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Topic Editors

Department of Nutrition and Food Science, Faculty of Pharmacy, Complutense University of Madrid (UCM), Madrid, Spain
1. Department of Basic Health Sciences, Faculty of Health Sciences, University Rey Juan Carlos (URJC), 28922 Alcorcón, Spain
2. High Performance Research Group in Physiopathology and Pharmacology of the Digestive System (NeuGut-URJC), University Rey Juan Carlos (URJC), 28922 Alcorcón, Spain

Nutrients, Food Bioactives, and Functional Foods in Gastrointestinal and Metabolic Disorders

Abstract submission deadline
31 March 2025
Manuscript submission deadline
31 May 2025
Viewed by
6669

Topic Information

Dear Colleagues,

We are pleased to announce a call for papers for a Topic focusing on "Nutrients, Food Bioactives, and Functional Foods in Gastrointestinal and Metabolic Disorders". This MDPI Topic aims to gather the latest research and developments in the field, providing a comprehensive overview of the current state of knowledge and identifying future directions. The Topic focuses on the critical roles of nutrients, food bioactives, and functional foods in the prevention and management of digestive diseases and metabolic disorders, whose growing prevalence underscores the need for the analysis and identification of novel bioactive food-derived compounds and innovative dietary strategies to target the pathophysiology of these alterations. This Topic aims to gather cutting-edge research and comprehensive reviews that explore the mechanisms through which specific nutrients and bioactive compounds potentially influence gut health, metabolic pathways, molecular and cellular mediators, and, ultimately, overall disease outcomes. The topics of interest include but are not limited to the health impact of dietary components on inflammation, gut microbiota, metabolic regulation, glycemic and lipid disorders, along with the design, development, and application of functional foods. Through this collection, we seek to advance our understanding of the preventive potential and health benefits of food-based approaches in managing digestive and metabolic disorders.

Dr. Samuel Fernández-Tomé
Dr. Ortega Moreno Lorena
Topic Editors

Keywords

  • functional foods
  • food bioactives
  • gastrointestinal diseases
  • metabolic disorders
  • mechanisms of action
  • health benefits
  • gut microbiota
  • glycemic and lipid alterations
  • inflammation
  • metabolomics

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Current Issues in Molecular Biology
cimb
2.8 2.9 1999 16.8 Days CHF 2200 Submit
Foods
foods
4.7 7.4 2012 14.3 Days CHF 2900 Submit
International Journal of Molecular Sciences
ijms
4.9 8.1 2000 18.1 Days CHF 2900 Submit
Scientia Pharmaceutica
scipharm
2.3 4.6 1930 31.4 Days CHF 1000 Submit
Antioxidants
antioxidants
6.0 10.6 2012 15.5 Days CHF 2900 Submit
Nutrients
nutrients
4.8 9.2 2009 17.5 Days CHF 2900 Submit

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Published Papers (5 papers)

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21 pages, 4181 KiB  
Systematic Review
Curcumin Attenuates Hyperglycemia and Inflammation in Type 2 Diabetes Mellitus: Quantitative Analysis of Randomized Controlled Trial
by Kabelo Mokgalaboni, Reneilwe G. Mashaba, Wendy N. Phoswa and Sogolo L. Lebelo
Nutrients 2024, 16(23), 4177; https://doi.org/10.3390/nu16234177 - 30 Nov 2024
Viewed by 1284
Abstract
Controlling hyperglycemia and inflammation in type 2 diabetes (T2D) remains an important approach to control diabetes. The use of phytochemicals found in natural herbs has been investigated widely, and there are inconsistent findings in clinical trials, likely associated with a small sample size. [...] Read more.
Controlling hyperglycemia and inflammation in type 2 diabetes (T2D) remains an important approach to control diabetes. The use of phytochemicals found in natural herbs has been investigated widely, and there are inconsistent findings in clinical trials, likely associated with a small sample size. A meta-analysis of clinical trials was performed by conducting a comprehensive literature search on PubMed, Scopus, EBSCOHost, and Web of Sciences. The search terms included Curcumin longa, turmeric, curcumin, curcuma xanthorrhiza, diferuloylmethane, and type 2 diabetes. Data were analyzed using an online meta-analysis tool, Jamovi version 2.4.8 and IBM SPSS statistics version 29. The data were reported as either mean difference (MD) or standard mean difference (SMD) and 95% confidence intervals. The evidence from 18 trials with 1382 T2D with a mean age of 55.9 years was analyzed. Supplementation with curcumin led to a significant decrease in fasting blood glucose, MD = −11.48 mg/dL, 95%CI (−14.26, −8.70), p < 0.01 and glycated hemoglobin, MD = −0.54%, 95%CI (−0.73, −0.35), p < 0.01. Additionally, there was a significant decrease in C-Reactive Protein in curcumin compared to a placebo, SMD = −0.59, 95%CI (−1.11, −0.07), p = 0.03. The findings observed in this study suggest that curcumin can ameliorate hyperglycemia and inflammation in T2D compared to a placebo. While the potential benefits were observed, it is recommended that future trials focus on finding a suitable dose and duration of intervention and incorporate formulation in curcumin to enhance its absorption. Full article
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Figure 1

