Search Results (15,841)

Salvia officinalis is an aromatic plant of Mediterranean origin traditionally used to treat inflammatory, cardiovascular, endocrine, and digestive diseases. In this work, the ability of the Salvia officinalis extract in the treatment of gastric ulcers was evaluated, and an innovative administration system was proposed to increase the therapeutic effect of this plant. Salvia officinalis ethanolic extract was prepared and analyzed by HPLC/UV-DAD and encapsulated in a matrix based on gelatin and pectin using an emulsion–coacervation process. The prepared microcapsules were analyzed by laser particle size, optical microscopy, in vitro dissolution kinetics, and ex vivo bioadhesion. In order to determine the action mechanism of Salvia officinalis extract, in the treatment of gastric ulcer, the in vivo anti-ulcerogenic activity in rats, using the ulcer model induced by ethanol; the in vivo anti-Helicobacter pylori activity; and in vitro inhibitory activity of H⁺/K⁺-ATPase were carried out. These three biological activities were evaluated for ethanolic extract and microcapsules to determine the effect of formulation on biological activities. Ethanolic extract of Salvia officinalis was mainly composed of polyphenols (chlorogenic acid 7.43%, rutin 21.74%, rosmarinic acid 5.88%, and quercitrin 14.39%). Microencapsulation of this extract allowed us to obtain microcapsules of 104.2 ± 7.5 µm in diameter, an encapsulation rate of 96.57 ± 3.05%, and adequate bioadhesion. The kinetics of in vitro dissolution of the extract increase significantly after its microencapsulation. Percentages of ulcer inhibition for 100 mg/kg of extract increase from 71.71 ± 2.43% to 89.67 ± 2.54% after microencapsulation. In vitro H⁺/K⁺-ATPase-inhibiting activity resulted in an IC50 of 86.08 ± 8.69 µM/h/mg protein for free extract and 57.43 ± 5.78 µM/h/mg protein for encapsulated extract. Anti-Helicobacter pylori activity showed a similar Minimum Inhibitory Concentration (MIC) of 50 µg/mL for the extract and microcapsules. Salvia officinalis ethanolic extract has a significant efficacy for the treatment of gastric ulcer; its mechanism of action is based on its gastroprotective effect, anti-Helicobacter pylori, and H⁺/K⁺-ATPase inhibitor. Moreover, the microencapsulation of this extract increases its gastroprotective and H⁺/K⁺-ATPase-inhibiting activities significantly. Full article

Extracts, fractions and the pure compound epifriedelanol of the medicinal plant Synadenium glaucescens have antibacterial properties. Herbal products are generally considered less prone to resistance development than conventional antimicrobials, as they contain multiple compounds, which makes bacteria less likely to develop resistance. However, data supporting this notion are lacking. This study evaluated the development of resistance in Staphylococcus aureus subjected to extract, fractions and epifriedelanol of S. glaucescens. It also identified S. aureus fitness genes contributing to intrinsic resistance to extract of S. glaucescens. Fluctuation and gradient concentration assays were used to determine mutation rates and growth adaptation, respectively, which were lower following exposure to growth in crude extract than the pure compound epifriedelanol. By subjecting 1920 single gene mutants from the Nebraska Transposon Mutant Library to growth in the presence of extract of S. glaucescens, 12 genes were identified as important for natural resistance in S. aureus JE2; however, only mutation in the hemB gene decreased the minimum inhibitory concentration by greater than 4-fold (64-fold). In conclusion, purifying active antimicrobial compounds from S. glaucescens and using them as antibacterial substances as an alternative to crude extract increased the risk of resistance development. Further, the gene hemBappears to have a significant role in the natural resistance to the extracts obtained from S. glaucescens in this study. Full article

Chrysanthemum has a long history of medicinal use with rich germplasm resources and extensive cultivation. Traditional chrysanthemum cultivation involves complex patterns and long flowering periods, with the ongoing expansion of planting areas complicating statistical surveys. Currently, reliable, timely, and universally applicable standardized monitoring methods for chrysanthemum cultivation areas remain underdeveloped. This research employed 16 m resolution satellite imagery spanning 2021 to 2023 alongside 2 m resolution data acquired in 2022 to quantify chrysanthemum cultivation extent across Sheyang County, Jiangsu Province, China. After evaluating multiple classifiers, Maximum Likelihood Classification was selected as the optimal method. Subsequently, time-series-based post-classification processing was implemented: initial cultivation information extraction was performed through feature comparison, supervised classification, and temporal analysis. Accuracy validation via Overall Accuracy, Kappa coefficient, Producer’s Accuracy, and User’s Accuracy identified critical issues, followed by targeted refinement of spectrally confused features to obtain precise area estimates. The chrysanthemum cultivation area in 2022 was quantified as 46,950,343 m² for 2 m resolution and 46,332,538 m² for 16 m resolution. Finally, the conversion ratio characteristics between resolutions were analyzed, yielding adjusted results of 38,466,192 m² for 2021 and 47,546,718 m² for 2023, respectively. These outcomes demonstrate strong alignment with local agricultural statistics, confirming method viability for chrysanthemum cultivation area computation. Full article

