AG1® Induces a Favorable Impact on Gut Microbial Structure and Functionality in the Simulator of Human Intestinal Microbial Ecosystem® Model.

Modulation of the human gut microbiome has become an area of interest in the nutraceutical space. We explored the effect of the novel foundational nutrition supplement AG1® on the composition of human microbiota in an in vitro experimental design. Employing the Simulator of Human Intestinal Microbial Ecosystem (SHIME®) model, AG1® underwent digestion, absorption, and subsequent colonic microenvironment simulation under physiologically relevant conditions in healthy human fecal inocula. Following 48 h of colonic simulation, the gut microbiota were described using shallow shotgun, whole genome sequencing. Metagenomic data were used to describe changes in community structure (alpha diversity, beta diversity, and changes in specific taxa) and community function (functional heterogeneity and changes in specific bacterial metabolic pathways). Results showed no significant change in alpha diversity, but a significant effect of treatment and donor and an interaction between the treatment and donor effect on structural heterogeneity likely stemming from the differential enrichment of eight bacterial taxa. Similar findings were observed for community functional heterogeneity likely stemming from the enrichment of 20 metabolic pathways characterized in the gene ontology term database. It is logical to conclude that an acute dose of AG1 has significant effects on gut microbial composition that may translate into favorable effects in humans.

Nutrient synergy: definition, evidence, and future directions.

Nutrient synergy refers to the concept that the combined effects of two or more nutrients working together have a greater physiological impact on the body than when each nutrient is consumed individually. While nutrition science traditionally focuses on isolating single nutrients to study their effects, it is recognized that nutrients interact in complex ways, and their combined consumption can lead to additive effects. Additionally, the Dietary Reference Intakes (DRIs) provide guidelines to prevent nutrient deficiencies and excessive intake but are not designed to assess the potential synergistic effects of consuming nutrients together. Even the term synergy is often applied in different manners depending on the scientific discipline. Considering these issues, the aim of this narrative review is to investigate the potential health benefits of consuming different nutrients and nutrient supplements in combination, a concept we define as nutrient synergy, which has gained considerable attention for its impact on overall well-being. We will examine how nutrient synergy affects major bodily systems, influencing systemic health. Additionally, we will address the challenges associated with promoting and conducting research on this topic, while proposing potential solutions to enhance the quality and quantity of scientific literature on nutrient synergy.

Diet-derived and diet-related endogenously produced palmitic acid: Effects on metabolic regulation and cardiovascular disease risk.

Palmitic acid is the predominant dietary saturated fatty acid (SFA) in the US diet. Plasma palmitic acid is derived from dietary fat and also endogenously from de novo lipogenesis (DNL) and lipolysis. DNL is affected by excess energy intake resulting in overweight and obesity, and the macronutrient profile of the diet. A low-fat diet (higher carbohydrate and/or protein) promotes palmitic acid synthesis in adipocytes and the liver. A high-fat diet is another source of palmitic acid that is taken up by adipose tissue, liver, heart and skeletal muscle via lipolytic mechanisms. Moreover, overweight/obesity and accompanying insulin resistance increase non-esterified fatty acid (NEFA) production. Palmitic acid may affect cardiovascular disease (CVD) risk via mechanisms beyond increasing low-density lipoprotein-cholesterol (LDL-C), notably synthesis of ceramides and possibly through branched fatty acid esters of hydroxy fatty acids (FAHFAs) from palmitic acid. Ceramides are positively associated with incident CVD, whereas the role of FAHFAs is uncertain. Given the new evidence about dietary regulation of palmitic acid metabolism there is interest in learning more about how diet modulates circulating palmitic acid concentrations and, hence, potentially CVD risk. This is important because of the heightened interest in low carbohydrate (carbohydrate controlled) and high carbohydrate (low-fat) diets coupled with the ongoing overweight/obesity epidemic, all of which can increase plasma palmitic acid levels by different mechanisms. Consequently, learning more about palmitic acid biochemistry, trafficking and how its metabolites affect CVD risk will inform future dietary guidance to further lower the burden of CVD.

