310 The Cell Language Theory: Connecting Mind and Matterb2861 The Cell Language Theory: Connecting Mind and Matter “6x9”intracellular levels of individual mRNA molecules would be determined
by the metabolic state of the whole cell. In contrast, the Survival Month
(SM) data of breast cancer patients after drug treatment would repre-
sent the phenotypes on the whole human body level, since the life and
death of an individual is determined ultimately by the physiology of the
whole human body, although mRNA levels of the breast tissues of
breast cancer patients can contribute significantly to the cause of their
deaths. Thus, it may be necessary to distinguish between at least two
types of phenotypes — the phenotype on the whole-cell level and the
phenotype on the whole-body level — the former may be referred to as
the whole-cell phenotype (WCP) and the latter the whole-body pheno-
type (WBP). As will be discussed in Sections 7.3.2 and 3.3.3, the rela-
tion between WCP and WBP appears to be not one-to-one but rather
one-to-many. For example, the WCPs, Mechanisms 2 and 6, which are
likely to be beneficial to patients judged from the perspective of cell
metabolism (since these mechanisms implicate mRNA changes that are
in the same direction whether caused by tumor or drug treatment), are
in fact found not to be so when compared against the SMs of breast
cancer patients. That is, when their associated mRNA data are analyzed
based on the PDE as described in Sections 7.3.2 and 3.3.3, Mechanism
2 is found more frequently among long survivors than among short
survivors, while Mechanism 6 is found less frequently among the long
survivors than among short survivors, the former being opposite to
what is expected solely based on the mechanism phenotypes or WCP
alone, although the latter turned out as expected on the basis of WCPs
(see Figure 7.20).
The blue curves in Figure 7.14 are the histograms constructed based
on the frequency distributions of the red (Mechanisms 2 and 6) and green
(Mechanisms 4 and 8) boxes in Figure 7.13. As evident, the blue curves
fit the Poisson distribution almost perfectly. The Poisson distribution, Eq.
(7.16), is a discrete probability distribution that expresses the probability
of a given number of events, k, occurring in a fixed interval of time and/
or space if these events occur with a known average rate, μ, and independ-
ent of the time since the last event [329].f(k; μ) = (μk/k!)e–μ (7.16)b2861_Ch-07.indd 310 17-10-2017 12:06:32 PM