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Research examining the changes in muscle oxygen saturation across multiple sets of resistance exercise is limited. The purpose of this study was to describe the physiological response of muscle oxygenation parameters during upper-body resistance exercise and examine the differential effects of relevant participant characteristics on resistance training performance and muscle oxygen saturation dynamics. Sixty-one recreationally trained men (n = 44; 21.8 ± 2.6 years) and women (n = 17; 20.2 ± 1.8 years) completed five-repetition maximum sets of barbell bench presses at a load equal to 75% 1-RM with a 2 min rest interval. Muscle oxygen saturation (SmO2) dynamics within the anterior deltoid were monitored using a portable near-infrared spectroscopy sensor. The percent change in SmO2 (∆%SmO2), the muscle oxygen re-saturation rate (SmO2RecSlope), and the highest measured SmO2 value during recovery periods (SmO2Peak) were measured. Two-way (sex [men, women] x time [sets 1–5]) repeated measures analyses of variance (ANOVA) were performed on muscle saturation variables. To examine the effect of relevant controlling variables, separate analyses of covariance (ANCOVA) with repeated measures were also performed. No differences were seen with ∆%SmO2 across sets. The main effects for sets occurred for SmO2RecSlope, whereby a decline was noted on sets 4 and 5 (p = 0.001) compared to set 1. Additionally, SmO2Peak was the lowest on set 5 (p < 0.001) compared to all other sets. Moreover, body mass (p = 0.013), diastolic blood pressure (p = 0.044), and mean arterial pressure (p = 0.033) for ∆%SmO2 were the only significant covariates noted amongst the muscle oxygenation variables. In conclusion, no sex differences and only a few set differences in muscle oxygen saturation dynamics were seen without employing any covariates. Body mass, diastolic blood pressure, and mean arterial pressure were identified as factors that could influence observed responses.

To observe workout pacing strategies and determine which best predicted performance, this retrospective study analyzed recorded efforts from a random selection of 160 high-ranking (top 10,000) men and women (n = 80 each) in the 2020 CrossFit® Open (CFO). Video recordings submitted to the official competition leaderboard for all five tests were analyzed to quantify overall test completion rates (and tie-break time for test 5 only) and within-test repetition completion rate (repetitions × sec−1) for each exercise, as well as the quantity of failed repetitions, break strategy (count and duration), and transition times. Each variable was aggregated into first-half, last-half, and total-test averages, slopes, and coefficient of variation; except on test 5 (total-test only). Spearman's rank correlation coefficients were calculated between test completion rates, each test's respective pacing variables, competitor demographics (height and body mass) and CFO experience (i.e., past participation, consecutive competitions, and ranks). Stepwise regression using significantly (p

This retrospective study collected video recordings of a random selection of eighty men and women (n = 160) completing all five tests of the 2020 CrossFit® Open. All competitors were ranked within the top 10,000 overall but were sub-divided based on whether they ranked within the top 10% of their respective divisions. To examine the effect of sex and rank on pacing strategy, video analysis quantified the overall repetition completion rate on each test, as well as per minute (or round) repetition completion rates for each test’s individual exercises, quantity of failed repetitions, break times, and transition times. All per minute (or round) data were aggregated into first- and last-half or total test average, slopes, and coefficient of variation. Sex and rank analyses of variance were performed on averages, slopes, and coefficients of variation for each variable calculated over the first and last halves of each test, except test 5 (total only). The top 10% of men were 17.5% faster (p < 0.001) than everyone else in tests 1, 3, and 5. The top 10% of women and remaining men were ~9.5% faster than remaining women in tests 1 and 3. In test 5, the remaining men were faster than top 10% of women (~11.2%, p < 0.001), and both were faster than the remaining women. In tests 2 and 4, the top 10% of athletes were 9.7% faster (p < 0.001) than remaining athletes, and at the same time, men were 7.7% faster (p < 0.001) than women. Analysis of each test’s components revealed the top 10% of competitors to be faster and more consistent in most areas, while men were generally faster than women in gymnastics components and more consistent with their pace for resistance training exercises. These data provide insight into the differential factors linked to success in the men’s and women’s CFO divisions.

