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Search Results (428)

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Keywords = intermittent fasting

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16 pages, 720 KiB  
Article
Effect of Time-Restricted Eating on Circulating Levels of IGF1 and Its Binding Proteins in Obesity: An Exploratory Analysis of a Randomized Controlled Trial
by Rand Talal Akasheh, Aparna Ankireddy, Kelsey Gabel, Mark Ezpeleta, Shuhao Lin, Chandra Mohan Tamatam, Sekhar P. Reddy, Bonnie Spring, Ting-Yuan David Cheng, Luigi Fontana, Seema Ahsan Khan, Krista A. Varady, Sofia Cienfuegos and Faiza Kalam
Nutrients 2024, 16(20), 3476; https://doi.org/10.3390/nu16203476 - 14 Oct 2024
Viewed by 424
Abstract
Obesity is associated with alterations in circulating IGF1, IGF1-binding proteins (IGFBPs), insulin, inflammatory markers, and hormones implicated in cardiovascular disease, diabetes, cancer, and aging. However, the effects of 4 and 6 h time-restricted eating (TRE) on circulating IGF1 and IGFBPs is uncertain. Objective: [...] Read more.
Obesity is associated with alterations in circulating IGF1, IGF1-binding proteins (IGFBPs), insulin, inflammatory markers, and hormones implicated in cardiovascular disease, diabetes, cancer, and aging. However, the effects of 4 and 6 h time-restricted eating (TRE) on circulating IGF1 and IGFBPs is uncertain. Objective: This study aimed to investigate the effects of TRE on plasma IGF1, IGFBP1, IGFBP2, and IGFBP3, and whether these effects were mediated by weight loss or body composition changes. Insulin sensitivity, glucose control, adipokines, and inflammatory markers were also examined. Design: An exploratory analysis of an 8-week randomized controlled trial implementing a daily TRE intervention was carried out. Participants/Setting: This study was conducted at the University of Illinois at Chicago in 2019. Participants with obesity were randomized to 4 or 6 h TRE (n = 35) or a control (n = 14) group. Plasma biomarkers were measured by ELISA at baseline and week 8. In a sub-analysis, participants were stratified into higher- (>3.5%) and lower- (≤3.5%) weight-loss groups. Intervention: Participants fasted daily from 7 p.m. to 3 p.m. in the 4 h TRE group (20 h) and from 7 p.m. to 1 p.m. in the 6 h TRE group (18 h), followed by ad libitum eating for the remainder of the day. Controls received no dietary recommendations. Main outcome measures: IGF1, IGFBPs, hsCRP, and adipokines were the main outcome measures of this analysis. Statistical Analysis: Repeated measures ANOVA and mediation analysis were conducted. Results: Body weight significantly decreased with TRE (−3.6 ± 0.3%), contrasting with controls (+0.2 ± 0.5%, p < 0.001). Significant effects of TRE over time were observed on plasma IGFBP2, insulin, HOMA-IR, and 8-isoprostane levels, without affecting other biomarkers. In the sub-analysis, IGFBP2 increased while leptin and 8-isoprostane decreased significantly only in the “higher weight loss” subgroup. Changes in insulin and HOMA-IR were related to TRE adherence. Conclusions: Eight-week daily 4 to 6 h TRE did not affect IGF1, IGFBP1, or IGFBP3 levels but improved insulin, HOMA-IR, and 8-isoprostane. IGFBP2 increased and leptin decreased when weight loss exceeded 3.5% of baseline. Full article
(This article belongs to the Special Issue Intermittent Fasting: A Heart-Healthy Dietary Strategy?)
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Figure 1

Figure 1
<p>Percentage of weight loss relative to baseline, stratified according to final weight loss percentage (lower vs. higher) over 8 weeks of time-restricted eating intervention. Data are expressed as mean ± SEM for percentage of weight loss (WL%) relative to baseline body weight. Participants were stratified into lower WL% (≤3.5%, n = 29) and higher WL% (&gt;3.5%, n = 20). * <span class="html-italic">p</span> &lt; 0.05 and *** <span class="html-italic">p</span> &lt; 0.001 for mean weight loss percentage in a specific week vs. group-matched baseline.</p>
Full article ">Figure 2
<p>Weight loss as a mediator of the effects of TRE on IGFBP2, 8-isoprostane, insulin, and HOMA-IR. Mediation models presenting (<b>A</b>) weight loss as a mediator of the increase in serum IGFBP2 and the decrease in serum 8-isoprostane levels induced by TRE; (<b>B</b>) weight loss as a mediator of the decrease in serum insulin and HOMA-IR induced by TRE, and the reversed model where the reduction in serum insulin or HOMA-IR mediate the effect of TRE on weight loss; and (<b>C</b>) fat mass loss as mediator of the decrease in serum leptin and the increase in high-molecular-weight adiponectin induced by TRE. The indirect effects of all these models were not significant, suggesting no mediation. IGFBP2: insulin-like growth factor 2; HOMA-IR: homeostatic model assessment of insulin resistance.</p>
Full article ">
18 pages, 2811 KiB  
Article
Metabolic Rate of Goldfish (Carassius auratus) in the Face of Common Aquaculture Challenges
by Lisbeth Herrera-Castillo, Germán Vallejo-Palma, Nuria Saiz, Abel Sánchez-Jiménez, Esther Isorna, Ignacio Ruiz-Jarabo and Nuria de Pedro
Biology 2024, 13(10), 804; https://doi.org/10.3390/biology13100804 - 9 Oct 2024
Viewed by 456
Abstract
This study examined the metabolic rate (MO2, oxygen consumption) of goldfish (Carassius auratus) under normal management conditions in aquaculture. Using an intermittent respirometry system, we assessed daily variations and the effects of feeding, handling, temperature increase, and anesthetics. MO [...] Read more.
This study examined the metabolic rate (MO2, oxygen consumption) of goldfish (Carassius auratus) under normal management conditions in aquaculture. Using an intermittent respirometry system, we assessed daily variations and the effects of feeding, handling, temperature increase, and anesthetics. MO2 exhibited a daily rhythm, with higher values during day. Feeding to satiety produced a 35% increase in MO2 compared to fasted animals, with a maximum peak after 3 h and returning to baseline after 7 h. Handling stress (5 min) produced a 140% MO2 peak (from 180 to 252 mg O2 kg−1 h−1), returning to the routine MO2 after 2.5 h. An increase in water temperature (+0.1 °C min−1) up to 30 °C caused MO2 to peak at 200% after 2.5 h from the start of the temperature increase. The use of common anesthetics in aquaculture (MS-222, 2-phenoxyethanol and clove oil in deep anesthesia concentration) affects MO2 during the first few minutes after anesthetic recovery, but also during the following 4 h. It can be concluded that the metabolic rate is a good indicator of the goldfish’s response to aquaculture practices involving energy expenditure and stress. Thus, intermittent respirometry is a valuable non-invasive tool for understanding and improving fish welfare in aquaculture. Full article
(This article belongs to the Section Zoology)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Locomotor activity of goldfish for 9 days. (<b>a</b>) The actogram is represented as double-plotted (48 h time scale) for better visualization. (<b>b</b>) Average waveform: mean (bold black line), standard deviation (gray lines), and periodic sinusoidal function wave. The white areas correspond to the light phase (08:00–20:00 h) and the shaded areas correspond to the dark phase (20:00–08:00 h). The red vertical lines indicate the feeding time (10:00 h). (<b>c</b>) The periodogram represents the % variance versus time. The horizontal line reflects the significance threshold (<span class="html-italic">p</span> &lt; 0.05) and the number above the observed peak indicates the value of the period in minutes.</p>
Full article ">Figure 2