Figure 1
<p>Preferred reporting items for systematic review and meta-analysis (PRISMA) flow diagram.</p>
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<p>Individual risk of bias (ROS) and individual domains across the included trials [<a href="#B28-nutrients-16-04177" class="html-bibr">28</a>,<a href="#B29-nutrients-16-04177" class="html-bibr">29</a>,<a href="#B30-nutrients-16-04177" class="html-bibr">30</a>,<a href="#B31-nutrients-16-04177" class="html-bibr">31</a>,<a href="#B43-nutrients-16-04177" class="html-bibr">43</a>,<a href="#B44-nutrients-16-04177" class="html-bibr">44</a>,<a href="#B45-nutrients-16-04177" class="html-bibr">45</a>,<a href="#B46-nutrients-16-04177" class="html-bibr">46</a>,<a href="#B47-nutrients-16-04177" class="html-bibr">47</a>,<a href="#B48-nutrients-16-04177" class="html-bibr">48</a>,<a href="#B49-nutrients-16-04177" class="html-bibr">49</a>,<a href="#B50-nutrients-16-04177" class="html-bibr">50</a>,<a href="#B51-nutrients-16-04177" class="html-bibr">51</a>,<a href="#B52-nutrients-16-04177" class="html-bibr">52</a>,<a href="#B53-nutrients-16-04177" class="html-bibr">53</a>,<a href="#B54-nutrients-16-04177" class="html-bibr">54</a>,<a href="#B55-nutrients-16-04177" class="html-bibr">55</a>,<a href="#B56-nutrients-16-04177" class="html-bibr">56</a>].</p>
Full article ">Figure 3
<p>Effect of curcumin on FBG in T2D [<a href="#B28-nutrients-16-04177" class="html-bibr">28</a>,<a href="#B29-nutrients-16-04177" class="html-bibr">29</a>,<a href="#B30-nutrients-16-04177" class="html-bibr">30</a>,<a href="#B31-nutrients-16-04177" class="html-bibr">31</a>,<a href="#B43-nutrients-16-04177" class="html-bibr">43</a>,<a href="#B45-nutrients-16-04177" class="html-bibr">45</a>,<a href="#B46-nutrients-16-04177" class="html-bibr">46</a>,<a href="#B47-nutrients-16-04177" class="html-bibr">47</a>,<a href="#B48-nutrients-16-04177" class="html-bibr">48</a>,<a href="#B49-nutrients-16-04177" class="html-bibr">49</a>,<a href="#B50-nutrients-16-04177" class="html-bibr">50</a>,<a href="#B52-nutrients-16-04177" class="html-bibr">52</a>,<a href="#B53-nutrients-16-04177" class="html-bibr">53</a>,<a href="#B54-nutrients-16-04177" class="html-bibr">54</a>,<a href="#B55-nutrients-16-04177" class="html-bibr">55</a>,<a href="#B56-nutrients-16-04177" class="html-bibr">56</a>]. The black-shaped diamond represents the overall effect estimate, the green square shows the sample size of the individual trials, and the error bars show individual trial confidence intervals. SD: standard deviation, CI: confidence intervals, IV: inverse variance.</p>
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<p>Effect of curcumin versus placebo on HBA1C in T2D patients [<a href="#B28-nutrients-16-04177" class="html-bibr">28</a>,<a href="#B29-nutrients-16-04177" class="html-bibr">29</a>,<a href="#B30-nutrients-16-04177" class="html-bibr">30</a>,<a href="#B43-nutrients-16-04177" class="html-bibr">43</a>,<a href="#B45-nutrients-16-04177" class="html-bibr">45</a>,<a href="#B46-nutrients-16-04177" class="html-bibr">46</a>,<a href="#B47-nutrients-16-04177" class="html-bibr">47</a>,<a href="#B48-nutrients-16-04177" class="html-bibr">48</a>,<a href="#B49-nutrients-16-04177" class="html-bibr">49</a>,<a href="#B50-nutrients-16-04177" class="html-bibr">50</a>,<a href="#B52-nutrients-16-04177" class="html-bibr">52</a>,<a href="#B54-nutrients-16-04177" class="html-bibr">54</a>,<a href="#B55-nutrients-16-04177" class="html-bibr">55</a>,<a href="#B56-nutrients-16-04177" class="html-bibr">56</a>]. The black-shaped diamond represents the overall effect estimate, the green square shows the sample size of the individual trials, and the error bars show individual trial confidence intervals. SD: standard deviation, std: standardized mean difference, CI: confidence intervals, IV: inverse variance.</p>
Full article ">Figure 5
<p>Effect of curcumin on CRP in T2D patients [<a href="#B29-nutrients-16-04177" class="html-bibr">29</a>,<a href="#B31-nutrients-16-04177" class="html-bibr">31</a>,<a href="#B44-nutrients-16-04177" class="html-bibr">44</a>,<a href="#B45-nutrients-16-04177" class="html-bibr">45</a>,<a href="#B47-nutrients-16-04177" class="html-bibr">47</a>,<a href="#B48-nutrients-16-04177" class="html-bibr">48</a>,<a href="#B49-nutrients-16-04177" class="html-bibr">49</a>,<a href="#B51-nutrients-16-04177" class="html-bibr">51</a>,<a href="#B53-nutrients-16-04177" class="html-bibr">53</a>,<a href="#B55-nutrients-16-04177" class="html-bibr">55</a>]. The diamond shape represents the overall effect size, the square shows the sample size of the individual trials, and the error bars show individual trial confidence intervals, SD: standard deviation, std: standardized, CI: confidence intervals, IV: inverse variance, and CRP: C-reactive protein.</p>
Full article ">Figure 6
<p>Meta-regression, showing an association between gender and CRP. Square blocks show the number of trials, and the line shows the meta-regression.</p>