Abstract Purpose To examine the relationships between past competition performances and 2020 CrossFit® Open (CFO) performance. Methods A random selection from the top one thousand athletes (n = 220, 28.5 ± 4.4 years, 178 ± 7 cm, 87.5 ± 10.2 kg) were selected for this study. Overall and weekly performances (including ranks and scores) of the 2020 CFO, as well as overall ranks from all previous CFO, regional, and Games™ competitions in which they competed, were recorded from their publicly available online profile. The highest, lowest, average, and standard deviation (SD) of past rankings, as well as participation statistics (i.e., years since first appearance, total and consecutive appearances, and participation rate), were calculated for each competition stage. Relationships were then assessed between 2020 CFO performance and all past competition experience variables by calculating Kendall’s tau (τ) correlation coefficients and Bayes factors (BF10). Results Overall and weekly ranking of the 2020 CFO was extremely favored (p 100) to be related to the athlete’s highest previous CFO rank (τ = 0.26–0.39) and individual regional appearances (τ = − 0.26 to − 0.34), as well as individual Games™ appearances (overall and for weeks 1, 3, and 4; τ = − 0.20 to − 0.22, p 100). Evidence for all other significant relationships ranged from moderate to very strong (p

IntroductionThe CrossFit® Open (CFO) acts a preliminary round that qualifies men and women for later stages of its annual Games competition. The CFO typically consists of 4-6 workouts that variably challenge an athlete's weightlifting strength, gymnastic skill, and endurance capacity. Except for differences in prescribed intensity loads, workouts are designed the same for men and women to elicit a similar challenge. While all workouts within a single year are unique to each other, one has been repeated from a previous CFO each year between 2012 and 2021. Because previous CFO workouts are often integrated into training, improvements are expected when a workout is officially repeated. However, besides documented record performances, it is unclear whether most athletes are improving, if these improvements affect ranking, or if differences exist between men and women.PurposeTo examine sex-division differences and performance changes across repeated CFO workouts, as well as their effect on CFO and workout ranking.MethodsEleven separate samples of 500 men and 500 women, who were representative of the same overall percent rank within each year involving one of the nine repeated CFO workouts (2011-2021) were drawn for this study. Each athlete's age (18-54 years), rank (overall and within each workout), and reported workout scores were collected from the competition's publicly-available leaderboard. Each sample had excluded any athlete who had not met minimum performance criteria (e.g., at least one completed round) for all prescribed (Rx) workouts within a given year (including those not analyzed). Since some workouts could be scored as repetitions completed or time-to-completion (TTC), and because programming was often scaled between men and women, all scores were converted to a repetition completion rate (repetitions divided by TTC [in minutes]).ResultsSeparate sex-division x time analyses of variance with repeated measures revealed significant (p < 0.05) interactions in all but one repeated workout comparison. Initially, men were faster in four workouts (~18.5%, range = 3.9-35.0%, p < 0.001), women in two (~7.1%, range = 5.2-9.0%, p < 0.001), and they tied in the remaining three workouts. When workouts were repeated in subsequent years, men were faster in three workouts (~5.4%, range = 0.9-7.8%, p < 0.05), while women were faster in two (~3.8%, range = 3.5-4.1%, p < 0.01). Though performance improved in seven of the nine workouts (~14.3%, p < 0.001) and percentile rank was controlled, athletes earned a lower rank (overall and within workout) on each repeated workout (p < 0.001).ConclusionsPerformance (measured as repetition completion rate) has improved in most repeated CFO workouts, particularly for women. However, improvements seen among all athletes, along with increased participation, have made it more difficult for athletes to improve their overall rank. To rank higher, individual athletes must improve their pace to a greater degree than the average improvements seen across the competitive field.

Background Systematic reviews and meta-analyses related to high-intensity functional training (HIFT) have been conducted. However, due to a restricted pool of available research, these investigations are often limited in scope. As such, a scoping review investigating the present literature surrounding the acute physiological response to HIFT-based exercise was chosen as a more appropriate structured review. Methodology A scoping review was conducted following Arksey and O’Malley’s framework. Three large scale databases were searched to reveal any article pertaining to HIFT and related exercise terminology. Results A total of 2,241 articles were found during the initial search. Following this, titles, then abstracts, and full-texts were reviewed to determine inclusion eligibility. A total of 60 articles which investigated a combined total of 35 unique HIFT workouts were included within this review. Conclusions A variety of physiological parameters and HIFT workouts have been examined. Markers of intensity (e.g., blood lactate concentrations, heart rate) have been most consistently assessed across all studies, and these support the idea that HIFT workouts are typically performed at high-intensity. In contrast, the inclusion of most other measures (e.g., hormonal, markers of inflammation and damage, energy expenditure, performance) has been inconsistent and has thus, limited the possibility for making generalized conclusions. Differences in study methodologies have further impacted conclusions, as different studies have varied in sample population characteristics, workouts assessed, and time points. Though it may be impossible to comprehensively research all possible HIFT workouts, consistent adoption of population definitions and workload quantification may overcome this challenge and assist with future comparisons.

