Low plasma lactate concentration as a biomarker of an incompetent brain-pull: a risk factor for weight gain in type 2 diabetes patients.

OBJECTIVE: Body weight development is closely regulated by central nervous mechanisms. As has been demonstrated recently, the capability of the brain to actively demand energy from the body (brain-pull) is indispensable for the maintenance of systemic homeostasis. A deficit in this brain-pull may result in compensatory ingestive behavior followed by weight gain in the medium or long term. The aim of this study was to establish a biomarker of such an incompetent brain-pull. Since lactate is an alternative cerebral energy substrate to glucose, we investigated whether low fasting plasma lactate concentrations are associated with weight gain and increased feelings of hunger in patients with type 2 diabetes over a 3-year period. METHODS: In a population based cohort study 134 type 2 diabetes patients were examined at baseline and 3-year follow-up. Plasma lactate concentrations and additional hormones associated with food intake such as e.g. insulin, or leptin, as well as psychological variables like hunger feelings before and after a standardized breakfast were measured. The relation between fasting plasma lactate concentrations and postprandial hunger as well as follow-up weight was analyzed. RESULTS: Low fasting plasma lactate concentrations predicted a higher 3-year follow-up weight (B=-1.268, SE=0.625, p=0.04). Moreover, low fasting plasma lactate concentrations were associated with more pronounced feelings of postprandial hunger (B=-0.406, SE=0.137, p<0.01). CONCLUSIONS: We conclude that low plasma lactate concentrations may represent a biomarker of an incompetent brain-pull, which is associated with weight gain and increased postprandial hunger in patients with type 2 diabetes mellitus. These results are in line with the view that plasma lactate can be used by the brain as an alternative energy substrate and thereby to some extent prevent overeating and obesity.

Effect of soccer training on the running speed and the blood lactate concentration at the lactate minimum test

Tegtbur et al. [23] devised a new method able to estimate the intensity at maximal lactate steady state termed lactate minimum test. According to Billat et al. [7], no studies have yet been published on the affect of training on highest blood lactate concentration that can be maintained over time without continual blood lactate accumulation. Therefore, the aim of the present study was to verify the effect of soccer training on the running speed and the blood lactate concentration (BLC) at the lactate minimum test (Lac(min)). Thirteen Brazilian male professional soccer players, all members of the same team playing at National level, volunteered for this study. Measurements were carried out before (pre) and after (post) eight weeks of soccer training. The Lac(min) test was adapted to the procedures reported by Tegtbur et al. [23]. The running speed at the Lac(min) test was taken when the gradient of the line was zero. Differences in running speed and blood lactate concentration at the Lac(min) test before (pre) and after (post) the training program were evaluated by Student's paired t-test. The training program increased the running speed at the Lac(min) test (14.94 +/- 0.21 vs. 15.44 +/- 0.42* km(.)h(-1)) and the blood lactate concentration (5.11 +/- 2.31 vs. 6.93 +/- 1.33* mmol(.)L(-1)). The enhance in the blood lactate concentration may be explained by an increase in the lactate/H+ transport capacity of human skeletal muscle verified by other authors.

Responses of blood lactate concentration in aerobic and anaerobic training protocols at different swimming exercise intensities in rats

A swimming periodized experimental training model in rats in which different training protocols (TP) were classified in aerobic (A) and anaerobic (AN) intensity levels. The purpose of the present study was to verify if the classification of the TP used in the periodized training experimental model presented the blood lactate concentration [La] response adequate to the aerobic and anaerobic intensities levels. Twenty three male Wistar rats were divided into three groups. Two groups of swimming training (continuous, CT, n = 7, and periodized training, PET, n = 7) rats were evaluated during 5 weeks in eight different TP (TP-1 to TP-8) through the analysis of the [La] response. The third group was the sedentary control (SC, n = 9). The TP were classified in five intensity levels, three aerobic (A-1, A-2, A-3) and two anaerobic (AN-1, AN-2). Analysis of variance (ANOVA one-way, P<0.05) indicated significant differences in the [La] among the TP and among the five intensity levels. All TP of the A-2 and A-3 intensity levels differed from the A-1 and AN-1. The A-1 and AN-1 also differed among them. These findings demonstrate that the TP were classified properly at different levels of aerobic and anaerobic intensities, as based on the [La] response in a way similar to that of high performance swimming with humans. The results offer new perspectives for the study of exercise training in swimming rats at different levels intensity for performance or for health.

