The Effects of Bifidobacterium Infantis 35624 on Inflammatory Markers and Exercise Performance in Collegiate Female Swimmers

The purpose of this study was to determine the effects Bifidobacterium infantis 35624 (B. infantis35624) has on exercise performance, inflammation/immune function, and cognitive outlook during a six week exercise training phase in collegiate female swimmers. Using a two-group matched, double-blind, placebo-controlled design, seventeen NCAA Division 1 female swimmers were assigned to either group and supplemented daily for six weeks a 1 x 109 CFU dosage of B. infantis35624 (n=8) or placebo (n=9). Both groups underwent an intensive six week swim and resistance training program. Exercise testing (aerobic/anaerobic swim time trials and force plate vertical jump) as well as serum and salivary samples (cytokine and gastrointestinal (GI) inflammatory and immune markers) were collected pre, mid (week 3), and post (week 6). Recovery-stress questionnaire for athletes (RESTQ-Sport) was administered at baseline and at the end of each training week. Study data was analyzed by Analysis of Covariance (ANCOVA) by time point design with the respective baseline values of each dependent variable being the covariate. The B. infantis35624 group had a significant reduction in the anti-inflammatory marker IL-1ra (p = 0.029, ηp2 = .296) and a noted statistical trend for a decrease in salivary IgA (p = 0.060, ηp2 = .231) in comparison to placebo at mid-point. The B. infantis35624 group had significantly higher RESTQ-sport values in the sport recovery than the placebo group. B. infantis35624 in Division 1 female swimmers does not directly influence exercise performance, but did influence markers of inflammation/immune function as well as cognitive outlook during six weeks of exercise training

Intrinsic Anthropometric Factors Associated with Bone Stress Injuries in Collegiate Runners: New Risk Metrics & Novel Field Screening Tools

Lower extremity bone stress injuries (BSI) (i.e. pelvis, femur, tibia) are common in distance running athletes relative to other sports. PURPOSE: To (1) characterize bone mineral density (BMD), body composition (BComp, DXA), and anthropometric parameters in D1A collegiate runners presenting with and without BSIs during a collegiate season and (2) develop BMD prediction models with an accompanying mobile application for novel noninvasive field prediction of BMD and BSI risk. METHODS: Distance runners (n = 79; 42♂, 37♀) from a single university track and field team were retrospectively enrolled into study. The runners completed a DXA scan during fall screening (August-November). Three months after scanning, medical records were reviewed for the occurrence of BSI confirmed by a licensed physician. A t-test was used to compare BMD (total and regional [spine, pelvis, and legs]), BComp (% body fat, fat mass, and lean mass), and anthropometric measurements (shoulder width and leg, arm, and trunk length) between runners with versus without BSI (included subgroup analysis by sex). Multiple linear regression with stepwise removal was used to determine variables most predictive of BMD. Xcode (Apple Inc.) was used to develop the mobile application based on the derived BMD prediction models utilizing lower-bound 95% confidence intervals for runner-specific BMD norms as risk cutoffs. RESULTS: Eighteen runners (22.8%; 11♀, 7♂) sustained a lower limb BSI. Compared to the noninjured group (NoBSI), injured runners (BSI) had lower total BMD (NoBSI: 1.24 0.02, BSI: 1.15 0.04, p\u3c0.001) and regional BMD (spine -11%, legs -9%, pelvis -10%, p\u3c0.001). Injured athletes were observed to have shorter leg length (NoBSI: 95.6 1.4cm, BSI: 91.9 2.6cm, p=0.015) and arm length (NoBSI: 56.1 0.8, BSI: 53.8 1.5, p=0.006). Injured males had lower fat mass (NoBSI: 7.7 0.5kg, BSI: 6.4 0.7cm, p=0.041) and injured females had lower leg lean mass (NoBSI: 14.7 0.6kg, BSI: 13.5 0.7kg, p=0.035). BComp and anthropometric measures were predictive of bone mass (p\u3c0.05, R2 =0.61; SE= ±0.27kg) and BMD (Total: p\u3c0.05, R2 =0.77; SE= ±0.05g/cm2). BONE MASS, kg = (0.046 x Ageyears) +(0.024 x Weightkg) +(0.014 x %BodyFat) +(-0.017 x Arm Lengthcm) +(0.017 x Shoulder Widthcm) +(-0.009 x Trunk Lengthcm) +(0.037 x Leg Lengthcm) -2.867] | BMD, g cm2 =(-0.011 x %BodyFat) + (0.016 x Fat Mass kg) + (0.203 x Bone Masskg) +(-0.003 x Leg Lengthcm) +1.023. The mobile application was able to successfully run the developed prediction models for BMD assessment. CONCLUSION: Collegiate distance runners with shorter limb lengths, reduced fat mass(♂), reduced leg lean mass(♀), and lower BMD are at an increased risk for a lower extremity BSI. BComp and anthropometric measures are predictive of BMD in this population and may be utilized with the mobile application developed here as a screening tool to identify potentially “at-risk” runners

Anthropometric Factors Associated With Bone Stress Injuries in Collegiate Distance Runners: New Risk Metrics and Screening Tools?

