Changes in systolic arterial pressure variability are associated with the decreased aerobic performance of rats subjected to physical exercise in the heat

Journal of Thermal Biology 63 (2017) 31–40

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Changes in systolic arterial pressure variability are associated with the decreased aerobic performance of rats subjected to physical exercise in the heat Flávia C. Müller-Ribeiroa, Samuel P. Wannera, Weslley H.M. Santosa, ⁎ Milene R. Malheiros-Limaa, Ivana A.T. Fonsecaa, Cândido C. Coimbrab, Washington Piresb,c,

a Exercise Physiology Laboratory, Department of Physical Education, School of Physical Education, Physiotherapy and Occupational Therapy, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil b Department of Physiology and Biophysics, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil c Department of Physical Education, Institute of Life Sciences, Universidade Federal de Juiz de Fora, Governador Valadares, MG, Brazil

A R T I C L E I N F O

A BS T RAC T

Keywords: Fatigue Hot environment Parasympathetic activity Sympathetic activity Sympathovagal balance Treadmill running

Enhanced cardiovascular strain is one of the factors that explains degraded aerobic capacity in hot environments. The cardiovascular system is regulated by the autonomic nervous system, whose activity can be indirectly evaluated by analyzing heart rate variability (HRV) and systolic arterial pressure (SAP) variability. However, no study has addressed whether HRV or SAP variability can predict aerobic performance during a single bout of exercise. Therefore, this study aimed to investigate whether there is an association between cardiovascular variability and performance in rats subjected to treadmill running at two ambient temperatures. In addition, this study investigated whether the heat-induced changes in cardiovascular variability and reductions in performance are associated with each other. Male Wistar rats were implanted with a catheter into their carotid artery for pulsatile blood pressure recordings. After recovery from surgery, the animals were subjected to incremental-speed exercise until they were fatigued under temperate (25 °C) and hot (35 °C) conditions. Impaired performance and exaggerated cardiovascular responses were observed in the hot relative to the temperate environment. Significant and negative correlations between most of the SAP variability components (standard deviation, variance, very low frequency [VLF], and low frequency [LF]) at the earlier stages of exercise and total exercise time were observed in both environmental conditions. Furthermore, the heat-induced changes in the sympathetic components of SAP variability (VLF and LF) were associated with heat-induced impairments in performance. Overall, the results indicate that SAP variability at the beginning of exercise predicts the acute performance of rats. Our findings also suggest that heat impairments in aerobic performance are associated with changes in cardiovascular autonomic control.

1. Introduction Physical exercise can be one of the most stressful conditions with which the body has to cope. Depending on its intensity, exercise may require a metabolic rate up to 15–20 times greater than the resting value (Ainsworth et al., 2011). Therefore, coordinated physiological responses are required to supply adequate oxygen and nutrients to the working muscles. The physiological response to match the augmented metabolic demands is characterized by substrate mobilization, blood flow redistribution, and increases in mean arterial pressure (MAP), heart rate (HR), minute ventilation, and oxygen consumption

(Laughlin, 1999; Pires et al., 2007, 2013; Whipp et al., 1984). Physically active individuals and athletes often exercise in hot environments that markedly influence their exercise-induced physiological adjustments. For instance, prolonged physical exertion under environmental heat stress is associated with higher cardiovascular strain characterized by an increased demand for blood in the skin vessels and active muscles, which is counterbalanced by a reduction in the renal, splanchnic, and non-exercising muscle blood flow (Radigan and Robinson, 1949; Rowell et al., 1968). In addition, increased HR and decreased stroke volume are reported in response to exercise in the heat relative to exercise in temperate conditions (Crandall and

⁎ Correspondence to: Laboratory of Endocrinology and Metabolism, Department of Physiology and Biophysics, Universidade Federal de Minas Gerais, Av. Antônio Carlos, 6627, Belo Horizonte, MG, Brazil. E-mail address: [email protected] (W. Pires).

http://dx.doi.org/10.1016/j.jtherbio.2016.11.006 Received 17 August 2016; Received in revised form 3 November 2016; Accepted 9 November 2016 Available online 20 November 2016 0306-4565/ © 2016 Elsevier Ltd. All rights reserved.

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in accordance with the Guidelines of the Committee's Principles Manual.

Gonzalez-Alonso, 2010; Galloway and Maughan, 1997; Pires et al., 2013). Of note, these cardiovascular adjustments result from changes in the autonomic outflow to the heart and blood vessels that can be indirectly determined by assessing HR and blood pressure variability (Goldstein et al., 2011). It is well established that hot environments effectively impair the physical (aerobic) performance of different animal species (Cheuvront et al., 2010; Febbraio et al., 1996; Nielsen et al., 1993; Rodrigues et al., 2003; Wanner et al., 2014). The attainment of critically high levels of core body temperature (TCORE) as well as both metabolic and central nervous system (CNS)-mediated mechanisms have been proposed to be modulating factors for physical performance in heat (Cheung and McLellan, 1998; Cheung and Sleivert, 2004; Cheuvront et al., 2010; Nielsen et al., 1993; Wanner et al., 2014). Cardiovascular mechanisms also seem to play a role, as suggested by the observations that, at least in humans, high skin temperature and TCORE impair aerobic performance in tandem, primarily through elevated cardiovascular strain rather than a deterioration in CNS function or skeletal muscle metabolism (Cheuvront et al., 2010; Cuddy et al., 2014). Heart rate variability (HRV) has been considered one of the most promising and non-invasive assessment tools for monitoring individual adaptation to chronic exercise (Buchheit et al., 2007; Hautala et al., 2009; Plews et al., 2013). Decreases in vagal-derived indices of HRV are thought to be associated with negative adaptations in response to endurance training loads (Bosquet et al., 2008; Hynynen et al., 2008; Plews et al., 2013), whereas increases in vagal-derived indices of HRV have been related to improved physical performance consequent to endurance training (Atlaoui et al., 2007; Garet et al., 2004; Plews et al., 2013). Overtraining, resulting from heavy endurance training without adequate recovery, also induces changes in autonomic function, as evidenced by decreased HRV (Lehmann et al., 1993; Uusitalo et al., 1998). HRV analysis has been extensively used as a tool to predict chronic fatigue and recovery in athletic training (Atlaoui et al., 2007; Plews et al., 2013); however, the use of this tool for predicting acute performance (e.g., total exercise time during a bout of exercise) is still unclear. Because impaired performance in the heat is associated with greater cardiovascular strain resulting from changes in the autonomic outflow to the heart and vessels, we hypothesized that the heat-induced changes in cardiovascular variability parameters would be associated with heat-induced impairment in aerobic performance. Therefore, the present study first investigated whether the cardiovascular variability parameters are associated with physical performance in temperate and hot environments. We then investigated whether the heat-induced changes in cardiovascular variability parameters are associated with reduced performance in such environmental conditions. Importantly, we evaluated the association between physical performance and the data regarding not only HRV but also systolic arterial pressure (SAP) variability. Indeed, arterial pressure is the regulated parameter in cardiovascular control (Dampney, 1994; Dampney et al., 2002) and, thus, SAP variability may be more associated with performance than HRV.