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<p>Funnel plots depicting publication bias across the analyzed trials. (<b>A</b>) fasting blood glucose [<a href="#B28-nutrients-16-04177" class="html-bibr">28</a>,<a href="#B29-nutrients-16-04177" class="html-bibr">29</a>,<a href="#B31-nutrients-16-04177" class="html-bibr">31</a>,<a href="#B43-nutrients-16-04177" class="html-bibr">43</a>,<a href="#B45-nutrients-16-04177" class="html-bibr">45</a>,<a href="#B46-nutrients-16-04177" class="html-bibr">46</a>,<a href="#B47-nutrients-16-04177" class="html-bibr">47</a>,<a href="#B48-nutrients-16-04177" class="html-bibr">48</a>,<a href="#B49-nutrients-16-04177" class="html-bibr">49</a>,<a href="#B50-nutrients-16-04177" class="html-bibr">50</a>,<a href="#B52-nutrients-16-04177" class="html-bibr">52</a>,<a href="#B53-nutrients-16-04177" class="html-bibr">53</a>,<a href="#B54-nutrients-16-04177" class="html-bibr">54</a>,<a href="#B55-nutrients-16-04177" class="html-bibr">55</a>,<a href="#B56-nutrients-16-04177" class="html-bibr">56</a>]; (<b>B</b>) glycated hemoglobin [<a href="#B28-nutrients-16-04177" class="html-bibr">28</a>,<a href="#B29-nutrients-16-04177" class="html-bibr">29</a>,<a href="#B43-nutrients-16-04177" class="html-bibr">43</a>,<a href="#B45-nutrients-16-04177" class="html-bibr">45</a>,<a href="#B46-nutrients-16-04177" class="html-bibr">46</a>,<a href="#B47-nutrients-16-04177" class="html-bibr">47</a>,<a href="#B48-nutrients-16-04177" class="html-bibr">48</a>,<a href="#B49-nutrients-16-04177" class="html-bibr">49</a>,<a href="#B50-nutrients-16-04177" class="html-bibr">50</a>,<a href="#B52-nutrients-16-04177" class="html-bibr">52</a>,<a href="#B54-nutrients-16-04177" class="html-bibr">54</a>,<a href="#B55-nutrients-16-04177" class="html-bibr">55</a>,<a href="#B56-nutrients-16-04177" class="html-bibr">56</a>]; (<b>C</b>) C-reactive protein [<a href="#B29-nutrients-16-04177" class="html-bibr">29</a>,<a href="#B31-nutrients-16-04177" class="html-bibr">31</a>,<a href="#B44-nutrients-16-04177" class="html-bibr">44</a>,<a href="#B45-nutrients-16-04177" class="html-bibr">45</a>,<a href="#B47-nutrients-16-04177" class="html-bibr">47</a>,<a href="#B48-nutrients-16-04177" class="html-bibr">48</a>,<a href="#B49-nutrients-16-04177" class="html-bibr">49</a>,<a href="#B51-nutrients-16-04177" class="html-bibr">51</a>,<a href="#B53-nutrients-16-04177" class="html-bibr">53</a>,<a href="#B55-nutrients-16-04177" class="html-bibr">55</a>].</p>
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19 pages, 2976 KiB  
Article
New Pipeline for Analysing Fruit Proteolytic Products Used as Digestive Health Nutraceuticals
by Iván Benito-Vázquez, Ana Muñoz-Labrador, Manuel Garrido-Romero, Gema Hontoria-Caballo, Carlos García-García, Marina Diez-Municio and F. Javier Moreno
Int. J. Mol. Sci. 2024, 25(19), 10315; https://doi.org/10.3390/ijms251910315 - 25 Sep 2024
Viewed by 891
Abstract
Proteolytic products are extensively used in the nutraceutical sector to improve protein digestion and muscle quality in target populations (e.g., athletes or elderly). These products are processed using techniques that often lead to low purity but competitive pricing. Despite their widespread use and [...] Read more.
Proteolytic products are extensively used in the nutraceutical sector to improve protein digestion and muscle quality in target populations (e.g., athletes or elderly). These products are processed using techniques that often lead to low purity but competitive pricing. Despite their widespread use and well-established production methods, the industry lacks standardized analytical methods for assessing these products and detecting potential fraud. This study proposes a comprehensive and harmonized pipeline for their analysis, which includes quantifying total soluble protein and proteolytic activity, as well as the determination of product stability and protein profile using SDS-PAGE and proteomic techniques. Despite the fact that protease extracts from pineapple had the highest protein content, most of the bromelain remained inactive, unlike in kiwi and papaya. SDS-PAGE revealed partial protein degradation of pineapple extracts, whereas kiwi extracts reflected a lower purification level but a higher protein integrity. The application of proteomic approaches strengthened the identification and origin tracing of the proteases. This study contributes to the development of a robust framework for analyzing proteolytic extracts, spanning from soluble protein quantification to protein profiling and activity determination. It may also ensure reliable supplier selection, high-quality manufacturing practices, and the implementation of optimal storage and formulation strategies in the nutraceutical industry. Full article
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Figure 1

