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Arbeitsgruppe fur Strahlenmedizininische Forschung
und
WHO-Kollaborationszentrum fur Strahlenunfallmanagement
an der
Universitat Ulm
Leiter: Prof. (em.) Dr. med. Dr. hc. mult. T.M. Fliedner
Simulation of Radiation E ects
Using Biomathematical Models of the
Megakaryocytic Cell Renewal System
Dissertation zur Erlangung des Doktorgrades der Humanbiologie
der Medizinischen Fakultat der Universitat Ulm
Vorgelegt von
Dieter Hans Gra le
aus Lauingen an der Donau
2000Amtierender Dekan: Prof. Peter Gierschik
1. Berichterstatter: Prof. Theodor M. Fliedner
2. Berich Prof. H. Wol
Tag der Promotion: 14.07.2000Contents
1 Introduction and Overview 1
1.1 Interaction of Mathematics and Biomedical Research . . . . . . . . . . 1
1.2 Biomathematical Models and Hematopoietic Radiation E ects . . . . . 3
1.3 Objectives of the Presented Thesis . . . . . . . . . . . . . . . . . . . . 4
1.4 Overview on the Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2 Material and Methods 7
2.1 Biological and Radiological Aspects . . . . . . . . . . . . . . . . . . . . 8
2.2 Data on Irradiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.3 Mathematical Techniques and Methods . . . . . . . . . . . . . . . . . . 23
2.4 Computer Science and Data Processing . . . . . . . . . . . . . . . . . . 51
3 Results 53
3.1 Modeling Thrombocytopoiesis in Rodents . . . . . . . . . . . . . . . . 55
3.2 Model Based Analysis of the Hematological E ects of Acute Irradiation 89
3.3 Model Based Analysis of the E ects of Chronic Irradiation109
3.4 Excess Cell Loss and Microdosimetric Radiation E ects . . . . . . . . . 124
4 Discussion 136
4.1 Modeling Thrombocytopoiesis in Rodents . . . . . . . . . . . . . . . . 137
4.2 Model Based Analysis of the Hematological E ects of Acute Irradiation 140
4.3 Model Based Analysis of the E ects of Chronic Irradiation144
4.4 Excess Cell Loss and Microdosimetric Radiation E ects . . . . . . . . . 146ii CONTENTS
4.5 Next Steps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
5 Summary 151ABBREVIATIONS
IR Set of Real Numbers
3HDFP Tritium Labeled Diisopropyl uorophosphate
3H-thymidine Tritium Labeled Thymidine
5-FU 5-Fluorouracyl
AChE Acetylcholinesterase
API Application Program Interface
APS Anti Platelet Serum
BFU-Mk Burst Forming Unit - Megakaryocyte
C1 Early Committed Progenitors (Model)
C2 Late (Model)
CC Committed (Progenitor) Cells
CD34 Cluster of Di eren tiation 34
CFU-GEMM Colony Forming Unit - Granulocyte Erythrocyte
Megakaryocyte Monocyte
CFU-GM Colony Forming Unit- Granulocyte Monocyte
CFU-Mk Colony Forming Unit - Megakaryocyte
CFU-S Colony Forming Unit - Spleen
DBMS Database Management System
DNA Deoxyribonucleic Acid
EMB Endoreduplicating Progenitors and Megakaryoblasts (Model)
GUI Graphical User Interface
LET Linear Energy Transfer
METREPOL Medical Treatment Protocols
Mk Megakaryocytes
MKi Megakaryocytes (Model)
MkMass Megakaryocyte Mass
NC Noncommitted Progenitor Cells (Model)
ODE Ordinary Di eren tial Equationiv Abbreviations
PC Personal Computer
PS Pluripotent Stem Cells
PSinj Injured Stem Cells
RC Response Category
Reg Regulator
SC Stem Cells
SQL Standard Query Language
TBI Total Body Irradiation
TH Thrombocytes (Model)Chapter 1
Introduction and Overview
Mathematical biology is one of the fast growing areas of interdisciplinary research.
The use of mathematics in biology and medicine increases as research in biological
and medical science becomes more and more quantitative and complex. On the other
hand, mathematics and computer science have developed new mathematical and com-
putational methods to solve complex mathematical problems. Thus, the basis was
created to apply mathematical formalisms to describe the complex processes of vari-
ous systems in biology and other scienti c disciplines.
1.1 Interaction of Mathematics and Biomedical
Research
Looking at the development of sciences in the past years it can be recognized that the
di eren t disciplines of research are successively tearing down separating walls and are
starting to cooperate in order to solve problems, or even grow together. Especially
in medicine the connection of biology and mathematics produced new approaches to
generateknowledge. Thebasicelement inapplicationofmathematicstoothersciences
is the "model", which is used to translate "nonmathematical" realities into mathema-
tical formalisms. The best known example is epidemiology, which connects research
on health and statistic models to produce new insights on the spread of diseases and
to implement the results in health policy making. Another area of medical research in
whichmathematical o wmodelswereearlyrecognizedtobetheappropriatemethodis
pharmakokinetics. There, thekey problem istodescribe thedistributionofsubstances
in the organ systems of the body as a function of time.
Mathematical models can support research in many ways:
Models can help to understand complex systems by representation of the know-
ledge in a closed and uniform way.2 Introduction and Overview
Possibilities
Biology / Medicine
BiomathematicsReality
???
?
Mathematics
Possibilities
Figure 1.1: Generation of knowledge by interaction between biomedical research and
mathematics.
Models can help to nd gaps of knowledge and to build new hypothesis.
Models can identify demand for experiments and help to design the setup.
Models can indirectly produce information on parameters, which are biologically
hard to determine.
Models can give medical assistance in diagnosis, prognosis and therapy.
The work done by biomathematics should not be seen only as simply combining bio-
logical facts and mathematical methods for calculations. Biomathematics should be
a permanent interaction between biomedical research and mathematics. For example,
mathematical models can help to give explanatory approaches and to set up new hy-
pothesis. These hypothesis can be proved or rejected by biology and medicine and
then improve the models. On the other hand, mathematical research is stimulated
by the demand of methods and applications. This way the search for "reality" is an
interacting process from two complementary sides, like vizualized in gure 1.1.
Ascanbeseen mathematicshave beenestablishednowinmany areasofbiomedicalre-
search. However, thedevelopment ofinterdisciplinary sciences such asbiomathematics
is still in progress.

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