Applications of the Cell Language Theory to Biomedical Sciences 321“6x9” b2861 The Cell Language Theory: Connecting Mind and Matterparameters A and C were then plotted as shown in Figure 7.18. As evident
in Figure 7.18, all the A vs. C plots show excellent linear correlations with
the R^2 values greater than 0.93. The A vs. B plots (not shown) did show
similarly excellent correlations. The following features are evident in
Figure 7.18:(1) The linearity of the A vs. C plots indicate that the PDE parameters, A
and C, are tightly coupled.
(2) Since A appears in the first term of PDE and C in the second term and
since the first term is most likely related to the number of standing
waves in the system involved and the second term to the average
energy of the standing waves (in analogy to Planckian radiation equa-
tion, Eq. (8.1)), it seems reasonable to postulate that the close cou-
pling between the numerical values of A and C indicates a close
coupling between the standing waves (which are thought to be related
to the organization of breast tissue and hence to the function of the
system, see Figure 8.8) and the energy (likely related to energy
metabolism of individual cells) content of the system. Since organi-
zation is a form of work, it must dissipate energy, thus justifying the
correlation between the A and C terms.
(3) The slope of the regression lines in the A vs. C plots in Figure 7.18
vary from 1.2 × 10−3 to 0.5 × 10−3, which may be related to the effi-
ciency of tissue organization, normal tissues most likely being more
efficient than tumor tissues.
(4) When the SM are plotted against the drug-induced changes in the
slope (∆slope) of the A vs. C plots, a linear correlation with a negative
slope was found in Figure 7.18 (see the bottom panel). Since the
x-axis encodes the effects of doxorubicin on the SMs of 20 breast
cancer patients, the negative slope indicates that the drug effect (as
mediated by the mRNA phenotypes of the randomly selected 300
genes) is harmful to patients.
(5) When similar analysis as in (4) is carried out with different sets of
300 genes randomly selected, about 10–20% of the sets tested
showed excellent linear correlations, some with positive and some
with negative slopes, the positive slope indicating that some genes
have RNA phenotypes that are beneficial to breast cancer patients,b2861_Ch-07.indd 321 17-10-2017 12:06:39 PM