The design of high-intensity functional training (HIFT; e. g., CrossFit®) workouts and targeted physiological trait(s) vary on any given training day, week, or cycle. Daily workouts are typically comprised of different modality and exercise combinations that are prescribed across a wide range of intensities and durations. The only consistent aspect appears to be the common instruction to maximize effort and workout density by either completing “as many repetitions as possible” within a time limit (e.g., AMRAP, Tabata) or a list of exercises as quickly as possible. However, because effort can vary within and across workouts, the impact on an athlete's physiology may also vary daily. Programming that fails to account for this variation or consider how targeted physiological systems interrelate may lead to overuse, maladaptation, or injury. Athletes may proactively monitor for negative training responses, but any observed response must be tied to a quantifiable workload before meaningful changes (to programming) are possible. Though traditional methods exist for quantifying the resistance training loads, gymnastic movements, and cardiorespiratory modalities (e.g., cycling running) that might appear in a typical HIFT workout, those methods are not uniform, and their meaning will vary based on a specific exercise's placement within a HIFT workout. To objectively quantify HIFT workloads, the calculation must overcome differences in measurement standards used for each modality, be able to account for a component's placement within the workout and be useful regardless of how a workout is commonly scored (e.g., repetitions completed vs. time-to-completion) so that comparisons between workouts are possible. This review paper discusses necessary considerations for quantifying various HIFT workout components and structures, and then details the advantages and shortcomings of different methods used in practice and the scientific literature. Methods typically used in practice range from being excessively tedious and not conducive for making comparisons within or across workouts, to being overly simplistic, based on faulty assumptions, and inaccurate. Meanwhile, only a few HIFT-related studies have attempted to report relevant workloads and have predominantly relied on converting component and workout performance into a rate (i.e., repetitions per minute or second). Repetition completion rate may be easily and accurately tracked and allows for intra- and inter-workout comparisons. Athletes, coaches, and sports scientists are encouraged to adopt this method and potentially pair it with technology (e.g., linear position transducers) to quantify HIFT workloads. Consistent adoption of such methods would enable more precise programming alterations, and it would allow fair comparisons to be made between existing and future research.

L-citrulline serves as a nitric oxide precursor with the potential to increase blood flow and improve resistance exercise performance, yet more research is needed to examine its ergogenic potential. To examine the effect of L-citrulline supplementation on resistance exercise performance, muscle oxygenation, and the subjective perception of effort, energy, focus, fatigue, and muscle pump, eighteen resistance-trained men (n = 11) and women (n = 7) (21.4 ± 1.8 years; 172.3 ± 7.5 cm; 76.9 ± 10.8 kg) were randomly assigned for supplementation with 8 g of L-citrulline (CIT) or a placebo (PL) in a cross-over fashion one hour prior to testing. Participants completed an isometric mid-thigh pull test (IMTP), a ballistic bench press protocol [two sets of two repetitions at 75% 1-repetition maximum (1 RM) with maximum ballistic intent], and a strength-endurance bench press protocol [five repetition-maximum sets at 75% 1RM]. Barbell velocity and power were measured via a linear position transducer during the ballistic protocol, while the repetitions completed, volume load and muscle oxygenation were quantified during the strength-endurance protocol. Subjective measures were assessed at the baseline and immediately pre- and post-exercise. Repeated measures of the analysis of variance and Bayesian equivalents revealed no significant interactions, providing evidence favoring the null hypothesis (BF10 < 1) for IMTP (PL 497.5 ± 133.6 vs. CIT 492.5 ± 129.4 N), barbell velocity, and power, and repetitions completed (PL 36.7 ± 7.2 vs. CIT 36.9 ± 8.1 repetitions). There were also no significant interactions for muscle oxygenation parameters or subjective measures except perceived fatigue. Women reported greater fatigue across all time points compared to men (~1.88 au, p = 0.045, BF10 = 0.2). The results indicate that a single 8 g dose of L-citrulline did not enhance isometric force production, muscle endurance, or muscle oxygenation parameters during the protocol implemented in this study.

This study examined relationships between body composition and high-intensity functional training (HIFT) workout performance. Fifty-seven men (31.4 ± 6.9 years, 177.2 ± 7.5 cm, 84.7 ± 8.5 kg) and thirty-eight women (29.2 ± 6.4 years, 166.6 ± 6.1 cm, 66.5 ± 7.7 kg) with HIFT experience (≥6 months) reported completing “Fran” (21-15-9 repetitions of barbell thrusters and pull-ups) in 4.78 ± 2.22 min and 6.05 ± 2.84 min, respectively, and volunteered to complete dual-energy X-ray absorptiometry assessments. Participants were grouped by competition class (men, women, master’s men, master’s women) and percentile rank in “Fran” (≤25th percentile, 25–75th percentiles, ≥75th percentile). Two-way analyses of variance revealed expected differences (p < 0.001) between men and women in non-bone lean mass (NBLM), fat-free mass index, and fat mass, and more NBLM (10.6–10.8 kg) and less fat mass (2.7–5.2 kg) in >75th percentile compared to other percentiles. Most body composition measures were significantly (p < 0.05) related to performance in men and women but limited in master’s men; no relationships were seen in master’s women. “Fran” time was negatively correlated to NBLM and fat-free mass index in all percentile groups (ρ = -0.37 to -0.64) and bone mineral characteristics for >25th percentile (ρ = −0.41 to −0.63), and positively correlated to fat mass in 25–75th percentiles (ρ = 0.33–0.60). No other relationships were seen in ≤25th percentile. The influence of body composition on “Fran” time appears to vary by both competition class and percentile rank. Though training to increase lean mass always seems relevant, reducing body fat only appears relevant in mid-skilled trainees and when it is outside healthy parameters.