2.2. Experimental design Most of the data presented in this paper consist of a deeper analysis of cardiovascular and performance data that have been taken from a previously published manuscript (Pires et al., 2013); therefore, the present paper proposes a new analysis aimed at understanding whether there is an association between cardiovascular variability and aerobic performance during treadmill running in rats. The rats were initially familiarized with exercising on the treadmill and then subjected to an incremental-speed exercise to evaluate their intrinsic aerobic capacity. On the following day, the animals were anesthetized with ketamine-xylazine (90 and 10.5 mg/kg body mass, respectively, i.p.). A small incision was made in the neck, and a polyethylene catheter (PE-10 connected to a PE-50; Becton Dickinson, Franklin Lakes, NJ, USA), filled with heparin diluted in isotonic saline, was inserted into the left common carotid artery. The free end of the PE-50 tubing was tunneled subcutaneously and exteriorized at the cervical dorsal area (Pires et al., 2007), and the incision in the neck was closed with small sutures. The adequacy of anesthesia was verified by the absence of a withdrawal response to nociceptive stimulation of a hind paw. Immediately after surgery, rats received an intramuscular prophylactic dose of antibiotics (pentabiotic, 48,000 IU/kg) and a subcutaneous injection of analgesic medication (flunixin meglumine, 1.1 mg/kg). The rats were then allowed to recover in their home cages for 48 h before experiments began. The blood pressure and HR were recorded from the indwelling carotid arterial catheter connected to a blood pressure transducer (model MP 100 A-CE, Biopac Systems). All animals for which data were reported remained in good health, as assessed by appearance, behavior, and maintenance of body weight, throughout recovery from the surgical procedures and experimental trials. At the completion of the experiments, rats were euthanized with an overdose of ketamine-xylazine (240 and 30 mg/kg body mass, respectively, i.p.). 2.3. Experimental trials Each rat was subjected to two experimental trials that consisted of incremental-speed running on a treadmill under temperate (25 °C) or hot (35 °C) conditions. A two-day interval was allowed between the trials. All experiments were performed between 0800 and 1600 h, and care was taken to test the same animal at the same time of day. The experiments in the temperate environment were always performed prior to those in the heat. A non-randomized experimental design was selected because of a concern regarding the occurrence of heat-related disorders after running at 35 °C, which would have prevented us from subjecting the rats to subsequent exercise at 25 °C. In this context, there is evidence that rats cannot restore their normal TCORE circadian rhythm during the 10 days that follow severe heat exposure (Leon and Helwig, 2010). In addition, it has been demonstrated that, following a 5-d familiarization protocol, repeated exposure to physical exercise does not influence performance during the second exercise bout compared to that during the first bout (Kunstetter et al., 2014; Pires et al., 2013). The temperature inside the treadmill chamber was set at 25 °C or 35 °C. The temperate environment was selected to be at 25 °C because previous data suggest that temperatures ranging between 24° and 26 °C correspond to the lower extremity of the thermoneutral zone of resting rats inside the chamber that contains the treadmill belt (Wanner et al., 2015a, 2015b). The hot environment was selected to be at a temperature of 35 °C because even non-exercising rats exposed to this temperature level display marked hyperthermia and activation of cutaneous heat loss (Lima et al., 2013). To heat the environment

2. Materials and methods 2.1. Animals Experiments were performed on six adult male Wistar rats weighing 280–350 g that were supplied by the Animal Resources CEBIO at the Universidade Federal de Minas Gerais (Belo Horizonte, Brazil). Animals were housed collectively and maintained in a room with a 14-h light-10-h dark cycle and ambient temperature controlled at 24 ± 1 °C. After the implantation of an arterial catheter, the rats were housed individually. The rats had free access to water and food. All experimental procedures were approved by the local Ethics Committee for Care and Use of Laboratory Animals (protocol 178/10) and carried out 32

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inside the chamber, an electrical heater (Britânia model AB 1100, Curitiba, PR, Brazil) was positioned at the same level, at a distance of 20–30 cm from the fan, and turned on at 1200 W. The arterial catheter was connected to the pressure transducer. Then, the animals were subjected to incremental-speed treadmill running: during the first 2 min of exercise, the rats ran at 10 m/min, followed by increments of 1 m/min every 2 min until they were fatigued (Wanner et al., 2011). The criterion for defining the end of exercise was the moment at which the animals were no longer able to keep pace with the treadmill for 10 s, even when under light electrical stimulation.

three values (i.e., delays) from ramps with positive or negative slopes. The analysis of spontaneous baroreflex gain provides some important advantages relative to conventional manual measurements because the latter measurements usually require the use of pharmacological agents, which may have direct effects at both peripheral (Casadei and Paterson, 2000) or central sites (Paton et al., 2001), thereby influencing baroreceptor reflex data. Moreover, the time-series analysis reduces the complications related to the injections of vasoactive drugs, which inevitably induce stress in animals caused by indwelling catheters.

2.4. Systolic arterial pressure and heart rate variability analyses

2.6. Calculations

The tape-recorded arterial pressure signal was sampled at 2 kHz. This sampling frequency has been used in previous studies that also performed power spectral analyses on 10-min series of SAP and pulse interval recordings (Bezerra et al., 2001; Chaar et al., 2015). The SAP values were identified beat by beat, and the pulse interval was computed as the interval between two consecutive systolic peaks using a customized routine (MATLAB 7.8, Mathworks, Natick, MA, USA). Time- and frequency-domain analyses and baroreflex sensitivity were evaluated in exercising rats using an 18-min period for the temperate environment and a 10.5-min period for the hot environment. Both periods were selected from continuous recording that were set as the speed interval corresponding to 45–75% of the maximum speed attained by each rat during the incremental exercise. For example, in a rat that attained a maximum speed of 29 m/min at 25 °C, the analyzed interval corresponded to speeds between 13 and 22 m/min. Studies analyzing blood lactate concentrations have shown that 75% of the maximum speed corresponds to the lactate threshold of running rats during incremental- speed exercises (Carvalho et al., 2005; Manchado et al., 2005). Time- and frequency-domain analyses were also performed for exercise intensities corresponding to 75–100% of the maximum speed attained by each rat. This intensity range is accepted as being above the lactate threshold and is associated with increased metabolic and respiratory strain (Katch et al., 1978; Simon et al., 1983). The power spectral density was obtained with fast Fourier transformation, and the size of the evaluated segment was established at 512 points with 50% overlap. The spectral power for very low frequency ([VLF] < 0.2 Hz), low frequency ([LF]=0.2–0.75 Hz), and high frequency ([HF]=0.75–3 Hz) bands was evaluated. To assess the sympatho-vagal balance to the heart, the LF-to-HF ratio of pulse interval variability was calculated (Montano et al., 1994). These bandwidths were previously used to analyze the spectrum of the blood pressure and HR variability in rats (Ceroni et al., 2009; Chaar et al., 2015; Tezini et al., 2013). The integration of the power spectrum density within each frequency bandwidth was obtained with the aid of software (Cardioseries v.2.2, São Paulo, SP, Brazil).

To determine the heat-induced reduction in aerobic performance, the total exercise time (TET) at 35 °C was expressed as a percentage relative to the TET at 25 °C and was calculated in the following manner: (TET at 35 °C/TTE at 25 °C)×100. The same method was used to calculate the heat-induced changes in the components of HR and SAP variability. Both calculations were performed for each of the animals used in this study.

2.7. Statistical Analysis The data are expressed as the means ± standard error of the mean. The Shapiro-Wilk test revealed normal data distribution. The cardiovascular adjustments in response to exercise were compared between ambient temperatures and across time points by two-way ANOVA with repeated measures. The post hoc Tukey test was used for multiple comparisons. The HR and blood pressure variability parameters and the physical performance indices (i.e., the total exercise time, the distance traveled, and the maximum speed attained during the incremental exercises) were compared between environmental conditions using paired Student's t-tests. The correlations between the HR and blood pressure variability parameters and the total exercise time in each environment were assessed using Pearson's coefficient. The correlations between the heat-induced changes in parameters of HR and blood pressure variability and the heat-induced decrement in physical performance were also assessed using Pearson's coefficient. The level of significance was set at p < 0.05. The above-mentioned correlations were classified according to Evans's criteria as follows: 0.00–0.19, very weak; 0.20–0.39, weak; 0.40–0.59, moderate; 0.60– 0.79, strong; and > 0.80, very strong (Evans, 1996).

