extract in ethanol solution were stored in ambient light or darkness. Through UHPLC-QTOF/MS or UHPLC-QQQ/MS, the concentration of Z,E-nepetalactone, E,Z-nepetalactone, nepetalic acid, and dihydronepetalactone were examined over 2 years and statistically analyzed for determination of best storage practices. Degradation kinetics were applied to each analyte using graphical estimation. With targeted formula searching, degradative byproducts were identified and quantified.
Results: Light exposure caused significant decreases in E,Z-nepetalactone concentration in all sample types, while having no effect on Z,E-nepetalactone as it decayed more rapidly. Extract samples lost nepetalactone content faster than biomass or extract solution. Dihydronepetalactone levels were low, but never declined over 2 years. Nepetalic acid increased over some periods, depending on sample type, indicating a relationship between the acid and nepetalactone. Four degradative byproducts-nepetonic acid, dehydronepetalactone, an anhydride, and an ethanolic ester-were identified, with variable responses to light exposure.
Conclusions: Protecting catnip products from light is necessary to preserve nepetalactones, and a discernable difference in nepetalactone isomer stability was discovered. Identifying Nepeta chemotypes rich in dihydronepetalactone may provide more resilient botanicals as starting materials for processing.
Introduction: Quality evaluation of Huang-qin is significant to ensure its clinical efficacy.
Objective: This study aims to establish an accurate, rapid and comprehensive Huang-qin quality evaluation method to overcome the time-consuming and laborious shortcomings of traditional herbal medicine quality assessment methods.
Methods: The contents of baicalin, baicalein and scutellarin in Huang-qin from five different origins were analyzed by FT-IR and NIR spectra combined with multivariate data technology. The quality of Huang-qin from different origins was evaluated by TOPSIS and consistency analysis based on the content of three active ingredients. The correlation between ecological factors and the accumulation of active ingredients was explored.
Results: Satisfactory prediction results of PLS models were obtained. Relatively, the model based on FT-IR combined with the PLS regression method has higher R2 and smaller RMSE than the NIR combined with the PLS method. TOPSIS and consistency analysis results showed that the quality of Huang-qin from different geographical origins was significantly different. The results showed that the quality of Huang-qin produced in Shanxi Province was the best among the five origins studied. The results also found that the quality of Huang-qin in different growing areas of the same origin was not completely consistent. The correlation study showed that altitude, sunshine duration and rainfall were the main factors that caused the quality difference of medicinal materials in different geographical origins.
Conclusion: This study provides a reference for the rapid quantitative analysis of the active components of herbal medicine and the quality evaluation of them.
Introduction: The quality of Chinese medicine preparations can be greatly influenced by the quality of the intermediates such as extracts or concentrates. However, it is highly challenging to evaluate the quality in a rapid and non-contact manner during manufacturing. Here, we introduce an intelligent hyperspectral analysis method integrating a self-built abnormal region removal algorithm with machine learning and demonstrate its utility using the concentrate of Weifuchun (WFC), a traditional Chinese medicine preparation made from Ginseng Radix et Rhizoma Rubra, Rabdosia Amethystoides, and Aurantii Fructus.
Objective: To rapidly and non-destructively detect quality attributes of the intermediates in the manufacturing processes of Chinese medicine, an intelligent hyperspectral analysis method was developed for simultaneously quantifying the contents of naringin, neohesperidin, rosmarinic acid, and relative density of WFC concentrates.
Methodology: Samples were evenly spread on solid white flat bottom containers, which were batch placed on a horizontal sample stage. Subsequent to the acquisition of near-infrared (NIR) hyperspectral images, abnormal pixels such as large/small bubbles and fine solids were first removed according to the differential pixel values in the binary grayscale map and the Mahalanobis distance metric. Then, partial least squares (PLS) and support vector machine (SVM) algorithms were used to construct hyperspectral quantitative calibration models for quality attributes. The hyperspectral images were reconstructed based on these models to visually evaluate the quality of the concentrates during manufacturing.
Results: As a case study, quality attributes of the WFC concentrates including contents of naringin, neohesperidin, rosmarinic acid, and relative density were determined simultaneously, and coefficients of determination of these quantitative correction models were 0.900, 0.891, 0.851, and 0.920, respectively.
Conclusion: The method proposed in this study favors real-time determination of multiple attributes in viscous samples with industrial application prospects.
Introduction: The identification of active dietary flavonoids in food is promising for novel drug discovery. The active ingredients of duckweed (a widely recognized food and herb with abundant flavonoids) that are associated with acute myeloid leukemia (AML) have yet to be identified, and their underlying mechanisms have not been elucidated.
Objectives: The objective of this study was to identify novel constituents exhibiting antileukemia activity in duckweed through the integration of chemical profiling, network pharmacology, and experimental validation.
Methods: First, high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) was used to characterize the primary constituents of duckweed. Subsequently, AML cell-xenograft tumor models were used to validate the anticancer effect of duckweed extract. Furthermore, network pharmacology analysis was conducted to predict the potential active compounds and drug targets against AML. Lastly, based on these findings, two monomers (apiin and luteoloside) were selected for experimental validation.
Results: A total of 17 compounds, all of which are apigenin and luteolin derivatives, were identified in duckweed. The duckweed extract significantly inhibited AML cell growth in vivo. Furthermore, a total of 88 targets for duckweed against AML were predicted, with key targets including PTGS2, MYC, MDM2, VEGFA, CTNNB1, CASP3, EGFR, TP53, HSP90AA1, CCND1, MMP9, TNF, and MAPK1. GO and KEGG pathway enrichment analyses indicated that these targets were primarily involved in the apoptotic signaling pathway. Lastly, both apiin and luteoloside effectively induced apoptosis through CASP3 activation, and this effect could be partially reversed by a caspase inhibitor (Z-VAD).
Conclusion: Duckweed extract has an antileukemic effect, and apiin derived from duckweed shows potential as a treatment for AML.
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