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(19) EFFECTS OF KNEE WRAPS ON IMMUNE CELL MOBILIZATION FOLLOWING RESISTANCE EXERCISE DESIGNED TO INDUCE MUSCLE DAMAGE

Emily C. Tagesen – Graduate Assistant , Kent State University

Joseph A. Laudato, MS, CSCS – Graduate Student, Kent State University

Brandon M. Gibson, MS – Graduate Student, Kent State University

Cody S. Dulaney

Cardyl P. P. Trionfante – Visiting Assistant Professor, Miami University

Adam R. Jajtner


Prior studies utilizing knee wraps (KWs) while performing a back squat have demonstrated a mechanical advantage that increases exercise volume and load. PURPOSE: To determine if knee wraps modify the immune response to resistance exercise. METHODS: 9 resistance trained men (22.6±3.6 yrs; 177.1±5.4cm; 83.2±17.3 kg) were recruited to participate in either a KW or control (CON) condition. During visit 1, participants performed a 1-repetition max (1-RM) and were required to attain a 1-RM between 1.5x-3.0x their body weight.  Participants then returned to the Exercise Performance and Recovery Lab for visit 2 at least 72 hours later, having fasted at least 10 hours, abstained from caffeine for 16 hours, nicotine and alcohol for at least 24 hours, and exercise for 72 hours. During this visit, participants completed a 5-minute warm up on a cycle ergometer at a self-selected pace before completing eight sets of ten repetitions of the squat at 70% of their 1-RM, with 2 minutes rest between sets.  Blood samples were obtained prior to exercise (PRE), immediately after (IP), 1-(1H), 24-(24H) and 48-(48H) hours after exercise.  Blood was immediately analyzed for total leukocyte count (WBC), as well as the number (#) and ratio (%) of lymphocytes (LY), monocytes (MO), and granulocytes (GR) using an automated hematology analyzer. Differences between conditions were analyzed using a Mann-Whitney U test, while differences across time were assessed with a Friedman’s ANOVA, and post-hoc analysis with a Wilcoxon rank sum test. RESULTS: Friedman’s ANOVA demonstrated differences (p=0.005) in the KW group for WBC, with increases observed from PRE (5.74±1.41x103·µL-1) to IP (9.73±1.15x103·µL-1; p=0.043), with no differences at 1H (5.41±1.04x103·µL-1), 24H (5.17±1.13x103·µL-1), or 48H (5.12±1.07x103·µL-1). Friedman’s ANOVA also indicated differences (p=0.004) in the KW group for LY%, with increases from PRE (34.7±3.8%) at IP (40.9±4.48%; p=0.043) and a decrease at 1H (22.6 ±3.1%; p=0.043). Friedman’s ANOVA revealed differences (p=0.002) for the KW group in LY#, with an increase (p=0.043) from PRE (1.96±0.39 x103·µL-1) at IP (3.97±0.597 x103·µL-1).  Friedman’s ANOVA indicated differences (p=0.015) in the KW group for MO#, with increases (p=0.043 ) at IP (0.67±0.17 x103·µL-1) compared to PRE (0.38±0.102 x103·µL-1), 1H (0.25±0.12 x103·µL-1), 24H (0.30±0.11 x103·µL-1) and 48H (0.32±0.08 x103·µL-1). Additionally, at IP, MO# were greater in KW (0.67±0.17x103·µL-1; p=0.036) versus CON (0.59± 0.13x103·µL-1). Friedman’s ANOVA demonstrated differences (p=0.004) in the KW group for GR% with increases (p=0.043 ) from PRE (58.1±5.1%) and IP (52.4±5.1%) at 1H (73.2 ±3.8%). Friedman’s ANOVA demonstrated differences (p=0.003) in the KW group for GR# with increases (p< 0.05) at IP (5.11±0.87x103·µL-1) compared to PRE (3.37±1.10 x103·µL-1), 1H(3.95±0.77 x103·µL-1), 24H(3.05±0.67 x103·µL-1) and 48H(2.79±0.60 x103·µL-1). CONCLUSION: A significant increase in circulating WBCs suggest KWs may increase the immune response possibly due to increased exercise volume.  Additionally, the monocyte response to exercise with KW may be enhanced, especially immediately after exercise. PRACTICAL APPLICATIONS: KWs appear to increase the immune response to resistance exercise, which may increase post-exercise inflammation.  Therefore, further research is necessary to determine if the use of KWs is beneficial to the athletes.

 



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(20) COMPARISON OF LYMPHOCYTE SUBSET RESPONSES TO HIGH-INTENSITY INTERVAL TRAINING, SPRINT INTERVAL TRAINING, AND MODERATE-INTENSITY CONTINUOUS TRAINING

Eliott Arroyo, MS – PhD Candidate, Kent State University

Emily C. Tagesen – Graduate Assistant , Kent State University

Tricia L. Hart, CSCS – n/a, n/a

Brandon A. Miller, CSCS – Graduate Student, Kent State University

Adam R. Jajtner


PURPOSE: To compare the effects of high-intensity interval training (HIIT), sprint interval training (SIT), and moderate-intensity continuous training (MCT) on lymphocyte subset populations. METHODS: Recreationally active men (n=3; 21.3±3.5 yrs; 182.8±6.3 cm; 79.4±8.7; 11.2±5.8 %BF; 44.1±3.2 ml·kg-1·min-1) completed a maximal graded exercise test (VO2max) and three exercise trials (HIIT, SIT, and MCT) in a randomized, counterbalanced fashion on a cycle ergometer. HIIT consisted of fifteen 90-second bouts at 85% VO2max interspersed with 90-second active recovery periods. SIT consisted of fifteen 20-second bouts at 130% maximum wattage interspersed with 160-second active recovery periods. MCT was a continuous bout at 65% VO2max. Each trial lasted 53 minutes, including a 5-minute warm-up and a 3-minute cool-down. Blood was collected before (PRE), immediately post (IP), 30 minutes (30P), 2 hours (2H), 6 hours (6H) and 24 hours (24H) post-exercise. The number and percentage of lymphocyte subsets (CD3+CD4+, CD3+CD8+, CD3CD56brightCD16-, CD3CD56dimCD16+, and CD3−CD19+) were analyzed via flow cytometry. Total lymphocyte count was analyzed via hematology analyzer. Changes were assessed using a two factor (time × trial) within-subjects repeated measures ANOVA. RESULTS: A significant time × trial interaction was observed for CD3+CD4+ percentage (F=2.989, p=0.018) and count (F=2.653, p=0.030). CD3+CD4+ count decreased from PRE to 24H in both MCT (p=0.007) and SIT (p=0.030), but not HIIT (p > 0.05). During HIIT, CD3+CD4+ count was increased from PRE to IP (p=0.008). A significant time × trial interaction was observed for CD3+CD8+ (F=4.909, p=0.001) and CD3-CD19+ counts (F=2.536, p=0.037). CD3+CD8+ count was elevated at 6H compared to 2H in both MCT (p=0.016) and HIIT (p=0.032), but not SIT. For HIIT, CD3-CD19+ count was greater at IP relative to PRE (p=0.019), 30P (p=0.033), and 24H (p=0.041). A significant time × trial interaction was observed for CD3-CD56brightCD16- count (F=6.010, p< 0.001). At IP, CD3-CD56brightCD16- count was greater for HIIT compared to MCT (p=0.017) and SIT (p=0.013).  A significant time × trial interaction was observed CD3-CD56dimCD16+ percentage (F=4.206, p=0.003) and count (F=3.203, p=0.013). For SIT, CD3-CD56dimCD16+ count was lower at 2H compared to PRE (p=0.047). CONCLUSION: Data suggest that both SIT and MCT, but not HIIT, elicited a decline in CD3+CD4+ count 24 h following exercise. HIIT and MCT triggered a significant increase in CD3+CD8+ count at 6H that was not observed following SIT. CD3-CD19+ count was elevated at IP following HIIT, but not following SIT or MCT. CD3-CD56brightCD16- count was significantly greater immediately after HIIT compared to SIT and MCT. CD3-CD56dimCD16+ count declined 2 h following SIT but not following HIIT or MCT. PRACTICAL APPLICATIONS: The results of this study suggest that, despite identical duration, HIIT, SIT, and MCT elicit dissimilar immune responses. T helper cells (CD3+CD4+), which play an important role in immune function, appear to be suppressed following SIT and MCT, but not HIIT. Cytotoxic NK cells (CD3-CD56dimCD16+) were depleted 2 h following SIT, but not following HIIT or MCT, indicating potential susceptibility to infection following SIT. Further research is needed to determine the practical effects of varying exercise intensities on immune function.

