Influence of recovery manipulation after hyperlactemia induction on the lactate minimum intensity

Determination of speed and assessment of conditioning in horses submitted to a lactate minimum test-alternative approaches

The maximal lactate steady state (MLSS) is a well-known gold standard method for determining the aerobic capacity of athletic horses. Owing to its high cost and complex execution, there is a search for standardized exercise tests that can predict this value in a single session. One of the methods described for this purpose is the lactate minimum test (LMT), which could be more accurate despite being adequate to predict MLSS. This study aimed to examine the impact of training on the speed corresponding to lactate minimum speed (LMS) and to apply new mathematical methods to evaluate the fitness level of horses based on the curve obtained by the LMT. Ten Arabian horses underwent a 6-week training program based on LMS calculated by second-degree polynomial regression (LMSP). In addition, the LMS was also determined by visual inspection (LMSV), bi-segmented linear regression (LMSBI) and spline regression (LMSS). From the curve obtained during the LMT, it was possible to calculate angles α, β and ω, as well as the total area under the curve (AUCTOTAL) before (AUCPRELMS) and after (AUCPOSLMS) the LMS. The methods for determining the LMS were evaluated by ANOVA, intraclass correlation coefficient (ICC) and effect size (ES) by Cohen's d test. The Pearson correlation coefficient (r) between the proposed LMS determination methods and other mathematical methods was also calculated. Despite showing a good correlation (ICC >0.7), the LMS determination methods differed from each other (p < 0.05), albeit without a significant difference resulting from conditioning. There were reductions in α:β ratio, angle α, and AUCPOSTLMS, with the latter indicating lower lactate accumulation in the incremental phase of LMT after conditioning, in addition to an improvement in the animals' aerobic capacity. Considering that the most common methods for determining the LMS are applicable yet with low sensitivity for conditioning assessment, the approaches proposed herein can aid in analyzing the aerobic capacity of horses subjected to LMT. The mathematical models presented in this paper have the potential to be applied in human lactate-guided training program trials with a comparable study basis.

Profiling the Aerobic Window of Horses in Response to Training by Means of a Modified Lactate Minimum Speed Test: Flatten the Curve

There is a great need for objective external training load prescription and performance capacity evaluation in equestrian disciplines. Therefore, reliable standardised exercise tests (SETs) are needed. Classic SETs require maximum intensities with associated risks to deduce training loads from pre-described cut-off values. The lactate minimum speed (LMS) test could be a valuable alternative. Our aim was to compare new performance parameters of a modified LMS-test with those of an incremental SET, to assess the effect of training on LMS-test parameters and curve-shape, and to identify the optimal mathematical approach for LMS-curve parameters. Six untrained standardbred mares (3–4 years) performed a SET and LMS-test at the start and end of the 8-week harness training. The SET-protocol contains 5 increments (4 km/h; 3 min/step). The LMS-test started with a 3-min trot at 36–40 km/h [until blood lactate (BL) > 5 mmol/L] followed by 8 incremental steps (2 km/h; 3 min/step). The maximum lactate steady state estimation (MLSS) entailed >10 km run at the LMS and 110% LMS. The GPS, heartrate (Polar^®), and blood lactate (BL) were monitored and plotted. Curve-parameters (R core team, 3.6.0) were (SET) VLa₁._5/2/4 and (LMS-test) area under the curve (AUC_>/<LMS), LMS and Aerobic Window (AW) via angular vs. threshold method. Statistics for comparison: a paired t-test was applied, except for LMS: paired Wilcoxon test; (p < 0.05). The Pearson correlation (r > 0.80), Bland-Altman method, and ordinary least products (OLP) regression analyses were determined for test-correlation and concordance. Training induced a significant increase in VLa₁._5/2/4. The width of the AW increased significantly while the AUC_</>LMS and LMS decreased post-training (flattening U-curve). The LMS BL steady-state is reached earlier and maintained longer after training. BL_max was significantly lower for LMS vs. SET. The 40° angular method is the optimal approach. The correlation between LMS and V_MLSS was significantly better compared to the SET. The VLa₄ is unreliable for equine aerobic capacity assessment. The LMS-test allows more reliable individual performance capacity assessment at lower speed and BL compared to SETs. The LMS-test protocol can be further adapted, especially post-training; however, inducing modest hyperlactatemia prior to the incremental LMS-stages and omitting inclusion of a per-test recovery contributes to its robustness. This LMS-test is a promising tool for the development of tailored training programmes based on the AW, respecting animal welfare.

