[go: up one dir, main page]

 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (19,703)

Search Parameters:
Keywords = phenol

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
24 pages, 2212 KiB  
Review
Plant Antioxidants: Therapeutic Potential in Cardiovascular Diseases
by Hilda Aguayo-Morales, Joan Poblano, Lia Berlanga, Ileana Castillo-Tobías, Sonia Yesenia Silva-Belmares and Luis E. Cobos-Puc
Compounds 2024, 4(3), 479-502; https://doi.org/10.3390/compounds4030029 (registering DOI) - 12 Aug 2024
Abstract
Cardiovascular diseases (CVDs) are a global health problem. The mortality associated with them is one of the highest. Essentially, CVDs occur when the heart or blood vessels are damaged. Oxidative stress is an imbalance between the production of reactive oxygen species (free radicals) [...] Read more.
Cardiovascular diseases (CVDs) are a global health problem. The mortality associated with them is one of the highest. Essentially, CVDs occur when the heart or blood vessels are damaged. Oxidative stress is an imbalance between the production of reactive oxygen species (free radicals) and antioxidant defenses. Increased production of reactive oxygen species can cause cardiac and vascular injuries, leading to CVDs. Antioxidant therapy has been shown to have beneficial effects on CVDs. Plants are a rich source of bioactive antioxidants on our planet. Several classes of these compounds have been identified. Among them, carotenoids and phenolic compounds are the most potent antioxidants. This review summarizes the role of some carotenoids (a/β-carotene, lycopene and lutein), polyphenols such as phenolic acids (caffeic, p-coumaric, ferulic and chlorogenic acids), flavonoids (quercetin, kaempferol and epigallocatechin gallate), and hydroxytyrosol in mitigating CVDs by studying their biological antioxidant mechanisms. Through detailed analysis, we aim to provide a deeper understanding of how these natural compounds can be integrated into cardiovascular health strategies to help reduce the overall burden of CVD. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Schematic representation of oxygen/nitrogen free radical (ROS/RNS) generation in cardiac cells. NOX: nicotinamide adenine dinucleotide phosphate (NADPH) oxidase; NOS: nitric oxide synthase; XO: xanthine oxidase; LO: lipoxygenases; MPO: myeloperoxidase; BH<sub>4</sub>: 2-amino-6-(1,2-dihydroxypropyl)-5,6,7,8-tetrahydro-1H-pteridin-4-one; mPTP: mitochondrial permeability transition pore; H<sub>2</sub>O<sub>2</sub>: hydrogen peroxide; mtNOS: mitochondrial NOS; Mitochondrial complexes: I, II, III, IV, V.</p>
Full article ">Figure 2
<p>Types of antioxidants and their main function. When the production of these antioxidants is exceeded by the generation of free radicals, oxidative stress occurs. O<sub>2</sub><sup>−</sup>: superoxide; O<sub>2</sub><sup>−2</sup>: peroxides.</p>
Full article ">Figure 3
<p>Schematic representation of the triad involved in the progression of cardiovascular diseases. ROS: reactive oxygen species; RNS: reactive nitrogen species; LDL: low-density lipoprotein; eNOS: endothelial nitric oxide synthase; NF-κB: nuclear factor-kappa B; AP-1: activator protein-1; MAPK: mitogen-activated protein kinase; TNF-α: tumor necrosis factor-α; IL-1β: interleukin-1β; IL-6: interleukin-6.</p>
Full article ">Figure 4
<p>Chemical structure of natural antioxidants belonging to the family of carotenoids and phenolic compounds.</p>
Full article ">
17 pages, 4257 KiB  
Article
Prediction and Classification of Phenol Contents in Cnidium officinale Makino Using a Stacking Ensemble Model in Climate Change Scenarios
by Hyunjo Lee, Hyun Jung Koo, Kyeong Cheol Lee, Yoojin Song, Won-Kyun Joo and Cheol-Joo Chae
Agronomy 2024, 14(8), 1766; https://doi.org/10.3390/agronomy14081766 - 12 Aug 2024
Abstract
Recent studies have focused on using big-data-based machine learning to address the effects of climate change scenarios on the production and quality of medicinal plants. Challenges relating to data collection can hinder the analysis of key feature variables that affect the quality of [...] Read more.
Recent studies have focused on using big-data-based machine learning to address the effects of climate change scenarios on the production and quality of medicinal plants. Challenges relating to data collection can hinder the analysis of key feature variables that affect the quality of medicinal plants. In the study presented herein, we analyzed feature variables that affect the phenolic content of Korean Cnidium officinale Makino (C. officinale Makino) under different climate change scenarios. We applied different climate change scenarios based on environmental information obtained from Yeongju city, Gyeongsangbuk-do, Republic of Korea, and cultivated C. officinale Makino to collect data. The collected data included 3237, 75, and 45 records, and data augmentation was performed to address this data imbalance. We designed a function based on the DPPH value to set the phenolic content grade in C. officinale Makino and proposed a stacking ensemble model for predicting the total phenol contents and classifying the phenolic content grades. The regression model in the performance evaluation presented an improvement of 6.23–7.72% in terms of the MAPE; in comparison, the classification model demonstrated a 2.48–3.34% better performance in terms of accuracy. The classification accuracy was >0.825 when classifying phenol content grades using the predicted total phenol content values from the regression model, and the area under the curve values of the model indicated high model fitness (0.987–0.981). We plan to identify the key feature variables for the optimal cultivation of C. officinale Makino and explore the relationships among these feature variables. Full article
Show Figures

Figure 1

Figure 1
<p>Flowchart of the proposed stacking ensemble model for the prediction and classification of phenol contents in <span class="html-italic">Cnidium officinale</span> Makino.</p>
Full article ">Figure 2
<p>Comparison of the quartiles between the original and augmented data: (<b>a</b>) SSP1-2.6; (<b>b</b>) SSP3-7.0; (<b>c</b>) SSP5-8.5. Note that in each column the quartile distribution and mean of the original data appear to be similar to those of the augmented data (with an average similarity of 90%). As the data distribution by column in the augmented data is similar to that of the original data, it can be concluded that using augmented data is useful.</p>
Full article ">Figure 3
<p>Comparison of vector lengths based on the different SSP scenarios: (<b>a</b>) regression models and (<b>b</b>) classification models.</p>
Full article ">Figure 4
<p>Proposed stacking ensemble prediction and classification model. The process of the proposed model consists of the following four stages: data collection, data preprocessing, model training, and model performance evaluation results. (1) In the data collection stage, data are collected by cultivating <span class="html-italic">C. officinale</span> Makino based on different climate change scenarios. The types of data collected are shown in the upper right corner of the figure. (2) Data augmentation is performed on the collected data, and the phenol content grade is measured. To evaluate performance based on feature variables, combinations of feature variable groups are generated. (3) From nine candidate models, base and metamodels for prediction and classification are selected to consist of an ensemble model and training is conducted. The nine candidate models are shown in the middle right of the figure. (4) Lastly, the model’s performance evaluation is conducted.</p>
Full article ">Figure 5
<p>Comparison of the vector lengths of the base models: (<b>a</b>) regression models and (<b>b</b>) classification models.</p>
Full article ">Figure 6
<p>Comparison of total vector lengths for selecting the best pair of base and metamodels: (<b>a</b>) regression models and (<b>b</b>) classification models.</p>
Full article ">Figure 7
<p>Comparison of vector lengths for the regression models based on feature variable groups: (<b>a</b>) comparison of SSP vector lengths between the two regression models and (<b>b</b>) comparison of R<sup>2</sup> values between the two regression models.</p>
Full article ">Figure 8
<p>Comparison of accuracies and F1 scores for the classification models based on feature variable groups for the classification of phenol content grades using the predicted total phenol contents: (<b>a</b>) accuracy; (<b>b</b>) F1 score; (<b>c</b>) ROC curve.</p>
Full article ">Figure 9
<p>Feature importance for the ensemble regression model: (<b>a</b>) regression and (<b>b</b>) classification.</p>
Full article ">
13 pages, 4856 KiB  
Article
Steam-Assisted Synthesis of Hectorite Loaded with Fe2O3 and Its Catalytic Fenton Degradation of Phenol
by Xia Liu, Haihui Xu, Xing Fu and Jinyang Chen
Catalysts 2024, 14(8), 521; https://doi.org/10.3390/catal14080521 - 12 Aug 2024
Abstract
Fe2O3 loaded in the interlayer of hectorite was synthesized using a steam-assisted one-pot method to replace the traditional high-temperature and high-pressure hydrothermal method. The samples were characterized by means of X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, scanning electron [...] Read more.
Fe2O3 loaded in the interlayer of hectorite was synthesized using a steam-assisted one-pot method to replace the traditional high-temperature and high-pressure hydrothermal method. The samples were characterized by means of X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), and N2 adsorption–desorption isotherms. Fe2O3/hectorite had a layered hectorite structure. Due to the insertion of Fe2O3, the interlayer spacing increased and had a large specific surface area and pore size, benefiting catalytic reactions. Fe2O3/hectorite was used as a catalyst to degrade phenol in wastewater via the Fenton reaction. With this catalyst, the optimal Fenton reaction conditions were determined with an orthogonal test: pH, 3; temperature, 60 °C; and catalyst dosage, 0.5 g dm−3. Under these optimal reaction conditions, the degradation rate of phenol (200 mg dm–3) was 99.27% in 3 h. After five cycles, the degradation rate reached 95.72%, indicating the excellent reusability of this catalyst. In the temperature range 303–330 K, the catalytic degradation kinetics were studied as a pseudo-first-order reaction, and the apparent activation energy was 30.71 kJ/mol. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic diagram of the interlayer components in hectorite.</p>
Full article ">Figure 2
<p>XRD patterns of hectorite and Fe<sub>2</sub>O<sub>3</sub>/hectorite.</p>
Full article ">Figure 3
<p>FTIR spectra of hectorite and Fe<sub>2</sub>O<sub>3</sub>/hectorite.</p>
Full article ">Figure 4
<p>SEM of hectorite and Fe<sub>2</sub>O<sub>3</sub>/hectorite: (<b>a</b>,<b>b</b>): hectorite; (<b>c</b>,<b>d</b>): Fe<sub>2</sub>O<sub>3</sub>/hectorite.</p>
Full article ">Figure 5
<p>Nitrogen adsorption–desorption isotherms: (<b>a</b>) hectorite and (<b>b</b>) Fe<sub>2</sub>O<sub>3</sub>/hectorite.</p>
Full article ">Figure 6
<p>DG of phenol at different temperatures (catalyst dosage, 0.5 g dm<sup>−3</sup>; pH 3.0, phenol, 200 mg dm<sup>−3</sup>; H<sub>2</sub>O<sub>2</sub>, 0.15 wt.%).</p>
Full article ">Figure 7
<p>Relationship between degradation constants and temperature.</p>
Full article ">Figure 8
<p>Schematic diagram of the synthesis process.</p>
Full article ">
23 pages, 5735 KiB  
Article
UV-B Stress-Triggered Amino Acid Reprogramming and ABA-Mediated Hormonal Crosstalk in Rhododendron chrysanthum Pall.
by Wang Yu, Xiangru Zhou, Hongwei Xu and Xiaofu Zhou
Plants 2024, 13(16), 2232; https://doi.org/10.3390/plants13162232 - 12 Aug 2024
Abstract
Increased UV-B radiation due to ozone depletion adversely affects plants. This study focused on the metabolite dynamics of Rhododendron chrysanthum Pall. (R. chrysanthum) and the role of ABA in mitigating UV-B stress. Chlorophyll fluorescence metrics indicated that both JA and ABA [...] Read more.
Increased UV-B radiation due to ozone depletion adversely affects plants. This study focused on the metabolite dynamics of Rhododendron chrysanthum Pall. (R. chrysanthum) and the role of ABA in mitigating UV-B stress. Chlorophyll fluorescence metrics indicated that both JA and ABA increased UV-B resistance; however, the effect of JA was not as strong as that of ABA. Metabolomic analysis using UPLC−MS/MS (ultra-performance liquid chromatography and tandem mass spectrometry) revealed significant fluctuations in metabolites under UV-B and ABA application. UV-B decreased amino acids and increased phenolics, suggesting antioxidant defense activation. ABA treatment upregulated lipids and phenolic acids, highlighting its protective role. Multivariate analysis showed distinct metabolic clusters and pathways responding to UV-B and ABA, which impacted amino acid metabolism and hormone signal transduction. Exogenous ABA negatively regulated the JA signaling pathway in UV-B-exposed R. chrysanthum, as shown by KEGG enrichment. This study deepens understanding of plant stress-tolerance mechanisms and has implications for enhancing plant stress tolerance through metabolic and hormonal interventions. Full article
(This article belongs to the Special Issue The Physiology of Abiotic Stress in Plants)
Show Figures