 



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(21) DOES SWEAT COLLECTION METHOD INFLUENCE ASSESSMENT OF ELECTROLYTE CONCENTRATION?

Nic Shea, MA, CSCS – PhD Candidate, Georgia Institute of Technology

Gyumin Kang – PhD Student, Georgia Institute of Technology

Michael Jones – Research Scientist, Georgia Institute of Technology

Mindy Millard-Stafford – Professor, Georgia Institute of Technology


Sweat rate and electrolyte concentration can widely vary across individuals; thus, these measures may inform practitioners regarding nutritional requirements and acclimatization status of athletes.  PURPOSE: To determine the impact of using different methods for sweat acquisition (by region and modality) on sweat electrolyte concentration. METHODS: Thirteen physically-active males (age: 22.4 ± 3.5, height 178.0 ± 6.1 cm, body mass: 69.9 ± 6.6 kg) participated after a standardized dinner and an overnight fast.  Sweat was acquired via Tegaderm absorbent patch on the left scapula (SCAP-Patch), left forearm (ARM-Patch), and Opsite dressing/parafilm pouch (Brisson method) on the right scapula (SCAP-Pouch) after ~1 h of exercise in the heat (38oC, 30% RH). Sweat was obtained from the beginning of exercise until patches were visibly saturated and pouch contained sufficient sample volume. Sweat was analyzed for sodium [Na+] and potassium [K+] via LAQUAtwin Na-11 and LAQUAtwin K-11. RESULTS: There was a significant effect for sweat acquisition method on Na+ (P=0.002) and K+ (P< 0.001).  CAP-Pouch had higher [Na+] by 16.9% compared to SCAP-Patch (83.1 ± 25.3 > 71.0 ± 18.2 mmol/L; P=0.010); however, this regional measure was highly correlated (r=0.861; P< 0.001) despite a different acquisition technique.  A similar finding was observed for [K+].  SCAP-Pouch had higher [K+] by 18.4% compared to SCAP-Patch (4.5 ± 0.6 > 3.8 ± 0.7 mmol/L; P=0.009) but was significantly correlated (r=0.815; P=0.001). Sodium differences across regions were not different for SCAP-Patch and ARM-Patch (71.0 ± 18.3 vs. 61.9 ± 21.6 mmol/L; P=0.084), but were highly correlated (r=0.795, P=0.001).  Regional differences were only observed for [K+].  Ard greater [K+] compared to SCAP-Patch 5.4 ± 1.2 > 3.8 ± 0.7 mmol/L; P=0.002) but was significantly correlated (r=0.734, P=0.024). CONCLUSIONS: Sweat electrolyte concentration may differ both by region and the acquisition method used in sample collection. The use of absorbent patches resulted in consistently lower electrolyte values for both [Na+]and [K+] compared to a custom-made pouch in the same region (i.e., scapula).  PRACTICAL APPLICATION:  Regional sweat collections within occlusive coverings may result in higher values compared to whole body sweat. However, despite potential differences by region and sample collection, the high correlation among methods indicates a benefit to correctly identify individuals who are at risk for excess sodium loss using these field techniques.

 



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(22) GLUCOCORTICOID RECEPTOR PHOSPHORYLATION AND SERUM CORTISOL RESPONSES ARE AUGMENTED FOLLOWING HIGH-FREQUENCY RESISTANCE EXERCISE OVERTRAINING

Justin X. Nicoll, PhD, CSCS*D – Assistant Professor, California State University, Northridge

Andrew C. Fry, PhD, CSCS*D, FNSCA – Professor, University of Kansas

Eric M. Mosier, PhD, USAW – Assistant Professor , Northwest Missouri State University

Luke A. Olsen – Doctoral Fellow, University of Kansas Medical Center

Stephanie A. Sontag, CSCS, NSCA-CPT – Student, University of Kansas


PURPOSE: Cortisol responses to stressful exercise are frequently investigated when studying overtraining. However, results are equivocal concerning the role cortisol contributes to maladaptation during overtraining. The intracellular steroid receptor for cortisol is the glucocorticoid receptor (GR). Recent evidence suggests the GR can be phosphorylated at several serine residues (ser134, ser211, and ser226) by the mitogen-activated protein kinase (MAPK) signaling pathway and modulates receptor function independent of hormones.  We have previously reported differences in the resting activity of MAPK after overtraining, but the phosphorylated GR (pGR) responses to overtraining have not been studied. Therefore, the purpose of this study was to determine if resting and exercise induced GR phosphorylation was augmented by a high-frequency resistance exercise overtraining stimulus.  METHODS:  Sixteen men were matched on barbell squat 1 repetition maximum (1RM) strength and randomized into a group that performed normal training or stressful training with insufficient recovery. The control group (CON; n=8, age=20.7±1.2yrs, hgt=180±10cm, body mass=83.9±10.7kg) performed three speed-squat training sessions on non-consecutive days, while the overtraining group (OT; n=8, age=21.3±2.3yrs, hgt=155±62cm, body mass=77.8±11.3kg) performed 15 training sessions over 7.5 days. Prior to (T1), and after the training intervention (T2) both groups performed and acute resistance exercise bout of 5 sets of 5 repetitions at 60% 1RM, and 3 sets of 10 repetition knee extensions. Resting and post-exercise skeletal muscle biopsies were obtained at T1 and T2. Samples were analyzed for total GR and pGR at ser134, ser211, and ser226. Serum samples were obtained at rest, after the final set of barbell squats, and 5 minutes post exercise to determine circulating cortisol concentrations. Significance determined at p < 0.05. RESULTS: The OT group had elevated cortisol values during the squat protocol at T1, but there was no cortisol response at T2. The CON group did not display an exercise induced cortisol response at any time-point (p >0.05).  pGRser134 decreased at T2 for CON (p=0.008) but was unchanged at any time point in the OT group.  pGRser226 increased at post-exercise in both groups at T1(p=0.008) and T2 (p=0.008). However, in the OT group, pGRser226 at rest was higher at T2 compared to T1 (p=0.008). The post exercise response in pGRser226 at T2 was less than the post-exercise response at T1 in OT (p=0.016). CONCLUSIONS: Despite differences in cortisol responses between groups before training, at the local skeletal muscle level pGR was similar between groups. After a period of overtraining, ser226 on the GR which regulates nuclear import and export appeared to be most influenced by the overtraining stimulus.  PRACTICAL APPLICATIONS: Coaches, athletes, and clinicians should be aware that changes in circulating cortisol following a training stimulus may not be completely reflective of changes occurring at the local skeletal muscle level. While monitoring circulating cortisol may provide valuable information about training load and stress, it is likely the GR integrates hormonal, contractile, metabolic stresses in tandem to modulate skeletal muscle adaptations during stressful training.

 



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(23) THE ACUTE CORTISOL RESPONSE TO RESISTANCE EXERCISE: THE IMPORTANCE OF TRAINING STATUS

Stephanie A. Sontag, CSCS, NSCA-CPT – Student, University of Kansas

Justin X. Nicoll, PhD, CSCS*D – Assistant Professor, California State University, Northridge

Andrew C. Fry, PhD, CSCS*D, FNSCA – Professor, University of Kansas

Eric M. Mosier, PhD, USAW – Assistant Professor , Northwest Missouri State University


PURPOSE: To examine the importance of training status on the acute cortisol response to a lower body high volume-moderate intensity resistance exercise (RE) bout in college aged men. METHODS: Resistance trained (RT) men (n = 10;  ± SD, age = 21.3 ± 1.7 yrs, height = 175.8 ± 6.8 cm, body mass = 84.5 ± 13.5 kg, squat 1RM = 154.3 ± 19.3 kg, training history = 5.4 ± 2.0 yrs) and untrained men (UT) (n = 9;  ± SD, age = 20.8 ± 3.1 yrs , height = 178.7 ± 8.9 cm, body mass = 81.0 ± 14.0 kg, squat 1RM = 108.1 ± 13.7 kg, training history = 0.7 ± 1.7 yrs) volunteered for this study. Some untrained subjects had prior RE experience but were classified as untrained due to a lack of current training. Prior to the RE bout, subjects came in for a 1RM strength test for the barbell back squat and leg extension according to NSCA guidelines (Baechle and Earle 2008). Subjects returned 4-7 days later euhydrated and at least 6 hours fasted, between 10am-2pm, and completed a RE bout consisting of 6 sets of 10 repetitions of barbell back squats at 75% 1RM with 1.5 min rest between sets, immediately followed by 4 sets of 10 repetitions of leg extensions at 75% 1RM with 1.5 min rest between sets. Blood samples were collected via venipuncture from an antecubital vein before the RE bout (PRE) and 5 min (5+), 15 min (15+), and 45 min (45+) post exercise. Circulating serum concentrations of cortisol were analyzed via ELISA. Statistical analyses were completed using 2-way repeated measures ANOVAs. RESULTS: In the RT group, there were significant increases (p< 0.05) from PRE to 5+ and PRE to 15+ post RE bout (See table 1). In the UT group, there were significant increases (p< 0.05) at 5+, 15+, and 45+ post RE bout (See table 1). CONCLUSIONS: While both RT and UT groups had significant increases in serum cortisol levels following a lower body RE bout, the UT group stayed elevated longer. PRACTICAL APPLICATION: Resistance trained and untrained individuals have similar initial responses in cortisol to RE; however, RT individuals are able to return to baseline quicker, indicating a faster recovery. For strength and conditioning professionals, it is important to understand there are differences in the physiological responses of individuals with different training statuses, thus affecting how they adapt and recover.

