Purpose: In the present study we investigated whether a high volume of cycling training would influence the metabolic changes associated with a succession of three exhaustive cycling exercises. Methods: Seven professional road cyclists (V˙O 2max: 74.3 ± 3.7 mLmin −1kg −1; maximal power tolerated: 475 ± 18 W; training: 22 ± 3 hwk −1) and seven sport sciences students (V˙O 2max: 54.2 ± 5.3 mLmin −1kg −1; maximal power tolerated: 341 ± 26 W; training: 6 ± 2 hwk −1) performed three different exhaustive cycling exercise bouts (progressive, constant load, and sprint) on an electrically braked cycloergometer positioned near the magnetic resonance scanner. Less than 45 s after the completion of each exercise bout, recovery kinetics of high-energy phosphorylated compounds and pH were measured using 31P-MR spectroscopy. Results: Resting values for phosphomonoesters (PME) and phosphodiesters (PDE) were significantly elevated in the cyclist group (PME/ATP: 0.82 ± 0.11 vs 0.58 ± 0.19; PDE/ATP: 0.27 ± 0.03 vs 0.21 ± 0.05).
Phosphocreatine (PCr) consumption and inorganic phosphate (Pi) accumulation measured at end of exercise bouts 1 (PCr: 6.5 ± 3.2 vs 10.4 ± 1.6 mM; Pi: 1.6 ± 0.7 vs 6.8 ± 3.4 mM) and 3 (PCr: 5.6 ± 2.4 vs 9.3 ± 3.9 mM; Pi: 1.5 ± 0.5 vs 7.7 ± 3.3 mM) were reduced in cyclists compared with controls. During the recovery period after each exercise bout, the pH-recovery rate was larger in professional road cyclists, whereas the PCr-recovery kinetics were significantly faster for cyclists only for bout 3. Discussion: Whereas the PDE and PME elevation at rest in professional cyclists may indicate fiber-type changes and an imbalance between glycogenolytic and glycolytic activity, the lower PCr consumption during exercise and the faster pH-recovery kinetic clearly suggest an improved mitochondrial function.
The classical functional tests used to evaluate the physical capacity of athletes provide systemic information that is mainly related to cardiovascular and respiratory adaptations during progressive exercise. However, the improvement in physical performance attributable to specific training is not only linked to a global metabolic capacity but also to adjustments occurring at the muscular and vascular levels ( ).
In addition, training-induced skeletal muscle adaptations can be independent of systemic changes ( ). In the last 20 yr, 31-phosphorus magnetic resonance spectroscopy ( 31P-MRS) has been used as a noninvasive tool to investigate muscle energetics. Given the possibility of monitoring changes in pH and high-energy phosphate compounds such as Pi, PCr, and ATP during and after exercise, and considering that similar results were obtained compared with biopsy studies, muscle energy metabolism has been investigated in a variety of conditions including metabolic myopathies and training ( ). However, very few 31P-MRS studies have been conducted in elite sportsmen ( ). In addition, because of methodological limitations (i.e., exercise performed inside the magnet), exercises performed by these athletes for the purposes of the metabolic investigations were very different from ecological situations. The use of investigated muscles was different from the specific use involved in the training process, which raises questions regarding the conclusions related to the local metabolic adaptations linked to exercise training. Very little is known about metabolic changes occurring during the recovery period after an exhaustive ecological exercise.
GPEXE advice is a service provided by our staff of physiologists to support the client with/in: technical consultancy, data analysis, and testing. To analyze training data in the light of individual physical fitness level assessed via the functional tests during the season.
Considering that recovery between episodes of high-intensity exercise could help determine muscle performance, detailed analysis of metabolic changes occurring during recovery periods deserves interest. In a recent 31P-MRS study ( ), we analyzed the metabolic recovery in a group of professional road cyclists immediately after a progressive pedaling exercise. We reported a higher PCr concentration at the end of exercise in professional road cyclists compared with untrained subjects. The combined analysis of the time-dependent changes in pH (reflecting exported and buffered protons) and PCr (an index of aerobic metabolism) during the postexercise recovery period also provided lines of evidence for a metabolic adaptation in this highly trained population, resulting in a significantly faster rate of pH recovery.