To create normative scores for all CrossFit® Open (CFO) workouts and compare male and female performances, official scores were collected from the official competition leaderboard for all competitors of the 2011–2022 CFO competitions. Percentiles were calculated for athletes (18–54 years) who completed all workouts within a single year ‘as prescribed’ and met minimum scoring thresholds. Independent t-tests revealed significant (p < 0.05) sex differences for 56 of 60 workouts. In workouts scored by repetitions completed, men completed more repetitions in 18 workouts by small to large differences (d = 0.22–0.81), whereas women completed more repetitions in 6 workouts by small to medium differences (d = 0.36–0.77). When workouts were scored by time to completion, men were faster in 10 workouts by small to large differences (d = 0.23–1.12), while women were faster in 3 workouts by small differences (d = 0.46). In three workouts scored by load lifted, men lifted more weight by large differences (d = 2.00–2.98). All other differences were either trivial or not significant. Despite adjusted programming for men and women, the persistence of performance differences across all CFO workouts suggests that resultant challenges are not the same. These normative values may be useful for training and research in male and female CrossFit® athletes.

To examine relationships between Brazilian Jiu Jitsu (BJJ) descriptors (belt rank, experience, gi preference, and fighting style), resistance training (RT) experience, and measures of body composition, strength (maximal handgrip, 3-5-repetition maximum [RM] in barbell glute bridge [GB], prone bench row [PBR], and bench press [BP]), and velocity (GB, PBR, and BP at 7 kg and 30–60% 1-RM), 13 experienced (4.3 ± 3.4 years) BJJ athletes were recruited for this cross-sectional, pilot study. Significant (p < 0.05) Kendall’s tau and Bayesian relationships were seen between belt rank and body fat percentage (τ = −0.53, BF10 = 6.5), BJJ experience and body fat percentage (τ = −0.44 to −0.66, BF10 = 2.6–30.8) and GB velocity (τ = −0.45 to −0.46, BF10 = 2.8–3.1), RT experience and strength (τ = 0.44 to 0.73, BF10 = 2.6–75.1) and velocity (τ = −0.44 to 0.47, BF10 = 2.6–3.3), gi preference-training and relative PBR strength (τ = 0.70, BF10 = 51.9), gi preference-competition and height and lean mass (τ = −0.57 to 0.67, BF10 = 5.3–12.4) and BP velocity (τ = −0.52 to 0.67, BF10 = 3.5–14.0). The relevance of body composition and performance measures to sport-specific training and research interpretation are differentially affected by a BJJ athlete’s experience (BJJ, belt rank, RT), gi preferences, and fighting style.

Background Muscular damage sustained while playing rugby may hinder performance across a season. β-Hydroxy β-Methylbutyrate (HMB) may help attenuate muscle damage and maintain lean mass and performance. This study sought to determine the effect of combining HMB with creatine monohydrate supplementation on measures of stress and muscle damage, body composition, strength and sprinting kinetics throughout a rugby season. Methods This double-blind, cross-over investigation recruited 16 male collegiate rugby players to provide resting blood samples and complete assessments of body composition, strength and sprinting performance prior to their fall season (PREFALL). After testing, the athletes were matched for fat-free mass and assigned to consume one of two supplementation regimens for 6 weeks: 5 g HMB + 5 g creatine per day (HMB-Cr: 20.9 ± 1.1 years; 177 ± 2 cm; 88.4 ± 4.9 kg) or 5 g creatine + 5 g placebo per day (Cr: 21.4 ± 2.1 years; 179 ± 2 cm; 88.3 ± 4.9 kg). After 6 weeks (POSTFALL), PREFALL testing was repeated in 13 of the original 16 athletes before a 10-wk wash-out period. Athletes who returned for the spring season (n = 8) repeated all fall-season procedures and testing prior to (PRESPRING) and following (POSTSPRING) their 6-wk spring season, except they were assigned to the opposite supplementation regimen. Results Linear mixed models with repeated measures revealed group x time interactions (p