 



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(24) COMPARISON OF BASELINE SALIVARY TESTOSTERONE AND CORTISOL BETWEEN NATIONAL COMPETITORS AND NON-QUALIFIERS IN WOMEN'S COLLEGIATE TRACK AND FIELD

Lauren M. Biscardi, MS, CSCS, CISSN – PhD Student, George Mason University

Margaret T. Jones – Full Professor, George Mason University

Matthew Andre – Assistant Professor, George Mason University


Testosterone and cortisol are both considered to be valid biomarkers in athletes, and are sometimes monitored to help to assess recovery in athletes (Fry & Kraemer, 1997). Further, scientists have wondered if resting concentrations of these hormones can help to predict talent and/or influence acute performance in athletes (Cardinale & Stone, 2006). Differences in baseline concentrations of salivary free testosterone and cortisol between elite and non-elite women athletes across various sports have been documented. The data suggests that more successful athletes have higher salivary testosterone and cortisol than less successful athletes (Cook et al., 2012; Crewther & Cook, 2018). While these studies have compared athletes at different levels of competition, differences in basal hormone concentrations of women athletes with differing performance success at the same level of competition is of interest. PURPOSE: To compare salivary free testosterone and cortisol between women NCAA DIII track and field athletes who were national competitors and matched athletes who did not qualify for nationals. METHODS: Resting saliva samples were collected from 12 NCAA DIII track and field athletes before a preseason time trial. For analysis, athletes were paired by event to include one athlete who scored points at the NCAA DIII National Championship, and one athlete who went through the same training protocol but did not qualify. Each pair of athletes had the same training schedule with the same coach, and the same competition schedule. Twelve matched pairs (2 throws, 2 sprints, 1 vault, 1 distance) were used for analysis. Independent samples t-tests were used to determine whether or not there was a statistically-significant (P < .05) difference between qualifying and non-qualifying athletes for free testosterone and cortisol. RESULTS: National competitors had higher salivary testosterone (mean ± SD: 0.427±0.137 versus 0.250±.078 nmol/L, p=0.020) and cortisol (11.54±4.73 versus 5.95±2.14 nmol/L, p=0.025) concentrations than non-qualifiers, both overall and when matched for event. CONCLUSIONS: Baseline testosterone and cortisol measures were higher in national competitors than non-qualifiers. This suggests that the trend observed in elite internationally-competitive women athletes versus non-elite athletes from various sports (including track and field) also occurs between nationally-competitive and non-qualifying NCAA DIII track and field athletes. PRACTICAL APPLICATIONS: These findings support the use of salivary testosterone and cortisol as valid biomarkers in women athletes. It is recommended that practitioners and sport scientists consider monitoring salivary testosterone and cortisol as a tool for differentiating athletic performance potential in addition to recovery assessment. Saliva samples can be collected on a consistent time interval before warming-up for an afternoon practice session, to be included along with other typical monitoring tools, such as surveys, performance tests, and measures of training and competition workload.

 



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(28) CHANGES IN PERFORMANCE, BODY COMPOSITION, AND BIOMARKERS IN COMPETITIVE MALE TRIATHLETES DURING A PREPARATION CYCLE

Alan J. Walker, PhD. – PhD., IFNH Center for Health and Human Performance, Rutgers University

Harry P. Cintineo, MS, CSCS – PhD Student, Rutgers University

Marissa L. Bello

Bridget A. McFadden, MBS, CSCS*D – PhD Candidate, Rutgers Center for Health and Human Performance

David J. Sanders, MS, CSCS*D – Research Assistant, Rutgers University

Brittany N. Bozzini, CSCS – PhD Student, IFNH Center for Health and Human Performance, Rutgers University

Shawn M. Arent


Research suggests endurance athletes manipulate training prior to a competition to achieve optimal performance capacity on race day. Tracking the physiological response, via blood biomarkers and performance changes, to this manipulation of training can provide additional information on the effectiveness of training. PURPOSE: To track changes in performance, body composition, training load (TL), and various biomarkers in competitive triathletes for a two-month preparation phase prior to a competition. METHODS: Male (N=6; Mage=45.16±13.23yrs; Mheight=167.64±8.75cm) competitive triathletes were used in this study. Athletes participated in three testing sessions consisting of body composition assessment, blood draws, and performance testing. Testing was performed two months (T1), one month (T2), and in conjunction with the taper prior to competition (T3). Athletes arrived fasted and euhydrated between 0700-0900h following a rest day. Body composition assessments included body weight (BW), body fat percentage (BF%), and lean body mass (LBM). Athletes then underwent blood draws for analysis of total and free testosterone (TT, FT), total and free cortisol (TC, FC), creatine kinase (CK), sex-hormone binding globulin (SHBG), and insulin-like growth factor 1 (IGF-1). They were then allowed to eat and hydrate an hour prior to performance testing. An intermittent lactate threshold protocol was used to measure VO2peak and velocity at lactate threshold (VLT). Athletes self-reported weekly distance and duration for each training modality. RM MANOVAs with univariate follow-ups were conducted with significance set at P< .05, and effect size (ES) was calculated using Cohen’s d. RESULTS: Over this training block, there were no changes in VO2peak, VLT, BW, BF%, or LBM (P >0.21). There were no significant changes in cycling and swimming distance or cycling, swimming, and running duration (P >0.11). There was a significant increase in weekly running distance (Δdis=7.85+5.2 km; P< 0.05, ES=0.65) with a trending increase in weekly total exercise duration (Δdur=2.72+1.33 hrs; P=0.097, ES=0.66). There were no significant changes in TT, FT, TC, CK, or SHBG (P >0.13). There was a significant increase from T1-T3 in FC (ΔFC=5.52+1.32 nmoL; P< 0.05, ES=0.62) with a trending increase from T1-T3 in IGF-1 (ΔIGF-1= 29.83+12.94 ng/mL; P=0.069, ES=0.85). CONCLUSIONS: These results show that despite a moderate increase in TL with moderate-large ES, the external stimulus of the training was insufficient in producing performance improvements. It appears these athletes focus more on maintenance rather than manipulating TL to peak for competition. These results suggest greater manipulation in TL can be used to produce favorable changes in fitness prior to a competition. Furthermore, these results highlight the difficulty for competitive, non-professional, athletes to find balance among training and other life stressors to adapt and improve fitness for competition. PRACTICAL APPLICATIONS: A more structured periodization plan should be used to produce a greater physical and physiological challenge for athletes to produce meaningful performance improvements. Utilization of biomarkers and monitoring TL can be used to fine-tune manipulations in training to ensure a minimal effective training dose is met to induce adaptations. Monitoring is vital during the peaking and tapering phases immediately prior to competition to prevent performance decrements from accumulated training stress.

