Yun Anthony J, Lee Patrick Y, Doux John D
Stanford University, Department of Radiology, 470 University Avenue, Palo Alto, CA 94301, USA.
Med Hypotheses. 2006;67(3):651-7. doi: 10.1016/j.mehy.2006.02.021. Epub 2006 Apr 3.
A network constitutes an abstract description of the relationships among entities, respectively termed links and nodes. If a power law describes the probability distribution of the number of links per node, the network is said to be scale-free. Scale-free networks feature link clustering around certain hubs based on preferential attachments that emerge due either to merit or legacy. Biologic systems ranging from sub-atomic to ecosystems represent scale-free networks in which energy efficiency forms the basis of preferential attachments. This paradigm engenders a novel scale-free network theory of evolution based on energy efficiency. As environmental flux induces fitness dislocations and compels a new meritocracy, new merit-based hubs emerge, previously merit-based hubs become legacy hubs, and network recalibration occurs to achieve system optimization. To date, Darwinian evolution, characterized by innovation sampling, variation, and selection through filtered termination, has enabled biologic progress through optimization of energy efficiency. However, as humans remodel their environment, increasing the level of unanticipated fitness dislocations and inducing evolutionary stress, the tendency of networks to exhibit inertia and retain legacy hubs engender maladaptations. Many modern diseases may fundamentally derive from these evolutionary displacements. Death itself may constitute a programmed adaptation, terminating individuals who represent legacy hubs and recalibrating the network. As memes replace genes as the basis of innovation, death itself has become a legacy hub. Post-Darwinian evolution may favor indefinite persistence to optimize energy efficiency. We describe strategies to reprogram or decommission legacy hubs that participate in human disease and death.
网络构成了对实体之间关系的抽象描述，这些实体分别被称为链接和节点。如果幂律描述了每个节点的链接数量的概率分布，那么该网络就被称为无标度网络。无标度网络的特点是基于因功绩或传承而出现的优先连接，链接聚集在某些枢纽周围。从亚原子系统到生态系统的生物系统都代表着无标度网络，其中能量效率构成了优先连接的基础。这种范式产生了一种基于能量效率的全新的无标度网络进化理论。随着环境通量引发适应性错位并迫使形成新的精英制度，新的基于功绩的枢纽出现，以前基于功绩的枢纽变成了传承枢纽，并且会发生网络重新校准以实现系统优化。迄今为止，以创新采样、变异以及通过过滤终止进行选择为特征的达尔文式进化，通过能量效率的优化实现了生物进化。然而，随着人类重塑环境，意外适应性错位的程度增加并引发进化压力，网络表现出惯性并保留传承枢纽的趋势会导致适应不良。许多现代疾病可能根本源于这些进化错位。死亡本身可能构成一种程序性适应，终结代表传承枢纽的个体并重新校准网络。随着文化基因取代基因成为创新的基础，死亡本身已成为一个传承枢纽。后达尔文式进化可能有利于无限期存续以优化能量效率。我们描述了对参与人类疾病和死亡的传承枢纽进行重新编程或使其退役的策略。