<p>Daily oxygen consumption of goldfish. (<b>a</b>) The 24 h profile of the metabolic rate of 8 goldfish during the first day (black dots) and the second day (white dots). The white areas correspond to the light phase (08:00–20:00 h), while the shaded areas correspond to the dark phase (20:00–08:00 h). (<b>b</b>) Oxygen consumption during photophase and scotophase on days 1 and 2. Data are represented as mean + S.E.M. (<span class="html-italic">n</span> = 8). Two-way ANOVA, Holm–Sidak test: ** <span class="html-italic">p</span> &lt; 0.001 for photophase versus scotophase on the same day; # <span class="html-italic">p</span> &lt; 0.05; ## <span class="html-italic">p</span> &lt; 0.001 for the same phase of the day comparing days 1 and 2. (<b>c</b>) Metabolic rate (mean ± S.E.M.) of <span class="html-italic">C. auratus</span> on the second day (data are grouped by hours). As the Cosinor analysis yielded significant results (Zero amplitude test: *** <span class="html-italic">p</span> &lt; 0.001), the sinusoidal periodic function is represented as a red curve.</p>
Full article ">Figure 3
<p>Effect of feeding on the metabolic rate of <span class="html-italic">C. auratus</span>. The % variation in MO<sub>2</sub> of fed fish with respect to the fasting group is represented by the mean ± S.E.M (<span class="html-italic">n</span> = 8 per group). Data are grouped by 10 min intervals. The points at which there are significant differences are indicated with a bracket and * (Paired Student <span class="html-italic">t</span>-test, <span class="html-italic">p</span> &lt; 0.05), and the red arrow indicates the time of maximum difference.</p>
Full article ">Figure 4
<p>Effect of acute stress on the metabolic rate of <span class="html-italic">C. auratus</span>. The blue points represent the raw data of 8 fish, the green points correspond to the mean of all values at each time, and the red line represents the regression line. Shaded regions correspond to 95% confidence intervals. The first arrow indicates the time of the maximum MO<sub>2</sub> and the second arrow the time when stabilization is reached.</p>
Full article ">Figure 5
<p>Effect of temperature increase on metabolic rate in <span class="html-italic">C. auratus</span>. (<b>a</b>) The blue points represent the raw data of 8 fish at each time, the green points correspond to the mean of these fish at each time, and the red line represents the fit of the data to a lineal regression. The arrow indicates the time at which the linearity break occurs (154 min). (<b>b</b>) The relationship between temperature and oxygen consumption during the first phase (154 min), with the raw data (blue) of 8 fish at each temperature represented with their fitted values (red). Shaded regions correspond to 95% confidence intervals.</p>
Full article ">Figure 6
<p>Effect of different anesthetics on the metabolic rate of <span class="html-italic">C. auratus</span>. The black line represents the fit of the data to a line regression. Shaded regions correspond to 95% confidence intervals. The first arrow indicates the time of the maximum MO<sub>2</sub> and the second arrow the time when stabilization is reached.</p>
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22 pages, 4935 KiB  
Systematic Review
The Effects of Time-Restricted Eating on Fat Loss in Adults with Overweight and Obese Depend upon the Eating Window and Intervention Strategies: A Systematic Review and Meta-Analysis
by Yixun Xie, Kaixiang Zhou, Zhangyuting Shang, Dapeng Bao and Junhong Zhou
Nutrients 2024, 16(19), 3390; https://doi.org/10.3390/nu16193390 - 5 Oct 2024
Viewed by 2012
Abstract
Time-restricted eating (TRE) is a circadian rhythm-based intermittent fasting intervention that has been used to treat obesity. However, the efficacy and safety of TRE for fat loss have not been comprehensively examined and the influences of TRE characteristics on such effects are unknown. [...] Read more.
Time-restricted eating (TRE) is a circadian rhythm-based intermittent fasting intervention that has been used to treat obesity. However, the efficacy and safety of TRE for fat loss have not been comprehensively examined and the influences of TRE characteristics on such effects are unknown. This systematic review and meta-analysis comprehensively characterized the efficacy and safety of TRE for fat loss in adults with overweight and obese, and it explored the influence of TRE characteristics on this effect. Methods: A search strategy based on the PICOS principle was used to find relevant publications in seven databases. The outcomes were body composition, anthropometric indicators, and blood lipid metrics. Twenty publications (20 studies) with 1288 participants, covering the period from 2020 to 2024, were included. Results: Compared to the control group, TRE safely and significantly reduced body fat percentage, fat mass, lean mass, body mass, BMI, and waist circumference (MDpooled = −2.14 cm, 95% CI = −2.88~−1.40, p < 0.001), and increased low-density lipoprotein (LDL) (MDpooled = 2.70, 95% CI = 0.17~5.22, p = 0.037), but it did not alter the total cholesterol, high-density lipoprotein, and triglycerides (MDpooled = −1.09~1.20 mg/dL, 95% CI −4.31~5.47, p > 0.05). Subgroup analyses showed that TRE only or TRE-caloric restriction with an eating window of 6 to 8 h may be appropriate for losing body fat and overall weight. Conclusions: This work provides moderate to high evidence that TRE is a promising dietary strategy for fat loss. Although it may potentially reduce lean mass and increase LDL, these effects do not pose significant safety concerns. This trial was registered with PROSPERO as CRD42023406329. Full article
(This article belongs to the Section Nutrition and Obesity)
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Figure 1

Figure 1
<p>Flow chart of the publication screening.</p>
Full article ">Figure 2
<p>Risk of bias assessment in the RCTs in the included studies. A total of 20 publications [<a href="#B10-nutrients-16-03390" class="html-bibr">10</a>,<a href="#B11-nutrients-16-03390" class="html-bibr">11</a>,<a href="#B12-nutrients-16-03390" class="html-bibr">12</a>,<a href="#B13-nutrients-16-03390" class="html-bibr">13</a>,<a href="#B21-nutrients-16-03390" class="html-bibr">21</a>,<a href="#B28-nutrients-16-03390" class="html-bibr">28</a>,<a href="#B29-nutrients-16-03390" class="html-bibr">29</a>,<a href="#B30-nutrients-16-03390" class="html-bibr">30</a>,<a href="#B31-nutrients-16-03390" class="html-bibr">31</a>,<a href="#B32-nutrients-16-03390" class="html-bibr">32</a>,<a href="#B33-nutrients-16-03390" class="html-bibr">33</a>,<a href="#B34-nutrients-16-03390" class="html-bibr">34</a>,<a href="#B35-nutrients-16-03390" class="html-bibr">35</a>,<a href="#B36-nutrients-16-03390" class="html-bibr">36</a>,<a href="#B37-nutrients-16-03390" class="html-bibr">37</a>,<a href="#B38-nutrients-16-03390" class="html-bibr">38</a>,<a href="#B39-nutrients-16-03390" class="html-bibr">39</a>,<a href="#B40-nutrients-16-03390" class="html-bibr">40</a>,<a href="#B41-nutrients-16-03390" class="html-bibr">41</a>,<a href="#B42-nutrients-16-03390" class="html-bibr">42</a>] were incorporated into the review.</p>
Full article ">Figure 3