 



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(31) FLUCTUATIONS IN INFLAMMATORY MARKERS IN NCAA MEN'S SOCCER ATHLETES OVER THE COURSE OF A SEASON

Javier A. Zaragoza, CSCS – Graduate Assistant, University Mary Hardin-Baylor

Andreas Kreutzer – Instructional Lab Coordinator, Texas Christian University

Jonathan M. Oliver – Assistant Professor and Director, Sport Science Center, Texas Christian University

Anthony Anzalone – Medical Student, Wake Forest School of Medicine

Tori Como – Research Associate, UNT Health Science Center

David Julovich – Senior Research Associate, UNT Health Science Center

James Hall – Professor, UNT Health Science Center

Sid O'Bryant – Professor, UNT Health Science Center

Stacie Urbina – Assistant Director, Human Performance Lab, University of Mary Hardin-Baylor

Lemuel Taylor – Associate Professor & Director of Graduate Studies, University of Mary Hardin-Baylor


Accumulation of physiological stress over the course of a season may affect the ability of the athletes to maintain competitive training and match demands. During the competitive season, collegiate athletes are faced with other stressors such as, but not limited to, work and school. With a condensed schedule of up to 3 games within 4 days, exacerbation of these metabolic and mechanical stressors during periods of prolonged exposure may be damaging to the players. PURPOSE: To examine the fluctuations of inflammatory markers during the competitive season as related to repetitive subconcussive impacts of the head. METHODS: Sixteen National Collegiate Athletic Association (NCAA) male soccer athletes (20.1±1.3 years, 178.6±8.3 cm, 77.8±11.3 kg, 15.0±6.0 %BF) participated in weekly blood sampling through an 18-week season. Athlete statistics of minutes played (MP), and headers (HEAD) were collected post-season from the coaches. Headers were defined as any impact of the players’ head with the ball. Serum samples were stored at -80°C until analysis for TNF-α, interleukin-6 (IL-6), and interleukin-10 (IL-10) using a Quanterix™ Simoa HD-1 analyzer. We used R statistical language and the lme4 statistical package to perform a linear mixed effects analysis of the relationships of MP and HEAD with TNF-α, IL-6, and IL-10. We included the intercept for subjects as a random effects, and time point (TP), MP and HEAD (without the interaction term) as fixed effects. P values for model comparisons were obtained by likelihood ratio tests. RESULTS: TNF-α, IL-6, and IL-10 had no significant changes over the course of the season when compared to baseline values. TNF-α was elevated in week 14 (0.384 pg/mL) when compared to baseline (0.33 pg/mL). IL-6 remained constant over time with little variations while IL-10 seemed to decrease over time. Adding MP or HEAD did not improve the model fit over models with time points only. The estimates for the effects of MP and HEAD for TNF-α, IL-6, and IL-10 were low and sometimes negative. CONCLUSIONS: In our study, neither MP nor HEAD were significant predictors for TNF-α, IL-6, and IL-10 across the course of an NCAA Men’s soccer season. Concentrations of these cytokines seemed to only slightly vary across the season with slight fluctuations decreasing towards the end of the season. PRACTICAL APPLICATIONS: The results of this investigation suggest that TNF-α, IL-6, and IL-10 are not significantly raised during an NCAA Men’s soccer season at both time points and MP or HEAD. Although this study did not show differences in inflammatory markers across the season, recovery and nutrition are still important to manage the potential for these inflammatory markers to raise across the season. Research reported in this publication was supported (in part) by the National Institute on Aging of the National Institutes of Health under Award Numbers R01AG051848, R01AG058537, and R01AG058252. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. 

 



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(32) MONITORING TRAINING, PERFORMANCE, AND BIOMARKERS THROUGHOUT A COMPETITIVE SEASON: A CASE STUDY OF A TRIATHLETE

Harry P. Cintineo, MS, CSCS – PhD Student, Rutgers University

Alan J. Walker, PhD. – PhD., IFNH Center for Health and Human Performance, Rutgers University

Marissa L. Bello

David J. Sanders, MS, CSCS*D – Research Assistant, Rutgers University

Bridget A. McFadden, MBS, CSCS*D – PhD Candidate, Rutgers Center for Health and Human Performance

Shawn M. Arent


Preparing for a triathlon requires planned and deliberate programming to maximize adaptations while minimizing health decrements. Monitoring training, performance, and biomarkers can be useful for determining physiological responses throughout a competitive season. Purpose: To monitor training, performance, and biomarkers in an international high-level, 41-year-old male triathlete over a 40-week period, including three 113.1-km triathlons. Methods: Training was monitored throughout the season by a fitness tracker. Body composition, performance, and biomarkers were measured every 32.5±6.2 d (T1-T8). The final testing session (T9) occurred 45 d after the final race. At each time point, the subject arrived in a fasted, euhydrated state between 0700-0900 h following a rest day. First, body composition was measured via BodPod. Blood samples were then collected for analysis of free and total cortisol (FC; TC) and free and total testosterone (FT; TT). Lastly, velocity at lactate threshold (VLT) and VO2peak were measured using an intermittent treadmill protocol. Results: Weekly training volume (VOL) throughout the season was 12.4±3.3 h, and competitions occurred between T3/T4, T7/T8, and T8/T9. VOL peaked in preparation of all races, with the largest increase occurring prior to the final race (18.1 h/wk) followed by a 3-wk VOL taper (6.5±6.7 h/wk). This coincided with the best performance (4h:10m:51s), which was a 36.78- and 15.43-min improvement over the first and second races, respectively. Following the final competition, VOL was 6.8±3.4 h/wk. Weekly training intensity (INT), indicated by average heart rate, did not vary notably throughout the season (145.7±3.2 beats/min). Fat free mass (FFM) increased slightly from T1-T2 (Δ+1.84 kg) and steadily decreased until T8, constituting a 3.69% decrease from T1 (Δ-4.00 kg). FFM rebounded by T9 but remained 0.93% below T1 (Δ-0.54 kg). VLT and VO2peak did not change over the season (12.9±0.4 km/h; 55.70±1.54 mL/kg/min). At T3, FC was 26% higher than T1 (Δ+0.24 mcg/mL) but remained stable until increasing again from T7-T9, reaching a 41% increase above T1 (Δ+0.38 mcg/mL). TC remained stable throughout the season (23.34±1.21 mcg/dL). FT and TT remained stable from T1-T7 (46.72±4.06 pg/mL; 543.33±49.47 ng/dL) but both began to fall at T8 and reached 39.47% and 49.40% decreases from T1 at T9  (Δ-18.00 pg/mL; Δ-288.00 ng/dL). Conclusions: Overall, a periodized training program aims to improve performance while maintaining health. Although the subject’s training VOL was structured appropriately, INT was not similarly manipulated. Interestingly, VLT, VO2peak, and FFM maintained or decreased, but race times improved throughout the season. The modest increase in FC at T3 corresponds with the first preparation period. Counterintuitively, despite the reduction in VOL and regain of FFM following the final competition, FC increased robustly along with a decrease in FT and TT, which may be attributable to lifestyle changes after this race. Practical Applications: Here, laboratory performance measures do not appear to vary with competition outcomes, likely due to the lack of specificity compared to the demands of triathlons or because of other factors impacting race performance. Additionally, a structured training and diet plan implemented immediately following the final race of the season may allow for a faster and complete recovery of FFM, FC, and FT while setting up athletes for a successful offseason.

 



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(33) HEMATOLOGICAL RESPONSES TO HIGH-INTENSITY INTERVAL TRAINING, AND MODERATE-INTENSITY CONTINUOUS TRAINING