However, this pilot study was restricted to a single incremental pedaling exercise. Because it has been shown that exercise duration and intensity affect metabolic recovery ( ), the conclusions of the latter study ( ) were limited to this specific protocol.
On that basis, we wanted to extend our previous study ( ) and document the metabolic changes associated with a succession of three various exhaustive and specific cycling exercises (progressive, constant load, and sprint exercise) in a population of professional road cyclists compared with moderately trained subjects. We hypothesized that, similar to what was observed for a single exercise bout, metabolic recovery after each of the typical exercise bouts would be faster in professional road cyclists than in controls. We analyzed the corresponding results in relation to possible adaptive mechanisms related to endurance training. Exercise protocol. Subjects attended the laboratory for two different sessions in the same day. To characterize our populations in terms of physical and physiological aptitudes, subjects performed, in the midmorning, incremental exercise to exhaustion (workload increments of 25 Wmin −1, starting at 100 W), during which the usual cardiorespiratory parameters were measured. Exhaustion was checked according to the Astrand criteria (HR corresponding to 220 − age) ( ).
Throughout this exercise trial, breath-by-breath data of V˙ E, V˙O 2, V˙CO 2, and the ventilatory equivalents for O 2 (V˙ E/V˙O 2) and CO 2 (V˙ E/V˙CO 2) were recorded (Oxycon Beta, Hellige, Germany). The final maximal power recorded during this exercise bout was referred as the maximal power tolerated (MPT).
Physical and physiological characteristics of the subjects are reported in. After a 5-h recovery period, including a freely chosen meal, cyclists performed three successive pedaling exercise bouts in the hallway of the MRI center adjacent to the superconducting magnet room. Ambient temperature (20-22°C) and relative humidity (45-50%) were kept constant throughout the exercise sessions. During cycling, the subjects adopted conventional (upright) cycling posture, characterized by a trunk inclination of approximately 75°. They positioned their hands on the handlebars with elbows slightly bent (10° flexion). To ensure optimal performance, pedaling rate was freely chosen by each subject.
Subjects used sport shoes with clip pedals. Both groups were investigated in the same period of the year (March-April). All of the professional road cyclists were in an active competitive period to prepare the 'Tour de France,' which was planned 2-3 months later. The protocol consisted of three different cycling exercise bouts performed on an electrically braked cycloergometer (Excalibur Sport, Lode, the Netherlands). The first bout (bout 1) was a progressive exercise identical to that performed during the morning session.
The second bout (bout 2) consisted of a limit time to exhaustion exercise performed at a constant load corresponding to the MPT determined during the morning session. Then, the subjects were asked to perform a maximal pedaling sprint (duration = 30 s; load = 0.80 nMkg −1) (bout 3). The subjects were verbally encouraged during each bout to give maximal effort. All bouts were preceded by a warm-up session (duration = 10 min; workload = 100 W) and separated by a recovery period of 15 min, during which 31P-MR spectra were recorded. The cycloergometer was placed in the hallway of the MRI center immediately adjacent to the superconducting magnet room so that the subjects could be positioned in the magnet and scanned within 45 s of completion of each cycling exercise.
31P-MRS measurements. MR spectra of thigh muscles (rectus femoris, vastus medialis, vastus lateralis) were recorded at 25.9 MHz in the 1.5-T magnet of a Siemens Vision Plus (Siemens AG, Erlangen, Germany) using a commercially available double-tuned 31P− 1H surface coil (liver coil, 14 cm in diameter for the outer coil and 8 cm in diameter for the inner coil). To ensure that the same muscles were measured in each subject, the localization of the probe was standardized using scout MR images recorded in the x, y, and z planes. Magnetic-field homogeneity shimming was performed on the proton signal using an automatic procedure. 31P spectra were time averaged in 2-s blocks (two scans, repetition time = 1 s, sweep width = 10 kHz) at rest and during 15 min of the early recovery period after the different exercises performed on the cycloergometer. Fully relaxed spectra ( N = 10, repetition time = 20 s) were recorded at rest to calculate the saturation factor of each metabolite.