Background: Lower limb bone stress injury (BSI) of the pelvis, femur, and tibia is prevalent in collegiate track and field distance runners. Bone mineral density (BMD), body composition (BComp), and anthropometric parameters before initial collegiate injury have not been compared between runners with BSI and their noninjured counterparts. Purpose: To characterize bone health in relation to BComp and anthropometric measurements from total-body dual x-ray absorptiometry (DXA) scans in collegiate male and female distance runners before BSI and develop BMD prediction models. Study Design: Case-control study; Level of evidence, 3. Methods: Distance runners (N = 79) from a single university track and field team were retrospectively enrolled into this study. The runners completed a DXA scan during the fall season (August-November) and participated in sport activities before the scan. Three months after scanning, electronic medical records were reviewed for the occurrence of BSI. An independent-sample t test was used to compare BMD (total and regional [spine, pelvis, and legs]), BComp (% body fat, fat mass, and lean mass), and anthropometric measurements (shoulder width and leg, arm, and trunk length) between runners with versus without BSI (included subgroup analysis by sex). Multiple linear regression with stepwise removal was used to determine variables most predictive of BMD. Results: Of the 79 enrolled participants (42 male, 37 female), 18 runners (22.8%; 11 female, 7 male) sustained a lower limb BSI. Compared with the noninjured group, injured runners had lower total and regional BMD (P < .001 for all) and shorter leg and arm lengths (P < .05 for both), whereas injured male runners had lower fat mass and injured female runners had lower lean mass in the legs (P < .05 for both). Injured runners’ age-matched total BMD Z score (-0.1 ± 0.6) was considered clinically normal. BComp and anthropometric measures were predictive of total and regional BMD (P < .05; R 2 = 0.64-0.80; percentage error = 3.8%-4.8%). Conclusion: The DXA scans of injured runners prior to incidence indicated lower BMD compared with noninjured runners. Shorter limb lengths, lower fat mass (male), and lower leg lean mass (female) may also be indicative of risk. Certain BComp and anthropometric measures were predictive of BMD

Sport Specificity and Training Influence Bone and Body Composition In Women Collegiate Athletes

Sport Specificity and Training Influence Bone and Body Composition In Women Collegiate Athletes Jennifer M. Markos†, Aaron F. Carbuhn†, Tara E. Fernandez‡, Amy F. Bragg‡, John S. Green‡, FACSM, and Stephen F. Crouse‡, FACSM. Department of Health and Kinesiology and Department of Athletics, Texas A&M University, College Station, TX 77843, (Sponsor: S.F. Crouse) This is a novel descriptive study to characterize off-season, pre-season, and post-season bone and body composition measures in women collegiate athletes. PURPOSE: To quantify changes in women collegiate athletes’ bone mineral content, bone mineral density (BMD), arm BMD, leg BMD, pelvis BMD, spine BMD, and body composition (i.e., total body mass, lean mass, fat mass, and percent body fat) within each sport through the seasonal periods, and among the sports at each seasonal period. METHODS: 67 women collegiate athletes from softball (n = 17), basketball (n = 10), volleyball (n = 7), swimming (n = 16), and track jumpers and sprinters (n = 17) were scanned using duel energy x-ray absorptiometry (DXA) at three seasonal periods: 1) before pre-season training defined as off-season (OFF), 2) at end of preseason training (PRE), and 3) after the competitive season (POST). Summary of RESULTS: Repeated measures ANOVA within-sport seasonal changes in table; PRE/POST = highest value measured at PRE or POST. α \u3c 0.05 for all tests of significance. Seasonal Period %Body fat BMD (g/cm2) Pelvis BMD (g/cm2) Spine BMD (g/cm2) Softball OFF 27.1±5.0* 1.254±0.081* 1.385±0.127 1.216±0.149 PRE/POST 25.7±5.0 1.261±0.082 1.405±0.141 1.268±0.154 Basketball OFF 25.5±5.5* 1.333±0.064* 1.469±0.123* 1.356±0.178 PRE/POST 22.7±5.6 1.349±0.055 1.494±0.119 1.391±0.146 Volleyball OFF 27.7±4.1 1.284±0.065* 1.366±0.139 1.254±0.102* PRE/POST 27.1±5.1 1.310±0.071 1.371±0.149 1.360±0.121 Swimming OFF 22.0±4.3 1.112±0.067 1.110±0.104* 1.063±0.127* PRE/POST 21.9±4.1 1.121±0.067 1.124±0.105 1.105±0.126 Track Jumpers and Sprinters OFF 15.4±4.6* 1.292±0.075* 1.432±0.124* 1.280±0.135* PRE/POST 14.3±3.9 1.307±0.080 1.470±0.128 1.337±0.140 Values are means ± standard deviations. *Significant difference between off-season and pre or post-season ANOVA for differences by sports at the PRE/POST period showed results for both pelvis BMD and spine BMD as follows: softball = basketball = volleyball = track \u3e swimmers. CONCLUSION: These data serve as sport-specific benchmarks for comparisons at in-season and off-season training periods among women collegiate athletes in various sports. They also serve to document changes in body composition and bone density with training, and may serve to guide coaches in the development of sport specific nutritional and strength and conditioning programs to optimize athletic performance. Research supported in part by the Sydney & J.L. Huffines Institute for Sports Medicine and Human Performanc

