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1 Laboratory of Experimental Cardiology, School of Medicine, K. U. Leuven, Belgium2 General Internal Medicine, University Hospital Gasthuisberg, K. U. Leuven, Belgium3 Laboratory for Agricultural Buildings, K. U. Leuven, Belgium
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(Received 13 December 2003;
accepted after revision 5 January 2004)
Corresponding author A. Aubert: Department of Cardiology, UZ Gasthuisberg O-N Herestraat 49, B-3000 Leuven, Belgium. Email: andre.aubert{at}med.kuleuven.ac.be
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Introduction |
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Detection of these fluctuations is obtained from computations of instantaneous heart rate, usually from ECG strips. However in avian embryos, heart rate has usually been determined non-invasively with other techniques (Tazawa et al. 1989a,b, 1992, 1993; Rahn et al. 1990; Hashimoto et al. 1991; Haque et al. 1994; Ono et al. 1994; Sakamoto et al. 1995; Leribaux et al. 1999; Aubert et al. 2000, 2001). These methods have some drawbacks for HRV determination. (1) The duration of measurement is sometimes limited for technical reasons. (2) They can be expensive or difficult to use. (3) Most often the accuracy is insufficient on a beat-to-beat basis.
In a previous study we obtained non-invasive recordings of the embryonic ECG (Aubert et al. 2000). In this study we improved our technique for recording high quality ECG signals from chicken embryos in their final developmental stage. It allowed us to compute HRV parameters, related to the autonomic modulation of the heart rate.
Previous studies on autonomic cardiovascular regulation in chicken embryos have indicated that functional vagal innervation appears already on day 12 of development (Pappano & Löffelholz, 1974), implying that autonomic regulation of heart rate could be operational during the last stage of chicken ontogeny. The aim of this work was to test the hypothesis that autonomic nervous cardiac modulation, as shown from HRV parameters, is present at the end of development and that it reaches a constant value during the last days of incubation.
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Methods |
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The experiments were performed in accordance with the international directions for the protection of animals used for scientific purposes and approved by the local ethical committee.
Measurement system
The content of the egg is an electrically conductive mass. The electrical excitation generated by the heart propagates through the embryonic body, the extra-embryonic fluids and the egg contents towards the eggshell. This electrical signal (ECG) can be detected with electrodes piercing the eggshell (Haque et al. 1994; Sugiyama et al. 1996; Pearson et al. 1998; Kato et al. 2002). Metal alloy electrodes with a diameter of 0.5 mm were used. Each electrode wire was bent at right angles 3–4 mm from one end. They were inserted into a small hole made by drilling on the upper surface of the egg. Three places were marked on the shell so that approximately an equilateral triangle with a side of about 3 cm was obtained. The needle electrodes were fixed onto the shell with hypodermic tape. Data recording was started after a stabilization period of 8–12 h.
The electrodes were connected to an ECG amplifier (Siemens Mingograph 82). Recordings were obtained during 5 min on days 19 and 20 of the incubation period. In adult humans, with a heart rate of approximately 5 times slower, a recording duration of 10 min is recommended (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996). A 5 min duration proved to be a good compromise between frequency resolution and stationarity. All measurements were obtained with the egg in the incubator. Recordings were made in the morning between 08.00 h and 10.00 h.
Data acquisition
Analog–digital conversion was performed with an external Dataq A/D converter (Dataq DI 220PGH, 8 channels, 12 bit precision, maximal 82.9 kHz sampling rate over all channels, DATAQ Instruments Inc., Akron, OH, USA). A PC, equipped with Windaq recording software (DATAQ Instruments Inc.), performed real-time digital signal acquisition to hard disk. The sampling rate was 1000 Hz per channel, thus giving a time resolution for the RR intervals of 1 ms. Baseline drift of the ECG was removed with a moving average method, corresponding to high-pass filtering.
Data analysis: embryonic ECG measurements
The continuous digitized ECG signal from each embryonic heart recording was analysed for time intervals and spectral analysis. Time intervals on the ECG were determined according to accepted international standards (Andries et al. 1999). Digital ECG strips were read by three cardiologists and mean values obtained on 10 consecutive heart beats.
