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Nutrients, Volume 15, Issue 4 (February-2 2023) – 268 articles

Cover Story (view full-size image): The primary aim of this study was to assess the efficacy of an 8-week very low-calorie ketogenic diet (VLCKD) on non-alcoholic fatty liver disease (NAFLD) in subjects affected by overweight or obesity; hepatic steatosis was diagnosed by transient elastography (FibroScan), utilized as a point-of-care strategy in diagnostic procedures of patients with suspected NAFLD. CAP, the FibroScan parameter quantifying fatty liver accumulation, and fatty liver index (FLI), a benchmark of steatosis, revealed a significant decline after VLCKD. Moreover, hematic parameters such as fasting glucose, insulin, lipidic profile, ALT, γGT concentrations, as well as insulin resistance  (quantified by HOMAIR), were significantly lower after VLCKD. View this paper
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19 pages, 1647 KiB  
Article
Association of Plant-Based and High-Protein Diets with a Lower Obesity Risk Defined by Fat Mass in Middle-Aged and Elderly Persons with a High Genetic Risk of Obesity
by James W. Daily and Sunmin Park
Nutrients 2023, 15(4), 1063; https://doi.org/10.3390/nu15041063 - 20 Feb 2023
Cited by 4 | Viewed by 4232
Abstract
Obesity has become a severe public health challenge globally. The present study aimed to identify separate and interactive dietary, genetic, and other factors that increase the risk of obesity as measured by body fat (BF) mass. We utilized a genome-wide association study to [...] Read more.
Obesity has become a severe public health challenge globally. The present study aimed to identify separate and interactive dietary, genetic, and other factors that increase the risk of obesity as measured by body fat (BF) mass. We utilized a genome-wide association study to identify genetic variants associated with high fat mass (obesity; n = 10,502) and combined them to generate polygenic risk scores (PRS) of genetic variants interacting with each other in adults aged over 40 while excluding body-fat-related diseases in a city-hospital-based cohort (n = 53,828). It was validated in Ansan/Ansung plus rural cohorts (n = 13,007). We then evaluated dietary and lifestyle factors in subjects to assess what factors might help overcome a genetic propensity for higher BF. The three-SNP model included brain-derived neurotrophic factor (BDNF)_rs6265, fat-mass- and obesity-associated protein (FTO)_rs1421085, and SEC16B_rs509325. The genes with the minor alleles of ADCY3_rs6545790 and BAIAP2_rs35867081 increased their gene expression in the visceral and subcutaneous adipocytes, but their gene expression decreased in the hypothalamus in eQTL analysis. In the three-SNP model, the PRS was associated with BF mass by 1.408 and 1.396 times after adjusting covariates 1 (age, gender, survey year, residence area, education, and income) and 2 (covariates in model 1 plus energy intake, alcohol intake, regular exercise, and smoking status), respectively. However, when separating subjects by PRS of the three-SNP model, a plant-based diet was the most significant factor associated with low BF, followed by high-protein diets and lower energy intakes. They could offset the effects of high genetic risk for high BF. In conclusion, modulating nutrient intakes might overcome a high genetic risk for obesity. Dietary choices favoring more plant-based and higher-protein foods might help prevent increased BF in Asians and potentially people of other ethnicities with high polygenetic risk scores. Full article
(This article belongs to the Special Issue Nutrigenomic and Metabolism)
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<p>The scheme of searching the genetic variants related to body fat mass and polygenic risk factor (PRS) of the selected genetic variants’ interaction with lifestyles. <sup>1</sup> High body fat mass (obesity) was defined as body fat higher than 25% and 30% of body weight for men and women, respectively. <sup>2</sup> Covariates included age, gender, residence area, survey year, daily energy intake, and education and income levels. <sup>3</sup> Covariates for model 1 were age, gender, residence area, survey year, education, and income; those for model 2 were covariates for model 1 plus energy intake, alcohol intake, regular exercise, and smoking status.</p>
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<p>Distribution of genetic variants for high body fat mass risk by genome-wide association study. (<b>A</b>) Manhattan plot of the <span class="html-italic">p</span>-value of genetic variants for high body fat risk. Red-dot and blue-dot lines indicate the <span class="html-italic">p</span>-value of 5 × 10<sup>−8</sup> and 5 × 10<sup>−5</sup>. (<b>B</b>) Q–Q plot of observed and expected <span class="html-italic">p</span>-values for body fat risk. Red and black lines represent theoretical and actual distributions, respectively.</p>
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<p>Gene expression according to the alleles of the selected SNPs for high body fat risk in different tissues. (<b>A</b>) <span class="html-italic">ADCY3</span>_rs6545790 in visceral adipose tissues (slope of the SNP alleles = 0.21, <span class="html-italic">p</span> = 4.1 × 10<sup>−14</sup>). (<b>B</b>) <span class="html-italic">ADCY3</span>_rs6545790 in subcutaneous adipose tissues (slope of the SNP alleles = 0.23, <span class="html-italic">p</span> = 2.2 × 10<sup>−19</sup>). (<b>C</b>) <span class="html-italic">ADCY3</span>_rs6545790 in the amygdala (slope of the SNP alleles = −0.18, <span class="html-italic">p</span> = 0.0064). (<b>D</b>) <span class="html-italic">ADCY3</span>_rs6545790 in the brain cortex (slope of the SNP alleles = −0.28, <span class="html-italic">p</span> = 5.4 × 10<sup>−10</sup>). (<b>E</b>) <span class="html-italic">SEC16B</span>_rs509325 in the adrenal gland (slope of the SNP alleles = 0.24, <span class="html-italic">p</span> = 0.0026). (<b>F</b>) <span class="html-italic">BAIAP2</span>_rs35867081 in subcutaneous adipose tissues (slope of the SNP alleles = 0.066, <span class="html-italic">p</span> = 0.025). (<b>G</b>) <span class="html-italic">BAIAP2</span>_rs35867081 in the hippocampus (slope of the SNP alleles = 0.066, <span class="html-italic">p</span> = 0.025). (<b>H</b>) <span class="html-italic">FARP1</span>_rs587056 in the hypothalamus (slope of the SNP alleles = −0.19, <span class="html-italic">p</span> = 0.00072).</p>
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<p>Adjusted odds ratio (ORs) and 95% confidence intervals (CI) of three-SNP PRS and six-SNP PRS for obesity defined with body fat mass. PRS was generated with the sum of the number of risk alleles in each SNP, and it was classified as low PRS, medium PRS, and high PRS according to the PRS was 0–2, 3–4, and ≥5 in the three-SNP model and 0–5, 6–7, and ≥8 in the six-SNP model, respectively. Models 1 and 2 were conducted with different covariates. Covariates were age, gender, residence area, education, and income for models 1 and 2 plus energy intake, alcohol intake, regular exercise, and smoking status.</p>
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<p>Percentage of the participants with high body fat mass. (<b>A</b>) According to energy intake. (<b>B</b>) According to protein intake. (<b>C</b>) According to a plant-based diet.</p>
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<p>Percentage of the participants with high body fat mass. (<b>A</b>) According to energy intake. (<b>B</b>) According to protein intake. (<b>C</b>) According to a plant-based diet.</p>
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17 pages, 1409 KiB  
Brief Report
The Healthy Eating Assessment Tool (HEAT): A Simplified 10-Point Assessment of CHILD-2 Dietary Compliance for Children and Adolescents with Dyslipidemia
by Sara DiLauro, Jonathan P. Wong, Tanveer Collins, Nita Chahal and Brian W. McCrindle
Nutrients 2023, 15(4), 1062; https://doi.org/10.3390/nu15041062 - 20 Feb 2023
Cited by 1 | Viewed by 4704
Abstract
Traditional dietary assessment tools used to determine achievement of cholesterol-lowering dietary targets, defined in the Cardiovascular Health Integrated Lifestyle Diet (CHILD-2), are time intensive. We sought to determine the utility of the Healthy Eating Assessment Tool (HEAT), a simplified 10-point dietary assessment tool, [...] Read more.
Traditional dietary assessment tools used to determine achievement of cholesterol-lowering dietary targets, defined in the Cardiovascular Health Integrated Lifestyle Diet (CHILD-2), are time intensive. We sought to determine the utility of the Healthy Eating Assessment Tool (HEAT), a simplified 10-point dietary assessment tool, in relation to meeting dietary cut points of the CHILD-2, as well as its association with markers of adiposity and lipid variables. We performed a 2-year single-center, prospective cross-sectional study of pediatric patients with dyslipidemia. HEAT score associations with meeting CHILD-2 fat targets were modest. Only patients with the highest HEAT scores (good 43%, excellent 64%) met the CHILD-2 cut point of <25% total fat calories (p = 0.03), with a non-significant trend for limiting the percentage of daily saturated fat to <8% (excellent 64%), and no association with cholesterol intake. There were more consistent associations with markers of adiposity (body mass index z-score r = −0.31, p = <0.01 and waist-to-height ratio r = −0.31, p = <0.01), and there was no independent association with lipid levels. While fat-restricted diets are safe, they are not particularly effective for treatment of dyslipidemia or for weight management alone. The HEAT may be a more useful and simplified way of assessing and tracking broader dietary goals in clinical practice. Full article
(This article belongs to the Special Issue Advances in Pediatric Cardiology Nutrition)
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<p>The Healthy Eating Assessment Tool (HEAT).</p>
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<p>Percent of Patients Within Each HEAT Score Category Who Meet CHILD-2 Targets for Fat and Cholesterol Intake.</p>
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<p>Association of HEAT Score Category with Markers of Adiposity. Box plots with boxes enclose the 25th–75th percentiles, with the line indicating the median and the diamond indicating the mean values, and the whiskers indicating the minimum and maximum values.</p>
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16 pages, 365 KiB  
Article
Fatty Acid Indices and the Nutritional Properties of Karakul Sheep Meat
by Otilia Cristina Murariu, Florin Murariu, Gabriela Frunză, Marius Mihai Ciobanu and Paul Corneliu Boișteanu
Nutrients 2023, 15(4), 1061; https://doi.org/10.3390/nu15041061 - 20 Feb 2023
Cited by 19 | Viewed by 3634
Abstract
This study aimed to evaluate the fatty acid profile and health lipid indices of sheep meat (from 52 Karakul sheep from NE Romania). The effect of age at slaughter and the influence of muscle region were studied for nutritional parameters, especially the fatty [...] Read more.
This study aimed to evaluate the fatty acid profile and health lipid indices of sheep meat (from 52 Karakul sheep from NE Romania). The effect of age at slaughter and the influence of muscle region were studied for nutritional parameters, especially the fatty acids from lipid fractions. Based on the fatty acid profiles and lipid contents, the sanogenic indices were determined for two sheep muscle groups. Thus, two different muscle regions from lamb and adult sheep were analysed from both genders, the Longissimus dorsi and Triceps brachii, to argue the advantages of each category and the rationalization, in terms of meat consumption, regarding their impact on human health. Sheep meat has many components with beneficial effects on human health. Apart from the fact that it is an important source of nutrients due to its high content of proteins, lipids, and minerals, it is also a product that can provide fundamental bioactive compounds for maintaining metabolic functions. The qualitative indices assessment revealed that lambs have meat with high PUFA content on Longissimus dorsi muscles (approx. 25% of total fatty acids), 0.68 for PUFA/SFA, with highest values for n-3 (approx. 8%) and n-6 (approx. 14%). Appropriate values can also be observed in Triceps brachii muscles from adult sheep. The sanogenic indices also presented good values for Longissimus dorsi from lambs and Triceps brachii from adult sheep (polyunsaturation index = 7.2–10.2; atherogenic index = 0.56–0.67; thrombogenic index = 0.78–0.96; hypocholesterolemic/hypercholesterolemic index = 2.4–2.7 (for Longissimus dorsi)). Full article
(This article belongs to the Topic Applied Sciences in Functional Foods - 2nd Volume)
17 pages, 755 KiB  
Article
Does Better Diet Quality Offset the Association between Depression and Metabolic Syndrome?
by In Seon Kim and Ji-Yun Hwang
Nutrients 2023, 15(4), 1060; https://doi.org/10.3390/nu15041060 - 20 Feb 2023
Cited by 1 | Viewed by 3029
Abstract
Several studies have shown that depression increases the risk of metabolic syndrome (MetS), which is often exacerbated by the fact that both exist concurrently. People with depression are more likely to have unhealthy eating habits, which can eventually trigger the development of MetS. [...] Read more.
Several studies have shown that depression increases the risk of metabolic syndrome (MetS), which is often exacerbated by the fact that both exist concurrently. People with depression are more likely to have unhealthy eating habits, which can eventually trigger the development of MetS. This study was to investigate whether diet quality modifies the association between depression and MetS in a total of 13,539 Korean adults aged 19 to 80 from 2014, 2016 and 2018 Korean National Health and Nutrition Examination Surveys. Depression was assessed by the Patient Health Questionnaire-9 (PHQ-9) and subjects were divided into subgroups according to the PHQ-9 scores: normal (<5), mild (5–9), and moderate-to-severe (≥10) groups. Diet quality was measured by the Korean Healthy Eating Index (KHEI). A complex sample multiple logistic regression stratified by tertiles of KHEI scores was used to explore whether diet quality modifies an association between depression severity and metabolic syndrome. Depression severity was positively associated with the risk of MetS (p trend = 0.006) after adjustment for potential confounders. Only the lowest diet quality, moderately-to-severely depressed group, showed a higher risk of MetS (OR: 1.72, 95% CI: 1.24–2.40) compared to the normal group. Our results suggest that healthy diet quality could offset the positive relationship between depression and MetS in the general Korean adult population. Encouraging a healthy diet regime can improve not only physical health but also the mental state of the general public. Full article
(This article belongs to the Special Issue Dietary Intake and Health throughout the Life Cycle)
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<p>Adjusted odds ratios of metabolic syndrome (<b>a</b>), abdominal obesity <b>(b</b>), and low HDL-cholesterol (<b>c</b>) according to depression severity after stratified by diet quality based on results of <a href="#nutrients-15-01060-t005" class="html-table">Table 5</a>. The reference group was a normal group of each diet quality level. PHQ-9: Patient Health Questionnaire-9. PHQ-9 depression severity was divided by total scores of PHQ-9: normal, mild, moderate, to severe. KHEI: Korean Healthy Eating Index. Diet quality level was divided into tertiles by total scores of KHEI: Low (T1), Medium (T2), and High (T3). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>A framework of mediation analysis. OR: odds ratios. X: independent variable. M: mediating variable.</p>
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16 pages, 2027 KiB  
Article
Short-Term Intake of Theobroma grandiflorum Juice Fermented with Lacticaseibacillus rhamnosus ATCC 9595 Amended the Outcome of Endotoxemia Induced by Lipopolysaccharide
by Adrielle Zagmignan, Yasmim Costa Mendes, Gabrielle Pereira Mesquita, Gabrielle Damasceno Costa dos Santos, Lucas dos Santos Silva, Amanda Caroline de Souza Sales, Simeone Júlio dos Santos Castelo Branco, Alexsander Rodrigues Carvalho Junior, José Manuel Noguera Bazán, Edinalva Rodrigues Alves, Bárbara Lima de Almeida, Anne Karoline Maiorana Santos, Wellyson da Cunha Araújo Firmo, Maria Raimunda Chagas Silva, Antônio José Cantanhede Filho, Rita de Cássia Mendonça de Miranda and Luís Cláudio Nascimento da Silva
Nutrients 2023, 15(4), 1059; https://doi.org/10.3390/nu15041059 - 20 Feb 2023
Cited by 6 | Viewed by 2256
Abstract
Endotoxemia is a condition caused by increasing levels of lipopolysaccharide (LPS) characterized by an impaired systemic response that causes multiple organ dysfunction. Lacticaseibacillus rhamnosus ATCC 9595 is a strain with probiotic potential which shows immunomodulatory properties. The incorporation of this bacterium in food [...] Read more.
