Affect and Response in Biological Processes - Rubikas, Jonas (Problemos, 2000)
Every biological process consists of two constituents: affect and response. The relation of response to affect could be described as that of linear or nonlinear dependence. However, when an affect changes in wide limits response changes too and graphically represents a slightly declined “S” letter. When the affect is gradually increased, the response at the beginning is rather weak; then when the affect reaches a definite strength, a response is equivalent to the affect. When the affect continues to increase the response again becomes not equivalent and even does not change. So the response changes from nonlinear to linear and then to nonlinear again. In biological processes the affect-response dependence can be regarded as taking place at two levels: the first is that of molecular interaction, atomic and linkage exchange, the second is that of cell and individual and organism. At the first level the affect-response processes are limited by conditions and amount of reacting substances: the reaction obeys the linear-nonlinear-linear dependence law. At the second level - in cells and organisms all the processes have chemical or physical background, but at the same time are influenced by the multi-step conditionalities. Therefore it is possible to affirm that every response in cells and organisms is like twofold: in individual it could be considered as probability, but in population it approaches to (almost) linear dependence. This situation is illustrated by putative examples: DNA replication, DNA transcription and protein synthesis. One of the most important conditionalities is the genetic regulation. In the case of human being an additional higher level conditionalities can be detected: feelings, will and consciousness. From this point of view the belief, miracles, predictions and other spiritual events can be considered as further conditionalities. Negation proves nothing. This is the weak site of the science.
Keywords: affect; response; probability; conditionality; genetic regulation