Ink marks on the thigh, aligned with the crosshairs of the scanner, allowed for identical positioning in the magnet bore for repeated scans. Relative concentrations of phosphocreatine (PCr), inorganic phosphate (Pi), adenosine triphosphate (ATP), phosphomonoesters (PME), and phosphodiesters (PDE) were obtained by a time domain-fitting routine using the AMARES algorithm and appropriate prior knowledge of the ATP multiplets. Intracellular pH was calculated from the chemical shift of the Pi relative to the PCr signal. Proton efflux was calculated by considering proton production from PCr resynthesis and pH changes during the early recovery period, as previously described ( ).
End-of-exercise PCr and pH values were extrapolated at time-zero using regression methods. Regression quality was estimated using Pearson product coefficients. Based on previous studies ( ), we considered that time-dependent PCr changes are linear during the initial period after exercise. Accordingly, we extrapolated end-of-exercise PCr values using a linear regression for the first 30 s of recovery. Regarding pH, we chose a biexponential regression for the overall dataset for each subject based on previous analyses during high-intensity exercise ( ). Because no reliable fitting method exists for PME and Pi, we have directly compared the values measured 1 min after the end of each exercise. Statistical analysis.
Results are expressed as means ± SD. A Kolmogorov-Smirnov test was used to check that the values were normally distributed. To investigate metabolic changes between rest, end of exercise, and end of the recovery period, and the difference between the two populations, we performed a two-way ANOVA (factor 1 = group, factor 2 = time) with repeated measurements ( post hoc: Bonferroni tests). Student's t-tests were performed to compare physiological and physical variables between the two groups. A Pearson correlation coefficient was calculated to evaluate the relationships between variables.
Statistical significance was established at the P. Exercise-induced metabolic changes. The time between the end of exercise and the beginning of scanning was not significantly different between groups or between bouts (professional road cyclists: 43.5 ± 8.0, 41.8 ± 6.8, and 38.5 ± 3.9 s for bouts 1, 2, and 3; sport science students: 35.4 ± 4.3, 37.0 ± 4.6, and 35.7 ± 4.5 s for bouts 1, 2, and 3). In addition, we found no significant correlation ( P ranging from 0.06 to 0.95) between extrapolated end-of-exercise pH and PCr values and the delay between the end of the exercise and the first scan. Physical performances achieved during the first two exercise bouts are summarized in.
Although MPT was significantly greater in cyclists (bout 1), the limit time to exhaustion was similar (bout 2) in both populations. Because of a technical problem, it was not possible to measure the mechanical variables related to the sprint (bout 3). The average PCr time-dependent changes for both groups and for each bout are displayed in. End-of-exercise PCr and pH values were extrapolated using specific regression methods as described in the Methods section.
The corresponding correlation coefficients ranged from 0.75 to 0.99. Extrapolated end-of-exercise PCr values were significantly higher in professional road cyclists compared with controls for bouts 1 ( P = 0.016) and 3 ( P = 0.046). Regarding the second exercise bout, extrapolated PCr values were not different ( P = 0.073) between the groups. Similarly, PCr values measured at the onset of the recovery period (i.e., at the beginning of the 31P-MRS measurements) were also significantly higher in cyclists for bouts 1 and 3, whereas the values measured throughout the remaining recovery period were similar in both groups.
We found no statistical difference between subjects regarding the PCr-recovery time constants measured for the first two exercise bouts. On the contrary, for the third exercise bout, PCr recovery was significantly faster ( P = 0.038) in professional cyclists (1.16 ± 0.16 min) compared with moderately trained subjects (0.64 ± 0.13 min). Time-dependent changes in pH are displayed in and illustrate that the three exhaustive exercises were coupled to a drastic intracellular acidosis, which was surprisingly similar in both groups. However, significant higher pH values for professional cyclist were measured the fifth minute of the recovery period for bouts 1 ( P = 0.042), 2 ( P = 0.032), and 3 ( P = 0.022). This difference ( P = 0.007) remained longer, 10 min after the end of the third exercise bout. This faster recovery rate in the cyclist group was further confirmed by a significantly faster proton efflux after the three exercise bouts.
