Toonaones A-I, limonoids with NLRP3 inflammasome inhibitory activity from Toona ciliata M. Roem

Toonanoronoids A-E, five new limonoids from Toona ciliata var. yunnanensis

Five new B-seco-limonoids, namely toonanoronoids A-E (1-5), in conjunction with three previously reported compounds, were isolated from the EtOAc extract of the twigs and leaves of Toona ciliata var. yunnanensis. Their structures were elucidated through comprehensive spectroscopic and X-ray crystallographic analysis. The cytotoxic activities of new compounds against five human tumor cell lines (HL-60, SMMC-7721, A549, MCF-7, and SW480) were screened, Compounds 4 and 5 exerted inhibition toward two tumor cell lines (HL-60, SW-480) with IC50 values between 1.7 and 5.9 μM.

B-seco Limonoids with anti-inflammatory activity from Tetradium fraxinifolium (Hook.) T.G.Hartley

Fraxinifolines A-F (1-6), six new B-seco limonoids, together with four known A,D-di-seco ones, were isolated from the twigs with leaves of Tetradium fraxinifolium. Their structures with absolute configurations were elucidated on the basis of analysis of MS, NMR, single-crystal X-ray diffraction and biogenetic pathway. An anti-inflammatory bioassay in vitro showed limonoids 1-3 had significant immunosuppressive effect against the production of pro-inflammatory cytokines (IL-1β and/or TNF-α) in lipopolysaccharide (LPS)-stimulated RAW264.7 cells.

Callicarpanes A-L, Twelve New Clerodane Diterpenoids with NLRP3 Inflammasome Inhibitory Activity from Callicarpa integerrima

Twelve new clerodane diterpenoids named callicarpanes A-L (1-12), together with eight known compounds (13-20), were isolated from Callicarpa integerrima. Their structures were determined by comprehensive spectroscopic data. The calculated chemical shifts were used to identify relative configurations using DP4+ analysis. The absolute configurations (AC) were assigned based on quantum chemical calculations and X-ray single-crystal diffraction methods. Compounds 1, 3, 5, 9, 10, 12, 15, 16, and 19 showed significant inhibitory activity for NLRP3 inflammasome activation, with the IC₅₀ against lactate dehydrogenase (LDH) release ranging from 0.08 to 4.78 μM. Further study revealed that compound 10 repressed IL-1β secretion and caspase-1 maturation in J774A.1 cell as well as blocked macrophage pyroptosis.

Unified Total Synthesis of the Limonoid Alkaloids: Strategies for the De Novo Synthesis of Highly Substituted Pyridine Scaffolds

Highly substituted pyridine scaffolds are found in many biologically active natural products and therapeutics. Accordingly, numerous complementary de novo approaches to obtain differentially substituted pyridines have been disclosed. This article delineates the evolution of the synthetic strategies designed to assemble the demanding tetrasubstituted pyridine core present in the limonoid alkaloids isolated from Xylocarpus granatum, including xylogranatopyridine B, granatumine A and related congeners. In addition, NMR calculations suggested structural misassignment of several limonoid alkaloids, and predicted their C3-epimers as the correct structures, which was further validated unequivocally through chemical synthesis. The materials produced in this study were evaluated for cytotoxicity, anti-oxidant effects, anti-inflammatory action, PTP1B and Nlrp3 inflammasome inhibition, which led to compelling anti-inflammatory activity and anti-oxidant effects being discovered.