<p>Meta−analysis results of (<b>A</b>) body fat percentage [<a href="#B12-nutrients-16-03390" class="html-bibr">12</a>,<a href="#B13-nutrients-16-03390" class="html-bibr">13</a>,<a href="#B21-nutrients-16-03390" class="html-bibr">21</a>,<a href="#B28-nutrients-16-03390" class="html-bibr">28</a>,<a href="#B29-nutrients-16-03390" class="html-bibr">29</a>,<a href="#B30-nutrients-16-03390" class="html-bibr">30</a>,<a href="#B31-nutrients-16-03390" class="html-bibr">31</a>,<a href="#B33-nutrients-16-03390" class="html-bibr">33</a>,<a href="#B34-nutrients-16-03390" class="html-bibr">34</a>,<a href="#B35-nutrients-16-03390" class="html-bibr">35</a>,<a href="#B36-nutrients-16-03390" class="html-bibr">36</a>,<a href="#B37-nutrients-16-03390" class="html-bibr">37</a>,<a href="#B38-nutrients-16-03390" class="html-bibr">38</a>,<a href="#B39-nutrients-16-03390" class="html-bibr">39</a>,<a href="#B42-nutrients-16-03390" class="html-bibr">42</a>], (<b>B</b>) fat mass [<a href="#B10-nutrients-16-03390" class="html-bibr">10</a>,<a href="#B11-nutrients-16-03390" class="html-bibr">11</a>,<a href="#B12-nutrients-16-03390" class="html-bibr">12</a>,<a href="#B13-nutrients-16-03390" class="html-bibr">13</a>,<a href="#B21-nutrients-16-03390" class="html-bibr">21</a>,<a href="#B28-nutrients-16-03390" class="html-bibr">28</a>,<a href="#B29-nutrients-16-03390" class="html-bibr">29</a>,<a href="#B30-nutrients-16-03390" class="html-bibr">30</a>,<a href="#B31-nutrients-16-03390" class="html-bibr">31</a>,<a href="#B34-nutrients-16-03390" class="html-bibr">34</a>,<a href="#B35-nutrients-16-03390" class="html-bibr">35</a>,<a href="#B36-nutrients-16-03390" class="html-bibr">36</a>,<a href="#B37-nutrients-16-03390" class="html-bibr">37</a>,<a href="#B39-nutrients-16-03390" class="html-bibr">39</a>,<a href="#B40-nutrients-16-03390" class="html-bibr">40</a>,<a href="#B41-nutrients-16-03390" class="html-bibr">41</a>,<a href="#B42-nutrients-16-03390" class="html-bibr">42</a>], and (<b>C</b>) lean mass [<a href="#B10-nutrients-16-03390" class="html-bibr">10</a>,<a href="#B11-nutrients-16-03390" class="html-bibr">11</a>,<a href="#B12-nutrients-16-03390" class="html-bibr">12</a>,<a href="#B13-nutrients-16-03390" class="html-bibr">13</a>,<a href="#B21-nutrients-16-03390" class="html-bibr">21</a>,<a href="#B29-nutrients-16-03390" class="html-bibr">29</a>,<a href="#B30-nutrients-16-03390" class="html-bibr">30</a>,<a href="#B31-nutrients-16-03390" class="html-bibr">31</a>,<a href="#B34-nutrients-16-03390" class="html-bibr">34</a>,<a href="#B35-nutrients-16-03390" class="html-bibr">35</a>,<a href="#B36-nutrients-16-03390" class="html-bibr">36</a>,<a href="#B37-nutrients-16-03390" class="html-bibr">37</a>,<a href="#B40-nutrients-16-03390" class="html-bibr">40</a>,<a href="#B41-nutrients-16-03390" class="html-bibr">41</a>,<a href="#B42-nutrients-16-03390" class="html-bibr">42</a>].</p>
Full article ">Figure 4
<p>Meta−analysis results for (<b>A</b>) body mass [<a href="#B11-nutrients-16-03390" class="html-bibr">11</a>,<a href="#B12-nutrients-16-03390" class="html-bibr">12</a>,<a href="#B13-nutrients-16-03390" class="html-bibr">13</a>,<a href="#B21-nutrients-16-03390" class="html-bibr">21</a>,<a href="#B28-nutrients-16-03390" class="html-bibr">28</a>,<a href="#B29-nutrients-16-03390" class="html-bibr">29</a>,<a href="#B30-nutrients-16-03390" class="html-bibr">30</a>,<a href="#B31-nutrients-16-03390" class="html-bibr">31</a>,<a href="#B33-nutrients-16-03390" class="html-bibr">33</a>,<a href="#B34-nutrients-16-03390" class="html-bibr">34</a>,<a href="#B35-nutrients-16-03390" class="html-bibr">35</a>,<a href="#B36-nutrients-16-03390" class="html-bibr">36</a>,<a href="#B37-nutrients-16-03390" class="html-bibr">37</a>,<a href="#B38-nutrients-16-03390" class="html-bibr">38</a>,<a href="#B39-nutrients-16-03390" class="html-bibr">39</a>,<a href="#B40-nutrients-16-03390" class="html-bibr">40</a>,<a href="#B41-nutrients-16-03390" class="html-bibr">41</a>,<a href="#B42-nutrients-16-03390" class="html-bibr">42</a>], (<b>B</b>) body mass index [<a href="#B12-nutrients-16-03390" class="html-bibr">12</a>,<a href="#B13-nutrients-16-03390" class="html-bibr">13</a>,<a href="#B30-nutrients-16-03390" class="html-bibr">30</a>,<a href="#B31-nutrients-16-03390" class="html-bibr">31</a>,<a href="#B33-nutrients-16-03390" class="html-bibr">33</a>,<a href="#B34-nutrients-16-03390" class="html-bibr">34</a>,<a href="#B35-nutrients-16-03390" class="html-bibr">35</a>,<a href="#B37-nutrients-16-03390" class="html-bibr">37</a>,<a href="#B38-nutrients-16-03390" class="html-bibr">38</a>,<a href="#B39-nutrients-16-03390" class="html-bibr">39</a>,<a href="#B40-nutrients-16-03390" class="html-bibr">40</a>,<a href="#B42-nutrients-16-03390" class="html-bibr">42</a>], and (<b>C</b>) waist circumference [<a href="#B11-nutrients-16-03390" class="html-bibr">11</a>,<a href="#B12-nutrients-16-03390" class="html-bibr">12</a>,<a href="#B13-nutrients-16-03390" class="html-bibr">13</a>,<a href="#B21-nutrients-16-03390" class="html-bibr">21</a>,<a href="#B31-nutrients-16-03390" class="html-bibr">31</a>,<a href="#B33-nutrients-16-03390" class="html-bibr">33</a>,<a href="#B34-nutrients-16-03390" class="html-bibr">34</a>,<a href="#B35-nutrients-16-03390" class="html-bibr">35</a>,<a href="#B38-nutrients-16-03390" class="html-bibr">38</a>,<a href="#B39-nutrients-16-03390" class="html-bibr">39</a>,<a href="#B40-nutrients-16-03390" class="html-bibr">40</a>,<a href="#B42-nutrients-16-03390" class="html-bibr">42</a>].</p>
Full article ">Figure 5
<p>Meta−analysis results for (<b>A</b>) total cholesterol [<a href="#B11-nutrients-16-03390" class="html-bibr">11</a>,<a href="#B12-nutrients-16-03390" class="html-bibr">12</a>,<a href="#B13-nutrients-16-03390" class="html-bibr">13</a>,<a href="#B21-nutrients-16-03390" class="html-bibr">21</a>,<a href="#B28-nutrients-16-03390" class="html-bibr">28</a>,<a href="#B31-nutrients-16-03390" class="html-bibr">31</a>,<a href="#B35-nutrients-16-03390" class="html-bibr">35</a>,<a href="#B37-nutrients-16-03390" class="html-bibr">37</a>,<a href="#B40-nutrients-16-03390" class="html-bibr">40</a>,<a href="#B42-nutrients-16-03390" class="html-bibr">42</a>], (<b>B</b>) high−density lipoprotein cholesterol [<a href="#B10-nutrients-16-03390" class="html-bibr">10</a>,<a href="#B11-nutrients-16-03390" class="html-bibr">11</a>,<a href="#B12-nutrients-16-03390" class="html-bibr">12</a>,<a href="#B13-nutrients-16-03390" class="html-bibr">13</a>,<a href="#B28-nutrients-16-03390" class="html-bibr">28</a>,<a href="#B29-nutrients-16-03390" class="html-bibr">29</a>,<a href="#B31-nutrients-16-03390" class="html-bibr">31</a>,<a href="#B35-nutrients-16-03390" class="html-bibr">35</a>,<a href="#B37-nutrients-16-03390" class="html-bibr">37</a>,<a href="#B40-nutrients-16-03390" class="html-bibr">40</a>,<a href="#B42-nutrients-16-03390" class="html-bibr">42</a>], (<b>C</b>) low−density lipoprotein cholesterol [<a href="#B10-nutrients-16-03390" class="html-bibr">10</a>,<a href="#B11-nutrients-16-03390" class="html-bibr">11</a>,<a href="#B12-nutrients-16-03390" class="html-bibr">12</a>,<a href="#B13-nutrients-16-03390" class="html-bibr">13</a>,<a href="#B28-nutrients-16-03390" class="html-bibr">28</a>,<a href="#B29-nutrients-16-03390" class="html-bibr">29</a>,<a href="#B35-nutrients-16-03390" class="html-bibr">35</a>,<a href="#B37-nutrients-16-03390" class="html-bibr">37</a>,<a href="#B40-nutrients-16-03390" class="html-bibr">40</a>,<a href="#B42-nutrients-16-03390" class="html-bibr">42</a>], and (<b>D</b>) triglycerides [<a href="#B10-nutrients-16-03390" class="html-bibr">10</a>,<a href="#B11-nutrients-16-03390" class="html-bibr">11</a>,<a href="#B12-nutrients-16-03390" class="html-bibr">12</a>,<a href="#B13-nutrients-16-03390" class="html-bibr">13</a>,<a href="#B28-nutrients-16-03390" class="html-bibr">28</a>,<a href="#B29-nutrients-16-03390" class="html-bibr">29</a>,<a href="#B35-nutrients-16-03390" class="html-bibr">35</a>,<a href="#B37-nutrients-16-03390" class="html-bibr">37</a>,<a href="#B40-nutrients-16-03390" class="html-bibr">40</a>,<a href="#B42-nutrients-16-03390" class="html-bibr">42</a>].</p>
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12 pages, 296 KiB  
Review
Fueling the Heart: What Are the Optimal Dietary Strategies in Heart Failure?
by Anahita Ataran, Alexander Pompian, Hamidreza Hajirezaei, Rehman Lodhi and Ali Javaheri
Nutrients 2024, 16(18), 3157; https://doi.org/10.3390/nu16183157 - 18 Sep 2024
Viewed by 892
Abstract
Objectives: Heart failure (HF) is a global health concern with rising incidence and poor prognosis. While the essential role of nutritional and dietary strategies in HF patients is acknowledged in the existing scientific guidelines and clinical practice, there are no comprehensive nutritional recommendations [...] Read more.