Wild edible plants, historically valued for their medicinal properties, can be a sustainable source of food, cosmetics, and pharmaceuticals. The blue berries of Prunus spinosa L., known as blackthorns, have antioxidant, astringent, and antimicrobial benefits. To preserve these properties after harvesting, understanding the best storage methods is essential. In this study, blackthorns were preserved using different methods (air-drying, freezing, or freeze-drying) to determine the optimal procedure for preserving their antioxidant activity. The fruits were extracted using a 50:50 (V/V) mixture of ethanol and water. The different extracts were phytochemically characterized for their phenolic content and antioxidant activity. The Folin–Ciocalteu test revealed total phenolic contents of 7.97 ± 0.04, 13.99 ± 0.04, and 7.39 ± 0.08 (mg GAE/g raw material) for the three types of extracts, respectively. The total flavonoid contents were 2.42 ± 0.16, 3.14 ± 0.15, and 2.32 ± 0.03 (mg QE/g raw material), respectively. In line with the polyphenol analysis, the antioxidant activity as determined by DPPH method was higher for the frozen extract, with a value of 91.78 ± 0.80%, which was confirmed by the ROS test on keratinocytes. These results show that both air-drying and freeze-drying processes negatively impact the preservation of antioxidant activity in blackthorns, suggesting that freezing may be the best preservation method before bioactive compound extraction. Full article

Accurate prediction of chlorophyll content in Brassica napus L. (rapeseed) is essential for monitoring plant nutritional status and precision agricultural management. The current study focuses on single cultivars, limiting general applicability. This study used unmanned aerial vehicle (UAV)-based RGB and multispectral imagery to evaluate six rapeseed cultivars chlorophyll content across mixed-growth stages, including seedling, bolting, and initial flowering stages. The ExG-ExR threshold segmentation was applied to remove background interference. Subsequently, color and spectral indices were extracted from segmented images and ranked according to their correlations with measured chlorophyll content. Partial Least Squares Regression (PLSR), Multiple Linear Regression (MLR), and Support Vector Regression (SVR) models were independently established using subsets of the top-ranked features. Model performance was assessed by comparing prediction accuracy (R² and RMSE). Results demonstrated significant accuracy improvements following background removal, especially for the SVR model. Compared to data without background removal, accuracy increased notably with background removal by 8.0% (R²p improved from 0.683 to 0.763) for color indices and 3.1% (R²p from 0.835 to 0.866) for spectral indices. Additionally, stepwise fusion of spectral and color indices further improved prediction accuracy. Optimal results were obtained by fusing the top seven color features ranked by correlation with chlorophyll content, achieving an R²p of 0.878 and an RMSE of 52.187 μg/g. These findings highlight the effectiveness of background removal and feature fusion in enhancing chlorophyll prediction accuracy. Full article

With increasing interest in natural therapeutic strategies for skin aging, plant-derived compounds have gained attention for their potential to protect against oxidative stress and inflammation. In this study, we investigated the anti-aging and anti-inflammatory effects of flavonoids isolated from Cercidiphyllum japonicum using a tumor necrosis factor-alpha (TNF-α)-stimulated normal human dermal fibroblast (NHDF) model. The aerial parts of C. japonicum were extracted and analyzed by high-performance liquid chromatography (HPLC), leading to the identification of four major compounds: maltol, chlorogenic acid, ellagic acid, and quercitrin. Each compound was evaluated for its antioxidant and anti-aging activities in TNF-α-stimulated NHDFs. Among them, ellagic acid exhibited the most potent biological activity and was selected for further mechanistic analysis. Ellagic acid significantly suppressed intracellular reactive oxygen species (ROS) generation and matrix metalloproteinase-1 (MMP-1) secretion (both p < 0.001), while markedly increasing type I procollagen production (p < 0.01). Mechanistic studies demonstrated that ellagic acid inhibited TNF-α-induced phosphorylation of mitogen-activated protein kinases (MAPKs), downregulated cyclooxygenase-2 (COX-2), and upregulated heme oxygenase-1 (HO-1), a key antioxidant enzyme. Additionally, ellagic acid attenuated the mRNA expression of inflammatory cytokines, including interleukin-6 (IL-6) and interleukin-8 (IL-8), indicating its broad modulatory effects on oxidative and inflammatory pathways. Collectively, these findings suggest that ellagic acid is a promising plant-derived bioactive compound with strong antioxidant and anti-inflammatory properties, offering potential as a therapeutic agent for the prevention and treatment of skin aging. Full article

