Background: Probiotic Bacillus coagulans GBI-30, 6086 (BC30) has been shown to increase protein digestion in an in vitro model of the stomach and small intestine. Once active in the small intestine after germination, BC30 aids the digestion of carbohydrates and proteins. The extent to which BC30 administration may impact protein digestion and amino acid appearance in humans after protein ingestion is currently unknown. This study examined the impact of adding BC30 to a 25-g dose of milk protein concentrate on post-prandial changes in blood amino acids concentrations. Methods: 14 males and 16 females (n = 30, 26.4 ± 6.5 years; 172.3 ± 10.8 cm; 78.2 ± 14.8 kg; 22.6 ± 7.2% fat) completed two supplementation protocols that each spanned two weeks separated by a washout period that lasted three weeks. Participants were instructed to track their dietary intake and ingest a daily 25-g dose of milk protein concentrate with (MPCBC30) or without (MPC) the addition of BC30. Body composition and demographics were assessed upon arrival to the laboratory. Upon ingestion of their final assigned supplemental dose, blood samples were taken at 0 (baseline), 30, 60, 90, 120, 180, and 240 min post-consumption and analyzed for amino acid concentrations. Results: Arginine (p = 0.03) and Isoleucine (p = 0.05) revealed greater area-under-the curve (AUC) in MPCBC30 group compared to MPC. In addition, Arginine (p = 0.02), Serine (p = 0.01), Ornithine (p = 0.02), Methionine (p = 0.04), Glutamic Acid (p = 0.01), Phenylalanine (p = 0.05), Isoleucine (p = 0.04), Tyrosine (p = 0.02), Essential Amino Acids (p = 0.02), and Total Amino Acids (p < 0.01) all revealed significantly greater concentration maximum (C_Max) in MPCBC30 compared to MPC. Finally, time to reach C_Max (T_Max) was significantly faster for Glutamine (p < 0.01), Citrulline (p < 0.01), Threonine (p = 0.04), Alanine (p = 0.02) in MPCBC30 when compared to MPC. Greater mean differences between groups for AUC and C_Max in women when compared to the mean differences in men were found for several amino acids. Conclusion: In concert with previous in vitro evidence of improved protein digestion and amino acid appearance, these results reveal that adding BC30 to protein sources such as milk protein concentrate can improve AUC, C_Max, and faster T_Max. Follow-up research should examine differences between gender and explore how aging can impact these outcomes. Retrospectively registered on June 11, 2020 at ClinicalTrials.gov as NCT04427020.

Aerobic exercise and thermal stress instigate robust challenges to the immune system. Various attempts to modify or supplement the diet have been proposed to bolster the immune system responses. The purpose of this study was to identify the impact of yeast beta-glucan (Saccharomyces cerevisiae) supplementation on exercise-induced muscle damage and inflammation. Healthy, active men (29.6 ± 6.7 years, 178.1 ± 7.2 cm, 83.2 ± 11.2 kg, 49.6 ± 5.1 mL/kg/min, n = 16) and women (30.1 ± 8.9 years, 165.6 ± 4.1 cm, 66.7 ± 10.0 kg, 38.7 ± 5.8 mL/kg/min, n = 15) were randomly assigned in a double-blind and cross-over fashion to supplement for 13 days with either 250 mg/day of yeast beta-glucan (YBG) or a maltodextrin placebo (PLA). Participants arrived fasted and completed a bout of treadmill exercise at 55% peak aerobic capacity (VO_2Peak) in a hot (37.2 ± 1.8 °C) and humid (45.2 ± 8.8%) environment. Prior to and 0, 2, and 72 h after completing exercise, changes in white blood cell counts, pro- and anti-inflammatory cytokines, markers of muscle damage, markers of muscle function, soreness, and profile of mood states (POMS) were assessed. In response to exercise and heat, both groups experienced significant increases in white blood cell counts, plasma creatine kinase and myoglobin, and soreness along with reductions in peak torque and total work with no between-group differences. Concentrations of serum pro-inflammatory cytokines in YBG were lower than PLA for macrophage inflammatory protein 1β (MIP-1β) (p = 0.044) and tended to be lower for interleukin 8 (IL-8) (p = 0.079), monocyte chemoattractment protein 1 (MCP-1) (p = 0.095), and tumor necrosis factor α (TNF-α) (p = 0.085). Paired samples t-tests using delta values between baseline and 72 h post-exercise revealed significant differences between groups for IL-8 (p = 0.044, 95% Confidence Interval (CI): (0.013, 0.938, d = −0.34), MCP-1 (p = 0.038, 95% CI: 0.087, 2.942, d = −0.33), and MIP-1β (p = 0.010, 95% CI: 0.13, 0.85, d = −0.33). POMS outcomes changed across time with anger scores in PLA exhibiting a sharper decline than YBG (p = 0.04). Vigor scores (p = 0.04) in YBG remained stable while scores in PLA were significantly reduced 72 h after exercise. In conclusion, a 13-day prophylactic period of supplementation with 250 mg of yeast-derived beta-glucans invoked favorable changes in cytokine markers of inflammation after completing a prolonged bout of heated treadmill exercise.