Tricia L. Hart, CSCS – n/a, n/a

Eliott Arroyo, MS – PhD Candidate, Kent State University

Emily C. Tagesen – Graduate Assistant , Kent State University

Brandon A. Miller, CSCS – Graduate Student, Kent State University

Adam R. Jajtner


PURPOSE: To compare the effects of high-intensity interval training (HIIT) and moderate-intensity continuous training (MCT) on leukocyte subset populations. METHODS: Recreationally active men (n=3; 21.3±3.5 yrs; 182.8±6.3 cm; 11.2±5.8 %BF; 79.4±8.7 kg; 44.1±3.2 ml·kg-1·min-1) completed a maximal graded exercise test (VO2max) and two exercise trials (HIIT and MCT) in a randomized, counterbalanced fashion on a cycle ergometer. HIIT consisted of fifteen 90-second bouts at 85% VO2max interspersed with 90-second active recovery periods. MCT consisted of a single continuous bout at 65% VO2max. Each trial lasted 53 minutes, including a 5-minute warm-up and a 3-minute cool-down. Blood was collected before (PRE), immediately post (IP), 30 minutes (30M), 2 hours (2H), 6 hours (6H) and 24 hours (24H) post-exercise. Leukocyte count (WBC), lymphocyte number and ratio (LY# and LY %), monocyte number and ratio (MO# and MO%) and granulocyte number and ratio (GR# and GR%) were analyzed via an automated hematology analyzer. Changes were assessed using a two factor (time × trial) within-subjects repeated measures ANOVA. All data were confirmed for normality via a Shapiro-Wilk test.  RESULTS: A significant interaction between trials was observed in WBC (F=4.59, p=0.020, η2p=0.70). During HIIT, significant increases in WBC were observed from PRE (3.75±1.15 103∙μL-1) to IP (8.08±1.76 103∙μL-1; p=0.013), 2H (7.42±1.26 103∙μL-1; p =0.002), and 6H (6.51±0.80 103∙μL-1; p =0.006) .  Additional increases were observed from 30M (4.27±1.26 103∙μL-1) to 2H (p=0.026) and 6H (p=0.035). During MCT, WBC increased from PRE (3.98±1.15 103∙μL-1) to 2H (6.81±1.16 103∙μL-1; p=0.014) and 6H (6.49±1.16 103∙μL-1; p=0.003). No differences were observed from PRE to IP (5.24±0.069 103∙μL-1), 30M (3.82±0.24 103∙μL-1) or 24H (3.66±0.54 103∙μL-1). A significant interaction between trials was observed for LY# (F=22.686, p< 0.001, η2p = 0.919). During HIIT, LY# increased from PRE (1.67±0.13 103∙μL-1) to IP (3.33±0.61 103∙μL-1; p=0.032), while decreases were observed relative to IP at 30M (1.34±0.16 103∙μL-1; p=0.021), 2H (1.43±0.10 103∙μL-1; p=0.040) and 24H (1.58±0.10 103∙μL-1; p=0.045). No differences were observed between PRE, 30M, 2H, 6H (2.13±0.09 103∙μL-1), or 24H. During MCT, LY# increased from 30M (1.57±0.23 103∙μL-1) and 2H (1.72±0.44 103∙μL-1; p=0.043) to 6H (2.42±0.42 103∙μL-1; p=0.044).  No differences were observed between PRE (2.06±0.22 103∙μL-1), IP (2.49±0.26 103∙μL-1), 30M, 2H and 24H (1.56±0.10 103∙μL-1). With all trials combined, significant time effects were observed for LY% (F=7.668, p=0.003, η2p = 0.793), MO% (F=5.352, p=0.012, η2p = 0.728), GR% (F=8.224, p=0.003, η2p = 0.804) and GR# (F=24.109, p< 0.001, η2p = 0.923), though no differences were observed between conditions (p > 0.05). CONCLUSION: Data suggest that HIIT stimulates WBC and LY# more than MCT at IP. Additionally, LY# may be suppressed at 30M and 2H in HIIT, but not MCT.  PRACTICAL APPLICATIONS: As interval training has been shown to be effective with a lessened duration, it is becoming popular among coaches and athletes, as well as the general population. Though further research is warranted, the immunosuppressive effects observed following HIIT suggest that intensity may have a greater effect than volume on the immune response to exercise.  Moreover, coaches may want to consider the potential immunosuppressive effects of HIIT training. This study was funded via an NSCA-Foundation Doctoral Research Grant.

 



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(1) AN ELECTROMYOGRAPHICAL COMPARISON OF THE RUSSIAN CURL AND RAZOR CURL

Paul Comfort, PhD, CSCS*D – Reader in Strength and Conditioning, University of Salford

John McMahon

Nicholas J. Ripley – Doctoral candidate, University of Salford

Timothy J. Suchomel, PhD, CSCS*D, RSCC – Assistant Professor, Carroll University

Matthew Cuthbert, BSc (Hons) MSc – PhD Candidate, University of Salford


PURPOSE: The hip extensors (gluteus maximus [GMax] and hamstrings) and knee flexors (hamstrings) play an important role in enhancing performance and reducing injury risk, during numerous athletic tasks. Additionally, the erector spinae (ES) muscles contribute to stabilization of the spine and therefore transference of forces from the lower to the upper body. Appropriate exercise selection and programming is, therefore, important for strengthening such muscles. It is important, therefore, to accurately determine the level of activation of these muscles, via electromyography (EMG), to permit effective comparisons between exercises. Interestingly, while researchers have reported very high EMG values (100-200% of maximum voluntary isometric contraction (MVIC)) for the hamstrings during the razor curl, these values were likely elevated due to suboptimal normalization techniques. Currently, no comparisons in peak EMG between the Russian curl and razor curl appear to have been published, which formed the aim of this investigation. METHODS: Subjects (n = 10; age = 23±4 years, height = 175.9±6.9 cm; mass = 75.2±9.7 kg) had EMG electrodes placed on GMax, biceps femoris (BF), and ES in accordance with SENIAM guidelines. Subjects performed 3 MVIC trials during hip extension, knee flexion and lumbar extension using an isokinetic dynamometer to normalize peak EMG. Subjects then performed 3 repetitions of both the Russian curl and the razor curl, in a randomized order. EMG data were analyzed in Microsoft Excel, identifying the start of the extension phase of the exercises based on thresholds of >2 standard deviations + mean EMG during periods of residual EMG, with the start of the flexion phase identified via a manual trigger during a pause between phases. Reliability between trials was assessed using intraclass correlation coefficients (ICC) and coefficient of variation (CV). Peak EMG data were compared between exercises, for both phases, using paired samples t-tests or Wilcoxon’s tests, based on the normality of data. Hedges g effect sizes were also calculated to determine the magnitude of differences in peak EMG between exercises. An a priori alpha level was set at p < 0.05. RESULTS: High reliability (ICC >0.80) was observed for all EMG data, with low variability (CV < 10%) for all muscles, other than the GMax during both phases of the razor curl. During the extension phase, greater peak EMG was observed in the BF and ES during the razor curl compared to the Russian curl, but not for the GMax. In contrast, during the flexion phase, peak EMG was greater for the BF and ES during the Russian curl compared to the razor curl, although not for the GMax (Table 1). PRACTICAL APPLICATIONS: The Russian curl is likely a more effective exercise for strengthening the BF and ES muscles compared to the razor curl, based on the EMG during flexion phase.

 



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(1) CHANGES IN ISOKINETIC HAMSTRINGS AND QUADRICEPS STRENGTH IN ACADEMY SOCCER PLAYERS DURING A 40-WEEK MACROCYCLE

Mark Stone, PhD MSc ASCC – Senior Lecturer in Strength and Conditioning, University of Central Lancashire

Karl Gibbon – Senior Research Officer, Liverpool John Moores University


Isokinetic peak torque (PT) and functional hamstrings to quadriceps ratio (H:Q) provide useful information about knee-joint strength and stability. Lenhart et al. (1) has previously shown that H:Q measured at an angular velocity of 60o·s-1 remains unchanged throughout a soccer season. However, changes in the torque-producing characteristics of these muscles are velocity specific and injuries tend to occur during joint movements at higher velocities. Changes in H:Q throughout the season could have important implications for training prescription and load management, therefore further research is needed to evaluate within-season changes in H:Q, at higher angular velocities. PURPOSE: The purpose of this study was to investigate whether any systematic changes in H:Q measured at a high angular velocity occur during a 40-week macrocycle. METHODS: Fourteen full-time male academy players (Mean ± SD; Age: 18.7+0.3 years; Height: 179.4+5.7 cm; Mass: 74.1+7.9 kg) from a professional soccer club in the UK volunteered to take part in this study. Players attended the laboratory during weeks one and six (the start and end of preseason) and weeks 23 and 40 (the middle and end of the competition phase) of the macrocycle.  During each visit, participants performed a RAMP warm up and a familiarisation on the dynamometer before completing the isokinetic test battery described in Crosier et al. (2). H:Q was calculated as the ratio between PT during eccentric-hamstrings and concentric-quadriceps exercise at angular velocities of 30 and 240o·s-1, respectively. An angular velocity of 30o·s-1 was deemed appropriate for the eccentric task because isokinetic measurements of eccentric-torque undertaken at high velocities are subject to high levels of measurement error, and in isokinetic testing the eccentric torque-velocity curve is relatively constant (2). Temporal changes in PT and H:Q were evaluated with a repeated-measures ANOVA. Significant main effects were followed up with Bonferroni-adjusted confidence intervals. RESULTS: At week six, H:Q was between 0.01-0.43 lower in the dominant leg (F13,3=3.61, p=0.02) and between 0.08-0.44 lower in the non-dominant leg than in week one (F13,3=5.52, p< 0.01). In the non-dominant leg this decrease in H:Q was attributable to a 2.4–49.4 N·m decrease in eccentric PT of the hamstrings (F13,3=3.77, p=0.02). H:Q in weeks 23 and 40 were not significantly different to any other time point, however concentric PT of the quadriceps in the non-dominant leg was between 0.2–37.7 and 5.1–44.1 N·m greater at weeks 23 and 40 than week one (F13,3=6.22, p< 0.001).  CONCLUSIONS: Several soccer teams routinely assess isokinetic strength of the hamstring and quadriceps at the start of preseason. However, the results of this experiment indicate that even players who present with normal H:Q may experience a decrease in eccentric hamstring PT which can have a deleterious effect on H:Q during the pre-competition phase. Conversely, concentric PT of the quadriceps at a high angular velocity increased during the competition phase.  PRACTICAL APPLICATIONS: Strength and conditioning coaches should be conscious of within-macrocycle changes in the torque-producing characteristics of the hamstring and quadriceps, and manage training-load accordingly.  Further research is warranted to investigate the effects of targeted interventions to maintain eccentric-hamstring PT during preseason in academy soccer players.