This investigation examined anthropometric, hormonal, and physiological differences between advanced (ADV; n = 8, 27.8 ± 4.2 years, 170 ± 11 cm, 79.8 ± 13.3 kg) and recreational (REC; n = 8, 33.5 ± 8.1 years, 172 ± 14 cm, 76.3 ± 19.5 kg) CrossFit (CF) trained participants in comparison to physically-active controls (CON; n = 7, 27.5 ± 6.7 years, 171 ± 14 cm, 74.5 ± 14.3 kg). ADV and REC were distinguished by their past competitive success. REC and CON were resistance-trained (>2 years) and exercised on 3-5 days·wk-1 for the past year, but CON utilized traditional resistance and cardiovascular exercise. All participants provided a fasted, resting blood sample and completed assessments of resting metabolic rate, body composition, muscle morphology, isometric mid-thigh pull strength, peak aerobic capacity, and a 3-minute maximal cycle ergometer sprint across two separate occasions (separated by 3-7 days). Blood samples were analyzed for testosterone, cortisol, and insulin-like growth factor-1. Compared to both REC and CON, one-way analysis of variance revealed ADV to possess lower body fat percentage (6.7-8.3%, p = 0.007), greater bone and non-bone lean mass (12.5-26.8%, p ≤ 0.028), muscle morphology characteristics (14.2-59.9%, p < 0.05), isometric strength characteristics (15.4-41.8%, p < 0.05), peak aerobic capacity (18.8-19.1%, p = 0.002), and 3-minute cycling performance (15.4-51.1%, p ≤ 0.023). No differences were seen between REC and CON, or between all groups for resting metabolic rate or hormone concentrations. These data suggest ADV possess several physiological advantages over REC and CON, whereas similar physiological characteristics were present in individuals who have been regularly participating in either CF or resistance and cardiovascular training for the past year.

PurposeThe purpose of this study was to compare early and late rapid torque parameters of the plantar flexors (PFs) in middle-aged (MM) and older (OM) males, and determine the effect of normalization to peak torque (PT) and muscle cross-sectional area (CSA).MethodsTwenty-nine healthy, MM (n = 14; 45 ± 2 yrs) and OM (n = 15; 65 ± 3 yrs) performed rapid, maximal isometric contractions of the PFs. PT, as well as rate of torque development and impulse during the early (0-50 ms; RTD0-50, IMP0-50) and late (100-200 ms; RTD100-200, IMP100-200) contraction phases were calculated. Torque at 50 (TQ50), 100 (TQ100), and 200 (TQ200) ms was also obtained. CSA and echo-intensity (EI) of the gastrocnemii were acquired via ultrasonography. Torque variables were normalized to PT and CSA. Rate of EMG rise (RER) for the medial gastrocnemius was calculated at 30, 50 and 75 ms.ResultsTQ100 (MM = 69.71 ± 16.85 vs. OM = 55.99 ± 18.54 Nm; p = 0.046), TQ200 (MM = 114.76 ± 26.79 vs. OM = 91.56 ± 28.10 Nm; p = 0.031), and IMP100-200 (MM = 4.79 ± 1.11 vs. OM = 3.83 ± 1.17 Nm·s; p = 0.032) were lower in OM. PT, TQ50, RTD0-50, IMP0-50, RTD100-200, RER, CSA, and EI were similar between groups (p > 0.05). No differences were found for normalized torque variables (p > 0.05). EI was moderately associated with normalized torque parameters only (r = -0.38 --0.45). RER, at 75 ms, was moderately correlated with early, absolute torque measures and rapid torque variables made relative to PT and CSA (r = 0.41 --0.64).ConclusionLate rapid torque parameters of the PFs were preferentially impaired in OM compared to MM, and PT as well as CSA appeared to mediate this result.

Abstract Background CrossFit® practitioners commonly track progress by monitoring their ability to complete a variety of standardized benchmark workouts within a typical class setting. However, objective assessment of progress is challenging because normative data does not currently exist for any of these benchmark workouts. Therefore, the purpose of this study was to develop normative values for five common benchmark workouts (i.e., Fran, Grace, Helen, Filthy-50 [F50], and Fight-Gone-Bad [FGB]). Methods Performance data from 133,857 male (M) and female (F) profiles located on a publicly available website were collected and sorted by sex (i.e., male [M] and female [F]) and competitive age classification (i.e., teen [T], individual [I], or masters [M]) and screened for errors. Subsequently, 10,000 valid profiles were randomly selected for analysis. Results Means and standard deviations were calculated for each category for Fran (IM 250 ± 106 s; IF 331 ± 181 s; MM 311 ± 138 s; MF 368 ± 138 s; TM 316 ± 136 s; and TF 334 ± 120 s), Grace (IM 180 ± 90 s; IF 213 ± 96 s; MM 213 ± 93 s; MF 238 ± 100 s; TM 228 ± 63 s; and TF 223 ± 69 s), Helen (IM 9.5 ± 1.9 min; IF 11.1 ± 2.4 min; MM 10.2 ± 2.0 min; MF 11.5 ± 2.3 min; TM 9.4 ± 1.6 min; and TF 12.7 ± 1.9 min), F50 (IM 24.4 ± 5.9 min; IF 27.3 ± 6.9 min; MM 26.7 ± 6.1 min; MF 28.2 ± 6.0 min; TM 25.9 ± 7.9 min; and TF 28.3 ± 8.1 min), and FGB (IM 335 ± 65 repetitions; IF 292 ± 62 repetitions; MM 311 ± 59 repetitions; MF 280 ± 54 repetitions; TM 279 ± 44 repetitions; and TF 238 ± 35 repetitions). These values were then used to calculate normative percentile (in deciles) values for each category within each workout. Separate, one-way analyses of variance revealed significant (p