Effects of an experimental taper period on male and female swimmers

BACKGROUND

This study investigated the possible influence of the gender on the responses of swimmers during a taper period (TP).

METHODS

Ten males (19 ± 3 years and 73.5 ± 7.8 kg) and ten females (17 ± 2 years and 54.7 ± 7.2 kg) swimmers were submitted to a 12-week training, followed by three weeks of the TP. Before and after the TP we evaluated the performance at 100 m freestyle, stroke parameters and lactacidemic responses; lactate minimum intensity (LMI) and stroke parameters associated with LMI and the propulsive force in tethered swimming. TP consisted of 14 sessions with mean volume 2,253 ± 1,213 m•session-1 at an intensity below than the LMI, 1,730 ± 327 m•session-1 at an intensity near the LMI and 1,530 ± 1,019 m•session-1 at an intensity above the LMI.

RESULTS

Significant effects of the genders were observed for LMI and stroke parameters (p-value < 0.001 and η2 > 0.52 [large]) and propulsive force (p-value = 0.001; η2 = 0.59 [large]). However, no significant effects of the TP were identified in the performance of the 100 m freestyle (p-value = 0.66; η2 = 0.006 [small]), propulsive force (p-value > 0.63; η2 < 0.006 [small]), aerobic parameters (LMI: p-value = 0.32 and η2 = 0.03 [small]) and mechanical parameters (p-value > 0.23; η2 = 0.01 [small]). Nonetheless, the peak blood lactate concentrations were improved after TP (p-value = 0.014; η2 = 0.16 [large]), without significant interactions (p-value = 0.38; η2 = 0.02 [small]), as well as the mechanical parameters during maximum 100 m freestyle (p-value < 0.04 and η2 > 0.10 [medium]).

CONCLUSIONS

Hence, men and women presenting significantly different values in the age group studied, the responses observed after the TP investigated were the same independent of gender.

Relationships Between Aerobic and Anaerobic Parameters With Game Technical Performance in Elite Goalball Athletes

Our aims were to compare physiological parameters from the laboratory environment (LaB) and simulated goalball games (GaM), test relationships between physiological parameters in the laboratory and game technical performance (GTP), and examine the associations between physiological and technical responses during games. Seven elite athletes from the Brazilian National Team performed in LaB environment; (i) an incremental test to determine peak oxygen consumption (O_2PEAK), its corresponding speed, and peak blood lactate concentration and (ii) submaximal and supramaximal efforts to estimate maximal anaerobic contribution (AnC). In GaM condition, simulated games were also performed to determine physiological responses throughout the game, and to analyze the GTP (number of throws, defenses, recovery, and density of actions). No correlations (unclear) were found between laboratory and games analyses for O_2PEAK [47.3 (17.2) vs. 25.8 (18.2) mL⋅Kg^-1⋅min^-1], peak blood lactate concentrations [10.2 (5.4) vs. 2.0 (0.7) mM], and total AnC [21.0 (14.0) vs. 4.8 (6.1) mL Kg^-1]. O_2PEAK in the laboratory condition presented very likely correlations with throw and recovery frequency in games (r = -0.87 and confidence interval [CI] = 0.41; r = -0.90 and CI = 0.35; respectively). Oxygen consumption remained above baseline while blood lactate concentration remained unchanged during the games. The very likely correlation between anaerobic alactic contribution and action density (r = 0.95 and CI = 0.25) highlights the importance of the alactic metabolism. In general, our study demonstrates that goalball can be characterized as a high-intensity intermittent effort, where athlete performance is based on aerobic metabolism predominance while determinant actions are supplied by the anaerobic alactic metabolism. Specifically, higher values of LaB vs. GaM highlighted the need for standardization of specific protocols for goalball evaluation, mainly for the reproduction of ecologically valid values. In addition, O_2PEAK correlated with recovery frequency in the LaB condition, demonstrating that passive or low-intensity recovery between actions is fundamental to maintain performance.

