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19 pages, 3457 KiB  
Article
Effects of Normobaric Hypoxia of Varying Severity on Metabolic and Hormonal Responses Following Resistance Exercise in Men and Women
by Jakub Foltyn, Kamila Płoszczyca, Miłosz Czuba, Adam Niemaszyk, Józef Langfort and Robert Gajda
J. Clin. Med. 2025, 14(5), 1514; https://doi.org/10.3390/jcm14051514 - 24 Feb 2025
Viewed by 128
Abstract
Background/Objectives: Resistance exercise under hypoxic conditions induces various metabolic and hormonal responses, yet the relationship between hypoxia severity and anabolic hormone responses remains unclear. This study aimed to assess the effects of a single bout of resistance exercise on metabolic and hormonal [...] Read more.
Background/Objectives: Resistance exercise under hypoxic conditions induces various metabolic and hormonal responses, yet the relationship between hypoxia severity and anabolic hormone responses remains unclear. This study aimed to assess the effects of a single bout of resistance exercise on metabolic and hormonal responses in normoxia and three levels of hypoxia in both men and women. Methods: The study involved 16 physically active individuals with at least two years of experience in recreational resistance training. The participants completed resistance exercise sessions in normoxia and normobaric hypoxia at simulated altitudes of 3000 m (H3000), 4000 m (H4000), and 5000 m (H5000). Blood levels of total testosterone (T), cortisol (C), growth hormone (GH), and metabolic variables were measured before and after exercise. Results: In women, severe hypoxia (H4000 and H5000) was found to significantly enhance post-exercise increases in T and GH compared to H3000 (p < 0.05), without affecting C levels. In men, hypoxia (regardless of intensity) did not significantly augment post-exercise changes in T and GH compared to normoxia. In H4000 conditions, an increase in C levels was observed (p < 0.05), leading to an unfavorable reduction in the T/C ratio. Additionally, a reduction in the total number of repetitions performed during the training session and a weakened metabolic response (lactate and creatine kinase) were observed in men at H5000. Conclusions: In women, severe hypoxia (H5000) was found to induce a pronounced hormonal response, particularly in GH levels. The use of severe hypoxia during resistance exercise appears unfavorable in men due to a reduced metabolic response, and diminished exercise capacity, coupled with a failure to induce more favorable changes in the secretion of anabolic hormones than in normoxic conditions. Full article
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<p>Total number of repetitions completed during a training unit in normoxia and various levels of hypoxia in the male group (<b>A</b>) and in the female group (<b>B</b>). # <span class="html-italic">p</span> &lt; 0.09.</p>
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<p>Blood T levels before (rest), immediately after (max), and 1 h after resistance exercise in normoxia (<b>A</b>) and hypoxia at simulated altitudes of 3000 m (<b>B</b>), 4000 m (<b>C</b>), and 5000 m (<b>D</b>) in the male group. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Blood T levels before (rest), immediately after (max), and 1 h after resistance exercise in normoxia (<b>A</b>) and hypoxia at simulated altitudes of 3000 m (<b>B</b>), 4000 m (<b>C</b>), and 5000 m (<b>D</b>) in the female group. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Blood C levels before (rest), immediately after (max), and 1 h after resistance exercise in normoxia (<b>A</b>) and hypoxia at simulated altitudes of 3000 m (<b>B</b>), 4000 m (<b>C</b>), and 5000 m (<b>D</b>) in the male group. ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Blood C levels before (rest), immediately after (max), and 1 h after resistance exercise in normoxia (<b>A</b>) and hypoxia at simulated altitudes of 3000 m (<b>B</b>), 4000 m (<b>C</b>), and 5000 m (<b>D</b>) in the female group. # <span class="html-italic">p</span> &lt; 0.07; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>The T/C ratio before (rest), immediately after (max), and 1 h after resistance exercise in normoxia (<b>A</b>) and hypoxia at simulated altitudes of 3000 m (<b>B</b>), 4000 m (<b>C</b>), and 5000 m (<b>D</b>) in the male group. ## <span class="html-italic">p</span> &lt; 0.06; * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The T/C ratio values before (rest), immediately after (max), and 1 h after resistance exercise in normoxia (<b>A</b>) and hypoxia at simulated altitudes of 3000 m (<b>B</b>), 4000 m (<b>C</b>), and 5000 m (<b>D</b>) in the female group. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Blood GH levels before (rest), immediately after (max), and 1 h after resistance exercise in normoxia (<b>A</b>) and hypoxia at simulated altitudes of 3000 m (<b>B</b>), 4000 m (<b>C</b>), and 5000 m (<b>D</b>) in the male group. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Blood GH levels before (rest), immediately after (max), and 1 h after resistance exercise in normoxia (<b>A</b>) and hypoxia at simulated altitudes of 3000 m (<b>B</b>), 4000 m (<b>C</b>), and 5000 m (<b>D</b>) in the female group. * <span class="html-italic">p</span> &lt; 0.05.</p>
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16 pages, 1529 KiB  
Article
Impact of Protein and Nutritional Support on the Muscular Status of Critically Ill Patients: A Pilot, Perspective, and Exploratory Study
by Marialaura Scarcella, Emidio Scarpellini, Silvia De Rosa, Michele Umbrello, Gian Marco Petroni, Riccardo Monti, Pierfrancesco Fusco, Edoardo De Robertis, Rita Commissari, Ludovico Abenavoli and Jan Tack
Nutrients 2025, 17(3), 497; https://doi.org/10.3390/nu17030497 - 29 Jan 2025
Viewed by 823
Abstract
Background: Malnutrition and muscle weakness are highly prevalent in critically admitted patients. To overcome sarcopenia and muscle weakness, physical activity and neuromuscular electric stimulation have been introduced with limited efficacy. Thus, several anabolic remedies have been introduced. An adequate increase in protein support [...] Read more.
Background: Malnutrition and muscle weakness are highly prevalent in critically admitted patients. To overcome sarcopenia and muscle weakness, physical activity and neuromuscular electric stimulation have been introduced with limited efficacy. Thus, several anabolic remedies have been introduced. An adequate increase in protein support according to indirect calorimetry and body composition and methyl hydroxybutyrate (HMB) is emerging. Therefore, we wanted to investigate the impact of HMB-enriched whey formula on the nutritional status, muscle weakness, and clinical course of critically ill patients undergoing nutritional status multimodal assessment and physical rehabilitation. Methods: We consecutively enrolled critically ill adult patients admitted to the intensive care unit (ICU) of “Santa Maria Hospital”, Terni, Italy. All patients underwent preliminary anthropometric, laboratory tests, nutritional (bioimpedance vector analysis and indirect calorimetry), and ultrasound muscle assessment at admission (T0). Laboratory tests monitoring continued throughout the ICU stay. Nutritional and muscle strength assessment was taken weekly throughout the patient’s ICU stay. All patients were enterally administered with a whey protein-enriched formula. Ten days after admission (during the physical rehabilitation period), patients were randomly administered a mixture of essential amino acids and methyl hydroxybutyrate (HMB). Results: We consecutively enrolled 54 ICU patients. At the baseline, survivors (n = 46) were significantly younger than non-survivors. The latter had a worse SAPS II score, nutritional status, and risk, with no significant difference in basal metabolism. Prealbumin values significantly correlated with improved nutritional status and metabolism. Starting from 10 days upon ICU admission, the pennation angle (used as a measure of muscle strength) significantly correlated with the improvement in nutritional status. Whey proteins were well tolerated. Its administration showed a tendency to improve the pennation angle. No specific effect of the mixture containing essential amino acids and methyl hydroxybutyrate was observed. Nutritional status improvement and the rise of basal metabolism were significantly correlated with the extubation time. On the other hand, the reduction in muscle weakness was not significantly correlated with the timing of extubation. Conclusions: Whey protein formula administration can significantly improve nutritional status and basal metabolism in ICU patients. This is reflected in improved muscle strength. Whey protein administration shows a tendency toward a rise in pennation angle. A similar and non-specific trend was observed upon HMB mixture add-one. Further prospective large-scale controlled studies are needed to confirm these promising results. Full article