The 2018 CrossFit Open (CFO) was the initial stage of an annual competition that consisted of five weekly workouts. Current evidence suggests that a variety of fitness parameters are important for progressing beyond this stage, but little is known about which are the most important. To examine relationships between CFO performance, experience, and physiological fitness, sixteen experienced (>2 years) athletes (30.7 ± 6.9 years, 171 ± 12 cm, 78.0 ± 16.2 kg) volunteered to provide information about their training and competitive history, and then complete a battery of physiological assessments prior to competing in the 2018 CFO. Athletes’ resting energy expenditure, hormone concentrations, body composition, muscle morphology, cardiorespiratory fitness, and isometric strength were assessed on two separate occasions. Spearman correlations demonstrated significant (p < 0.05) relationships between most variables and performance on each workout. Stepwise regression revealed competition experience (R2 = 0.31–0.63), body composition (R2 = 0.55–0.80), vastus lateralis cross-sectional area (R2 = 0.29–0.89), respiratory compensation threshold (R2 = 0.54–0.75), and rate of force development (R2 = 0.30–0.76) to be the most common predictors. Of these, body composition was the most important. These fitness parameters are known targets with established training recommendations. Though preliminary, athletes may use these data to effectively train for CFO competition.

This double-blind study examined effects of a protease enzyme blend (Prohydrolase®) added to whey protein on post-resistance exercise aminoacidemia and intramuscular anabolic signaling were investigated in ten resistance-trained males. Participants completed 4 sets of 8−10 repetitions in the leg press and leg extension exercises at 75% of 1-repetition maximum. Participants then consumed either 250 mg of Prohydrolase® + 26 g of whey protein (PW), 26 g whey alone (W), or non-nutritive control (CON) in counterbalanced order. Blood samples were obtained prior to exercise (baseline) and then immediately-post (IP), 30-, 60-, 90-, 120-, and 180-min post-exercise. Muscle biopsies were taken at baseline, 1-h (1H), and 3-h (3H) post-exercise. Phosphorylation of AKTSer437 was decreased (3H only: p < 0.001), mTORSer2448 was increased (1H: p = 0.025; 3H: p = 0.009), and p70S6KThr412 remained unchanged similarly for each condition. Plasma leucine, branch-chained amino acids, and essential amino acid concentrations for PW were significantly higher than CON (p < 0.05) at 30 min and similar to W. Compared to IP, PW was the only treatment with elevated plasma leucine levels at 30 min (p = 0.007; ∆ = 57.8 mmol/L, 95% Confidence Interval (CI): 20.0, 95.6) and EAA levels at 180 min (p = 0.003; ∆ = 179.1 mmol/L, 95% CI: 77.5, 280.7). Area under the curve amino acid analysis revealed no differences between PW and W. While no different than W, these data indicate that PW was the only group to produce elevated amino acid concentrations 30-min and 180-min post-ingestion.

Resistance training may differentially affect morphological adaptations along the length of uni-articular and bi-articular muscles. The purpose of this study was to compare changes in muscle morphology along the length of the rectus femoris (RF) and vastus lateralis (VL) in response to resistance training. Following a 2-wk preparatory phase, 15 resistance-trained men (24.0 ± 3.0 y, 90.0 ± 13.8 kg, 174.9 ± 20.7 cm) completed pre-training (PRE) assessments of muscle thickness (MT), pennation angle (PA), cross-sectional area (CSA), and echo-intensity in the RF and VL at 30, 50, and 70% of each muscle's length; fascicle length (FL) was estimated from respective measurements of MT and PA within each muscle and region. Participants then began a high intensity, low volume (4 x 3-5 repetitions, 3min rest) lower-body resistance training program, and repeated all PRE-assessments after 8 weeks (2 d ∙ wk-1) of training (POST). Although three-way (muscle [RF, VL] x region [30, 50, 70%] x time [PRE, POST]) repeated measures analysis of variance did not reveal significant interactions for any assessment of morphology, significant simple (muscle x time) effects were observed for CSA (p = 0.002) and FL (p = 0.016). Specifically, average CSA changes favored the VL (2.96 ± 0.69 cm2, p < 0.001) over the RF (0.59 ± 0.20 cm2, p = 0.011), while significant decreases in average FL were noted for the RF (-1.03 ± 0.30 cm, p = 0.004) but not the VL (-0.05 ± 0.36 cm, p = 0.901). No other significant differences were observed. The findings of this study demonstrate the occurrence of non-homogenous adaptations in RF and VL muscle size and architecture following 8 weeks of high-intensity resistance training in resistance-trained men. However, training does not appear to influence region-specific adaptations in either muscle.

