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Eva Piatrikova, Ana C. Sousa, Javier T. Gonzalez, and Sean Williams

Purpose: To assess the concurrent and predictive validity of the 3-minute all-out test (3MT) against conventional methods (CM) of determining critical speed (CS) and curvature constant (D′) and to examine the test–retest reliability of the 3MT in highly trained swimmers. Methods: Thirteen highly trained swimmers (age 16 [2] y, weight 64.7 [8.5] kg, height 1.76 [0.07] m) completed 4 time trials and two 3MTs over 2 wk. The distance–time (DT) and speed–1/time (1/T) models were used to determine CS and D′ from 4 time trials. CS3MT and D3MT were determined as the mean speed in the final 30 s of 3MT and as the speed–time integral above CS, respectively. Results: CS3MT (1.33 [0.06] m·s−1) did not differ from CSCM (1.33 [0.06] m·s−1, P > .05) and correlated nearly perfectly with CSCM (r = .95, P < .0001). D3MT (19.50 [3.52] m) was lower than DDT (23.30 [6.24] m, P < .05) and D1/T (22.15 [5.75] m, P = .09). Correlations between D3MT and DCM were very large (r = .79, P = .002). CS and D′ between the two 3MT trials were not different (CS mean change = −0.009 m·s−1, P = .102; D′ mean change = 0.82 m, P = .221). Correlations between the two 3MT trials were nearly perfect and very large for CS (r = .97) and D′ (r = .87, P < .05), respectively, with coefficients of variation of 0.9% for CS and 9.1% for D′. Conclusion: The 3MT is a valid protocol for estimation of CS and produces high test–retest reliability for CS and D′ in highly trained swimmers.

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Edward A. Gray, Thomas A. Green, James A. Betts, and Javier T. Gonzalez

During short-term recovery, postexercise glucose–fructose coingestion can accelerate total glycogen repletion and augment recovery of running capacity. It is unknown if this advantage translates to cycling, or to a longer (e.g., overnight) recovery. Using two experiments, the present research investigated if postexercise glucose–fructose coingestion augments exercise capacity following 4-hr (short experiment; n = 8) and 15-hr (overnight experiment; n = 8) recoveries from exhaustive exercise in trained cyclists, compared with isocaloric glucose alone. In each experiment, a glycogen depleting exercise protocol was followed by a 4-hr recovery, with ingestion of 1.5 or 1.2 g·kg−1·hr−1 carbohydrate in the short experiment (double blind) and the overnight experiment (single blind), respectively. Treatments were provided in a randomized order using a crossover design. Four or fifteen hours after the glycogen depletion protocol, participants cycled to exhaustion at 70% W max or 65% W max in the short experiment and the overnight experiment, respectively. In both experiments there was no difference in substrate oxidation or blood glucose and lactate concentrations between treatments during the exercise capacity test (trial effect, p > .05). Nevertheless, cycling capacity was greater in glucose + fructose versus glucose only in the short experiment (28.0 ± 8.4 vs. 22.8 ± 7.3 min, d = 0.65, p = .039) and the overnight experiment (35.9 ± 10.7 vs. 30.6 ± 9.2 min, d = 0.53, p = .026). This is the first study to demonstrate that postexercise glucose–fructose coingestion enhances cycling capacity following short-term (4 hr) and overnight (15 hr) recovery durations. Therefore, if multistage endurance athletes are ingesting glucose for rapid postexercise recovery then fructose containing carbohydrates may be advisable.

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Benjamin J. Narang, Greg Atkinson, Javier T. Gonzalez, and James A. Betts

The analysis of time series data is common in nutrition and metabolism research for quantifying the physiological responses to various stimuli. The reduction of many data from a time series into a summary statistic(s) can help quantify and communicate the overall response in a more straightforward way and in line with a specific hypothesis. Nevertheless, many summary statistics have been selected by various researchers, and some approaches are still complex. The time-intensive nature of such calculations can be a burden for especially large data sets and may, therefore, introduce computational errors, which are difficult to recognize and correct. In this short commentary, the authors introduce a newly developed tool that automates many of the processes commonly used by researchers for discrete time series analysis, with particular emphasis on how the tool may be implemented within nutrition and exercise science research.

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Javier T. Gonzalez, Martin J. Barwood, Stuart Goodall, Kevin Thomas, and Glyn Howatson

Unaccustomed eccentric exercise using large muscle groups elicits soreness, decrements in physical function and impairs markers of whole-body insulin sensitivity; although these effects are attenuated with a repeated exposure. Eccentric exercise of a small muscle group (elbow flexors) displays similar soreness and damage profiles in response to repeated exposure. However, it is unknown whether damage to small muscle groups impacts upon whole-body insulin sensitivity. This pilot investigation aimed to characterize whole-body insulin sensitivity in response to repeated bouts of eccentric exercise of the elbow flexors. Nine healthy males completed two bouts of eccentric exercise separated by 2 weeks. Insulin resistance (updated homeostasis model of insulin resistance, HOMA2-IR) and muscle damage profiles (soreness and physical function) were assessed before, and 48 h after exercise. Matsuda insulin sensitivity indices (ISIMatsuda) were also determined in 6 participants at the same time points as HOMA2-IR. Soreness was elevated, and physical function impaired, by both bouts of exercise (both p < .05) but to a lesser extent following bout 2 (time x bout interaction, p < .05). Eccentric exercise decreased ISIMatsuda after the first but not the second bout of eccentric exercise (time x bout interaction p < .05). Eccentric exercise performed with an isolated upper limb impairs whole-body insulin sensitivity after the first, but not the second, bout.