Objectives: Heart failure (HF) is a global health concern with rising incidence and poor prognosis. While the essential role of nutritional and dietary strategies in HF patients is acknowledged in the existing scientific guidelines and clinical practice, there are no comprehensive nutritional recommendations for optimal dietary management of HF. Methods: In this review, we discuss results from recent studies on the obesity paradox and the effects of calorie restriction and weight loss, intermittent fasting, the Western diet, the Mediterranean diet, the ketogenic diet, and the DASH diet on HF progression. Results: Many of these strategies remain under clinical and basic investigation for their safety and efficacy, and there is considerable heterogeneity in the observed response, presumably because of heterogeneity in the pathogenesis of different types of HF. In addition, while specific aspects of cardiac metabolism, such as changes in ketone body utilization, might underlie the effects of certain dietary strategies on the heart, there is a critical divide between supplement strategies (i.e., with ketones) and dietary strategies that impact ketogenesis. Conclusion: This review aims to highlight this gap by exploring emerging evidence supporting the importance of personalized dietary strategies in preventing progression and improving outcomes in the context of HF. Full article
14 pages, 1113 KiB  
Article
The 5:2 Diet Affects Markers of Insulin Secretion and Sensitivity in Subjects with and without Type 2 Diabetes—A Non-Randomized Controlled Trial
by Neda Rajamand Ekberg, Anton Hellberg, Michaela Linn Sundqvist, Angelica Lindén Hirschberg, Sergiu-Bogdan Catrina and Kerstin Brismar
Int. J. Mol. Sci. 2024, 25(17), 9731; https://doi.org/10.3390/ijms25179731 - 8 Sep 2024
Viewed by 1148
Abstract
This non-randomized controlled trial aimed to compare the effect of the 5:2 diet on insulin levels as a primary outcome and markers of insulin secretion (connecting peptide (C-peptide) and insulin-like growth factor binding protein-1 (IGFBP-1)) and sensitivity (Homeostatic Model Assessment for Insulin Resistance [...] Read more.
This non-randomized controlled trial aimed to compare the effect of the 5:2 diet on insulin levels as a primary outcome and markers of insulin secretion (connecting peptide (C-peptide) and insulin-like growth factor binding protein-1 (IGFBP-1)) and sensitivity (Homeostatic Model Assessment for Insulin Resistance (HOMA-IR)), as well as body composition as secondary outcomes in overweight/obese individuals with and without type 2 diabetes (T2D). Ninety-seven participants (62% women), 35 with T2D and 62 BMI- and waist-matched controls without T2D, followed the 5:2 diet (two days per week of fasting) for six months with a 12-month follow-up. At six months, there was no loss to follow-up in the T2D group, whereas four controls discontinued this study. Overall, 82% attended the 12-month follow-up. After the intervention, insulin levels decreased in the control group and glucose decreased in the T2D group, while C-peptide, HOMA-IR, waist circumference, BMI, trunk, and total fat% decreased in both groups. Furthermore, low IGFBP-1, indicating hyperinsulinemia, improved in the T2D group. The changes in fasting glucose and waist measurement were significantly more improved in the T2D group than in the controls. Persistent positive effects were observed at the 12-month follow-up. The 5:2 diet for six months was feasible and efficient to reduce markers of insulin secretion and resistance and therefore holds promise as management of overweight/obesity in subjects with and without T2D. Full article
(This article belongs to the Special Issue Molecular Diagnosis and Treatments of Diabetes Mellitus)
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<p>Flowchart of the study with a 6-month intervention and a 12-month follow-up.</p>
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<p>(<b>a</b>) Fasting insulin levels and (<b>b</b>) HOMA-IR values at baseline, 6 month intervention, and 12-month follow-up for participants with type 2 diabetes (T2D group) and controls, respectively. Within-group differences are represented by * = <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.</p>
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20 pages, 2621 KiB  
Systematic Review
Effects of Different Exercises Combined with Different Dietary Interventions on Body Composition: A Systematic Review and Network Meta-Analysis
by Yongchao Xie, Yu Gu, Zhen Li, Bingchen He and Lei Zhang
Nutrients 2024, 16(17), 3007; https://doi.org/10.3390/nu16173007 - 5 Sep 2024
Viewed by 4536
Abstract
Background: Exercise and dietary interventions are essential for maintaining weight and reducing fat accumulation. With the growing popularity of various dietary strategies, evidence suggests that combining exercise with dietary interventions offers greater benefits than either approach alone. Consequently, this combined strategy has become [...] Read more.
Background: Exercise and dietary interventions are essential for maintaining weight and reducing fat accumulation. With the growing popularity of various dietary strategies, evidence suggests that combining exercise with dietary interventions offers greater benefits than either approach alone. Consequently, this combined strategy has become a preferred method for many individuals aiming to maintain health. Calorie restriction, 5/2 intermittent fasting, time-restricted feeding, and the ketogenic diet are among the most popular dietary interventions today. Aerobic exercise, resistance training, and mixed exercise are the most widely practiced forms of physical activity. Exploring the best combinations of these approaches to determine which yields the most effective results is both meaningful and valuable. Despite this trend, a comparative analysis of the effects of different exercise and diet combinations is lacking. This study uses network meta-analysis to evaluate the impact of various combined interventions on body composition and to compare their efficacy. Methods: We systematically reviewed literature from database inception through May 2024, searching PubMed, Web of Science, Embase, and the Cochrane Library. The study was registered in PROSPERO under the title: “Effects of Exercise Combined with Different Dietary Interventions on Body Composition: A Systematic Review and Network Meta-Analysis” (identifier: CRD42024542184). Studies were meticulously selected based on specific inclusion and exclusion criteria (The included studies must be randomized controlled trials involving healthy adults aged 18 to 65 years. Articles were rigorously screened according to the specified inclusion and exclusion criteria.), and their risk of bias was assessed using the Cochrane risk of bias tool. Data were aggregated and analyzed using network meta-analysis, with intervention efficacy ranked by Surface Under the Cumulative Ranking (SUCRA) curves. Results: The network meta-analysis included 78 randomized controlled trials with 5219 participants, comparing the effects of four combined interventions: exercise with calorie restriction (CR+EX), exercise with time-restricted eating (TRF+EX), exercise with 5/2 intermittent fasting (5/2F+EX), and exercise with a ketogenic diet (KD+EX) on body composition. Intervention efficacy ranking was as follows: (1) Weight Reduction: CR+EX > KD+EX > TRF+EX > 5/2F+EX (Relative to CR+EX, the effect sizes of 5/2F+EX, TRF+EX and KD+EX are 2.94 (−3.64, 9.52); 2.37 (−0.40, 5.15); 1.80 (−1.75, 5.34)). (2) BMI: CR+EX > KD+EX > 5/2F+EX > TRF+EX (Relative to CR+EX, the effect sizes of 5/2F+EX, TRF+EX and KD+EX are 1.95 (−0.49, 4.39); 2.20 (1.08, 3.32); 1.23 (−0.26, 2.71)). (3) Body Fat Percentage: CR+EX > 5/2F+EX > TRF+EX > KD+EX (Relative to CR+EX, the effect sizes of 5/2F+EX, TRF+EX and KD+EX are 2.66 (−1.56, 6.89); 2.84 (0.56, 5.13); 3.14 (0.52, 5.75).). (4) Lean Body Mass in Male: CR+EX > TRF+EX > KD+EX (Relative to CR+EX, the effect sizes of TRF+EX and KD+EX are −1.60 (−6.98, 3.78); −2.76 (−7.93, 2.40)). (5) Lean Body Mass in Female: TRF+EX > CR+EX > 5/2F+EX > KD+EX (Relative to TRF+EX, the effect sizes of CR+EX, 5/2F+EX and KD+EX are −0.52 (−2.58, 1.55); −1.83 (−4.71, 1.04); −2.46 (−5.69,0.76).). Conclusion: Calorie restriction combined with exercise emerged as the most effective strategy for reducing weight and fat percentage while maintaining lean body mass. For women, combining exercise with time-restricted eating proved optimal for preserving muscle mass. While combining exercise with a ketogenic diet effectively reduces weight, it is comparatively less effective at decreasing fat percentage and preserving lean body mass. Hence, the ketogenic diet combined with exercise is considered suboptimal. Full article
(This article belongs to the Section Sports Nutrition)
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<p>Flow diagram of study selection.</p>
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<p>Network Meta-Analysis of Weight: Network Plot, League Table, and SUCRA Plot. (<b>A</b>) Network Plot. The size of the nodes is proportional to the sample size of each dietary intervention, and the thickness of the lines corresponds to the number of available studies. (<b>B</b>) Pairwise comparison League Table, where the estimated effect size differences (SMD with 95% CI) represent the difference between the intervention on the top and the intervention on the right. (<b>C</b>) The SUCRA Plot, where the size of the area under the curve indicates the effectiveness of each intervention.</p>
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<p>Network Meta-Analysis of BMI: Network Plot, League Table, and SUCRA Plot. (<b>A</b>) Network Plot. The size of the nodes is proportional to the sample size of each dietary intervention, and the thickness of the lines corresponds to the number of available studies. (<b>B</b>) Pairwise comparison League Table, where the estimated effect size differences (SMD with 95% CI) represent the difference between the intervention on the top and the intervention on the right. (<b>C</b>) The SUCRA Plot, where the size of the area under the curve indicates the effectiveness of each intervention.</p>
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<p>Network Meta-Analysis of Body fat percentage: Network Plot, League Table, and SUCRA Plot. (<b>A</b>) Network Plot. The size of the nodes is proportional to the sample size of each dietary intervention, and the thickness of the lines corresponds to the number of available studies. (<b>B</b>) Pairwise comparison League Table, where the estimated effect size differences (SMD with 95% CI) represent the difference between the intervention on the top and the intervention on the right. (<b>C</b>) The SUCRA Plot, where the size of the area under the curve indicates the effectiveness of each intervention.</p>
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<p>Network Meta-Analysis of male lean body mass: Network Plot, League Table, and SUCRA Plot. (<b>A</b>) Network Plot. The size of the nodes is proportional to the sample size of each dietary intervention, and the thickness of the lines corresponds to the number of available studies. (<b>B</b>) Pairwise comparison League Table, where the estimated effect size differences (SMD with 95% CI) represent the difference between the intervention on the top and the intervention on the right. (<b>C</b>) The SUCRA Plot, where the size of the area under the curve indicates the effectiveness of each intervention.</p>
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<p>Network Meta-Analysis of female lean body mass: Network Plot, League Table, and SUCRA Plot. (<b>A</b>) Network Plot. The size of the nodes is proportional to the sample size of each dietary intervention, and the thickness of the lines corresponds to the number of available studies. (<b>B</b>) Pairwise comparison League Table, where the estimated effect size differences (SMD with 95% CI) represent the difference between the intervention on the top and the intervention on the right. (<b>C</b>) The SUCRA Plot, where the size of the area under the curve indicates the effectiveness of each intervention.</p>
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17 pages, 965 KiB  
Review
Molecular Mechanisms of Healthy Aging: The Role of Caloric Restriction, Intermittent Fasting, Mediterranean Diet, and Ketogenic Diet—A Scoping Review
by Roxana Surugiu, Mihaela Adela Iancu, Ștefănița Bianca Vintilescu, Mioara Desdemona Stepan, Daiana Burdusel, Amelia Valentina Genunche-Dumitrescu, Carmen-Adriana Dogaru and Gheorghe Gindrovel Dumitra
Nutrients 2024, 16(17), 2878; https://doi.org/10.3390/nu16172878 - 28 Aug 2024
Viewed by 4917
Abstract
As the population ages, promoting healthy aging through targeted interventions becomes increasingly crucial. Growing evidence suggests that dietary interventions can significantly impact this process by modulating fundamental molecular pathways. This review focuses on the potential of targeted dietary strategies in promoting healthy aging [...] Read more.
As the population ages, promoting healthy aging through targeted interventions becomes increasingly crucial. Growing evidence suggests that dietary interventions can significantly impact this process by modulating fundamental molecular pathways. This review focuses on the potential of targeted dietary strategies in promoting healthy aging and the mechanisms by which specific nutrients and dietary patterns influence key pathways involved in cellular repair, inflammation, and metabolic regulation. Caloric restriction, intermittent fasting, the Mediterranean diet, as well as the ketogenic diet showed promising effects on promoting healthy aging, possibly by modulating mTORC1 AMPK, an insulin signaling pathway. By understanding the intricate interplay between diet and molecular pathways, we can develop personalized dietary strategies that not only prevent age-related diseases, but also promote overall health and well-being throughout the aging process. Full article
(This article belongs to the Section Geriatric Nutrition)
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<p>Main effects of dietary interventions on healthy aging.</p>
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<p>Main metabolic pathways and effect of caloric restriction, intermittent fasting, ketogenic diet, and Mediterranean diet (created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 19 August 2024)).</p>
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12 pages, 2671 KiB  
Article
Effects of Fasting on THP1 Macrophage Metabolism and Inflammatory Profile
by Julia Rius-Bonet, Salvador Macip, Marta Massip-Salcedo and Daniel Closa
Int. J. Mol. Sci. 2024, 25(16), 9029; https://doi.org/10.3390/ijms25169029 - 20 Aug 2024
Viewed by 564
Abstract
Fasting can affect the body’s inflammatory response, and this has been linked to potential health benefits, including improvements for people with rheumatic diseases. In this work, we evaluated, in vitro, how changes in nutrient availability alter the inflammatory response of macrophages. Macrophage-differentiated THP1 [...] Read more.