Effects of Nut Consumption on Blood Lipids and Lipoproteins: A Comprehensive Literature Update.

In the present review, we provide a comprehensive narrative overview of the current knowledge on the effects of total and specific types of nut consumption (excluding nut oil) on blood lipids and lipoproteins. We identified a total of 19 systematic reviews and meta-analyses of randomized controlled trials (RCTs) that were available in PubMed from the inception date to November 2022. A consistent beneficial effect of most nuts, namely total nuts and tree nuts, including walnuts, almonds, cashews, peanuts, and pistachios, has been reported across meta-analyses in decreasing total cholesterol (mean difference, MD, -0.09 to -0.28 mmol/L), LDL-cholesterol (MD, -0.09 to -0.26 mmol/L), and triglycerides (MD, -0.05 to -0.17 mmol/L). However, no effects on HDL-cholesterol have been uncovered. Preliminary evidence indicates that adding nuts into the regular diet reduces blood levels of apolipoprotein B and improves HDL function. There is also evidence that nuts dose-dependently improve lipids and lipoproteins. Sex, age, or nut processing are not effect modifiers, while a lower BMI and higher baseline lipid concentrations enhance blood lipid/lipoprotein responses. While research is still emerging, the evidence thus far indicates that nut-enriched diets are associated with a reduced number of total LDL particles and small, dense LDL particles. In conclusion, evidence from clinical trials has shown that the consumption of total and specific nuts improves blood lipid profiles by multiple mechanisms. Future directions in this field should include more lipoprotein particle, apolipoprotein B, and HDL function studies.

The Dynamic Interplay of Healthy Lifestyle Behaviors for Cardiovascular Health.

PURPOSE OF REVIEW: The recent rise in cardiovascular disease (CVD) deaths in the USA has sparked interest in identifying and implementing effective strategies to reverse this trend. Healthy lifestyle behaviors (i.e., healthy diet, regular physical activity, achieve and maintain a healthy weight, avoid tobacco exposure, good quality sleep, avoiding and managing stress) are the cornerstone for CVD prevention. RECENT FINDINGS: Achieving all of these behaviors significantly benefits heart health; however, even small changes lower CVD risk. Moreover, there is interplay among healthy lifestyle behaviors where changing one may result in concomitant changes in another behavior. In contrast, the presence of one or more unhealthy lifestyle behaviors may attenuate changing another lifestyle behavior(s) (poor diet, inadequate physical activity, overweight/obesity, poor sleep quality, tobacco exposure, and poor stress management). It is important to assess all of these lifestyle behaviors with patients to plan an intervention program that is best positioned for adherence.

Peanuts as a nighttime snack enrich butyrate-producing bacteria compared to an isocaloric lower-fat higher-carbohydrate snack in adults with elevated fasting glucose: A randomized crossover trial.

BACKGROUND: Tree nuts have glucoregulatory effects and influence gut microbiota composition. The effect of peanuts on the microbiota has not been investigated. OBJECTIVES: The aim was to examine the effect of 28 g/d of peanuts for 6-wks, compared to an isocaloric lower-fat higher-carbohydrate (LFHC) snack, on gut microbiota composition. A secondary aim was to identify functional and active compositional differences in a subset of participants using metatranscriptomics. METHODS: In a randomized, crossover trial, 50 adults (48% female; 42 ± 15 y; BMI 28.3 ± 5.6 kg/m2; plasma glucose 100 ± 8 mg/dL) consumed 28 g/d of dry roasted, unsalted, peanuts (164 kcal; 11% E carbohydrate, 17% E protein, 73% E fat, and 2.4 g fiber) or a LFHC snack (164 kcal; 53% E carbohydrate, 17% E protein, 33% E fat, and 3 g fiber) for 6-wk (4-wk washout period). Gut bacterial composition was measured using 16S rRNA sequencing in the whole cohort. Exploratory metatranscriptomic analyses were conducted on a random subset (n = 24) of samples from the Peanut condition. RESULTS: No between-condition differences in α- or ß- diversity were observed. Following peanut intake, Ruminococcaceae were significantly more abundant [Linear discriminant analysis score (LDA) = 2.8; P = 0.027)] compared to LFHC. Metatranscriptomics showed increased expression of the K03518 (aerobic carbon-monoxide dehydrogenase small subunit) gene following peanut intake (LDA = 2.0; P = 0.004) and Roseburia intestinalis L1-82 was identified as a contributor to the increased expression. CONCLUSION: An increased abundance of Ruminococcaceae was observed following consumption of 28 g/d of peanuts in adults with elevated fasting glucose after 6-wks. Metatranscriptomics revealed increased expression of the K03518 gene. These results suggest peanut intake enriches a known butyrate producer and the increased expression of a gene implicated in butyrate production adds further support for peanut-induced gut microbiome modulation. NCT: 03654651.