Endotoxemia is a condition caused by increasing levels of lipopolysaccharide (LPS) characterized by an impaired systemic response that causes multiple organ dysfunction. Lacticaseibacillus rhamnosus ATCC 9595 is a strain with probiotic potential which shows immunomodulatory properties. The incorporation of this bacterium in food rich in bioactive compounds, such as cupuaçu juice (Theobroma grandiflorum), could result in a product with interesting health properties. This work evaluated the effects of the oral administration of cupuaçu juice fermented with L. rhamnosus on the outcome of LPS-induced endotoxemia in mice. C57BL/6 mice (12/group) received oral doses (100 µL) of saline solution and unfermented or fermented cupuaçu juice (108 CFU/mL). After 5 days, the endotoxemia was induced by an intraperitoneal injection of LPS (10 mg/kg). The endotoxemia severity was evaluated daily using a score based on grooming behavior, mobility, presence of piloerection, and weeping eyes. After 6 h and 120 h, the mice (6/group) were euthanized for analysis of cell counts (in peritoneal lavage and serum) and organ weight. L. rhamnosus grew in cupuaçu juice and produced organic acids without the need for supplementation. The bacteria counts were stable in the juice during storage at 4 °C for 28 days. The fermentation with L. rhamnosus ATCC 9595 changed the metabolites profile of cupuaçu juice due to the biotransformation and enhancement of some compounds. In general, the administration of L. rhamnosus-fermented juice allowed a significant improvement in several characteristics of endotoxemic status (weight loss, hypothermia, severity index, cell migration). In addition, treatment with fermented juice significantly reduced the weight of the spleen, liver, intestine, and kidneys compared to the saline-treated endotoxemic group. Taken together, our data show that short-term intake therapy of cupuaçu juice fermented with L. rhamnosus ATCC 9595 can reduce systemic inflammation in an experimental model of LPS-induced endotoxemia in mice. Full article
(This article belongs to the Special Issue Role of Lactobacillus and Probiotics in Human Health and Diseases)
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<p>Growth and production of lactic acid by <span class="html-italic">Lacticaseibacillus rhamnosus</span> in cupuaçu juice. (A) Survival of <span class="html-italic">L. rhamnosus</span> ATCC 9595 in the fermentations of cupuaçu juice by <span class="html-italic">L. rhamnosus</span> ATCC 9595 during the storage period. (<b>B</b>) Response surface obtained for RVpH as a function of pulp and inoculum concentrations in cupuaçu juice fermentations by <span class="html-italic">L. rhamnosus</span> ATCC 9595. (<b>C</b>) Response surface obtained for lactic acid concentration as a function of pulp and inoculum concentrations in cupuaçu juice fermentations by <span class="html-italic">L. rhamnosus</span> ATCC 9595.</p>
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<p>Comparative chromatograms of the ethyl acetate phase of cupuaçu juice (<span class="html-italic">Theobroma grandiflorum</span>) with and without fermentation by <span class="html-italic">Lacticaseibacillus rhamnosus</span> ATCC 9595.</p>
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<p>Effects of fermented and unfermented <span class="html-italic">Theobroma grandiflorum</span> juice on some pathologic parameters associated with LPS-mediated endotoxemia. (<b>A</b>) Kinects of variation of severity score; (<b>B</b>) Area under curve from data of severity score analysis; (<b>C</b>) Kinects of variation of weight loss; (<b>D</b>) Area under curve from data of weight loss analysis; (<b>E</b>) Kinects of variation of body temperature reduction; (<b>F</b>) Area under curve from data of body temperature reduction analysis. * Significant differences with <span class="html-italic">p</span> &lt; 0.05; *** Significant differences with <span class="html-italic">p</span> &lt; 0.0001. LPS: mice submitted to LPS-mediated endotoxemia; LPS + CUP: mice treated with unfermented <span class="html-italic">T. grandiflorum</span> juice and submitted to LPS-mediated endotoxemia; LPS + Lrh-CUP: mice treated with <span class="html-italic">L. rhamnosus</span>-fermented <span class="html-italic">T. grandiflorum</span> juice and submitted to LPS-mediated endotoxemia.</p>
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<p>Effects of fermented and unfermented <span class="html-italic">Theobroma grandiflorum</span> juice on the weight of some organs of mice submitted to LPS-mediated endotoxemia. (<b>A</b>) Spleen; (<b>B</b>) Liver; (<b>C</b>) Gut; (<b>D</b>) Kidneys. * Significant differences with <span class="html-italic">p</span> &lt; 0.05; ** Significant differences with <span class="html-italic">p</span> &lt; 0.01; *** Significant differences with <span class="html-italic">p</span> &lt; 0.0001. LPS: mice submitted to LPS-mediated endotoxemia; LPS + CUP: mice treated with unfermented <span class="html-italic">T. grandiflorum</span> juice and submitted to LPS-mediated endotoxemia; LPS + Lrh-CUP: mice treated with <span class="html-italic">L. rhamnosus</span>-fermented <span class="html-italic">T. grandiflorum</span> juice and submitted to LPS-mediated endotoxemia.</p>
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<p>Effects of fermented and unfermented <span class="html-italic">Theobroma grandiflorum</span> juice in the migration of cells to the peritoneal cavity in mice submitted to LPS-mediated endotoxemia. (<b>A</b>) Total leukocytes in the peritoneal cavity after 6 h of LPS-mediated endotoxemia; (<b>B</b>) Polymorphonuclear leukocytes in the peritoneal cavity after 6 h of LPS-mediated endotoxemia; (<b>C</b>) Mononuclear cells in the peritoneal cavity after 6 h of LPS-mediated endotoxemia; (<b>D</b>) Total leukocytes in the peritoneal cavity after 120 h of LPS-mediated endotoxemia; (<b>E</b>) Polymorphonuclear leukocytes in the peritoneal cavity after 120 h of LPS-mediated endotoxemia; (<b>F</b>) Mononuclear cells in the peritoneal cavity after 120 h of LPS-mediated endotoxemia. * Significant differences with <span class="html-italic">p</span> &lt; 0.05; ** Significant differences with <span class="html-italic">p</span> &lt; 0.01; *** Significant differences with <span class="html-italic">p</span> &lt; 0.0001. LPS: mice submitted to LPS-mediated endotoxemia; LPS + CUP: mice treated with unfermented <span class="html-italic">T. grandiflorum</span> juice and submitted to LPS-mediated endotoxemia; LPS + Lrh-CUP: mice treated with <span class="html-italic">L. rhamnosus</span>-fermented <span class="html-italic">T. grandiflorum</span> juice and submitted to LPS-mediated endotoxemia.</p>
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<p>Effects of fermented and unfermented <span class="html-italic">Theobroma grandiflorum</span> juice in leukocytes population in the blood of mice submitted to LPS-mediated endotoxemia. (<b>A</b>) Total leukocytes in the peritoneal cavity after 6 h of LPS-mediated endotoxemia; (<b>B</b>) Polymorphonuclear leukocytes in the peritoneal cavity after 6 h of LPS-mediated endotoxemia; (<b>C</b>) Mononuclear cells in the peritoneal cavity after 6 h of LPS-mediated endotoxemia; (<b>D</b>) Total leukocytes in the peritoneal cavity after 120 h of LPS-mediated endotoxemia; (<b>E</b>) Polymorphonuclear leukocytes in the peritoneal cavity after 120 h of LPS-mediated endotoxemia; (<b>F</b>) Mononuclear cells in the peritoneal cavity after 120 h of LPS-mediated endotoxemia. * Significant differences with <span class="html-italic">p</span> &lt; 0.05; ** Significant differences with <span class="html-italic">p</span> &lt; 0.01; *** Significant differences with <span class="html-italic">p</span> &lt; 0.0001. LPS: mice submitted to LPS-mediated endotoxemia; LPS + CUP: mice treated with unfermented <span class="html-italic">T. grandiflorum</span> juice and submitted to LPS-mediated endotoxemia; LPS + Lrh-CUP: mice treated with <span class="html-italic">L. rhamnosus</span>-fermented <span class="html-italic">T. grandiflorum</span> juice and submitted to LPS-mediated endotoxemia.</p>
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12 pages, 272 KiB  
Article
The Ketogenic Diet in Children with Epilepsy: A Focus on Parental Stress and Family Compliance
by Francesca Felicia Operto, Angelo Labate, Salvatore Aiello, Cristina Perillo, Valeria de Simone, Rosetta Rinaldi, Giangennaro Coppola and Grazia Maria Giovanna Pastorino
Nutrients 2023, 15(4), 1058; https://doi.org/10.3390/nu15041058 - 20 Feb 2023
Cited by 17 | Viewed by 3781
Abstract
(1) Background: The aim of our study was to evaluate parental stress after 6 and 12 months of a ketogenic diet, considering demographic and clinical variables (epilepsy type, epilepsy duration, seizure number, antiseizure medications, comorbidities, efficacy, and adverse events). (2) Methods: We consecutively [...] Read more.
(1) Background: The aim of our study was to evaluate parental stress after 6 and 12 months of a ketogenic diet, considering demographic and clinical variables (epilepsy type, epilepsy duration, seizure number, antiseizure medications, comorbidities, efficacy, and adverse events). (2) Methods: We consecutively enrolled 36 children aged between 3 and 10 years who had been diagnosed with various types of drug-resistant epilepsy and who were in therapy with a ketogenic diet for better seizure control. A standardized neuropsychological questionnaire (Parenting Stress Index–PSI) was administered to the parents evaluating parental stress at baseline (T0), after 6 (T1) months, and after 12 months (T2). (3) Results: After 6 and 12 months of dietary treatment, Parental Distress and Total Stress mean scores were statistically significantly increased. Post hoc analysis showed no significant changes in the scores between T0 and T1, although there was a significant increase between T1 and T2. We did not find statistically significant relationships between parental stress and the other variables considered. (4) Conclusions: The ketogenic diet can be challenging for parents and can affect the perception of parental stress, especially in the long term. Parents may feel inadequate in their role; therefore, they should be helped and encouraged through additional supports in order to maximize the adherence to diet therapy. Full article
(This article belongs to the Section Pediatric Nutrition)
18 pages, 8430 KiB  
Article
No Evidence of a Genetic Causal Relationship between Ankylosing Spondylitis and Gut Microbiota: A Two-Sample Mendelian Randomization Study
by Mingyi Yang, Xianjie Wan, Haishi Zheng, Ke Xu, Jiale Xie, Hui Yu, Jiachen Wang and Peng Xu
Nutrients 2023, 15(4), 1057; https://doi.org/10.3390/nu15041057 - 20 Feb 2023
Cited by 48 | Viewed by 8893
Abstract
Objective: Ankylosing spondylitis (AS) is associated with a variety of gut microbiotas. We aim to analyze the causal relationship between the two at the genetic level. Methods: Mendelian randomization (MR) is a type of instrumental variables (IVs) analysis; MR follows the Mendelian genetic [...] Read more.
Objective: Ankylosing spondylitis (AS) is associated with a variety of gut microbiotas. We aim to analyze the causal relationship between the two at the genetic level. Methods: Mendelian randomization (MR) is a type of instrumental variables (IVs) analysis; MR follows the Mendelian genetic rule of “parental alleles are randomly assigned to offspring” and takes genetic variation as IVs to infer the causal association between exposure factors and study outcome in observational studies. Genome-wide association study (GWAS) summary data of AS were from the FinnGen consortium, and the gut microbiota (Bacteroides, Streptococcus, Proteobacteria, Lachnospiraceae) were from the MiBioGen consortium. The TwoSampleMR and MRPRESSO packages of the R were used to perform a two-sample MR study. Random-effects inverse variance weighted (IVW) was the main analysis method, and MR Egger, weighted median, simple mode, and weighted mode were used as supplementary methods. We examined heterogeneity and horizontal pleiotropy, and examined whether the analysis results were influenced by a single SNP. We applied radial variants of the IVW and MR-Egger model for the improved visualization of the causal estimate. We further examined the causal relationship between AS and gut microbiota, and the robustness of the analysis results. Finally, we performed maximum likelihood, penalized weighted median, and IVW (fixed effects) to further identify the potential causal association. Results: The random-effects IVW results showed that Bacteroides (p = 0.965, OR 95% confidence interval [CI] = 0.990 [0.621–1.579]), Streptococcus (p = 0.591, OR 95% CI = 1.120 [0.741–1.692]), Proteobacteria (p = 0.522, OR 95% CI = 1.160 [0.737–1.826]), and Lachnospiraceae (p = 0.717, OR 95% CI = 1.073 [0.732–1.574]) have no genetic causal relationship with AS. There was no heterogeneity, horizontal pleiotropy or outliers, and results were normally distributed. The MR analysis results were not driven by a single SNP. Conclusions: This study showed that Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae, four common gut microbiotas associated with AS, had no causal relationship with AS at the genetic level. This study makes a positive contribution to the genetics of AS, but the insufficient number of gut microbiota included is a limitation. Full article
(This article belongs to the Section Nutrigenetics and Nutrigenomics)
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<p>MR analysis between the gut microbiota (Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae) and ankylosing spondylitis. Five methods: random-effects IVW, MR Egger, weighted median, simple mode, and weighted mode.</p>
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<p>Scatter plot of MR analysis. (<b>A</b>) Bacteroides and ankylosing spondylitis; (<b>B</b>) Streptococcus and ankylosing spondylitis; (<b>C</b>) Proteobacteria and ankylosing spondylitis; (<b>D</b>) Lachnospiraceae and ankylosing spondylitis.</p>
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<p>“Leave one out” analysis. The red lines are the analysis results of random effects IVW. (<b>A</b>) Bacteroides and ankylosing spondylitis; (<b>B</b>) Streptococcus and ankylosing spondylitis; (<b>C</b>) Proteobacteria and ankylosing spondylitis; (<b>D</b>) Lachnospiraceae and ankylosing spondylitis.</p>
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<p>The MR estimate visualizes the radial plot of a single outlier SNPs, and the curve shows the ratio estimate of each SNP. Black dots show valid SNPs. (<b>A</b>) MR radial plots of Bacteroides and ankylosing spondylitis; (<b>B</b>) MR radial plots of Streptococcus and ankylosing spondylitis; (<b>C</b>) MR radial plots of Proteobacteria and ankylosing spondylitis; (<b>D</b>) MR radial plots of Lachnospiraceae and ankylosing spondylitis.</p>
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<p>The normal distribution plots of MR analysis for gut microbiota and ankylosing spondylitis. (<b>A</b>) Bacteroides and ankylosing spondylitis; (<b>B</b>) Streptococcus and ankylosing spondylitis; (<b>C</b>) Proteobacteria and ankylosing spondylitis; (<b>D</b>) Lachnospiraceae and ankylosing spondylitis.</p>
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<p>The MR analysis between gut microbiota (Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae) and ankylosing spondylitis. Three methods: maximum likelihood, penalized weighted median and IVW (fixed effects).</p>
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<p>MR analysis of the Proteobacteria and ankylosing spondylitis after exclusion of one outlier SNP (rs11715072). (<b>A</b>) Scatter plot; (<b>B</b>) “Leave one out” analysis, the red lines are the analysis results of random effects IVW; (<b>C</b>) MR radial plots; (<b>D</b>) the normal distribution plots.</p>
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<p>MR analysis of the Proteobacteria and ankylosing spondylitis after exclusion of one outlier SNP (rs11715072). Nine methods: MR Egger, weighted median, random-effects IVW, simple mode, weighted mode, MR-RAPS, maximum likelihood, penalized weighted median, and IVW (fixed effects).</p>
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3 pages, 213 KiB  
Editorial
Impact of Different Nutrition Strategies on Patients with Inflammatory Bowel Disease (IBD)
by Konstantinos Papadimitriou and Sousana K. Papadopoulou
Nutrients 2023, 15(4), 1056; https://doi.org/10.3390/nu15041056 - 20 Feb 2023
Cited by 2 | Viewed by 1621
Abstract
In 1932, Burrill B [...] Full article
15 pages, 859 KiB  
Article
School Lunch Programs and Nutritional Education Improve Knowledge, Attitudes, and Practices and Reduce the Prevalence of Anemia: A Pre-Post Intervention Study in an Indonesian Islamic Boarding School
by Rimbawan Rimbawan, Reisi Nurdiani, Purnawati Hustina Rachman, Yuka Kawamata and Yoshizu Nozawa
Nutrients 2023, 15(4), 1055; https://doi.org/10.3390/nu15041055 - 20 Feb 2023
Cited by 8 | Viewed by 5657
Abstract
Indonesians face serious health issues that arise from malnutrition, particularly in children who are under unfavorable dietary environments. The present study established a school meal program consisting of dietary and educational interventions and evaluated its impact on promoting continuous improvement in dietary behavior [...] Read more.
Indonesians face serious health issues that arise from malnutrition, particularly in children who are under unfavorable dietary environments. The present study established a school meal program consisting of dietary and educational interventions and evaluated its impact on promoting continuous improvement in dietary behavior among junior and senior high school students in Indonesia. A total of 319 students belonging to an Islamic Boarding School participated in the pre-post intervention study for 9 months. All participants were assessed based on their Knowledge, Attitude, and Practice (KAP). A subgroup of 115 participants who were anemic and underweight was examined for dietary intake, nutrition status, and hemoglobin level. The KAP test scores for both nutrition and hygiene showed a significant increase for all students and the undernutrition group post-intervention. Protein, iron, and vitamin C intake significantly improved. Although there were no significant improvements in nutrition status, there was a significant increase in the hemoglobin level and a reduction in the prevalence of anemia from 42.6% to 21.7%. Thus, school meal program that combines dietary and educational interventions may effectively improve anemia in undernourished students as well as enhance the knowledge, attitudes, and practices related to health, nutrition, and hygiene in junior and senior high school students. Full article
(This article belongs to the Section Nutritional Policies and Education for Health Promotion)
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<p>Changes of percentage of anemic and non-anemic students in the subgroup.</p>
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<p>Changes in nutritional status of students.</p>
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18 pages, 1645 KiB  
Article
Effects of Endurance Exercise Intensities on Autonomic and Metabolic Controls in Children with Obesity: A Feasibility Study Employing Online Exercise Training
by Valeria Calcaterra, Giuseppina Bernardelli, Mara Malacarne, Matteo Vandoni, Savina Mannarino, Vittoria Carnevale Pellino, Cristiana Larizza, Massimo Pagani, Gianvincenzo Zuccotti and Daniela Lucini
Nutrients 2023, 15(4), 1054; https://doi.org/10.3390/nu15041054 - 20 Feb 2023
Cited by 2 | Viewed by 2677
Abstract
Exercise is one of the major determinants of a healthy lifestyle, which is particularly important in childhood and serves as a powerful preventive tool. On the other hand, obesity and arterial hypertension rates are increasing in children, representing a huge risk for developing [...] Read more.
Exercise is one of the major determinants of a healthy lifestyle, which is particularly important in childhood and serves as a powerful preventive tool. On the other hand, obesity and arterial hypertension rates are increasing in children, representing a huge risk for developing major cardiovascular and metabolic diseases in adult life. Of fundamental importance is the modality and volume of exercise required to obtain benefits. In this feasibility study, we considered a group of obese children, studied before and after a 12-week online exercise training program, and subdivided the participants into two groups considering the volume of exercise performed (above or below 1200 MET·min/week). This threshold level was applied in two different ways: subdivision A considered the total weekly physical activity volume (considering both time spent walking for at least 10 min consecutively and time spent performing structured exercise) and subdivision B considered only the weekly volume of structured exercise. We assessed autonomic and metabolic control and auxological and lifestyle parameters. We observed that the improved volume of structured exercise was associated with reduced arterial pressure percentile only in subdivision B and an improvement in markers of vagal and metabolic control was evident. Moreover, the 12-week online exercise training program, defined considering individual fitness level and progressively adapted as the goal was reached, proved to be sustainable from an economical and organizational point of view. Full article
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<p>Exercise program.</p>
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11 pages, 242 KiB  
Article
The Complexities of Managing Gestational Diabetes in Women of Culturally and Linguistically Diverse Backgrounds: A Qualitative Study of Women’s Experiences
by Melissa Oxlad, Sharni Whitburn and Jessica A. Grieger
Nutrients 2023, 15(4), 1053; https://doi.org/10.3390/nu15041053 - 20 Feb 2023
Cited by 4 | Viewed by 9622
Abstract
Aim: This study aimed to explore women’s perspectives and experiences concerning how culture impacts the lifestyle management of gestational diabetes mellitus (GDM) in women of culturally and linguistically diverse (CALD) backgrounds. Methods: Women of any cultural background diagnosed with GDM within the previous [...] Read more.
Aim: This study aimed to explore women’s perspectives and experiences concerning how culture impacts the lifestyle management of gestational diabetes mellitus (GDM) in women of culturally and linguistically diverse (CALD) backgrounds. Methods: Women of any cultural background diagnosed with GDM within the previous 12 months were purposively recruited from two Australian metropolitan hospitals. Data collected using semi-structured interviews (n = 18) and focus groups (n = 15 women in three groups) were analysed using reflexive thematic analysis. Results: Three themes were generated: “cultural beliefs and obligations impact lifestyle management of gestational diabetes”, which describes how some cultures lack awareness about GDM, and modifications or restrictions were viewed as depriving the infant, but sometimes adaptions could be made so that a culturally appropriate meal was suitable for GDM management; “the relationship between cultural foods and gestational diabetes management”, which discusses how important cultural foods may be incompatible with appropriate GDM management, so women worked to find solutions; “gestational diabetes education lacks cultural awareness and sensitivity”, which illustrates how current education fails to address differences in cultural beliefs, language and eating practices. Conclusion: Cultural beliefs, obligations and food practices must be considered when assisting women of CALD backgrounds using lifestyle modification to manage GDM. GDM education must be culturally sensitive and competent and, where possible, be delivered by health professionals of a shared cultural group. Full article
28 pages, 3268 KiB  
Review
COVID-19 in Pregnancy: Influence of Body Weight and Nutritional Status on Maternal and Pregnancy Outcomes—A Review of Literature and Meta-Analysis
by Rossella Attini, Maria Elena Laudani, Elisabetta Versino, Alessio Massaro, Arianna Pagano, Francesca Petey, Alberto Revelli and Bianca Masturzo
Nutrients 2023, 15(4), 1052; https://doi.org/10.3390/nu15041052 - 20 Feb 2023
Cited by 1 | Viewed by 2503
Abstract
In the last two and a half years, COVID-19 has been one of the most challenging public health issues worldwide. Based on the available evidence, pregnant women do not appear to be more susceptible to infection than the general population but having COVID-19 [...] Read more.