Influence of intensive training on salivary flow, on salivary pH and on salivary lactate concentration: consequences for oral health

Abstract of the poster presented at the First international Congress of CiiEM “From Basic Sciences to Clinical Research”, 27-28 November 2015, Egas Moniz, Caparica, Portugal.

Net increase of lactate and glutamate concentration in activated human visual cortex detected with magnetic resonance spectroscopy at 7 tesla.

After the landmark studies reporting changes in the cerebral metabolic rate of glucose (CMRGlc ) in excess of those in oxygen (CMRO2 ) during physiological stimulation, several studies have examined the fate of the extra carbon taken up by the brain, reporting a wide range of changes in brain lactate from 20% to 250%. The present study reports functional magnetic resonance spectroscopy measurements at 7 Tesla using the enhanced sensitivity to study a small cohort (n = 6). Small increases in lactate (19% ± 4%, P < 0.05) and glutamate (4% ± 1%, P < 0.001) were seen within the first 2 min of activation. With the exception of glucose (12% ± 5%, P < 0.001), no other metabolite concentration changes beyond experimental error were significantly observed. Therefore, the present study confirms that lactate and glutamate changes during physiological stimulation are small (i.e. below 20%) and shows that the increased sensitivity allows reproduction of previous results with fewer subjects. In addition, the initial rate of glutamate and lactate concentration increases implies an increase in CMRO2 that is slightly below that of CMRGlc during the first 1-2 min of activation.

Maximal lactate steady state concentration independent of pedal cadence in active individuals

The maximal lactate steady state (MLSS) is defined as the highest blood lactate concentration that can be maintained over time without a continual blood lactate accumulation. The objective of the present study was to analyze the effects of pedal cadence (50 vs. 100 rev min(-1)) on MLSS and the exercise workload at MLSS (MLSSworkload) during cycling. Nine recreationally active males (20.9 +/- 2.9 years, 73.9 +/- 6.5 kg, 1.79 +/- 0.09 m) performed an incremental maximal load test (50 and 100 rev min(-1)) to determine anaerobic threshold (AT) and peak workload (PW), and between two and four constant submaximal load tests (50 and 100 rev min(-1)) on a mechanically braked cycle ergometer to determine MLSSworkload and MLSS. MLSSworkload was defined as the highest workload at which blood lactate concentration did not increase by more than 1 mM between minutes 10 and 30 of the constant workload. The maximal lactate steady state intensity (MLSSintensity) was defined as the ratio between MLSSworkload and PW. MLSSworkload (186.1 +/- 21.2 W vs. 148.2 +/- 15.5 W) and MLSSintensity (70.5 +/- 5.7% vs. 61.4 +/- 5.1%) were significantly higher during cycling at 50 rev min(-1) than at 100 rev min(-1), respectively. However, there was no significant difference in MLSS between 50 rev min(-1) (4.8 +/- 1.6 mM) and 100 rev min(-1) (4.7 +/- 0.8 mM). We conclude that MLSSworkload and MLSSintensity are dependent on pedal cadence (50 vs. 100 rev min(-1)) in recreationally active individuals. However, this study showed that MLSS is not influenced by the different pedal cadences analyzed.

Influence of exercise mode and maximal lactate-steady-state concentration on the validity of OBLA to predict maximal lactate-steady-state in active individuals

The aim of this study was to analyze the effects of exercise mode on the validity of onset of blood lactate accumulation (OBLA-3.5-mM fixed blood lactate concentration) to predict the work-rate at maximal lactate steady state (MLSSwork-rate). Eleven recreationally active mates (21.3 +/- 2.9 years, 72.8 +/- 6.7 kg, 1.78 +/- 0.1 m) performed randomly incremental tests to determine OBLA (stage duration of 3 min), and 2 to 4 constants work-rate exercise tests to directly determine maximal lactate steady state parameters on a cycle-ergometer and treadmill. For both exercise modes, the OBLA was significantly correlated to MLSSwork-rate, (cycling: r = 0.81 p = 0.002; running: r = 0.94, p < 0.001). OBLA (156.2 +/- 41.3 W) was lower than MLSSwork-rate (179.6 +/- 26.4 W) during cycling exercise (p = 0.007). However, for running exercise, there was no difference between OBLA (3.2 +/- 0.6 m s(-1)) and MLSSwork-rate (3.1 +/- 0.4 m s(-1)). The difference between OBLA and MLSSworkrate on the cycle-ergometer (r = 0.86; p < 0.001) and treadmill (r = 0.64; p = 0.048) was significantly related to the specific MLSS. We can conclude that the validity of OBLA on predicting MLSSwork-rate is dependent on exercise mode and that its disagreement is related to individual variations in MLSS. (C) 2007 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Methods of quantification of training load in exercise performed at maximal lactate steady state