Peanuts or an Isocaloric Lower Fat, Higher Carbohydrate Nighttime Snack Have Similar Effects on Fasting Glucose in Adults with Elevated Fasting Glucose Concentrations: a 6-Week Randomized Crossover Trial.

BACKGROUND: The glycemic effects of peanuts are not well studied and no trials have been conducted in adults with elevated fasting plasma glucose (FPG). Furthermore, intake of peanuts as a nighttime snack, an eating occasion affecting FPG, has not been examined. OBJECTIVES: The aim was to determine the effect of consuming 28 g/d of peanuts as a nighttime snack for 6 wk on glycemic control and cardiovascular disease risk factors, compared with an isocaloric lower fat, higher carbohydrate (LFHC) snack (whole grain crackers and low-fat cheese), in adults with elevated FPG. METHODS: In a randomized crossover trial, 50 adults (FPG 100 ± 8 mg/dL) consumed dry roasted, unsalted peanuts [164 kcal; 11% energy (E) carbohydrate, 17% E protein, and 73% E fat] or a LFHC snack (164 kcal; 54% E carbohydrate, 17% E protein, and 33% E fat) in the evening (after dinner and before bedtime) for 6 wk with a 4-wk washout period. Primary (FPG) and secondary end points [Healthy Eating Index-2015 (HEI-2015), weight, insulin, fructosamine, lipids/lipoproteins, central and peripheral blood pressure, and pulse wave velocity] were evaluated at the beginning and end of each condition. Linear mixed models were used for data analysis. RESULTS: FPG was not different between the peanut and LFHC conditions (end point mean difference: -0.6 mg/dL; 95% CI: -2.7, 1.6; P = 0.67). There were no between-condition effects for secondary cardiometabolic endpoints. The HEI-2015 score was not different between the conditions (3.6 points; P = 0.19), although the seafood/plant protein (2.0 points; P < 0.01) and added sugar (0.8 points; P = 0.04) components were improved following peanut intake. The whole grain component was lower with peanuts compared with LFHC (-2.6 points; P < 0.01). CONCLUSIONS: In adults with elevated FPG, peanuts as a nighttime snack (28 g/d) did not affect FPG compared with an isocaloric LFHC snack after 6 wk.This trial was registered at clinicaltrials.gov as NCT03654651.

Maximal Strength, Muscle Activation, and Bar Velocity Comparisons Between Squatting With a Traditional or Safety Squat Bar.

ABSTRACT: Vantrease, WC, Townsend, JR, Sapp, PA, Henry, RN, and Johnson, KD. Maximal strength, muscle activation, and bar velocity comparisons between squatting with a traditional or safety squat bar. J Strength Cond Res 35(2S): S1-S5, 2021-The purpose of this study was to compare strength, muscle activation, and bar velocity between the traditional (TRAD) and safety squat bar (SSB) back squat. Thirty-two men (21.94 ± 3.1 years, 1.78 ± 0.8 m, 81.7 ± 10.1 kg) volunteered to complete this randomized, crossover-design study. Subjects completed 2 separate 1 repetition maximum (1RM) sessions using either the TRAD or SSB. Subsequently, subjects completed 1 session of 3 repetitions at 65 and 85% of their 1RM for each squat condition (SSB & TRAD). Peak muscle activation of 7 muscles from the lower body and trunk was recorded through surface electromyography (EMG), and mean velocity (MV) was recorded by a linear transducer. Electromyography and MV were analyzed by a 2 × 2 (bar × load) repeated-measures analysis of variance. A Pearson correlation was used to determine the relationship of 1RM load between bars. Squat 1RM was significantly higher (p < 0.001; 11.6%) for TRAD (144.7 kg) compared with SSB (128.8 kg), and a strong correlation (r = 0.94) was observed between 1RM values of each bar. A significant main effect was seen in EMG (p < 0.001) and MV for load (p < 0.001). No significant bar × load interaction was observed between conditions for any EMG or bar velocity measure (p > 0.05). The SSB produces similar muscle activation and bar velocities compared with the TRAD at relative intensities. However, absolute loads should be adjusted when changing squat bars during a training cycle.