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Javier Raya-González, Aaron T. Scanlan, María Soto-Célix, Alejandro Rodríguez-Fernández, and Daniel Castillo

Purpose: To examine the effects of acute caffeine supplementation on physical performance during fitness testing and activity during simulated games in basketball players. Methods: A double-blind, counterbalanced, randomized, crossover study design was followed. A total of 14 professional male basketball players ingested a placebo (sucrose) and caffeine (6 mg·kg−1 of body mass) in liquid form prior to completing 2 separate testing sessions. Each testing session involved completion of a standardized 15-minute warm-up followed by various fitness tests including 20-m sprints, countermovement jumps, Lane Agility Drill trials, and a repeated-sprint-ability test. Following a 20-minute recovery, players completed 3 × 7-minute 5-vs-5 simulated periods of full-court basketball games, each separated by 2 minutes of recovery. Local positioning system technology was used to measure player activity during games. Players completed a side-effects questionnaire 12 to 14 hours after testing. Results: Players experienced significant (P < .05), moderatevery large (effect size = −2.19 to 0.89) improvements in 20-m sprint, countermovement jump, Lane Agility Drill, and repeated-sprint-ability performance with caffeine supplementation. However, external workloads completed during simulated games demonstrated nonsignificant, trivialsmall (effect size = −0.23 to 0.12) changes between conditions. In addition, players reported greater (P < .05) insomnia and urine output after caffeine ingestion. Conclusions: Acute caffeine supplementation could be effective to improve physical performance during tests stressing fitness elements important in basketball. However, acute caffeine supplementation appears to exert no meaningful effects on the activity completed during simulated basketball games and may promote sleep disturbances and exert a diuretic effect when taken at 6 mg·kg−1 of body mass in professional players.

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Eva Piatrikova, Nicholas J. Willsmer, Ana C. Sousa, Javier T. Gonzalez, and Sean Williams

Purpose: To monitor physiological, technical, and performance responses to individualized high-intensity interval training (HIIT) prescribed using the critical speed (CS) and critical stroke rate (CSR) concepts in swimmers completing a reduced training volume program (≤30 km·wk−1) for 15 weeks. Methods: Over the 15-week period, 12 highly trained swimmers (age 16 [1] y, height 179 [8] cm, weight 66 [8] kg) completed four 3-minute all-out tests to determine CS and the finite capacity to work above CS (D′), and four 200-m tests at CS to establish a CSR estimate. Combining CS and D′, 2 HIIT sessions designed as 5 × 3-minute intervals depleting 60% of D′ and 3 × 3.5-minute intervals depleting 80% of D′ were prescribed once per week, respectively. An additional HIIT session was prescribed using CS and CSR as 10 × 150 m or 200 m at CS with 2 cycles per minute lower stroke rate than the CSR estimate. Additional monitored variables included peak speed, average speed for 150 seconds (speed150s) and 180 seconds (speed180s), competition performance and stroke length (SL), stroke count (SC), and stroke index (SI) adopted at CS. Results: At the end of the intervention, swimmers demonstrated faster CS (mean change ± 90% confidence limits: +5.4 ± 1.6%), speed150s (+2.5 ± 0.9%), speed180s (+3.0 ± 0.9%), and higher stroke rate (+6.4 ± 3.0%) and stroke index (+4.2 ± 3.6%). D′ was reduced (−25.2 ± 7.5%), whereas peak speed, SL, and SC changed only trivially. The change in the swimmers’ personal best times in the first and second main event was −1.2 ± 1.3% and −1.6 ± 0.9%, respectively. Conclusion: HIIT prescribed based on the CS and CSR concepts was associated with improvements in several physiological, technical, and performance parameters in highly trained swimmers while utilizing time- and resource-efficient approach. This was achieved despite a ≥25% reduction in training volume.