Figure 1

Figure 1
<p>The chlorophyll fluorescence characteristics of the experimental materials altered in accordance with UV-B light and exogenous hormones (100 μmol/L). (<b>a</b>,<b>b</b>) ETR and NPQ foldplots of <span class="html-italic">R. chrysanthum</span>. The PAR (photosynthetic active radiation) treatment group was used as a negative control to show the status of chlorophyll fluorescence parameters of <span class="html-italic">R. chrysanthum</span> in the absence of UV-B radiation. Data were analyzed by Origin 2021. (<b>c</b>) Histogram of various photosynthetic parameters of <span class="html-italic">R. chrysanthum</span>. The heights of the bars depict the means of three biological duplicate experiments (<span class="html-italic">n</span> = 3), while the error bars depict the standard deviations of the samples. Different letter markers indicate significant differences across data groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 1 Cont.
<p>The chlorophyll fluorescence characteristics of the experimental materials altered in accordance with UV-B light and exogenous hormones (100 μmol/L). (<b>a</b>,<b>b</b>) ETR and NPQ foldplots of <span class="html-italic">R. chrysanthum</span>. The PAR (photosynthetic active radiation) treatment group was used as a negative control to show the status of chlorophyll fluorescence parameters of <span class="html-italic">R. chrysanthum</span> in the absence of UV-B radiation. Data were analyzed by Origin 2021. (<b>c</b>) Histogram of various photosynthetic parameters of <span class="html-italic">R. chrysanthum</span>. The heights of the bars depict the means of three biological duplicate experiments (<span class="html-italic">n</span> = 3), while the error bars depict the standard deviations of the samples. Different letter markers indicate significant differences across data groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 2
<p>Exogenous ABA altered the levels of JA and its products in UV-B-treated experimental materials. (<b>a</b>) Histogram of JA content. (<b>b</b>) Histogram of JA-Val content. The heights of the bars depict the means of three biological duplicate experiments (<span class="html-italic">n</span> = 3), while the error bars depict the standard deviations of the samples. Different letter marks indicate significant differences across data groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 3
<p>Metabolomic analysis of <span class="html-italic">R. chrysanthum</span> under UV-B stress. (<b>a</b>) Statistics on the quantities of different types of primary and secondary metabolites. Data were analyzed by Origin 2021. (<b>b</b>) Orthogonal partial least-squares discriminant analysis (OPLS-DA) of each sample after UV-B radiation treatment. OPLS-DA was centered after log2 transformation of the raw data. Analyses were performed using the MetaboAnalystR package OPLSR and the Anal function in R software (1.0.1). (<b>c</b>) Pearson’s correlation coefficients (PCCs) between the quality control samples (QCs) and each sample. The Pearson’s correlation coefficients were calculated using the inbuilt cor function in R software.</p>
Full article ">Figure 4
<p>Analysis of DMs in <span class="html-italic">R. chrysanthum</span> under UV-B radiation and exogenous ABA treatment. (<b>a</b>) Statistics on the upregulation and downregulation of primary and secondary differential metabolites produced by UV-B treatment. Plotted by chiplot (<a href="http://www.chiplot.online" target="_blank">www.chiplot.online</a> (accessed on 21 September 2023)), a free online data analysis website. (<b>b</b>) Heatmap of clustering composed of differential metabolites produced by UV-B treatment. The horizontal coordinate is the name of the sample, the vertical coordinate is the first-level classification of the differential metabolite, the different colors represent the different values obtained from the standardization of the different relative contents (red for high content, green for low content), “Group” refers to the grouping, and “Class” refers to the first-level classification of the substance. The clustered heatmaps applied UV (unit variance scaling) processing for the raw relative contents of the differential metabolites by rows, and these were graphically plotted via Metware Cloud (<a href="https://cloud.metware.cn" target="_blank">https://cloud.metware.cn</a> (accessed on 23 October 2023)), a free online data analysis platform. (<b>c</b>) Statistics on the upregulation and downregulation of primary and secondary differential metabolites produced by exogenous ABA treatment. (<b>d</b>) Heatmap of clustering composed of differential metabolites produced by ABA treatment.</p>
Full article ">Figure 4 Cont.
<p>Analysis of DMs in <span class="html-italic">R. chrysanthum</span> under UV-B radiation and exogenous ABA treatment. (<b>a</b>) Statistics on the upregulation and downregulation of primary and secondary differential metabolites produced by UV-B treatment. Plotted by chiplot (<a href="http://www.chiplot.online" target="_blank">www.chiplot.online</a> (accessed on 21 September 2023)), a free online data analysis website. (<b>b</b>) Heatmap of clustering composed of differential metabolites produced by UV-B treatment. The horizontal coordinate is the name of the sample, the vertical coordinate is the first-level classification of the differential metabolite, the different colors represent the different values obtained from the standardization of the different relative contents (red for high content, green for low content), “Group” refers to the grouping, and “Class” refers to the first-level classification of the substance. The clustered heatmaps applied UV (unit variance scaling) processing for the raw relative contents of the differential metabolites by rows, and these were graphically plotted via Metware Cloud (<a href="https://cloud.metware.cn" target="_blank">https://cloud.metware.cn</a> (accessed on 23 October 2023)), a free online data analysis platform. (<b>c</b>) Statistics on the upregulation and downregulation of primary and secondary differential metabolites produced by exogenous ABA treatment. (<b>d</b>) Heatmap of clustering composed of differential metabolites produced by ABA treatment.</p>
Full article ">Figure 5
<p>Multivariate analysis of DMs in <span class="html-italic">R. chrysanthum</span> under UV-B stress and exogenous ABA. (<b>a</b>) The radar image shows the top 15 DMs screened based on VIP values under UV-B stress and exogenous ABA treatment. Data were analyzed by Origin 2021. (<b>b</b>) Primary and secondary main contributing metabolites. The horizontal lines at the top and bottom of the box plots represent the maximum and minimum values, respectively, and the horizontal lines inside the boxes represent the median. Graphing by Metware Cloud (<a href="https://cloud.metware.cn" target="_blank">https://cloud.metware.cn</a> (accessed on 18 October 2023)), a free online data analysis platform.</p>
Full article ">Figure 5 Cont.
<p>Multivariate analysis of DMs in <span class="html-italic">R. chrysanthum</span> under UV-B stress and exogenous ABA. (<b>a</b>) The radar image shows the top 15 DMs screened based on VIP values under UV-B stress and exogenous ABA treatment. Data were analyzed by Origin 2021. (<b>b</b>) Primary and secondary main contributing metabolites. The horizontal lines at the top and bottom of the box plots represent the maximum and minimum values, respectively, and the horizontal lines inside the boxes represent the median. Graphing by Metware Cloud (<a href="https://cloud.metware.cn" target="_blank">https://cloud.metware.cn</a> (accessed on 18 October 2023)), a free online data analysis platform.</p>
Full article ">Figure 6
<p>(<b>a</b>) Differential abundance (DA) of DMs treated by UV-B. (<b>b</b>) Differential abundance (DA) of DMs treated by ABA. The horizontal coordinates represent the differential abundance scores, which were calculated as the ratio of the difference between upregulated and downregulated metabolites involved in the pathway to the number of all metabolites involved in the pathway. The length of the line segments represents the absolute value of the DA score, the size of the dot at the end of the line segments represents the number of differential metabolites in the pathway, and the color of the line segments and dots reflects the <span class="html-italic">p</span>-value size (the closer it is to red, the smaller the <span class="html-italic">p</span>-value, and the closer it is to purple, the larger the <span class="html-italic">p</span>-value). Graphing by Metware Cloud (<a href="https://cloud.metware.cn" target="_blank">https://cloud.metware.cn</a> (accessed on 6 May 2023)), a free online data analysis platform.</p>
Full article ">Figure 6 Cont.
<p>(<b>a</b>) Differential abundance (DA) of DMs treated by UV-B. (<b>b</b>) Differential abundance (DA) of DMs treated by ABA. The horizontal coordinates represent the differential abundance scores, which were calculated as the ratio of the difference between upregulated and downregulated metabolites involved in the pathway to the number of all metabolites involved in the pathway. The length of the line segments represents the absolute value of the DA score, the size of the dot at the end of the line segments represents the number of differential metabolites in the pathway, and the color of the line segments and dots reflects the <span class="html-italic">p</span>-value size (the closer it is to red, the smaller the <span class="html-italic">p</span>-value, and the closer it is to purple, the larger the <span class="html-italic">p</span>-value). Graphing by Metware Cloud (<a href="https://cloud.metware.cn" target="_blank">https://cloud.metware.cn</a> (accessed on 6 May 2023)), a free online data analysis platform.</p>
Full article ">Figure 7
<p>UV-B-induced metabolic pathway rearrangement network in <span class="html-italic">R. Chrysanthum</span>. (<b>a</b>) Simplified modeling of amino acid-related metabolic pathways exposed to UV-B radiation. The contents of the involved metabolites are presented as heatmaps after data normalization, where the red and green arrows on the left side of the heatmaps positively represent increases and decreases in metabolite contents after UV-B radiation, respectively, and “*” indicates that the relevant metabolites changed significantly. The three adjacent squares in the left half of the heatmaps represent the expression of each metabolite from three replicate experiments (<span class="html-italic">n</span> = 3) in group M, and the three adjacent squares in the right half of the heatmaps represent the expression of each metabolite from three replicate experiments in group N. (<b>b</b>) Simplified modeling of JA production and signaling pathways following exogenous ABA treatment. The three adjacent squares in the left half of the heatmaps represent the expression of each metabolite from three replicate experiments (<span class="html-italic">n</span> = 3) in group N, and the three adjacent squares in the right half of the heatmaps represent the expression of each metabolite from three replicate experiments in group Q. The heights of the bars in the graph depict the means of the three biological duplicate experiments (<span class="html-italic">n</span> = 3), while the error bars depict the standard deviations of the samples. Different letter markers indicate significant differences across data groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 7 Cont.
<p>UV-B-induced metabolic pathway rearrangement network in <span class="html-italic">R. Chrysanthum</span>. (<b>a</b>) Simplified modeling of amino acid-related metabolic pathways exposed to UV-B radiation. The contents of the involved metabolites are presented as heatmaps after data normalization, where the red and green arrows on the left side of the heatmaps positively represent increases and decreases in metabolite contents after UV-B radiation, respectively, and “*” indicates that the relevant metabolites changed significantly. The three adjacent squares in the left half of the heatmaps represent the expression of each metabolite from three replicate experiments (<span class="html-italic">n</span> = 3) in group M, and the three adjacent squares in the right half of the heatmaps represent the expression of each metabolite from three replicate experiments in group N. (<b>b</b>) Simplified modeling of JA production and signaling pathways following exogenous ABA treatment. The three adjacent squares in the left half of the heatmaps represent the expression of each metabolite from three replicate experiments (<span class="html-italic">n</span> = 3) in group N, and the three adjacent squares in the right half of the heatmaps represent the expression of each metabolite from three replicate experiments in group Q. The heights of the bars in the graph depict the means of the three biological duplicate experiments (<span class="html-italic">n</span> = 3), while the error bars depict the standard deviations of the samples. Different letter markers indicate significant differences across data groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 8