3. Results 3.1. Physiological responses evoked by incremental-speed exercise in temperate and hot environments Incremental-speed treadmill running increased the mean arterial pressure (MAP) and HR in both environments (Fig. 1), with the exercise-induced increases being more pronounced in the hot than in the temperate environment (changes in BP: 50 ± 3 mmHg, hot vs. 10 ± 4 mmHg, temperate; p < 0.001 and changes in HR: 180 ± 22 bpm in hot vs. 118 ± 9 bpm in temperate; p < 0.05) (Fig. 2). Regarding physical performance, the rats ran for 39 ± 2 min and attained a maximum speed of 29 ± 1 m/min at 25 °C, which indicates that they completed the 19th stage of the incremental exercise. A marked heat-related impairment in exercise capacity was observed. The total exercise time and maximum speed attained during the treadmill running were 38.5% and 24.2% lower, respectively, when the rats exercised in the hot environment (Table 1). Furthermore, the rats showed a significant 48.5% reduction in the total distance traveled in the hot environment compared with the distance traveled in the temperate environment (387 ± 37 m vs. 752 ± 64 m; p=0.0026).

2.5. Spontaneous baroreflex sensitivity (gain) The baroreflex gain was determined from spontaneous changes in blood pressure and pulse interval using a time-series method designed for the rat (Oosting et al., 1997; Waki et al., 2006). First, spontaneously occurring ramps of either decreasing or increasing blood pressure of four beats were used to calculate baroreceptor reflex gain. Second, for each pair of blood pressure and pulse interval ramps, measurements were made at delays of three, four and five beats; this is based on the delay time from a change in blood pressure to a reflex response in pulse interval in the rat as described by Oosting et al. (1997). Third, from these three ramps, plots were made of the changes in pulse interval vs blood pressure to form slopes for each of the delays, and averaged values of the slope were calculated for each of the delays. Finally, the baroreflex sensitivity values quoted represent the mean value of the 33

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Fig. 1. Examples of arterial pressure (mmHg) and heart rate (bpm) recordings depicting the response to the incremental-speed exercise. A: temperate environment. B: hot environment.

3.2. Time and frequency domain of cardiovascular variability during incremental exercises in temperate and hot environments

Table 1 Indices of physical performance of rats subjected to incremental-speed exercise at 25 and 35 °C.

We first compared the time- and frequency-domain of cardiovascular variability and baroreflex sensitivity between the two environments at the interval corresponding to 45–75% of the maximum speed (Table 2). The incremental exercise at 35 °C had a significantly higher SAP variability - standard deviation (SD), variance and HF component - than incremental exercise at 25 °C. Regarding the HRV-associated parameters, exercise in the heat increased the SD, variance and root mean square of successive differences (RMSSD) and all of the frequency-domain parameters (i.e., LF, HF, and LF/HF) relative to the values exhibited by rats running in the temperate environment. There was no difference in baroreflex sensitivity between environments during the exercise interval corresponding to 45–75% of the maximum speed. Of note, the fact that different durations were used to analyze the cardiovascular recordings in the temperate (18 min) and hot

Performance Index

25 °C

35 °C

Decrease %

p-value

Running time (min) Maximum speed (m/min) Distance traveled (m)

39 ± 2 29 ± 1 752 ± 64

24 ± 2 22 ± 1 387 ± 37

38.5 24.2 48.5

0.0026 0.0026 0.0026

(10.5 min) environments did not influence our results. There were no major differences in the results yielded by cardiovascular variability analysis when the recording duration was fixed at 10.5 min for both environments compared to when recordings were made at the speed interval corresponding to 45–75% of the maximum speed (Supplemental material). We then compared the variability at the interval corresponding to 75–100% of the maximum speed between the two environments

Fig. 2. Cardiovascular response induced by incremental-speed exercise in temperate and hot environments. Temporal profile of the exercise-induced changes in the mean arterial pressure (A) and heart rate (B) in temperate (25 °C) and hot (35 °C) environments. The values represent the means ± SEM. *p < 0.05 compared with the temperate environment.

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Table 2 Time- and frequency-domain of cardiovascular variabilities and baroreflex sensitivity of rats at the intervals corresponding to 45–75% and 75–100% of the maximum speed in the temperate and hot environments. 75–100% Smax

Exercise intensity

45–75% Smax

Average parameters

Temperate

Hot

p-value

Temperate

Hot

p-value

“Blood pressure variability” Systolic pressure (mmHg) S.D. (mmHg) Variance (mmHg2) VLF component (mmHg2) LF component (mmHg2) HF component (mmHg2)

140 ± 4.5 6.7 ± 0.7 47.9 ± 9.6 14.0 ± 3.3 12.2 ± 3.9 10.3 ± 1.4

156 ± 6 13.2 ± 2.1* 169.4 ± 42.1* 26.2 ± 9.5 14.6 ± 2.1 17.0 ± 1.4*

0.060 0.016 0.018 0.267 0.592 0.006

144 ± 4 6.3 ± 0.6 41.9 ± 7.4 7.5 ± 2.1 7.4 ± 1.7 13.5 ± 2.3

187 ± 5* 11.5 ± 1.9* 149.6 ± 43.3* 7.4 ± 1.5 9.3 ± 1.0 21.4 ± 1.0*

< 0.001 0.027 0.034 0.954 0.470 0.010

“Heart rate variability” Pulse interval (ms) S.D. (ms) Variance (ms2) RMSSD (ms) LF component (ms2) HF component (ms2) LF-to-HF ratio Baroreflex sensitivity

120 ± 2 6.3 ± 0.8 42.7 ± 11.7 8.7 ± 0.6 0.7 ± 0.1 12.5 ± 1.6 0.050 ± 0.005 1.30 ± 0.04

135 ± 7 11.6 ± 0.8* 139.3 ± 18.2* 15.1 ± 1.4* 4.6 ± 0.6* 47.9 ± 7.3* 0.090 ± 0.006* 1.83 ± 0.23

0.061 < 0.001 0.001 0.002 0.013 < 0.001 < 0.001 0.067

115 ± 2 6.0 ± 0.4 36.6 ± 4.8 9.6 ± 0.8 0.85 ± 0.2 12.7 ± 1.8 0.064 ± 0.003 1.11 ± 0.39

111 ± 5 9.9 ± 1.1* 104.3 ± 20.3* 10.9 ± 0.7 1.3 ± 0.4 17.4 ± 5.4 0.081 ± 0.010 1.07 ± 0.09

0.547 0.006 0.008 0.264 0.345 0.467 0.247 0.929

Data are expressed as means ± SEM. HF=high frequency; LF=low frequency; RMSSD=root mean square of successive differences; S.D.=standard deviation; VLF=very low frequency. * p < 0.05 compared with the temperate environment.

conditions. This analysis was only performed with the variability components that were significantly associated with total exercise time in both environments (i.e., SD, variance, and VLF and LF components of SAP variability during the intensity interval ranging from 45% to 75% of the SMAX). Indeed, very strong negative correlations were observed between heat-induced reduction in physical performance and the heat-induced changes in the VLF (r=0.84; p=0.034) and LF components (r=0.87; p=0.023) but not in the SD and variance of SAP variability (Fig. 4).