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Oliver J. Chrzanowski-Smith, Robert M. Edinburgh, Mark P. Thomas, Aaron Hengist, Sean Williams, James A. Betts, and Javier T. Gonzalez

This study explored lifestyle and biological determinants of peak fat oxidation (PFO) during cycle ergometry, using duplicate measures to account for day-to-day variation. Seventy-three healthy adults (age range: 19–63 years; peak oxygen consumption [V˙O2peak]:42.4[10.1]ml·kgBM1·min1; n = 32 women]) completed trials 7–28 days apart that assessed resting metabolic rate, a resting venous blood sample, and PFO by indirect calorimetry during an incremental cycling test. Habitual physical activity (combined heart rate accelerometer) and dietary intake (weighed record) were assessed before the first trial. Body composition was assessed 2–7 days after the second identical trial by dual-energy X-ray absorptiometry scan. Multiple linear regressions were performed to identify determinants of PFO (mean of two cycle tests). A total variance of 79% in absolute PFO (g·min−1) was explained with positive coefficients for V˙O2peak (strongest predictor), FATmax (i.e the % of V˙O2peak that PFO occurred at), and resting fat oxidation rate (g·min−1), and negative coefficients for body fat mass (kg) and habitual physical activity level. When expressed relative to fat-free mass, 64% of variance in PFO was explained: positive coefficients for FATmax (strongest predictor), V˙O2peak, and resting fat oxidation rate, and negative coefficients for male sex and fat mass. This duplicate design revealed that biological and lifestyle factors explain a large proportion of variance in PFO during incremental cycling. After accounting for day-to-day variation in PFO, V˙O2peak and FATmax were strong and consistent predictors of PFO.

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Campbell Menzies, Michael Wood, Joel Thomas, Aaron Hengist, Jean-Philippe Walhin, Robbie Jones, Kostas Tsintzas, Javier T. Gonzalez, and James A. Betts

The timing of carbohydrate ingestion and how this influences net muscle glycogen utilization and fatigue has only been investigated in prolonged cycling. Past findings may not translate to running because each exercise mode is distinct both in the metabolic response to carbohydrate ingestion and in the practicalities of carbohydrate ingestion. To this end, a randomized, cross-over design was employed to contrast ingestion of the same sucrose dose either at frequent intervals (15 × 5 g every 5 min) or at a late bolus (1 × 75 g after 75 min) during prolonged treadmill running to exhaustion in six well-trained runners (V˙O2max 61 ± 4 ml·kg−1·min−1). The muscle glycogen utilization rate was lower in every participant over the first 75 min of running (Δ 0.51 mmol·kg dm−1·min−1; 95% confidence interval [−0.02, 1.04] mmol·kg dm−1·min−1) and, subsequently, all were able to run for longer when carbohydrate had been ingested frequently from the start of exercise compared with when carbohydrate was ingested as a single bolus toward the end of exercise (105.6 ± 3.0 vs. 96.4 ± 5.0 min, respectively; Δ 9.3 min, 95% confidence interval [2.8, 15.8] min). A moderate positive correlation was apparent between the magnitude of glycogen sparing over the first 75 min and the improvement in running capacity (r = .58), with no significant difference in muscle glycogen concentrations at the point of exhaustion. This study indicates that failure to ingest carbohydrates from the outset of prolonged running increases reliance on limited endogenous muscle glycogen stores—the ergolytic effects of which cannot be rectified by subsequent carbohydrate ingestion late in exercise.

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Eva Piatrikova, Nicholas J. Willsmer, Marco Altini, Mladen Jovanović, Lachlan J.G. Mitchell, Javier T. Gonzalez, Ana C. Sousa, and Sean Williams

Purpose: First, to examine whether heart rate variability (HRV) responses can be modeled effectively via the Banister impulse-response model when the session rating of perceived exertion (sRPE) alone, and in combination with subjective well-being measures, are utilized. Second, to describe seasonal HRV responses and their associations with changes in critical speed (CS) in competitive swimmers. Methods: A total of 10 highly trained swimmers collected daily 1-minute HRV recordings, sRPE training load, and subjective well-being scores via a novel smartphone application for 15 weeks. The impulse-response model was used to describe chronic root mean square of the successive differences (rMSSD) responses to training, with sRPE and subjective well-being measures used as systems inputs. Changes in CS were obtained from a 3-minute all-out test completed in weeks 1 and 14. Results: The level of agreement between predicted and actual HRV data was R 2 = .66 (.25) when sRPE alone was used. Model fits improved in the range of 4% to 21% when different subjective well-being measures were combined with sRPE, representing trivial-to-moderate improvements. There were no significant differences in weekly group averages of log-transformed (Ln) rMSSD (P = .34) or HRV coefficient of variation of Ln rMSSD (P = .12); however, small-to-large changes (d = 0.21–1.46) were observed in these parameters throughout the season. Large correlations were observed between seasonal changes in HRV measures and CS (changes in averages of Ln rMSSD: r = .51, P = .13; changes in coefficient of variation of Ln rMSSD: r = −.68, P = .03). Conclusion: The impulse-response model and data collected via a novel smartphone application can be used to model HRV responses to swimming training and nontraining-related stressors. Large relationships between seasonal changes in measured HRV parameters and CS provide further evidence for incorporating a HRV-guided training approach.

Open access

James A. Betts, Javier T. Gonzalez, Louise M. Burke, Graeme L. Close, Ina Garthe, Lewis J. James, Asker E. Jeukendrup, James P. Morton, David C. Nieman, Peter Peeling, Stuart M. Phillips, Trent Stellingwerff, Luc J.C. van Loon, Clyde Williams, Kathleen Woolf, Ron Maughan, and Greg Atkinson