(This article belongs to the Special Issue Nutritional Management in Intensive Care)
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<p>Study design representation. All patients underwent preliminary anthropometric, laboratory tests, nutritional (bioimpedance vector analysis and indirect calorimetry), and ultrasound muscle assessment at admission (namely, T0). Laboratory test monitoring continued throughout the ICU stay. Nutritional and muscle strength assessment was taken weekly throughout the patient’s ICU stay. Upon whey protein formula administration, from day 10 onward, patients were randomly assigned to a mixture of essential amino acids and hydroxy methyl butyrate.</p>
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<p>Improvement in nutritional status and basal metabolism among survivor patients. Starting from day 10 onward, nutritional status (dark grey, PhA °) and basal metabolism (light grey, kcal/kg/day) significantly improved vs. baseline in survivor patients only (ANOVA, both (* and **) <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>(<b>a</b>). Correlation between basal metabolism and prealbumin values (r = 0.34). Prealbumin values significantly rose and correlated with those of basal metabolism, assessed with IC. (<b>b</b>). Nutritional status (light grey, PhA °) and prealbumin values (dark grey, mg/dL). Prealbumin values significantly rose and correlated with those of nutritional status, assessed with BIVA (*, r = 0.37).</p>
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<p>Correlation between nutritional status and pennation angle (r = 0.371).</p>
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<p>Correlation between prealbumin values and the pennation angle (r = 0.354).</p>
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<p>(<b>a</b>). Correlation between nutritional status, basal metabolism, and extubation time. Survivor patients showed a significant correlation between improved nutritional status (PhA °), basal metabolism (IC, mREE, kcal/kg/d), and extubation time, r = 0.38 and 0.332. For each patient, the last PhA and IC value available before the extubation are represented. (<b>b</b>). Muscle strength (measured with the pennation angle) and extubation time (days). The improvement in the pennation angle did not correlate with the extubation time, r = NS.</p>
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<p>(<b>a</b>). HMB administration, nutritional status, and basal metabolism. During the physical rehabilitation period, HMB mixture administration did not significantly affect the improvement in nutritional status and basal metabolism of survivors (ANOVA, ten days upon ICU admission vs. 20 and 30 days, all <span class="html-italic">p</span> = NS). Legend: PhA-HMB, PhA, phase angle in HMB-administered and non-administered patients, respectively. IC-HMB and IC, indirect calorimetry in HMB-administered and non-administered patients, respectively. (<b>b</b>). HMB administration and pennation angle delta. Survivor patients administered with the HMB mixture showed the tendency to have higher pennation angle values at 20 and 30 days vs. ten days upon ICU admission, ANOVA, <span class="html-italic">p</span> = 0.08, <span class="html-italic">p</span> = 0.09, respectively.</p>
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21 pages, 1694 KiB  
Review
Molecular Insights in the Anticancer Activity of Natural Tocotrienols: Targeting Mitochondrial Metabolism and Cellular Redox Homeostasis
by Raffaella Chiaramonte, Giulia Sauro, Domenica Giannandrea, Patrizia Limonta and Lavinia Casati
Antioxidants 2025, 14(1), 115; https://doi.org/10.3390/antiox14010115 - 20 Jan 2025
Viewed by 887
Abstract
The role of mitochondria as the electric engine of cells is well established. Over the past two decades, accumulating evidence has pointed out that, despite the presence of a highly active glycolytic pathway (Warburg effect), a functional and even upregulated mitochondrial respiration occurs [...] Read more.
The role of mitochondria as the electric engine of cells is well established. Over the past two decades, accumulating evidence has pointed out that, despite the presence of a highly active glycolytic pathway (Warburg effect), a functional and even upregulated mitochondrial respiration occurs in cancer cells to meet the need of high energy and the biosynthetic demand to sustain their anabolic growth. Mitochondria are also the primary source of intracellular ROS. Cancer cells maintain moderate levels of ROS to promote tumorigenesis, metastasis, and drug resistance; indeed, once the cytotoxicity threshold is exceeded, ROS trigger oxidative damage, ultimately leading to cell death. Based on this, mitochondrial metabolic functions and ROS generation are considered attractive targets of synthetic and natural anticancer compounds. Tocotrienols (TTs), specifically the δ- and γ-TT isoforms, are vitamin E-derived biomolecules widely shown to possess striking anticancer properties since they regulate several intracellular molecular pathways. Herein, we provide for the first time an overview of the mitochondrial metabolic reprogramming and redox homeostasis perturbation occurring in cancer cells, highlighting their involvement in the anticancer properties of TTs. This evidence sheds light on the use of these natural compounds as a promising preventive or therapeutic approach for novel anticancer strategies. Full article
(This article belongs to the Special Issue Mitochondrial Oxidative Stress in Aging and Disease—2nd Edition)
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<p>Schematic overview of the mitochondrial metabolic reprogramming occurring in cancer cells. Despite the presence of highly active glycolysis, functional mitochondrial respiration (OXPHOS) is present in cancer cells. Mitochondrial metabolic rewiring is frequently associated with mutations in nuclear genes encoding enzymes involved in the TCA cycle, such as succinate dehydrogenase and fumarate hydratase (δ−, loss of function) and isocitrate dehyadrogenase (δ+, gain of function), leading to the accumulation of the oncometabolites succinate, fumarate, and 2-hydroxyglutarate. Somatic mtDNA mutations affecting the expression of proteins of the ETC complexes have also been pointed out in tumor cells. Together, oncometabolites and mtDNA mutants promote dysregulation of the ETC activity, leading to ROS generation, accountable for tumor development and progression. OXPHOS—oxidative phosphorylation; TCA cycle—tricarboxylic acid cycle; mtDNA—mitochondrial DNA; ETC—electron transport chain. This figure was created with BioRender.com.</p>
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<p>Differential effects of ROS levels in normal and cancer cells. In normal cells, low ROS levels are involved in the control of cell growth and survival. In cancer cells, moderate ROS levels are essential for cancer cells to sustain their proliferative, invasive, metastatic, and drug-resistant behavior. On the other hand, excessive ROS levels trigger oxidative stress, resulting in cancer cell death pathways. This figure was created with BioRender.com.</p>
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<p>Chemical structure of the four tocotrienol isoforms (α, β, γ, and δ). This figure was created with BioRender.com.</p>
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<p>Schematic representation depicting the involvement of mitochondrial metabolic reprogramming and ROS generation in the anticancer activity of δ-TT (δ-Tocotrienol). δ-TT triggers ER stress, leading to Ca<sup>2+</sup> release from ER and its accumulation in mitochondria. Ca<sup>2+</sup> overload promotes an impairment of mitochondrial metabolic functions associated with ROS overgeneration, ultimately responsible for the induction of cancer cell death pathways. ER—endoplasmic reticulum; OXPHOS—oxidative phosphorylation; p-AMPK—phosphorylated adenosine monophosphate-activated protein kinase. This figure was created with BioRender.com.</p>
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14 pages, 1008 KiB  
Review
Targeting Asparagine Metabolism in Solid Tumors
by Keita Hanada, Kenji Kawada and Kazutaka Obama
Nutrients 2025, 17(1), 179; https://doi.org/10.3390/nu17010179 - 3 Jan 2025
Viewed by 947
Abstract
Reprogramming of energy metabolism to support cellular growth is a “hallmark” of cancer, allowing cancer cells to balance the catabolic demands with the anabolic needs of producing the nucleotides, amino acids, and lipids necessary for tumor growth. Metabolic alterations, or “addiction”, are promising [...] Read more.