Berberine is a natural alkaloid used to improve glycemia but displays poor bioavailability and increased rates of gastrointestinal distress at higher doses. Recently, dihydroberberine has been developed to combat these challenges. This study was designed to determine the rate and extent to which berberine appeared in human plasma after oral ingestion of a 500 mg dose of berberine (B500) or 100 mg and 200 mg doses of dihydroberberine (D100 and D200). In a randomized, double-blind, crossover fashion, five males (26 ± 2.6 years; 184.2 ± 11.6 cm; 91.8 ± 10.1 kg; 17.1 ± 3.5% fat) completed a four-dose supplementation protocol of placebo (PLA), B500, D100, and D200. The day prior to their scheduled visit, participants ingested three separate doses with breakfast, lunch, and dinner. Participants fasted overnight (8–10 h) and consumed their fourth dose with a standardized test meal (30 g glucose solution, 3 slices white bread) after arrival. Venous blood samples were collected 0, 20, 40, 60, 90, and 120 minutes (min) after ingestion and analyzed for BBR, glucose, and insulin. Peak concentration (C_Max) and area under the curve (AUC) were calculated for all variables. Baseline berberine levels were different between groups (p = 0.006), with pairwise comparisons indicating that baseline levels of PLA and B500 were different than D100. Berberine C_Max tended to be different (p = 0.06) between all conditions. Specifically, the observed C_Max for D100 (3.76 ± 1.4 ng/mL) was different than PLA (0.22 ± 0.18 ng/mL, p = 0.005) and B500 (0.4 ± 0.17 ng/mL, p = 0.005). C_Max for D200 (12.0 ± 10.1 ng/mL) tended (p = 0.06) to be different than B500. No difference in C_Max was found between D100 and D200 (p = 0.11). Significant differences in berberine AUC were found between D100 (284.4 ± 115.9 ng/mL × 120 min) and PLA (20.2 ± 16.2 ng/mL × 120 min, p = 0.007) and between D100 and B500 (42.3 ± 17.6 ng/mL × 120 min, p = 0.04). Significant differences in D100 BBR AUC (284.4 ± 115.9 ng/mL×120 min) were found between PLA (20.2 ± 16.2 ng/mL × 120 min, p = 0.042) and B500 (42.3 ± 17.6 ng/mL × 120 min, p = 0.045). Berberine AUC values between D100 and D200 tended (p = 0.073) to be different. No significant differences in the levels of glucose (p = 0.97) and insulin (p = 0.24) were observed across the study protocol. These results provide preliminary evidence that four doses of a 100 mg dose of dihydroberberine and 200 mg dose of dihydroberberine produce significantly greater concentrations of plasma berberine across of two-hour measurement window when compared to a 500 mg dose of berberine or a placebo. The lack of observed changes in glucose and insulin were likely due to the short duration of supplementation and insulin responsive nature of study participants. Follow-up efficacy studies on glucose and insulin changes should be completed to assess the impact of berberine and dihydroberberine supplementation in overweight, glucose intolerant populations.

