Claudio Franceschi — Page 7

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What studies on human longevity tell us about the risk for cancer in the oldest old: data and hypotheses on the genetics and immunology of centenarians.

Centenarians are people who escaped from major common diseases, including cancer, and reached the extreme limits of human life-span. The analysis of demographic data indicates that cancer incidence and mortality show a levelling off around the age of 85-90 years, and suggests that oldest old people and centenarians are protected from cancer onset and progression. In this paper, we review data of recent literature on the distribution in centenarians of germ-line polymorphisms, which are supposed to affect the individual susceptibility to cancer (p53, HRAS1, BRCA1, glutathione transferases, cytochrome oxidases, steroid-5 alpha-reductase enzyme type II). Moreover, we add new data on two p53 polymorphisms in a total of 1086 people of different age, including 307 centenarians. In addition, we put forth the hypothesis that the remodelling of the immune system occurring with age is capable of creating a hostile environment for the growth of cancer cells in these exceptional individuals. We conclude that future studies on centenarians regarding the germ-line variability of genes involved in the control of the immune response, including apoptosis (ApoJ), are likely to be of fundamental importance in understanding the basic mechanisms for cancer, aging and their complex relationship.

Adult↗

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Role of connectivity in immune and neural network models: memory development and aging.

In this paper we analyzed how connectivity (defined as number of connections between network elements) can affect the memory capacity of a network-based model of the Immune System (IS) and of a model of the Nervous System (NS) synaptic plasticity (BCM model). The key point is the concept of competition between the characteristic variables that represent the response of such systems to environmental stimuli: the clonal concentrations for the IS, and the neuron responses for the BCM model. The memory states of both systems are characterized by a high selectivity to specific input patterns, reflecting a similar behaviour of their development rules. This selectivity property of memory states can be controlled by changing the degree of the internal connectivity in each system. We can explain the changes occurring in IS memory states during lifespan as due to a reshaping of its internal connectivity. This assumption is in agreement with experimental observations, reporting an increase of IS memory cells during lifespan. The change of connectivity in the BCM model leads to the introduction of quasilocal variables governing the plasticity of groups of synaptic junctions. This could be interpreted as the result of a refinement of neuron internal mechanisms during development, or it could be seen as a different learning rule deriving from the original BCM theory. We argue that connectivity seems to play an important role in a large class of biological systems controlled by competition mechanisms. Moreover, changes in connectivity may lead to changes in memory properties during development and aging.

Aging↗