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Research Abstracts Online
January 2009 - March 2010

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University of Minnesota Twin Cities
Medical School
Department of Laboratory Medicine and Pathology

PI: Franz Halberg, Associate Fellow
PI: Germain G. Cornélissen

Assessment of Physiologic Chronomes From Womb to Tomb

Strokes and other adverse vascular events are major cripplers at an estimated yearly cost of over $30 billion. These researchers are developing a system for the chronomic analysis of cardiovascular records with focus on disease prevention, while also addressing the question of the optimal kind and scheduling of treatment. Ambulatory devices are used in different geographic locations to monitor blood pressure for seven days at the outset. Analyses serve to improve screening, diagnosis, and treatment, and to assess which and how environmental factors affect human physiology, notably heart rate and blood pressure. In addition to known photic solar effects (day/night, seasons), non-photic effects (including magnetoperiodisms) may account for ~16- and ~5-month cycles also observed in the incidence of sudden cardiac death and in the occurrence of ventricular arrhythmia triggering therapy from defibrillators in Minnesota. Newly mapped are components with periods of ~10 (Schwabe) and ~20 (Hale) years, as well as the rediscovered ~35-year cycle, all of which have several-fold impacts on human affairs and climate.

The researchers use supercomputing resources: to analyze long and dense data series; to organize data into databases; to automatically update reference standards as added data accumulate; to detect the earliest risk by means of chronome (time structure) alterations; to follow up at-risk individuals longitudinally by means of control charts; and to explore large-parameter spaces in nonlinear analyses not requiring the specification of initial values.

Group Members

Jerzy Czaplicki, Institute of Pharmacology and Structural Biology, Paul Sabatier University, Toulouse, France
Dewayne Hillman, Halberg Chronobiology Center, University of Minnesota, Minneapolis, Minnesota
Miguel A. Revilla, Department of Applied and Computational Mathematics, Faculty of Sciences, University of Valladolid, Valladolid, Spain