(Table 2). Again, incremental exercise at 35 °C exhibited a significantly higher SAP variability - SD, variance and HF component - than incremental exercise at 25 °C. Regarding the HRV-associated parameters, the differences observed with the higher intensity exercise were less evident than those observed at lower intensities. Differences were only observed in SD and variance, with no differences observed in RMSSD or any of the frequency-domain parameters. The baroreflex sensitivity was also not different between environments during the exercise interval corresponding to 75–100% of the maximum speed. Next, we analyzed the power spectral density of the SAP and HR variability of individual rats subjected to incremental exercise. For example, the LF component of SAP variability was higher in animals with lower physical performance at relative to those with higher performance (Fig. 3). Based on these observations, we decided to investigate the associations between the variability parameters and physical performance of the rats. The cardiovascular recordings corresponding to 45–75% of the maximum speed attained by each rat were then analyzed. The total exercise time at 25 °C was significantly and negatively correlated with all components of SAP variability (Table 3). These correlations between total exercise time and SAP variability components were similarly observed at 35 °C, except for the lack of a significant correlation between systolic pressure and physical performance. In contrast, correlations between HRV and physical performance were less evident. A positive and significant correlation was observed for the association between total exercise time and the pulse interval during exercise at 35 °C, and a trend toward a positive and significant correlation was observed at 25 °C (Table 3). We then investigated whether the association between total exercise time and the variability parameters would still be observed when examining the cardiovascular recordings corresponding to 75–100% of the maximum speed (SMAX). No association between total exercise time and SAP variability components were observed in either environment, except for a significant and negative correlation between the systolic pressure and physical performance of rats subjected to exercise at 25 °C (Table 4). Regarding the HRV-related parameters, a significant association between total exercise time and the ratio between the LF and HF (LF-to-HF ratio) was only observed at 25 °C, with a trend toward a positive association at 35 °C (Table 4). The last analysis we performed allowed us to verify whether the changes in cardiovascular variability parameters induced by heat were associated with the reduced performance in such environmental

4. Discussion The present study revisited previously published data (Pires et al., 2013) in which rats were subjected to incremental-speed exercise at two different ambient temperatures while their cardiovascular parameters were recorded. As expected, these rats showed reduced physical performance and exaggerated exercise-induced increases in HR and MAP at 35 °C relative to 25 °C (Table 1 and Fig. 1). In addition, almost all components of HRV were higher at 35 °C than at 25 °C at the lower exercise intensity (45–75% of SMAX), and some of them remained higher at the higher intensity (75–100% of SMAX). Regarding SAP variability, SD and variance were higher in the heat throughout incremental-speed treadmill running. One of the main findings of the present study was the existence of negative and significant correlations between most of the SAP variability components and total exercise time of rats subjected to incremental exercise in both environments. Some correlation coefficients were noticeably high when data corresponding to exercise intensities of 45–75% of the SMAX were analyzed (Table 3). Finally, heat-induced increases in the VLF and LF components of SAP variability were associated with heat-induced impairments of physical performance (Fig. 4). The HRV measurement has been increasingly used as a tool to monitor individual adaptation to training and to avoid the imbalance between intense training load and inadequate recovery periods (Atlaoui et al., 2007; Hedelin et al., 2000; Plews et al., 2013). Changes in HRV during rest or post-exercise have been related to alterations in the autonomic nervous system (ANS) (Hautala et al., 2009; Hedelin et al., 2001; Pichot et al., 2000; Portier et al., 2001). Herein, we propose the use of HRV as a tool for predicting acute physical performance. This proposal is based on the assumptions that recovery is driven by prior fatigue (Bishop et al., 2008; Lehmann et al., 1993) and that an 35

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Fig. 3. Examples of spectral density of SAP variability (mmHg2) during incremental-speed exercise in the temperate environment. Each green line represents one segment number or a hanning window containing 512 points of the spectral analysis. A: Low performance rat that attained 30 min of total exercise time and a maximal speed of 25 m/min. B: High performance rat that attained 46.5 min of total exercise time and a maximal speed of 33 m/min. C: Correlation between the LF component of SAP variability (mmHg2) and total exercise time (min) in the temperate and hot environments. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

(Table 3). This finding is relevant because most studies with athletes do not evaluate SAP variability. In exercising humans, HRV can be easily determined from electrocardiogram recordings or with the use of HR monitors, whereas blood pressure monitoring is more difficult, especially during training sessions or competitions. The maintenance of arterial blood pressure is a major function of the ANS (Dampney, 1994; Dampney et al., 2002), and several physiological responses, including autonomic-mediated responses, are triggered to avoid great oscillations in blood pressure. For instance, elevated pressure variability is an undesirable condition that is commonly observed in patients with hypertension (Masson et al.,

individual will perform better in conditions of entire rather than incomplete recovery. Moreover, the present study proposes the analysis of HRV and SAP variability during exercise, a condition that is characterized by cardiovascular strain and augmented sympathetic outflow to the peripheral organs (Christensen and Galbo, 1983; Rowell and O'Leary, 1990; Shepherd, 1987). Interestingly, our study demonstrated that, at the beginning of incremental exercises, SAP variability is a more powerful tool than HRV to predict fatigue, as evidenced by the significant correlations between most SAP variability components and total exercise time and the scarce significant correlations between HRV and total exercise time

Table 3 Correlations between the total exercise time during incremental exercise and the systolic arterial pressure and heart rate variability parameters at intensities that correspond to 45 – 75% of the maximum speed attained by each rat. The correlations were performed both in temperate (n=6) and hot (n=6) environments. Temperate (25 °C)

Hot (35 °C)

Average parameters

r

p-value

Classification according to Evan's criteria

r

p-value

Classification according to Evan's criteria

“Blood pressure” Systolic pressure (mmHg) S.D. (mmHg) Variance (mmHg2) VLF component (mmHg2) LF component (mmHg2) HF component (mmHg2)

−0.822 −0.873 −0.856 −0.829 −0.915 −0.319

0.044* 0.023* 0.029* 0.041* 0.010* 0.538

Very strong Very strong Very strong Very strong Very strong Weak

−0.345 −0.925 −0.896 −0.942 −0.818 −0.742

0.504 0.008* 0.015* 0.005* 0.046* 0.091

Weak Very strong Very strong Very strong Very strong Strong

“Heart rate” Pulse interval (ms) S.D. (ms) Variance (ms2) RMSSD (ms) LF component (ms2) HF component (ms2) LF-to-HF ratio Baroreflex sensitivity

0.746 −0.113 −0.141 −0.376 −0.585 −0.508 −0.366 0.011

0.088 0.831 0.790 0.462 0.223 0.303 0.476 0.983

Strong Very weak Very weak Weak Moderate Moderate Weak Very weak

0.804 −0.315 −0.294 −0.549 −0.734 0.313 0.470 0.576

0.045* 0.543 0.571 0.259 0.096 0.546 0.347 0.231

Very strong Weak Weak Moderate Strong Weak Moderate Moderate

HF=high frequency; LF=low frequency; RMSSD=root mean square of successive differences; S.D.=standard deviation; VLF=very low frequency. * significant (p < 0.05) correlation.