Figure 1
<p>Total soluble protein in milligrams per gram of commercial product. (<b>A</b>) K, kiwi products; PAP, papaya products; P, pineapple products; and (<b>B</b>) F, Fig products.</p>
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<p>Proteolytic activity using as a substrate casein (<b>A</b>) or Z-L-Lys-ONp hydrochloride (<b>B</b>). K, kiwi products; PAP, papaya products; P, pineapple products; and F, Fig products. CDU, Casein Digestion Units. U, units.</p>
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<p>Specific proteolytic activity of fruit products using as a substrate casein (<b>A</b>) or Z-L-Lys-ONp hydrochloride (<b>B</b>). K, kiwi products; PAP, papaya products; P, pineapple products; and F, Fig products. CDU, Casein Digestion Units. U, units.</p>
Full article ">Figure 4
<p>Stability test in long-term conditions (25 °C, 60% relative humidity) of fruit proteolytic products (PPs) using casein assay during 6 months for K2 (<b>A</b>), F2 (<b>B</b>), P4 (<b>C</b>), and PAP2 (<b>D</b>). T1, 1 week. T2, 2 weeks. T3, 3 weeks. T4, 1 month. T5, 1.5 months. T6, 2 months. T7, 2.5 months. T8, 3 months. T9, 6 months. * <span class="html-italic">p</span> &lt; 0.001, significant difference with respect to T0. Horizontal bar to compare bars at both ends.</p>
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<p>SDS-PAGE fruit controls. (<b>A</b>) Lane 1. Protein Marker. Lane 2, Fig. Lane 3, Papaya. Lane 4, Pineapple Pulp. Lane 5, Pineapple Core. Lane 6, Pineapple Peel. (<b>B</b>) Lane 1, Protein Marker. Lane 2, Kiwi Green. Lane 3, Kiwi Gold. Code of colors: Purple, fig. Light yellow, pineapple. Bright yellow, kiwi gold. Green, kiwi green. Orange, papaya.</p>
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<p>SDS-PAGE pineapple products. (<b>A</b>) Protein Marker and pineapple product P4. (<b>B</b>) Pineapple product P5. (<b>C</b>) Pineapple product P2. (<b>D</b>) Pineapple product P6. Code of colors: Light yellow, pineapple.</p>
Full article ">Figure 7
<p>(<b>A</b>) Kiwi products SDS-PAGE. Lane 1 and 7, Protein Marker. Lane 2, Kiwi Product K2. Lane 3, Kiwi Product K4. Lane 4, Kiwi Product K3. Lane 5, Kiwi Product K5. Lane 6, Kiwi Product K6. (<b>B</b>) Fig product SDS-PAGE. Lane 1, Protein Marker. Lane 2, Fig product F2. (<b>C</b>) SDS-PAGE Papaya product. Lane 1, Protein Marker. Lane 2, Papaya product PAP1. (<b>D</b>) SDS-PAGE Papaya product. Lane 1, Papaya product PAP2. Lane 2, Protein Marker.</p>
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<p>Venn diagrams of identified protein of fruit (colored) and commercial products (grey) using proteomics. (<b>A</b>) Kiwi green. (<b>B</b>) Kiwi gold. (<b>C</b>) Fig. (<b>D</b>) Papaya. (<b>E</b>) Pineapple P4 (dark-yellow pineapple core and light-yellow pineapple pulp). (<b>F</b>) Pineapple P5 (dark-yellow pineapple core and light-yellow pineapple pulp). The common protein percentage in P4 and P5 is divided into pineapple pulp and pineapple core by a slash.</p>
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8 pages, 4098 KiB  
Article
Dietary Isoflavones Intake and Gastric Cancer
by Arianna Natale, Federica Fiori, Maria Parpinel, Claudio Pelucchi, Eva Negri, Carlo La Vecchia and Marta Rossi
Nutrients 2024, 16(16), 2771; https://doi.org/10.3390/nu16162771 - 20 Aug 2024
Viewed by 1066
Abstract
Dietary isoflavones have been associated with a lower risk of gastric cancer (GC), but the evidence for this association is still limited. We investigated the association between isoflavone intake and GC risk using data from a case–control study including 230 incident, histologically confirmed [...] Read more.