<p>Simplified model of the experimental treatment of <span class="html-italic">R. chrysanthum</span>.</p>
Full article ">
14 pages, 4064 KiB  
Article
Encapsulation of Pink Pepper Essential Oil (Schinus terebinthifolius Raddi) in Albumin and Low-Methoxyl Amidated Pectin Cryogels
by Ana María Chaux-Gutiérrez, Ezequiel José Pérez-Monterroza, Marília Gonçalves Cattelan, Vânia Regina Nicoletti and Márcia Regina de Moura
Processes 2024, 12(8), 1681; https://doi.org/10.3390/pr12081681 - 12 Aug 2024
Viewed by 101
Abstract
This study evaluated cryogels from albumin (ALB) and albumin–pectin (ALB:PEC) as carriers for pink pepper (Schinus terebinthifolius Raddi) essential oil. Cryogels were evaluated through infrared spectrophotometry, X-ray diffraction, scanning electron microscopy, thermogravimetric analysis, and differential scanning calorimetry. The bioactivity of the cryogels [...] Read more.
This study evaluated cryogels from albumin (ALB) and albumin–pectin (ALB:PEC) as carriers for pink pepper (Schinus terebinthifolius Raddi) essential oil. Cryogels were evaluated through infrared spectrophotometry, X-ray diffraction, scanning electron microscopy, thermogravimetric analysis, and differential scanning calorimetry. The bioactivity of the cryogels was analyzed by measuring their encapsulation efficiency (EE%), the antimicrobial activity of the encapsulated oil against S. aureus, E. coli, and B. cereus using the agar diffusion method; total phenolic content and antioxidant activity were analyzed by UV-vis spectrophotometry. The EE% varied between 59.61% and 77.41%. The cryogel with only ALB had the highest total phenolic content with 2.802 mg GAE/g, while the cryogel with the 30:70 ratio (ALB:PEC) presented a value of 0.822 mg GAE/g. A higher proportion of PEC resulted in a more significant inhibitory activity against S. aureus, reaching an inhibition zone of 18.67 mm. The cryogels with ALB and 70:30 ratio (ALB:PEC) presented fusion endotherms at 137.16 °C and 134.15 °C, respectively, and semicrystalline structures. The interaction between ALB and PEC increased with their concentration, as evidenced by the decreased intensity of the O-H stretching peak, leading to lower encapsulation efficiency. The cryogels obtained can be considered a suitable matrix for encapsulating pink pepper oil. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic diagram for the preparation of ALB and ALB:PEC cryogels.</p>
Full article ">Figure 2
<p>Inhibitory activity assay agar disk diffusion of pink pepper essential oil encapsulated in ALB (<b>a</b>), 70:30 ALB:PEC (<b>b</b>), 50:50 ALB:PEC (<b>c</b>), and 30:70 (<b>d</b>) cryogels against <span class="html-italic">S. aureus</span> (ATCC 6538).</p>
Full article ">Figure 3
<p>Infrared spectra of albumin (ALB) and albumin:pectin (ALB:PEC) cryogels with and without pink pepper essential oil encapsulated.</p>
Full article ">Figure 4
<p>X-ray diffraction patterns of albumin (ALB) (<b>a</b>), 70:30 (ALB:PEC) (<b>b</b>), 50:50 (ALB:PEC) (<b>c</b>), and 30:70 (ALB:PEC) (<b>d</b>) cryogels with pink pepper essential oil encapsulated, albumin pure (<b>e</b>), and amidated low methoxyl pectin (PEC) pure (<b>f</b>).</p>
Full article ">Figure 5
<p>TGA curves (<b>a</b>) and DTG (<b>b</b>) of ALB and ALB:PEC cryogels with pink pepper essential oil encapsulated and thermogram DSC of ALB cryogel (<b>c</b>), and 70:30 (ALB:PEC) (<b>d</b>), 50:50 (ALB:PEC) (<b>e</b>), and 30:70 (ALB:PEC) (<b>f</b>) cryogels with pink pepper essential oil encapsulated.</p>
Full article ">Figure 6
<p>SEM micrographs of ALB (<b>a</b>), 70:30 ALB:PEC (<b>b</b>), 50:50 ALB:PEC (<b>c</b>), and 30:70 ALB:PEC (<b>d</b>) (magnification 150× (<b>1</b>), 400× (<b>2</b>), 1000× (<b>3</b>), and 2500× (<b>4</b>)).</p>
Full article ">
13 pages, 3469 KiB  
Article
Comparative Analysis of Phytochemical Composition and Antioxidant Properties of Smilax china Rhizome from Different Regions
by Chang-Dae Lee, Neil Patrick Uy, Yunji Lee, Dong-Ha Lee and Sanghyun Lee
Horticulturae 2024, 10(8), 850; https://doi.org/10.3390/horticulturae10080850 (registering DOI) - 12 Aug 2024
Viewed by 85
Abstract
This study aimed to investigate variations in the phytochemical compound contents and antioxidant potential of the ethanol rhizome extracts of Smilax china L., belonging to the Liliaceae family, from different parts of Korea, namely Uiwang (Mt. Gamnamugol), Gyeonggi Province (SC1); Geochang, Gyeongnam Province [...] Read more.
This study aimed to investigate variations in the phytochemical compound contents and antioxidant potential of the ethanol rhizome extracts of Smilax china L., belonging to the Liliaceae family, from different parts of Korea, namely Uiwang (Mt. Gamnamugol), Gyeonggi Province (SC1); Geochang, Gyeongnam Province (SC2); Yeongwol, Gangwon Province (SC3); and Chungju, Chungbuk Province (SC4). The phenolic and flavonoid contents, radical scavenging activity, and proximate composition of the ethanol extracts from the rhizome samples were determined. The total polyphenol content (TPC) of the extracts ranged between 13.6 and 67.5 mg tannic acid equivalent/g. TPC analysis showed that TPC was higher in SC2 than in SC3, SC4, or SC1. Among the rhizome samples, the SC3 rhizomes had the highest total flavonoid content (TFC) (5.2 mg quercetin equivalents/g). Additionally, SC2 showed the highest radical scavenging activity against DPPH and ABTS+ radicals. Chemical characterization using UPLC/UV revealed that the extracts contained compounds such as apiin, kaempferol-3-rutinoside, and chlorogenic acid. Specifically, in SC2, chlorogenic acid was the dominant compound, which supported the levels observed in the UPLC/UV and HPLC/ELSD investigations. Dioscin, another phytochemical, was detected in SC2, SC3, and SC4, indicating the diversity of compounds among the rhizome extracts. Variations in the phytochemical content and antioxidant activity were observed in the extracts from the different regions, underlining the role of geographical variation in the functional characteristics of S. china. The observed differences could have important implications for the medicinal use of S. china extracts in applications such as anti-inflammatory treatments, diabetes management, and potential anticancer therapies. This study underscores the critical need to consider geographical origin when sourcing and utilizing S. china for therapeutic purposes, as it may significantly impact its bioactive profile and efficacy. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Geographic locations of <span class="html-italic">S. china</span> rhizome sample collection sites.</p>
Full article ">Figure 2
<p>Chemical structures of chlorogenic acid (<b>1</b>), apiin (<b>2</b>), afzelin (<b>3</b>), naringenin (<b>4</b>), and dioscin (<b>5</b>).</p>
Full article ">Figure 2 Cont.
<p>Chemical structures of chlorogenic acid (<b>1</b>), apiin (<b>2</b>), afzelin (<b>3</b>), naringenin (<b>4</b>), and dioscin (<b>5</b>).</p>
Full article ">Figure 3
<p>Results of the (<b>a</b>) TPC and (<b>b</b>) TFC analyses (<b>c</b>) DPPH, and (<b>d</b>) ABTS<sup>+</sup> assays. Each bar presents the mean ± SD. <sup>a–c</sup> indicates significant differences at <span class="html-italic">p</span> &lt; 0.0001. Ascorbic acid (AA) was used as the positive control.</p>
Full article ">Figure 4
<p>UPLC/UV chromatograms of four <span class="html-italic">S. china</span> rhizome samples: (<b>a</b>) SC1; (<b>b</b>) SC2; (<b>c</b>) SC3; (<b>d</b>) SC4. (<b>1</b>: chlorogenic acid, <b>2</b>: apiin, <b>3</b>: afzelin, <b>4</b>: naringenin).</p>
Full article ">Figure 4 Cont.
<p>UPLC/UV chromatograms of four <span class="html-italic">S. china</span> rhizome samples: (<b>a</b>) SC1; (<b>b</b>) SC2; (<b>c</b>) SC3; (<b>d</b>) SC4. (<b>1</b>: chlorogenic acid, <b>2</b>: apiin, <b>3</b>: afzelin, <b>4</b>: naringenin).</p>
Full article ">Figure 5
<p>Pearson’s correlation coefficient network (<span class="html-italic">r</span> ≥│1.00│) among the response variables in phytochemical concentrations and antioxidant activities measures in <span class="html-italic">S. china</span> rhizomes. The red and blue lines indicate the positive and negative correlation coefficients between variables, respectively.</p>
Full article ">Figure 6
<p>HPLC/ELSD chromatograms of four <span class="html-italic">S. china</span> rhizome samples: (<b>a</b>) SC1; (<b>b</b>) SC2; (<b>c</b>) SC3; (<b>d</b>) SC4. (<b>5</b>: dioscin).</p>
Full article ">
13 pages, 11706 KiB  
Article
Chemical Profile and Potential Applications of Sclerocarya birrea (A.Rich.) Hochst. subsp. caffra (Sond.) Kokwaro Kernel Oils: Analysis of Volatile Compounds and Fatty Acids
by Callistus Bvenura and Learnmore Kambizi
Molecules 2024, 29(16), 3815; https://doi.org/10.3390/molecules29163815 - 11 Aug 2024
Viewed by 327
Abstract
Sclerocarya birrea kernel volatile compounds and fatty acid methyl esters (FAMEs) from the Bubi district in Matabeleland North province of Zimbabwe were characterised by GC–MS. The volatile compounds of the oil include 65 different compounds from 24 distinct classes, dominated by 13 alcohols [...] Read more.
Sclerocarya birrea kernel volatile compounds and fatty acid methyl esters (FAMEs) from the Bubi district in Matabeleland North province of Zimbabwe were characterised by GC–MS. The volatile compounds of the oil include 65 different compounds from 24 distinct classes, dominated by 13 alcohols and 14 aldehydes (42%). Other classes include carboxylic acids, phenols, sesquiterpenes, lactones, pyridines, saturated fatty acids, ketones, and various hydrocarbons. The kernel oils revealed essential fatty acids such as polyunsaturated (α-linolenic and linoleic acids) and monounsaturated fatty acids (palmitic, palmitoleic, and oleic acids). Notably, oleic acid is the predominant fatty acid at 521.61 mg/g, constituting approximately 73% of the total fatty acids. Linoleic acid makes up 8%, and saturated fatty acids make up about 7%, including significant amounts of stearic (42.45 mg/g) and arachidic (3.46 mg/g) acids. These results validate the use of marula oils in food, pharmaceutical, and health industries, as well as in the multibillion USD cosmetics industry. Therefore, the potential applications of S. berria kernel oils are extensive, necessitating further research and exploration to fully unlock their capabilities. Full article
(This article belongs to the Special Issue Functional Evaluation of Bioactive Compounds from Natural Sources)
26 pages, 3918 KiB  
Article
Recovery of Scots Pine Seedlings from Long-Term Zinc Toxicity
by Yury V. Ivanov, Alexandra I. Ivanova, Alexander V. Kartashov and Vladimir V. Kuznetsov
Plants 2024, 13(16), 2227; https://doi.org/10.3390/plants13162227 - 11 Aug 2024
Viewed by 190
Abstract
We studied the recovery of the growth and physiological parameters of Scots pine seedlings after long-term zinc toxicity. The removal of excess zinc from the nutrient solution resulted in the rapid recovery of primary root growth but did not promote the initiation and [...] Read more.
We studied the recovery of the growth and physiological parameters of Scots pine seedlings after long-term zinc toxicity. The removal of excess zinc from the nutrient solution resulted in the rapid recovery of primary root growth but did not promote the initiation and growth of lateral roots. The recovery of root growth was accompanied by the rapid uptake of manganese, magnesium, and copper. Despite the maximum rate of manganese uptake by the roots, the manganese content in the needles of the recovering plants did not reach control values during the 28 days of the experiment, unlike magnesium, iron, and copper. In general, the recovery of ion homeostasis eliminated all of the negative effects on the photosynthetic pigment content in the needles. However, these changes, along with recovery of the water content in the needles, were not accompanied by an increase in the weight gain of the recovering seedlings compared with that of the Zn-stressed seedlings. The increased accumulation of phenolic compounds in the needles persisted for a long period after excess zinc was removed from the nutrient solution. The decreased lignin content in the roots and needles is a characteristic feature of Zn-stressed plants. Moreover, the removal of excess zinc from the nutrient solution did not lead to an increase in the lignin content in the organs. Full article
Show Figures