Accuracy of a Modified Lactate Minimum Test and Reverse Lactate Threshold Test to Determine Maximal Lactate Steady State

Wahl, P, Manunzio, C, Vogt, F, Strütt, S, Volmary, P, Bloch, W, and Mester, J. Accuracy of a modified lactate minimum test and reverse lactate threshold test to determine maximal lactate steady state. J Strength Cond Res 31(12): 3489-3496, 2017-This study evaluated the accuracy of a modified lactate minimum test (mLMT), a modified reverse lactate threshold test (mRLT), compared with 2 established threshold concepts (onset of blood lactate accumulation [OBLA] and modified maximal deviation method [mDmax]) to determine power output at maximal lactate steady state (MLSS) in cycling. Nineteen subjects performed an mLMT, mRLT, graded exercise test (100 W start, +20 W every 3 minutes) and 3 or more constant-load tests of 30 minutes to determine power output at MLSS. The mLMT and mRLT both consisted of an initial lactate priming segment, followed by a short recovery phase. Afterward, the initial load of the subsequent incremental or reverse segment was calculated individually and was increased or decreased by 10 W every 90 seconds, respectively. The mean difference to MLSS was +2 ± 7 W (mLMT), +5 ± 10 W (mRLT), +9 ± 21 W (OBLA), and +6 ± 14 W (mDmax). The correlation between power output at MLSS and mLMT was highest (r = 0.99), followed by mRLT (r = 0.98), mDmax (r = 0.95), and OBLA (r = 0.90). Because of the higher accuracy of the mLMT and the mRLT to determine MLSS compared with OBLA and mDmax, we suggest both tests as valid and meaningful concepts to estimate power output at MLSS in one single test in moderately trained to well-trained athletes. Additionally, our modified tests provide anaerobic data and do not require detailed knowledge of the subjects' training status compared with previous LMT or RLT protocols.

The Lactate Minimum Test: Concept, Methodological Aspects and Insights for Future Investigations in Human and Animal Models

In 1993, Uwe Tegtbur proposed a useful physiological protocol named the lactate minimum test (LMT). This test consists of three distinct phases. Firstly, subjects must perform high intensity efforts to induce hyperlactatemia (phase 1). Subsequently, 8 min of recovery are allowed for transposition of lactate from myocytes (for instance) to the bloodstream (phase 2). Right after the recovery, subjects are submitted to an incremental test until exhaustion (phase 3). The blood lactate concentration is expected to fall during the first stages of the incremental test and as the intensity increases in subsequent stages, to rise again forming a “U” shaped blood lactate kinetic. The minimum point of this curve, named the lactate minimum intensity (LMI), provides an estimation of the intensity that represents the balance between the appearance and clearance of arterial blood lactate, known as the maximal lactate steady state intensity (iMLSS). Furthermore, in addition to the iMLSS estimation, studies have also determined anaerobic parameters (e.g., peak, mean, and minimum force/power) during phase 1 and also the maximum oxygen consumption in phase 3; therefore, the LMT is considered a robust physiological protocol. Although, encouraging reports have been published in both human and animal models, there are still some controversies regarding three main factors: (1) the influence of methodological aspects on the LMT parameters; (2) LMT effectiveness for monitoring training effects; and (3) the LMI as a valid iMLSS estimator. Therefore, the aim of this review is to provide a balanced discussion between scientific evidence of the aforementioned issues, and insights for future investigations are suggested. In summary, further analyses is necessary to determine whether these factors are worthy, since the LMT is relevant in several contexts of health sciences.