Reprogramming of energy metabolism to support cellular growth is a “hallmark” of cancer, allowing cancer cells to balance the catabolic demands with the anabolic needs of producing the nucleotides, amino acids, and lipids necessary for tumor growth. Metabolic alterations, or “addiction”, are promising therapeutic targets and the focus of many drug discovery programs. Asparagine metabolism has gained much attention in recent years as a novel target for cancer therapy. Asparagine is widely used in the production of other nutrients and plays an important role in cancer development. Nutritional inhibition therapy targeting asparagine has been used as an anticancer strategy and has shown success in the treatment of leukemia. However, in solid tumors, asparagine restriction alone does not provide ideal therapeutic efficacy. Tumor cells initiate reprogramming processes in response to asparagine deprivation. This review provides a comprehensive overview of asparagine metabolism in cancers. We highlight the physiological role of asparagine and current advances in improving survival and overcoming therapeutic resistance. Full article
(This article belongs to the Section Proteins and Amino Acids)
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<p>Regulatory mechanism of ASNS expression. ASNS activity is regulated by signaling pathway in response to cellular stresses: amino acid depletion and endoplasmic reticulum (ER) stress. GCN2, general control nonderepressible 2; eIF2α, eukaryotic initiation factor 2α; ATF4, activating transcription factor 4; PERK, PKR-like endoplasmic reticulum-resident kinase.</p>
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<p>Regulation of intracellular asparagine levels by ASNS, autophagy, and macropinocytosis. Cancer cells exposed to ASNase prevent cell death by inducing autophagy and macropinocytosis. Autophagy attempts to rescue cancer cells by reducing reactive oxygen species (ROS) levels through the elimination of damaged mitochondria. Cancer cells respond to asparagine depletion by inducing macropinocytosis, uptake of extracellular albumin, and amino acid degradation.</p>
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33 pages, 5885 KiB  
Article
Obesity and Metabolic Disease Impair the Anabolic Response to Protein Supplementation and Resistance Exercise: A Retrospective Analysis of a Randomized Clinical Trial with Implications for Aging, Sarcopenic Obesity, and Weight Management
by Mats I. Nilsson, Donald Xhuti, Nicoletta Maria de Maat, Bart P. Hettinga and Mark A. Tarnopolsky
Nutrients 2024, 16(24), 4407; https://doi.org/10.3390/nu16244407 - 23 Dec 2024
Viewed by 2752
Abstract
Background: Anabolic resistance accelerates muscle loss in aging and obesity, thus predisposing to sarcopenic obesity. Methods: In this retrospective analysis of a randomized clinical trial, we examined baseline predictors of the adaptive response to three months of home-based resistance exercise, daily physical activity, [...] Read more.
Background: Anabolic resistance accelerates muscle loss in aging and obesity, thus predisposing to sarcopenic obesity. Methods: In this retrospective analysis of a randomized clinical trial, we examined baseline predictors of the adaptive response to three months of home-based resistance exercise, daily physical activity, and protein-based, multi-ingredient supplementation (MIS) in a cohort of free-living, older males (n = 32). Results: Multiple linear regression analyses revealed that obesity and a Global Risk Index for metabolic syndrome (MetS) were the strongest predictors of Δ% gains in lean mass (TLM and ASM), LM/body fat ratios (TLM/%BF, ASM/FM, and ASM/%BF), and allometric LM (ASMI, TLM/BW, TLM/BMI, ASM/BW), with moderately strong, negative correlations to the adaptive response to polytherapy r = −0.36 to −0.68 (p < 0.05). Kidney function, PA level, and chronological age were only weakly associated with treatment outcomes (p > 0.05). Next, we performed a subgroup analysis in overweight/obese participants with at least one other MetS risk factor and examined their adaptive response to polytherapy with two types of protein-based MIS (PLA; collagen peptides and safflower oil, n = 8, M5; whey/casein, creatine, calcium, vitamin D3, and fish oil, n = 12). The M5 group showed greater improvements in LM (ASM; +2% vs. −0.8%), LM/body fat ratios (ASM/FM; +3.8% vs. −5.1%), allometric LM (ASM/BMI; +1.2% vs. −2.5%), strength (leg press; +17% vs. −1.4%), and performance (4-Step-Stair-Climb time; −10.5% vs. +1.1%) vs. the PLA group (p < 0.05). Bone turnover markers, indicative of bone accretion, were increased pre-to-post intervention in the M5 group only (P1NP; p = 0.036, P1NP/CTX ratio; p = 0.088). The overall anabolic response, as indicated by ranking low-to-high responders for Δ% LM (p = 0.0079), strength (p = 0.097), and performance (p = 0.19), was therefore significantly higher in the M5 vs. PLA group (p = 0.013). Conclusions: Our findings confirm that obesity/MetS is a key driver of anabolic resistance in old age and that a high-quality, whey/casein-based MIS is more effective than a collagen-based alternative for maintaining musculoskeletal health in individuals at risk for sarcopenic obesity, even when total daily protein intake exceeds current treatment guidelines. Full article
(This article belongs to the Special Issue Diet and Nutrition Approaches in Obesity Treatment)
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Graphical abstract
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<p>Consort flow chart. Left panel (1–4): Enrollment, allocation, follow-up, and analysis of the original clinical trial (Nilsson et al. [<a href="#B22-nutrients-16-04407" class="html-bibr">22</a>]). Right panel (5–6): The retrospective data analyses conducted for the current manuscript.</p>
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<p>RCT timeline and clinical testing. X = time point of procedure (weeks 0–1 and 13–14).</p>
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<p>Overall best fit in prediction model 1. Baseline obesity (BMI) was the strongest individual predictor of % lean mass gains following three months of HBRE + PA + MIS polytherapy. The sample size for analyses <span class="html-italic">n</span> = 30–32. All correlations are shown in <a href="#nutrients-16-04407-t001" class="html-table">Table 1</a> and <a href="#app1-nutrients-16-04407" class="html-app">Table S1</a>. (<b>A</b>) Baseline BMI vs. Δ TLM (% change); (<b>B</b>) Baseline BMI vs Δ ASM (% change); (<b>C</b>) Baseline BMI vs Δ ASMI (% change).</p>
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<p>Overall best fit in prediction model 2. Compared to the individual metabolic risk factors (i.e., obesity, dyslipidemia, dysglycemia, and systemic inflammation), the Global MetS Risk Index (i.e., total MetS risk factors <a href="#sec2dot11-nutrients-16-04407" class="html-sec">Section 2.11</a>) was the overall strongest predictor of % lean mass gains following three months of HBRE + PA + MIS polytherapy. The sample size for analyses <span class="html-italic">n</span> = 30–32. All correlations are shown in <a href="#nutrients-16-04407-t002" class="html-table">Table 2</a> and <a href="#app1-nutrients-16-04407" class="html-app">Table S2</a>. (<b>A</b>) Baseline MetS Risk Index vs. Δ TLM (% change); (<b>B</b>) Baseline MetS Risk Index vs. Δ ASM (% change); (<b>C</b>) Baseline MetS Risk Index vs. Δ ASMI (% change).</p>
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<p>Δ LM, FM, and % BF. Between-group differences in the adaptive response (i.e., Δ% changes) were analyzed by independent <span class="html-italic">t</span>-tests (** <span class="html-italic">p</span> ≤ 0.01; <sup>†</sup> <span class="html-italic">p</span> &gt; 0.05 &lt; 0.100). Within-group differences in pre-post intervention results were analyzed by paired <span class="html-italic">t</span>-tests (<sup>#</sup> <span class="html-italic">p</span> ≤ 0.05; <sup>‡</sup> <span class="html-italic">p</span> &gt; 0.05 &lt; 0.100) (<a href="#nutrients-16-04407-t008" class="html-table">Table 8</a>). Sample size for analyses <span class="html-italic">n</span> = 20 (PLA; <span class="html-italic">n</span> = 8, M5; <span class="html-italic">n</span> = 12). (<b>A</b>) Δ TLM (% change); (<b>B</b>) Δ ASM (% change); (<b>C</b>) Δ FM (% change); (<b>D</b>) Δ% Body fat (% change).</p>
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<p>Δ Body Composition Indices. Between-group differences in the adaptive response (i.e., Δ% changes) were analyzed by independent <span class="html-italic">t</span>-tests (* <span class="html-italic">p</span> ≤ 0.05; ** <span class="html-italic">p</span> ≤ 0.01). Within-group differences in pre-post intervention results were analyzed by paired <span class="html-italic">t</span>-tests (<sup>#</sup> <span class="html-italic">p</span> ≤ 0.05) (<a href="#nutrients-16-04407-t008" class="html-table">Table 8</a>). Sample size for analyses <span class="html-italic">n</span> = 20 (PLA; <span class="html-italic">n</span> = 8, M5; <span class="html-italic">n</span> = 12). (<b>A</b>) Δ TLM/FM (% change); (<b>B</b>) Δ TLM/%BF (% change); (<b>C</b>) Δ ASM/FM (% change); (<b>D</b>) Δ ASM/%BF (% change).</p>