Figure 1

Figure 1
<p>The development of Scots pine seedlings throughout the experiment: (<b>a</b>) fresh weight; (<b>b</b>) dry weight; and (<b>c</b>) water content. Pairwise comparisons of the means with controls at corresponding time points were performed using the Student’s <span class="html-italic">t</span>-test for normally distributed data (significant differences at <span class="html-italic">p</span> &lt; 0.05 denoted by asterisks (*)) or the Mann–Whitney rank sum test when the <span class="html-italic">t</span>-test was not applicable (significant differences at <span class="html-italic">p</span> &lt; 0.05 denoted by multiplication symbols (×)). The significance of the variant (V), sampling time (T), and variant × time (V × T) interactions were calculated using 2-way ANOVA (<span class="html-italic">p</span> &lt; 0.05), with a circle (•) indicating a significant difference and “ns” indicating no significant difference.</p>
Full article ">Figure 2
<p>The development of the root system of Scots pine seedlings throughout the experiment: (<b>a</b>) primary root length; (<b>b</b>) number of first-order lateral roots; (<b>c</b>) distance from the tip of the primary root to the first lateral root; and (<b>d</b>) number of second-order lateral roots. Pairwise comparisons of the means with controls at corresponding time points were performed using the Student’s <span class="html-italic">t</span>-test for normally distributed data (significant differences at <span class="html-italic">p</span> &lt; 0.05 denoted by asterisks (*)) or the Mann–Whitney rank sum test when the <span class="html-italic">t</span>-test was not applicable (significant differences at <span class="html-italic">p</span> &lt; 0.05 denoted by multiplication symbols (×)). The significance of the variant (V), sampling time (T), and variant × time (V × T) interactions were calculated using 2-way ANOVA (<span class="html-italic">p</span> &lt; 0.05), with a circle (•) indicating a significant difference.</p>
Full article ">Figure 3
<p>The growth of the above-ground organs of Scots pine seedlings throughout the experiment: (<b>a</b>) hypocotyl diameter; (<b>b</b>) epicotyl length; and (<b>c</b>) number of needles. Pairwise comparisons of the means with controls at corresponding time points were performed using the Student’s <span class="html-italic">t</span>-test for normally distributed data (significant differences at <span class="html-italic">p</span> &lt; 0.05 denoted by asterisks (*)) or the Mann–Whitney rank sum test when the <span class="html-italic">t</span>-test was not applicable (significant differences at <span class="html-italic">p</span> &lt; 0.05 denoted by multiplication symbols (×)). The significance of the variant (V), sampling time (T), and variant × time (V × T) interactions were calculated using 2-way ANOVA (<span class="html-italic">p</span> &lt; 0.05), with a circle (•) indicating a significant difference and “ns” indicating no significant difference.</p>
Full article ">Figure 4
<p>The nutrient contents: (<b>a</b>,<b>b</b>) Zn; (<b>c</b>,<b>d</b>) Mg; (<b>e</b>,<b>f</b>) Fe; (<b>g</b>,<b>h</b>) Mn; and (<b>i</b>,<b>j</b>) Cu in the roots (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>,<b>i</b>) and needles (<b>b</b>,<b>d</b>,<b>f</b>,<b>h</b>,<b>j</b>) of Scots pine seedlings throughout the experiment. Pairwise comparisons of the means with controls at corresponding time points were performed using the Student’s <span class="html-italic">t</span>-test for normally distributed data (significant differences at <span class="html-italic">p</span> &lt; 0.05 denoted by asterisks (*)) or the Mann–Whitney rank sum test when the <span class="html-italic">t</span>-test was not applicable (significant differences at <span class="html-italic">p</span> &lt; 0.05 denoted by multiplication symbols (×)).</p>
Full article ">Figure 5
<p>Heatmap analysis of low-molecular-weight antioxidant and lignin contents in the roots and needles of Scots pine seedlings during the experiment. The value of a given parameter in the control plants at the initial point was taken as 1.0 (white); the relative increase is indicated in green, and the relative decrease is indicated in red. Pairwise comparisons of the means with controls at corresponding time points were performed using the Student’s <span class="html-italic">t</span>-test for normally distributed data (significant differences at <span class="html-italic">p</span> &lt; 0.05 denoted by asterisks (*)) or the Mann–Whitney rank sum test when the <span class="html-italic">t</span>-test was not applicable (significant differences at <span class="html-italic">p</span> &lt; 0.05 denoted by multiplication symbols (×)).</p>
Full article ">Figure 6
<p>Lignin content in the epicotyls (after removing the needles) of the plants on the 28th day of the experiment. Statistical analyses of the data were performed with one-way ANOVA followed by Duncan’s post hoc test. Identical lowercase letters indicate that there are no differences between the experimental groups.</p>
Full article ">
14 pages, 3380 KiB  
Article
Effects of Fermentation with Kombucha Symbiotic Culture of Bacteria and Yeasts on Antioxidant Activities, Bioactive Compounds and Sensory Indicators of Rhodiola rosea and Salvia miltiorrhiza Beverages
by Jin Cheng, Dan-Dan Zhou, Ruo-Gu Xiong, Si-Xia Wu, Si-Yu Huang, Adila Saimaiti, Xiao-Yu Xu, Guo-Yi Tang, Hua-Bin Li and Sha Li
Molecules 2024, 29(16), 3809; https://doi.org/10.3390/molecules29163809 - 11 Aug 2024
Viewed by 202
Abstract
Kombucha is a well-known fermented beverage traditionally made from black tea infusion. Recent studies have focused on finding alternative materials to create novel kombucha beverages with various health benefits. In this study, we prepared and evaluated two novel kombucha beverages using Rhodiola rosea [...] Read more.
Kombucha is a well-known fermented beverage traditionally made from black tea infusion. Recent studies have focused on finding alternative materials to create novel kombucha beverages with various health benefits. In this study, we prepared and evaluated two novel kombucha beverages using Rhodiola rosea and Salvia miltiorrhiza as materials. The effects of fermentation with the residue of these plants on the kombucha were also investigated. The antioxidant activities, total phenolic contents, and concentrations of the bioactive compounds of the kombucha beverages were determined by the Trolox equivalent antioxidant capacity test, ferric-reducing antioxidant power test, Folin–Ciocalteu method, and high-performance liquid chromatography, respectively. The results revealed that the kombucha beverages made with Rhodiola rosea and Salvia miltiorrhiza had strong antioxidant capacities and abundant phenolic contents. Additionally, the kombucha fermented with Rhodiola rosea residue had higher FRAP, TEAC and TPC values than that fermented without residue. On the other hand, the Salvia miltiorrhiza kombucha fermented with residue had similar FRAP and TEAC values but lower TPC values compared to that fermented without residue. The correlation analysis showed that gallic acid, salidroside, and tyrosol were responsible for the antioxidant abilities and total phenolic contents of the Rhodiola rosea kombucha, and salvianolic acid A and salvianolic acid B contributed to the antioxidant abilities of the Salvia miltiorrhiza kombucha. Furthermore, the kombucha fermented with Rhodiola rosea residue had the highest sensory scores among the kombucha beverages studied. These findings suggest that Rhodiola rosea and Salvia miltiorrhiza are suitable for making novel kombucha beverages with strong antioxidant abilities and abundant phenolic contents, which can be used in preventing and managing oxidative stress-related diseases. Full article
Show Figures

Figure 1

Figure 1
<p>The appearances of kombucha beverages. (<b>a</b>) Kombucha fermented without <span class="html-italic">Rhodiola rosea</span> residue (<b>left</b>) or with <span class="html-italic">Rhodiola rosea</span> residue (<b>right</b>). (<b>b</b>) Kombucha fermented without <span class="html-italic">Salvia miltiorrhiza</span> residue (<b>left</b>) or with <span class="html-italic">Salvia miltiorrhiza</span> residue (<b>right</b>).</p>