Fasting can affect the body’s inflammatory response, and this has been linked to potential health benefits, including improvements for people with rheumatic diseases. In this work, we evaluated, in vitro, how changes in nutrient availability alter the inflammatory response of macrophages. Macrophage-differentiated THP1 cells were cultured, deprived of FCS or subjected to cycles of FCS deprivation and restoration to mimic intermittent fasting. Changes in the macrophage phenotype, the cells’ response to inflammatory stimuli and the level of mitochondrial alteration were assessed. The results indicate that while periods of serum starvation are associated with a decrease in IL1β and TNFα expression, consistent with an anti-inflammatory response, intermittent serum starvation cycles promote a pro-inflammatory phenotype. Rapid changes in reducing capacity and mitochondrial response were also observed. Of note, while some changes, such as the production of oxygen free radicals, were reversed with refeeding, others, such as a decrease in reducing capacity, were maintained and even increased. This study shows that different fasting protocols can have diverging effects and highlights that time-limited nutrient changes can significantly affect macrophage functions in cell cultures. These findings help elucidate some of the mechanisms by which specific fasting dietary interventions could help control inflammatory diseases. Full article
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<p>SD modulates the macrophages’ profiles and response to LPS stimulation. (<b>A</b>) mRNA expression of IL-1β in macrophages cultured for 3 h at different FCS concentrations and the effect of LPS (100 ng/mL) treatment, as measured by qPCR (<span class="html-italic">n</span> = 4). (<b>B</b>) Expression of IL-1β (<span class="html-italic">n</span> = 3), TNFα (<span class="html-italic">n</span> = 4), MRC1 and ARG1 (<span class="html-italic">n</span> = 3) in macrophages under different conditions and ratios: IL-1β/MR and TNFα/ARG1 (<span class="html-italic">n</span> = 3). (<b>C</b>) Gene expression of IL-1β in macrophages stimulated with LPS (100 ng/mL) with different periods of nutrient availability (<span class="html-italic">n</span> = 4). Data are expressed as mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05 vs. control (10% FCS) group, + <span class="html-italic">p</span> &lt; 0.05 vs. SD group. ANOVA with Tukey’s post-test was used to obtain <span class="html-italic">p</span>-values. ISD1C, intermittent SD, 1 cycle; ISD3C, intermittent SD, 3 cycles.</p>
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<p>SD effects on NF-κB activation. Immunofluorescence of p65 subunit of NF-κB in macrophages under the FCS conditions described in <a href="#ijms-25-09029-f001" class="html-fig">Figure 1</a>. In control and SD groups, p65 subunit of NFkB remains in cytoplasmatic localization. Nuclear translocation was mainly observed in ISD groups (<span class="html-italic">n</span> = 3).</p>
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<p>SD affects the metabolic activity of macrophages independently of cell viability. (<b>A</b>) MTS assay (<span class="html-italic">n</span> = 4); (<b>B</b>) total cell number; and (<b>C</b>) live cell number of macrophages undergoing different SD and refeeding time periods (<span class="html-italic">n</span> = 3). (<b>D</b>) Macrophages grown under different SD and refeeding time periods; pictures were taken with a microscope at the end of the treatments. Scale bars represent 200 μm (<span class="html-italic">n</span> = 3). (<b>E</b>) Kinetics of MTS of macrophages undergoing different SD and refeeding cycles; measurements were performed every 5 min for an hour after each change of media. Data are expressed as mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05 vs. control group (<span class="html-italic">n</span> = 3). ANOVA with Tukey’s post-test was used to obtain <span class="html-italic">p</span>-values. SD, serum deprivation; R, refeeding.</p>
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<p>SD and ISD alter cell metabolism caused by regulating mitochondrial dynamics. NADH and NAD<sup>+</sup> concentrations and NAD<sup>+</sup>/NADH ratio (<span class="html-italic">n</span> = 2), phosphorylated AMPK (<span class="html-italic">n</span> = 2), TMRE (<span class="html-italic">n</span> = 3) and ROS (<span class="html-italic">n</span> = 2) under the different SD protocols. Data are expressed as mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05 vs. control group; + <span class="html-italic">p</span> &lt; 0.05 vs. fasting group. ISD1C, intermittent SD, 1 cycle; ISD3C, intermittent SD, 3 cycles; NAD, nicotinamide adenine dinucleotide; AMPK, 5′ adenosine monophosphate-activated protein kinase; TMRE, tetramethylrhodamine, ethyl ester; ROS, reactive oxygen species.</p>
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9 pages, 598 KiB  
Brief Report
Effect of Time-Restricted Eating on Sleep in Type 2 Diabetes
by Vasiliki Pavlou, Shuhao Lin, Sofia Cienfuegos, Mark Ezpeleta, Mary-Claire Runchey, Sarah Corapi, Kelsey Gabel, Faiza Kalam, Shaina J. Alexandria, Alaina P. Vidmar and Krista A. Varady
Nutrients 2024, 16(16), 2742; https://doi.org/10.3390/nu16162742 - 17 Aug 2024
Viewed by 1223
Abstract
The aim of this secondary analysis was to compare the effects of time-restricted eating (TRE) versus calorie restriction (CR) and controls on sleep in adults with type 2 diabetes (T2D). Adults with T2D (n = 75) were randomized to 1 of 3 interventions [...] Read more.
The aim of this secondary analysis was to compare the effects of time-restricted eating (TRE) versus calorie restriction (CR) and controls on sleep in adults with type 2 diabetes (T2D). Adults with T2D (n = 75) were randomized to 1 of 3 interventions for 6 months: 8 h TRE (eating only between 12 and 8 pm daily); CR (25% energy restriction daily); or control. Our results show that TRE has no effect on sleep quality, duration, insomnia severity, or risk of obstructive sleep apnea, relative to CR and controls, in patients with T2D over 6 months. Full article
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<p>Change in body weight, HbA1c, and sleep parameters between TRE, CR, and control groups <sup>a</sup>. Abbreviations: CON: control group, CR: calorie restriction group, HbA1c: glycated hemoglobin, TRE: time-restricted eating group. (<b>A</b>) Change in body weight between groups. (<b>B</b>) Change in HbA1c between groups. (<b>C</b>) Change in sleep quality score between groups. (<b>D</b>) Change in sleep duration between groups. (<b>E</b>) Change in insomnia severity score between groups. (<b>F)</b> Change in risk of obstructive sleep apnea between groups. <sup>a</sup> Means were estimated using an intention-to-treat analysis using a linear mixed model with 95% CIs for each parameter from baseline by group. <sup>b</sup> Indicates statistical significance using Bonferroni-adjusted two-tailed <span class="html-italic">p</span> &lt; 0.017. <sup>c</sup> Indicates statistical significance using <span class="html-italic">p</span> &lt; 0.05.</p>
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19 pages, 726 KiB  
Review
Therapeutic Potential of Various Intermittent Fasting Regimens in Alleviating Type 2 Diabetes Mellitus and Prediabetes: A Narrative Review
by Sthembiso Msane, Andile Khathi and Aubrey Sosibo
Nutrients 2024, 16(16), 2692; https://doi.org/10.3390/nu16162692 - 14 Aug 2024
Cited by 1 | Viewed by 1583
Abstract
Intermittent fasting has drawn significant interest in the clinical research community due to its potential to address metabolic complications such as obesity and type 2 diabetes mellitus. Various intermittent fasting regimens include alternate-day fasting (24 h of fasting followed by 24 h of [...] Read more.
Intermittent fasting has drawn significant interest in the clinical research community due to its potential to address metabolic complications such as obesity and type 2 diabetes mellitus. Various intermittent fasting regimens include alternate-day fasting (24 h of fasting followed by 24 h of eating), time-restricted fasting (fasting for 14 h and eating within a 10 h window), and the 5:2 diet (fasting for two days and eating normally for the other five days). Intermittent fasting is associated with a reduced risk of type 2 diabetes mellitus-related complications and can slow their progression. The increasing global prevalence of type 2 diabetes mellitus highlights the importance of early management. Since prediabetes is a precursor to type 2 diabetes mellitus, understanding its progression is essential. However, the long-term effects of intermittent fasting on prediabetes are not yet well understood. Therefore, this review aims to comprehensively compile existing knowledge on the therapeutic effects of intermittent fasting in managing type 2 diabetes mellitus and prediabetes. Full article
(This article belongs to the Special Issue Intermittent Fasting on Human Health and Disease)
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<p>Illustrates the primary organs and molecules whose modifications contribute to the progression of type 2 diabetes mellitus.</p>
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17 pages, 1016 KiB  
Review
Ketogenic Interventions in Autosomal Dominant Polycystic Kidney Disease: A Comprehensive Review of Current Evidence
by Carla Pezzuoli, Giuseppe Biagini and Riccardo Magistroni
Nutrients 2024, 16(16), 2676; https://doi.org/10.3390/nu16162676 - 13 Aug 2024
Viewed by 2063
Abstract
Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a genetic disorder characterized by the development and enlargement of multiple kidney cysts, leading to progressive kidney function decline. To date, Tolvaptan, the only approved treatment for this condition, is able to slow down the loss [...] Read more.
Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a genetic disorder characterized by the development and enlargement of multiple kidney cysts, leading to progressive kidney function decline. To date, Tolvaptan, the only approved treatment for this condition, is able to slow down the loss of annual kidney function without stopping the progression of the disease. Furthermore, this therapy is approved only for patients with rapid disease progression and its compliance is problematic because of the drug’s impact on quality of life. The recent literature suggests that cystic cells are subject to several metabolic dysregulations, particularly in the glucose pathway, and mitochondrial abnormalities, leading to decreased oxidative phosphorylation and impaired fatty acid oxidation. This finding paved the way for new lines of research targeting potential therapeutic interventions for ADPKD. In particular, this review highlights the latest studies on the use of ketosis, through ketogenic dietary interventions (daily calorie restriction, intermittent fasting, time-restricted feeding, ketogenic diets, and exogenous ketosis), as a potential strategy for patients with ADPKD, and the possible involvement of microbiota in the ketogenic interventions’ effect. Full article
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<p>Metabolic pathways in normal and highly proliferative cells under different conditions. The image illustrates the different metabolic pathways of normal differentiated cells and highly proliferative cells under three conditions: oxidative phosphorylation—OXPHOS (in the presence of oxygen), anaerobic glycolysis (in the absence of oxygen), and ketosis. In normal cells in the presence of oxygen, glucose is metabolized through glycolysis, producing pyruvate, which enters the mitochondria to be converted into acetyl-CoA, initiating the tricarboxylic acid (TCA) cycle and ATP production via oxidative phosphorylation, yielding around 30–32 molecules of ATP per molecule of glucose. In the absence of oxygen, pyruvate is converted into lactate, yielding two molecules of ATP per molecule of glucose. During ketosis, the scarcity of glucose and the presence of ketone bodies lead to a suppression of glycolysis, with acetyl-CoA derived from ketone bodies entering the TCA cycle to produce around 20 ATP molecules. In contrast, in highly proliferative cells, even in the presence of oxygen, pyruvate is preferentially converted into lactate (aerobic glycolysis or Warburg Effect), which yields much less energy (approximately four molecules of ATP per molecule of glucose) compared to OXPHOS. Under ketosis conditions, these cells show suppression of both glycolysis and OXPHOS, highlighting the distinctive metabolic phenotype of highly proliferative cells compared to normal cells. OXPHOS: oxidative phosphorylation; ATP: adenosine triphosphate; acetyl-CoA: acetyl coenzyme A; and TCA: tricarboxylic acid cycle.</p>
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16 pages, 1419 KiB  
Article
Twenty-Four Hour Glucose Profiles and Glycemic Variability during Intermittent Religious Dry Fasting and Time-Restricted Eating in Subjects without Diabetes: A Preliminary Study
by Beeke Peters, Christina Laetitia Pappe, Daniela A. Koppold, Katharina Schipp, Bert Arnrich, Andreas Michalsen, Henrik Dommisch, Nico Steckhan and Olga Pivovarova-Ramich
Nutrients 2024, 16(16), 2663; https://doi.org/10.3390/nu16162663 - 12 Aug 2024
Viewed by 1287
Abstract
Intermittent religious fasting increases the risk of hypo- and hyperglycemia in individuals with diabetes, but its impact on those without diabetes has been poorly investigated. The aim of this preliminary study was to examine the effects of religious Bahá’í fasting (BF) on glycemic [...] Read more.
Intermittent religious fasting increases the risk of hypo- and hyperglycemia in individuals with diabetes, but its impact on those without diabetes has been poorly investigated. The aim of this preliminary study was to examine the effects of religious Bahá’í fasting (BF) on glycemic control and variability and compare these effects with time-restricted eating (TRE). In a three-arm randomized controlled trial, 16 subjects without diabetes were assigned to a BF, TRE, or control group. Continuous glucose monitoring and food intake documentation were conducted before and during the 19 days of the intervention, and the 24 h mean glucose and glycemic variability indices were assessed. The BF and TRE groups, but not the control group, markedly reduced the daily eating window while maintaining macronutrient composition. Only the BF group decreased caloric intake (−677.8 ± 357.6 kcal, p = 0.013), body weight (−1.92 ± 0.95 kg, p = 0.011), and BMI (−0.65 ± 0.28 kg, p = 0.006). Higher maximum glucose values were observed during BF in the within-group (+1.41 ± 1.04, p = 0.039) and between-group comparisons (BF vs. control: p = 0.010; TRE vs. BF: p = 0.022). However, there were no alterations of the 24 h mean glucose, intra- and inter-day glycemic variability indices in any group. The proportions of time above and below the range (70–180 mg/dL) remained unchanged. BF and TRE do not exhibit negative effects on glycemic control and variability in subjects without diabetes. Full article
(This article belongs to the Special Issue Dietary Strategies in Metabolic Disorders)
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<p>Study design. Intervention start indicates the beginning of the intermittent fasting in the BF and TRE groups, whereas the control group was instructed not to alter its habitual food and eating timing.</p>
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<p>Twenty-four hour glucose profiles and eating windows in the control group (<b>A</b>), BF group (<b>B</b>), and TRE group (<b>C</b>) before and during the intervention. For the glucose profiles (above), the <span class="html-italic">p</span>-values show the comparison of diurnal glucose profiles between the baseline and intervention phases, calculated by the RM ANOVA. Eating windows (below) are presented for the baseline (bas) and intervention (int) phases. The data are shown as the mean ± SD.</p>
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<p>Timely compliance, energy intake, and macronutrient composition in the study groups. (<b>A</b>) Daily eating duration; (<b>B</b>) reduction in the eating window; (<b>C</b>) energy intake; and the energy percent of the macronutrient composition in the control (<b>D</b>), BF (<b>E</b>), and TRE (<b>F</b>) groups. The non-shaded bars depict the values at the baseline; the shaded bars show the values during the intervention. The data are shown as the mean ± SD. * <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.</p>
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<p>The changes in anthropometric measures in the study groups: (<b>A</b>) body weight; (<b>B</b>) BMI; and (<b>C</b>) waist circumference. The data are shown as the mean ± SD. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 in the within-group comparisons of the parameters (after the intervention vs. before the intervention), assessed by the paired <span class="html-italic">t</span>-test or Wilcoxon test.</p>
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16 pages, 1741 KiB  
Review
Chrononutrition and Cardiometabolic Health: An Overview of Epidemiological Evidence and Key Future Research Directions
by Oluwatimilehin E. Raji, Esther B. Kyeremah, Dorothy D. Sears, Marie-Pierre St-Onge and Nour Makarem
Nutrients 2024, 16(14), 2332; https://doi.org/10.3390/nu16142332 - 19 Jul 2024
Viewed by 2742
Abstract
Chrononutrition is a rapidly evolving field of nutritional epidemiology that addresses the complex relationship between temporal eating patterns, circadian rhythms, and metabolic health, but most prior research has focused on the cardiometabolic consequences of time-restricted feeding and intermittent fasting. The purpose of this [...] Read more.
Chrononutrition is a rapidly evolving field of nutritional epidemiology that addresses the complex relationship between temporal eating patterns, circadian rhythms, and metabolic health, but most prior research has focused on the cardiometabolic consequences of time-restricted feeding and intermittent fasting. The purpose of this topical review is to summarize epidemiological evidence from observational and intervention studies regarding the role of chrononutrition metrics related to eating timing and regularity in cardiometabolic health preservation and cardiovascular disease prevention. Observational studies are limited due to the lack of time-stamped diet data in most population-based studies. Findings from cohort studies generally indicate that breakfast skipping or the later timing of the first eating occasion, a later lunch and dinner, and a greater proportion of caloric intake consumed in the evening are associated with adverse cardiometabolic outcomes, including higher risk for coronary heart disease, hypertension, type 2 diabetes, obesity, dyslipidemia, and systemic inflammation. Randomized controlled trials are also limited, as most in the field of chrononutrition focus on the cardiometabolic consequences of time-restricted feeding. Overall, interventions that shift eating timing patterns to earlier in the day and that restrict evening caloric intake tend to have protective effects on cardiometabolic health, but small sample sizes and short follow-up are notable limitations. Innovation in dietary assessment approaches, to develop low-cost validated tools with acceptable participant burden that reliably capture chrononutrition metrics, is needed for advancing observational evidence. Culturally responsive pragmatic intervention studies with sufficiently large and representative samples are needed to understand the impact of fixed and earlier eating timing schedules on cardiometabolic health. Additional research is warranted to understand the modifiable determinants of temporal eating patterns, to investigate the role of chrononutrition in the context of other dimensions of diet (quantity, quality, and food and nutrition security) in achieving cardiometabolic health equity, and to elucidate underlying physiological mechanisms. Full article
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<p>Determinants of eating timing and regularity.</p>
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<p>Mechanisms linking temporal eating patterns to cardiometabolic disease. Created with BioRender.com (accessed on 19 December 2023).</p>
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<p>Summary of research priorities on eating timing and regularity and cardiometabolic health.</p>
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21 pages, 1817 KiB  
Review
The Effects of Different Dietary Patterns on Bone Health
by Xiaohua Liu, Yangming Wu, Samuel Bennett, Jun Zou, Jiake Xu and Lingli Zhang
Nutrients 2024, 16(14), 2289; https://doi.org/10.3390/nu16142289 - 17 Jul 2024
Viewed by 2589
Abstract
Bone metabolism is a process in which osteoclasts continuously clear old bone and osteoblasts form osteoid and mineralization within basic multicellular units, which are in a dynamic balance. The process of bone metabolism is affected by many factors, including diet. Reasonable dietary patterns [...] Read more.