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Table 4 Correlations between the total exercise time during incremental exercises and the systolic arterial pressure and heart rate variability parameters at intensities that correspond to 75– 100% of the maximum speed attained by each rat. The correlations were performed both in temperate (n=6) and hot (n=6) environments. Temperate (25 °C)

Hot (35 °C)

Average parameters

r

p-value

Classification according to Evan's criteria

r

p-value

Classification according to Evan's criteria

“Blood pressure” Systolic pressure (mmHg) S.D. (mmHg) Variance (mmHg2) VLF component (mmHg2) LF component (mmHg2) HF component (mmHg2)

−0.850 −0.480 −0.538 −0.218 −0.470 0.441

0.032* 0.336 0.271 0.679 0.347 0.381

Very strong Moderate Moderate Weak Moderate Moderate

−0.396 0.350 0.260 −0.737 −0.010 0.176

0.437 0.496 0.619 0.094 0.984 0.739

Weak Weak Weak Strong Very weak Very weak

“Heart rate” Pulse interval (ms) S.D. (ms) Variance (ms2) RMSSD (ms) LF component (ms2) HF component (ms2) LF-to-HF ratio Baroreflex sensitivity

0.784 −0.572 −0.584 −0.513 0.528 −0.265 0.835 0.014

0.065 0.236 0.224 0.298 0.281 0.612 0.038* 0.979

Strong Moderate Moderate Moderate Moderate Weak Very strong Very weak

0.675 −0.174 −0.169 0.011 −0.103 0.452 −0.767 −0.301

0.141 0.741 0.749 0.984 0.846 0.368 0.075 0.562

Strong Very weak Very weak Very weak Very weak Moderate Strong Weak

HF=high frequency; LF=low frequency; RMSSD=root mean square of successive differences; S.D.=standard deviation; VLF=very low frequency. * significant (p < 0.05) correlation.

Fig. 4. Correlations between heat-induced changes in SAP variability components and heat-induced impairment in exercise performance. A: heat-induced impairment in exercise performance and SD of SAP; B: heat-induced impairment in exercise performance and variance of SAP; C: heat-induced impairment in exercise performance and VLF of SAP; D: heatinduced impairment in exercise performance and LF of SAP. Pearson's coefficients and p-values are shown in each panel.

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dependent on exercise intensity (Copp et al., 2010). Miki et al. (2004) showed that the increase in lumbar sympathetic nerve activity caused vasoconstriction of the hindquarter vasculature during rapid eye movement sleep. Thus, the increase in the LF component of SAP variability of the rats exercising at 35 °C would be associated with vasoconstriction of the hindlimb vasculature that may reduce blood flow to the skeletal muscles, thereby affecting substrate supply and consequently physical performance. So far, no study has investigated the association between the LF component of SAP variability and muscle blood flow in exercising rats, and, therefore, the present hypothesis should be evaluated in future studies. In addition, we observed an association between the VLF component of SAP variability and total exercise time during incremental exercise in both environmental conditions (Table 3). The VLF component has been associated with adrenergic sympathetic activity, as evidenced by the fact that infusion of adrenergic vasoconstrictors generated striking VLF fluctuations in blood pressure variability of unrestrained ganglion-blocked rats through stimulation of α2 receptors (Radaelli et al., 2006). In accordance with these findings, the negative correlation between the VLF component and total exercise time in our study shows that the rats with lower performance exhibited augmented adrenergic activity at the beginning of the exercise. This increase in adrenergic activity may have resulted in unbalanced adaptive vasomotor responses to exercising and, thus, contributed to the early interruption of physical exertion. The exacerbated adrenergic activity exhibited by the low performance animals might also reflect the augmented metabolic demands leading to blood flow redistribution to the active skeletal muscles. The CNS regulates the cardiac autonomic function in a reciprocal way, i.e., increased sympathetic activity is usually associated with reduced vagal modulation. In this sense, the LH-to-HF ratio of HRV has been used to simultaneously assess the two branches of the autonomic nervous system (Montano et al., 1994). In our study, the rats with a higher LF-to-HF ratio (i.e., those rats with higher cardiac sympathetic outflow) at higher exercise intensities at 25 °C had lower performance, as shown by the negative correlation between the LF-toHF ratio and total exercise time (Table 4). Our findings corroborate those provided by Hautala et al. (2008), who showed that subjects with lower VO2MAX exhibited a higher LF-to-HF ratio, indicating that low aerobic fitness is associated with augmented cardiac sympathetic activity and suggesting that optimal aerobic fitness is associated with high vagal modulation. Moreover, physical training-mediated increases in performance are thought to be associated with increases in vagalrelated indices of HRV, which lead to reductions in the LF-to-HF ratio (Atlaoui et al., 2007; Buchheit et al., 2012). The correlation between SAP variability and physical performance was more evident when cardiovascular data were analyzed at lower exercise intensities (Tables 3 and 4), most likely when rats were exercising at intensities lower than their lactate threshold. At intensities above this threshold, minute ventilation is greatly increased to aid in acid-base regulation. Marked changes in ventilation affect cardiovascular variability components, particularly by decreasing the HF component of both the HR and SAP variability (Bartels et al., 2004; Beda et al., 2007; Hansson-Sandsten and Jonsson, 2007), usually associated with parasympathetic activity (Hansson-Sandsten and Jonsson, 2007). This respiratory influence may help to explain the lower correlation coefficients when data obtained at higher exercise intensities were analyzed. Together, these observations indicate that analyses of HRV and SAP variability aimed at predicting performance during incremental exercise should be restrained to lower intensities. It is relevant to state that the present investigation consisted of an exploratory study; thus, our data do not assert the existence of a mechanistic link between cardiovascular variability parameters and physical performance, which should be addressed in future studies. In addition, the fact that cardiovascular parameters were associated with total exercise time does not rule out a role of changes in CNS function

2014). In contrast, because changes in HR are relevant to the autonomic regulation of blood pressure, augmented HRV is accepted as an indicator of good health (Achten and Jeukendrup, 2003; JensenUrstad et al., 1997) and generally associated with the positive adaptations resulting from physical training (Atlaoui et al., 2007; Buchheit et al., 2012; Seals and Chase, 1989). Notably, the significant correlations that we observed between the components of SAP variability and physical performance were always negative, whereas the correlations between HRV and performance were positive (Tables 3 and 4). HR and SAP variability can be assessed in both the time- and frequency-domains. HR variability in the time-domain and the HF power of HR variability in the frequency-domain mainly reflect respiratory sinus arrhythmia, which is mediated by parasympathetic cardiac outflow (Akselrod et al., 1981; Goldstein et al., 2011; Hayano et al., 1991; Pomeranz et al., 1985). In contrast, the LF component has been traditionally associated with the cardiac sympathetic outflow, although an alternative interpretation has associated this index with baroreflex function (Goldstein et al., 2011). Finally, the LF-to-HF ratio has been used as an index of the sympatho-vagal balance to the heart (Montano et al., 1994; Pagani et al., 1986), with higher ratio values meaning predominant cardiac sympathetic activity. When analyzing SAP variability, no specific autonomic modulation has been associated with the different components in the time-domain as of yet. Regarding SAP variability analysis in the frequency- domain, the LF power in the spectral density reflects a sympathetic vasomotor modulation (deBoer et al., 1987; Madwed et al., 1989; Waki et al., 2006), whereas the VLF power depends on modifications caused by hormonal agents (Akselrod et al., 1985; Cerutti et al., 1991), including adrenergic vasoconstrictors (Radaelli et al., 2006). Therefore, considering the information presented in this and the previous paragraph, it becomes clear that determination of HR and SAP variability parameters is useful to assess autonomic control over the cardiovascular system. An interesting feature revealed by our analysis was the significant and negative correlation between the LF component of SAP variability at 45–75% of the SMAX and total exercise time (Table 3). Waki et al. (2006) showed a positive correlation between the lumbar sympathetic nerve activity and the LF power of SAP variability, indicating that LF is an index that permits the assessment of changes in vasomotor sympathetic nerve activity. In our study, animals with high levels of lumbar sympathetic activity (those presenting with high LF values at the beginning of the exercise) exhibited low performance (Table 3). In addition, the heat-induced increase in the LF component was positively associated with the heat-induced reduction in total exercise time (Fig. 4), suggesting that high lumbar sympathetic activity may also explain the degraded aerobic performance in hot environments. The lumbar sympathetic chain mostly contains axons of neurons supplying the skeletal muscle and skin of the hindlimb (Habler et al., 1994; Montano et al., 2009), but this sympathetic chain also modulates the vasomotor tone of the tail (Rathner and McAllen, 1998). Based on this anatomo-physiological evidence, there are two hypothetical mechanisms that could explain why a greater increase in the LF component of SAP variability is associated with an impaired physical performance in the heat. First, we have hypothesized that the marked impairment of the physical performance of rats subjected to incremental exercise at 35 °C could at least be partially explained by an increased sympathetic activity to the tail, resulting in reduction of cutaneous heat loss and exacerbated hyperthermia. However, because we have not measured body temperature during this exercise protocol, we cannot state that rats exhibited a reduced cutaneous heat loss during exercise in the heat. Moreover, a decreased thermal gradient between the body and the environment by itself would reduce cutaneous heat loss, regardless of changes in the sympathetic vasomotor tonus of the tail. Another explanation may arise from the fact that blood flow to the hindlimb and the recruitment of highly glycolytic muscle fibers are 38