Frequency analysis, with fast Fourier transform (FFT) techniques, was performed on selected ECG strips after applying a Hanning window and digital low-pass filtering (–3 db at 24 Hz).
Data analysis: tachogram measurements
Pre-processing and peak detection of the Windaq files with the ECG signal was performed with software as previously described (automated calculation of tachograms and systograms (ACTS); Beckers et al. 1999), that was written in LabVIEW 4.0.1. HRV parameters were calculated in general agreement with the standards of measurement proposed by the Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (1996). The discrete time series values of RR intervals derived from ACTS were used as input to the LabVIEW program Main Analysis 2.0 (Aubert et al. 1999). Premature ectopic beats or artifacts were eliminated by careful editing and visual inspection of the signals (Aubert et al. 1998). In case of ectopic beats, two linear filters could be applied to correct for data points outside a limit interval.
Time domain. Parameters in the time domain were determined on the original tachogram: mean and standard deviation (S.D.) of RR tachogram, maximum and minimum of RR values, the square root of the mean of the sum of the squares of differences between adjacent RR intervals (rMSSD), percentage of intervals that vary by more than 5 ms from the previous beat (pNN5; value of 5 ms was selected because of the high mean heart rate in chicken embryos: 200–300 beats min–1) and the standard deviation of the 1 min average of RR intervals (SDANN1).
Frequency domain. Different approaches can be used to circumvent the problem caused by a series of point events with variable distance on a time scale (de Boer et al. 1984, 1985; Berger et al. 1986). In this study we used equidistant sampling of the event series (RR intervals) by using a cubic spline approximation (Kreyszig, 1979; Aubert et al. 1998, 1999).
On the tachogram, data sets consisting of 256 points (this corresponds to a time window of 25.6 s), and overlapping by 50% were processed. This method is based on multiple computation and averaging of the fast Fourier transform (FFT) of overlapping data segments. For each data set the DC component was removed by subtracting the mean value and a Hanning window was applied. Power spectral density (in ms2 Hz–1) was then computed using a FFT algorithm. The frequency resolution (Ramirez, 1985) was: 
f= 1/(N x t) or 0.039 Hz (N, number of points (256); t, time resolution (0.1 s)). The maximum frequency was: fmax=f x N/2 or 5 Hz. Two frequency bands were defined with limits as used in small animals with high heart rate (Aubert et al. 1999): a low frequency (LF) band from 0.195 to 0.74 Hz and a high frequency (HF) band from 0.78 to 2.5 Hz. Within each frequency band, power was computed by integration of the power spectral density function, in absolute values of low, high and total power (in ms2), and a low-to-high ratio.
Statistical analysis
Statistical analysis was performed with SPSS for Windows Release 7.5 (Scientific Packages for Social Sciences, Inc., Chicago, IL, USA). To test the association between the different indices at different days, a non-parametric Mann–Whitney U rank-sum test was calculated. With this procedure, assumptions about the distribution of the observations were avoided. To test the association between the different indices at days 19 and 20 of incubation, a Spearman rank correlation coefficient was calculated. Data are expressed as mean ±S.D. and 95% confidence interval for the mean (Gardner & Altman, 1999). Differences with P < 0.05 were considered statistically significant.
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Figure 1 shows an example of a short strip of an ECG recording taken from a 20-day-old embryo. The QRS deflections are prominent and automatic peak detection can easily be performed. The amplitudes of the QRS deflections are of the order of microvolts.
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Figure 2 shows the spectral analysis (power spectral density) of an ECG recording lasting 4.096 s. Different peaks corresponding to breathing and heart rate can be distinguished on this spectrum. Breathing frequency has been determined previously with an independent method (Leribaux et al. 1999) based on ballistocardiography. Basic heart rate corresponds to the peak at 5.18 Hz (311 beats min–1, comparing with 314 ± 2.6 beats min–1 as found in the time domain on the ECG strip of Fig. 1) and harmonics at 10.34 Hz, 15.58 Hz and 21.5 Hz. The larger amplitude of the harmonic peak at 15.58 Hz is probably due to interference of this HR harmonic with PR periodicity (range, 15.7–16.6 Hz).