Ultrasonography of the lower body typically encompasses supine rest due to fluid shifts affecting tissue size and composition. However, vastus lateralis (VL) examination is completed in the lateral recumbent position, and this positional change may influence morphology and its ability to predict function. This study aimed to examine the effect of position on VL morphology and its relationship with lower-body performance. Cross-sectional area (CSA), muscle thickness (MT), pennation angle (PA), echo intensity (UnCorEI), subcutaneous adipose tissue thickness (SFT), and echo intensity corrected for SFT (CorEI) were assessed in 31 resistance-trained males (23.0 ± 2.1 yrs; 1.79 ± 0.08 m; 87.4 ± 11.7 kg) immediately after transitioning from standing to supine (IP), after 15 min of standing (ST), and after 15 min of rest in three recumbent positions: supine (SUP), dominant lateral recumbent (DLR), non-dominant lateral recumbent (NDLR). Participants also completed unilateral vertical jumps, isometric/isokinetic tests, and a one-repetition maximum leg press. CSA, MT, PA, and SFT were greater in ST compared to NDLR, DLR, and SUP (p < 0.05). CSA, UnCorEI, and CorEI were different between recumbent positions; however no differences were observed for MT, PA, and SFT. Different magnitudes of relationships were observed between muscle morphological characteristics measured after rest in different positions and performance variables. Muscle morphology in IP generally appears to be the best predictor of performance for most variables, although utilizing the NDLR and DLR positions may provide comparable results, whereas morphology measured in ST and SUP provide weaker relationships with physical performance. IP also requires less time and fewer requirements on the technician and subject, thus researchers should consider this positioning for VL examination.

To evaluate the feasibility of on-site collection of subjective anxiety, autonomic nervous system activity, and salivary catecholamines surrounding high-intensity functional training (HIFT) competition, ten experienced HIFT competitors completed baseline assessments of anxiety and heart rate variability (HRV). Then, in two consecutive weeks (Workout 1 and 2) within the competition, HRV was recorded and examined in 5-min segments prior to exercise (PRE) and across a 30-min period after competitors completed their choice of the prescribed or scaled each workout. Subjective anxiety ratings and saliva samples were collected at PRE and immediately-(IP), 30-min (30P), and 60-min post-exercise (60P). Saliva samples were analyzed for concentrations of epinephrine and norepinephrine. Generalized linear mixed models with repeated measures revealed significant (p < 0.05) differences between workouts for all measures. Compared to Workout 1, anxiety (~50%), epinephrine (173−340%), norepinephrine (29−234%) were greater in Workout 2 and various HRV-derived indices were more depressed. Additionally, some HRV-derived indices appeared to be modulated (p < 0.05) by competitive level and sex at PRE and throughout the 30-min recovery period. These data suggest that autonomic activity may differ between the competitive and laboratory settings, and that the response may be further modulated by the workout’s design, the athlete’s sex, and competitive level.

To determine the agreement between the Open Barbell (OB) and Tendo weightlifting analyzer (TWA) for measuring barbell velocity, eleven men (19.4 ± 1.0 y) performed one set of 2−3 repetitions at four sub-maximal percentage loads, [i.e., 30, 50, 70, and 90% one-repetition maximum (1RM)] in the back (BS) and front squat (FS) exercises. During each repetition, peak and mean barbell velocity were recorded by OB and TWA devices, and the average of the 2−3 repetitions was used for analyses. Although the repeated measures analysis of variance revealed significantly (p ≤ 0.005) greater peak and mean velocity scores from OB across all intensities, high intraclass correlation coefficients (ICC2,K = 0.790−0.998), low standard error of measurement (SEM2,K = 0.040−0.119 m·s−1), and coefficients of variation (CV = 2−4%) suggested consistency between devices. Positive (r = 0.491−0.949) Pearson correlations between averages and differences (between devices) in peak velocity, as well as associated Bland-Altman plots, showed greater differences occurred as the velocity increased, particularly at low-moderate intensity loads. OB consistently provides greater barbell velocity scores compared to TWA, and the differences between devices were more apparent as the peak velocity increased with low-to-moderate loads. Strength coaches and athletes may find better agreement between devices if the mean velocity scores are only considered.