In the last two and a half years, COVID-19 has been one of the most challenging public health issues worldwide. Based on the available evidence, pregnant women do not appear to be more susceptible to infection than the general population but having COVID-19 during pregnancy may increase the risk of major complications for both the mother and the fetus. The aim of this study is to identify the correlation between BMI and nutritional status and the likelihood of contracting COVID-19 infection in pregnancy, its severity, and maternal pregnancy outcomes. We carry out a systematic literature search and a meta-analysis using three databases following the guidelines of the Cochrane Collaboration. We include 45 studies about COVID-19-positive pregnant women. Compared with normal-weight pregnant women with COVID-19, obesity is associated with a more severe infection (OR = 2.32 [1.65–3.25]), increased maternal death (OR = 2.84 [2.01–4.02]), and a higher rate of hospital admission (OR = 2.11 [1.37–3.26]). Obesity may be associated with adverse maternal and pregnancy outcomes by increasing symptom severity and, consequently, hospital and Intensive Care Unit (ICU) admission, and, finally, death rates. For micronutrients, the results are less definite, even if there seems to be a lower level of micronutrients, in particular Vitamin D, in COVID-19-positive pregnant women. Full article
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<p>Flow chart for the selection of studies.</p>
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<p>BMI &gt;= 30 vs. BMI &lt; 30—disease severity (critical/severe vs. mild) [<a href="#B15-nutrients-15-01052" class="html-bibr">15</a>,<a href="#B16-nutrients-15-01052" class="html-bibr">16</a>,<a href="#B17-nutrients-15-01052" class="html-bibr">17</a>,<a href="#B18-nutrients-15-01052" class="html-bibr">18</a>,<a href="#B19-nutrients-15-01052" class="html-bibr">19</a>,<a href="#B20-nutrients-15-01052" class="html-bibr">20</a>,<a href="#B21-nutrients-15-01052" class="html-bibr">21</a>,<a href="#B22-nutrients-15-01052" class="html-bibr">22</a>].</p>
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<p>BMI &gt;= 30 vs. BMI &lt; 30—maternal death due to COVID-19-related causes) [<a href="#B23-nutrients-15-01052" class="html-bibr">23</a>,<a href="#B24-nutrients-15-01052" class="html-bibr">24</a>,<a href="#B25-nutrients-15-01052" class="html-bibr">25</a>,<a href="#B26-nutrients-15-01052" class="html-bibr">26</a>].</p>
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<p>BMI &gt;= 30 vs. BMI &lt; 30—hospital admissions for COVID-19-related causes [<a href="#B27-nutrients-15-01052" class="html-bibr">27</a>,<a href="#B28-nutrients-15-01052" class="html-bibr">28</a>,<a href="#B29-nutrients-15-01052" class="html-bibr">29</a>,<a href="#B30-nutrients-15-01052" class="html-bibr">30</a>,<a href="#B31-nutrients-15-01052" class="html-bibr">31</a>].</p>
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<p>COVID-19-positive pregnant women vs. COVID-19-negative pregnant women—vitamin D serum levels [<a href="#B32-nutrients-15-01052" class="html-bibr">32</a>,<a href="#B33-nutrients-15-01052" class="html-bibr">33</a>].</p>
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<p>(<b>A</b>) Sensitivity analysis including small sample size studies (&lt;100 per arm) and using a fixed effect model. BMI &gt;= 30 vs. BMI &lt;3 0—Disease severity [<a href="#B15-nutrients-15-01052" class="html-bibr">15</a>,<a href="#B16-nutrients-15-01052" class="html-bibr">16</a>,<a href="#B17-nutrients-15-01052" class="html-bibr">17</a>,<a href="#B18-nutrients-15-01052" class="html-bibr">18</a>,<a href="#B19-nutrients-15-01052" class="html-bibr">19</a>,<a href="#B20-nutrients-15-01052" class="html-bibr">20</a>,<a href="#B21-nutrients-15-01052" class="html-bibr">21</a>,<a href="#B22-nutrients-15-01052" class="html-bibr">22</a>]. (<b>B</b>) Sensitivity analysis including small sample size studies (&lt;100 per arm) and using a fixed effect model. BMI &gt;= 30 vs. BMI &lt; 30—Hospital admissions [<a href="#B27-nutrients-15-01052" class="html-bibr">27</a>,<a href="#B28-nutrients-15-01052" class="html-bibr">28</a>,<a href="#B29-nutrients-15-01052" class="html-bibr">29</a>,<a href="#B30-nutrients-15-01052" class="html-bibr">30</a>,<a href="#B31-nutrients-15-01052" class="html-bibr">31</a>]. (<b>C</b>) Sensitivity analysis including only good quality studies—Disease severity. BMI &gt;= 30 vs. BMI &lt; 30 –. [<a href="#B15-nutrients-15-01052" class="html-bibr">15</a>,<a href="#B16-nutrients-15-01052" class="html-bibr">16</a>,<a href="#B17-nutrients-15-01052" class="html-bibr">17</a>,<a href="#B18-nutrients-15-01052" class="html-bibr">18</a>,<a href="#B19-nutrients-15-01052" class="html-bibr">19</a>,<a href="#B20-nutrients-15-01052" class="html-bibr">20</a>,<a href="#B21-nutrients-15-01052" class="html-bibr">21</a>,<a href="#B22-nutrients-15-01052" class="html-bibr">22</a>]. (<b>D</b>) Sensitivity analysis including only good quality studies—Maternal death. [<a href="#B23-nutrients-15-01052" class="html-bibr">23</a>,<a href="#B24-nutrients-15-01052" class="html-bibr">24</a>,<a href="#B25-nutrients-15-01052" class="html-bibr">25</a>,<a href="#B26-nutrients-15-01052" class="html-bibr">26</a>]. (<b>E</b>) Sensitivity analysis including only good quality studies—Hospital admission. [<a href="#B27-nutrients-15-01052" class="html-bibr">27</a>,<a href="#B28-nutrients-15-01052" class="html-bibr">28</a>,<a href="#B29-nutrients-15-01052" class="html-bibr">29</a>,<a href="#B30-nutrients-15-01052" class="html-bibr">30</a>,<a href="#B31-nutrients-15-01052" class="html-bibr">31</a>]. (<b>F</b>) Sensitivity analysis including only good quality studies—Vit D serum levels [<a href="#B32-nutrients-15-01052" class="html-bibr">32</a>,<a href="#B33-nutrients-15-01052" class="html-bibr">33</a>].</p>
Full article ">Figure A1 Cont.
<p>(<b>A</b>) Sensitivity analysis including small sample size studies (&lt;100 per arm) and using a fixed effect model. BMI &gt;= 30 vs. BMI &lt;3 0—Disease severity [<a href="#B15-nutrients-15-01052" class="html-bibr">15</a>,<a href="#B16-nutrients-15-01052" class="html-bibr">16</a>,<a href="#B17-nutrients-15-01052" class="html-bibr">17</a>,<a href="#B18-nutrients-15-01052" class="html-bibr">18</a>,<a href="#B19-nutrients-15-01052" class="html-bibr">19</a>,<a href="#B20-nutrients-15-01052" class="html-bibr">20</a>,<a href="#B21-nutrients-15-01052" class="html-bibr">21</a>,<a href="#B22-nutrients-15-01052" class="html-bibr">22</a>]. (<b>B</b>) Sensitivity analysis including small sample size studies (&lt;100 per arm) and using a fixed effect model. BMI &gt;= 30 vs. BMI &lt; 30—Hospital admissions [<a href="#B27-nutrients-15-01052" class="html-bibr">27</a>,<a href="#B28-nutrients-15-01052" class="html-bibr">28</a>,<a href="#B29-nutrients-15-01052" class="html-bibr">29</a>,<a href="#B30-nutrients-15-01052" class="html-bibr">30</a>,<a href="#B31-nutrients-15-01052" class="html-bibr">31</a>]. (<b>C</b>) Sensitivity analysis including only good quality studies—Disease severity. BMI &gt;= 30 vs. BMI &lt; 30 –. [<a href="#B15-nutrients-15-01052" class="html-bibr">15</a>,<a href="#B16-nutrients-15-01052" class="html-bibr">16</a>,<a href="#B17-nutrients-15-01052" class="html-bibr">17</a>,<a href="#B18-nutrients-15-01052" class="html-bibr">18</a>,<a href="#B19-nutrients-15-01052" class="html-bibr">19</a>,<a href="#B20-nutrients-15-01052" class="html-bibr">20</a>,<a href="#B21-nutrients-15-01052" class="html-bibr">21</a>,<a href="#B22-nutrients-15-01052" class="html-bibr">22</a>]. (<b>D</b>) Sensitivity analysis including only good quality studies—Maternal death. [<a href="#B23-nutrients-15-01052" class="html-bibr">23</a>,<a href="#B24-nutrients-15-01052" class="html-bibr">24</a>,<a href="#B25-nutrients-15-01052" class="html-bibr">25</a>,<a href="#B26-nutrients-15-01052" class="html-bibr">26</a>]. (<b>E</b>) Sensitivity analysis including only good quality studies—Hospital admission. [<a href="#B27-nutrients-15-01052" class="html-bibr">27</a>,<a href="#B28-nutrients-15-01052" class="html-bibr">28</a>,<a href="#B29-nutrients-15-01052" class="html-bibr">29</a>,<a href="#B30-nutrients-15-01052" class="html-bibr">30</a>,<a href="#B31-nutrients-15-01052" class="html-bibr">31</a>]. (<b>F</b>) Sensitivity analysis including only good quality studies—Vit D serum levels [<a href="#B32-nutrients-15-01052" class="html-bibr">32</a>,<a href="#B33-nutrients-15-01052" class="html-bibr">33</a>].</p>
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<p>(<b>A</b>) Covid+ pregnant women vs. Covid- pregnant women, outcome: 1.1 Vitamin D serum levels. Funnel plot. (<b>B</b>) Funnel plot of comparison: 2 BMI &gt;= 30 vs. BMI &lt; 30, outcome: Disease severity. (<b>C</b>) Funnel plot of comparison: 2 BMI &gt;= 30 vs. BMI &lt; 30, outcome: Maternal death. (<b>D</b>) Funnel plot of comparison: 2 BMI &gt;= 30 vs. BMI &lt; 30, outcome: Hospital admission.</p>
Full article ">Figure A2 Cont.
<p>(<b>A</b>) Covid+ pregnant women vs. Covid- pregnant women, outcome: 1.1 Vitamin D serum levels. Funnel plot. (<b>B</b>) Funnel plot of comparison: 2 BMI &gt;= 30 vs. BMI &lt; 30, outcome: Disease severity. (<b>C</b>) Funnel plot of comparison: 2 BMI &gt;= 30 vs. BMI &lt; 30, outcome: Maternal death. (<b>D</b>) Funnel plot of comparison: 2 BMI &gt;= 30 vs. BMI &lt; 30, outcome: Hospital admission.</p>
Full article ">Figure A2 Cont.
<p>(<b>A</b>) Covid+ pregnant women vs. Covid- pregnant women, outcome: 1.1 Vitamin D serum levels. Funnel plot. (<b>B</b>) Funnel plot of comparison: 2 BMI &gt;= 30 vs. BMI &lt; 30, outcome: Disease severity. (<b>C</b>) Funnel plot of comparison: 2 BMI &gt;= 30 vs. BMI &lt; 30, outcome: Maternal death. (<b>D</b>) Funnel plot of comparison: 2 BMI &gt;= 30 vs. BMI &lt; 30, outcome: Hospital admission.</p>
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23 pages, 4025 KiB  
Article
Multi-Omics Analysis Reveals the Potential Effects of Maternal Dietary Restriction on Fetal Muscle Growth and Development
by Xinyue Wang, Mingyu Shang, Wenping Hu and Li Zhang
Nutrients 2023, 15(4), 1051; https://doi.org/10.3390/nu15041051 - 20 Feb 2023
Cited by 2 | Viewed by 2733
Abstract
In terms of fetal muscle growth, development, and health, maternal nutrition is a crucial influence, although the exact biochemical mechanism by which this occurs is still not fully understood. To examine the potential impacts of maternal dietary restriction on fetal muscle development, the [...] Read more.
In terms of fetal muscle growth, development, and health, maternal nutrition is a crucial influence, although the exact biochemical mechanism by which this occurs is still not fully understood. To examine the potential impacts of maternal dietary restriction on fetal muscle development, the sheep maternal dietary restriction model was developed for this study. In our study, 12 pregnant ewes were evenly split into two experimental groups and fed either 75% or 100% of a maternal nutrient. In addition, a multi-omics analysis was used to study the embryonic longissimus dorsis on gestational days (GD) 85 and 135. The fetal weight at GD 135 was significantly below normal due to the maternal restricted diet (p < 0.01). When fetuses were exposed to the dietary deficit, 416 mRNAs and 40 proteins were significantly changed. At GD 85, the multi-omics analysis revealed that maternal dietary restriction led to a significant up-regulation of the cell cycle regulator CDK2 gene in the cellular senescence signaling pathway, and the results of the qRT-PCR were similar to the multi-omics analysis, which showed that SIX1, PAX7, the cell cycle factors CDK4 and CDK6, and the BCL-2 apoptosis factor were up-regulated and several skeletal muscle marker genes, such as MYF5 and MyoD were down-regulated. At GD 135, maternal dietary restriction blocks the muscle fiber differentiation and maturation. The multi-omics analysis revealed that the TEAD1 gene was in the Hippo signaling pathway, the muscle marker genes MYF5 and MyoG were significantly down-regulated, and the TEAD1 binding of the down-regulated VGLL3 gene might be potential mechanisms affecting myofiber differentiation and maturation. Knocking down the CDK2 gene could inhibit the proliferation of primary embryonic myoblasts, and the expression levels of cell cycle regulatory factors CDK4 and CDK6 were significantly changed. Under low nutrient culture conditions, the number of myoblasts decreased and the expression of CDK2, CDK6, MYF5, PAX7 and BCL-2 changed, which was in perfect agreement with the multi-omics analysis. All of the findings from our study helped to clarify the potential effects of maternal dietary restriction on fetal muscle growth and development. They also provided a molecular foundation for understanding the molecular regulatory mechanisms of maternal nutrition on fetal muscle growth and development, as well as for the development of new medications and the management of related metabolic diseases. Full article
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<p>Dietary treatment and sampling diagram for the pregnant ewes. The long orange bar indicates the time of the maternal normal diet. The long gray bar indicates the time of the maternal restricted diets. D85N indicates the group of normal diets; D85T indicates the group of the maternal restricted diets. D135N indicates the group of normal diets; D135T indicates the group of restricted diets.</p>
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<p>Phenotype analysis. Phenotype analysis of the fetal sheep at (<b>a</b>) GD 85 and (<b>b</b>) GD 135. The black box is the restricted maternal nutrition, the gray box is the normal maternal nutrition, and <span class="html-italic">p</span> &lt; 0.01 (**) indicates an extremely significant difference.</p>
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<p>D85T vs. D85N differential expression mRNA and protein enrichment analysis. (<b>a</b>) Differential expression mRNA Gene Ontology (GO) term analysis; mRNAs, as classified into three main categories by the GO analysis, blue indicates the biological process, green indicates the cellular component and orange indicates the molecular function. (<b>b</b>) GO enrichment analysis. (<b>c</b>) Differential expression mRNA KEGG analysis, in (<b>b</b>,<b>c</b>), the size and color of the bubble indicate the number and significant characters of the differential expression mRNAs that are enriched in GO terms. (<b>d</b>) In the functional classification chart of the differential protein abundance (COG), the orthologous proteins are classified into different functions. (<b>e</b>) Differential protein abundance GO term analysis. Proteins, as classified into three main categories by the GO analysis, green, indicates a biological process, orange indicates the cellular component and purple indicates molecular function.</p>
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<p>D85T vs. D85N differential expression mRNA-protein enrichment analysis and key candidate gene related the gene expression analysis. (<b>a</b>) Differential expression mRNA-protein Gene Ontology (GO) term analysis; mRNA-protein, as classified into three main categories by the GO analysis, purple indicates the biological process, blue indicates the cellular component and green indicates the molecular function. (<b>b</b>) Differential expression mRNA-protein GO enrichment analysis. (<b>c</b>) Differential expression mRNA-protein KEGG analysis, in (<b>b</b>,<b>c</b>), the size and color of the bubble indicate the number and significant characters of the differential expression mRNA-proteins. (<b>d</b>) Differential expression mRNA-protein KEGG enrichment analysis and the orthologous signaling pathways are classified into different functions. (<b>e</b>) <span class="html-italic">CDK2</span>-related gene expression analysis, <span class="html-italic">p</span> &lt; 0.05 (*), <span class="html-italic">p</span> &lt; 0.01 (**) or <span class="html-italic">p</span> &lt; 0.001 (***).</p>
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<p>D135T vs. D135N differential expression mRNA and protein enrichment analysis. (<b>a</b>) Differential expression mRNA Gene Ontology (GO) term analysis; mRNAs are classified into three main categories by the GO analysis, blue indicates the biological process, green indicates the cellular component and orange indicates the molecular function. (<b>b</b>) Differential expression mRNA GO enrichment analysis. (<b>c</b>) Differential expression mRNA KEGG enrichment analysis, in (<b>b</b>,<b>c</b>), the size and color of the bubble indicate the number and significant characters of the differentially expressed mRNAs. (<b>d</b>) The functional classification chart of the differential abundance proteins (COG), the orthologous proteins were classified into different functions. (<b>e</b>) Differential protein abundance GO term analysis, the proteins were classified into three main categories by the GO analysis, green indicates a biological process, orange indicates the cellular component and purple indicates molecular function. (<b>f</b>) Differential protein abundance KEGG enrichment analysis, the size, and the color of the bubble indicate the number and significant characters of the differentially expressed proteins.</p>
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<p>D135T vs. D135N differential expression mRNA-protein enrichment analysis and key candidate gene-related gene expression analysis. (<b>a</b>) Differential expression mRNA-protein Gene Ontology (GO) term analysis; mRNA-protein are classified into three main categories by the GO analysis, purple indicates the biological process, blue indicates the cellular component and green indicates the molecular function. (<b>b</b>) Differential expression mRNA-protein GO enrichment analysis. (<b>c</b>) Differential expression mRNA-protein KEGG analysis, in (<b>b</b>,<b>c</b>), the size and color of the bubble indicate the number and significant characters of the differentially expressed mRNA-proteins. (<b>d</b>) Differential expression mRNA-protein KEGG enrichment analysis, the orthologous signaling pathways are classified into different functions. (<b>e</b>) <span class="html-italic">TEAD1</span>-related gene expression analysis, <span class="html-italic">p</span> &lt; 0.01 (**) or <span class="html-italic">p</span> &lt; 0.001 (***).</p>
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<p><span class="html-italic">CDK2</span> knockdown expression affects the cell cycle of sheep primary embryonic myoblasts. (<b>a</b>) Comparing the transfection effect of three siRNAs, (<b>b</b>) the phenotypes of the sheep primary embryonic myoblasts transfected with siRNA3-<span class="html-italic">CDK2,</span> siNC, and control were analyzed, and (<b>c</b>) the qRT-PCR results of the related genes after the siRNA3-<span class="html-italic">CDK2</span> knockdown, muscle growth and development, cell cycle, and apoptosis-related genes, <span class="html-italic">p &lt;</span> 0.05 (*), <span class="html-italic">p &lt;</span> 0.01 (**), or <span class="html-italic">p &lt;</span> 0.001 (***).</p>
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<p>Low nutrient culture affects the sheep primary embryonic myoblast proliferation and growth. (<b>a</b>) The different period phenotypes of sheep primary embryonic myoblasts cultured with DMEM/F12 (low nutrition) and DMEM/F12 containing 10% FBS (normal nutrition). (<b>b</b>) qRT-PCR results of the related genes with the two experimental groups, <span class="html-italic">p</span> &lt; 0.05 (*), <span class="html-italic">p</span> &lt; 0.01 (**), or <span class="html-italic">p</span> &lt; 0.001 (***).</p>
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<p>Low nutrient culture affects the sheep primary embryonic myoblast proliferation and growth. (<b>a</b>) The different period phenotypes of sheep primary embryonic myoblasts cultured with DMEM/F12 (low nutrition) and DMEM/F12 containing 10% FBS (normal nutrition). (<b>b</b>) qRT-PCR results of the related genes with the two experimental groups, <span class="html-italic">p</span> &lt; 0.05 (*), <span class="html-italic">p</span> &lt; 0.01 (**), or <span class="html-italic">p</span> &lt; 0.001 (***).</p>
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23 pages, 3189 KiB  
Article
The Effect of Non-Nutritive Sweetened Beverages on Postprandial Glycemic and Endocrine Responses: A Systematic Review and Network Meta-Analysis
by Roselyn Zhang, Jarvis C. Noronha, Tauseef A. Khan, Néma McGlynn, Songhee Back, Shannan M. Grant, Cyril W. C. Kendall and John L. Sievenpiper
Nutrients 2023, 15(4), 1050; https://doi.org/10.3390/nu15041050 - 20 Feb 2023
Cited by 26 | Viewed by 18710
Abstract
Background: There has been an emerging concern that non-nutritive sweeteners (NNS) can increase the risk of cardiometabolic disease. Much of the attention has focused on acute metabolic and endocrine responses to NNS. To examine whether these mechanisms are operational under real-world scenarios, we [...] Read more.