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<p>Δ Allometric LM. Between-group differences in the adaptive response (i.e., Δ% changes) were analyzed by independent <span class="html-italic">t</span>-tests (* <span class="html-italic">p</span> ≤ 0.05). Within-group differences in pre-post intervention results were analyzed by paired <span class="html-italic">t</span>-tests (<sup>#</sup> <span class="html-italic">p</span> ≤ 0.05; <sup>‡</sup> <span class="html-italic">p</span> &gt; 0.05 &lt; 0.100) (<a href="#nutrients-16-04407-t008" class="html-table">Table 8</a>). Sample size for analyses <span class="html-italic">n</span> = 20 (PLA; <span class="html-italic">n</span> = 8, M5; <span class="html-italic">n</span> = 12). (<b>A</b>) Δ TLM/BW (% change); (<b>B</b>) Δ TLM/BMI (% change); (<b>C</b>) Δ ASM/BW (% change); (<b>D</b>) Δ ASM/BMI (% change).</p>
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<p>Δ Strength and Muscle Quality. Between-group differences in the adaptive response (i.e., Δ% changes) were analyzed by independent <span class="html-italic">t</span>-tests (<sup>†</sup> <span class="html-italic">p</span> &gt; 0.05 &lt; 0.100). Within-group differences in pre-post intervention results were analyzed by paired <span class="html-italic">t</span>-tests (<sup>#</sup> <span class="html-italic">p</span> ≤ 0.05; <sup>##</sup> <span class="html-italic">p</span> ≤ 0.01) (<a href="#nutrients-16-04407-t009" class="html-table">Table 9</a>). Sample size for strength outcomes <span class="html-italic">n</span> = 19 (PLA; <span class="html-italic">n</span> = 7, M5; <span class="html-italic">n</span> = 12). (<b>A</b>) Δ Leg Press (% change); (<b>B</b>) Knee Extension (% change); (<b>C</b>) Grip Strength (% change); (<b>D</b>) Δ Muscle Quality (% change).</p>
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<p>Δ Performance. Between-group differences in the adaptive response (i.e., Δ% changes) were analyzed by independent <span class="html-italic">t</span>-tests (no significance detected). Within-group differences in pre-post intervention results were analyzed by paired <span class="html-italic">t</span>-tests (<sup>‡</sup> <span class="html-italic">p</span> &gt; 0.05 &lt; 0.100) (<a href="#nutrients-16-04407-t010" class="html-table">Table 10</a>). Sample size for performance outcomes <span class="html-italic">n</span> = 19 (PLA; <span class="html-italic">n</span> = 7, M5; <span class="html-italic">n</span> = 12). (<b>A</b>) Δ 4SSC (% change); (<b>B</b>) Δ SPPB Score (% change).</p>
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<p>Anabolic Ranks. Ranks (low 1- high 20) of anabolic responses (Δ lean mass, Δ strength, Δ performance, and Δ overall) in high-quality (<span class="html-italic">n</span> = 12; M5 + fish oil) vs. lower-quality (<span class="html-italic">n</span> = 8; PLA; collagen + safflower oil) supplement groups in obese/MetS older males following three months of home-based resistance exercise and daily walking (HBRE + PA). Between-group differences in the anabolic response ranks were analyzed by independent <span class="html-italic">t</span>-tests (* <span class="html-italic">p</span> ≤ 0.05; **<span class="html-italic">p</span> ≤ 0.01; <sup>†</sup> <span class="html-italic">p</span> &gt; 0.05 &lt; 0.100). Sample size for anabolic ranks <span class="html-italic">n</span> = 19–20 (PLA; <span class="html-italic">n</span> = 7–8, M5; <span class="html-italic">n</span> = 12). The rankings for lean mass, strength, performance and overall anabolic response are defined in <a href="#sec3dot9-nutrients-16-04407" class="html-sec">Section 3.9</a>. (<b>A</b>) Δ Lean Mass Rank (1–20); (<b>B</b>) Δ Strength Rank (1–20); (<b>C</b>) Δ Performance Rank (1–20); (<b>D</b>) Overall Anabolic Rank (1–20).</p>
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<p>Δ Sarcopenic Obesity Risk Rank. Between-group differences in the adaptive response (i.e., Δ% changes) were analyzed by independent <span class="html-italic">t</span>-tests (** <span class="html-italic">p</span> ≤ 0.01). Within-group differences in pre-post intervention results were analyzed by paired <span class="html-italic">t</span>-tests (<sup>##</sup> <span class="html-italic">p</span> ≤ 0.01) (<a href="#nutrients-16-04407-t003" class="html-table">Table 3</a>). The Sarcopenic Obesity Risk Rank is defined in <a href="#sec2dot11-nutrients-16-04407" class="html-sec">Section 2.11</a>. Sample size for anabolic ranks <span class="html-italic">n</span> = 19 (PLA; <span class="html-italic">n</span> = 7, M5; <span class="html-italic">n</span> = 12).</p>
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<p>Drivers and countermeasures of anabolic resistance in sarcopenic obesity.</p>
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22 pages, 1445 KiB  
Review
Nrf2 Signaling in Renal Cell Carcinoma: A Potential Candidate for the Development of Novel Therapeutic Strategies
by Valentina Schiavoni, Monica Emanuelli, Giulio Milanese, Andrea Benedetto Galosi, Veronica Pompei, Eleonora Salvolini and Roberto Campagna
Int. J. Mol. Sci. 2024, 25(24), 13239; https://doi.org/10.3390/ijms252413239 - 10 Dec 2024
Viewed by 900
Abstract
Renal cell carcinoma (RCC) is the most common type of kidney cancer arising from renal tubular epithelial cells and is characterized by a high aggressive behavior and invasiveness that lead to poor prognosis and high mortality rate. Diagnosis of RCC is generally incidental [...] Read more.
Renal cell carcinoma (RCC) is the most common type of kidney cancer arising from renal tubular epithelial cells and is characterized by a high aggressive behavior and invasiveness that lead to poor prognosis and high mortality rate. Diagnosis of RCC is generally incidental and occurs when the stage is advanced and the disease is already metastatic. The management of RCC is further complicated by an intrinsic resistance of this malignancy to chemotherapy and radiotherapy, which aggravates the prognosis. For these reasons, there is intense research focused on identifying novel biomarkers which may be useful for a better prognostic assessment, as well as molecular markers which could be utilized for targeted therapy. Nuclear factor erythroid 2-related factor 2 (Nrf2) is a transcriptional factor that has been identified as a key modulator of oxidative stress response, and its overexpression is considered a negative prognostic feature in several types of cancers including RCC, since it is involved in various key cancer-promoting functions such as proliferation, anabolic metabolism and resistance to chemotherapy. Given the key role of Nrf2 in promoting tumor progression, this enzyme could be a promising biomarker for a more accurate prediction of RCC course and it can also represent a valuable therapeutic target. In this review, we provide a comprehensive literature analysis of studies that have explored the role of Nrf2 in RCC, underlining the possible implications for targeted therapy. Full article
(This article belongs to the Special Issue NRF2/KEAP1 Signalling in Cancer)
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<p>Schematic representation of <span class="html-italic">Nrf2</span> domains structure. Neh: NRF2-ECH homology domains; KEAP1: Kelch-like-ECH-associated protein 1; ARE: antioxidant response elements; CBP: CREB-binding protein; βTrCP: β-transducin repeat-containing protein; RXRα: retinoic X receptor.</p>
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<p>KEAP1–Nrf2-ARE pathway in constitutive condition and under oxidative stimuli. Nrf2 is continuously produced: in constitutive conditions, it is retained in the cytoplasm by KEAP1, which promotes its degradation via the CUL3-RBX1 ubiquitin ligase complex; under oxidative stimuli, ROS modify KEAP1 cysteines, leading to Nrf2 translocation to the nucleus where it activates the expression of genes involved in the oxidant response. KEAP1: Kelch-like ECH-associated protein 1; Nrf2: nuclear factor-erythroid 2; ARE, antioxidant response elements; CUL3: cullin 3; RBX1: RING-box protein 1; NFE2L2: <span class="html-italic">Nrf2</span> gene; Ub: ubiquitin; NQO1: NAD(P)H quinone oxidoreductase 1; GST: glutathione S-transferases; HO-1: heme oxygenase-1; TRX: thioredoxin; ROS: reactive oxygen species.</p>
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<p>Nrf2 signaling pathway in RCC. RCC: renal cell carcinoma; ccRCC: clear cell renal cell carcinoma; pRCC: papillary renal cell carcinoma; HLRCC: hereditary leiomyomatosis and renal cell carcinoma; CIMP-RCC: CpG Island Methylator Phenotype-RCC; <span class="html-italic">VHL</span>: von Hippel–Lindau; HIF: hypoxia-inducible factor; VEGF: vascular endothelial growth factor; TGFβ: transforming growth factor; <span class="html-italic">CDKN2A</span>: cyclin-dependent kinase inhibitor 2A; <span class="html-italic">SETD2</span>: histone lysine methyltransferase; <span class="html-italic">TFE3</span>: transcription factor E3; <span class="html-italic">FH</span>: fumarate hydratase.</p>
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18 pages, 5572 KiB  
Article
Genetic Analysis of the Peach SnRK1β3 Subunit and Its Function in Transgenic Tomato Plants
by Shilong Zhao, Xuelian Wu, Jiahui Liang, Zhe Wang, Shihao Fan, Hao Du, Haixiang Yu, Yuansong Xiao and Futian Peng
Genes 2024, 15(12), 1574; https://doi.org/10.3390/genes15121574 - 6 Dec 2024
Viewed by 898
Abstract
Background/Objectives: The sucrose non-fermentation-related kinase 1 (SnRK1) protein complex in plants plays an important role in energy metabolism, anabolism, growth, and stress resistance. SnRK1 is a heterotrimeric complex. The SnRK1 complex is mainly composed of α, β, βγ, and γ subunits. Studies on [...] Read more.