Lactate minimum underestimates the maximal lactate steady-state in swimming mice

The intensity of lactate minimum (LM) has presented a good estimate of the intensity of maximal lactate steady-state (MLSS); however, this relationship has not yet been verified in the mouse model. We proposed validating the LM protocol for swimming mice by investigating the relationship among intensities of LM and MLSS as well as differences between sexes, in terms of aerobic capacity. Nineteen mice (male: 10, female: 9) were submitted to the evaluation protocols for LM and MLSS. The LM protocol consisted of hyperlactatemia induction (30 s exercise (13% body mass (bm)), 30 s resting pause and exhaustive exercise (13% bm), 9 min resting pause and incremental test). The LM underestimated MLSS (mice: 17.6%; male: 13.5%; female: 21.6%). Pearson's analysis showed a strong correlation among intensities of MLSS and LM (male (r = 0.67, p = 0.033); female (r = 0.86, p = 0.003)), but without agreement between protocols. The Bland-Altman analysis showed that bias was higher for females (1.5 (0.98) % bm; mean (MLSS and LM): 4.4%-6.4% bm) as compared with males (0.84 (1.24) % bm; mean (MLSS and LM): 4.5%-7.5% bm). The error associated with the estimated of intensity for males was lower when compared with the range of means for MLSS and LM. Therefore, the LM test could be used to determine individual aerobic intensity for males (considering the bias) but not females. Furthermore, the females supported higher intensities than the males. The differences in body mass between sexes could not explain the higher intensities supported by the females.

Blood lactate minimum of rats during swimming test using three incremental stages

AbstractThe purpose of this study was to determine the lactate minimum intensity (LMI) by swimming LACmintest using three incremental stages (LACmintest3) and to evaluate its sensitivity to changes in aerobic fitness (AF). Twenty Wistar rats performed: LACmintest3 (1): induction of hyperlactacidemia and incremental phase (4%, 5% and 6.5% of bw); Constant loads tests on (2) and above (3) the LMI. Half of the animals were subjected to training with the individual LMI and the tests were performed again. The mean exercise load in LACmintest3 was 5.04 ± 0.13% bw at 5.08 ± 0.55 mmol L-1 blood lactate minimum (BLM). There was a stabilize and disproportionate increase of blood lactate in tests 2 and 3, respectively. After the training period, the mean BLM was lower in the trained animals. The LACmintest3 seems to be a good indicator of LMI and responsive to changes in AF in rats subjected to swim training.

Anaerobic and aerobic performances in elite basketball players

The purpose of this study was to propose a specific lactate minimum test for elite basketball players considering the: Running Anaerobic Sprint Test (RAST) as a hyperlactatemia inductor, short distances (specific distance, 20 m) during progressive intensity and mathematical analysis to interpret aerobic and anaerobic variables. The basketball players were assigned to four groups: All positions (n=26), Guard (n= 7), Forward (n=11) and Center (n=8). The hyperlactatemia elevation (RAST) method consisted of 6 maximum sprints over 35 m separated by 10 s of recovery. The progressive phase of the lactate minimum test consisted of 5 stages controlled by an electronic metronome (8.0, 9.0, 10.0, 11.0 and 12.0 km/h) over a 20 m distance. The RAST variables and the lactate values were analyzed using visual and mathematical models. The intensity of the lactate minimum test, determined by a visual method, reduced in relation to polynomial fits (2nd degree) for the Small Forward positions and General groups. The Power and Fatigue Index values, determined by both methods, visual and 3rd degree polynomial, were not significantly different between the groups. In conclusion, the RAST is an excellent hyperlactatemia inductor and the progressive intensity of lactate minimum test using short distances (20 m) can be specifically used to evaluate the aerobic capacity of basketball players. In addition, no differences were observed between the visual and polynomial methods for RAST variables, but lactate minimum intensity was influenced by the method of analysis.