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variability? Am. J. Physiol. Heart Circ. Physiol. 293, H8-10. Buchheit, M., Simpson, M.B., Al Haddad, H., Bourdon, P.C., Mendez-Villanueva, A., 2012. Monitoring changes in physical performance with heart rate measures in young soccer players. Eur. J. Appl. Physiol. 112, 711–723. Carvalho, J.F., Masuda, M.O., Pompeu, F.A., 2005. Method for diagnosis and control of aerobic training in rats based on lactate threshold. Comparative biochemistry and physiology. Comp. Biochem. Physiol Part A: Mol. Integr. Physiol. 140, 409–413. Casadei, B., Paterson, D.J., 2000. Should we still use nitrovasodilators to test baroreflex sensitivity? J. Hypertens. 18, 3–6. Ceroni, A., Chaar, L.J., Bombein, R.L., Michelini, L.C., 2009. Chronic absence of baroreceptor inputs prevents training-induced cardiovascular adjustments in normotensive and spontaneously hypertensive rats. Exp. Physiol. 94, 630–640. Cerutti, C., Gustin, M.P., Paultre, C.Z., Lo, M., Julien, C., Vincent, M., Sassard, J., 1991. Autonomic nervous system and cardiovascular variability in rats: a spectral analysis approach. Am. J. Physiol. 261, H1292–H1299. Chaar, L.J., Alves, T.P., Batista Junior, A.M., Michelini, L.C., 2015. Early traininginduced reduction of angiotensinogen in autonomic areas-the main effect of exercise on brain renin-angiotensin system in hypertensive rats. PLoS One 10, e0137395. Cheung, S.S., McLellan, T.M., 1998. Heat acclimation, aerobic fitness, and hydration effects on tolerance during uncompensable heat stress. J. Appl. Physiol. 84, 1731–1739. Cheung, S.S., Sleivert, G.G., 2004. Multiple triggers for hyperthermic fatigue and exhaustion. Exerc. Sport Sci. Rev. 32, 100–106. Cheuvront, S.N., Kenefick, R.W., Montain, S.J., Sawka, M.N., 2010. Mechanisms of aerobic performance impairment with heat stress and dehydration. J. Appl. Physiol. 109, 1989–1995. Christensen, N.J., Galbo, H., 1983. Sympathetic nervous activity during exercise. Annu. Rev. Physiol. 45, 139–153. Copp, S.W., Hirai, D.M., Musch, T.I., Poole, D.C., 2010. Critical speed in the rat: implications for hindlimb muscle blood flow distribution and fibre recruitment. J. Physiol. 588, 5077–5087. Crandall, C.G., Gonzalez-Alonso, J., 2010. Cardiovascular function in the heat-stressed human. Acta Physiol. 199, 407–423. Cuddy, J.S., Hailes, W.S., Ruby, B.C., 2014. A reduced core to skin temperature gradient, not a critical core temperature, affects aerobic capacity in the heat. J. Therm. Biol. 43, 7–12. Dampney, R.A., 1994. Functional organization of central pathways regulating the cardiovascular system. Physiol. Rev. 74, 323–364. Dampney, R.A., Coleman, M.J., Fontes, M.A., Hirooka, Y., Horiuchi, J., Li, Y.W., Polson, J.W., Potts, P.D., Tagawa, T., 2002. Central mechanisms underlying short- and longterm regulation of the cardiovascular system. Clin. Exp. Pharmacol. Physiol. 29, 261–268. deBoer, R.W., Karemaker, J.M., Strackee, J., 1987. Hemodynamic fluctuations and baroreflex sensitivity in humans: a beat-to-beat model. Am. J. Physiol. 253, H680–H689. Evans, J.D., 1996. Straightfoward Statistics for the Behavioral Sciences. Brooks/Cole Publishing Company, Pacific Groove, CA. Febbraio, M.A., Carey, M.F., Snow, R.J., Stathis, C.G., Hargreaves, M., 1996. Influence of elevated muscle temperature on metabolism during intense, dynamic exercise. Am. J. Physiol. 271, R1251–R1255. Galloway, S.D., Maughan, R.J., 1997. Effects of ambient temperature on the capacity to perform prolonged cycle exercise in man. Med. Sci. Sports Exerc. 29, 1240–1249. Garet, M., Tournaire, N., Roche, F., Laurent, R., Lacour, J.R., Barthelemy, J.C., Pichot, V., 2004. Individual Interdependence between nocturnal ANS activity and performance in swimmers. Med. Sci. Sports Exerc. 36, 2112–2118. Goldstein, D.S., Bentho, O., Park, M.Y., Sharabi, Y., 2011. Low-frequency power of heart rate variability is not a measure of cardiac sympathetic tone but may be a measure of modulation of cardiac autonomic outflows by baroreflexes. Exp. Physiol. 96, 1255–1261. Habler, H.J., Janig, W., Krummel, M., Peters, O.A., 1994. Reflex patterns in postganglionic neurons supplying skin and skeletal muscle of the rat hindlimb. J. Neurophysiol. 72, 2222–2236. Hansson-Sandsten, M., Jonsson, P., 2007. Multiple window correlation analysis of HRV power and respiratory frequency. IEEE Trans. Bio-med. Eng. 54, 1770–1779. Hautala, A.J., Kiviniemi, A.M., Makikallio, T.H., Tiinanen, S., Seppanen, T., Huikuri, H.V., Tulppo, M.P., 2008. Muscle sympathetic nerve activity at rest compared to exercise tolerance. Eur. J. Appl. Physiol. 102, 533–538. Hautala, A.J., Kiviniemi, A.M., Tulppo, M.P., 2009. Individual responses to aerobic exercise: the role of the autonomic nervous system. Neurosci. Biobehav. Rev. 33, 107–115. Hayano, J., Sakakibara, Y., Yamada, A., Yamada, M., Mukai, S., Fujinami, T., Yokoyama, K., Watanabe, Y., Takata, K., 1991. Accuracy of assessment of cardiac vagal tone by heart rate variability in normal subjects. Am. J. Cardiol. 67, 199–204. Hedelin, R., Bjerle, P., Henriksson-Larsen, K., 2001. Heart rate variability in athletes: relationship with central and peripheral performance. Med. Sci. Sports Exerc. 33, 1394–1398. Hedelin, R., Kentta, G., Wiklund, U., Bjerle, P., Henriksson-Larsen, K., 2000. Short-term overtraining: effects on performance, circulatory responses, and heart rate variability. Med. Sci. Sports Exerc. 32, 1480–1484. Hynynen, E., Uusitalo, A., Konttinen, N., Rusko, H., 2008. Cardiac autonomic responses to standing up and cognitive task in overtrained athletes. Int. J. Sports Med. 29, 552–558. Jensen-Urstad, K., Storck, N., Bouvier, F., Ericson, M., Lindblad, L.E., Jensen-Urstad, M., 1997. Heart rate variability in healthy subjects is related to age and gender. Acta Physiol. Scand. 160, 235–241. Katch, V., Weltman, A., Sady, S., Freedson, P., 1978. Validity of the relative percent