Background/Objectives: The sucrose non-fermentation-related kinase 1 (SnRK1) protein complex in plants plays an important role in energy metabolism, anabolism, growth, and stress resistance. SnRK1 is a heterotrimeric complex. The SnRK1 complex is mainly composed of α, β, βγ, and γ subunits. Studies on plant SnRK1 have primarily focused on the functional α subunit, with the β regulatory subunit remaining relatively unexplored. The present study aimed to elucidate the evolutionary relationship, structural prediction, and interaction with the core α subunit of peach SnRK1β3 (PpSnRK1) subunit. Methods: Bioinformatics analysis of PpSnRK1 was performed through software and website. We produced transgenic tomato plants overexpressing PpSnRK1 (OEPpSnRK1). Transcriptome analysis was performed on OEPpSnRK1 tomatoes. We mainly tested the growth index and drought resistance of transgenic tomato plants. Results: The results showed that PpSnRK1 has a 354 bp encoded protein sequence (cds), which is mainly located in the nucleus and cell membrane. Phylogenetic tree analysis showed that PpSnRK1β3 has similar domains to other woody plants. Transcriptome analysis of OEPpSnRK1β3 showed that PpSnRK1β3 is widely involved in biosynthetic and metabolic processes. Functional analyses of these transgenic plants revealed prolonged growth periods, enhanced growth potential, improved photosynthetic activity, and superior drought stress tolerance. Conclusions: The study findings provide insight into the function of the PpSnRK1 subunit and its potential role in regulating plant growth and drought responses. This comprehensive analysis of PpSnRK1 will contribute to further enhancing our understanding of the plant SnRK1 protein complex. Full article
(This article belongs to the Section Plant Genetics and Genomics)
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<p>Length, structure prediction, and subcellular localization of PpSnRK1β3. (<b>a</b>) The cds length electropherogram of PpSnRK1β3. (<b>b</b>) Spatial structure prediction of PpSnRK1β3. (<b>c</b>) Subcellular localization of PpSnRK1β3.</p>
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<p>Phylogenetic tree analysis of PpSnRK1β3. (<b>a</b>) Phylogenetic tree analysis of the SnRK1β3 protein in different species. (<b>b</b>) Sequence alignment of the SnRK1β3 protein from different species.</p>
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<p>Interaction between the PpSnRK1β3 and PpSnRK1α subunits. (<b>a</b>) Yeast two-hybrid assay of PpSnRK1β3 and PpSnRK1α. (<b>b</b>) Bimolecular fluorescence complementation (BiFC) assay of PpSnRK1β3 and PpSnRK1α. (<b>c</b>) Dual luciferase assay of PpSnRK1β3 and PpSnRK1α.</p>
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<p>GO enrichment analysis of the comparison between OEPpSnRK1β3 and WT tomatoes. DEGs were selected based on a cut-off of <span class="html-italic">p</span>-adjust  &lt;  0.05 and |log2FC| ≥ 1, <span class="html-italic">p</span>-adjust lists the top 20 enrichments in ascending order. (<b>a</b>–<b>c</b>) Downregulated WT genes were associated with biological processes, cellular components, and molecular functions in GO enrichment compared with the OEPpSnRK1β3 tomatoes. (<b>d</b>–<b>f</b>) WT upregulated in biological processes, cellular components, and molecular functions in GO enrichment compared with the OEPpSnRK1β3 tomatoes.</p>
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<p>KEGG enrichment analysis of the comparison between OEPpSnRK1β3 and WT tomatoes. DEGs were selected based on a cut-off of <span class="html-italic">p</span>-adjust  &lt;  0.05 and |log2FC| ≥ 1; <span class="html-italic">p</span>-adjust lists the top 20 enrichments in ascending order. (<b>a</b>) Downregulated WT genes by KEGG enrichment compared with OEPpSnRK1β3 tomatoes. (<b>b</b>) Upregulated WT genes by KEGG enrichment compared with OEPpSnRK1β3 tomatoes.</p>
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<p>Growth characteristics of the OEPpSnRK1β3 tomatoes. (<b>a</b>) Growth period of OEPpSnRK1β3 and WT tomatoes (white line in the diagram indicates the height of 1 cm). (<b>b</b>) Fruit development period of OEPpSnRK1β3 and WT tomatoes (white line in the diagram indicates the length of 1 cm). Comparison of plant height (<b>c</b>), stem diameter (<b>d</b>), leaf area (<b>e</b>), and number of days in the growth period (<b>f</b>) for three strains of OEPpSnRK1β3 and WT tomatoes. Error bars represent the means ± SD (<span class="html-italic">n</span> = 3) from three independent biological replicates. Note: For (<b>c</b>–<b>f</b>), asterisks represent significant differences (LSD test, *, <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Photosynthetic indicators of OEPpSnRK1β3 tomatoes. Comparison of maximum net photosynthetic efficiency (<b>a</b>), chlorophyll content (<b>b</b>), stomatal conductance (<b>c</b>), and intercellular carbon dioxide concentration (<b>d</b>) for three strains of OEPpSnRK1β3 and WT tomatoes. Error bars represent the means ± SD (<span class="html-italic">n</span> = 3) from three independent biological replicates. Asterisks represent significant differences (LSD test, *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Physiological indexes of stress in OEPpSnRK1β3 tomatoes under drought stress. (<b>a</b>) The state of OEPpSnRK1β3 and WT tomatoes under normal and 14-day drought stress. Comparison of maximum photochemical efficiency (<b>b</b>), malondialdehyde content (<b>c</b>), hydrogen peroxide content (<b>d</b>), superoxide anion content (<b>e</b>), and relative electrolyte leakage (<b>f</b>) for three strains of OEPpSnRK1β3 and WT tomatoes under normal and 14-day drought stress conditions. Error bars represent the means ± SD (<span class="html-italic">n</span> = 3) from three independent biological replicates. Note: For (<b>b</b>–<b>f</b>), asterisks represent significant differences (LSD test, *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01).</p>
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11 pages, 563 KiB  
Review
Metabolic, Inflammatory, and Molecular Impact of Cancer Cachexia on the Liver
by Daniela Caetano Gonçalves, Silvio Pires Gomes and Marília Seelaender
Int. J. Mol. Sci. 2024, 25(22), 11945; https://doi.org/10.3390/ijms252211945 - 7 Nov 2024
Viewed by 1603
Abstract
Cancer-associated cachexia (CAC) is a severe wasting syndrome, marked by involuntary weight loss and muscle wasting. It is a leading cause of cancer-related morbidity and mortality, and is driven by systemic, chronic low-grade inflammation. Key cytokines, such as IL-6 and GDF15, activate catabolic [...] Read more.