Ultra-short-term PV power prediction (USTPVPP) results provide a basis for the development of intra-day rolling power generation plans. However, due to the feature information and the unpredictability of meteorology, the current ultra-short-term PV power prediction accuracy improvement still faces technical challenges. In this paper, we propose a combined prediction framework that takes into account the reconfiguration of the predictable components of PV stations and the spatiotemporal heterogeneous maps. A circuit singular spectral decomposition (CISSD) intrinsic predictable component extraction method is adopted to obtain specific frequency components in sensitive meteorological variables, a mechanism based on radiation characteristics and PV power trend predictable component extraction and reconstruction is proposed to enhance power predictability, and a spatiotemporal heterogeneous graph neural network (STHGNN) combined with a Non-stationary Transformer (Ns-Transformer) combination architecture to achieve joint prediction for different PV components. The proposed method is applied to a PV power plant in Gansu, China, and the results show that the prediction method based on the proposed combined spatio-temporal heterogeneous graph neural network model combined with the proposed predictable component extraction achieves an average reduction of 6.50% in the RMSE, an average reduction of 2.50% in the MAE, and an average improvement of 11.93% in the R² over the direct prediction method, respectively. Full article

Excessive nitrogen (N) fertilizer usage in agriculture has prompted the exploration of sustainable strategies to enhance nitrogen use efficiency (NUE) while maintaining crop yield and quality. Processed tomatoes (Solanum lycopersicum L.) were grown for two years (2023 and 2024) following a two-way factorial randomized complete block (RCBD) design, considering three biostimulants and three N regimes as two factors, to assess their morphophysiological, biochemical, anatomical and yield performances. Nitrogen application significantly influenced biomass accumulation, the leaf area index (LAI), nitrogen uptake and yield with notable comparable values between reduced and optimal nitrogen dose, indicating improved nitrogen use efficiency. Biostimulants showed limited effects alone but enhanced plant performance under reduced nitrogen conditions, particularly improving chlorophyll content, crop growth, N uptake, yield and anatomical adaptations. Moreover, compared to 2024, biostimulant application enhanced tomato growth more evidently in 2023 due to environmental variations, likely due to the occurrence of stress conditions. Importantly, biostimulants, together with N regimes, i.e., optimal and reduced doses, showed improved anatomical traits, especially regarding leaf thickness and thickness between the two epidermises, indicating adaptive responses that may support sustained productivity under N-limited conditions. Among the biostimulants used, the processed tomatoes responded better to protein hydrolysate and endophytic N-fixing bacteria than to seaweed extract. These findings suggest that although biostimulants alone were not affected, integrating them with reduced N fertilization provides a viable strategy for optimizing tomato production, conserving resources and minimizing the environmental impact without compromising yield or quality. Full article

With the growth of the plant-based food sector, increasing amounts of by-products are generated. Sea buckthorn pomace (SBP), a by-product of juice and other manufacturing products, is rich in bioactive compounds such as phenolics, oligosaccharides, proteins, and dietary fiber. The aim of the study was to evaluate the impact of modification methods, such as enzymatic hydrolysis and supercritical carbon dioxide extraction (SFE-CO₂), on the chemical composition and technological properties of SBP. SBP and SBP obtained after SFE-CO₂ (SBP-CO₂) were enzymatically modified using Pectinex^® Ultra Tropical, Viscozyme^® L, and Celluclast^® 1.5 L (Novozyme A/S, Bagsværd, Denmark). The SBP’s main constituent was insoluble dietary fiber (IDF), followed by crude proteins and lipids (respectively, 58.7, 21.1 and 12.6 g/100 in d.m.). SFE-CO₂ reduced the lipid content (by 85.7%) in the pomace while increasing protein and TDF content. Enzymatic hydrolysis decreased the content of both soluble dietary fiber (SDF) and IDF, and increased the content of mono- and oligosaccharides as well as free phenolics, depending on the commercial enzyme preparation used in SBP and SBP-CO₂ samples. Celluclast^® 1.5 L was the most effective in hydrolyzing IDF, while Viscozyme^® L and Pectinex^® Ultra Tropical were the most effective in degrading SDF. Enzymatic treatment improved water swelling capacity, water retention capacity, water solubility index, oil retention capacity of SBP and SBP-CO₂; however, it did not have a significant effect on the stability of the emulsions. Modification of SBP by SFE-CO₂ effectively increased WSC and WSI, however it reduced WRC. These findings highlight the potential of targeted modifications to enhance the nutritional and technological properties of SBP for functional food applications. Full article