Background: There has been an emerging concern that non-nutritive sweeteners (NNS) can increase the risk of cardiometabolic disease. Much of the attention has focused on acute metabolic and endocrine responses to NNS. To examine whether these mechanisms are operational under real-world scenarios, we conducted a systematic review and network meta-analysis of acute trials comparing the effects of non-nutritive sweetened beverages (NNS beverages) with water and sugar-sweetened beverages (SSBs) in humans. Methods: MEDLINE, EMBASE, and The Cochrane Library were searched through to January 15, 2022. We included acute, single-exposure, randomized, and non-randomized, clinical trials in humans, regardless of health status. Three patterns of intake were examined: (1) uncoupling interventions, where NNS beverages were consumed alone without added energy or nutrients; (2) coupling interventions, where NNS beverages were consumed together with added energy and nutrients as carbohydrates; and (3) delayed coupling interventions, where NNS beverages were consumed as a preload prior to added energy and nutrients as carbohydrates. The primary outcome was a 2 h incremental area under the curve (iAUC) for blood glucose concentration. Secondary outcomes included 2 h iAUC for insulin, glucagon-like peptide 1 (GLP-1), gastric inhibitory polypeptide (GIP), peptide YY (PYY), ghrelin, leptin, and glucagon concentrations. Network meta-analysis and confidence in the network meta-analysis (CINeMA) were conducted in R-studio and CINeMA, respectively. Results: Thirty-six trials involving 472 predominantly healthy participants were included. Trials examined a variety of single NNS (acesulfame potassium, aspartame, cyclamate, saccharin, stevia, and sucralose) and NNS blends (acesulfame potassium + aspartame, acesulfame potassium + sucralose, acesulfame potassium + aspartame + cyclamate, and acesulfame potassium + aspartame + sucralose), along with matched water/unsweetened controls and SSBs sweetened with various caloric sugars (glucose, sucrose, and fructose). In uncoupling interventions, NNS beverages (single or blends) had no effect on postprandial glucose, insulin, GLP-1, GIP, PYY, ghrelin, and glucagon responses similar to water controls (generally, low to moderate confidence), whereas SSBs sweetened with caloric sugars (glucose and sucrose) increased postprandial glucose, insulin, GLP-1, and GIP responses with no differences in postprandial ghrelin and glucagon responses (generally, low to moderate confidence). In coupling and delayed coupling interventions, NNS beverages had no postprandial glucose and endocrine effects similar to controls (generally, low to moderate confidence). Conclusions: The available evidence suggests that NNS beverages sweetened with single or blends of NNS have no acute metabolic and endocrine effects, similar to water. These findings provide support for NNS beverages as an alternative replacement strategy for SSBs in the acute postprandial setting. Full article
(This article belongs to the Section Clinical Nutrition)
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Figure 1
<p>Network plot and meta-analysis of uncoupling interventions evaluating the effect of non-nutritive sweetened beverages (NNS beverages) sweetened single or blends of non-nutritive sweeteners (NNS), water, and sugar-sweetened beverages (SSBs) sweetened with caloric sweeteners on postprandial blood glucose response in healthy participants. Network plot: the size of the nodes is proportional to the number of participants and the line width is proportional to the number of studies. Network table: treatments are grouped by treatment type (i.e., single NNS, NNS blends, water, and caloric sweeteners) and are reported in alphabetical order. Treatment estimates (mmol*min/L) are MDs and 95% CIs of the column-defining treatment compared with the row-defining treatment. MDs less than 0 favor the column-defining treatment. MDs greater than 0 favor the row-defining treatment. Statistically significant results are bolded in black. Results that are not statistically significant are grey and not bolded. The minimally important difference (MID) for postprandial glucose response is 100 mmol*min/L. Trivial effects (&lt;1 MID) or no effects have a white background; small important effects (≥1 MID) have a light blue background; moderate effects (≥2 MID) have a darker blue background; large effects (≥5 to &lt;10 MID) have a purple background; and very large effects (≥10 MID) have a black background. Confidence in the effect estimate (CINeMA) is shown for each treatment comparison: high confidence ⊕⊕⊕⊕; moderate confidence ⊕⊕⊕; low confidence ⊕⊕; and very low confidence ⊕. See <a href="#app1-nutrients-15-01050" class="html-app">Supplementary Table S6</a> for overall CiNEMA assessments and <a href="#app1-nutrients-15-01050" class="html-app">Supplementary Figures S6–S9</a> for detailed assessments of the confidence in the effect estimate using the CINeMA framework.</p>
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<p>Network plot and meta-analysis of uncoupling interventions evaluating the effect of non-nutritive sweetened beverages (NNS beverages) sweetened single or blends of non-nutritive sweeteners (NNS), water, and sugar-sweetened beverages (SSBs) sweetened with caloric sweeteners on postprandial blood glucose response in participants with type 2 diabetes. Network plot: the size of the blue nodes is proportional to the number of participants and the line width is proportional to the number of studies. Network table: treatments are grouped by treatment type (i.e., individual non-nutritive sweeteners (NNS), NNS blends, water, and caloric sweeteners) and are reported in alphabetical order. Treatment estimates (mmol*min/L) are MDs and 95% CIs of the column-defining treatment compared with the row-defining treatment. MDs less than 0 favor the column-defining treatment. MDs greater than 0 favor the row-defining treatment. Significant results are bolded in black. Non-significant results are grey and not bolded. The minimally important difference (MID) for postprandial glucose response is 100 mmol*min/L. Trivial (significant) effects (&lt;1 MID) or no effects have a white background; small important effects (≥1 MID) have a light blue background; moderate effects (≥2 MID) have a darker blue background; large effects (≥5 to &lt;10 MID) have a purple background; and very large effects (≥10 MID) have a black background. Confidence in the effect estimate is shown for each treatment comparison: high confidence ⊕⊕⊕⊕; moderate confidence ⊕⊕⊕; low confidence ⊕⊕; and very low confidence ⊕. See <a href="#app1-nutrients-15-01050" class="html-app">Supplementary Table S7 and Figures S10–S13</a> for detailed assessments of the confidence in the effect estimate using the CINeMA framework.</p>
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<p>Network plot and meta-analysis of coupling interventions evaluating the effect of non-nutritive sweetened beverages (NNS beverages) sweetened single or blends of non-nutritive sweeteners (NNS) and controls on postprandial glucose response in healthy participants. Network plot: the size of the blue nodes is proportional to the number of participants and the line width is proportional to the number of studies. Network table: treatments are grouped by treatment type (i.e., individual non-nutritive sweeteners (NNS), NNS blends, water, and caloric sweeteners) and are reported in alphabetical order. Treatment estimates (mmol*min/L) are MDs and 95% CIs of the column-defining treatment compared with the row-defining treatment. MDs less than 0 favor the column-defining treatment. MDs greater than 0 favor the row-defining treatment. Significant results are bolded in black. Non-significant results are grey and not bolded. The minimally important difference (MID) for postprandial glucose response is 100 mmol*min/L. Trivial (significant) effects (&lt;1 MID) or no effects have a white background; small important effects (≥1 MID) have a light blue background; moderate effects (≥2 MID) have a darker blue background; large effects (≥5 to &lt;10 MID) have a purple background; and very large effects (≥10 MID) have a black background. Confidence in the effect estimate is shown for each treatment comparison: high confidence ⊕⊕⊕⊕; moderate confidence ⊕⊕⊕; low confidence ⊕⊕; and very low confidence ⊕. See <a href="#app1-nutrients-15-01050" class="html-app">Supplementary Table S15 and Figure S34</a> for detailed assessments of the confidence in the effect estimate using the CINeMA framework.</p>
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<p>Network plot and meta-analysis of delayed coupling interventions evaluating the effect of non-nutritive sweetened beverages (NNS beverages) sweetened single or blends of non-nutritive sweeteners (NNS), water, and sugar-sweetened beverages (SSBs) sweetened with caloric sweeteners on postprandial blood glucose response in healthy participants. Network plot: the size of the blue nodes is proportional to the number of participants and the line width is proportional to the number of studies. Network table: treatments are grouped by treatment type (i.e., individual non-nutritive sweeteners (NNS), NNS blends, water, and caloric sweeteners) and are reported in alphabetical order. Treatment estimates (mmol*min/L) are MDs and 95% CIs of the column-defining treatment compared with the row-defining treatment. MDs less than 0 favor the column-defining treatment. MDs greater than 0 favor the row-defining treatment. Significant results are bolded in black. Non-significant results are grey and not bolded. The minimally important difference (MID) for postprandial glucose response is 100 mmol*min/L. Trivial (significant) effects (&lt;1 MID) or no effects have a white background; small important effects (≥1 MID) have a light blue background; moderate effects (≥2 MID) have a darker blue background; large effects (≥5 to &lt;10 MID) have a purple background; very large effects (≥10 MID) have a black background. Confidence in the effect estimate is shown for each treatment comparison: high confidence ⊕⊕⊕⊕; moderate confidence ⊕⊕⊕; low confidence ⊕⊕; very low confidence ⊕. See <a href="#app1-nutrients-15-01050" class="html-app">Supplementary Table S17 and Figures S37–S40</a> for detailed assessments of the confidence in the effect estimate using the CINeMA framework.</p>
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<p>Network plot and meta-analysis of delayed coupling interventions evaluating the effect of non-nutritive sweetened beverages (NNS beverages) sweetened single or blends of non-nutritive sweeteners (NNS), water, and sugar-sweetened beverages (SSBs) sweetened with caloric sweeteners on postprandial blood glucose response in participants with type 2 diabetes. Network plot: the size of the blue nodes is proportional to the number of participants and the line width is proportional to the number of studies. Network table: treatments are grouped by treatment type (i.e., individual non-nutritive sweeteners (NNS), NNS blends, water, and caloric sweeteners) and are reported in alphabetical order. Treatment estimates (mmol*min/L) are MDs and 95% CIs of the column-defining treatment compared with the row-defining treatment. MDs less than 0 favor the column-defining treatment. MDs greater than 0 favor the row-defining treatment. Significant results are bolded in black. Non-significant results are grey and not bolded. The minimally important difference (MID) for postprandial glucose response is 100 mmol*min/L. Trivial (significant) effects (&lt;1 MID) or no effects have a white background; small important effects (≥1 MID) have a light blue background; moderate effects (≥2 MID) have a darker blue background; large effects (≥5 to &lt;10 MID) have a purple background; and very large effects (≥10 MID) have a black background. Confidence in the effect estimate is shown for each treatment comparison: high confidence ⊕⊕⊕⊕; moderate confidence ⊕⊕⊕; low confidence ⊕⊕; and very low confidence ⊕. See <a href="#app1-nutrients-15-01050" class="html-app">Supplementary Table S18 and Figure S41</a> for detailed assessments of the confidence in the effect estimate using the CINeMA framework.</p>
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16 pages, 3224 KiB  
Article
Ursolic Acid Ameliorates Myocardial Ischaemia/Reperfusion Injury by Improving Mitochondrial Function via Immunoproteasome-PP2A-AMPK Signalling
by Luo-Luo Xu, Hui-Xiang Su, Pang-Bo Li and Hui-Hua Li
Nutrients 2023, 15(4), 1049; https://doi.org/10.3390/nu15041049 - 20 Feb 2023
Cited by 18 | Viewed by 3087
Abstract
Cardiac ischaemia/reperfusion (I/R) injury causes cardiomyocyte apoptosis and mitochondrial dysfunction. Ursolic acid (UA), as a pentacyclic triterpenoid carboxylic acid, exerts several bioactivities in animal models of different diseases, but the preventive role of UA in I/R-induced myocardial dysfunction remains largely unknown. Male wild-type [...] Read more.