Background: Specific mood states were examined during the CrossFit Open, a consecutive 5-week fitness competition involving five separate CrossFit® workouts, to determine whether the unique design or strenuous workouts of the competition resulted in acute and/or chronic mood state alterations. Methods: Participants (n = 8) completed the Profile of Mood States (POMS) questionnaire one-week prior to the competition (baseline), prior to (PRE), immediately post (IP), 30-min post- (30P) and 60-min post-workout (60P) each week. Tension, depression, anger, confusion, fatigue and vigor were derived from the POMS, as was Total Mood Disturbance (TMD) and an Energy Index (EI). Results: Workout intensity exceeded 93% HRmax each week. No differences were observed between baseline and PRE-workout mood states across weeks, indicating little effect of the unique competition design. Significant (week x time) interactions were observed for TMD (p = 0.037), EI (p = 0.038) and fatigue (p = 0.005). Acute mood state fluctuations were consistent across each week, where mood states improved to and beyond PRE values 60-min post-workout. Conclusions: In competitors, the differences in workout design between each week did not influence mood states. This may be related to adaptation to this style of training, while the acute mood state alterations are likely due to the workout intensity.

To determine the salivary steroid response to high-intensity functional training (HIFT) competition workouts, saliva samples were collected from ten recreationally trained male and female competitors during a 5-week (WK1–WK5) international competition. Competitors arrived at their local affiliate and provided samples prior to (PRE) their warm-up, immediately (IP), 30-min (30P), and 60-min (60P) post-exercise. Samples were analyzed for concentrations of testosterone (T), cortisol (C), and their ratio (TC). Generalized linear mixed models with repeated measures revealed significant main effects for time (p < 0.001) for T, C, and TC. Compared to PRE-concentrations, elevated (p < 0.05) T was observed at IP on WK2–WK5 (mean difference: 135–511 pg·mL−1), at 30P on WK3 (mean difference: 81.0 ± 30.1 pg·mL−1) and WK5 (mean difference: 56.6 ± 22.7 pg·mL−1), and at 60P on WK3 (mean difference: 73.5 ± 29.7 pg·mL−1) and WK5 (mean difference: 74.3 ± 28.4 pg·mL−1). Compared to PRE-concentrations, elevated (p < 0.05) C was noted on all weeks at IP (mean difference: 9.3–15.9 ng·mL−1) and 30P (mean difference: 6.0–19.9 ng·mL−1); significant (p < 0.006) elevations were noted at 60P on WK1 (mean difference: 9.1 ± 3.0 ng·mL−1) and WK5 (mean difference: 12.8 ± 2.9 ng·mL−1). Additionally, TC was significantly reduced from PRE-values by 61% on WK1 at 60P (p = 0.040) and by 80% on WK5 at 30P (p = 0.023). Differences in T, C, and TC were also observed between weeks at specific time points. Although each workout affected concentrations in T, C, and/or the TC ratio, changes appeared to be modulated by the presence of overload and workout duration. During periods of elevated training or competition, athletes and coaches may consider monitoring these hormones for consistency and as a means of assessing workout difficulty.

The purpose of this investigation was to compare the effect of two commonly used therapeutic modalities a.) neuromuscular electrical stimulation (NMES) and b.) cold water immersion (CWI) on circulating tumor necrosis factor alpha (TNF-α) and monocyte TNF-α receptor (TNFR1) expression following intense acute resistance exercise and subsequent recovery. Thirty (n=30) resistance trained men (22.5 ± 2.7 y) performed an acute heavy resistance exercise protocol on three consecutive days followed by one of three recovery methods (CON, NMES, and CWI). Circulating TNF-α levels were assayed and TNFR1 expression on CD14+ monocytes was measured by flow cytometry measured PRE, immediately post (IP), 30-minutes post (30M), 24 hours post (24H), and 48 hours post (48H) exercise. Circulating TNF-α was elevated at IP (p = 0.001) and 30M (p = 0.005) and decreased at 24H and 48H recovery from IP in CON (p = 0.015) and CWI (p = 0.011). TNF-α did not significantly decrease from IP during recovery in NMES. TNFR1 expression was elevated (p < 0.001) at 30M compared to PRE and all other time points. No significant differences between groups were observed in TNFR1 expression. During recovery (24H, 48H) from muscle damaging exercise, NMES treatment appears to prevent the decline in circulating TNF-α observed during recovery in those receiving no treatment or CWI.

Objective. To examine the endocrine response to a bout of heavy resistance exercise following acute β-hydroxy-β-methylbutyrate free acid (HMB-FA) ingestion. Design. Twenty resistance trained men were randomized and consumed either 1 g of HMB-FA (BetaTor) or placebo (PL) 30 min prior to performing an acute heavy resistance exercise protocol. Blood was obtained before (PRE), immediately after (IP), and 30 min after exercise (30P). Circulating concentrations of testosterone, growth hormone (GH), insulin-like growth factor (IGF-1), and insulin were assayed. Data were analyzed with a repeated measures ANOVA and area under the curve (AUC) was analyzed by the trapezoidal rule. Results. The resistance exercise protocol resulted in significant elevations from PRE in testosterone P