Bone metabolism is a process in which osteoclasts continuously clear old bone and osteoblasts form osteoid and mineralization within basic multicellular units, which are in a dynamic balance. The process of bone metabolism is affected by many factors, including diet. Reasonable dietary patterns play a vital role in the prevention and treatment of bone-related diseases. In recent years, dietary patterns have changed dramatically. With the continuous improvement in the quality of life, high amounts of sugar, fat and protein have become a part of people’s daily diets. However, people have gradually realized the importance of a healthy diet, intermittent fasting, calorie restriction, a vegetarian diet, and moderate exercise. Although these dietary patterns have traditionally been considered healthy, their true impact on bone health are still unclear. Studies have found that caloric restriction and a vegetarian diet can reduce bone mass, the negative impact of a high-sugar and high-fat dietary (HSFD) pattern on bone health is far greater than the positive impact of the mechanical load, and the relationship between a high-protein diet (HPD) and bone health remains controversial. Calcium, vitamin D, and dairy products play an important role in preventing bone loss. In this article, we further explore the relationship between different dietary patterns and bone health, and provide a reference for how to choose the appropriate dietary pattern in the future and for how to prevent bone loss caused by long-term poor dietary patterns in children, adolescents, and the elderly. In addition, this review provides dietary references for the clinical treatment of bone-related diseases and suggests that health policy makers should consider dietary measures to prevent and treat bone loss. Full article
(This article belongs to the Section Sports Nutrition)
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<p>The effects of calorie restriction, intermittent fasting, and vegetarian diets on bone health. Caloric restriction can reduce bone mass and bone strength, inhibit bone formation, and promote bone resorption. The effect of fasting on bone mass is not clear. Interestingly, it can effectively reduce the expression of pro-inflammatory factors. Studies have shown that vegetarian diets may reduce bone mass by reducing the synthesis of vitamin B12 and IGF-1.Abbreviations: BMD = bone mineral density; BSAP = bone-specific alkaline phosphatase; OCN = osteocalcin; IGF-1 = insulin-like growth factor 1; CTX-1 = type I collagen carboxy-terminal peptide; TRAP = tartrate-resistant acid phosphatase; CRP = c-reactive protein; IL1β = interleukin-1β; IL6 = interleukin-6; IGF-1 = insulin-like growth factor 1. ↑ = The expression level of this substance is upregulated. ↓ = The expression level of this substance is downregulated.</p>
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<p>The effects of a high-sugar diet, high-fat diet, high-fat and high-sugar diet, and high-protein dietary patterns on bone health. A high-sugar diet, high-fat diet, and high-fat and high-sugar diet can reduce bone mass and bone strength, inhibit bone formation, and promote bone absorption. But research shows that a high-fat diet also plays a positive role in bone health. The relationship between a high-protein diet and bone health is still controversial. It plays an active role in bone health by upregulating IGF-1, inhibiting the PTH, and promoting the intestinal absorption of calcium, while its hypercalciuria and other effects may have adverse effects on bone. Abbreviations: ALP = alkaline phosphatase; Runx2/PPARγ = runt-related transcription factor 2/peroxisome proliferator-activated receptors-γ; BMD = bone mineral density; PINP = procollagen type I N-terminal propeptide; OCN = osteocalcin; OSX = osterix; CTX-1 = type I collagen carboxy-terminal peptide; MCSF = macrophage colony-stimulating factor; TRAP = tartrate-resistant acid phosphatase; IGF-1 = insulin-like growth factor 1; PTH = parathyroid hormone; IL6 = interleukin-6. ↑ = The expression level of this substance is upregulated. ↓ = The expression level of this substance is downregulated.</p>
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Article
Ramadan Intermittent Fasting and Plasma Volume Variations in Individuals with Different Body Weights
by Jihen Khalfoun, Hassane Zouhal, Raoua Triki, Wafa Jribi, Ayoub Saeidi, Abdullah Almaqhawi, Cain C. T. Clark, Ismail Laher and Abderraouf Ben Abderrahman
Medicina 2024, 60(7), 1143; https://doi.org/10.3390/medicina60071143 - 16 Jul 2024
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Abstract
Background: There is increasing awareness of the physiological effects of Ramadan intermittent fasting (RIF) in obese subjects. However, there are no data on the effects of RIF on plasma volume changes (ΔPV) in individuals with different body weights. Background and Objectives: [...] Read more.
Background: There is increasing awareness of the physiological effects of Ramadan intermittent fasting (RIF) in obese subjects. However, there are no data on the effects of RIF on plasma volume changes (ΔPV) in individuals with different body weights. Background and Objectives: This study investigated the effects of RIF on ΔPV in normal-weight (NW) and overweight (OW) adult men, and adult men with obesity (OB) and severe obesity (SO). Materials and Methods: Thirty-two male subjects (32) were divided into four groups (n = 8 per group) according to their body mass index (BMI): normal weight (NW) (BMI < 25 kg/m2; age = 27.4 ± 3.8), overweight (OW) (BMI between 25 and 29.9 kg/m2; age = 26.8 ± 3.7), obese subjects (OB) (BMI between 30 and 34.9 kg/m2; age = 25.6 ± 2.9), and severely obesity (SO) (BMI between 35 and 40 kg/m2; age = 24.0 ± 4.1). Blood samples were collected for 24 h on 4 different occasions, at T0 before the start of the Ramadan month, at T1 15 days after the start of Ramadan, at T2 one day after the end of Ramadan, and at T3 on the 21st day after the end of Ramadan to determine ΔPV. All groups completed their fasting rituals for the 30 days of Ramadan. Results: A significant group × time effect occurred for body mass (p = 0.001; ES = 0.53), BMI (p = 0.001; ES = 0.53), and body fat percentage (p = 0.001; ES = 0.52). Post hoc tests indicated reductions in body mass in OB and SO at T1 (p = 0.03; ES = 0.21 and p = 0.002; ES = 0.12) and T2 (p = 0.03; ES = 0.31 and p = 0.02; ES = 0.23), reductions in BMI in OB and SO at T1 (p = 0.04; ES = 0.35 and p = 0.03; ES = 0.42) and T2 (p = 0.03; ES = 0.52 and p = 0.005; ES = 0.48), and reductions in body fat percentage only in OB AT T1 (p = 0.002; ES = 0.31) and T2 (p = 0.001; ES = 0.17). A significant group × time effect occurred for hematocrit (p = 0.02; ES = 0.34), hemoglobin (p = 0.01; ES = 0.35), and ΔPV (p = 0.02; ES = 0.18). Post hoc tests indicated increases in hematocrit in OB at T2 (p = 0.03; ES = 0.36) and hemoglobin in OB and SO at T1 (p = 0.03; ES = 0.35 and p = 0.002; ES = 0.32) and T2 (p = 0.003; ES = 0.21 and p = 0.002; ES = 0.33). There were also increases in ΔPV in OB at T1 and T2 (p = 0.002; ES = 0.25 and p = 0.003; ES = 0.22) and in SO only at T2 (p = 0.02; ES = 0.37). Contrast analysis indicated that NW was significantly lower than the grand mean of OW, Ob, and SO for all anthropometric and PVV variables (all p < 0.05). Conclusions: The effects of RIF on ΔPV and anthropometric characters was greater in obese individuals compared to normal-weight and overweight participants, suggesting that the improvements in body composition and ΔPV produced by RIF could positively influence obesity. Full article
(This article belongs to the Special Issue Challenges and Perspectives for Physical Medicine and Rehabilitation)
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<p>Graphical overview of study design.</p>
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<p>Plasma volume variations in groups with different body weights. **: <span class="html-italic">p</span> &lt; 0.01; *: <span class="html-italic">p</span> &lt; 0.05.</p>
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