Full article ">Figure 2
<p>FRAP values. (<b>a</b>) Kombucha made from <span class="html-italic">Rhodiola rosea</span>, (<b>b</b>) kombucha made from <span class="html-italic">Salvia miltiorrhiza</span>. The different red letters indicate that there were significant differences among kombucha beverages fermented without residue at different times (<span class="html-italic">p</span> &lt; 0.05). The different black letters indicate that there were significant differences among kombucha beverages fermented with residue at different times (<span class="html-italic">p</span> &lt; 0.05). * indicates there was a significant difference between fermentation with residue and without residue at the same time (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 3
<p>TEAC values. (<b>a</b>) Kombucha made from <span class="html-italic">Rhodiola rosea</span>, (<b>b</b>) kombucha made from <span class="html-italic">Salvia miltiorrhiza</span>. The different red letters indicate that there were significant differences among kombucha beverages fermented without residue at different times (<span class="html-italic">p</span> &lt; 0.05). The different black letters indicate that there were significant differences among kombucha beverages fermented with residue at different times (<span class="html-italic">p</span> &lt; 0.05). * indicates there was a significant difference between fermentation with residue and without residue at the same time (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 4
<p>TPC values. (<b>a</b>) Kombucha made from <span class="html-italic">Rhodiola rosea</span>, (<b>b</b>) kombucha made from <span class="html-italic">Salvia miltiorrhiza</span>. The different red letters indicate that there were significant differences among kombucha beverages fermented without residue at different times (<span class="html-italic">p</span> &lt; 0.05). The different black letters indicate that there were significant differences among kombucha beverages fermented with residue at different times (<span class="html-italic">p</span> &lt; 0.05). * indicates there was a significant difference between fermentation with residue and without residue at the same time (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 5
<p>Chromatograms of standards and kombucha beverages. (<b>a</b>) Standards for <span class="html-italic">Rhodiola rosea</span> at 275 nm, (<b>b</b>) kombucha fermented with <span class="html-italic">Rhodiola rosea</span> residue at 275 nm, (<b>c</b>) kombucha fermented without <span class="html-italic">Rhodiola rosea</span> residue at 275 nm, (<b>d</b>) standards for <span class="html-italic">Salvia miltiorrhiza</span> at 287 nm, (<b>e</b>) kombucha fermented with <span class="html-italic">Salvia miltiorrhiza</span> residue at 287 nm, (<b>f</b>) kombucha fermented without <span class="html-italic">Salvia miltiorrhiza</span> residue at 287 nm. EGCG, epigallocatechin gallate.</p>
Full article ">Figure 5 Cont.
<p>Chromatograms of standards and kombucha beverages. (<b>a</b>) Standards for <span class="html-italic">Rhodiola rosea</span> at 275 nm, (<b>b</b>) kombucha fermented with <span class="html-italic">Rhodiola rosea</span> residue at 275 nm, (<b>c</b>) kombucha fermented without <span class="html-italic">Rhodiola rosea</span> residue at 275 nm, (<b>d</b>) standards for <span class="html-italic">Salvia miltiorrhiza</span> at 287 nm, (<b>e</b>) kombucha fermented with <span class="html-italic">Salvia miltiorrhiza</span> residue at 287 nm, (<b>f</b>) kombucha fermented without <span class="html-italic">Salvia miltiorrhiza</span> residue at 287 nm. EGCG, epigallocatechin gallate.</p>
Full article ">Figure 6
<p>The concentrations of bioactive components in kombucha beverages. (<b>a</b>–<b>d</b>) <span class="html-italic">Rhodiola rosea</span> kombucha, (<b>e</b>–<b>g</b>) <span class="html-italic">Salvia miltiorrhiza</span> kombucha. The different red letters indicate that there were significant differences among kombucha beverages fermented without residue at different times (<span class="html-italic">p</span> &lt; 0.05). The different black letters indicate that there were significant differences among kombucha beverages fermented with residue at different times (<span class="html-italic">p</span> &lt; 0.05). * indicates there was a significant difference between fermentation with residue and without residue at the same time (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 6 Cont.
<p>The concentrations of bioactive components in kombucha beverages. (<b>a</b>–<b>d</b>) <span class="html-italic">Rhodiola rosea</span> kombucha, (<b>e</b>–<b>g</b>) <span class="html-italic">Salvia miltiorrhiza</span> kombucha. The different red letters indicate that there were significant differences among kombucha beverages fermented without residue at different times (<span class="html-italic">p</span> &lt; 0.05). The different black letters indicate that there were significant differences among kombucha beverages fermented with residue at different times (<span class="html-italic">p</span> &lt; 0.05). * indicates there was a significant difference between fermentation with residue and without residue at the same time (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 7
<p>Heatmaps of parameters and compound concentrations. (<b>a</b>) Kombucha fermented with <span class="html-italic">Rhodiola rosea</span> residue, (<b>b</b>) kombucha fermented without <span class="html-italic">Rhodiola rosea</span> residue, (<b>c</b>) kombucha fermented with <span class="html-italic">Salvia miltiorrhiza</span> residue, (<b>d</b>) kombucha fermented without <span class="html-italic">Salvia miltiorrhiza</span> residue. EGCG, epigallocatechin gallate. The red color means positive correlation, and the blue color means negative correlation. The darker the color, the stronger correlation.</p>
Full article ">Figure 8
<p>The sensory analysis results of kombucha beverages from <span class="html-italic">Rhodiola rosea</span> and <span class="html-italic">Salvia miltiorrhiza</span>.</p>
Full article ">
14 pages, 902 KiB  
Article
Solid-State Fermentation for Phenolic Compounds Recovery from Mexican Oregano (Lippia graveolens Kunth) Residual Leaves Applying a Lactic Acid Bacteria (Leuconostoc mesenteroides)
by Israel Bautista-Hernández, Ricardo Gómez-García, Cristóbal N. Aguilar, Guillermo C. G. Martínez-Ávila, Cristian Torres-León and Mónica L. Chávez-González
Agriculture 2024, 14(8), 1342; https://doi.org/10.3390/agriculture14081342 - 11 Aug 2024
Viewed by 457
Abstract
The Mexican oregano by-products are a source of bioactive molecules (polyphenols) that could be extracted using solid-state fermentation (SSF). This study fermented the by-products via SSF (120 h) with a lactic acid bacteria (LAB) Leuconostoc mesenteroides. Sequentially, a bioactive and chemical determination [...] Read more.
The Mexican oregano by-products are a source of bioactive molecules (polyphenols) that could be extracted using solid-state fermentation (SSF). This study fermented the by-products via SSF (120 h) with a lactic acid bacteria (LAB) Leuconostoc mesenteroides. Sequentially, a bioactive and chemical determination was made according to the phenolic content, antioxidant activity (DPPH/FRAP), bioactive properties (α-amylase inhibition and antimicrobial activity against Escherichia coli), and chemical composition (HPLC-MS). The results showed that the total phenolics and flavonoid content, as well as the antioxidant activity, increased (0.60, 2.55, and 3.01 times, respectively) during the SSF process compared with unfermented material. Also, the extracts showed antimicrobial activity against E. coli and α-amylase inhibition. These inhibitory results could be attributed to bioactive compounds identified via HPLC, such as gardenin B, trachelogenin, ferulic acid, and resveratrol 3-O-glucoside. Therefore, the application of L. mesenteroides under SSF on oregano by-products comprises an eco-friendly strategy for their valorization as raw materials for the recovery of phenolic compounds that could be natural alternatives against synthetic antioxidant and antimicrobial agents, promoting a more circular and sustainable supply system within the oregano industry. Full article
Show Figures