Prediction of the Total Energy Cost of an Acute Bout of Resistance Exercise in Young Men and Women

Prediction of the Total Energy Cost of an Acute Bout of Resistance Exercise in Young Men and Women Brad S. Lambert†, Steven E. Martin‡, John S. Green‡ (FACSM), Aaron F. Carbuhn†, Stephen F. Crouse‡ (FACSM). Department of Health and Kinesiology, Texas A&M University, College Station, TX (Sponsor S.F. Crouse) ACSM currently recommends resistance training (RT) for each major muscle group at least 2 times per week with a traditional repetition range of 8-12 per set. Because many investigators as well as fitness professionals consider kcal expenditure when creating training protocols, energy costs during both RT and aerobic training must be considered. PURPOSE: To develop a regression equation to predict kcal expenditure for a RT bout involving each major muscle group using VO2max, height, weight, lean body mass, fat mass, and total exercise volume (TV=sets*reps*wt) as independent variables. METHODS: Twelve subjects (7 men, 5 women, age 21-25 yrs) were tested using the standard Bruce treadmill protocol for VO2max, and strength tested to determine their 3-5 repetition max (RM) on Keiser® RT equipment 1 week prior to their experimental RT bout. Body composition was assessed using DEXA. For their experimental RT bout, a warm-up set followed by 2-3 sets of 8-12 reps at 60-70% predicted 1RM were performed for each exercise. Each set was started every two minutes. Exercises progressed in the following order: leg press, chest press, leg curl, lat pull, leg ext., triceps ext., biceps curl. Oxygen consumption was measured continuously throughout the RT bout using an automated metabolic cart. Multiple Linear Regression was used to determine the best model for prediction of kcal consumption. Results: Mean kcal expenditure for the entire RT bout was 221.8±20.65 kcal (men = 272±36 & women = 150±16) with a mean kcal cost of 26.32-38.94 per exercise. Large muscle group/multi-joint exercises had the highest total kcal expenditures as expected. Collinearity diagnostics from the regression revealed that VO2max (L/min) and the square root of TV (TV0.5) were the only predictors needed in the model with all other variables being highly intercorrellated with VO2max (L/min), thus not adding significant improvement to the model. The prediction equation was (p\u3c0.05, R2=0.86): Total kcal = (37.264*VO2max L/min) + (1.087*TV0.5) – 132.488 CONCLUSIONS: VO2max (L/min) and TV0.5 were found to be significant predictors of the energy cost of a RT bout involving each major muscle group. In regards to fitness, performance, and weight management, this equation may aid practitioners and young exercising adults in documenting kcal expenditure from resistance training

Effects of Probiotic (Bifidobacterium longum 35624) Supplementation on Exercise Performance, Immune Modulation, and Cognitive Outlook in Division I Female Swimmers

This work is licensed under a Creative Commons Attribution 4.0 International License.Our aim was to determine the effects of probiotic supplementation (Bifidobacterium longum 35624; 1 billion CFU·d−1) on exercise performance, immune modulation, and cognitive outlook in collegiate female athletes during six weeks of offseason training. Seventeen National Collegiate Athletic Association (NCAA) Division 1 collegiate female swimmers participated in this two-group matched, double-blind, placebo controlled design. Via stratified randomization, participants were assigned to probiotic (B. longum 35624; n = 8) or placebo (n = 9) groups. Pre, mid, and post-training, all participants completed exercise performance testing (aerobic/anaerobic swim time trials and force plate vertical jump) as well as provided serum (cytokine and gastrointestinal inflammatory markers) and salivary immunoglobulin A samples. Recovery-stress questionnaire for athletes (RESTQ-Sport) was administered at baseline and conclusion of each week. Data were analyzed by analysis of covariance (ANCOVA) by time point with the respective baseline values of each dependent variable being the covariate. No significant differences in exercise performance and biochemical markers were observed between groups following offseason training. Recovery-Stress Questionnaire for Athletes (RESTQ-sport) values in B. longum 35624 group had significantly higher (i.e., more desired; p < 0.05) values in sport recovery (weeks five and six) than placebo. Probiotic supplementation in collegiate female swimmers did not affect exercise performance or immune function throughout offseason training, but did indicate alterations in cognitive outlook.Procter & Gamble, Cincinnati, OH, USA gran

International Society of Sports Nutrition Position Stand: Probiotics.