The acidosis extent was slightly smaller at end of the third exercise bout compared with the other exercise bouts. However, this reduction was only significant ( P = 0.018) in the group of sport science students. As illustrated in, Pi evolved differently with respect to time in the two groups. After a minute of recovery, Pi was significantly higher in moderately trained subjects compared with professional road cyclists (bout 1: 6.8 ± 3.4 vs 1.6 ± 0.7 mM ( P = 0.002); bout 2: 5.5 ± 2.8 vs 1.7 ± 0.5 mM ( P = 0.004); bout 3: 7.7 ± 3.3 vs 1.5 ± 0.5 mM ( P = 0.0003)).
This significant difference remained until the end of the recovery period for the third exercise bout (4.39 ± 0.8 vs 2.9 ± 0.3 mM ( P = 0.001) for sport science students and professional road cyclists, respectively). PME time-dependent changes are depicted in.
We found a significantly higher PME concentration in professional road cyclists 1 min after the end of the first bout (10.6 ± 2.4 vs 7.4 ± 2.0 mM ( P = 0.014)). In contrast, PME concentrations were not different between groups 1 min after the ends of bouts 2 and 3. DISCUSSION In the present study, we have reported the metabolic recovery kinetics (PCr, pH, PME, and Pi) in a group of professional road cyclists after three different pedaling exercise bouts performed until exhaustion.
Our data mainly show that PCr consumption and Pi accumulation were reduced throughout the exercise bouts in cyclists compared with controls. Highly trained subjects also recovered their initial pH values faster than controls, as previously described throughout a single exercise condition ( ). In addition, PME and PDE resting values with respect to ATP were significantly larger in cyclists. The ability to recover quickly is critical if subsequent bouts of intense exercise are to be performed.
In competitive road cycling, these high-intensity exercise bouts come into play in critical phases such as closing gaps, short climbs at all-out speed, finish sprints, or time trials. It has been proposed that adaptations associated with endurance training should enhance recovery from high-intensity exercise ( ). Theoretically, an increase in aerobic fitness could enhance recovery from anaerobic performance, both by supplementing anaerobic energy during the exercise and by providing aerobically derived energy at a faster rate during the recovery period. Additionally, any mechanisms improving blood supply and/or muscle washout from end products of ATP degradation could enhance muscle performance ( ).
Our results are consistent with these concepts and clearly show a faster pH recovery and a lesser PCr consumption during different types of exercise bouts. The reduced PCr consumption calculated in professional cyclists throughout the first and the third exercise bouts could illustrate a larger aerobic capacity, as previously suggested ( ). This would be consistent with an enhanced aerobic ATP capacity related to training, as previously demonstrated during submaximal exercise ( ). However, very few studies have reported PCr consumption at the end of exhaustive exercise.
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To the best of our knowledge, only the results of Takahashi et al. ( ) are in line with our observations, showing a higher end of exercise PCr content in long-distance runners compared with untrained subjects.
It is noteworthy that single-fiber studies have shown that high-intensity exercise tends to preferentially reduce PCr content in fast-twitch compared with slow-twitch fibers ( ). In that respect, fiber composition would condition PCr use and could account for the present result. During the postexercise period, PCr resynthesis is exclusively aerobic; as a matter of consequence, it has been used as an index of mitochondrial metabolism. Previous studies in trained and diseased subjects have clearly identified reduced and accelerated PCr-recovery rates in skeletal muscle as a sign of defective or improved mitochondrial function ( ). However, despite the considerable amount of evidence supporting a link between V˙O 2max and PCr-recovery kinetics, attempts to establish a relationship between these two variables have provided conflicting results. For instance, PCr-resynthesis rates measured after high-intensity exercise were similar in groups displaying very different maximal oxidative capacities (64.4 ± 1.4 vs 46.6 ± 1.1 mLmin −1kg −1) ( ). In contrast, Yoshida et al.