The aim of the present study was to compare and correlate training impulse (TRIMP) estimates proposed by Banister (TRIMP(Banister)), Stagno (TRIMP(Stagno)) and Manzi (TRIMP(Manzi)). The subjects were submitted to an incremental test on cycle ergometer with heart rate and blood lactate concentration measurements. In the second occasion, they performed 30 min. of exercise at the intensity corresponding to maximal lactate steady state, and TRIMP(Banister), TRIMP(Stagno) and TRIMP(Manzi) were calculated. The mean values of TRIMP(Banister) (56.5 +/- 8.2 u.a.) and TRIMP(Stagno) (51.2 +/- 12.4 u.a.) were not different (P > 0.05) and were highly correlated (r = 0.90). Besides this, they presented a good agreement level, which means low bias and relatively narrow limits of agreement. On the other hand, despite highly correlated (r = 0.93), TRIMP(Stagno) and TRIMP(Manzi) (73.4 +/- 17.6 u.a.) were different (P < 0.05), with low agreement level. The TRIMP(Banister) e TRIMP(Manzi) estimates were not different (P = 0.06) and were highly correlated (r = 0.82), but showed low agreement level. Thus, we concluded that the investigated TRIMP methods are not equivalent. In practical terms, it seems prudent monitor the training process assuming only one of the estimates.

Physiological and perceived exertion responses at intermittent critical power and intermittent maximal lactate steady state

Okuno, NM, Perandini, LAB, Bishop, D, Simoes, HG, Pereira, G, Berthoin, S, Kokubun, E, and Nakamura, FY. Physiological and perceived exertion responses at intermittent critical power and intermittent maximal lactate steady state. J Strength Cond Res 25(7): 2053-2058, 2011-The aim of this study was to compare the power outputs of the intermittent critical power (CPi) with the intermittent maximal lactate steady state (MLSSi) and to compare the physiological and perceptual responses exercising at CPi and MLSSi. Ten subjects performed intermittent trials on a cycle ergometer to determine CPi and MLSSi using 30: 30 seconds of effort and pause. The oxygen uptake ((V) over dotO(2)), heart rate (HR), blood lactate concentration ([Lac]), and rating of perceived exertion (RPE) responses were compared during 30-minute cycling at CPi and MLSSi. The CPi (267 6 45 W) was similar to MLSSi (254 6 39 W), and they were correlated (r = 0.88; p<0.05). The (V) over dotO(2) and HR responses stabilized throughout exercising at CPi (2.52 +/- 0.52 L.min(-1); 156 +/- 8 b.min(-1)) and MLSSi (2.41 +/- 0.32 L.min(-1); 152 +/- 10 b.min(-1)). These physiological variables were similar between conditions. However, the [Lac] and RPE were higher from the middle to the end of exercise duration at CPi ([Lac] = 6.9 +/- 2.6 mM; RPE = 17.1 +/- 2.1 a.u.) compared to MLSSi ([Lac] = 5.1 +/- 0.9 mM; RPE = 15.7 +/- 1.8 a.u.). Therefore, CPi intensity determined from 30: 30 seconds of effort and rest periods on a cycle ergometer is equivalent to the MLSSi, and there is a physiological steady state throughout both exercise intensities, although the [Lac] and RPE responses at CPi are higher than at MLSSi. Thus, the CPi and MLSSi may be used as tools for intermittent training evaluation and prescription.

