When Models Interact with their Subjects: The Dynamics of Model Aware Systems

A scientific model need not be a passive and static descriptor of its subject. If the subject is affected by the model, the model must be updated to explain its affected subject. In this study, two models regarding the dynamics of model aware systems are presented. The first explores the behavior of "prediction seeking" (PSP) and "prediction avoiding" (PAP) populations under the influence of a model that describes them. The second explores the publishing behavior of a group of experimentalists coupled to a model by means of confirmation bias. It is found that model aware systems can exhibit convergent random or oscillatory behavior and display universal 1/f noise. A numerical simulation of the physical experimentalists is compared with actual publications of neutron life time and {\Lambda} mass measurements and is in good quantitative agreement.Comment: Accepted for publication in PLoS-ON

Immunotherapy for colorectal cancer.

There have been significant improvements in the diagnosis and treatment of colorectal cancer over the past 15 years. However, some 30% of patients with colorectal cancer have disseminated disease at presentation, and furthermore, 50% of patients initially believed to be cured by surgery subsequently relapse and die of the disease. Novel treatment concepts based on understanding the molecular signatures that separate tumor from normal epithelium, such as immunotherapy, are aimed at abolishing microscopic residual disease post standard treatment. The authors provide an overview of progress in the development of specific and nonspecific immunotherapies and explain why definition of end-points and early translation of immunotherapy into the adjuvant field are key to effective use of such agents in the clinical setting