and/or thermoregulatory parameters (i.e., TCORE and the core-to-skin temperature gradient) in the modulation of physical performance in the heat. More recent theoretical models to explain exercise fatigue and performance propose that changes occurring at different peripheral physiological systems act as afferent signalers, which modulate control processes in the brain in a dynamic, nonlinear, and integrative manner (Lambert et al., 2005). 5. Conclusion In conclusion, the rats with lower physical performance exhibited high SAP variability at the beginning of exercise, whereas the rats with higher performance had low variability. Indeed, most of the SAP variability components were significantly and negatively correlated with performance, irrespective of the environmental conditions. In contrast, scarce significant correlations were observed between HRV and total exercise time. Taken together, these results suggest that evaluation of SAP variability at the beginning of an incremental exercise is a tool that predicts the physical performance of rats. Finally, heat-induced changes in some components of SAP variability (i.e., VLF and LF) were associated with heat-induced reductions in performance, suggesting that the autonomic control of the cardiovascular system, particularly augmented sympathetic activity, contributes to the degraded aerobic performance in hot environments. Acknowledgements This work was supported by Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG; grant APQ-01946-14). WP is recipient of a postdoctoral fellowship from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq; grant 168145/ 2014-6). FCMR is recipient of a postdoctoral fellowship from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES; grant 2251/2011). Appendix A. Supporting information Supplementary data associated with this article can be found in the online version at doi:10.1016/j.jtherbio.2016.11.006. References Achten, J., Jeukendrup, A.E., 2003. Heart rate monitoring: applications and limitations. Sports Med. 33, 517–538. Ainsworth, B.E., Haskell, W.L., Herrmann, S.D., Meckes, N., Bassett, D.R., Jr., TudorLocke, C., Greer, J.L., Vezina, J., Whitt-Glover, M.C., Leon, A.S., 2011. 2011 Compendium of Physical Activities: a second update of codes and MET values. Med. Sci. Sports Exerc. 43, 1575–1581. Akselrod, S., Gordon, D., Madwed, J.B., Snidman, N.C., Shannon, D.C., Cohen, R.J., 1985. Hemodynamic regulation: investigation by spectral analysis. Am. J. Physiol. 249, H867–H875. Akselrod, S., Gordon, D., Ubel, F.A., Shannon, D.C., Berger, A.C., Cohen, R.J., 1981. Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-tobeat cardiovascular control. Science 213, 220–222. Atlaoui, D., Pichot, V., Lacoste, L., Barale, F., Lacour, J.R., Chatard, J.C., 2007. Heart rate variability, training variation and performance in elite swimmers. Int. J. Sports Med. 28, 394–400. Bartels, M.N., Jelic, S., Ngai, P., Gates, G., Newandee, D., Reisman, S.S., Basner, R.C., De Meersman, R.E., 2004. The effect of ventilation on spectral analysis of heart rate and blood pressure variability during exercise. Respir. Physiol. Neurobiol. 144, 91–98. Beda, A., Jandre, F.C., Phillips, D.I., Giannella-Neto, A., Simpson, D.M., 2007. Heart-rate and blood-pressure variability during psychophysiological tasks involving speech: influence of respiration. Psychophysiology 44, 767–778. Bezerra, S.M., dos Santos, C.M., Moreira, E.D., Krieger, E.M., Michelini, L.C., 2001. Chronic AT(1) receptor blockade alters autonomic balance and sympathetic responses in hypertension. Hypertension 38, 569–575. Bishop, P.A., Jones, E., Woods, A.K., 2008. Recovery from training: a brief review: brief review. J. Strength Cond. Res./Natl. Strength Cond. Assoc. 22, 1015–1024. Bosquet, L., Merkari, S., Arvisais, D., Aubert, A.E., 2008. Is heart rate a convenient tool to monitor over-reaching? A systematic review of the literature. Br. J. Sports Med. 42, 709–714. Buchheit, M., Papelier, Y., Laursen, P.B., Ahmaidi, S., 2007. Noninvasive assessment of cardiac parasympathetic function: postexercise heart rate recovery or heart rate

39

Journal of Thermal Biology 63 (2017) 31–40

F.C. Müller-Ribeiro et al.