The objective of the study was to examine the impact of a multi-strain probiotic (MSP) on sleep, physical activity, and body composition changes. We used a randomised, double-blind, placebo-controlled approach with 70 healthy men and women (31.0 ± 9.5 years, 173.0 ± 10.4 cm, 73.9 ± 13.8 kg, 24.6 ± 3.5 kg/m²) supplemented daily with MSP (4 × 10⁹ live cells Limosilactobacillus fermentum LF16, Lacticaseibacillus rhamnosus LR06, Lactiplantibacillus plantarum LP01, and Bifidobacterium longum 04; Probiotical S.p.A., Novara, Italy) or placebo (PLA). In response to supplementation (after 0, 2, 4, and 6 weeks of supplementation) and 3 weeks after stopping supplementation, participants had subjective (Pittsburgh Sleep Quality Index, PSQI) and objective sleep indicators, body composition, daily physical activity and resting hemodynamics assessed. Subjective sleep quality indicators using the PSQI (sleep latency, sleep disturbance, and global PSQI score) improved () at various time points with MSP supplementation. Systolic blood pressure in PLA increased () after 6 weeks of supplementation with no change in MSP. No changes () in sleep (hours asleep, minutes awake, number of times awake) or physical activity (step count, minutes of sedentary activity, total active minutes) metrics assessed by the wearable device were observed. Additionally, no changes in resting heart rate, diastolic blood pressure, and body composition were discerned. In conclusion, MSP supplementation improved the subjective ability to fall asleep faster and disturbances experienced during sleep, which resulted in improved overall sleep quality as assessed by the PSQI. No differences in other sleep indicators, physical activity, hemodynamics, and body composition were observed during or following MSP supplementation. Registered at clinicaltrials.gov: NCT05343533

Large (48-g), isonitrogenous doses of rice and whey protein have previously been shown to stimulate similar adaptations to resistance training, but the impact of consuming smaller doses has yet to ...

Currier, BS, Harty, PS, Zabriskie, HA, Stecker, RA, Moon, JM, Jagim, AR, and Kerksick, CM. Fat-free mass index in a diverse sample of male collegiate athletes. J Strength Cond Res 33(6): 1474–1479, 2019—Fat-free mass index (FFMI) is a body composition metric that has been used to assess relative muscularity in athletes. Fat-free mass index is calculated by dividing FFM by height squared, although further height corrections through linear regression may be needed in taller individuals. This study reported height-adjusted FFMI (FFMI_Adj) data in 209 male collegiate athletes from 10 sports (baseball, cross country, football, golf, ice hockey, weightlifting, rugby, swimming, track and field, and water polo) and the FFMI_Adj natural upper limit for sports with sufficient sample size. The body composition of all subjects (mean ± SD; age: 20.7 ± 1.9 years, height: 182.9 ± 6.7 cm, body mass: 90.8 ± 16.8 kg, and percent body fat: 15.6 ± 5.3) was measured using dual-energy x-ray absorptiometry. Linear regression was used to adjust for height, and the FFMI_Adj natural upper limit was determined by calculating the 97.5th percentile of all values. One-way analyses of variance with Games-Howell post hoc comparisons were used to determine between-sport differences. A paired-samples t-test revealed a significant difference (p < 0.001) between unadjusted and adjusted mean FFMI values. The overall mean FFMI_Adj was 22.8 ± 2.8 kg·m⁻². Significant between-sport differences (p < 0.001) in FFMI_Adj were identified. Average FFMI_Adj was highest in football athletes (24.28 ± 2.39 kg·m⁻²) and lowest in water polo athletes (20.68 ± 3.56 kg·m⁻²). The FFMI_Adj upper limit was calculated for all athletes (28.32 kg·m⁻²), rugby (29.1 kg·m⁻²), and baseball (25.5 kg·m⁻²). This study reported FFMI_Adj values in a diverse cohort of male collegiate athletes, providing data for the first time in several sports. These values can be used to guide nutritional and exercise interventions, predict athletic performance, and provide coaches with standardized information regarding the potential for further FFM accretion in male athletes.