Cancer-associated cachexia (CAC) is a severe wasting syndrome, marked by involuntary weight loss and muscle wasting. It is a leading cause of cancer-related morbidity and mortality, and is driven by systemic, chronic low-grade inflammation. Key cytokines, such as IL-6 and GDF15, activate catabolic pathways in many organs. This study examined the role of inflammation and metabolic disruption in the liver during CAC, focusing on its dual role as both a target and a source of inflammatory factors. The analysis covered protein and lipid metabolism disturbances, including the hepatic production of acute-phase proteins and insulin resistance. Hepatic inflammation contributes to systemic dysfunction in CAC. The increased production of C-Reactive Protein (CRP) impacts muscle wasting, while liver inflammation leads to insulin resistance and hepatic steatosis, aggravating the cachectic state. Therefore, understanding the molecular mechanisms of liver metabolism in CAC is essential for developing effective therapies. Potential interventions include anti-inflammatory treatments, anabolic strategies, and restoration of lipid metabolism. Further research is necessary to explore the liver’s full contribution to CAC and its systemic effects, allowing to the development of liver-targeted therapeutic strategies. Full article
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<p>Schematic overview of the liver’s central role in the development of cachexia. The Liver interacts with the immune system, muscle tissue, and adipose tissue in cycles involving inflammation, proteolysis, and fat mobilization. The figure was created using resources from BioRender (<a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a>), accessed on 15 October 2024.</p>
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14 pages, 3091 KiB  
Article
Integrated Transcriptomic Analyses of Liver and Mammary Gland Tissues Reveals the Regulatory Mechanism Underlying Dairy Goats at Late Lactation When Feeding Rumen-Protected Lysine
by Wenting Dai, Bingqing Han, Yalu Sun, Pengfei Hou, Chong Wang, Weini Li and Hongyun Liu
Int. J. Mol. Sci. 2024, 25(21), 11376; https://doi.org/10.3390/ijms252111376 - 23 Oct 2024
Viewed by 958
Abstract
Although low-protein diets can improve the nitrogen utilization efficiency and alleviate economic pressures in ruminants, they may also negatively impact dairy performance. Rumen-protected lysine (RPL) supplementation can improve the health status and growth performance of ruminants without compromising nitrogen utilization efficiency and feed [...] Read more.
Although low-protein diets can improve the nitrogen utilization efficiency and alleviate economic pressures in ruminants, they may also negatively impact dairy performance. Rumen-protected lysine (RPL) supplementation can improve the health status and growth performance of ruminants without compromising nitrogen utilization efficiency and feed intake. In this study, a total of thirty-three multiparous dairy goats in the late-lactation period were randomly divided into three groups that were separately fed the control diet (namely the protein-adequacy group), the low-protein diet (namely the protein-deficient group), and the RPL-supplemented protein-deficient diet (namely RPL-supplementation group) for five weeks. Here, we investigated the molecular mechanisms regarding how low-protein diets with RPL supplementation compromise lactation phenotypes in dairy goats through cross-tissue transcriptomic analyses. Dietary protein deficiency caused an imbalance in amino acid (AA) intake, disrupted hepatic function, and impaired milk synthesis. Transcriptomic analyses further showed that RPL supplementation exhibited some beneficial effects, like mitigating abnormal lipid and energy metabolism in the liver, elevating hepatic resistance to oxidative stress, improving the mammary absorption of AAs, as well as activating mammary lipid and protein anabolism primarily through peroxisome proliferator-activated receptor (PPAR) and janus kinase-signal transducer (JAK)—signal transducer and activator of transcription (STAT) signaling, respectively. RPL supplementation of a low-protein diet contributes to maintaining late lactation in dairy goats primarily through mitigating hepatic energy disturbances and activating both lipid and protein metabolism in the mammary glands. Since RPL supplementation initiated a series of comprised events on mammary protein and lipid metabolism as well as the hepatic function and energy generation in dairy goats under protein deficiency during late lactation, these findings thus provide some insights into how RPL supplementation helps maintain milk production and health in dairy mammals especially at late lactation. Full article
(This article belongs to the Section Molecular Endocrinology and Metabolism)
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<p>Effects of supplying lysine on hepatic transcriptome of dairy goats during late lactation. (<b>A</b>) GSEA analysis of DEGs from liver in D vs. C groups. MF in grey represents molecular function; CC in green represents cell component; BP in black represents biological process. (<b>B</b>) Hub genes from liver in D vs. C and DL vs. D groups. DEGs from liver in D vs. C (<b>C</b>) and DL vs. C (<b>D</b>) groups are involved in the lipid metabolism, carbohydrate metabolism, and amino acid metabolism. (<b>E</b>) KEGG analysis of the up-regulated and down-regulated DEGs from liver in DL vs. D groups. “C” represents the control group, namely protein-adequacy group; “D” represents the protein-deficient group; and “DL” represents the rumen-protected lysine (RPL)-supplemented protein-deficient group.</p>
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<p>Effects of lysine supplementation on mammary gland transcriptome of dairy goats at late lactation. (<b>A</b>) GSEA analysis of DEGs from mammary glands in D vs. C and DL vs. D groups. (<b>B</b>) DEGs from mammary glands in D vs. C and DL vs. D groups are involved in the nutrient metabolism and signaling pathway. (<b>C</b>) KEGG analysis of the up-regulated and down-regulated DEGs from mammary glands in DL vs. D groups. (<b>D</b>) Hub genes from mammary glands in DL vs. D groups. “C” represents the control group, namely protein-adequacy group; “D” represents the protein-deficient group; and “DL” represents the rumen-protected-lysine-supplemented protein-deficient group.</p>
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<p>DEGs are involved in lactation processes in liver and mammary glands of dairy goats during late lactation. The effects of protein deficiency (<b>A</b>) and lysine supplementation (<b>B</b>) on differential gene profiles from both liver and mammary glands of dairy goats during late lactation. “C” represents the control group, namely protein-adequacy group; “D” represents the protein-deficient group; and “DL” represents the rumen-protected-lysine-supplemented protein-deficient group.</p>
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<p>Schematic model depicting how RPL supplementation of a low-protein diet contributed to maintaining milk production and health at late lactation by integrated transcriptomics at cross-tissue levels. RPL: rumen-protected lysine.</p>
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26 pages, 1423 KiB  
Review
Personalized Nutrition in the Pediatric ICU: Steering the Shift from Acute Stress to Metabolic Recovery and Rehabilitation
by George Briassoulis, Stavroula Ilia and Efrossini Briassouli
Nutrients 2024, 16(20), 3523; https://doi.org/10.3390/nu16203523 - 17 Oct 2024
Cited by 1 | Viewed by 2187
Abstract
Background: Nutrition significantly impacts the outcomes of critically ill children in intensive care units (ICUs). Due to the evolving metabolic, neuroendocrine, and immunological disorders associated with severe illness or trauma, there are dynamically changing phases of energy needs requiring tailored macronutrient intake. Objectives: [...] Read more.
Background: Nutrition significantly impacts the outcomes of critically ill children in intensive care units (ICUs). Due to the evolving metabolic, neuroendocrine, and immunological disorders associated with severe illness or trauma, there are dynamically changing phases of energy needs requiring tailored macronutrient intake. Objectives: This study aims to assess the changing dietary needs from the acute phase through recovery, provide recommendations for implementing evidence-based strategies to ensure adequate energy and nutrient provision in pediatric ICUs, and optimize patient outcomes. Methods: A comprehensive search of the MEDLINE-PubMed database was conducted, focusing on randomized controlled trials, meta-analyses, and systematic reviews related to the nutrition of critically ill children. The study highlights recent guidelines using the GRADE approach, supplemented by relevant adult studies, current clinical practices, challenges, gaps in knowledge, and future directions for research aimed at improving nutritional interventions. Results: Early personalized, incremental enteral feeding helps mitigate the negative energy balance during the acute phase, aids organ function restoration in the stabilization phase, and supports growth during the recovery phase and beyond. Conversely, early full nutritional support, high protein doses, or isolated micronutrient administration have not demonstrated benefits due to anabolic resistance in these patients. Moreover, early parenteral nutrition during the acute phase may suppress autophagy and lead to worse outcomes. Accurate assessment of nutritional status and monitoring of daily energy and protein needs are crucial. Conclusions: Strong evidence supports the establishment of a dedicated nutritional team and the implementation of individualized nutritional protocols in the ICU to reduce morbidity and mortality in critically ill children. Full article
(This article belongs to the Section Clinical Nutrition)
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<p>Typical metabolic adaptations during the acute phase of severe illness.</p>
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<p>The evolving energy demands during different metabolic phases of critical illness.</p>
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<p>Composition and functions of the intestinal microbiome in critically ill patients compared to healthy children.</p>
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41 pages, 1903 KiB  
Review
Acute Sarcopenia: Mechanisms and Management
by Sarah Damanti, Eleonora Senini, Rebecca De Lorenzo, Aurora Merolla, Simona Santoro, Costanza Festorazzi, Marco Messina, Giordano Vitali, Clara Sciorati and Patrizia Rovere-Querini
Nutrients 2024, 16(20), 3428; https://doi.org/10.3390/nu16203428 - 10 Oct 2024
Cited by 1 | Viewed by 4784
Abstract
Background: Acute sarcopenia refers to the swift decline in muscle function and mass following acute events such as illness, surgery, trauma, or burns that presents significant challenges in hospitalized older adults. Methods: narrative review to describe the mechanisms and management of acute sarcopenia. [...] Read more.