Figure 1

Figure 1
<p>General process diagram of bioactive activity and chemical evaluation of <span class="html-italic">Lippia graveolens</span> by-product valorization through SSF process.</p>
Full article ">Figure 2
<p>Polyphenolic compounds concentration in fermentative extracts obtained from SSF process using <span class="html-italic">L. mesenteroides</span>. (<b>A</b>) Total polyphenolic content (TPC) and (<b>B</b>) total flavonoid content (TFC). Different letters show significant differences (α = 0.05).</p>
Full article ">Figure 3
<p>Antioxidant activity of fermentative extracts via the SSF process using <span class="html-italic">L. mesenteroides</span>; (<b>A</b>) FRAP assay and (<b>B</b>) DPPH<sup>●</sup> assay. The different letters show significant differences (α = 0.05).</p>
Full article ">
15 pages, 16273 KiB  
Article
Xanthoxylin Attenuates Lipopolysaccharide-Induced Lung Injury through Modulation of Akt/HIF-1α/NF-κB and Nrf2 Pathways
by Fu-Chao Liu, Yuan-Han Yang, Chia-Chih Liao and Hung-Chen Lee
Int. J. Mol. Sci. 2024, 25(16), 8742; https://doi.org/10.3390/ijms25168742 (registering DOI) - 10 Aug 2024
Viewed by 263
Abstract
Xanthoxylin, a bioactive phenolic compound extracted from the traditional herbal medicine Penthorum Chinense Pursh, is renowned for its anti-inflammatory effects. While previous studies have highlighted the anti-inflammatory and antioxidant properties of Xanthoxylin, its precise mechanisms, particularly concerning immune response and organ protection, [...] Read more.
Xanthoxylin, a bioactive phenolic compound extracted from the traditional herbal medicine Penthorum Chinense Pursh, is renowned for its anti-inflammatory effects. While previous studies have highlighted the anti-inflammatory and antioxidant properties of Xanthoxylin, its precise mechanisms, particularly concerning immune response and organ protection, remain underexplored. This study aimed to elucidate the effects of Xanthoxylin on inflammation and associated signaling pathways in a mouse model of lipopolysaccharide (LPS)-induced acute lung injury (ALI). ALI was induced via intratracheal administration of LPS, followed by intraperitoneal injections of Xanthoxylin at doses of 1, 2.5, 5, and 10 mg/kg, administered 30 min post-LPS exposure. Lung tissues were harvested for analysis 6 h after LPS challenge. Xanthoxylin treatment significantly mitigated lung tissue damage, pathological alterations, immune cell infiltration, and the production of pro-inflammatory cytokines, including tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6). Additionally, Xanthoxylin modulated the expression of key proteins in the protein kinase B (Akt)/hypoxia-inducible factor 1-alpha (HIF-1α)/nuclear factor-kappa B (NF-κB) signaling pathway, as well as nuclear factor erythroid 2-related factor 2 (Nrf2) and oxidative markers such as superoxide dismutase (SOD) and malondialdehyde (MDA) in the context of LPS-induced injury. This study demonstrates that Xanthoxylin exerts protective and anti-inflammatory effects by down-regulating and inhibiting the Akt/HIF-1α/NF-κB pathways, suggesting its potential as a therapeutic target for the prevention and treatment of ALI or acute respiratory distress syndrome (ARDS). Full article
(This article belongs to the Special Issue New Insights in Natural Bioactive Compounds 3.0)
Show Figures