Dietary isoflavones have been associated with a lower risk of gastric cancer (GC), but the evidence for this association is still limited. We investigated the association between isoflavone intake and GC risk using data from a case–control study including 230 incident, histologically confirmed GC cases and 547 controls with acute, non-neoplastic conditions. Dietary information was collected through a validated food frequency questionnaire (FFQ) and isoflavone intake was estimated using ad hoc databases. We estimated the odds ratios (OR) and the corresponding 95% confidence intervals (CI) of GC using logistic regression models, including terms for total energy intake and other major confounders. The OR for the highest versus the lowest tertile of intake was 0.65 (95%CI = 0.44–0.97, p for trend = 0.04) for daidzein, 0.75 (95%CI = 0.54–1.11, p for trend = 0.15) for genistein, and 0.66 (95%CI = 0.45–0.99, p for trend = 0.05) for total isoflavones. Stratified analyses by sex, age, education, and smoking showed no heterogeneity. These findings indicate a favorable effect of dietary isoflavones on GC. Full article
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Figure 1
<p>Odds ratios <sup>a</sup> (OR) of gastric cancer and corresponding 95% confidence intervals (C) for the highest versus the lowest tertile of isoflavone intake in the strata of selected characteristics. Italy 1997–2007. <b><sup>a</sup></b> Derived from the logistic regression model adjusting for sex, age, education, year of interview, smoking status, and total energy intake.</p>
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13 pages, 1661 KiB  
Article
Optimization of Pectin Extraction from Melon Peel as a New Source of Pectin and Pectin Hydrolysate with Prebiotic Potential
by Saroya Bilraheem, Sirasit Srinuanpan, Benjamas Cheirsilp, Apichat Upaichit, Fusako Kawai and Uschara Thumarat
Foods 2024, 13(16), 2554; https://doi.org/10.3390/foods13162554 - 16 Aug 2024
Viewed by 1141
Abstract
Food wastes have a large number of functional ingredients that have potential for valorization. Melon peels are increasingly produced as waste in food industries in Thailand. This study aimed to optimize pectin extraction conditions from melon peel for its prebiotic potential. Optimization was [...] Read more.
Food wastes have a large number of functional ingredients that have potential for valorization. Melon peels are increasingly produced as waste in food industries in Thailand. This study aimed to optimize pectin extraction conditions from melon peel for its prebiotic potential. Optimization was conducted using a response surface methodology and Box–Behnken experimental design. An analysis of variance indicated a significant interaction between the extraction conditions on extraction yield and degree of esterification (DE). These include pH and solvent-to-sample ratio. The conditions for the extraction of pectin with low DE (LDP), medium DE (MDP) and high DE (HDP) were optimized. Pectin hydrolysate from LDP, MDP and HDP was prepared by enzymatic hydrolysis into LPEH, MPEH and HPEH, respectively. LDP, MDP, HDP, LPEH, MPEH and HPEH were compared for their efficiency in terms of the growth of three probiotic strains, namely Lactobacillus plantarum TISTR 877, Lactobacillus casei TISTR 390 and Enterococcus faecium TISTR 1027. Among the samples tested, HPEH showed the highest ability as a carbon source to promote the growth and prebiotic activity score for these three probiotic strains. This study suggests that melon peel waste from agro-industry can be a novel source for prebiotic production. Full article
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Graphical abstract