References
Croisier, JLS, Ganteaume, J, Binet, M, Genty, Ferret, J-M. Strength imbalances and prevention of hamstring injury in professional soccer players: A prospective study. Am J Sports Med 36: 1469-1475, 2008.
Lehnert, M, Xaverová, Z, De Ste Croix, M. Changes in muscle strength in U19 soccer players during an annual training cycle. J Hum Kinet 42: 175-185, 2014.

 



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(1) DOUBLE PEAK MUSCLE ACTIVATION PATTERN IN A BASEBALL SWING

Garrett A. Ball – Student, Colorado Mesa University

Nicholas Cardinale – Student, Colorado Mesa University

Pedro Gonzalez – Student, Colorado Mesa University

Brent Alumbaugh

Michael Reeder

Kristin J. Heumann, PhD, CSCS, c-EP – Associate Professor , Colorado Mesa University


The double peak muscle activation pattern has shown a positive relationship with enhanced speed and force in a golf swing and in mixed martial arts striking. Similar to golf and a mixed martial arts strike, a baseball swing is a rotational swinging motion with potential to display the double peak phenomenon. PURPOSE: To observe muscle activation patterns using surface electromyography (sEMG) in three phases of the baseball swing. METHODS: Single subject analysis of muscle activation while hitting a ball off of a tee was performed on six NCAA Division II male baseball athletes. Subjects were asked to hit a baseball off of a baseball tee into a net using game-emulated swings. Surface EMG electrodes were attached to the left and right rectus abdominis and left and right erector spinae muscles of each subject. While using a high-speed camera synchronized to the Noraxon sEMG electrodes, muscle voltage was recorded and compared to the three different phases of the swing: initial movement towards the ball, early to mid-swing phase, and bat to ball contact. RESULTS: Double peak muscle activation patterns were observed in the swings of all subjects; however, the prevalence of the double peak phenomenon varied between subjects. In the swings that produced a double peak, there was a period of initial muscle activation in phase one (initial movement towards the ball), a decrease in muscle activation in phase two (early to mid-swing phase), and another spike in muscle activation in phase three (bat to ball contact). In the swings where a distinct double peak was not observed, there was a consistent increase in muscle amplitude through phase three (bat to ball contact). CONCLUSION: This study observed a double peak muscle activation pattern during a baseball swing in Division II collegiate baseball players. PRACTICAL APPLICATIONS: These results could be used to enhance training regimens for specific rotational sports that aim to increase the consistency of the double peak in key muscle groups, increasing the effective mass transferred into an object. Future research should be conducted to determine the relationship between double peak muscle activation, bat velocity, and hitting performance.

 



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(1) PREDICTING BALL EXIT VELOCITY WITH AN INERTIAL MEASUREMENT UNIT IN COLLEGIATE BASEBALL PLAYERS

Reyhan Eusufzai – Student, University of North Texas

Chris A. Bailey – Clinical Assistant Professor, University of North Texas


Inertial measurement units (IMU) are increasing in popularity in research and in practice as a method of acquiring kinematic data, likely due to their minimal spatial constraints. This technology has been applied to several sports, including baseball, but their utility for performance monitoring and identification of key performance indicators (KPI) needs to be evaluated. PURPOSE: The purpose of this study was to evaluate the association between batted ball exit velocity (BEV) and kinematic performance variables assessed with an IMU. METHODS: 13 collegiate baseball players (NCAA DIII) volunteered for this study (82.2 ± 10.9 kg, 178.3 ± 5.5 cm, 19.9 ± 1.3 yrs,). After a total body dynamic warm-up and 10 practice swings (5 dry swings, 5 hitting off of a batting tee), 3 maximal effort swings were completed. During each maximal effort trials, athletes used a standardized bat to hit a ball off of a batting tee at a self-selected height. Kinematic swing performance data were collected via an IMU collecting data at 1,000 Hz. Variables included bat speed at impact (BSI), hand speed max (HSM), time to impact (TTI), bat vertical angle (BVA), and attack angle (AA). BEV was simultaneously collected a with radar gun positioned directly behind the batter. Association between IMU derived variables and BEV were evaluated via bivariate Pearson’s product moment correlations. RESULTS: BSI was the only variable shown to produce a practically significant relationship with BEV (r = 0.53, p = 0.06) but statistical significance was not achieved at the p ≤ 0.05 level. All results can be seen in Figure 1. CONCLUSIONS: While, the small sample size associated with this study likely decreased the chances of achieving statistical significance for many of the variables, only BSI was predictive of BEV from a practical standpoint. BEV and all the IMU variables are likely still important and should continue to be monitored, but further research is necessary to evaluate their importance to performance. PRACTICAL APPLICATIONS: Based on the findings of this study, BSI may be moderately predictive of BEV. It is important to note that the current investigation only looked at BEV as a performance measure and there are many other KPIs associated with hitting that should be evaluated in the future. Furthermore, changes in IMU variables in response to different training volumes and associate fatigue may be of value.

 



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(2) EFFECTS OF LOAD ON JERK TECHNICAL EFFICIENCY IN MASTERS OLYMPIC WEIGHTLIFTERS

Jadeon D. Carreker – Graduate Assistant, Georgia Southern University-Armstrong Campus

Jeremy Ford – Graduate Teaching Assistant, The University of Alabama

Ammar Achraf – Researcher, Georgia Southern University-Armstrong Campus

Robert LeFavi – Founding Dean, University of South Carolina-Beaufort

Bryan Riemann


The ability to jerk the barbell overhead is often the limiting factor in an athlete’s maximal clean and jerk (C&J). Studying the effect of increasing load on jerk performance might identify common underlying technical inefficiencies and limiting factors, with the effects being greater for less successful weightlifters. PURPOSE: To determine the effects of increasing load on jerk technical efficiency, and to determine differences between sexes and championship meet success groups. METHODS: 31 National Masters Olympic Weightlifting Championship competitors (19 women, 12 men, 35-65yrs) completed two C&J lifts using 65, 75, and 85% of their self-reported maximum two to three days before the Championship meet. A 12-camera high-speed kinematic system captured three-dimensional barbell kinematics. From the barbell kinematics, three jerk characteristics that have been suggested to relate to jerk technical proficiency were computed: peak vertical barbell velocity (PVBV) and vertical (VBTR) and horizontal (HBTR) barbell travel range. PVBV was computed during the drive phase. HBTR was defined as the peak posterior to anterior barbell displacement during the dip and drive phases. VBTR was defined as the difference between peak vertical displacement and minimum vertical displacement during the unsupported catch and supported catch phases, respectively.  Both HBTR and VBTR were normalized to body height. Within each sex, participants were split into two groups based on the median meet C&J maximum performance relative to body mass.  Each characteristic was entered into a sex by load by meet success analysis of variance with statistical significance considered at α=.05. RESULTS: Post-hoc linear trend analysis of a significant group x sex x load interaction (P=.016, η2p=.141) for PVBV revealed below median men to be most affected by load (P< .020, d=.44-.71) compared to the other sub-groups.  Increasing load had similar effects on the PVBV between the above median men and women groups (P=.077, d=.34). Load had a significant effect on VBTR, with post-hoc testing revealing significantly less travel for the 85% load compared to the 75% (P=.015, d=.48) and 65% (P=.001, d=.81) loads. Only a significant sex main effect was revealed for HBTR (P=.022, d=.42), with the women demonstrating 61% greater HBTR. CONCLUSION: Increasing loads influences VBTR and PVBV. Interestingly, in the sample studied, the below median men demonstrated the greatest PVBV response to increasing load. Additionally, the above median men and women demonstrated similar PVBR responses suggesting equal proficiency.  Increasing load had no effect on HBTR.  PRACTICAL APPLICATION: The results of this study show that PVBV and VBTR are influenced by increasing the load. Both parameters were measured during the drive, unsupported, and supported phase. A strength and conditioning coach that coaches Masters Olympic Weightlifters should focus on decreasing horizontal displacement in women, and increasing peak velocity at heavier loads in men with less jerk aptness.