Plasma Amino Acid Response to Whey Protein Ingestion Following 28 Days of Probiotic (Bacillus subtilis DE111) Supplementation in Active Men and Women.

We sought to determine if 28 days of probiotic supplementation influenced the plasma amino acid (AA) response to acute whey protein feeding. METHODS: Twenty-two recreationally active men (n = 11; 24.3 ± 3.2 yrs; 89.3 ± 7.2 kg) and women (n = 11; 23.0 ± 2.8 yrs; 70.2 ± 15.2 kg) participated in this double-blind, placebo-controlled, randomized study. Before (PRE) and after 28 days of supplementation (POST), participants reported to the lab following a 10-hr fast and provided a resting blood draw (0 min), then subsequently consumed 25 g of whey protein. Blood samples were collected at 15-min intervals for 2 h post-consumption (15-120 min) and later analyzed for plasma leucine, branched-chain AA (BCAA), essential AA (EAA), and total AA (TAA). Participants received a probiotic (PROB) consisting of 1 x10-9 colony forming units (CFU) Bacillus subtilis DE111 (n = 11) or a maltodextrin placebo (PL) (n = 11) for 28 days. Plasma AA response and area under the curve (AUC) values were analyzed via repeated measures analysis of variance. RESULTS: Our analysis indicated no significant (p < 0.05) differential responses for plasma leucine, BCAA, EAA, or TAA between PROB and PL from PRE to POST. AUC analysis revealed no group × time interaction for plasma leucine (p = 0.524), BCAA (p = 0.345), EAA (p = 0.512), and TAA (p = 0.712). CONCLUSION: These data indicate that 28 days of Bacillus subtilis DE111 does not affect plasma AA appearance following acute whey protein ingestion.

Effects of Probiotic (Bacillus subtilis DE111) Supplementation on Immune Function, Hormonal Status, and Physical Performance in Division I Baseball Players.

We sought to determine the effects of probiotic supplementation (Bacillus subtilis DE111; 1 billion CFU∙d-1) on markers of immune and hormonal status in collegiate male athletes following 12 weeks of offseason training. Twenty-five Division I male baseball athletes (20.1 ± 1.5 years, 85.5 ± 10.5 kg, 184.7 ± 6.3 cm) participated in this double blind, placebo-controlled, randomized study. Participants were randomly assigned to a probiotic (PRO; n = 13) or placebo (PL; n = 12) group. Pre- and post-training, all athletes provided resting blood and saliva samples. Circulating concentrations of testosterone, cortisol, TNF-α, IL-10, and zonulin were examined in the blood, while salivary immunoglobulin A (SIgA) and SIgM were assayed as indicators of mucosal immunity. Separate analyses of covariance (ANCOVA) were performed on all measures collected post intervention. No differences in measures of body composition or physical performance were seen between groups. TNF-α concentrations were significantly (p = 0.024) lower in PRO compared to PL, while there were no significant group differences in any other biochemical markers examined. A main effect for time was observed (p < 0.05) for increased testosterone (p = 0.045), IL-10 (p = 0.048), SIgA rate (p = 0.031), and SIgM rate (p = 0.002) following offseason training. These data indicate that probiotic supplementation had no effect on body composition, performance, hormonal status, or gut permeability, while it may attenuate circulating TNF-α in athletes.