Research progress of meliaceous limonoids from 2011 to 2021

Covering: July 2010 to December 2021Limonoids, a kind of natural tetranortriterpenoids with diverse skeletons and valuable insecticidal and medicinal bioactivities, are the characteristic metabolites of most plants of the Meliaceae family. The chemistry and bioactivities of meliaceous limonoids are a continuing hot area of natural products research; to date, about 2700 meliaceous limonoids have been identified. In particular, more than 1600, including thirty kinds of novel rearranged skeletons, have been isolated and identified in the past decade due to their wide distribution and abundant content in Meliaceae plants and active biosynthetic pathways. In addition to the discovery of new structures, many positive medicinal bioactivities of meliaceous limonoids have been investigated, and extensive achievements regarding the chemical and biological synthesis have been made. This review summarizes the recent research progress in the discovery of new structures, medicinal and agricultural bioactivities, and chem/biosynthesis of limonoids from the plants of the Meliaceae family during the past decade, with an emphasis on the discovery of limonoids with novel skeletons, the medicinal bioactivities and mechanisms, and chemical synthesis. The structures, origins, and bioactivities of other new limonoids were provided as ESI. Studies published from July 2010 to December 2021 are reviewed, and 482 references are cited.

Non-destructive Measurements of Toona sinensis Chlorophyll and Nitrogen Content Under Drought Stress Using Near Infrared Spectroscopy

Drought is a climatic event that considerably impacts plant growth, reproduction and productivity. Toona sinensis is a tree species with high economic, edible and medicinal value, and has drought resistance. Thus, the objective of this study was to dynamically monitor the physiological indicators of T. sinensis in real time to ensure the selection of drought-resistant varieties of T. sinensis. In this study, we used near-infrared spectroscopy as a high-throughput method along with five preprocessing methods combined with four variable selection approaches to establish a cross-validated partial least squares regression model to establish the relationship between the near infrared reflectance spectroscopy (NIRS) spectrum and physiological characteristics (i.e., chlorophyll content and nitrogen content) of T. sinensis leaves. We also tested optimal model prediction for the dynamic changes in T. sinensis chlorophyll and nitrogen content under five separate watering regimes to mimic non-destructive and dynamic detection of plant leaf physiological changes. Among them, the accuracy of the chlorophyll content prediction model was as high as 72%, with root mean square error (RMSE) of 0.25, and the RPD index above 2.26. Ideal nitrogen content prediction model should have R ² of 0.63, with RMSE of 0.87, and the RPD index of 1.12. The results showed that the PLSR model has a good prediction effect. Overall, under diverse drought stress treatments, the chlorophyll content of T. sinensis leaves showed a decreasing trend over time. Furthermore, the chlorophyll content was the most stable under the 75% field capacity treatment. However, the nitrogen content of the plant leaves was found to have a different and variable trend, with the greatest drop in content under the 10% field capacity treatment. This study showed that NIRS has great potential for analyzing chlorophyll nitrogen and other elements in plant leaf tissues in non-destructive dynamic monitoring.

Estimation of Plant Height and Aboveground Biomass of Toona sinensis under Drought Stress Using RGB-D Imaging

Rapid and accurate plant growth and biomass estimation is essential for formulating and implementing targeted forest cultivation measures. In this study, RGB-D imaging technology was used to obtain the RGB and depth imaging data for a Toona sinensis seedling canopy to estimate plant growth and aboveground biomass (AGB). Three hundred T. sinensis seedlings from 20 varieties were planted under five different drought stress treatments. The U-Net model was applied first to achieve highly accurate segmentation of plants from complex backgrounds. Simple linear regression (SLR) was used for plant height prediction, and the other three models, including multivariate linear (ML), random forest (RF) and multilayer perceptron (MLP) regression, were applied to predict the AGB and compared for optimal model selection. The results showed that the SLR model yields promising and reliable results for the prediction of plant height, with R2 and RMSE values of 0.72 and 1.89 cm, respectively. All three regression methods perform well in the prediction of AGB estimation. MLP yields the highest accuracy in predicting dry and fresh aboveground biomass compared to the other two regression models, with R2 values of 0.77 and 0.83, respectively. The combination of Gray, Green minus red (GMR) and Excess green index (ExG) was identified as the key predictor by RReliefF for predicting dry AGB. GMR was the most important in predicting fresh AGB. This study demonstrated that the merits of RGB-D and machine learning models are effective phenotyping techniques for plant height and AGB prediction, and can be used to assist dynamic responses to drought stress for breeding selection.