( ) showed faster PCr-kinetics recovery in long-distance runners compared with sedentary subjects. In the present study, we failed to observe a faster PCr recovery in trained subjects. As mentioned above, most of the previous studies have documented training effects throughout recovery periods after submaximal efforts. In addition, no standardization procedure was used regarding exercise intensity. Given that we analyzed recovery period after exhaustive exercise, and considering that we standardized the exercise intensity according to the MPT, we cannot reliably compare our results with those from previous studies. It has been clearly established that the rate of proton efflux is influenced by the extent of acidosis reached at the end of exercise ( ).
Accordingly, similar pH values between groups discard pH differences as an accounting factor for the different pH-recovery rates. Therefore, the faster rate of pH recovery and the corresponding faster rate of proton efflux, taking into account both pH changes and the proton load linked to PCr resynthesis, further illustrate a metabolic adaptation in highly trained subjects. The metabolic changes reported in the present study are actually difficult to compare with those from other studies because of different exercise intensity or duration.
Other MR studies have reported limited pH changes (range: 0.07 to 0.22 pH units), likely resulting from the reduced work rate that could be performed inside a superconducting magnet ( ). Our pH values, which range from 6.86 to 6.20, are closer to those reported from muscle biopsy studies during cycling exercise ( ). Although early research focused on acidosis as the most likely cause of muscular fatigue, recent findings have pointed out the rate of glucose flow through glycogen as a limiting factor of exercise ( ), whereas others have paid attention to the intramuscular Pi accumulation ( ). During exercise, ATP hydrolysis is the major source of Pi production. Our results are consistent with those showing a lesser Pi accumulation during exercise in endurance-trained subjects as further indicating less ATP consumption. As previously suggested, the kinetics of Pi recovery from exhaustive exercise illustrate the kinetics of Pi transport ( ).
To the best of our knowledge, only Yoshida and Watari ( ) have examined this topic, reporting faster Pi-recovery kinetics in long-distance runners compared with control subjects. Interestingly, we found a Pi undershoot below the initial resting value at the beginning of the recovery period for professional cyclists only. This undershoot has been previously reported and accounted for by a temporary Pi trapping in the glycolytic sugar-phosphates pool ( ).
Taken together, results of pH, PCr, Pi, and PME recovery kinetics suggest that the high training status of the professional road cyclists accounts for a homogeneous change in fiber-type composition, as proposed in the literature. In this line, it has been reported that human skeletal-muscle fibers can be distinguished by their resting contents of PCr, ATP, and Pi ( ). Accordingly, a significantly reduced PCr/Pi ratio has been reported in long-distance runners ( ) and cross-country skiers ( ) compared with untrained subjects or sprinters ( ) and downhill skiers ( ), likely illustrating fiber-type changes resulting from training or, simply, a natural selection for those particular sports. We found no difference regarding Pi, PCr, and PCr/Pi at rest between professional road cyclists and sport science students.
These results are inconsistent with those from previous studies, and this discrepancy could originate from the fact that measurements were performed in different muscles (i.e., calf or wrist-flexor muscles). It is noteworthy that such a PCr/Pi reduction has also been reported in quadriceps muscles of long-distance runners compared with sprinters ( ). The physical fitness of our control population would more likely account for these discrepant results. In the present study, control subjects were enrolled in a regular physical activity (6 hwk −1), and the corresponding MPT was larger than what has been generally reported in young sedentary subjects.
In contrast, we showed higher PDE/ATP and PME/ATP ratios at rest in professional road cyclists. The higher PDE/ATP ratio would be consistent with a higher content of type I oxidative fibers ( ), as previously concluded from biopsy studies in trained cyclists ( ). PDE generation has been reported during the stimulation-mediated fast- to slow-muscle transformation in rabbit ( ), and higher PDE concentrations have been reported in long-distance runners compared with sprinters ( ).
This is interesting in that numerous studies have shown that fiber-type composition could be linked to performance and reflect adaptive responses to physical training ( ). At rest, the PME signal has been mainly attributed to glycolytic intermediates such as glucose and fructose-6 phosphate ( ). PME actually depict the imbalance between glycogen phosphorylase and phosphofructokinase (PFK) activities ( ).