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Tachogram and embryonic heart rate variability
Figure 3 (upper trace) presents a tachogram obtained from the RR intervals of the entire 5 min ECG recording of a 20-day-old embryo. The mean RR interval of 205.6 ms corresponds to a mean heart rate over the total period of 291.8 beats min–1.
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No significant differences between HRV indices in both time and frequency domain, obtained at 19 days and at 20 days of incubation, are present (Table 1).
For all indices an association between mean RR and HRV parameters rMSSD and pNN5 exists (Table 2). A lesser correlation is present between parameters reflecting global variability such as variance and total power. No correlation is present with SDANN1. As expected, the different time-domain vagal indices pNN5 and rMSSD correlate very well (r= 0.95), as does the global variability reflecting time-domain parameters variance and total power. RMSSD and pNN5 correlate with frequency-domain LF and HF power. The frequency-domain parameter total power shows a strong association with LF and HF power. LF is also associated with HF power. No correlation is present between LF/HF and the other HRV parameters.
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Discussion |
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Determination of heart rate
As in different individuals, in all species resting heart rate varies (Aubert & Ramaekers, 1999; Massimini et al. 2000). However as a general rule, the smaller the animal, the higher its heart rate and breathing rate. Also during embryonic development changes in heart rate will occur (Yu & Lumbers, 2000).
ECG recordings in chicken embryos during late incubation are not easy to obtain due to the small amplitude and movement artefacts. The amplitude problem was overcome in a study by Kato et al. (2002) by using emu eggs with a mass of 600 g and therefore a larger heart mass resulting in a larger amplitude ECG signal. Motion artefacts can be removed with adequate signal filtering techniques. The recording of motility, postural reflexes and ventilatory activities is in itself of importance in studying the development of the embryo (Pappano, 1975). However in our study the main accent was on obtaining technically excellent ECG signals, enabling an adequate QRS peak detection and subsequent computing of the tachogram. Baseline drift due to motion was also removed by high-pass filtering, imposed by a moving average and careful editing after peak detection to obtain a tachogram.
The mean heart rate as obtained in this study (246 beats min–1, with a range of 207–314 beats min–1) is within the range given by several authors in chicken embryos. In a previous study (Aubert et al. 2000) we reported heart rate values ranging between 250 and 270 beats min–1 on days 19 and 20 of incubation. All studies on mean heart rates reported so far obtained similar results. In two different studies, the following values were reported by Tazawa et al. (1989b, 1991): 277 ± 12 and 266 ± 11 (day 19); and 298 ± 12 and 300 ± 21 (day 20), respectively. In a study of instantaneous heart rate obtained from blood pressure recordings Höchel et al. (1998) reported nearly identical values on day 19 (244 ± 5 beats min–1) and on day 20 (243 ± 9 beats min–1).
Interesting to note is the close correlation between mean values for breathing frequency and heart rate obtained from the frequency spectrum of the ECG (Fig. 2) and the instantaneous values obtained from HRV analysis. However, the main advantage of HRV analysis (tachogram on Fig. 3) is to have instantaneous values for HR to the contrary of mean values over the time duration of the ECG strip as used for power spectral density determination on an ECG epoch (Fig. 2).
Rather unexpected is that the ratio between heart rate and breathing frequency does not correspond to a rational number. In humans under resting or sleeping conditions this ratio is very near to an integer, usually 4:1. This is also found during anaesthesia. In anaesthetized rats breathing at an imposed frequency of 1.25 Hz, we found (Aubert et al. 1999) a corresponding heart rate of 300, resulting in a ratio of 4:1. Galletly & Larsen (2001) obtained similar findings in anaesthetized humans.
