The human genome with its 23 pairs of chromosomes, is the result of evolution. This evolution has been ruled by the mutation process and also by the physiological and pathological reorganization of the genomic material inside or between the chromosomes, which are conditioning the genomic variability. This reorganization is starting at singular points on the short or long chromosomic arms, called crossing-over, or translocations, insertions, break points. In this paper, we will show that these points, also called weak points or hot spots of the genome are correlated, independently of their origin. In addition, we will give some properties of the genetic interaction matrices in terms of attractors of the genetic expression dynamics.

To investigate the interindividual differences in respiratory sinus arrhythmia (RSA), recordings of ventilation and electrocardiogram were obtained from 12 healthy subjects for five imposed breathing periods (T(TOT)) surrounding each individual's spontaneous breathing period. In addition to the spectral analysis of the R-R interval signal at each breathing period, RSA characteristics were quantified by using a breath-by-breath analysis where a sinusoid was fitted to the changes in instantaneous heart rate in each breath. The amplitude and phase (or delay = phase x T(TOT)) of this sinusoid were taken as the RSA characteristics for each breath. It was found that for each subject the RSA amplitude-T(TOT) relationship was linear, whereas the delay-T(TOT) relationship was parabolic. However, the parameters of these relationships differed between individuals. Linear correlation between the slopes of RSA amplitude versus T(TOT) regression lines and 1) mean breathing period and 2) mean R-R interval during spontaneous breathing were calculated. Only the correlation coefficient with breathing period was significantly different from zero, indicating that the longer the spontaneous breathing period the lesser the increase in RSA amplitude with increasing breathing period. Similarly, only the correlation coefficient between the curvature of the RSA delay-T(TOT) parabola and mean breathing period was significantly different from zero; the longer the spontaneous breathing period the larger the curvature of RSA delay. These results suggest that the changes in RSA characteristics induced by changing the breathing period may be explained partly by the spontaneous breathing period of each individual. Furthermore, a transfer function analysis performed on these data suggested interindividual differences in the autonomic modulation of the heart rate.

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