Position statement: The International Society of Sports Nutrition (ISSN) provides an objective and critical review of the mechanisms and use of probiotic supplementation to optimize the health, performance, and recovery of athletes. Based on the current available literature, the conclusions of the ISSN are as follows: 1)Probiotics are live microorganisms that, when administered in adequate amounts, confer a health benefit on the host (FAO/WHO).2)Probiotic administration has been linked to a multitude of health benefits, with gut and immune health being the most researched applications.3)Despite the existence of shared, core mechanisms for probiotic function, health benefits of probiotics are strain- and dose-dependent.4)Athletes have varying gut microbiota compositions that appear to reflect the activity level of the host in comparison to sedentary people, with the differences linked primarily to the volume of exercise and amount of protein consumption. Whether differences in gut microbiota composition affect probiotic efficacy is unknown.5)The main function of the gut is to digest food and absorb nutrients. In athletic populations, certain probiotics strains can increase absorption of key nutrients such as amino acids from protein, and affect the pharmacology and physiological properties of multiple food components.6)Immune depression in athletes worsens with excessive training load, psychological stress, disturbed sleep, and environmental extremes, all of which can contribute to an increased risk of respiratory tract infections. In certain situations, including exposure to crowds, foreign travel and poor hygiene at home, and training or competition venues, athletes' exposure to pathogens may be elevated leading to increased rates of infections. Approximately 70% of the immune system is located in the gut and probiotic supplementation has been shown to promote a healthy immune response. In an athletic population, specific probiotic strains can reduce the number of episodes, severity and duration of upper respiratory tract infections.7)Intense, prolonged exercise, especially in the heat, has been shown to increase gut permeability which potentially can result in systemic toxemia. Specific probiotic strains can improve the integrity of the gut-barrier function in athletes.8)Administration of selected anti-inflammatory probiotic strains have been linked to improved recovery from muscle-damaging exercise.9)The minimal effective dose and method of administration (potency per serving, single vs. split dose, delivery form) of a specific probiotic strain depends on validation studies for this particular strain. Products that contain probiotics must include the genus, species, and strain of each live microorganism on its label as well as the total estimated quantity of each probiotic strain at the end of the product's shelf life, as measured by colony forming units (CFU) or live cells.10)Preclinical and early human research has shown potential probiotic benefits relevant to an athletic population that include improved body composition and lean body mass, normalizing age-related declines in testosterone levels, reductions in cortisol levels indicating improved responses to a physical or mental stressor, reduction of exercise-induced lactate, and increased neurotransmitter synthesis, cognition and mood. However, these potential benefits require validation in more rigorous human studies and in an athletic population

Effects of Probiotic (Bifidobacterium longum 35624) Supplementation on Exercise Performance, Immune Modulation, and Cognitive Outlook in Division I Female Swimmers

Our aim was to determine the effects of probiotic supplementation (Bifidobacterium longum 35624; 1 billion CFU&middot;d&minus;1) on exercise performance, immune modulation, and cognitive outlook in collegiate female athletes during six weeks of offseason training. Seventeen National Collegiate Athletic Association (NCAA) Division 1 collegiate female swimmers participated in this two-group matched, double-blind, placebo controlled design. Via stratified randomization, participants were assigned to probiotic (B. longum 35624; n = 8) or placebo (n = 9) groups. Pre, mid, and post-training, all participants completed exercise performance testing (aerobic/anaerobic swim time trials and force plate vertical jump) as well as provided serum (cytokine and gastrointestinal inflammatory markers) and salivary immunoglobulin A samples. Recovery-stress questionnaire for athletes (RESTQ-Sport) was administered at baseline and conclusion of each week. Data were analyzed by analysis of covariance (ANCOVA) by time point with the respective baseline values of each dependent variable being the covariate. No significant differences in exercise performance and biochemical markers were observed between groups following offseason training. Recovery-Stress Questionnaire for Athletes (RESTQ-sport) values in B. longum 35624 group had significantly higher (i.e., more desired; p &lt; 0.05) values in sport recovery (weeks five and six) than placebo. Probiotic supplementation in collegiate female swimmers did not affect exercise performance or immune function throughout offseason training, but did indicate alterations in cognitive outlook