On the other hand the ratio is not always an integer in the case of non-absolute resting conditions in humans. Strano et al. (1998) and Penntilläet al. (2001) showed that in supine-positioned humans breathing at four different imposed breathing rates, the mean heart rate did not change. Consequently the ratio must vary from integer to non-integer. Under similar circumstances (breathing imposed at fixed rates) we found ratios of 4.07, 5.08 and 5.5 at imposed breathing rates of 0.25, 0.2 and 0.15 Hz, respectively. Also under six different conditions of solvent inhalation (Hauman et al. 2003) one integer number was found and five non-integer (4.03, 4.74, 4.4, 4.36 and 4.35).
In view of all these arguments from our data and from data in the literature, it is not surprising to find a non-integer ratio between heart rate and breathing frequency for the following reasons: (1) we did not use any anaesthesia; and (2) it can be assumed that the embryo was not asleep during the recordings.
Breathing, heart rate and heart rate variability
At day 19 lung breathing is starting (Romanoff, 1968). This causes large mechanical fetal movements (Altimiras & Crossley, 2000) that are measurable on the egg shell. Previously (Leribaux et al. 1999) we reported the onset of breathing on day 19, measured with a ballistocardiogram method. A respiration frequency of 1.19 Hz (71.12 respirations min–1) was found, similar to the value shown in Fig. 2, obtained from FFT analysis of the ECG. Akiyama et al. (1999) detected the onset of breathing on day 18–19 with an acoustocardiogram method. They reported values between 1 and 1.5 Hz prior to hatching.
Recently Tazawa et al. (2003) reported HF oscillations between 0.4 and 1.25 Hz in newly hatched chicken. These oscillations were described as being related to respiratory sinus arrhythmia (Moriya et al. 2000).
Respiration modulates heart rate (increase of heart rate during inspiration and decrease during expiration). This modulation is expected to show in the spectrum obtained from FFT analysis of the ECG time strip. So it can be stated with confidence that the values shown in Fig. 2 correspond to breathing frequency. Moreover they are comparable to values obtained from independent methods (Akiyama et al. 1999; Leribaux et al. 1999) (see also Appendix).
Respiration is one of the sources of cardiovascular variability and the respiratory peak can be used as an estimate for vagal activity, a measure for the integrity of vagal control and a detector of its possible malfunction (Akselrod, 1995). It can be measured as the HF component in the power spectral density of HRV. As breathing rate is altered, this HF component will move accordingly as was described in humans (Akselrod, 1995). Due to technical limitations of our experimental set-up we were unable to perform such interventions on the chicken eggs. However own similar experiments in humans are described in the Appendix.
Heart rate variability
This is to our knowledge, the first time that spectral analysis was performed from tachograms computed from ECG recordings of embryonic heart in chickens. In the wide diversity of mammals investigated in the literature, essentially the same spectral pattern can be observed (Akselrod, 1995; Akiyama et al. 1999), even if resting heart rate varies widely. For this reason the LF and HF regions in the spectrum need to be adapted to the species under study. Previously we established these limits in rat experiments (Aubert et al. 1999). The same regions were used in this study as the heart rate in these animals is comparable (280–320 beats min–1 in rats) and the frequency limits for LF and HF were defined as 0.195–0.74 Hz and 0.78–2.5 Hz, respectively. A methodological improvement to confirm frequency limits (although technically difficult in the egg) would be using a vasoconstrictor, a sympatholytic or parasympatholytic drug, to see whether spectral power would show the predicted changes if autonomic control was present.
The power distribution in two principal frequency ranges can be interpreted in view of the neural branches controlling or transferring the fluctuations to the cardiovascular system (Akselrod et al. 1981). The LF content is thought to represent sympathetic and parasympathetic modulation with a possible involvement of the baroreflex. The HF component on the other hand is attributed to parasympathetic or vagal mechanisms and is related to the respiratory cycles and/or respiratory sinus arrhythmia (Malpas, 2002), as described above. This is illustrated in Fig. 3 where the HF peak at 1.4 Hz corresponds to a breathing frequency of 84 min–1.