Background: Acute sarcopenia refers to the swift decline in muscle function and mass following acute events such as illness, surgery, trauma, or burns that presents significant challenges in hospitalized older adults. Methods: narrative review to describe the mechanisms and management of acute sarcopenia. Results: The prevalence of acute sarcopenia ranges from 28% to 69%, likely underdiagnosed due to the absence of muscle mass and function assessments in most clinical settings. Systemic inflammation, immune–endocrine dysregulation, and anabolic resistance are identified as key pathophysiological factors. Interventions include early mobilization, resistance exercise, neuromuscular electrical stimulation, and nutritional strategies such as protein supplementation, leucine, β-hydroxy-β-methyl-butyrate, omega-3 fatty acids, and creatine monohydrate. Pharmaceuticals show variable efficacy. Conclusions: Future research should prioritize serial monitoring of muscle parameters, identification of predictive biomarkers, and the involvement of multidisciplinary teams from hospital admission to address sarcopenia. Early and targeted interventions are crucial to improve outcomes and prevent long-term disability associated with acute sarcopenia. Full article
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<p>Main modifications in aging muscles.</p>
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<p>Patterns of acute and chronic sarcopenia throughout the lifespan.</p>
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<p>Predisposing and precipitating risk factors for acute sarcopenia.</p>
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<p>Consequences of acute sarcopenia.</p>
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<p>Consequences of acute sarcopenia.</p>
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27 pages, 7759 KiB  
Review
Emerging Targets and Treatments for Sarcopenia: A Narrative Review
by Stefano Cacciatore, Riccardo Calvani, Ilaria Esposito, Claudia Massaro, Giordana Gava, Anna Picca, Matteo Tosato, Emanuele Marzetti and Francesco Landi
Nutrients 2024, 16(19), 3271; https://doi.org/10.3390/nu16193271 - 27 Sep 2024
Cited by 2 | Viewed by 4898
Abstract
Background: Sarcopenia is characterized by the progressive loss of skeletal muscle mass, strength, and function, significantly impacting overall health and quality of life in older adults. This narrative review explores emerging targets and potential treatments for sarcopenia, aiming to provide a comprehensive overview [...] Read more.
Background: Sarcopenia is characterized by the progressive loss of skeletal muscle mass, strength, and function, significantly impacting overall health and quality of life in older adults. This narrative review explores emerging targets and potential treatments for sarcopenia, aiming to provide a comprehensive overview of current and prospective interventions. Methods: The review synthesizes current literature on sarcopenia treatment, focusing on recent advancements in muscle regeneration, mitochondrial function, nutritional strategies, and the muscle–microbiome axis. Additionally, pharmacological and lifestyle interventions targeting anabolic resistance and neuromuscular junction integrity are discussed. Results: Resistance training and adequate protein intake remain the cornerstone of sarcopenia management. Emerging strategies include targeting muscle regeneration through myosatellite cell activation, signaling pathways, and chronic inflammation control. Gene editing, stem cell therapy, and microRNA modulation show promise in enhancing muscle repair. Addressing mitochondrial dysfunction through interventions aimed at improving biogenesis, ATP production, and reducing oxidative stress is also highlighted. Nutritional strategies such as leucine supplementation and anti-inflammatory nutrients, along with dietary modifications and probiotics targeting the muscle–microbiome interplay, are discussed as potential treatment options. Hydration and muscle–water balance are emphasized as critical in maintaining muscle health in older adults. Conclusions: A combination of resistance training, nutrition, and emerging therapeutic interventions holds potential to significantly improve muscle function and overall health in the aging population. This review provides a detailed exploration of both established and novel approaches for the prevention and management of sarcopenia, highlighting the need for further research to optimize these strategies. Full article
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<p>Overview of emerging pathways and potential therapeutic approaches for age-related sarcopenia. Abbreviations: Ach, acetylcholine; AchE, acetylcholinesterase; Akt, protein kinase B; ATP, adenosine triphosphate; IGF-1, insulin-like growth factor 1; mTOR: mechanistic target of rapamycin; MuSK, muscle-specific kinase; NAD+, nicotinamide adenine dinucleotide; NMJ, neuromuscular junction; PGC-1α, peroxisome proliferator-activated receptor gamma coactivator 1-alpha; PI3K, phosphoinositide 3-kinase; SCFA, short-chain fatty acids.</p>
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<p>Age-related changes in neuromuscular junction potentially contributing to sarcopenia. Abbreviations: nAchR, nicotinic acetylcholine receptors; MuSK, muscle-specific kinase.</p>
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Review
A Narrative Review of the Diagnosis and Treatment of Sarcopenia and Malnutrition in Patients with Heart Failure
by Lucía de Jorge-Huerta, Cristian Marco-Alacid, Cristina Grande and Christian Velardo Andrés
Nutrients 2024, 16(16), 2717; https://doi.org/10.3390/nu16162717 - 15 Aug 2024
Viewed by 2542
Abstract
The prevalence of sarcopenia (loss of muscle strength, mass and function) in individuals with heart failure (HF) stands at a considerable level (approximately 20%), contributing to heightened mortality rates and diminished quality of life. The underlying pathophysiological mechanisms involve the presence of low-grade [...] Read more.
The prevalence of sarcopenia (loss of muscle strength, mass and function) in individuals with heart failure (HF) stands at a considerable level (approximately 20%), contributing to heightened mortality rates and diminished quality of life. The underlying pathophysiological mechanisms involve the presence of low-grade inflammation and a disturbance of the anabolic–catabolic protein balance. The nutritional assessment of patients with HF is a key aspect, and diverse diagnostic tools are employed based on patient profiles (outpatient, inpatient and nursing home). The Global Leadership Initiative on Malnutrition (GLIM) criteria serves as a consensus for diagnosing malnutrition. Given that edema can impact body mass index (BMI) in patients with HF, alternative body assessment technical methods, such as bioelectrical vector impedance (BiVA), BIA (without vector mode), computer tomography (CT) or clinical ultrasound (US), are useful. Scientific evidence supports the efficacy of both aerobic and resistance physical exercises in ameliorating and preventing muscle wasting associated with HF. Dietary strategies emphasize the importance of protein intake, while certain micronutrients like coenzyme Q10 or intravenous iron may offer benefits. This narrative review aims to present the current understanding of the pathogenesis, diagnosis and treatment of muscle loss in individuals with heart failure and its consequential impact on prognosis. Full article
(This article belongs to the Section Clinical Nutrition)
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<p>Body composition phenotypes and the progressive loss of cardiorespiratory fitness and muscle strength in heart failure. BC: Body Composition; O: Obesity; C: Cachexia; S: Sarcopenia; CRF: Cardiorespiratory Fitness; +: Increase; −: Decrease; ±: Unchanged.</p>
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<p>Eligibility criteria flowchart.</p>
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<p>Main pathophysiological alterations that occur in the development of malnutrition in relation to heart failure [<a href="#B8-nutrients-16-02717" class="html-bibr">8</a>]. GH: growth hormone; IGF-1: insulin-like growth factor-1; TNF-α: tumor necrosis factor alpha; CRP: C-reactive protein; IL-6: interleukin-6; RAAS: renin–angiotensin–aldosterone system; SNS: sympathetic nervous system. Reproduced with permission from Fernández Pombo A et al. Relevance of nutritional assessment and treatment to counteract cardiac cachexia and sarcopenia in chronic heart failure. Clin. Nutr. 2021, 40, 5141–5155. CC-BY-NC-ND License.</p>
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<p>Diagnostic flowchart of GLIM criteria and phenotypic and etiologic criteria.</p>
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<p>Calf circumference adjustment factors based on BMI [<a href="#B25-nutrients-16-02717" class="html-bibr">25</a>,<a href="#B26-nutrients-16-02717" class="html-bibr">26</a>,<a href="#B27-nutrients-16-02717" class="html-bibr">27</a>].</p>
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<p>Sarcopenia diagnosis flowchart following EWGSOP2 algorithm for case-finding, making a diagnosis and quantifying severity in practice. Adapted from Cruz-Jentoff A. J. et al. 2019 [<a href="#B2-nutrients-16-02717" class="html-bibr">2</a>]. SPPB: short physical performance battery; TUG: timed-up-and-go test.</p>
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14 pages, 971 KiB  
Article
Effectiveness of Resistance Training Program on Body Composition in Adults Following Vegan Diet versus Omnivorous Diet; Developed in Mobile Health Modality
by Richar Cárcamo-Regla, Rafael Zapata-Lamana, Carolina Ochoa-Rosales, Miquel Martorell, Fernanda Carrasco-Marín and Guillermo Molina-Recio
Nutrients 2024, 16(15), 2539; https://doi.org/10.3390/nu16152539 - 2 Aug 2024
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Abstract
Background: The vegan diet (VEGD) has gained popularity in recent years for ecological and ethical reasons, as well as for its health benefits. In addition to the type of diet, the resistance training program (RTP) plays a fundamental role [...] Read more.