The relationship between plasma lactate parameters, W-peak and 1-h cycling performance in women

Purpose: The relationship between six descriptors of lactate increase, peak (V) over dot O-2,W-peak, and 1-h cycling performance were compared in 24 trained, female cyclists (peak (V) over dot O-2 = 48.11 +/- 6.32 mL . kg(-1) . min(-1)). Methods: The six descriptors of lactate increase were: 1) lactate threshold (LT; the power output at which plasma lactate concentration begins to increase above the resting level during an incremental exercise test), 2) LT1 (the power output at which plasma lactate increases by 1 mM or more), 3) LTD (the lactate threshold calculated by the D-max method), 4) LTMOD (the lactate threshold calculated by a modified D-max method), 5) L4 (the power output at which plasma lactate reaches a concentration of 4 mmol-L-1), and 6) LTLOG (the power output at which plasma lactate concentration begins to increase when the log([La-]) is plotted against the log (power output)). Subjects first completed a peak (V) over dot O-2 test on a cycle ergometer. Finger-tip capillary blood was sampled within 30 s of the end of each 3-min stage for analysis of plasma lactate. Endurance performance was assessed 7 d later using a 1-h cycle test (OHT) in which subjects were directed to achieve the highest possible average power output. Results: The mean power output (W) for the OHT (+/- SD) was 183.01 +/- 18.88, and for each lactate variable was: LT (138.54 +/- 46.61), LT1 (179.17 +/- 27.25), LTLOG (143.97 +/- 45.74), L4 (198.09 +/- 33.84), LTD (178.79 +/- 24.07), LTMOD (212.28 +/- 31.75). Average power output during the OHT was more strongly correlated with all plasma lactate parameters (0.61 < r < 0.84) and W-peak (r = 0.81) than with peak (V) over dot O-2 (r = 0.55). The six lactate parameters were strongly correlated with each other (0.54 < r < 0.91) and of the six lactate parameters, LTD correlated best with endurance performance (r = 0.84). Conclusions: It was concluded that plasma lactate parameters and W-peak provide better indices of endurance performance than peak (V) over dot O-2 and that, of the six descriptors of lactate increase measured in this study, LTD is most strongly related to 1-h cycling performance in trained, female cyclists.

Heart rate, blood lactate and kinematic data of elite colts (under-19) rugby union players during competition

Physiological and kinematic data were collected from elite under-19 rugby union players to provide a greater understanding of the physical demands of rugby union. Heart rate, blood lactate and time-motion analysis data were collected from 24 players (mean +/- s((x) over bar): body mass 88.7 +/- 9.9 kg, height 185 +/- 7 cm, age 18.4 +/- 0.5 years) during six competitive premiership fixtures. Six players were chosen at random from each of four groups: props and locks, back row forwards, inside backs, outside backs. Heart rate records were classified based on percent time spent in four zones (>95%, 85-95%, 75-84%, <75% HRmax). Blood lactate concentration was measured periodically throughout each match, with movements being classified as standing, walking, jogging, cruising, sprinting, utility, rucking/mauling and scrummaging. The heart rate data indicated that props and locks (58.4%) and back row forwards (56.2%) spent significantly more time in high exertion (85-95% HRmax) than inside backs (40.5%) and outside backs (33.9%) (P < 0.001). Inside backs (36.5%) and outside backs (38.5%) spent significantly more time in moderate exertion (75-84% HRmax) than props and locks (22.6%) and back row forwards (19.8%) (P < 0.05). Outside backs (20.1%) spent significantly more time in low exertion (< 75% HRmax) than props and locks (5.8%) and back row forwards (5.6%) (P < 0.05). Mean blood lactate concentration did not differ significantly between groups (range: 4.67 mmol.l(-1) for outside backs to 7.22 mmol.l(-1) for back row forwards; P < 0.05). The motion analysis data indicated that outside backs (5750 m) covered a significantly greater total distance than either props and locks or back row forwards (4400 and 4080 m, respectively; P < 0.05). Inside backs and outside backs covered significantly greater distances walking (1740 and 1780 m, respectively; P < 0.001), in utility movements (417 and 475 m, respectively; P < 0.001) and sprinting (208 and 340 m, respectively; P < 0.001) than either props and locks or back row forwards (walking: 1000 and 991 m; utility movements: 106 and 154 m; sprinting: 72 and 94 m, respectively). Outside backs covered a significantly greater distance sprinting than inside backs (208 and 340 m, respectively; P < 0.001). Forwards maintained a higher level of exertion than backs, due to more constant motion and a large involvement in static high-intensity activities. A mean blood lactate concentration of 4.8-7.2 mmol.l(-1) indicated a need for 'lactate tolerance' training to improve hydrogen ion buffering and facilitate removal following high-intensity efforts. Furthermore, the large distances (4.2-5.6 km) covered during, and intermittent nature of, match-play indicated a need for sound aerobic conditioning in all groups (particularly backs) to minimize fatigue and facilitate recovery between high-intensity efforts.