Figure 1

Figure 1
<p>The effect of Xanthoxylin on the viability and pro-inflammatory cytokine levels of RAW 264.7 cells in the presence and absence of LPS. (<b>A</b>) RAW 264.7 cells were treated with various concentrations of DMSO (0.01, 0.05, and 0.5 μL) or Xanthoxylin (0.1, 1, 5, 10, 20, and 50 μM) for 24 h. Results are expressed as a percentage relative to the control group and shown as mean ± SD (<span class="html-italic">n</span> = 6 per group). (<b>B</b>) RAW 264.7 cells were treated with Xanthoxylin (0, 5, and 10 μM) followed by LPS exposure for 48 h to assess cell viability. Results are expressed as a percentage relative to the control group and shown as mean ± SD (<span class="html-italic">n</span> = 12 per group). (<b>C</b>) Pro-inflammatory cytokines IL-1β, IL-6, and TNF-α levels in the supernatants of RAW 264.7 cells were measured after treatment with Xanthoxylin, followed by LPS exposure. ### <span class="html-italic">p</span> &lt; 0.005 vs. control group; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.005 vs. LPS group.</p>
Full article ">Figure 2
<p>General lung appearance after LPS-induced injury and Xanthoxylin treatment. Mice received an intratracheal LPS challenge followed by intraperitoneal administration of Xanthoxylin (XT, 1, 2.5, 5, and 10 mg/kg) or saline. Lungs were collected 6 h post-LPS challenge for analysis.</p>
Full article ">Figure 3
<p>Histological examination of lung tissues stained with H&amp;E after LPS challenge and Xanthoxylin treatment. Mice received LPS intratracheally and were then treated with Xanthoxylin (XT, 1, 2.5, 5, and 10 mg/kg) or saline intraperitoneally. Lungs were harvested 6 h post-LPS challenge for H&amp;E staining. Representative images show ALI and histological changes (100× magnification, scar bar = 100 μm). Quantification of histologic lung injury was analyzed according to American Thoracic Society (ATS) scoring system (<span class="html-italic">n</span> = 6 per group). # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.005 vs. control group; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.001 vs. LPS group.</p>
Full article ">Figure 4
<p>Neutrophil infiltration in lungs following LPS-induced injury and Xanthoxylin treatment. Mice were challenged with LPS intratracheally and treated with Xanthoxylin (XT, 1, 2.5, 5, and 10 mg/kg) or saline intraperitoneally. Lungs were collected 6 h post-LPS challenge and immunostained with Ly6G antibody (200× magnification, scar bar = 50 μm). Quantification of positive cells was analyzed under high power field (HPF). Data are mean ± SD (<span class="html-italic">n</span> = 6 per group). ### <span class="html-italic">p</span> &lt; 0.005 vs. control group; * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.005 vs. LPS group.</p>
Full article ">Figure 5
<p>Macrophage infiltration in lungs following LPS-induced injury and Xanthoxylin treatment. Mice received LPS intratracheally and were treated with Xanthoxylin (XT, 1, 2.5, 5, and 10 mg/kg) or saline intraperitoneally. Lungs were harvested 6 h post-LPS challenge and immunostained with Mac-2 antibody (200× magnification, scar bar = 50 μm). Quantification of positive cells was analyzed under HPF. Data are mean ± SD (<span class="html-italic">n</span> = 6 per group). ### <span class="html-italic">p</span> &lt; 0.005 vs. control group; *** <span class="html-italic">p</span> &lt; 0.005 vs. LPS group.</p>
Full article ">Figure 6
<p>Levels of (<b>A</b>) IL-6 and (<b>B</b>) TNF-α in lungs after LPS challenge and Xanthoxylin treatment. Mice were given intratracheal LPS challenge followed by Xanthoxylin (XT, 1, 2.5, 5, and 10 mg/kg) or saline intraperitoneally. Lungs were harvested 6 h post-LPS challenge for ELISA. Data are mean ± SD (<span class="html-italic">n</span> = 6 per group). # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.005 vs. control group; ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.005 vs. LPS group.</p>
Full article ">Figure 7
<p>Levels of (<b>A</b>) MDA and (<b>B</b>) SOD in lungs after LPS challenge and Xanthoxylin treatment. Mice received intratracheal LPS challenge and were treated with Xanthoxylin (XT, 1, 2.5, 5, and 10 mg/kg) or saline intraperitoneally. Lungs were collected 6 h post-LPS challenge for oxidative stress assays. Data are mean ± SD (<span class="html-italic">n</span> = 6 per group). # <span class="html-italic">p</span> &lt; 0.05, ### <span class="html-italic">p</span> &lt; 0.005 vs. control group; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.005 vs. LPS group.</p>
Full article ">Figure 8
<p>Effects of Xanthoxylin on expression of (<b>A</b>) Akt, (<b>B</b>) NF-κB, (<b>C</b>) HIF-1α, and (<b>D</b>) Nrf2 in lungs after LPS challenge. Mice were administered Xanthoxylin (XT, 2.5, 5, and 10 mg/kg) or saline intraperitoneally 30 min post-LPS challenge. Lungs were harvested 6 h later for Western blot analysis. Data are mean ± SD (<span class="html-italic">n</span> = 6 per group). ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.005 vs. control group; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.005 vs. LPS group.</p>
Full article ">Figure 9
<p>Nrf2 expression in lungs after LPS-induced injury and Xanthoxylin treatment. Mice received intratracheal LPS challenge followed by Xanthoxylin (XT, 1, 2.5, 5, and 10 mg/kg) or saline intraperitoneally. Lungs were collected 6 h post-LPS challenge and immunostained with Nrf2 antibody (400× magnification, scar bar = 25 μm). Quantification of positive cells was analyzed under HPF. Data are mean ± SD (<span class="html-italic">n</span> = 6 per group). ### <span class="html-italic">p</span> &lt; 0.005 vs. control group; *** <span class="html-italic">p</span> &lt; 0.005 vs. LPS group.</p>
Full article ">Figure 10
<p>A schematic representation of the involvement of Akt/HIF-1α/NF-κB and Nrf2 signaling pathways in the protective effects of Xanthoxylin against LPS-induced lung injury. Xanthoxylin modulates Akt expression, suppresses HIF-1α/NF-κB signaling, and activates Nrf2, thereby reducing cell damage and oxidative stress. It also inhibits TNF-α and IL-6 release from macrophages.</p>
Full article ">
19 pages, 777 KiB  
Review
Regulation of Intestinal Inflammation by Walnut-Derived Bioactive Compounds
by Kexin Dai, Neel Agarwal, Alexander Rodriguez-Palacios and Abigail Raffner Basson
Nutrients 2024, 16(16), 2643; https://doi.org/10.3390/nu16162643 - 10 Aug 2024
Viewed by 624
Abstract
Walnuts (Juglans regia L.) have shown promising effects in terms of ameliorating inflammatory bowel disease (IBD), attributed to their abundant bioactive compounds. This review comprehensively illustrates the key mechanisms underlying the therapeutic potential of walnuts in IBD management, including the modulation of [...] Read more.
Walnuts (Juglans regia L.) have shown promising effects in terms of ameliorating inflammatory bowel disease (IBD), attributed to their abundant bioactive compounds. This review comprehensively illustrates the key mechanisms underlying the therapeutic potential of walnuts in IBD management, including the modulation of intestinal mucosa permeability, the regulation of inflammatory pathways (such as NF-kB, COX/COX2, MAPCK/MAPK, and iNOS/NOS), relieving oxidative stress, and the modulation of gut microbiota. Furthermore, we highlight walnut-derived anti-inflammatory compounds, such as polyunsaturated fatty acids (PUFA; e.g., ω-3 PUFA), tocopherols, phytosterols, sphingolipids, phospholipids, phenolic compounds, flavonoids, and tannins. We also discuss unique anti-inflammatory compounds such as peptides and polysaccharides, including their extraction and preparation methods. Our review provides a theoretical foundation for dietary walnut supplementation in IBD management and provides guidance for academia and industry. In future, research should focus on the targeted isolation and purification of walnut-derived anti-inflammatory compounds or optimizing extraction methods to enhance their yields, thereby helping the food industry to develop dietary supplements or walnut-derived functional foods tailored for IBD patients. Full article
Show Figures

Figure 1

Figure 1
<p>The mechanism of walnuts regulating IBD. (1) An illustration of the intestinal mucosal barrier and the effect of walnuts on permeability. (2) A depiction of the antioxidant effects of walnuts on ROS. (3) A pathway map showing NF-κB, COX/COX-2 and MAPK signaling modulation by walnuts. (4) Diagram showing changes in gut microbiota composition due to walnut consumption.</p>
Full article ">
15 pages, 2283 KiB  
Article
Immunomodulatory Effects of Anadenanthera colubrina Bark Extract in Experimental Autoimmune Encephalomyelitis
by Karla A. Ramos, Igor G. M. Soares, Larissa M. A. Oliveira, Mariana A. Braga, Pietra P. C. Soares, Gracimerio J. Guarneire, Elaine C. Scherrer, Fernando S. Silva, Nerilson M. Lima, Felipe A. La Porta, Teresinha de Jesus A. S. Andrade, Gagan Preet, Sandra B. R. Castro, Caio César S. Alves and Alessandra P. Carli
Curr. Issues Mol. Biol. 2024, 46(8), 8726-8740; https://doi.org/10.3390/cimb46080515 (registering DOI) - 10 Aug 2024
Viewed by 342
Abstract
This study aimed to evaluate the efficacy of the ethanolic extract of Anadenanthera colubrina in modulating the immune response in the Experimental Autoimmune Encephalomyelitis (EAE) model. The ethanolic extract of the dried bark was analyzed by ESI (+) Orbitrap-MS to obtain a metabolite [...] Read more.
This study aimed to evaluate the efficacy of the ethanolic extract of Anadenanthera colubrina in modulating the immune response in the Experimental Autoimmune Encephalomyelitis (EAE) model. The ethanolic extract of the dried bark was analyzed by ESI (+) Orbitrap-MS to obtain a metabolite profile, demonstrating a wide variety of polyphenols, such as flavonoids and phenolic acids. Various parameters were evaluated, such as clinical signs, cytokines, cellular profile, and histopathology in the central nervous system (CNS). The ethanolic extract of A. colubrina demonstrated significant positive effects attenuating the clinical signs and pathological processes associated with EAE. The beneficial effects of the extract treatment were evidenced by reduced levels of pro-inflammatory cytokines, such as IL1β, IL-6, IL-12, TNF, IFN-γ, and a notable decrease in several cell profiles, including CD8+, CD4+, CD4+IFN-γ, CD4+IL-17+, CD11c+MHC-II+, CD11+CD80+, and CD11+CD86+ in the CNS. In addition, histological analysis revealed fewer inflammatory infiltrates and demyelination sites in the spinal cord of mice treated with the extract compared to the control model group. These results showed, for the first time, that the ethanolic extract of A. colubrina exerts a modulatory effect on inflammatory processes, improving clinical signs in EAE, in the acute phase of the disease, which could be further explored as a possible therapeutic alternative. Full article
Show Figures

