The Center for the Biology of Chronic Disease

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Elena N. Naumova, PhD

Associate Professor, Department of Family Medicine and Community Health, Tufts University School of Medicine

REVIEW

To be honest, it took me three attempts to read this book. The first attempt resulted in frustration and confusion. The unusual writing style, complex terminology, and volume of information was daunting. I put the book aside, but the seeds of curiosity had been planted, and intriguing ideas took root. They began to grow, and soon I was forced to return to my reading. My second attempt was far more productive but nevertheless challenging. I went through all seven chapters of technical notes. It was a slow process, not because of the numerous mathematical equations (which were straightforward and well-supported) but because I found myself repeatedly distracted by independent thoughts and ideas triggered by the content of the book. I would read a sentence or two and immediately attach my own observations to the proposed frame, and test the fit; I was amazed by the serendipities. My third attempt was joyous; the book served its purpose – it made me think differently! What had first seemed cumbersome technical notations became transparent when I connected them to the work I perform daily. I also realized that the area of my research interest - mathematical modeling of disease temporality - would benefit greatly by applying the fruitful ideas presented in Dr. Polansky's book.

The general underpinning of this work is to outline a foundation for understanding mechanisms behind the origins of chronic diseases and provide a methodology for investigating complex biological systems. The foundation laid out is an elegant set of fundamental concepts and operational rules for their connection, which form a unique language of complex systems. By applying this language, Dr. Polansky's theory of microcompetition and chronic disease initiation, progression and resolution, was delivered with amazing elegance and ease.

Understanding complex living systems is an enterprise that is interdisciplinary in its nature; to effectively communicate ideas, facts, and inferences, a common language is a must. Dr. Polansky's work compellingly demonstrates a framework that could bring together researchers from different fields. His proposed theory will work its magic by clarifying ambiguous definitions, identifying similarities and differences in various biological processes, and discovering new pathways.

I consider this book a guide for recognizing scientific puzzles, solving them, and collecting pieces for future ones. This book is a well-justified manual of fascinating algorithms for putting seemingly disconnected observations into a multi-dimensional framework for understanding chronic disease etiology. The content of the book is presented in an array of logical sequences of conceptual building blocks, corresponding models, anticipated outcomes, and collections of observations. While challenging to read initially, the book stimulates constructive thinking and teaches one to look for the unexpected while leaving room for creativity and imagination.

I believe that Dr. Polansky's book will catalyze the scientific learning process, promote interdisciplinary cross-fertilization, stimulate development of treatment strategies and drug discovery, and leave the reader inspired.

Thank you for the opportunity to review Dr. Polansky’s book and provide commentary.

BIOGRAPHY

Dr. Elena N. Naumova, PhD, is an associate professor in the Department of Family Medicine and Community Health, Tufts University School of Medicine. Educated in Novosibirsk, Russia, she continued her advanced studies at the Bauman Technical University in Moscow, focusing on design of expert systems in immunology. Her research emphasizes the creation and application of mathematical/statistical tools to understand disease temporality, and evaluate influences of intermediate events on spatial and temporal disease patterns. Her research interests include development of analytical tools for time series and longitudinal data analysis applied to disease surveillance, exposure assessment, and growth studies. Her research activities span a broad range of research programs in infectious disease, environmental epidemiology, immunology and developmental biology. Dr. Naumova is currently working on several large NIH-funded studies and teaches biostatistics and data visualization courses in the Graduate Programs in Public Health at Tufts University.

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