Lactate and glucose metabolism in severe sepsis and cardiogenic shock.

OBJECTIVE: To evaluate the relative importance of increased lactate production as opposed to decreased utilization in hyperlactatemic patients, as well as their relation to glucose metabolism. DESIGN: Prospective observational study. SETTING: Surgical intensive care unit of a university hospital. PATIENTS: Seven patients with severe sepsis or septic shock, seven patients with cardiogenic shock, and seven healthy volunteers. INTERVENTIONS: C-labeled sodium lactate was infused at 10 micromol/kg/min and then at 20 micromol/kg/min over 120 mins each. H-labeled glucose was infused throughout. MEASUREMENTS AND MAIN RESULTS: Baseline arterial lactate was higher in septic (3.2 +/- 2.6) and cardiogenic shock patients (2.8 +/- 0.4) than in healthy volunteers (0.9 +/- 0.20 mmol/L, p < .05). Lactate clearance, computed using pharmacokinetic calculations, was similar in septic, cardiogenic shock, and controls, respectively: 10.8 +/- 5.4, 9.6 +/- 2.1, and 12.0 +/- 2.6 mL/kg/min. Endogenous lactate production was determined as the initial lactate concentration multiplied by lactate clearance. It was markedly enhanced in the patients (septic 26.2 +/- 10.5; cardiogenic shock 26.6 +/- 5.1) compared with controls (11.2 +/- 2.7 micromol/kg/min, p < .01). C-lactate oxidation (septic 54 +/- 25; cardiogenic shock 43 +/- 16; controls 65 +/- 15% of a lactate load of 10 micromol/kg/min) and transformation of C-lactate into C-glucose were not different (respectively, 15 +/- 15, 9 +/- 18, and 10 +/- 7%). Endogenous glucose production was markedly increased in the patients (septic 14.8 +/- 1.8; cardiogenic shock 15.0 +/- 1.5) compared with controls (7.2 +/- 1.1 micromol/kg/min, p < .01) and was not influenced by lactate infusion. CONCLUSIONS: In patients suffering from septic or cardiogenic shock, hyperlactatemia was mainly related to increased production, whereas lactate clearance was similar to healthy subjects. Increased lactate production was concomitant to hyperglycemia and increased glucose turnover, suggesting that the latter substantially influences lactate metabolism during critical illness.

Effect of major hepatectomy on glucose and lactate metabolism.

BACKGROUND: The liver plays an important role in glucose and lactate metabolism. Major hepatectomy may therefore be suspected to cause alterations of glucose and lactate homeostasis. METHODS: Thirteen subjects were studied: six patients after major hepatectomy and seven healthy subjects who had fasted overnight. Glucose turnover was measured with 6,6(2)H glucose. Lactate metabolism was assessed using two complementary approaches: 13C-glucose synthesis and 13CO2 production from an exogenous 13C-labeled lactate load infused over 15 minutes were measured, then the plasma lactate concentrations observed over 185 minutes after lactate load were fitted using a biexponential model to calculate lactate clearance, endogenous production, and half-lives. RESULTS: Three to five liver segments were excised. Compared to healthy controls, the following results were observed in the patients: 1) normal endogenous glucose production; 2) unchanged 13C-lactate oxidation and transformation into glucose; 3) similar basal plasma lactate concentration, lactate clearance, and lactate endogenous production; 4) decreased plasma lactate half-life 1 and increased half-life 2. CONCLUSIONS: Glucose and lactate metabolism are well maintained in patients after major hepatectomy, demonstrating a large liver functional reserve. Reduction in the size of normal liver parenchyma does not lead to hyperlactatemia. The use of a pharmacokinetic model, however, allows the detection of subtle alterations of lactate metabolism.