The response of the lactate minimum test to a 12-week swimming training

Despite the utilization of lactate minimum test (LMT) in training, its intensity response to training remains controversial. The aim of the present study was to verify alterations of LMT intensity in swimmers during a 12-week training protocol. Eight swimmers were submitted to three LMT assessments: beginning of the season, T0; after four, T4; and twelve weeks, T12. The LMT consisted of a 200m maximal effort and, after eight minutes of passive rest, five incremental stages of 200m swimming. The intensities of the incremental stages were defined subjectively ("very light," "light," "moderate," "hard," and "all-out"). The training was divided in two blocks of periodization: endurance training period (ETP, T0 - T4), and quality plus taper period (QTP, T4 - T12). The LMT intensity of T4 and T12 were significantly higher than T0. We conclude that LMT is modified due to swimming training and can be used for training prescription and detection of aerobic capacity alterations during a season.

Hyperlactemia induction modes affect the lactate minimum power and physiological responses in cycling

The aim of this study was to verify the influence of hyperlactemia and blood acidosis induction on lactate minimum intensity (LMI). Twenty recreationally trained males who were experienced in cycling (15 cyclists and 5 triathletes) participated in this study. The athletes underwent 3 lactate minimum tests on an electromagnetic cycle ergometer. The hyperlactemia induction methods used were graded exercise test (GXT), Wingate test (WAnT), and 2 consecutive Wingate tests (2 × WAnTs). The LMI at 2 × WAnTs (200.3 ± 25.8 W) was statistically higher than the LMI at GXT (187.3 ± 31.9 W) and WAnT (189.8 ± 26.0 W), with similar findings for blood lactate, oxygen uptake, and pulmonary ventilation at LMI. The venous pH after 2 × WAnTs was lower (7.04 ± 0.24) than in (p ≤ 0.05) the GXT (7.19 ± 0.05) and WAnT (7.19 ± 0.05), whereas the blood lactate response was higher. In addition, similar findings were observed for bicarbonate concentration [HCO3] (2 × WAnTs lower than WAnT; 15.3 ± 2.6 mmol·L and 18.2 ± 2.7 mmol·L1, respectively) (p ≤ 0.05). However, the maximal aerobic power and total time measured during the incremental phase also did not differ. Therefore, we can conclude that the induction mode significantly affects pH, blood lactate, and [HCO3] and consequently they alter the LMI and physiological parameters at LMI.

Methods of exercise intensity and lactataemia determination of lactate minimum test in rats

The lactate minimum test (LMT) is a useful protocol for determining the intensity corresponding to the maximal lactate steady state. Nevertheless, different methods to determine LMT variables are found in the literature. The aim of this study was to analyse three different methods for determining the effort intensity (LMTi) and lactataemia (LMTLAC) corresponding to LMT. We subjected seventeen rats to LMT in a swimming ergometer, following three steps: (1) acidosis induction phase; (2) recovery of nine minutes; and (3) incremental swimming intensity phase. We determined the LMTi and LMTLAC using three methods: visual inspection (VI - non-mathematic), second order polynomial function (fPOLY - mathematic) and spline function (fSPL - mathematic). Results showed no significant differences between the LMTi or LMTLAC values determined using VI (5.32+0.50% bw and 5.62+0.78 mM, respectively), fPOLY (5.31+0.53% bw and 5.64+0.72 mM, respectively) and fSPL (5.32+0.54% bw and 5.59+0.76 mM, respectively). We found significant correlations between the three methods (P<0.05). We concluded that the determination of the intensity and lactataemia corresponding to LMT are not influenced by mathematic or non-mathematic methods in swimming sedentary rats.