Graphical abstract
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<p>Three-dimensional response surface representations illustrating the impact of temperature (°C), extraction time (min), pH and the solvent-to-solid ratio (ml/g) on the extraction yield (%). The interactions are depicted in subfigures: (<b>A</b>) solvent-to-solid ratio vs. temperature; (<b>B</b>) solvent-to-solid ratio vs. extraction time; (<b>C</b>) pH vs. extraction time; (<b>D</b>) pH vs. temperature; (<b>E</b>) extraction time vs. temperature; and (<b>F</b>) solvent-to-solid ratio vs. pH.</p>
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<p>Three-dimensional response surface representations illustrating the impact of temperature (°C), extraction time (min), pH, and solvent-to-solid ratio (mL/g) on the extraction DE (%). The interactions are depicted in subfigures: (<b>A</b>) extraction time vs. temperature; (<b>B</b>) pH vs. temperature; (<b>C</b>) solvent-to-solid ratio vs. temperature; (<b>D</b>) pH vs. extraction time; (<b>E</b>) solvent-to-solid ratio vs. extraction time; and (<b>F</b>) solvent-to-solid ratio vs. pH.</p>
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<p>The prebiotic activity scores of bacterial cultures grown in MRS supplemented with 2% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) pectin (LDP, MDP, and HDP) or pectin enzyme hydrolysates (PEHs: LPEH, MPEH, and HPEH), as well as inulin, are presented. Data are shown from three independent repeats.</p>
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13 pages, 5475 KiB  
Article
Naringenin Promotes Gastrointestinal Motility in Mice by Impacting the SCF/c-Kit Pathway and Gut Microbiota
by Lei Wu, Yao Niu, Boyang Ren, Shengyu Wang, Yuhong Song, Xingyu Wang, Kai Zhao, Zhao Yue, Yaru Li and Jianhua Gao
Foods 2024, 13(16), 2520; https://doi.org/10.3390/foods13162520 - 12 Aug 2024
Viewed by 1418
Abstract
Naringenin (NRG) is widely found in citrus fruits and has anti-inflammatory, hypoglycemic, and immunomodulatory effects. Previous studies have shown that NRG promotes gastrointestinal motility in mice constipation models, but there are few systematic evaluations of its effects on normal animals. This study first [...] Read more.
Naringenin (NRG) is widely found in citrus fruits and has anti-inflammatory, hypoglycemic, and immunomodulatory effects. Previous studies have shown that NRG promotes gastrointestinal motility in mice constipation models, but there are few systematic evaluations of its effects on normal animals. This study first clarified the promotive effects of NRG on gastric emptying and small intestine propulsion (p < 0.01). NRG can also regulate the release of gastrointestinal hormones, including enhancing gastrin (GAS) and motilin (MTL) (p < 0.01), while reducing vasoactive intestinal peptide (VIP) secretion (p < 0.01). Using NRG to stimulate the isolated stomach, duodenum, and colon showed similar promotive effects to those observed in vivo (p < 0.01). A Western blot analysis indicated that this effect may be mediated by increasing the expression of stem cell factor (SCF) and its receptor (c-Kit) in these three segments, thus regulating their downstream pathways. It is worth noting that NRG can also increase the proportion of beneficial bacteria (Planococcaceae, Bacteroides acidifaciens, Clostridia_UCG-014) in the intestine and reduce the quantity of harmful bacteria (Staphylococcus). These findings provide a new basis for the application of NRG. Full article
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Figure 1