Pires, W., Wanner, S.P., Lima, M.R., Fonseca, I.A., Fumega, U., Haibara, A.S., Coimbra, C.C., Lima, N.R., 2013. Physical exercise performance in temperate and warm environments is decreased by an impaired arterial baroreflex. PLoS One 8, e72005. Plews, D.J., Laursen, P.B., Stanley, J., Kilding, A.E., Buchheit, M., 2013. Training adaptation and heart rate variability in elite endurance athletes: opening the door to effective monitoring. Sports Med. 43, 773–781. Pomeranz, B., Macaulay, R.J., Caudill, M.A., Kutz, I., Adam, D., Gordon, D., Kilborn, K.M., Barger, A.C., Shannon, D.C., Cohen, R.J., et al., 1985. Assessment of autonomic function in humans by heart rate spectral analysis. Am. J. Physiol. 248, H151–H153. Portier, H., Louisy, F., Laude, D., Berthelot, M., Guezennec, C.Y., 2001. Intense endurance training on heart rate and blood pressure variability in runners. Med. Sci. Sports Exerc. 33, 1120–1125. Radaelli, A., Castiglioni, P., Centola, M., Cesana, F., Balestri, G., Ferrari, A.U., Di Rienzo, M., 2006. Adrenergic origin of very low-frequency blood pressure oscillations in the unanesthetized rat. Am. J. Physiol. Heart Circ. Physiol. 290, H357–H364. Radigan, L.R., Robinson, S., 1949. Effects of environmental heat stress and exercise on renal blood flow and filtration rate. J. Appl. Physiol. 2, 185–191. Rathner, J.A., McAllen, R.M., 1998. The lumbar preganglionic sympathetic supply to rat tail and hindpaw. J. Auton. Nerv. Syst. 69, 127–131. Rodrigues, L.O., Oliveira, A., Lima, N.R., Machado-Moreira, C.A., 2003. Heat storage rate and acute fatigue in rats. Braz. J. Med. Biol. Res.=Rev. Bras. Pesqui. Med. Biol./ Soc. Bras. Biofis. … [et al.] 36, 131–135. Rowell, L.B., Brengelmann, G.L., Blackmon, J.R., Twiss, R.D., Kusumi, F., 1968. Splanchnic blood flow and metabolism in heat-stressed man. J. Appl. Physiol. 24, 475–484. Rowell, L.B., O'Leary, D.S., 1990. Reflex control of the circulation during exercise: chemoreflexes and mechanoreflexes. J. Appl. Physiol. 69, 407–418. Seals, D.R., Chase, P.B., 1989. Influence of physical training on heart rate variability and baroreflex circulatory control. J. Appl. Physiol. 66, 1886–1895. Shepherd, J.T., 1987. Circulatory response to exercise in health. Circulation 76, VI3–10. Simon, J., Young, J.L., Gutin, B., Blood, D.K., Case, R.B., 1983. Lactate accumulation relative to the anaerobic and respiratory compensation thresholds. J. Appl. Physiol.: Respir. Environ. Exerc. Physiol. 54, 13–17. Tezini, G.C., Dias, D.P., Souza, H.C., 2013. Aerobic physical training has little effect on cardiovascular autonomic control in aging rats subjected to early menopause. Exp. Gerontol. 48, 147–153. Uusitalo, A.L., Uusitalo, A.J., Rusko, H.K., 1998. Endurance training, overtraining and baroreflex sensitivity in female athletes. Clin. Physiol. 18, 510–520. Waki, H., Katahira, K., Polson, J.W., Kasparov, S., Murphy, D., Paton, J.F., 2006. Automation of analysis of cardiovascular autonomic function from chronic measurements of arterial pressure in conscious rats. Exp. Physiol. 91, 201–213. Wanner, S.P., Costa, K.A., Soares, A.D., Cardoso, V.N., Coimbra, C.C., 2014. Physical exercise-induced changes in the core body temperature of mice depend more on ambient temperature than on exercise protocol or intensity. Int. J. Biometeorol. 58, 1077–1085. Wanner, S.P., Guimaraes, J.B., Pires, W., Marubayashi, U., Lima, N.R., Coimbra, C.C., 2011. Muscarinic receptors within the ventromedial hypothalamic nuclei modulate metabolic rate during physical exercise. Neurosci. Lett. 488, 210–214. Wanner, S.P., Leite, L.H., Guimaraes, J.B., Coimbra, C.C., 2015a. Increased brain Larginine availability facilitates cutaneous heat loss induced by running exercise. Clin. Exp. Pharmacol. Physiol. 42, 609–616. Wanner, S.P., Prímola-Gomes, T.N., Pires, W., Guimarães, J.B., Hudson, A.S.R., Kunstette, rA.C., Fonseca, C.G., Drummond, L.R., Damasceno, W.C., TeixeiraCoelho, F., 2015b. Thermoregulatory responses in exercising rats: methodological aspects and relevance to human physiology. Temperature 2, 457–475. Whipp, B.J., Ward, S.A., Wasserman, K., 1984. Ventilatory responses to exercise and their control in man. Am. Rev. Respir. Dis. 129, S17–S20.

concept for equating training intensity. Eur. J. Appl. Physiol. Occup. Physiol. 39, 219–227. Kunstetter, A.C., Wanner, S.P., Madeira, L.G., Wilke, C.F., Rodrigues, L.O., Lima, N.R., 2014. Association between the increase in brain temperature and physical performance at different exercise intensities and protocols in a temperate environment. Braz. J. Med. Biol. Res.=Rev. Bras. Pesqui. Med. Biol./Soc. Bras. Biofis. … [et al.] 47, 679–688. Lambert, E.V., St, Clair Gibson, A., Noakes, T.D., 2005. Complex systems model of fatigue: integrative homoeostatic control of peripheral physiological systems during exercise in humans. Br. J. Sports Med. 39, 52–62. Laughlin, M.H., 1999. Cardiovascular response to exercise. Am. J. Physiol. 277, S244–S259. Lehmann, M., Foster, C., Keul, J., 1993. Overtraining in endurance athletes: a brief review. Med. Sci. Sports Exerc. 25, 854–862. Leon, L.R., Helwig, B.G., 2010. Heat stroke: role of the systemic inflammatory response. J. Appl. Physiol. 109, 1980–1988. Lima, M.R., Pires, W., Fonseca, I.A., Fonseca, C.G., Martinelli, P.M., Wanner, S.P., Lima, N.R., 2013. Chronic sympathectomy of the caudal artery delays cutaneous heat loss during passive heating. Neurosci. Lett. 537, 11–16. Madwed, J.B., Albrecht, P., Mark, R.G., Cohen, R.J., 1989. Low-frequency oscillations in arterial pressure and heart rate: a simple computer model. Am. J. Physiol. 256, H1573–H1579. Manchado, F.B., Gobatto, C.A., Contarteze, R.V.L., Papoti, M., de Mello, M.A.R., 2005. Maximal lactate steady state in running rats. J. Exerc. Physiol. Online 8, 29–35. Masson, G.S., Costa, T.S., Yshii, L., Fernandes, D.C., Soares, P.P., Laurindo, F.R., Scavone, C., Michelini, L.C., 2014. Time-dependent effects of training on cardiovascular control in spontaneously hypertensive rats: role for brain oxidative stress and inflammation and baroreflex sensitivity. PLoS One 9, e94927. Miki, K., Oda, M., Kamijyo, N., Kawahara, K., Yoshimoto, M., 2004. Lumbar sympathetic nerve activity and hindquarter blood flow during REM sleep in rats. J. Physiol. 557, 261–271. Montano, N., Furlan, R., Guzzetti, S., McAllen, R.M., Julien, C., 2009. Analysis of sympathetic neural discharge in rats and humans. Philos. Trans. Ser. A Math. Phys. Eng. Sci. 367, 1265–1282. Montano, N., Ruscone, T.G., Porta, A., Lombardi, F., Pagani, M., Malliani, A., 1994. Power spectrum analysis of heart rate variability to assess the changes in sympathovagal balance during graded orthostatic tilt. Circulation 90, 1826–1831. Nielsen, B., Hales, J.R., Strange, S., Christensen, N.J., Warberg, J., Saltin, B., 1993. Human circulatory and thermoregulatory adaptations with heat acclimation and exercise in a hot, dry environment. J. Physiol. 460, 467–485. Oosting, J., Struijker-Boudier, H.A., Janssen, B.J., 1997. Validation of a continuous baroreceptor reflex sensitivity index calculated from spontaneous fluctuations of blood pressure and pulse interval in rats. J. Hypertens. 15, 391–399. Pagani, M., Lombardi, F., Guzzetti, S., Rimoldi, O., Furlan, R., Pizzinelli, P., Sandrone, G., Malfatto, G., Dell'Orto, S., Piccaluga, E., et al., 1986. Power spectral analysis of heart rate and arterial pressure variabilities as a marker of sympatho-vagal interaction in man and conscious dog. Circ. Res. 59, 178–193. Paton, J.F., Deuchars, J., Ahmad, Z., Wong, L.F., Murphy, D., Kasparov, S., 2001. Adenoviral vector demonstrates that angiotensin II-induced depression of the cardiac baroreflex is mediated by endothelial nitric oxide synthase in the nucleus tractus solitarii of the rat. J. Physiol. 531, 445–458. Pichot, V., Roche, F., Gaspoz, J.M., Enjolras, F., Antoniadis, A., Minini, P., Costes, F., Busso, T., Lacour, J.R., Barthelemy, J.C., 2000. Relation between heart rate variability and training load in middle-distance runners. Med. Sci. Sports Exerc. 32, 1729–1736. Pires, W., Wanner, S.P., La Guardia, R.B., Rodrigues, L.O., Silveira, S.A., Coimbra, C.C., Marubayashi, U., Lima, N.R., 2007. Intracerebroventricular physostigmine enhances blood pressure and heat loss in running rats. J. Physiol. Pharmacol. 58, 3–17.

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