Cardiac ischaemia/reperfusion (I/R) injury causes cardiomyocyte apoptosis and mitochondrial dysfunction. Ursolic acid (UA), as a pentacyclic triterpenoid carboxylic acid, exerts several bioactivities in animal models of different diseases, but the preventive role of UA in I/R-induced myocardial dysfunction remains largely unknown. Male wild-type mice were pre-administered with UA at a dosage of 80 mg/kg i.p. and then subjected to cardiac I/R injury for 24 h. Cardiac function and pathological changes were examined by echocardiography and histological staining. The protein and mRNA levels of the genes were determined using qPCR and immunoblotting analysis. Our results revealed that UA administration in mice significantly attenuated the I/R-induced decline in cardiac function, infarct size, myocyte apoptosis, and oxidative stress. Mechanistically, UA increased three immunoproteasome catalytic subunit expressions and activities, which promoted ubiquitinated PP2A degradation and activated AMPK-PGC1α signalling, leading to improved mitochondrial biosynthesis and dynamic balance. In vitro experiments confirmed that UA treatment prevented hypoxia/reperfusion (H/R)-induced cardiomyocyte apoptosis and mitochondrial dysfunction through activation of AMPK signalling. In summary, our findings identify UA as a new activator of the immunoproteasome that exerts a protective role in I/R-induced myocardial dysfunction and suggest that UA supplementation could be beneficial for the prevention of cardiac ischaemic disease. Full article
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Graphical abstract
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<p>Administration of UA increases the immunoproteasome catalytic subunit activity and expression. (<b>A</b>) Chemical structure and molecular weight of UA. (<b>B</b>) Male mice (<span class="html-italic">n</span> = 6 per group) were administered with UA (40 or 80 mg/kg) for 24 h, serum LDH activity was measured in mice (<span class="html-italic">n</span> = 6 per group). (<b>C</b>) Analysis of three immunoproteasome activity types in the heart tissues of mice at 24 h after UA administration (40 or 80 mg/kg) (<span class="html-italic">n</span> = 6 per group). (<b>D</b>) Measurement of three immunoproteasome activity types in cardiac tissue of mice at 12 or 24 h after UA (80 mg/kg) treatment (<span class="html-italic">n</span> = 6 per group). (<b>E</b>) The mRNA levels of six catalytic subunits of the proteasome in the heart tissues were detected by qPCR analysis (<span class="html-italic">n</span> = 6 per group). (<b>F</b>) The protein levels of the β1i, β2i, and β5i subunits in the heart tissues were detected by immunoblot analysis (left) and quantification of the relative protein intensities (right, <span class="html-italic">n</span> = 4 per group). GAPDH was used as an internal control.</p>
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<p>UA enhances the immunoproteasome catalytic subunit expression and activities in the I/R heart tissues. (<b>A</b>) Schematic diagram of the experimental design. (<b>B</b>) Male mice (<span class="html-italic">n</span> = 6 per group) were pretreated with UA (80 mg/kg) before sham or I/R surgery. After 24 h treatment, 3 immunoproteasome activity types in the cardiac tissues of mice were measured (<span class="html-italic">n</span> = 6 per group). (<b>C</b>) The mRNA levels of the β1i, β2i, and β5i subunits (β1i, β2i, and β5i) in the heart tissue were detected by qPCR analyses (<span class="html-italic">n</span> = 6 per group). (<b>D</b>) The protein levels of the β1i, β2i, and β5i subunits in the heart tissue were examined by immunoblot analysis (left) and quantification of the relative protein intensities (right, <span class="html-italic">n</span> = 4 per group). GAPDH was used as an internal control.</p>
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<p>Administration of UA alleviates I/R-triggered cardiac injury and dysfunction. (<b>A</b>) Male mice (<span class="html-italic">n</span> = 6 per group) were pretreated with UA (80 mg/kg) and then exposed to sham or I/R surgery for 24 h. Representative M-mode echocardiographic images of the LV (left). Scale bar: 0.2 s. Quantification of EF% or FS% in each group (right, <span class="html-italic">n</span> = 6 per group). (<b>B</b>) Representative images of TTC/Evans blue staining of heart sections (left). The ratios of area at risk (AAR)/LV area and infarct size/AAR (right, <span class="html-italic">n</span> = 6 per group). (<b>C</b>) Representative images of TUNEL (red), α-actinin (green), and DAPI (blue) staining of the heart sections and percentage of TUNEL-positive nuclei (<span class="html-italic">n</span> = 6 per group). (<b>D</b>) The mRNA levels of Bax and Bcl-2 were detected by qPCR analysis. The results are presented as the Bax/Bcl-2 ratio (<span class="html-italic">n</span> = 6 per group). (<b>E</b>) DHE staining of heart sections (left) and quantification of the DHE fluorescence intensity for ROS level (right, <span class="html-italic">n</span> = 6 per group). Scale bar: 50 μm. (<b>F</b>) The mRNA levels of NOX2 and NOX4 were detected by qPCR analysis (<span class="html-italic">n</span> = 6 per group). (<b>G</b>) Measurement of LDH activity in serum and heart tissues (<span class="html-italic">n</span> = 6 per group).</p>
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<p>UA promotes mitochondrial biogenesis and dynamic balance via AMPK–PGC1α-activated AMPK signalling in the I/R heart. (<b>A</b>) Male mice (<span class="html-italic">n</span> = 6 per group) were pretreated with UA (80 mg/kg) and then exposed to I/R for 24 h. Immunoblotting analysis of phosphorylated (<span class="html-italic">p</span>)-AMPKα (T172), total AMPKα, and PGC1α proteins in the heart tissue (left) and quantification of relative <span class="html-italic">p</span>-AMPKα/AMPKα and PGC1α protein levels (right, <span class="html-italic">n</span> = 4 per group). (<b>B</b>) qPCR analysis of TFAM and TFB2M (<span class="html-italic">n</span> = 6 per group). (<b>C</b>) Immunoblot analysis of Drp1 and Mfn1/2 proteins in heart tissue (left) and analysis of the relative protein intensities (right, <span class="html-italic">n</span> = 4 per group). GAPDH is an internal control. (<b>D</b>) Measurement of relative ATP levels (<span class="html-italic">n</span> = 6 per group). (<b>E</b>) Immunoblot analysis of PP2A protein in heart tissue (top) and analysis of the relative protein intensities (bottom, <span class="html-italic">n</span> = 4 per group). (<b>F</b>) Lysates from heart tissue pretreated with vehicle or UA after sham or I/R operation before harvest were used for immunoprecipitation with anti-PP2A antibody. The ubiquitinated PP2A was evaluated by immunoblotting analysis with anti-ubiquitin (Ub, upper left) and anti-PP2A antibody (lower left). Input showed the protein levels of Ub and PP2A in heart lysates (right).</p>
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<p>Inhibiting AMPK activation abolishes the UA-mediated protective effect against H/R-triggered cardiomyocyte apoptosis, mitochondrial fragmentation, and mitochondrial dysfunction in vitro. (<b>A</b>) NRCMs were cotreated with CC (an AMPK inhibitor; 10 µM) and UA (0.5 µM) and then subjected to H/R for 24 h. TUNEL (red) and DAPI (blue) staining of NRCMs (left). Five images from each sample were randomly selected to calculate the apoptotic cells (right, <span class="html-italic">n</span> = 3 independent experiments). (<b>B</b>) Immunofluorescence staining of mitochondrial morphology in NRCMs was performed (left). The images were captured using confocal microscopy. Five images from each sample were randomly selected to calculate the percentage of mitochondrial fission in each image to obtain the mean value of each sample (right, <span class="html-italic">n</span> = 3 independent experiments). (<b>C</b>) JC-1 fluorescence staining of NRCMs to determine the ΔΨm. Red: high potential (J-aggregates); green: low potential (J-monomers). The images were visualized using fluorescence microscopy. Five visual fields were selected randomly from each sample to analyse the JC-1 intensity (right, <span class="html-italic">n</span> = 3 independent experiments). (<b>D</b>) Fluorescence staining of NRCMs to detect mPTP opening (left). The images were visualized using fluorescence microscopy. Five visual fields were selected randomly from each sample to analyse the mPTP intensity (right, <span class="html-italic">n</span> = 3 independent experiments). Scale bar: 50 μm.</p>
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13 pages, 1843 KiB  
Article
Fecal Calprotectin in Self-Reported Milk Intolerance: Not Only Lactose Intolerance
by Aurelio Seidita, Pasquale Mansueto, Alessandra Giuliano, Marta Chiavetta, Maurizio Soresi, Antonio Carroccio and the Internal Medicine Study Group
Nutrients 2023, 15(4), 1048; https://doi.org/10.3390/nu15041048 - 20 Feb 2023
Viewed by 3268
Abstract
The hypothesis is that inflammatory/allergic conditions should be considered in self-reported milk intolerance (SRMI) patients who test negative and/or are asymptomatic at Lactose Hydrogen Breath Test (LHBT). We analyzed fecal calprotectin (FCP) values in SRMI patients to investigate the frequency of a “positive” [...] Read more.
The hypothesis is that inflammatory/allergic conditions should be considered in self-reported milk intolerance (SRMI) patients who test negative and/or are asymptomatic at Lactose Hydrogen Breath Test (LHBT). We analyzed fecal calprotectin (FCP) values in SRMI patients to investigate the frequency of a “positive” intestinal inflammation marker and its correlation with lactose tolerance/intolerance. Data from 329 SRMI patients were retrospectively analyzed; according to the positive/negative results (maldigester/digester) and the presence/absence of symptoms reported during LHBT (intolerant/tolerant), patients were divided into: ‘lactose tolerants’ (n. 104), ‘maldigesters/intolerants’ (n. 187), ‘digesters/intolerants’ (n. 38). FCP values were analyzed in all three subgroups. A percentage of SRMI patients complained of constipation (>15%), extraintestinal symptoms (>30% including anemia), multiple food hypersensitivity (7.6%) and had intraepithelial lymphocytic infiltration at duodenal biopsy (>50%). Over 50.0% showed FCP values above the normal limit. Lactose tolerants and maldigesters/intolerants had higher positivity frequencies (p < 0.0001, for both) and absolute values (p = 0.04, for maldigesters/intolerants) of FCP compared to digesters/intolerants. FCP was not useful to differentiate tolerant from intolerant subjects (AUC 0.58). Our data suggest the existence of an allergic/inflammatory pathogenetic mechanism in a subset of SRMI subjects. FCP results are in keeping with this hypothesis, even if they cannot differentiate lactose tolerant from intolerant patients. Full article
(This article belongs to the Special Issue Food Intolerance and Food Allergy: Novel Aspects in a Changing World)
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<p>Characteristics of the three subgroups.</p>
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<p>Flow-chart of the study, showing distribution of the patients in different subgroups according to LHBT results and appearance of symptoms after LHBT test.</p>
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<p>Receiver operating characteristic (ROC) curve analysis of the FCP values in the lactose tolerants vs. all intolerants.</p>
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18 pages, 3704 KiB  
Article
Transcriptomics Dissection of Calorie Restriction and Exercise Training in Brown Adipose Tissue and Skeletal Muscle
by Yonghao Feng, Zhicheng Cui, Xiaodan Lu, Hongyu Gong, Xiaoyu Liu, Hui Wang, Haoyu Cheng, Huanqing Gao, Xiaohong Shi, Yiming Li, Hongying Ye, Qiongyue Zhang and Xingxing Kong
Nutrients 2023, 15(4), 1047; https://doi.org/10.3390/nu15041047 - 20 Feb 2023
Cited by 6 | Viewed by 3823
Abstract
Calorie restriction (CR) and exercise training (EX) are two critical lifestyle interventions for the prevention and treatment of metabolic diseases, such as obesity and diabetes. Brown adipose tissue (BAT) and skeletal muscle are two important organs for the generation of heat. Here, we [...] Read more.
Calorie restriction (CR) and exercise training (EX) are two critical lifestyle interventions for the prevention and treatment of metabolic diseases, such as obesity and diabetes. Brown adipose tissue (BAT) and skeletal muscle are two important organs for the generation of heat. Here, we undertook detailed transcriptional profiling of these two thermogenic tissues from mice treated subjected to CR and/or EX. We found transcriptional reprogramming of BAT and skeletal muscle as a result of CR but little from EX. Consistent with this, CR induced alterations in the expression of genes encoding adipokines and myokines in BAT and skeletal muscle, respectively. Deconvolution analysis showed differences in the subpopulations of myogenic cells, mesothelial cells and endogenic cells in BAT and in the subpopulations of satellite cells, immune cells and endothelial cells in skeletal muscle as a result of CR or EX. NicheNet analysis, exploring potential inter-organ communication, indicated that BAT and skeletal muscle could mutually regulate their fatty acid metabolism and thermogenesis through ligands and receptors. These data comprise an extensive resource for the study of thermogenic tissue molecular responses to CR and/or EX in a healthy state. Full article
(This article belongs to the Special Issue Adipose Tissue Metabolism and Exercise in Health and Disease)
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<p>Study overview and phenotypic responses. (<b>A</b>) Overview of the mouse study and tissue profiling. (<b>B</b>–<b>F</b>) Body weight change (<b>B</b>), ratio of lean mass to body weight (<b>C</b>), ratio of fat mass to body weight (<b>D</b>), BAT weight (<b>E</b>) and fed glucose (<b>F</b>) in the four intervention groups. (<b>G</b>) Representative hematoxylin and eosin staining images of BAT (scale bars, 40 μm). (<b>H</b>) Areas of the droplets from H&amp;E staining images of BAT. Statistical comparisons were carried out using unpaired one-tailed t tests or Wilcoxon rank sum and signed rank tests (<b>B</b>–<b>F</b>,<b>H</b>). Data are represented as means ± SD. * <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; 0.001,**** <span class="html-italic">p</span> &lt; 0.0001; ns, not significant; BW, body weight; CR, calorie restriction; EX, exercise training; CREX, calorie restriction combined with exercise training; BAT, brown adipose tissue.</p>
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<p>Transcriptomic changes in BAT upon CR with or without EX. (<b>A</b>,<b>B</b>) Principal component analysis plot of the BAT samples in the control and CR groups (<b>A</b>) and in the EX and CREX groups (<b>B</b>). (<b>C</b>,<b>D</b>) Volcano plots of DEGs in the CR vs. control groups (<b>C</b>) and in the CREX vs. EX groups (<b>D</b>). The top 20 genes with the highest absolute values for the log2FC were labeled (down: <span class="html-italic">p</span> &lt; 0.05 and log2FC &lt; −0.58; up: <span class="html-italic">p</span> &lt; 0.05 and log2FC &gt; 0.58). (<b>E</b>) Enriched GO terms for all DEGs in BAT upon CR. (<b>F</b>) Enriched KEGG pathways for all DEGs in BAT upon CR. (<b>G</b>) Enriched GO terms for all DEGs in BAT upon CREX. (<b>H</b>) Enriched KEGG pathways for all DEGs in BAT upon CREX. (<b>I</b>) Dot plot of genes’ log2FC in CR vs. control groups and CREX vs. EX groups. Stable, genes that were not differently expressed in the CR vs. control groups or CREX vs. EX groups; Both down, downregulated DEGS across the two comparisons; Both up, upregulated DEGS across the two comparisons; CR down, specific downregulated DEGS in the comparison between the CR and control groups; CR up, upregulated DEGS in the comparison between the CR and control groups; CREX down, specific downregulated DEGS in the comparison between the CREX and EX groups; CREX up, upregulated DEGS in the comparison between the CREX and EX groups. (<b>J</b>) Venn plot of common and distinct DEGs upon CR with or without EX. Brick red, enriched GO terms for upregulated DEGs; navy blue, enriched GO terms for downregulated DEGs; bright red, enriched KEGG pathways for upregulated DEGs; green, enriched KEGG pathways for downregulated DEGs.</p>
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<p>GO terms and KEGG pathways enriched by DEGs encoding adipokines upon CR with or without EX. (<b>A</b>,<b>B</b>) Heatmap plot of DEGs encoding adipokines in CR vs. control groups (<b>A</b>) and in CREX vs. EX groups (<b>B</b>). (<b>C</b>) Venn plot of common and distinct DEGs encoding adipokines upon CR with or without EX. (<b>D</b>) Enriched GO terms for common DEGs encoding adipokines in BAT upon CR with or without EX. (<b>E</b>) Enriched KEGG pathways for common DEGs encoding adipokines in BAT upon CR with or without EX. (<b>F</b>) Enriched GO terms for specific DEGs encoding adipokines in BAT upon CR. (<b>G</b>) Enriched KEGG pathways for specific DEGs encoding adipokines in BAT upon CR. Brick red, enriched GO terms for upregulated DEGs encoding adipokines; navy blue, enriched GO terms for downregulated DEGs encoding adipokines; bright red, enriched KEGG pathways for upregulated DEGs encoding adipokines; green, enriched KEGG pathways for downregulated DEGs encoding adipokines.</p>
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<p>Transcriptomic changes in skeletal muscle upon CR with or without EX. (<b>A</b>,<b>B</b>) principal component analysis plot of the skeletal muscle samples in the control and CR groups (<b>A</b>) and in the EX and CREX groups (<b>B</b>). (<b>C</b>,<b>D</b>) Volcano plots of DEGs in the CR vs. control groups (<b>C</b>) and in the CREX vs. EX groups (<b>D</b>). The top 20 genes with the largest absolute values for log2FC were labeled (down: <span class="html-italic">p</span> &lt; 0.05 and log2FC &lt; −0.58; up: <span class="html-italic">p</span> &lt; 0.05 and log2FC &gt; 0.58). (<b>E</b>) Enriched GO terms for all DEGs in the skeletal muscle upon CR. (<b>F</b>) Enriched KEGG pathways for all DEGs in the skeletal muscle upon CR. (<b>G</b>) Enriched GO terms for all DEGs in the skeletal muscle upon CREX. (<b>H</b>) Enriched KEGG pathways for all DEGs in the skeletal muscle upon CREX. (<b>I</b>) Dot plot of genes’ log2FC in CR vs. control groups and CREX vs. EX groups. Dots with different colors represent genes in different patterns. Stable, genes that were not differently expressed in the CR vs. control groups or CREX vs. EX groups; Both down, downregulated DEGS across the two comparisons; Both up, upregulated DEGS across the two comparisons; CR down, specific downregulated DEGS in the comparison between the CR and control groups; CR up, upregulated DEGS in the comparison between the CR and control groups; CREX down, specific downregulated DEGS in the comparison between the CREX and EX groups; CREX up, upregulated DEGS in the comparison between the CREX and EX groups. (<b>J</b>) Venn plot of common and distinct DEGs upon CR with or without EX. Brick red, enriched GO terms for upregulated DEGs; navy blue, enriched GO terms for downregulated DEGs; bright red, enriched KEGG pathways for upregulated DEGs; green, enriched KEGG pathways for downregulated DEGs.</p>
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<p>GO terms and KEGG pathways enriched for DEGs encoding myokines upon CR with or without EX. (<b>A</b>,<b>B</b>) Heatmap plots of DEGs encoding myokines in the CR vs. control groups (<b>A</b>) and in the CREX vs. EX groups (<b>B</b>). (<b>C</b>) Venn plot of common and distinct DEGs encoding myokines upon CR with or without EX. (<b>D</b>) Enriched GO terms for common DEGs encoding myokines in the skeletal muscle upon CR with or without EX. (<b>E</b>) Enriched KEGG pathways for common DEGs encoding myokines in the skeletal muscle upon CR with or without EX. (<b>F</b>) Enriched GO terms for specific DEGs encoding myokines in the skeletal muscle upon CR without EX. (<b>G</b>) Enriched KEGG pathways for specific DEGs encoding myokines in the skeletal muscle upon CR. (<b>H</b>) Enriched GO terms for specific DEGs encoding myokines in the skeletal muscle upon CR with EX. (<b>I</b>) Enriched KEGG pathways for specific DEGs encoding myokines in the skeletal muscle upon CR with EX. Brick red, enriched GO terms for upregulated DEGs encoding myokines; navy blue, enriched GO terms for downregulated DEGs encoding myokines; bright red, enriched KEGG pathways for upregulated DEGs encoding myokines; green, enriched KEGG pathways for downregulated DEGs encoding myokines.</p>
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<p>Cell proportion alterations as a result of CR with or without EX across the two tissues. (<b>A</b>) Boxplots of estimated cell type proportions in BAT bulk RNA sequencing from four intervention groups. Cell populations with numbers equal to or close to zero are not shown. (<b>B</b>) Boxplots of estimated cell type proportions in skeletal muscle bulk RNA sequencing from four intervention groups. Cell populations with numbers equal to or close to zero are not shown. Statistical significance was measured using unpaired one-tailed t tests or Wilcoxon rank sum and signed rank tests. Data are represented as means ± SEM. * <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; 0.001; ns, not significant. FAP, fibro-adipogenic progenitor.</p>
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<p>The crosstalk between BAT and muscle. (<b>A</b>) Gene networks for selected DEGs from the two tissues that encoded interacting proteins clustered by MCODE, with each cluster named according to the most significantly enriched pathway. The clusters are colored according to the DEG direction and tissue category. (<b>B</b>) NicheNet workflow (left top), the activity of the top five putative BAT ligands (left bottom) and the interaction potential for the putative receptors of the top five BAT ligands in skeletal muscle (right). (<b>C</b>) Predicted interactions between BAT ligands and their predicted skeletal muscle target genes associated with the indicated KEGG pathways. (<b>D</b>,<b>E</b>) Expressions of the genes encoding the top five predicted upstream ligands in BAT (<b>D</b>) and of their top target genes in skeletal muscle related to the indicated KEGG pathways (<b>E</b>). (<b>F</b>) NicheNet workflow (bottom), the activity of the top five putative skeletal muscle ligands (bottom) and the interaction potential for the putative BAT receptors (right). (<b>G</b>) Predicted interactions between skeletal muscle-derived ligands and their predicted BAT target genes belonging to the indicated KEGG pathways. (<b>H</b>,<b>I</b>) Expressions of the genes encoding the top five predicted ligands in skeletal muscle (<b>H</b>) and of their top target genes in BAT associated with the indicated KEGG pathways (<b>I</b>).</p>
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13 pages, 302 KiB  
Article
The Relationship between Sleep Duration and Metabolic Syndrome Severity Scores in Emerging Adults
by Bilal A. Chaudhry, Michael S. Brian and Jesse Stabile Morrell
Nutrients 2023, 15(4), 1046; https://doi.org/10.3390/nu15041046 - 20 Feb 2023
Cited by 5 | Viewed by 4189
Abstract
Background: Research suggests sleep duration can influence metabolic systems including glucose homeostasis, blood pressure, hormone regulation, nervous system activity, and total energy expenditure (TEE), all of which are related to cardiometabolic disease risk, even in young adults. The purpose of this study was [...] Read more.