Adulteration detection in medicinal plant powders remains a critical challenge in quality control. In this study, we propose a hyperspectral imaging (HSI)-based method combined with deep learning models to quantitatively analyze adulteration levels in Anoectochilus roxburghii powder. After preprocessing the spectral data using raw, first-order, and second-order Savitzky–Golay derivatives, we systematically evaluated the performance of traditional machine learning models (Random Forest, Support Vector Regression, Partial Least Squares Regression) and deep learning architectures. While traditional models achieved reasonable accuracy (R² up to 0.885), their performance was limited by feature extraction and generalization ability. A single-channel convolutional neural network (CNN) utilizing individual spectral representations improved performance marginally (maximum R² = 0.882), but still failed to fully capture the multi-scale spectral features. To overcome this, we developed a multi-channel CNN that simultaneously integrates raw, SG-1, and SG-2 spectra, effectively leveraging complementary spectral information. This architecture achieved a significantly higher prediction accuracy (R² = 0.964, MSE = 0.005), demonstrating superior robustness and generalization. The findings highlight the potential of multi-channel deep learning models in enhancing quantitative adulteration detection and ensuring the authenticity of herbal products. Full article

Ruminant livestock production plays a crucial role in the agricultural systems of Sub-Saharan Africa, significantly supporting rural livelihoods through income generation, improved nutrition, and employment opportunities. Despite its importance, the sector continues to face substantial challenges, such as low feed quality, seasonal feed shortages, and climate-related stresses, all of which limit productivity and sustainability. Considering these challenges, the adoption of natural feed additives has emerged as a promising strategy to enhance animal performance, optimise nutrient utilisation, and mitigate environmental impacts, including the reduction of enteric methane emissions. This review underscores the significant potential of natural feed additives such as plant extracts, essential oils, probiotics, and mineral-based supplements such as fossil shell flour as sustainable alternatives to conventional growth promoters in ruminant production systems across the region. All available documented evidence on the topic from 2000 to 2024 was collated and synthesised through standardised methods of systematic review protocol—PRISMA. Out of 319 research papers downloaded, six were included and analysed directly or indirectly in this study. The results show that the addition of feed additives to ruminant diets in all the studies reviewed significantly (p < 0.05) improved growth parameters such as average daily growth (ADG), feed intake, and feed conversion ratio (FCR) compared to the control group. However, no significant (p > 0.05) effect was found on cold carcass weight (CCW), meat percentage, fat percentage, bone percentage, or intramuscular fat (IMF%) compared to the control. The available evidence indicates that these additives can provide tangible benefits, including improved growth performance, better feed efficiency, enhanced immune responses, and superior meat quality, while also supporting environmental sustainability by reducing nitrogen excretion and decreasing dependence on antimicrobial agents. Full article

The induction of type I interferon (IFN) via intracellular nucleic acid sensors may be useful in preventing viral infections. However, little is known about the effect of natural plant materials on sensor responses. We previously found that cardamom (Elettaria cardamomum (L.) Maton) seed extract (CSWE) enhanced type I IFN expression and prevented influenza virus infection. In this study, we investigated the effect of CSWE on type I IFN responses using intracellular nucleic acid sensor molecules. Human lung epithelial A549 cells were treated with CSWE and transfected with poly(dA:dT) or poly(I:C) using lipofection. CSWE and 1,8-cineole, the major CSWE components, dose-dependently induced type I IFNs and IFN-stimulated genes in both poly(dA:dT)- and poly(I:C)-transfected A549 cells. The type I IFN-enhancing effect of CSWE was dependent on the stimulator of interferon genes (STING), whereas the effect of 1,8-cineole was independent of STING and mediated by the down-regulation of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)-inducible poly-ADP-ribose polymerase expression. Our study suggests that CSWE has the potential to act as a beneficial antiviral agent by enhancing homeostatic type I IFN production. Full article