Figure 1
<p>Impact of varying concentrations of NRG on gastric emptying rate (<b>A</b>) and intestinal propulsive rate (<b>B</b>) in vivo. Statistical significance between the groups is indicated by the capital letters (<span class="html-italic">p</span> &lt; 0.01) and/or lowercase letters (<span class="html-italic">p</span> &lt; 0.05) above the bars. Each experimental group consisted of six mice.</p>
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<p>Impact of varying concentrations of NRG on the secretion of GAS (<b>A</b>), MTL (<b>B</b>), and VIP (<b>C</b>) in mouse serum after 7 d of administration. Statistical significance between the groups is indicated by the capital letters (<span class="html-italic">p</span> &lt; 0.01) and lowercase letters (<span class="html-italic">p</span> &lt; 0.05) above the bars. Each experimental group consisted of six mice.</p>
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<p>In vitro effects of high NRG concentrations on the contraction of isolated muscle strips from various gastrointestinal tissues (<b>A</b>) Stomach; (<b>B</b>) Duodenum; (<b>C</b>) Colon. Contraction activity is presented as a percentage (%) of the spontaneous activity relative to the negative control (NC, normalized to 100%). Statistical significance between the groups is indicated by the capital letters (<span class="html-italic">p</span> &lt; 0.01) above the bars. Each experimental group consisted of six mice.</p>
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<p>Western blotting analysis of SCF and c-Kit in the stomach (<b>A</b>,<b>B</b>), duodenum (<b>C</b>,<b>D</b>), and colon (<b>E</b>,<b>F</b>) tissues of each group. Statistical significance between the groups is indicated by the capital letters (<span class="html-italic">p</span> &lt; 0.01) and/or lowercase letters (<span class="html-italic">p</span> &lt; 0.05) above the bars. Each experimental group consisted of four mice.</p>
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<p>PCoA analysis of the OTU levels of gut microbiota. Each experimental group consisted of five mice.</p>
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<p>The variations in gut microbiota composition are displayed at the phylum (<b>A</b>), family (<b>B</b>), genus (<b>C</b>), and species levels (<b>D</b>), respectively. Each experimental group consisted of five mice.</p>
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<p>The linear discriminant analysis histogram of the control and NRG_H groups. Each experimental group consisted of five mice.</p>
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