 



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(2) VARYING SHOULDER ANGLE INCREASES MUSCLE ACTIVATION OF THE BICEPS BRACHII WITHOUT IMPACTING VOLUME LOAD WITHIN A TRAINING SESSION

Jeremy R. Pearson, MS – Graduate Assistant, The University of Tampa

Christopher Barakat – Adjunct Professor, University of Tampa

Eduardo O. De Souza

Jay O'Sullivan

Michael Alvarez – Research Assistant, University of Tampa

Jacob Rauch

Daniel Aube – Student, University of Tampa

Renato Barroso – Assistant Professor, University of Campinas


Introduction: Manipulating resistance training (RT) variables has been suggested as a means to optimize muscular adaptations. For instance, training volume and muscle activation are two variables that quantify the demands placed on the muscle within a session. However, there is a paucity of data on how these elements are influenced by varying joint angles within a training session. Purpose: Therefore, the aim of this study was to examine how altering the shoulder angle (glenohumeral joint [GH]) affects volume load and muscle activation of the biceps brachii within a training session. Methods: Eleven resistance trained individuals (5 males, 6 females, age: 21 years ± 1.47, height: 166.8cm ± 7.1, body mass: 66.6kg ± 10.4, RT experience: 4.7years ± 1.91) volunteered for this study. Subjects performed three familiarization sessions prior to the experimental sessions. Baseline 10 repetition-maximum (RM) elbow flexion values were recorded during the familiarization sessions in three different GH joint angles (-30°, 0°, 90°). This 10RM load was used for the first working set of each experimental session and the load was adjusted during subsequent sets. Forty-eight hours after the familiarization sessions, subjects underwent two experimental conditions with a one-week washout period between conditions, control (CON) and varying GH joint angle (VAR), in a randomized, cross-over design. Before any experimental session, surface electromyography (EMG) was applied to the mid-belly of the biceps brachii. In order to normalize the EMG data, a maximum voluntary isometric contraction (MVIC) was performed at each shoulder position before starting the experimental conditions working sets. During the MVIC, the root mean square (RMS) of the EMG signal was calculated in 500ms windows, and the highest value was used for normalization of the dynamic contractions. During the working sets, repetitions of each set were divided into quartiles and raw EMG signal was converted into RMS values for each quartile. The CON condition performed all 9 sets of elbow flexion with their GH joint at 0°(i.e., neutral position). The VAR condition performed 3 sets of elbow flexion in each position (-30°, 0°, 90°), in a randomized fashion. A paired t-test was used to compare volume load and muscle activation between conditions. The significance level was set at p< 0.05. RESULTS: For muscle activation, the overall session EMG amplitude was significantly higher (p=0.0001) in the VAR condition compared to CON (CI: 8.4% to 23.3%). Interestingly , regarding volume load, there were no differences between conditions (VAR 596 kg ± 170, CON 606 kg ± 175). Conclusion: Our results suggest that despite similar volume load between conditions, varying joint angles increases muscle activation within a training session. Practical Application: Our data suggest that altering joint angles during exercise increases muscle activation in an acute fashion. However, these findings should be examined with caution since these acute responses may not be associated with long term adaptations. Therefore, future investigations are warranted to determine any chronic effects.

 



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(3) ESTABLISHING EFFECTIVENESS OF MUSCLE RECRUITMENT IN A MEDICINE BALL VERSUS A BALLISTIC BALL DURING UPPER EXTREMITY EXERCISE

Heather Milton, MS RCEP CSCS – Clinical Specialist Exercise Physiologist, NYU Langone Sports Performance Center

April Davis – Clinical Specialist, Faculty, NYU Langone Health

Julie Fernandes – Hand Therapy Fellowship Coordinator, NYU Langone Health


Background: Various exercise tools are used in abundance during training and rehabilitation of athletes susceptible to shoulder injury as a means to strengthen stabilizing muscles of the shoulder, and trunk. In contrast to the vast amount of literature evaluating muscular activity during traditional medicine balls and Bodyblade® tools, there is no peer reviewed literature evaluating muscular activity during exercise using new varieties of medicine balls that are currently being sold to rehabilitation and exercise professionals. Hypothesis/Purpose: The purpose of this study was to compare the electromyogram (EMG) activity of shoulder and trunk stabilizing muscles during three commonly performed medicine ball exercises using both a standard medicine ball and a ballistic medicine ball (SB) Methods: Twenty-four healthy volunteers (17 female and 7 male) with a mean (± standard deviation) age of 35.5±9.2 years and a body mass index (BMI) of 22.7±2.8 were enrolled. Following a familiarization session, wireless surface EMG probes were placed on subject’s infraspinatus (IS), latissimus dorsi (LD), anterior deltoid (AD) and external obliquus (EO). The order of exercises and ball selection were randomly drawn. Each subject performed three exercises using MB and SB. Results: There were no significant (p >0.05) differences in maximal and mean muscle activity in any muscle group between exercises with the MB and SB. Two-way analyses of variance showed no significant (p< 0.05) differences in muscle activity between the two ball types for all muscle groups. Conclusions: This study suggests that the new SB exercise tool may be a useful tool for rehabilitation of athletes in need of tools to aid in shoulder and trunk stabilization. The lack of statistical significance between ball types suggests there is no added benefit to use the SB over traditional MB. Future study is recommended using a variety of SB and MB weights and sizes to further evaluate muscle recruitment during common exercises using these tools. Practical Application: Rehabilitation therapists and exercise professionals alike may further consider utilizing newly marketed exercise tools not as a replacement of traditional tools, but rather as a compliment for training variety in athletes.

 



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(3) GENDER COMPARISONS OF RATE OF NEUROMUSCULAR FATIGUE ACROSS HANDLE TYPES DURING SEATED ROW EXERCISE

Tatum M. Mack – Graduate Assistant, Bloomsburg University of Pennsylvania

Swapan Mookerjee – Professor, Bloomsburg University

Sam Meske – Graduate Student, Bloomsburg University

Kyle S. Beyer, PhD, CSCS*D – Assistant Professor, Bloomsburg University

Dan G. Drury – Associate Professor, Gettysburg College


Muscular responses, rate of neuromuscular fatigue, and performance during seated row exercise may be affected by using a neutral wrist (NW) or a flexed wrist (FW) handle design. PURPOSE: To compare rate of fatigue differences between the Biceps Brachii (BB), Latissimus Dorsi (LD), and Flexor Carpi Radialis (FCR) across the two handle types during seated row exercise. A secondary purpose was to compare performance differences and rate of fatigue between genders. METHODS: A sample of 10 males (21.6 ± 1.30 yrs) and 10 females (22.1 ± 2.80 yrs) with prior resistance training experience (5.0 ± 2.5 yrs) completed a 1 repetition maximum (1-RM) seated row with both NW and FW handle types in a randomized order. This was followed by a maximal repetition set to failure using 85% 1-RM with both handle types in a randomized order. Electromyography of the BB, LD, and FCR were assessed during the maximal repetition set to failure at 85% 1-RM. Root mean square from the BB, LD, and FCR were determined for each repetition and slope coefficients were calculated for each maximal repetition set to determine rate of neuromuscular fatigue. Two-way mixed factorial ANOVAs were used to analyze gender and handle differences in 1-RM and number of repetitions to failure. Three-way mixed factorial ANOVA was used to analyze rate of fatigue between gender, muscle, and handle type. RESULTS: The 1-RM lifts were significantly greater (p< 0.001) with the FW handle (90.2 ± 30.5 kg) versus the NW handle (87.8 ± 30.4 kg). There were significant differences (p< 0.001) between genders for the 1-RM lifts across both handle types (males - FW: 117.3 ± 16.5 kg, NW: 114.5 ± 17.2 kg; females - FW: 63.2 ± 6.17 kg, NW: 61.1 ± 6.05 kg).  A significant handle×gender interaction (p=0.047) was noted for repetitions to failure at 85% 1-RM. Post hoc tests revealed that males completed the same number of repetitions with the NW (11.9±3.7 reps) and FW (11.2±2.4 reps) handles, while there was a trend (p=0.051) for females to complete more repetitions with the FW (12.7±3.7 reps) than NW (11.5±2.3 reps). There was no significant 3-way interaction (p=0.576) for the rate of fatigue. However, a trend (p=0.052) for a muscle×gender interaction was noted, and a significant main effect of muscle (p=0.014) was observed. Regardless of handle or gender, the LD (2.43±1.12 mV/rep) had a significantly (p=0.014) greater rate of fatigue than the BB (1.22±1.24mV/rep) or FCR (0.41±2.19 mV/rep). CONCLUSIONS: These findings showed significantly higher 1-RM with the FW handle type. Furthermore, females may be able to complete a greater number of repetitions to failure with the FW handle when compared to NW. Finally, neuromuscular fatigue was not affected by gender or handle types, but the LD had the greatest neuromuscular fatigue during the seated row. Possible mechanisms for the 1-RM differences may be related to actin and myosin overlap of the forearm flexors, ergonomic factors such as grip comfort and differences in handle contact surface area. PRACTICAL APPLICATIONS: Alterations in wrist positioning during seated row exercise was shown to result in significant increases in 1-RM for both genders and in repetitions to failure for females only. These findings are important from an equipment design, training, and performance perspective.  Using the WF handle allows for a greater amount of weight to be lifted, and may ultimately improve overall development of strength.