An abnormal PME accumulation has been reported in patients with PFK deficiency, whereas in patients with glycogen phosphorylase deficiency, the PME signal does not change during exercise ( ). In that respect, a higher PME level at rest could indicate a larger imbalance between glycogenolysis and glycolysis in cyclists compared with controls. This imbalance would be in keeping with a higher glycogen content reported previously in a group of trained rats ( ). Considering the reduced glycogen phosphorylase activity reported by Cusso et al. ( ) as a result of training, the abnormal PME accumulation at rest would then be attributable to a limitation below the glycogen degradation (e.g., at the PFK level).
One could question the exhaustive nature of the exercise bouts performed by the cyclists and the controls. First of all, according to the Astrand criteria-based heart rate measurements reached at end of exercise, the exercise bout performed during the morning session was clearly exhaustive; that is, heart rate in the cyclist group was 97% of the theoretical maximum, and it reached 98% in the control group. On the basis of the work rate measurements, the first exercise bout performed during the afternoon session was identical to the bout performed during the morning session. In addition, intramuscular pH values reported in our study were lower than those reported in the literature for similar exhaustive exercises ( ). Finally, we specifically chose to include moderately trained subjects in the control group because they were familiar with exhaustive exercises. One could also wonder whether the delay between the cessation of exercise and the scanning onset could account for the differences between both groups.
For each exercise bout, we found no significant difference regarding this delay. CONCLUSION In the present study, we documented for the first time that intracellular acidosis is large at end of three different exhausting exercises and not significantly different between professional road cyclists and moderately trained subjects.
The clearest effects of a superior aerobic capacity are linked to a reduced PCr consumption and Pi accumulation and a faster pH recovery in cyclists. Our study further confirms that 31P-MRS data characterizing muscle energy can enable discrimination between two groups of subjects with different training status. Further investigations are needed to study the sensitivity of 31P-MRS measurements to follow up on the efficiency and adequacy of a specific training program in the course of a cyclist's season.
Nightscout Web Monitor (a.k.a. Cgm-remote-monitor) This acts as a web-based CGM (Continuous Glucose Monitor) to allow multiple caregivers to remotely view a patient's glucose data in real time. The server reads a MongoDB which is intended to be data from a physical CGM, where it sends new SGV (sensor glucose values) as the data becomes available.
The data is then displayed graphically and blood glucose values are predicted 0.5 hours ahead using an autoregressive second order model. Alarms are generated for high and low values, which can be cleared by any watcher of the data. Community maintained fork of the. Table of Contents. Install Supported configurations: If you plan to use Nightscout, we recommend using, as Nightscout can reach the usage limits of the free Azure plan and cause it to shut down for hours or days.
If you end up needing a paid tier, the $7/mo Heroku plan is also much cheaper than the first paid tier of Azure. Currently, the only added benefit to choosing the $7/mo Heroku plan vs the free Heroku plan is a section showing site use metrics for performance (such as response time). This has limited benefit to the average Nightscout user. In short, Heroku is the free and best option for Nightscout hosting. Nightscout Setup with Heroku (recommended).
Nightscout Setup with Microsoft Azure (not recommended, please ). Linux based install (Debian, Ubuntu, Raspbian) install with own Node.JS and MongoDB install (see software requirements below). Windows based install with own Node.JS and MongoDB install (see software requirements below) Software requirements:. Latest Node 8 LTS (Node 8.11.3 or later). Use or use setup.sh). 3.x or later. MongoDB 2.4 is only supported for Raspberry Pi.
As a non-root user clone this repo then install dependencies into the root of the project. Host$ vagrant up host$ vagrant ssh vm$ setup.sh The setup script will install OS packages then run npm install. The Vagrant VM serves to your host machine only on 192.168.33.10, you can access the web interface on More questions? Feel free to, but read the first. License cgm-remote-monitor - web app to broadcast cgm readings Copyright (C) 2017 Nightscout contributors. See the COPYRIGHT file at the root directory of this distribution and at This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details. You should have received a copy of the GNU Affero General Public License along with this program.