Background: Research suggests sleep duration can influence metabolic systems including glucose homeostasis, blood pressure, hormone regulation, nervous system activity, and total energy expenditure (TEE), all of which are related to cardiometabolic disease risk, even in young adults. The purpose of this study was to examine the relationship between sleep duration and metabolic syndrome severity scores (MSSS) in a sample of emerging adults (18–24 y/o). Methods: Data were collected between 2012 and 2021 from the College Health and Nutrition Assessment Survey, an ongoing, cross-sectional study conducted at a midsized northeastern university. Anthropometric, biochemical, and clinical measures were obtained following an overnight fast and used to assess the prevalence of metabolic syndrome (MetS). MetS severity scores (MSSS) were calculated using race- and sex-specific formulas. Sleep duration was calculated from the difference in self-reported bedtime and wake time acquired through an online survey. ANCOVA was used to examine the relationship between sleep duration and MetS severity score while adjusting for covariates (age, sex, BMI, physical activity level, smoking status, alcohol consumption, and academic major). Results: In the final sample (n = 3816), MetS (≥3 criteria) was present in 3.3% of students, while 15.4% of students presented with ≥2 MetS criteria. Mean MSSS was −0.65 ± 0.56, and the reported sleep duration was 8.2 ± 1.3 h/day. MSSS was higher among low sleepers (<7 h/day) and long sleepers (>9 h/day) compared to the reference sleepers (7–8 h/day) (−0.61 ± 0.02 and −0.63 ± 0.01 vs. −0.7 ± 0.02, respectively, p < 0.01). Conclusions: Our findings suggest short (<7 h/day) and long (>9 h/day) sleep durations raise the risk of MetS in a sample of emerging adults. Further research is needed to elucidate the impact of improving sleep habits on future disease risk. Full article
(This article belongs to the Section Nutrition and Metabolism)
12 pages, 1537 KiB  
Article
Pilot Study of the Applicability, Usability, and Accuracy of the Nutricate© Online Application, a New Dietary Intake Assessment Tool for Managing Infant Cow’s Milk Allergy
by Pauline Azzano, Line Samier, Alain Lachaux, Florence Villard Truc and Laurent Béghin
Nutrients 2023, 15(4), 1045; https://doi.org/10.3390/nu15041045 - 20 Feb 2023
Cited by 1 | Viewed by 2349
Abstract
Background/Objectives: The mainstay treatment of cow’s milk allergy (CMA) is to remove cow’s milk proteins from children’s dietary intake. In this context, dietary intake of children with CMA should be particularly checked and monitored. The objective of this study was to assess the [...] Read more.
Background/Objectives: The mainstay treatment of cow’s milk allergy (CMA) is to remove cow’s milk proteins from children’s dietary intake. In this context, dietary intake of children with CMA should be particularly checked and monitored. The objective of this study was to assess the applicability, usability, and accuracy of a new dietary intake (DI) assessment online tool (Nutricate© online application) for managing CMA in children. Subjects/Methods: This study used a pre-existing database of DI from the Nutricate© online application. DIs from 30 CMA children were used to compare micro/macronutrients (energy, protein, calcium, and iron intakes) calculated by Nutricate© and NutriLog© as the reference method. Comparisons were performed using the Pearson correlation analysis and the Bland–Altman plot. The Nutricate© tool usability was assessed via a System Usability Scale questionnaire (SUSq). Results: Correlation coefficient between the levels of micro/macronutrients obtained by Nutrilog© and Nutricate© software were highly significant (p = 0.0001) and were well-correlated (R coefficient > 0.6), indicating a very good concordance between the two methods. This observation was reinforced by the Bland–Altman plot, indicating the absence of proportional or fixed bias for energy, protein, calcium, and iron intakes. The mean SUSq score obtained was 81 ± 14, which is considered to be an excellent score. Conclusions: Nutricate© online application is a reliable method to assess micro/macronutrient (energy, protein, calcium, and iron intakes) intake in CMA children. Applicability and usability of this new dietary intake assessment online tool is excellent. Full article
(This article belongs to the Section Pediatric Nutrition)
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<p>(<b>a</b>) Screenshot of the Nutricate© homepage (translated version). (<b>b</b>) Screenshot of Nutricate© food pictures with increasing portion sizes (translated version).</p>
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<p>(<b>a</b>) Bland–Altman plot for energy intake between Nutricate© and Nutrilog© (kcal/d). (<b>b</b>) Bland–Altman plot for protein intake between Nutricate© and Nutrilog© (g). (<b>c</b>) Bland–Altman plot for calcium intake between Nutricate© and Nutrilog© (mg/d). (<b>d</b>) Bland–Altman plot for iron intake between Nutricate© and Nutrilog© (µg/d). The differences between the two methods were calculated as follows: Nutrilog©–Nutricate©. The 95% upper limit (UL) and lower limit (LL) of agreement (SD 1.96) are depicted as a long, dashed line. The full line indicates the mean difference and zero.</p>
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<p>Screenshot of the Nutricate© individual dietary counseling report.</p>
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12 pages, 1240 KiB  
Article
Prognostic Impact of Nutritional Status on Overall Survival and Health-Related Quality of Life in Men with Advanced Prostate Cancer
by Luka Cavka, Maja Pohar Perme, Nada Rotovnik Kozjek and Bostjan Seruga
Nutrients 2023, 15(4), 1044; https://doi.org/10.3390/nu15041044 - 20 Feb 2023
Cited by 3 | Viewed by 2253
Abstract
Purpose: Prognostic role of nutritional status (NS) in patients with metastatic castrate-resistant prostate cancer (mCRPC) is unknown. We hypothesized that patients’ NS at the presentation of mCRPC is prognostic for health-related quality of life (HRQoL) and overall survival (OS). Methods: We conducted a [...] Read more.
Purpose: Prognostic role of nutritional status (NS) in patients with metastatic castrate-resistant prostate cancer (mCRPC) is unknown. We hypothesized that patients’ NS at the presentation of mCRPC is prognostic for health-related quality of life (HRQoL) and overall survival (OS). Methods: We conducted a prospective observational study in mCRPC patients. At enrollment, we allocated each patient into one of four NS categories: (i) well-nourished (WN), (ii) nutritional risk without sarcopenia/cachexia (NR), (iii) sarcopenia, or (iv) cachexia. We sought the prognostic role of the NS for OS and HRQoL by regression models. Results: 141 patients were included into our study. When compared to WN patients, those with NR and cachexia had a higher chance of worse HRQoL (OR 3.45; 95% CI [1.28 to 9.09], and OR 4.17; 95% CI [1.28 to 12.5], respectively), as well as shorter OS (HR 2.04; 95% CI [1.19 to 3.39] and HR 2.9; 95% CI [1.56 to 5.41], respectively). However, when accounting for possible confounding factors, we could not prove the significant importance of NS for chosen outcomes. Conclusions: Suboptimal NS might be an unfavorable prognostic factor for HRQoL and OS. Further interventional studies focusing on therapy or prevention are warranted. Full article
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<p>Algorithm for allocation in nutritional status category. (BMI body mass index, CRP C-reactive protein, Hb hemoglobin, PG-SGA patient generated subjective global assessment).</p>
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<p>Flow chart of patients included into the study.</p>
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<p>Distribution of actual and attributed HRQoL data six months after enrollment in each NS category according to the best-case scenario (all 21 patients not available for assessment for unknown reasons were attributed favorable HRQoL and all 27 patients not available for assessment for disease-related reasons were attributed unfavorable HRQoL).</p>
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<p>Kaplan Mayer curves of overall survival according to nutritional status.</p>
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15 pages, 5902 KiB  
Article
Protective Effects of Hydroxyphenyl Propionic Acids on Lipid Metabolism and Gut Microbiota in Mice Fed a High-Fat Diet
by Jingling Guo, Pan Wang, Yifan Cui, Xiaosong Hu, Fang Chen and Chen Ma
Nutrients 2023, 15(4), 1043; https://doi.org/10.3390/nu15041043 - 20 Feb 2023
Cited by 12 | Viewed by 2806
Abstract
Gut microbiota imbalances lead to the pathogenesis of non-alcoholic fatty liver disease (NAFLD), which is primarily accompanied by hepatic steatosis. Hydroxyphenyl propionic acids (HPP) have shown great potential in inhibiting lipid accumulation but their protective effects concerning NAFLD and intestinal microbiota have remained [...] Read more.
Gut microbiota imbalances lead to the pathogenesis of non-alcoholic fatty liver disease (NAFLD), which is primarily accompanied by hepatic steatosis. Hydroxyphenyl propionic acids (HPP) have shown great potential in inhibiting lipid accumulation but their protective effects concerning NAFLD and intestinal microbiota have remained unclear. In this paper, we investigated the efficacies of 3-HPP and 4-HPP on hepatic steatosis and gut flora in mice fed a high-fat diet (HFD). We found that 3-HPP and 4-HPP administration decreased body weight and liver index, ameliorated dyslipidemia, and alleviated hepatic steatosis. Furthermore, 3-HPP and 4-HPP enhanced the multiformity of gut microbiota; improved the relative abundance of GCA-900066575, unidentified_Lachnospiraceae, and Lachnospiraceae_UCG-006 at genus level; increased concentration of acetic acid, propionic acid and butanoic acid in faeces; and reduced systemic endotoxin levels in NAFLD mice. Moreover, 4-HPP upregulated the relative abundance of genera Rikenella and downregulated the relative abundance of Faecalibaculum. Furthermore, 3-HPP and 4-HPP regulated lipid metabolism and ameliorated gut dysbiosis in NAFLD mice and 4-HPP was more effective than 3-HPP. Full article
(This article belongs to the Special Issue The Perspectives of Plant Natural Products for Mitigation of Obesity)
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<p>The influence of 3-hydroxyphenyl propionic acid (3−HPP) and 4−HPP on physiological indexes. (<b>A</b>) Schematic diagram of animal experiment period. (<b>B</b>) Final body weight (BW). (<b>C</b>) BW gain. (<b>D</b>) Energy intake. (<b>E</b>) Liver index. Data are expressed as mean ± SD. n = 6 if not specified. According to Duncan’s test, mean values with different letters mean significant differences at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The impacts of 3-HPP and 4-HPP on hepatic steatosis and liver injury. (<b>A</b>) Graphs of H&amp;E staining and ORO staining. (<b>B</b>) Hepatic TG levels. (<b>C</b>) Hepatic TC levels. (<b>D</b>) Serum contents of ALT. (<b>E</b>) Serum contents of AST. Data are shown as the mean ± SD. n = 6 if not specified. According to Duncan’s test, mean values with different letters mean significant differences at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The impacts of 3−HPP and 4−HPP on gene expression of hepatic lipid metabolism. mRNA expression of (<b>A</b>) Fasn, (<b>B</b>) Acaca, (<b>C</b>) Thrsp, (<b>D</b>) Elovl6, (<b>E</b>) Dgat1, (<b>F</b>) Dgat2, (<b>G</b>) Sqle, (<b>H</b>) Acly, and (<b>I</b>) Ppara in liver. Data are shown as the mean ± SD. n = 6 if not specified. According to Duncan’s test, mean values with different letters mean significant differences at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The impacts of 3−HPP and 4−HPP on α and β diversity of gut flora. ACE (<b>A</b>), Chao (<b>B</b>), and Shannon (<b>C</b>) indexes. (<b>D</b>) Simpson’s index of diversity ACE. (<b>E</b>) NMDS analysis based on Weighted Unifrac distance. Data are expressed as mean ± SD. n = 5 if not specified. According to Duncan’s test, mean values with different letters denote significant differences at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The effects of 3−HPP and 4−HPP on the relative abundance of gut microbiota at the phylum level. Relative abundance of <span class="html-italic">Firmicutes</span> (<b>A</b>), <span class="html-italic">Bacteroidetes</span> (<b>B</b>), <span class="html-italic">unidentified_Bacteria</span> (<b>D</b>), <span class="html-italic">Verrucomicrobita</span> (<b>E</b>), and <span class="html-italic">Deferribacteres</span> (<b>F</b>). (<b>C</b>) The ratio of <span class="html-italic">Firmicutes</span> to <span class="html-italic">Bacteroidetes</span>. Data are expressed as means ± SDs. n = 5 if not specified. According to Duncan’s test, mean values with different letters denote significant differences at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The effects of 3−HPP and 4−HPP on the relative abundance of key genera in different groups. Relative abundance of <span class="html-italic">Desulfovibrio</span> (<b>A</b>) between the ND and HFD groups. Relative abundance of <span class="html-italic">Lachnospiraceae_UCG-006</span> (<b>B</b>), <span class="html-italic">GCA-900066575</span> (<b>C</b>), and <span class="html-italic">unidentified_Lachnospiraceae</span> (<b>D</b>) between the 3−HPP and HFD groups. Relative abundance of <span class="html-italic">Rikenella</span> (<b>E</b>), <span class="html-italic">Faecalibaculum</span> (<b>F</b>), <span class="html-italic">Lachnospiraceae_UCG-006</span> (<b>G</b>), <span class="html-italic">GCA-900066575</span> (<b>H</b>), and <span class="html-italic">unidentified_Lachnospiraceae</span> (<b>I</b>) between the 4−HPP and HFD groups. Data are expressed as means ± SDs. n = 5 if not specified. The results were analysed by a Wilcoxon rank sum test. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 compared to the HFD group.</p>
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<p>The effects of 3−HPP and 4−HPP on the predicated metabolic profile of gut microbiota. (<b>A</b>) Comparison between HFD and 3−HPP. (<b>B</b>) Comparison between HFD and 4−HPP. The key metabolic pathways predicted by PICRUSt2 and KEGG were selected based on a t-test at <span class="html-italic">p</span> &lt; 0.05. n = 5 if not specified. The colour of the circle is the same as the group with a higher function. The line segment indicates the 95% confidence interval.</p>
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<p>The effects of 3−HPP and 4−HPP on SCFAs content of feces. Fecal concentrations of acetic acid (<b>A</b>), propanoic acid (<b>B</b>), butanoic acid (<b>C</b>), isobutyric acid (<b>D</b>), valeric acid (<b>E</b>), isovaleric acid (<b>F</b>), hexanoic acid (<b>G</b>), and isohexanoic acid (<b>H</b>). n = 6 if not specified. According to Duncan’s test, mean values with different letters mean significant differences at <span class="html-italic">p</span> &lt; 0.05.</p>
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13 pages, 3980 KiB  
Article
Effects of Chronic Administration of Green Tea Ethanol Extract on Sleep Architecture in Mice: A Comparative Study with a Representative Stimulant Caffeine
by Duhyeon Kim, Seonghui Kim, Minseok Yoon, Min Young Um and Suengmok Cho
Nutrients 2023, 15(4), 1042; https://doi.org/10.3390/nu15041042 - 20 Feb 2023
Viewed by 3062
Abstract
Wakefulness is defined as a state in which individuals can react to a change in situations. The number of people staying awake and compensating for lack of sleep has increased in recent years. Caffeine, a representative stimulant, is the most extensively consumed compound [...] Read more.
Wakefulness is defined as a state in which individuals can react to a change in situations. The number of people staying awake and compensating for lack of sleep has increased in recent years. Caffeine, a representative stimulant, is the most extensively consumed compound globally and is mainly consumed through coffee. Although green tea (Camellia sinensis L.) contains high caffeine content like coffee, its arousal-inducing effects have not yet been studied. In the present study, we aimed to identify the arousal-inducing effect of GT during a chronic administration period (three weeks) using analysis of sleep architecture. Treatment with GT (1500 mg/kg) significantly elevated the sleep latency and wakefulness throughout the treatment period, and chronic administration of GT consistently maintained an increase in wakefulness for up to 3 h. During the treatment period, the arousal-inducing effect of GT (1500 mg/kg) occurred without any change in the tolerance phenomenon or withdrawal symptoms, similar to that observed with caffeine (25 mg/kg). GT (1500 mg/kg) containing 95.6 mg/kg of caffeine did not produce a better arousal-inducing effect than caffeine at 25 mg/kg. These results indicate that the arousal-inducing effect of GT persisted for three weeks without adverse effects and that GT can control the arousal-inducing effects of caffeine due to the hypnotic effects of its other constituents. Full article
(This article belongs to the Section Phytochemicals and Human Health)
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<p>Experimental procedure involving chronic administration of GT for polysomnographic recordings. BL, baseline; p.o., per os administration.</p>
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<p>Effects of chronic administration of caffeine (25 mg/kg) and GT (1500 mg/kg) on (<b>a</b>) sleep latency and (<b>b</b>) amount of wakefulness and NREMS stages during the 3 h after administration. Grey bars illustrate the baseline day (vehicle). Brown and green bars illustrate caffeine and GT treatments, respectively. Light brown and green bars illustrate the withdrawal (WD) days after caffeine and GT treatments, respectively. Every column denotes the mean ± SEM (<span class="html-italic">n</span> = 7–8). *** <span class="html-italic">p</span> &lt; 0.001 indicates significant differences compared to the vehicle (Dunnett’s test). BL, baseline; CF, caffeine; GT, green tea ethanol extract; NREMS, non-rapid-eye-movement sleep; Wake, wakefulness; SEM, standard error of the mean.</p>
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<p>Time-course changes of caffeine (25 mg/kg) treatment during each stage over the whole administration period. Grey circles illustrate the baseline day (vehicle). Brown circles illustrate caffeine treatment. Light brown circles illustrate the withdrawal (WD) day during the end of caffeine treatment. Every circle denotes the hourly mean ± SEM (<span class="html-italic">n</span> = 7–8) in each stage. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 indicate significant differences compared to the vehicle (Dunnett’s test). BL, baseline; CF, caffeine; NREMS, non-rapid-eye-movement sleep; REMS, rapid-eye-movement sleep; Wake, wakefulness; SEM, standard error of the mean.</p>
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<p>Time-course changes of GT (1500 mg/kg) treatment during each stage over the whole administration period. Grey circles indicate the baseline day (vehicle). Green circles illustrate GT treatment. Light green circles illustrate the withdrawal (WD) day during the end of GT treatment. Every circle denotes the hourly mean ± SEM (<span class="html-italic">n</span> = 7–8) in each stage. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 indicate significant differences compared to the vehicle (Dunnett’s test). BL, baseline; GT, green tea ethanol extract; NREMS, non-rapid-eye-movement sleep; REMS, rapid-eye-movement sleep; Wake, wakefulness; SEM, standard error of the mean.</p>
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<p>Features of sleep–wake bouts during the 3 h following sample treatment for the chronic administration period (21 days). (<b>a</b>) Changes in mean duration of wakefulness and NREMS after caffeine (25 mg/kg) treatment. (<b>b</b>) Changes in mean duration of wakefulness and NREMS after GT (1500 mg/kg) treatment. (<b>c</b>) The number of bouts of wakefulness and NREMS after caffeine treatment. (<b>d</b>) The number of bouts of wakefulness and NREMS after GT treatment. Grey bars illustrate the baseline day (vehicle). Brown and green bars illustrate days when caffeine and GT treatment were administered, respectively. Light brown and green bars illustrate withdrawal (WD) days after caffeine and GT treatments, respectively. Every column denotes the mean ± SEM (<span class="html-italic">n</span> = 7–8). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001, indicate significant differences compared to the vehicle (Dunnett’s test). CF, caffeine; GT, green tea ethanol extract; NREMS, non-rapid-eye-movement sleep; Wake, wakefulness; SEM, standard error of the mean.</p>
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<p>(<b>a</b>) Changes in stage transition number during the 3 h following caffeine (25 mg/kg) and GT (1500 mg/kg) treatments for the chronic administration period (21 days). Changes in the number of bouts of (<b>b</b>) wakefulness and (<b>c</b>) NREMS after caffeine and GT treatments during the chronic administration period (21 days). Grey bars illustrate the baseline day (vehicle). Brown and green bars illustrate caffeine and GT treatments, respectively. Light green and brown bars illustrate the withdrawal (WD) day after of GT and caffeine treatments, respectively. Every column denotes the mean ± SEM (<span class="html-italic">n</span> = 7–8). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 indicate significant differences compared to the vehicle (Dunnett’s test). CF, caffeine; GT, green tea ethanol extract; NREMS, non-rapid-eye-movement sleep; Wake, wakefulness; SEM, standard error of the mean.</p>
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<p>Changes in the EEG power density curve in NREMS during the administration of (<b>a</b>) caffeine and (<b>b</b>) GT. Grey curves illustrate the baseline day (vehicle). Brown and green curves illustrate caffeine and GT treatments, respectively. Light brown and green curves illustrate the withdrawal (WD) days. The solid bar (—) illustrates the delta wave range from 0.5 to 4 Hz. The delta activity compared with vehicle is presented in the inset bar graph. CF, caffeine; GT, green tea ethanol extract; NREMS, non-rapid-eye-movement sleep; Wake, wakefulness.</p>
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<p>HPLC analysis chromatogram of caffeine standard (<b>a</b>) and GT (<b>b</b>). GT, green tea ethanol extract.</p>
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13 pages, 618 KiB  
Systematic Review
The Influence of Nutritional Intervention in the Treatment of Hashimoto’s Thyroiditis—A Systematic Review
by Karolina Osowiecka and Joanna Myszkowska-Ryciak
Nutrients 2023, 15(4), 1041; https://doi.org/10.3390/nu15041041 - 20 Feb 2023
Cited by 13 | Viewed by 18809
Abstract
Diet can be a complementary treatment for Hashimoto’s disease by affecting thyroid function and anti-inflammatory properties. It is still unclear which dietary strategy would be the most beneficial. The aim of this systematic review is to examine all the data currently available in [...] Read more.