 



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(4) COMPARISON OF STRIDE LENGTH AND STRIDE FREQUENCY PATTERNS OF SPRINT PERFORMANCE IN OVERGROUND VS MOTORIZED TREADMILL SPRINTING

Lance D. Gruber – Graduate Student, University of Texas at El Paso

Samuel Montalvo, MS., CSCS – PhD Candidate, University of Texas at El Paso

Sandor Dorgo


Sprint Performance (SP) and the ability to attain maximal sprinting velocity is a major factor in many athletic events. Stride length (SL) and stride frequency (SF) are critical variables when looking at SP. SP can be improved by training overground (on track) (OG), as well as on motorized high-speed treadmills (TM). However, our current understanding is lacking regarding kinematic differences, specifically SL and SF patterns, between motorized treadmill and overground sprinting conditions. Purpose: 1) To examine the relationship between SL and SF between OG and TM sprinting; and 2) examine if SL and SF are predictors of OG and TM maximal sprint speeds. Methods: Forty subjects, 20 NCAA sprint athletes and 20 recreationally trained college-aged athletes took part in a single-day testing session. Testing consisted of two 60m OG sprints and two maximal sprints on a highspeed motorized treadmill. In addition to SL and SF, contact time (CT), and flight time (FT) were recorded using a photoelectric cells device. For the OG testing, two timing gates were also used to record maximal sprint speed over the final 10m of each 60m sprint. Subjects were instructed to use the 50-m prior to the testing zone for acceleration in order to achieve maximal speed. For the TM sprinting testing, a motorized treadmill with a max speed of 13.5 m/s was used. Subjects wore a safety harness connected to a steel frame to prevent being ejected from the treadmill. In the testing run, subjects were instructed to gradually transfer their weight on to the moving belt while holding onto the handrails. Subjects were asked to keep up with the belt speed for 3-4 seconds. If successful, belt speed was increased for the subsequent trials until the subjects’ failure to keep up. Results: Among the 40 subjects, there was a strong positive correlation for speed, CT, and SF performed in OG modality. A correlation was also found between speed, CT and SF performed in the TM condition (Pearson R = 0.94; R = 0.68; and R = 0.65, respectively). In addition, we observed a significant difference (p = 0.00) between OG-speed & TM speed (mean and SD diff = -0.214 ± 0.384), OG-CT & TM-CT (mean and SD diff = -0.010 ± 0.020), and OG-SF & TM-SF (mean and SD diff = -0.471 ± 0.311). No significance difference was observed between OG-FT & TM-FT (mean and SD diff = -0.101 ± 0.248) and OG-SL & TM-SL (mean and SD diff = -65.325 ± 95.750). Among 40 subjects, CT, FT, and SF were found to be predictors of sprint speed in the overground modality (p = 0.000) while SL was not a predictor of sprint speed in this modality. Linear regression for motorized treadmill conditions in 40 subjects showed that CT, FT, SL and SF are all predictors of sprint speed (p < 0.05). Discussion: Results show that motorized treadmill increases stride frequency dramatically when compared to overground, which could result in the motorized treadmill being used as a training tool to enhance stride frequency. However, the optimal ratio used to achieve sprint speed was altered on the motorized treadmill when compared to overground running. Therefore, while there may benefits to using such an instrument to enhance speed, it is unclear how much improvement is transferred to overground condition. Practical Application: A High-speed motorized treadmill can be used as a supplemental training tool to induce supramaximal sprint running, in aid of acquiring neural muscular adaptations and improvement of stride frequency and ground contact time.

 



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(4) EFFECT OF POST ACTIVATION POTENTIATION ON WEIGHTLIFTING PERFORMANCE.

Shyam Chavda, MSc – Technical Tutor, Middlesex University

Angela Sorensen – Student, Middlesex University

James Vernau – Strength and conditioning coach, Highgate school

Chris J. Bishop, MSc, ASCC – Senior Lecturer in Strength & Conditioning, Middlesex University

Anthony Turner – Associate Professor, Middlesex University


EFFECT OF POST ACTIVATION POTENTIATION ON WEIGHTLIFTING PERFORMANCE. INTRODUCTION: Post activation potentiation (PAP) has been shown to increase kinetic profiles of athletic movements following ballistic or high intensity resistance exercises. The elicitation of PAP is heavily dependent on the biomechanical similarity of the conditioning stimuli to the movement which is to be potentiated. While PAP has been heavily investigated within the context of sprinting and jumping, a lack of information currently exists on the effects of PAP on the kinetics and kinematics of the clean. PURPOSE: The primary aim of this study was to examine the acute performance enhancing effects of a single supramaximal clean pull performed at 120% of clean and jerk (CJ) one repetition maximum (1RM) on clean performance at 90% 1RM. METHODS: Eight (n = 8) ranked collegiate level male and female weightlifters (Mean ± SD; Age: 25.8 ± 6.1 years; Height: 1.69 ± 0.97 m; Mass: 68.1 ± 10.9 kg) volunteered to participate in this study. A control session was used to identify a baseline measure of clean performance conducted at 90% of predetermined 1RM CJ. The experimental condition required participants to perform a single clean pull at 120% of CJ 1RM followed by three minutes recovery, prior to executing three cleans with one-minute recovery between repetitions. All lifts were performed on a dual force plate set up (Kistler 9286AA and BA, Winterhur, Switzerland), synchronised with a 3D motion capture system (CODA motion capture, Charnwood dynamics, Rothley, UK) to simultaneously record barbell and vertical ground reaction force (vGRF) data. All statistical analyses were performed utilizing SPSS 24.0 (IBM Corp, Armonk, NY). Reliability was quantified for six independent kinetic and kinematic variables using the coefficient of variation (CV) and interclass correlation coefficient (ICC). A paired samples t-test was performed to evaluate the differences that may exist between independent variables between the two conditions (Control vs PAP). The criterion for statistical significance was set at an alpha-level of p < 0.05. The magnitude of change was also quantified between independent variables using Cohen’s d effect sizes, with 95% confidence intervals (CI). Individual subject analysis was calculated using percentage change of the average result from the three trials performed at 90% for each condition (control vs experimental). RESULTS: All variables demonstrated good reliability except for the unweighting vertical impulse which showed poor reliability (CV = -22.45, ICC = 0.67, [-0.26 – 0.95]). The paired samples t-test indicated no statistical significance between the control and PAP condition across variables. Magnitude of change between the control and PAP condition were trivial to moderate (ES = 0.14 to -0.67, [-1.27 to 1.12]), displaying both positive and negative effects. Further analysis on individual percentage change within the six kinetic and kinematic variables demonstrated values, both positive and negative, ranging from -13% to 27%. CONCLUSION: The results demonstrate that PAP on kinetic and kinematic measures, during the clean are subject specific, and therefore may negatively affect some and not others. This is evidenced through the lack of statistical significance found between the control and experimental condition across all variables (p = 0.14 – 0.80) but is highlighted when percentage change is considered for each individual. PRACTICAL APPLICATION: The results indicate that utilising a supramaximal clean pull of 120% 3 minutes prior to performing a clean at 90% of 1RM will likely elicit a positive response for some and not others. Given that the current protocol had little effect on the group, it is suggested that individual analysis of PAP on kinetic and kinematic indices related to weightlifting is conducted in response to load, time and rest period. Identifying a potentiating stimulus for an individual within weightlifting may increase the likelihood of greater accessibility of force, thus increasing the chances of lifting a greater load.

 



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