Figure 1

Figure 1
<p>Clinical signs of EAE. Animals (n = 8/group) were monitored daily for clinical signs of EAE after immunization with 100 µg of MOG<sub>35–55</sub> peptide. Mice were treated with 200 mg/kg of the ethanolic extract of <span class="html-italic">A. colubrina</span> barks (EtAc) for six days. The dotted line indicates the start of treatment. Each dot represents the arithmetic mean ± SEM. * indicates <span class="html-italic">p</span> &lt; 0.05 compared to induced and PBS-treated animals (EAE), analyzed by two-way ANOVA with Dunnett’s correction. CN = negative control (not induced and treated with PBS).</p>
Full article ">Figure 2
<p>Histopathology of the spinal cord of mice. Histopathology of the spinal cord of mice immunized or not immunized with 100 µg of MOG<sub>35–55</sub> (n = 8/group). Figures are representative of the histological analysis of each experimental group: CN= non-immunized and PBS-treated group (<b>A</b>,<b>B</b>), EAE = immunized and PBS-treated group (<b>C</b>,<b>D</b>), EtAc = immunized and treated with 200 mg/kg ethanolic extract of <span class="html-italic">A. colubrina</span> barks for six days (<b>E</b>,<b>F</b>). The examined groups representative sections (5 µm) were stained with hematoxylin and eosin (H&amp;E) to analyze the cell infiltrate. Original magnification: 10× objective (<b>A</b>,<b>C</b>,<b>E</b>), 40× (<b>B</b>,<b>D</b>,<b>F</b>). Scale bars = 100 µm (10×) and 50 µm (40×). Arrows indicate cellular infiltrates.</p>
Full article ">Figure 3
<p>Demyelination of the spinal cord of mice. Histopathology of spinal cords of mice immunized or not immunized with 100 µg of MOG35–55 (n = 8/group). Figures are representative of the histological analysis of each experimental group: CN= non-immunized and PBS-treated group (<b>A</b>), EAE = immunized and PBS-treated group (<b>B</b>), EtAc = immunized and treated with 200 mg/kg ethanolic extract of <span class="html-italic">A. colubrina</span> barks for six days (<b>C</b>). Representative sections (8 µm) of the examined groups, stained with Luxol fast blue, for analysis of the demyelination. Original magnification: 10× objective. Scale bars = 100 µm. Delimited areas = areas of demyelination.</p>
Full article ">Figure 4
<p>Cellular profile. Mononuclear cell counts (<b>A</b>,<b>E</b>) and cellular profile determination (<b>B</b>–<b>D</b>,<b>F</b>–<b>H</b>) in the brains (<b>A</b>–<b>D</b>) and spinal cords (<b>E</b>–<b>H</b>) of mice immunized or not immunized with 100 µg of MOG<sub>35–55</sub> (n = 8/group). Mice were treated with 200 mg/kg of the ethanolic extract of <span class="html-italic">A. colubrina</span> barks (EtAc) for six days. Each bar represents the arithmetic mean ± SEM. * indicates <span class="html-italic">p</span> &lt; 0.05 compared to induced and PBS-treated animals (EAE). CN = negative control (not induced and treated with PBS).</p>
Full article ">Figure 5
<p>Absolute intensity of the most abundant phenolic acids (cinnamic acid, gallic acid, and <span class="html-italic">p</span>-coumaric acid) and flavonoids (apigenin, catechin, quercetin, and myricetin) annotated through ESI (+) Orbitrap-MS analysis of the ethanolic extract from <span class="html-italic">A. colubrina</span> bark.</p>
Full article ">Figure 6
<p>ESI (+) Orbitrap-MS-based metabolite profiling of <span class="html-italic">A. colubrina</span> showing the major classes identified in bark ethanolic extract.</p>
Full article ">
15 pages, 2531 KiB  
Article
Seed Disinfection Treatments Minimized Microbial Load and Enhanced Nutritional Properties of Fenugreek Sprouts Which Alleviated Diabetes-Negative Disorders in Diabetic Rats
by Abeer A. Dahab, Hala M. Bayomy, Hemat S. Abd El-Salam, Seham E. Almasoudi, Nawal A. Ozaybi, Gehan A. Mahmoud, Amira K. G. Atteya and Rasha S. El-Serafy
Nutrients 2024, 16(16), 2635; https://doi.org/10.3390/nu16162635 - 10 Aug 2024
Viewed by 545
Abstract
Sprouts are an attractive food product that contains high amounts of nutritional substances and has pro-health features. Sprout consumption has strongly increased despite its potential risk to health due to its microbial load. Both the safety and shelf life of sprouts may be [...] Read more.
Sprouts are an attractive food product that contains high amounts of nutritional substances and has pro-health features. Sprout consumption has strongly increased despite its potential risk to health due to its microbial load. Both the safety and shelf life of sprouts may be negatively affected by a high microbial load. To reduce the microbial contamination in sprouts before consumption, the initial microbial load on the seeds needs to be controlled. Many herbal sprouts have been recommended for diabetes, and fenugreek is one of these sprouts. Thus, the current experiment aimed at disinfecting fenugreek seeds using microwave (5, 10, and 20 s) and hot water (30, 45, and 60 s) treatments for different durations. The best-disinfected sprouts with the highest nutritional properties were used to evaluate their influence on streptozocin-induced diabetic rats in comparison with fenugreek seed feeding. Microwave treatments showed the highest sprout length, fresh weight, total free amino acids, antioxidants, reducing sugars, and total phenols. Additionally, microwave seed treatments showed the lowest bacteria and mold counts on sprouts produced relative to hot water treatments, and the best seed treatment was a microwave for 20 s, which gave the best values in this respect. Feeding diabetic rats with different fenugreek seeds or sprout rates (0, 5, 7.5, and 10% w/w) improved body weight, restricted the growth of glucose levels, lowered total cholesterol and triglycerides, and improved HDL compared with the positive control group, and fenugreek sprouts at higher rates showed the maximum improvements in blood glucose, total cholesterol, and triglycerides. Treating fenugreek seed with microwave radiation for 20 s to disinfect the seeds before sprouting is recommended for lowering the microbial load with optimum nutritional and antioxidant activity, and feeding diabetic rats with these sprouts at the rate of 7.5 and 10% had promising effects on hyperglycemia and associated disorders. Full article
(This article belongs to the Special Issue Association of Dietary Intake with Chronic Disease and Human Health)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Germination% (<b>a</b>), sprout length (<b>b</b>), and 10 sprouts fresh weight (<b>c</b>) of fenugreek sprouts in response to microwave and hot water seed disinfection treatments. M5s, microwave for 5 s; M10s, microwave for 10 s; M20s, microwave for 20 s; W30s, hot water for 30 s; W45s, hot water for 45 s; and W60s, hot water for 60 s. All data denote mean ± S.E. Means with different letters significantly differed, using Tukey test at <span class="html-italic">p</span> ≤ 0.05.</p>
Full article ">Figure 2
<p>Total free amino acid (<b>a</b>), antioxidant (<b>b</b>), reducing sugars (<b>c</b>), and total phenols (<b>d</b>) of fenugreek sprouts in response to microwave and hot water seed disinfection treatments. M5s, microwave for 5 s; M10s, microwave for 10 s; M20s, microwave for 20 s; W30s, hot water for 30 s; W45s, hot water for 45 s; and W60s, hot water for 60 s. All data denote mean ± S.E. Means with different letters significantly differed, using Tukey test at <span class="html-italic">p</span> ≤ 0.05.</p>
Full article ">Figure 3
<p>Total bacteria (<b>a</b>) and total mold (<b>b</b>) of fenugreek sprouts in response to microwave and hot water seed disinfection treatments. M5s, microwave for 5 s; M10, microwave for 10 s; M20s, microwave for 20 s; W30s, hot water for 30 s; W45s, hot water for 45 s; and W60s, hot water for 60 s. All data denote mean ± S.E. Means with different letters significantly differed, using Tukey test at <span class="html-italic">p</span> ≤ 0.05.</p>
Full article ">
19 pages, 1636 KiB  
Article
Assessing the Impact of (Poly)phenol-Rich Foods on Cardiometabolic Risk in Postmenopausal Women: A Dietary Trial
by Lorena Sánchez-Martínez, Rocío González-Barrio, Javier García-Alonso, Pedro Mena and María-Jesús Periago
Antioxidants 2024, 13(8), 973; https://doi.org/10.3390/antiox13080973 (registering DOI) - 9 Aug 2024
Viewed by 179
Abstract
Menopause is a critical stage in a woman’s life in which cardiometabolic alterations appear, such as insulin resistance or a predisposition to visceral fat deposits, leading to an increased risk of cardiometabolic diseases (R-CMBs). New strategies to reduce the R-CMBs in postmenopausal women [...] Read more.
Menopause is a critical stage in a woman’s life in which cardiometabolic alterations appear, such as insulin resistance or a predisposition to visceral fat deposits, leading to an increased risk of cardiometabolic diseases (R-CMBs). New strategies to reduce the R-CMBs in postmenopausal women using natural compounds without adverse effects are desirable. In this sense, plant-based diets rich in fruits and vegetables could play a fundamental role due to the high content of bioactive compounds found in these diets, such as (poly)phenols, known for their antioxidant, anti-inflammatory and vasodilator properties. The aim of this research was to carry out a dietary trial to evaluate the effect of the daily intake of different (poly)phenol-rich foods (PP-rich foods) for 2 months on the modulation of the main cardiometabolic risk biomarkers of postmenopausal women. The results showed a slight improvement in blood pressure (BP), lipid profile and oxidative stress, endothelial function and inflammatory biomarkers. These findings suggest that daily consumption of PP-rich foods alleviated the R-CMBs of postmenopausal women by reducing the oxidative stress and, thus, the risk of cardiovascular events; however, the magnitude of the cardioprotective effect of (poly)phenols depends on inter-individual variability. Full article
(This article belongs to the Special Issue Natural Antioxidants and Metabolic Diseases)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Flowchart of the recruitment period and experimental design. R-CMBs: risk of cardiometabolic diseases. Time points: (T0) baseline; (T1) control period in which participants followed their habitual diet for 1 month; (T2) experimental period, in which the diet of the participants was supplemented with (poly)phenol-rich foods for 2 months. Blood and 24 h urine were collected at T0, T1 and T2 to determine different parameters related to cardiometabolic risk, as indicated by (*).</p>
Full article ">Figure 2
<p>(Poly)phenolic profile of dietary supplementation. (<b>A</b>) Percentage of (poly)phenols and antioxidant capacity provided by each food included in the supplementation. (<b>B</b>) Percentage of the main (poly)phenol families provided by dietary supplementation.</p>
Full article ">Figure 3
<p>Potential mechanisms of (poly)phenol-rich foods to improve cardiometabolic and cardiovascular risk in postmenopausal women. ↑: Variables that increase; ↓: Variables that decrease.</p>
Full article ">
Back to TopTop