Diet can be a complementary treatment for Hashimoto’s disease by affecting thyroid function and anti-inflammatory properties. It is still unclear which dietary strategy would be the most beneficial. The aim of this systematic review is to examine all the data currently available in the literature on the effects of nutritional intervention on biochemical parameters (anti-thyroid antibody and thyroid hormones levels) and characteristic symptoms in the course of Hashimoto’s thyroiditis. This systematic review was prepared based on PRISMA guidelines. Articles in PubMed and Scopus databases published up to November 2022 were searched. As a result of the selection, out of 1350 publications, 9 were included for further analysis. The nutritional interventions included the following: elimination of gluten (3 articles) or lactose (1 article), energy restriction with or without excluding selected foods (n = 2), consumption of Nigella sativa (n = 2), or dietary iodine restriction (n = 1). The intervention duration ranged from 21 days to 12 months and included individuals with various thyroid function. Of the nine studies, three studies were female only. An improvement was observed during an energy deficit and after the elimination of selected ingredients (e.g., gluten, lactose, or goitrogens), as well as after the intervention of Nigella sativa. These interventions improved antibody levels against peroxidase (anti-TPO), (thyrotropin) TSH, and free thyroxine (fT4). No improvement was seen on the iodine-restricted diet. Varied outcomes of analyzed dietary interventions may be due to the heterogeneous thyroid condition, high variability between patients, and differences in habitual intake of critical nutrients (e.g., iodine, selenium, and iron) in different populations. Therefore, there is a great need for further experimental studies to determine whether any nutritional interventions are beneficial in Hashimoto’s disease. Full article
(This article belongs to the Section Nutritional Immunology)
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<p>PRISMA flow diagram of the selected and included articles. HT—Hashimoto’s thyroiditis; AITD—autoimmune thyroid disease.</p>
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11 pages, 289 KiB  
Article
Higher Intake of Vegetable Protein and Lower Intake of Animal Fats Reduce the Incidence of Diabetes in Non-Drinking Males: A Prospective Epidemiological Analysis of the Shika Study
by Aya Ogawa, Hiromasa Tsujiguchi, Masaharu Nakamura, Koichi Hayashi, Akinori Hara, Keita Suzuki, Sakae Miyagi, Takayuki Kannon, Chie Takazawa, Jiaye Zhao, Yasuhiro Kambayashi, Yukari Shimizu, Aki Shibata, Tadashi Konoshita, Fumihiko Suzuki, Hirohito Tsuboi, Atsushi Tajima and Hiroyuki Nakamura
Nutrients 2023, 15(4), 1040; https://doi.org/10.3390/nu15041040 - 19 Feb 2023
Cited by 2 | Viewed by 3214
Abstract
Although nutrient intake and alcohol consumption are both closely associated with the incidence of diabetes, their interrelationships remain unclear. Therefore, we herein have investigated the interrelationships among nutrient intake, alcohol consumption, and the incidence of diabetes using longitudinal data. This study included 969 [...] Read more.
Although nutrient intake and alcohol consumption are both closely associated with the incidence of diabetes, their interrelationships remain unclear. Therefore, we herein have investigated the interrelationships among nutrient intake, alcohol consumption, and the incidence of diabetes using longitudinal data. This study included 969 residents ≥40 years living in Japan. In 2011 and 2012, a baseline study was conducted using questionnaires on basic demographics, diabetes, nutrient intake, and lifestyle habits. In 2018 and 2019, a follow-up study was performed using questionnaires and medical records on diabetes. Two-way analysis of covariance (two-way ANCOVA) was used to test the interactions of drinking habits and diabetes incidence on nutrients intake. The prospective relationship between nutrient intake at baseline and the incidence of diabetes in the follow-up stratified by drinkers and non-drinkers was evaluated using multiple logistic regression analysis. Interactions were observed for vegetable protein intake (p = 0.023) and animal fat intake (p = 0.016) in males. Vegetable protein intake negatively correlated with the incidence of diabetes in non-drinkers (odds ratio (OR): 0.208; 95% confidence interval (95% CI): 0.046–0.935; p = 0.041). Furthermore, animal fat intake positively correlated with the incidence of diabetes in non-drinkers (OR: 1.625; 95% CI: 1.020–2.589; p = 0.041). Therefore, vegetable protein and animal fat intakes in combination with drinking habits need to be considered for the prevention of diabetes. Full article
(This article belongs to the Special Issue The Role of Dietary Fatty Acids in Metabolic Health)
12 pages, 522 KiB  
Review
The Effect of β-Alanine Supplementation on Performance, Cognitive Function and Resiliency in Soldiers
by Ishay Ostfeld and Jay R. Hoffman
Nutrients 2023, 15(4), 1039; https://doi.org/10.3390/nu15041039 - 19 Feb 2023
Cited by 15 | Viewed by 8078
Abstract
β-alanine is a nonessential amino acid that combines with the amino acid histidine to form the intracellular dipeptide carnosine, an important intracellular buffer. Evidence has been well established on the ability of β-alanine supplementation to enhance anaerobic skeletal muscle performance. As a result, [...] Read more.
β-alanine is a nonessential amino acid that combines with the amino acid histidine to form the intracellular dipeptide carnosine, an important intracellular buffer. Evidence has been well established on the ability of β-alanine supplementation to enhance anaerobic skeletal muscle performance. As a result, β-alanine has become one of the more popular supplements used by competitive athletes. These same benefits have also been reported in soldiers. Evidence accumulated over the last few years has suggested that β-alanine can result in carnosine elevations in the brain, which appears to have broadened the potential effects that β-alanine supplementation may have on soldier performance and health. Evidence suggests that β-alanine supplementation can increase resilience to post-traumatic stress disorder, mild traumatic brain injury and heat stress. The evidence regarding cognitive function is inconclusive but may be more of a function of the stressor that is applied during the assessment period. The potential benefits of β-alanine supplementation on soldier resiliency are interesting but require additional research using a human model. The purpose of this review is to provide an overview of the physiological role of β-alanine and why this nutrient may enhance soldier performance. Full article
(This article belongs to the Section Sports Nutrition)
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<p>Physical performance and cognitive function changes subsequent to β-alanine supplementation in soldiers. Data from [<a href="#B52-nutrients-15-01039" class="html-bibr">52</a>,<a href="#B53-nutrients-15-01039" class="html-bibr">53</a>,<a href="#B54-nutrients-15-01039" class="html-bibr">54</a>,<a href="#B58-nutrients-15-01039" class="html-bibr">58</a>,<a href="#B61-nutrients-15-01039" class="html-bibr">61</a>].</p>
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15 pages, 2632 KiB  
Article
Immune-Enhancing Effects of Limosilactobacillus fermentum in BALB/c Mice Immunosuppressed by Cyclophosphamide
by SukJin Kim, Hwan Hee Lee, Chang-Ho Kang, Hyojeung Kang and Hyosun Cho
Nutrients 2023, 15(4), 1038; https://doi.org/10.3390/nu15041038 - 19 Feb 2023
Cited by 5 | Viewed by 2743
Abstract
This study evaluates the immune-enhancing effects of Limosilactobacillus fermentum on cyclophosphamide (CP)-induced immunosuppression in BALB/c mice. In vitro, the expressions of pro-inflammatory cytokines and MAPK signaling molecules in Raw264.7 cells were analyzed by ELISA and Western blot analysis. Moreover, cell proliferation, surface receptor [...] Read more.
This study evaluates the immune-enhancing effects of Limosilactobacillus fermentum on cyclophosphamide (CP)-induced immunosuppression in BALB/c mice. In vitro, the expressions of pro-inflammatory cytokines and MAPK signaling molecules in Raw264.7 cells were analyzed by ELISA and Western blot analysis. Moreover, cell proliferation, surface receptor expression, and cytotoxicity of NK-92 cells were examined by Cell Counting Kit-8, CytoTox96 assay, and flow cytometry, respectively. To investigate the immune-enhancing effects of selected L. fermentum strains in vivo, these strains were orally administered to BALB/c mice for 2 weeks, and CP was intraperitoneally injected. Then, liver, spleen, and whole blood were isolated from each animal. Administration of single L. fermentum strains or their mixture sustained the spleen weight, the counts of white blood cells compared to non-fed group. Splenocyte proliferation and NK cytotoxicity were significantly increased in all L. fermentum-fed groups. The frequency of B220+ cells was also significantly enhanced in splenocytes isolated from L. fermentum groups. In addition, the production of cytokines (TNF-α, IFN-γ) and antibodies was recovered in splenocyte supernatants isolated from L. fermentum groups. In conclusion, L. fermentum could be a suitable functional food additive for immune-enhancing effect. Full article
(This article belongs to the Special Issue Prebiotics and Probiotics in Immune Health)
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<p>Effects of <span class="html-italic">Bifidobacterium</span> and <span class="html-italic">Limosilactobacillus</span> on pro-inflammatory cytokine production and the expression of MAPK signaling molecules in RAW 264.7 cells. Cells were incubated with <span class="html-italic">Bifidobacterium</span> or <span class="html-italic">Limosilactobacillus</span> (5 mg/mL) or lipopolysaccharide (LPS; 1 µg/mL) for 24 h and culture supernatants were harvested. Production of (<b>A</b>) TNF-α, (<b>B</b>) IL-6, and (<b>C</b>) IL-1β was measured by enzyme-linked immunosorbent assay. To examine MAPK signaling pathways, the following ratios were determined by Western blot analysis: (<b>D</b>) pErk/Erk, (<b>E</b>) pNF-κB/NF-κB and (<b>F</b>) TLR2/GAPDH. All data are means ± SD from three independent experiments. * <span class="html-italic">p</span> &lt; 0.05 vs. control cells.</p>
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<p>Effect of <span class="html-italic">Bifidobacterium</span> and <span class="html-italic">Limosilactobacillus</span> on NK-92 cells. (<b>A</b>) NK-92 cell proliferation determined using CCK-8 assay. (<b>B</b>) Cytotoxicity of NK-92 cells against K562 cells. (<b>C</b>) Secretion of granzyme B. (<b>D</b>,<b>F</b>) Representative FACS plots showing CD56+ and NKG2D+ expression. (<b>E</b>) and (<b>G</b>) Percentage of CD56+ and NKG2D+ expression. All data are means ± SD from three independent experiments. * <span class="html-italic">p</span> &lt; 0.05 vs. control cells.</p>
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<p>Effects of <span class="html-italic">L. fermentum</span> on body and organ weight changes in cyclophosphamide (CP)-treated immunosuppressed mice. Mice were intraperitoneally injected with CP (150 and 100 mg/kg) after administration of drinking water (control and CP-only groups), red ginseng (RG) extract (10 mg/kg), <span class="html-italic">L. fermentum</span> MG4538 (1 × 10<sup>9</sup> cells/mouse), <span class="html-italic">L. fermentum</span> MG5091 (1 × 10<sup>9</sup> cells/mouse), <span class="html-italic">L. fermentum</span> MG5159 (1 × 10<sup>9</sup> cells/mouse), or a mixture of MG4538, MG5091, and MG5159 (3 × 10<sup>9</sup> cells/mouse in total). (<b>A</b>) Whole body weight change was monitored daily until the experimental end point. (<b>B</b>) Liver and (<b>C</b>) spleen weight. All data are means ± SD (<span class="html-italic">n</span> = 6) and were analyzed with one-way ANOVA to compare differences between groups for each item. Different letters indicate significant difference between means at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effect of <span class="html-italic">L. fermentum</span> on the frequency of T cells and cytotoxicity of NK cells in CP-treated immunosuppressed mice. (<b>A</b>) Splenocyte proliferation, (<b>B</b>) cytotoxicity of NK cells against YAC-1 cells. Frequencies of (<b>C</b>) CD4+, (<b>D</b>) CD8+, and (<b>E</b>) B220+ cells were analyzed using flow cytometry. All data are means ± SD (<span class="html-italic">n</span> = 6) and were analyzed with one-way ANOVA to compare differences between groups for each item. Different letters indicate significant difference between means at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effect of <span class="html-italic">L. fermentum</span> on splenocyte cytokines (TNF-α, IFN-γ) and antibodies (IgM, total IgG) in CP-treated immunosuppressed mice. Primary mouse splenocytes were seeded in a 6-well flat-bottom plate with or without Con A (10 μg/mL) and incubated for 72 h. Then ELISA kits were used to measure the production of (<b>A</b>) IgM, (<b>B</b>) IgG, (<b>C</b>) TNF-α, and (<b>D</b>) IFN-γ. All data are means ± SD (<span class="html-italic">n</span> = 6) and were analyzed with one-way ANOVA to compare differences between groups for each item. Different letters indicate significant difference between means at <span class="html-italic">p</span> &lt; 0.05: uppercase, comparisons among cells with ConA; lowercase, comparisons among cells without ConA.</p>
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<p>Effect of <span class="html-italic">L. fermentum</span> on the intestinal mucosal barrier in immunosuppressed mice. (<b>A</b>) H&amp;E staining. Immunohistochemistry of (<b>B</b>) occludin and (<b>C</b>) ZO-1. Scale bars, 100 px. Black arrows indicate the dots of occludin and ZO-1 (magnification 400×).</p>
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16 pages, 1619 KiB  
Article
Grape-Seed Proanthocyanidins Modulate Adipose Tissue Adaptations to Obesity in a Photoperiod-Dependent Manner in Fischer 344 Rats
by Èlia Navarro-Masip, Marina Colom-Pellicer, Francesca Manocchio, Anna Arola-Arnal, Francisca Isabel Bravo, Begoña Muguerza and Gerard Aragonès
Nutrients 2023, 15(4), 1037; https://doi.org/10.3390/nu15041037 - 19 Feb 2023
Cited by 3 | Viewed by 2699
Abstract
Seasonal rhythms drive metabolic adaptations that influence body weight and adiposity. Adipose tissue is a key regulator of energy homeostasis in the organism, and its healthiness is needed to prevent the major consequences of overweight and obesity. In this context, supplementation with proanthocyanidins [...] Read more.