Monitoring the height of secondary forest regrowth is essential for assessing ecosystem recovery, but current methods rely on field surveys, airborne or UAV LiDAR, and 3D reconstruction from high-resolution UAV imagery, which are often costly or limited by logistical constraints. Here, we address the challenge of scaling up canopy height monitoring by evaluating a recent deep learning model, trained on data from the Amazon and Atlantic Forests, developed to extract canopy height from RGB-NIR Planet NICFI imagery. The research questions are as follows: (i) How are canopy height estimates from the model affected by slope and orientation in natural forests, based on a large and well-balanced experimental design? (ii) How effectively does the model capture the growth trajectories of Pinus and Eucalyptus plantations over an eight-year period following planting? We find that the model closely tracks Pinus growth at the parcel scale, with predictions generally within one standard deviation of UAV-derived heights. For Eucalyptus, while growth is detected, the model consistently underestimates height, by more than 10 m in some cases, until late in the cycle when the canopy becomes less dense. In stable natural forests, the model reveals seasonal artifacts driven by topographic variables (slope × aspect × day of year), for which we propose strategies to reduce their influence. These results highlight the model’s potential as a cost-effective and scalable alternative to field-based and LiDAR methods, enabling broad-scale monitoring of forest regrowth and contributing to innovation in remote sensing for forest dynamics assessment. Full article

Essential oils (EOs) constitute intricate mixtures of volatile phytochemicals that have garnered significant attention due to their multifaceted biological effects. Notably, the presence of bioactive constituents capable of inhibiting tyrosinase enzyme activity and scavenging reactive oxygen species (ROS) underpins their potential utility in skin-related applications, particularly through the modulation of melanin biosynthesis and protection of skin-relevant cells from oxidative damage—a primary contributor to hyperpigmentation disorders. Zingiber officinale Rosc. (ginger) and Humulus lupulus L. (hop) are medicinal plants widely recognized for their diverse pharmacological properties. To the best of our knowledge, this study provides the first report on the synergistic interactions between essential oils derived from these species (referred to as EOZ and EOH) offering novel insights into their combined bioactivity. The purpose of this study was to evaluate essential oils extracted from ginger rhizomes and hop strobiles with respect to the following: (1) chemical composition, determined by gas chromatography–mass spectrometry (GC-MS); (2) tyrosinase inhibitory activity; (3) capacity to inhibit linoleic acid peroxidation; (4) ABTS^•+ radical scavenging potential. Furthermore, the study utilizes both the combination index (CI) and dose reduction index (DRI) as quantitative parameters to evaluate the nature of interactions and the dose-sparing efficacy of essential oil (EO) combinations. GC–MS analysis identified EOZ as a zingiberene-rich chemotype, containing abundant sesquiterpene hydrocarbons such as α-zingiberene, β-bisabolene, and α-curcumene, while EOH exhibited a caryophyllene diol/cubenol-type profile, dominated by oxygenated sesquiterpenes including β-caryophyllene-9,10-diol and 1-epi-cubenol. In vitro tests demonstrated that both oils, individually and in combination, showed notable anti-tyrosinase, radical scavenging, and lipid peroxidation inhibitory effects. These results support their multifunctional bioactivity profiles with possible relevance to skin care formulations, warranting further investigation. Full article

Natural enemies commonly probe larval bodies and frass with their antennae for prey hunting. However, the attractants to natural enemies emitted directly from hosts and host-associated tissues remained largely unknown. Here, we used two generalist noctuid species, Helicoverpa armigera (Hübner) and Spodoptera frugiperda (JE Smith), along with the larval endoparasitoid Microplitis mediator (Haliday) to address the question. Extracts of larval frass of both the noctuid species were strongly attractive to M. mediator females when hosts were fed either maize, cotton, soybean leaves, or an artificial diet without leaf tissues. By using a combination of electrophysiological measurements and behavioral tests, we found that the attractiveness of frass mainly relied on a volatile compound ethyl palmitate. The compound was likely to be a by-product of host digestion involving gut bacteria because an antibiotic supplement in diets reduced the production of the compound in frass and led to the decreased attractiveness of frass to the parasitoids. In contrast, extracts of the larval bodies of both the noctuid species appeared to be less attractive to the parasitoids than their respective fecal extracts, independently of types of food supplied to the larvae. Altogether, larval frass of the two noctuid species was likely to be more important than their bodies in attracting the endoparasitoid species, and the main attractant of frass was probably one of the common metabolites of digestion involving gut microbes, and its emission is likely to be independent of host plant species. Full article