Background: The vegan diet (VEGD) has gained popularity in recent years for ecological and ethical reasons, as well as for its health benefits. In addition to the type of diet, the resistance training program (RTP) plays a fundamental role as one of the main natural anabolic stimuli to increase musculoskeletal mass and reduce fat mass. Methods: The study was a 16-week non-randomized controlled clinical trial consisting of three RTP sessions per week. The sample included 70 Chilean individuals, aged between 18 and 59 years, who had been following a VEGD or omnivorous diet (OMND) for the past 6 months. Four groups were established: Vegan Diet Resistance Training Program (VEGD-RTP), Vegan Diet Control (VEGD-C), Omnivorous Diet Resistance Training Program (OMND-RTP), and Omnivorous Diet Control (OMND-C). Results: The sample consisted of 47 women and 23 men, with a mean age of 30.1 (±8.6) years. A reduction of 1.20% in the percentage of fat mass (%FM) was observed in the VEGD-RTP group (r = 0.554, p = 0.016), as well as a reduction of 0.70 kg in kilograms of fat mass (KFM) (r = 0.480, p = 0.036). The OMND-RTP group decreased %FM by 0.90% (r = 0.210, p = 0.432) and KFM by 0.50 kg (r = 0.109, p = 0.683). Conclusions: RTP combined with VEGD or OMND significantly reduced the percentage of fat mass, although its effect was more significant in the VEGD-RTP participants. Full article
(This article belongs to the Section Sports Nutrition)
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<p>Images extracted from the APPTIVATE platform.</p>
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<p>This figure shows the flow diagrams of the participants, separated according to their type of diet, and assigned to either the intervention group with RT<sub>P</sub> or the control group.</p>
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15 pages, 3553 KiB  
Article
Electrochemical and Fluorescence MnO2-Polymer Dot Electrode Sensor for Osteoarthritis-Based Peroxisomal β-Oxidation Knockout Model
by Akhmad Irhas Robby, Songling Jiang, Eun-Jung Jin and Sung Young Park
Biosensors 2024, 14(7), 357; https://doi.org/10.3390/bios14070357 - 22 Jul 2024
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Abstract
A coenzyme A (CoA-SH)-responsive dual electrochemical and fluorescence-based sensor was designed utilizing an MnO2-immobilized-polymer-dot (MnO2@D-PD)-coated electrode for the sensitive detection of osteoarthritis (OA) in a peroxisomal β-oxidation knockout model. The CoA-SH-responsive MnO2@D-PD-coated electrode interacted sensitively with CoA-SH [...] Read more.
A coenzyme A (CoA-SH)-responsive dual electrochemical and fluorescence-based sensor was designed utilizing an MnO2-immobilized-polymer-dot (MnO2@D-PD)-coated electrode for the sensitive detection of osteoarthritis (OA) in a peroxisomal β-oxidation knockout model. The CoA-SH-responsive MnO2@D-PD-coated electrode interacted sensitively with CoA-SH in OA chondrocytes, triggering electroconductivity and fluorescence changes due to cleavage of the MnO2 nanosheet on the electrode. The MnO2@D-PD-coated electrode can detect CoA-SH in immature articular chondrocyte primary cells, as indicated by the significant increase in resistance in the control medium (R24h = 2.17 MΩ). This sensor also sensitively monitored the increase in resistance in chondrocyte cells in the presence of acetyl-CoA inducers, such as phytol (Phy) and sodium acetate (SA), in the medium (R24h = 2.67, 3.08 MΩ, respectively), compared to that in the control medium, demonstrating the detection efficiency of the sensor towards the increase in the CoA-SH concentration. Furthermore, fluorescence recovery was observed owing to MnO2 cleavage, particularly in the Phy- and SA-supplemented media. The transcription levels of OA-related anabolic (Acan) and catabolic factors (Adamts5) in chondrocytes also confirmed the interaction between CoA-SH and the MnO2@D-PD-coated electrode. Additionally, electrode integration with a wireless sensing system provides inline monitoring via a smartphone, which can potentially be used for rapid and sensitive OA diagnosis. Full article
(This article belongs to the Special Issue Electrochemical Biosensors for Disease Detection)
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<p>(<b>a</b>) Illustration of MnO<sub>2</sub>@D-PD-coated electrode fabrication and application for CoA-SH sensing. (<b>b</b>) UV-vis spectra, (<b>c</b>) PL spectra, (<b>d</b>) DLS profiles, and (<b>e</b>) XRD analysis of MnO<sub>2</sub>@D-PD nanoparticles in the absence and presence of CoA-SH.</p>
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<p>(<b>a</b>) EIS spectra, (<b>b</b>) sourcemeter measurement, and (<b>c</b>) wireless sensing profiles (shown as resistance graph) of MnO<sub>2</sub>@D-PD-coated Si wafer in the presence of various concentrations of CoA-SH. The effect of CoA-SH (10 mM) on the (<b>d</b>) fluorescence of the coated PET surface, and (<b>e</b>) surface morphology/AFM profile of MnO<sub>2</sub>@D-PD-coated Si wafer.</p>
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<p>(<b>a</b>) Pathway enrichment analysis of downregulated genes in IL1β-treated human chondrocytes (GSE162510) and osteoarthritis patient chondrocytes (GSE75181) with key affected biological processes and pathways and corresponding <span class="html-italic">p</span>-values. (<b>b</b>) Bright field image of iMACs treated with Phy and SA, compared to controls. (<b>c</b>) The fold-change of peroxisome-related genes in iMACs treated with Phy or SA compared to control, presented as a heat map. (<b>d</b>) Venn diagram illustrating the overlapping peroxisomal genes both in human and mouse during OA pathogenesis.</p>
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<p>(<b>a</b>) Sourcemeter measurement (* = <span class="html-italic">p</span> &lt; 0.1, *** = <span class="html-italic">p</span> &lt; 0.001), (<b>b</b>) EIS spectra (24 h incubation), (<b>c</b>) wireless sensing (24 h incubation) of MnO<sub>2</sub>@D-PD-coated electrode, and (<b>d</b>) confocal imaging of MnO<sub>2</sub>@D-PD-coated electrode PET surface before (negative control) and after incubation with iMACs in control, Phy, and SA media.</p>
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<p>(<b>a</b>) SEM-EDX images of MnO<sub>2</sub>@D-PD-coated electrode surface after incubation with iMACs in control, Phy, and SA media. Cellular uptake of cells seeded on MnO<sub>2</sub>@D-PD-coated electrode in control, Phy, and SA media observed via (<b>b</b>) confocal microscopy and (<b>c</b>) flow cytometry. (<b>d</b>) Transcriptional level of aggrecan (<span class="html-italic">Acan</span>) and <span class="html-italic">Adamts5</span> genes in iMACs cultured in control, Phy, and SA media (**** = <span class="html-italic">p</span> &lt; 0.0001).</p>
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