Seasonal rhythms drive metabolic adaptations that influence body weight and adiposity. Adipose tissue is a key regulator of energy homeostasis in the organism, and its healthiness is needed to prevent the major consequences of overweight and obesity. In this context, supplementation with proanthocyanidins has been postulated as a potential strategy to prevent the alterations caused by obesity. Moreover, the effects of these (poly)phenols on metabolism are photoperiod dependent. In order to describe the impact of grape-seed proanthocyanidins extract (GSPE) on important markers of adipose tissue functionality under an obesogenic environment, we exposed Fischer 344 rats to three different photoperiods and fed them a cafeteria diet for five weeks. Afterwards, we supplemented them with 25 mg GSPE/kg/day for four weeks. Our results revealed that GSPE supplementation prevented excessive body weight gain under a long photoperiod, which could be explained by increased lipolysis in the adipose tissue. Moreover, cholesterol and non-esterified fatty acids (NEFAs) serum concentrations were restored by GSPE under standard photoperiod. GSPE consumption slightly helped combat the obesity-induced hypertrophy in adipocytes, and adiponectin mRNA levels were upregulated under all photoperiods. Overall, the administration of GSPE helped reduce the impact of obesity in the adipose tissue, depending on the photoperiod at which GSPE was consumed and on the type of adipose depots. Full article
(This article belongs to the Special Issue Effects of Polyphenol-Rich Foods on Chronic Diseases)
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<p>Adipocyte area (<b>A</b>), adipocyte volume (<b>B</b>), adipocyte number (<b>C</b>) and adipocyte area frequencies (<b>D</b>) of inguinal white adipose tissue (iWAT) of rats treated with grape seed proanthocyanidin extract (GSPE) at different photoperiods, 12 h of light:12 h of darkness (L12); 18 h of light:6 h of darkness (L18); 6 h of light:18 h of darkness (L6). Histological study of iWAT morphology of Fisher 344 rats fed with standard diet (STD) or cafeteria diet (CAF) for 9 weeks and treated with GSPE (25 mg/kg body weight) or vehicle (VH) the last 4 weeks of the study; STD-VH group; CAF-VH group; CAF-GSPE group, under different photoperiods; L12, L18 or L6. For adipocyte area frequency, adipocytes were distributed in two groups according to their areas (&lt;3000 or &gt;3000 μm<sup>2</sup>). The results are presented as the mean ± SEM (<span class="html-italic">n</span> = 6). Significant differences were assessed through two-way ANOVA analysis (<span class="html-italic">p</span> &lt; 0.05). Diet: diet effect within VH groups; GSPE: GSPE consumption effect within CAF groups; <b>#</b>: tendency (0.05 &lt; <span class="html-italic">p</span> &lt; 1). Different letters denote significant differences within each photoperiod group (assessed with one-way ANOVA followed by Tukey’s <span class="html-italic">post hoc</span> test, <span class="html-italic">p</span> &lt; 0.05; <b>#</b>: tendency: 0.05 &lt; <span class="html-italic">p</span> &lt; 1).</p>
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<p>Effect of grape seed proanthocyanidin extract (GSPE) consumption at different photoperiods, 12 h of light:12 h of darkness (L12); 18 h of light:6 h of darkness (L18); 6 h of light:18 h of darkness (L6) on the expression of gens related to adipogenesis, lipogenesis, lipolysis and adipokines in inguinal white adipose tissue (iWAT) of diet-induced obese rats. Fisher 344 rats were fed standard diet (STD) or cafeteria diet (CAF) for 9 weeks and treated with GSPE (25 mg/kg body weight) or vehicle (VH) the last 4 weeks of the study; STD-VH group; CAF-VH group; CAF-GSPE group, under different photoperiods; L12, L18 or L6. The expression of genes involved in adipogenesis (<b>A</b>), lipogenesis (<b>B</b>), lipolysis (<b>C</b>) and adipokines (<b>D</b>) was measured by qPCR and normalized by <span class="html-italic">Ppia</span>. The relative expression (presented as fold-change) of CAF-VH and CAF-GSPE was normalized to the corresponding STD-VH control group (L12 photoperiod). Significant differences were assessed through two-way ANOVA analysis (<span class="html-italic">p</span> &lt; 0.05). Diet: diet effect within VH groups; Diet * Photoperiod: interaction effect between diet and photoperiod within VH groups; GSPE * Photoperiod: interaction effect between GSPE consumption and photoperiod within CAF groups. Different letters denote significant differences within each photoperiod group (assessed with two-way ANOVA followed by Tukey’s <span class="html-italic">post hoc</span> test, <span class="html-italic">p</span> &lt; 0.05; <b>#</b>: tendency: 0.05 &lt; <span class="html-italic">p</span> &lt; 1).</p>
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<p>Adipocyte area (<b>A</b>), adipocyte volume (<b>B</b>), adipocyte number (<b>C</b>) and adipocyte area frequencies (<b>D</b>) of epididymal white adipose tissue (eWAT) of rats treated with grape seed proanthocyanidin extract (GSPE) at different photoperiods, 12 h of light:12 h of darkness (L12); 18 h of light:6 h of darkness (L18); 6 h of light:18 h of darkness (L6). Histological study of eWAT morphology of Fisher 344 rats fed with standard diet (STD) or cafeteria diet (CAF) for 9 weeks and treated with GSPE (25 mg/kg body weight) or vehicle (VH) the last 4 weeks of the study; STD-VH group; CAF-VH group; CAF-GSPE group, under different photoperiods; L12, L18 or L6. For adipocyte area frequency, adipocytes were distributed in two groups according to their areas (&lt;3000 or &gt;3000 μm<sup>2</sup>). The results are presented as the mean ± SEM (<span class="html-italic">n</span> = 6). Significant differences were assessed through two-way ANOVA analysis (<span class="html-italic">p</span> &lt; 0.05). Diet: diet effect within VH groups; GSPE: GSPE consumption effect within CAF groups; #: tendency (0.05 &lt; <span class="html-italic">p</span> &lt; 1). Different letters denote significant differences within each photoperiod group (assessed with one-way ANOVA followed by Tukey’s <span class="html-italic">post hoc</span> test, <span class="html-italic">p</span> &lt; 0.05; <b>#</b>: tendency: 0.05 &lt; <span class="html-italic">p</span> &lt; 1).</p>
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<p>Effect of grape seed proanthocyanidin extract (GSPE) consumption at different photoperiods, 12 h of light:12 h of darkness (L12); 18 h of light:6 h of darkness (L18); 6 h of light:18 h of darkness (L6) on the expression of gens related to adipogenesis, lipid transport, lipolysis and adipokines in epididymal white adipose tissue (eWAT) of diet-induced obese rats. Fisher 344 rats were fed standard diet (STD) or cafeteria diet (CAF) for 9 weeks and treated with GSPE (25 mg/kg body weight) or vehicle (VH) the last 4 weeks of the study; STD-VH group; CAF-VH group; CAF-GSPE group, under different photoperiods; L12, L18 or L6. The expression of genes involved in adipogenesis (<b>A</b>), lipid transport (<b>B</b>), lipolysis (<b>C</b>) and adipokines (<b>D</b>) was measured by qPCR and normalized by <span class="html-italic">Ppia</span>. The relative expression (presented as fold-change) of CAF-VH and CAF-GSPE was normalized to the corresponding STD-VH control group (L12 photoperiod). Significant differences were assessed through two-way ANOVA analysis (<span class="html-italic">p</span> &lt; 0.05). Diet: diet effect within VH groups; GSPE: GSPE consumption effect within CAF groups; Diet * Photoperiod: interaction effect between diet and photoperiod within VH groups; GSPE * Photoperiod: interaction effect between GSPE consumption and photoperiod within CAF groups; #: tendency: 0.05 &lt; <span class="html-italic">p</span> &lt; 1. Different letters denote significant differences within each photoperiod group (assessed with two-way ANOVA followed by Tukey’s <span class="html-italic">post hoc</span> test, <span class="html-italic">p</span> &lt; 0.05; <b>#</b>: tendency: 0.05 &lt; <span class="html-italic">p</span> &lt; 1).</p>
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<p>Effect of grape seed proanthocyanidin extract (GSPE) consumption at different photoperiods, 12 h of light:12 h of darkness (L12); 18 h of light:6 h of darkness (L18); 6 h of light:18 h of darkness (L6) on the expression of key metabolic genes in brown adipose tissue (BAT) of diet-induced obese rats. Fisher 344 rats were fed standard diet (STD) or cafeteria diet (CAF) for 9 weeks and treated with GSPE (25 mg/kg body weight) or vehicle (VH) the last 4 weeks of the study; STD-VH group; CAF-VH group; CAF-GSPE group, under different photoperiods; L12, L18 or L6. The gene expression of <span class="html-italic">Pgc1α</span> (<b>A</b>), <span class="html-italic">Cpt1β</span> (<b>B</b>), <span class="html-italic">Dio2</span> (<b>C</b>) and <span class="html-italic">Pparα</span> (<b>D</b>) was measured by qPCR and normalized by <span class="html-italic">Ppia</span>. The relative expression (presented as fold-change) of CAF-VH and CAF-GSPE was normalized to the corresponding STD-VH control group (L12 photoperiod). Significant differences were assessed through two-way ANOVA analysis (<span class="html-italic">p</span> &lt; 0.05). Diet: diet effect within VH groups; Diet * Photoperiod: interaction effect between diet and photoperiod within VH groups; GSPE * Photoperiod: interaction effect between GSPE consumption and photoperiod within CAF groups; #: tendency: 0.05 &lt; <span class="html-italic">p</span> &lt; 1. Different letters denote significant differences within each photoperiod group (assessed with two-way ANOVA followed by Tukey’s post hoc test, <span class="html-italic">p</span> &lt; 0.05; #: tendency: 0.05 &lt; <span class="html-italic">p</span> &lt; 1).</p>
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19 pages, 2829 KiB  
Review
Nutritional Approaches to Modulate Cardiovascular Disease Risk in Systemic Lupus Erythematosus: A Literature Review
by Karen Pesqueda-Cendejas, Melissa Rivera-Escoto, Mónica R. Meza-Meza, Bertha Campos-López, Isela Parra-Rojas, Margarita Montoya-Buelna and Ulises De la Cruz-Mosso
Nutrients 2023, 15(4), 1036; https://doi.org/10.3390/nu15041036 - 19 Feb 2023
Cited by 9 | Viewed by 4602
Abstract
Systemic lupus erythematosus (SLE) is a chronic pathology characterized by a bimodal mortality pattern attributed to clinical disease activity and cardiovascular disease (CVD). A complex interaction between traditional CVD risk factors such as obesity, dyslipidemia, smoking, insulin resistance, metabolic syndrome, and hypertension, as [...] Read more.
Systemic lupus erythematosus (SLE) is a chronic pathology characterized by a bimodal mortality pattern attributed to clinical disease activity and cardiovascular disease (CVD). A complex interaction between traditional CVD risk factors such as obesity, dyslipidemia, smoking, insulin resistance, metabolic syndrome, and hypertension, as well as the presence of non-traditional CVD risk factors such as hyperhomocysteinemia, pro-inflammatory cytokines, and C-reactive protein levels, has been suggested as a cause of the high prevalence of CVD in SLE patients. On the other hand, environmental factors, such as nutritional status, could influence the disease’s prognosis; several nutrients have immunomodulators, antioxidants, and anti-cardiometabolic risk properties which could reduce SLE severity and organ damage by decreasing the development of traditional and non-traditional CVD risk factors. Therefore, this critical literature review discusses the therapeutic potential of nutritional approaches that could modulate the development of the main comorbidities related to CVD risk in SLE patients. Full article
(This article belongs to the Special Issue Nutrition and Cardiovascular Outcomes)
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<p>Methodological diagram of the literature search and selection process.</p>
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<p>Traditional and non-traditional cardiovascular disease risk factors in SLE patients. SLE patients have a high prevalence of traditional risk factors for CVD, which are also common in the general population. However, SLE patients have CVD risk factors related to SLE pathophysiology and SLE pharmacotherapy, known as non-traditional CVD risk factors. The interaction between traditional and non-traditional CVD risk factors results in high morbidity and mortality in SLE patients due to cardiovascular alterations. SLE: systemic lupus erythematosus; TC: total cholesterol; TG: triglycerides; LDL-C: low-density lipoprotein cholesterol; HDL-C: high-density lipoprotein cholesterol; BMI: body mass index; TNF-α: tumor necrosis factor alpha; IL-17: interleukin 17; IFN-1: Type 1 interferons; IL-6: interleukin 6; CRP: C-reactive protein; <b>ox-LDL:</b> oxidized low-density lipoprotein; anti-β-2GP1: anti-beta-2 glycoprotein 1 antibodies.</p>
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<p>Nutrients that modulate the cardiovascular disease risk in SLE patients. (<b>a</b>) PUFAs: can reduce triglycerides through activation of PPARs to increase expression of genes involved in fatty acid oxidation. (<b>b</b>) Antioxidants vitamins C and E: can decrease lipoperoxidation and reduce superoxide and hydrogen peroxide generation linked to CVD. (<b>c</b>) Vitamin A: decreases expression of the <span class="html-italic">IL17A</span> gene, which could reduce the inflammatory process and slow atherosclerosis progression. (<b>d</b>) Selenium: reduces ADMA concentration, which is considered an independent cardiovascular risk factor due to its capacity to inhibit NO production. (<b>e</b>) Coenzyme Q10: can improve the lipid profile and reduce insulin resistance through modulation of insulin and adiponectin receptors. (<b>f</b>) Probiotics: can deconjugate bile acids which coprecipitate with total cholesterol, to compensate for the loss of bile acids; the liver then converts cholesterol into new bile acids, which can reduce serum total cholesterol levels. (<b>g</b>) B vitamins (B12 and B9): act as cofactors in Hcy metabolism and promote its conversion to methionine, thus decreasing Hcy serum levels. (<b>h</b>) Dietary fiber: its fermentation by gut bacteria provides short-chain fatty acids, such as propionic acid; its absorption decreases cholesterol synthesis in the liver and increases water and sodium absorption into the colonic mucosal cells. SLE: systemic lupus erythematosus; PUFAs: polyunsaturated fatty acids; PPARs: peroxisome proliferator-activated receptors; CVD: cardiovascular disease; ADMA: asymmetric dimethylarginine NO: nitric oxide; Hcy: homocysteine.</p>
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17 pages, 1950 KiB  
Article
Evaluation of Anti-Oxinflammatory and ACE-Inhibitory Properties of Protein Hydrolysates Obtained from Edible Non-Mulberry Silkworm Pupae (Antheraea assama and Philosomia ricinii)
by Preeti Sarkar, Alessandra Pecorelli, Brittany Woodby, Erika Pambianchi, Francesca Ferrara, Raj Kumar Duary and Giuseppe Valacchi
Nutrients 2023, 15(4), 1035; https://doi.org/10.3390/nu15041035 - 19 Feb 2023
Cited by 11 | Viewed by 2673
Abstract
Food-derived bioactive peptides (BAPs) obtained from edible insect-protein hold multiple activities promising the potential to target complex pathological mechanisms responsible for chronic health conditions such as hypertension development. In this study, enzymatic protein hydrolysates from non-mulberry edible silkworm Antheraea assama (Muga) and Philosomia [...] Read more.
Food-derived bioactive peptides (BAPs) obtained from edible insect-protein hold multiple activities promising the potential to target complex pathological mechanisms responsible for chronic health conditions such as hypertension development. In this study, enzymatic protein hydrolysates from non-mulberry edible silkworm Antheraea assama (Muga) and Philosomia ricini (Eri) pupae, specifically Alcalase (A. assama) and Papain (P. ricini) hydrolysates obtained after 60 and 240 min, exhibited the highest ACE-inhibitory and antioxidant properties. The hydrolysates’ fractions (<3, 3–10 and >10 kDa), specifically Alc_M60min_F3 (≤3 kDa) and Pap_E240min_F3 (≤3 kDa), showed the highest antioxidant and ACE-inhibitory activities, respectively. Further RP-HPLC purified sub-fractions F4 and F6 showed the highest ACE inhibition as well as potent anti-oxinflammatory activities in lipopolysaccharide (LPS)-treated endothelial cells. Indeed, F4 and F6 ACE-inhibitory peptide fractions were effective in preventing p65 nuclear translocation after 3 h of LPS stimulation along with the inhibition of p38 MAPK phosphorylation in HUVEC cells. In addition, pretreatment with F4 and F6 ACE-inhibitory peptide fractions significantly prevented the LPS-induced upregulation of COX-2 expression and IL-1β secretion, while the expression of NRF2 (nuclear factor erythroid 2-related factor 2)-regulated enzymes such as HO-1 and NQO1 was induced by both peptide fractions. The derived peptides from edible pupae protein hydrolysates have potentialities to be explored as nutritional approaches against hypertension and related cardiovascular diseases. Full article
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Figure 1
<p>Effect of six proteases (Alcalase, Flavourzyme, Thermolysin, Papain, Pepsin and Trypsin) on the degree of hydrolysis: (<b>A</b>) Muga pupae whole protein concentrate (MPPC) and (<b>B</b>) Eri pupae whole protein concentrate (EPPC).</p>
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<p>Influence of six proteases on the ACE-inhibition activity of hydrolysates obtained from (<b>A</b>) Muga pupae protein extract (MPPC) and (<b>B</b>) Eri pupae protein extract (EPPC). The values are expressed as mean ± SD of triplicate tests. Statistical difference (<span class="html-italic">p</span> &lt; 0.05) within the same enzyme at different time points is denoted by letters a–e, and difference within six various enzymes at each time point is denoted with letters a′–e′.</p>
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<p>Elution profiles of Alc_M60min_F3 and Pap_E240min_F3 fractions by RP-HPLC and the ACE-inhibitory activity of each sub-fraction; (<b>A</b>) Alc_M60min_F3, (<b>B</b>) Pap_E240min_F3. Red numbers in the chromatograms indicate the peptides’ sub-fractions F1-F5 of Alc_M60min_F3 and F1-F9 of Pap_E240min_F3. Statistical difference (<span class="html-italic">p</span> &lt; 0.05) is denoted by letters a–c. Shared letters indicate no significant difference.</p>
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<p>Cell viability of HUVECs treated with F4 and F6 at different concentrations (0, 10, 20, 50, 100, 300, 500 and 1000 µg mL<sup>−1</sup>) for 24 h. Data are the results of the averages of at least three different experiments.</p>
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<p>Effects of F4 and F6 on LPS-induced inflammatory processes in endothelial cells. (<b>A</b>) NF-κB p65 nuclear translocation was evaluated by confocal microscopy after 3 h of LPS stimulation. Images were captured and p65 nuclear translocation quantified using ImageJ software. (<b>B</b>) Phosphorylation of p38 MAPK was measured by immunoblotting. Protein bands of phospho-p38 were normalized to the total form and the values in the groups were relative values to the control group. Protein bands were quantified by densitometry and normalized to their respective loading controls. (<b>C</b>,<b>D</b>) COX-2 protein expression and IL-1β secretion at 12 h of LPS stimulation were assessed by ELISA assay. The protein level in the control group was set as 1 and the values in the other groups were relative values to the control group. Statistical difference (<span class="html-italic">p</span> &lt; 0.05) is denoted by letters a–c. Shared letters indicate no significant difference.</p>
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<p>(<b>A</b>,<b>B</b>) Effects of F4 and F6 on LPS-induced antioxidant responses in endothelial cells. Eighteen hours after LPS addition, HO-1 and NQO-1 expression was measured by immunoblotting. The contents in the control groups were set as 1, and the values in the other groups were relative values to the control group. Protein bands were quantified by densitometry and normalized to their respective loading controls. The values are expressed as mean ± SD. Data are the results of the averages of at least three different experiments. Statistical difference (<span class="html-italic">p</span> &lt; 0.05) is denoted by letters a–c. Shared letters indicate no significant difference.</p>
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10 pages, 267 KiB  
Article
Association between Hyperactivity and SSB Consumption in Schoolchildren: A Cross-Sectional Study in China
by Yushan Zhang, Zhaohuan Gui, Nan Jiang, Xueya Pu, Meiling Liu, Yingqi Pu, Shan Huang, Shaoyi Huang and Yajun Chen
Nutrients 2023, 15(4), 1034; https://doi.org/10.3390/nu15041034 - 19 Feb 2023
Cited by 2 | Viewed by 3318
Abstract
Sugar-sweetened beverages (SSBs) consumption has risen significantly, which may lead to various health problems. Studies about the association between SSBs and attention-deficit/hyperactivity disorder (ADHD) in children are rare and inconsistent. We have used the two-stage cluster sampling method to select 6541 students aged [...] Read more.
Sugar-sweetened beverages (SSBs) consumption has risen significantly, which may lead to various health problems. Studies about the association between SSBs and attention-deficit/hyperactivity disorder (ADHD) in children are rare and inconsistent. We have used the two-stage cluster sampling method to select 6541 students aged 6–12. We further investigated their basic information and SSB intake. Teachers’ questionnaires and parents’ questionnaires were used to evaluating the hyperactive behaviors in children. We examined the associations between SSB consumption and hyperactivity index (HI) by adopting the censored least absolute deviation (CLAD) estimator. Then, we further evaluated the impacts of sex and age on the association between SSB intake and hyperactivity. Children who weekly drank SSB two or more times were associated with 0.05 (0.04, 0.07) and 0.04 (0.02, 0.06) higher scores of ln (HI+1) reported by teachers and parents, respectively, compared to non-consumers children (p for trend < 0.05). A stronger association between SSB intake and hyperactivity occurred in girls and old children. (p for interaction < 0.05). SSB intake has a positive correlation with the risk of hyperactivity in children, and the frequency of SSB consumption and hyperactivity have a dose–response relationship. Full article
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