The relationship between various time-domain indices was studied previously in humans (Kleiger et al. 1991) and in rats (Ramaekers, 1999). It was shown that the variables calculated from the differences between adjacent cycles such as pNN5 and rMSSD are highly correlated. Similar results were shown in this study (Table 2). These parameters are widely accepted as estimates of short-term components of HRV, strongly reflecting modulations of vagal tone, as shown from the high correlation with HF (Table 2). Parseval's theorem states that the total energy computed in the time domain (reflected in S.D.) must equal the total energy computed in the frequency domain (conservation of energy). Therefore it is not surprising that total power and its components (LF and HF) are correlated to S.D. (Table 2). Also parameters shown to reflect mainly parasympathetic activity (pNN5 and rMSSD) correlate well with HF. They also correlate with LF, suggesting influence by both vagal and sympathetic tone.
Autonomic nervous system
An interesting finding is the lack of significant difference between all HRV indices of day 19 compared to day 20 (Table 1). Confidence intervals were compared (Gardner & Altman, 1999), and it was found that they overlap and are in the same range. This fact suggests that the autonomic nervous system of the chick embryo has already reached a constant level or an equilibrium on day 19 of incubation. This result is in agreement with previous reports indicating that the vagal pathway to the heart becomes functional after 5 or 6 days of incubation (LeGrande et al. 1966) and that the sympathetic nerve fibres are present on day 10 (Pappano & Löffelholz, 1974). Sympathetic control of the heart is established by the 15th or 16th day (Pappano, 1975; Kirby & Steward, 1986). Characterization of ECG changes at embryonic day 17 showed a maturity of the sympathetic and parasympathetic nervous systems (LeGrande et al. 1966). The development of innervation and the embryonic growth that may be associated with different somatic activities may be related to the changes in daily heart rates reported in the literature (Tazawa et al. 1991; Höchel et al. 1998). Our finding was similar to that reported by Altimiras & Crossley (2000). They showed that baroroflex regulation begins late in incubation and the gain of this reflex matures over the final 3 days of incubation.
Heart rate variations are dependent on activity of the autonomic nervous system and its different components, which not only differ in their function of accelerating or decelerating the heart, but also in their neurogenic or humoral origin which conditions the time constant of their influence (Crossley et al. 2003). Roughly speaking the main function of the vagus is to slow the heart rate down whereas the sympathetic accelerates it. In fact these functions depend on the balance of the driving system.
Applications of this model
Stable ECG tracings could be obtained from chicken embryos at the end of their incubation from these experiments. The question of whether chicken embryos could be used as an alternative experimental animal for cardiovascular investigations has already been partially answered by Sugiyama et al. (1996) who studied the influence of anaesthesia on chicken embryonic heart rate. Crossley et al. (2003) studied the influence of hypoxia and temperature on chicken embryos. Therefore this model may be applicable for the investigation of the developing heart and the evaluation of cardiovascular drugs.
Study limitations
There are a number of limitations to this study.
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To our knowledge this is one of the first attempts to apply HRV methods in the evaluation of chicken fetal heart rate, obtained from ECG recordings, without anaesthesia. This offers new possibilities for studying the evolution of the autonomic nervous system during its embryonic phase.
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Appendix |
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Synchronized breathing. Synchronization of breathing and heart rate (increase of heart rate during inspiration and decrease during expiration) has since long been a landmark in HRV determination. Previously (Aubert et al. 1999) we described an experiment with an anaesthetized rat with artificial breathing at a rate of 75 min–1 (1.25 Hz). Due to the anaesthesia the power spectral density is completely depressed, with the exception of a large peak due to the respiratory sinus arrhythmia at 1.25 Hz and a harmonic at 2.5 Hz.
Metronomic breathing. Inspiration and expiration performed at a constant rate accentuate the normal respiratory sinus arrhythmia observed in most individuals (Piha, 1991). This sinus arrhythmia has often been used to establish physical fitness (Aubert et al. 1996). In the same study on physical fitness we imposed metronomic breathing at different rates and observed consequent changes in the HF component of HRV. Indirectly, breathing activity is mediated by the vagus nerve to the heart and the HF component is therefore generally accepted as a marker of pure parasympathetic modulation (Hirsch & Bishop, 1981).
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