A general dynamical statistical model with causal interpretation

We develop a general dynamical model as a framework for possible causal interpretation. We first state a criterion of local independence in terms of measurability of processes involved in the Doob-Meyer decomposition of stochastic processes, as in Aalen (1987); then we define direct and indirect influence. We propose a definition of causal influence using the concepts of ``physical system''. This framework makes it possible to link descriptive and explicative statistical models, and encompasses quantitative processes and events. One of the features of this paper is the clear distinction between the model for the system and the model for the observation. We give a dynamical representation of a conventional joint model for HIV load and CD4 counts. We show its inadequacy to capture causal influences while on the contrary known mechanisms of HIV infection can be expressed directly through a system of differential equations

Early Events Leading to Radiation-Induced Biological EffectsComprehensive Biomedical Physics

Many different orders of magnitude are involved in the development of radiation-induced biological damage, both at a spatial level (from atomic dimensions to cellular and organ dimensions) and at a temporal level (from the 10−15 s of the physical interactions to the hours, and possibly years, of the biological processes). This chapter considers the very early events. The following aspects are treated: radiation interaction with matter; the Monte Carlo method; the track structure method, time evolution of the track, including the pre-chemical phase (radiolysis and radical production) and the chemical phase (diffusion and interaction with biological structures); the DNA damage; the microdosimetric approach; and the amorphous track approach. A final section is devoted to the criteria to integrate physical mechanistic investigations and approaches with a systems radiation biology approach