Concentrated patterns in biological systems [Elektronische Ressource] / vorgelegt von Matthias Winter
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Concentrated patterns in biological systems [Elektronische Ressource] / vorgelegt von Matthias Winter

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Concentrated Patterns in BiologicalSystemsVon der Fakultat Mathematik und Physik derUniversitat Stuttgart als Habilitationsschriftgenehmigte AbhandlungVorgelegt vonDr. Matthias Wintergeboren in Neuenstadt am KocherGutachter:Prof. Dr. Arjen DoelmanProf. Dr. Messoud EfendievProf. Dr. Karl-Peter HadelerProf. Dr. Alexander MielkeFachbereich Mathematik2003Key words and phrases. Concentration Phenomena, Gierer-MeinhardtSystem, Mathematical Biology, Pattern Formation, Singular Perturbation,Elliptic SystemsContentsChapter 1. Introduction 5Chapter 2. Preliminaries 171. Two linear operators in half space 172. Calculating the heights of the spikes 19Chapter 3. Existence 231. Construction of the Approximate Solutions 232. The Liapunov-Schmidt Reduction Method 313. The Reduced Problem 39Chapter 4. Stability 471. The Large Eigenvalues 472. The Small Eigenvalues 54Chapter 5. Appendices 651. Appendix A 652. Appendix B 703. Appendix C 744. Appendix D 785. Appendix E 82Chapter 6. Discussion 851. Discussion 85Bibliography 873CHAPTER 1IntroductionThis thesis is concerned with pattern formation in biological systems, inparticular those having the property that they concentrate at a boundarypoint in a bounded smooth domain.We study this problem within the framework of deterministic reaction-di usion systems.



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Published 01 January 2004
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Concentrated Patterns in Biological Systems
k und ysik der Von der Fakulta Pht Mathemati t Stu rt g als Habilitationsschrift Universitatt a genehmigte Abhandlung
Vorgelegt von Dr. Matthias Winter geboren in Neuenstadt am Kocher
Gutachter: Prof. Dr. Arjen Doelman Prof. Dr. Messoud Efendiev Prof. Dr. Karl-Peter Hadeler Prof. Dr. Alexander Mielke
Fachbereich Mathematik 2003
Key words and phrases.Concentration Phenomena, Gierer-Meinhardt System, Mathematical Biology, Pattern Formation, Singular Perturbation, Elliptic Systems
17 17 19
Chapter 4. Stability 1. The Large Eigenvalues 2. The Small Eigenvalues
Chapter 5. Appendices 1. Appendix A 2. Appendix B 3. Appendix C
Chapter 6. Discussion 1. Discussion
4. 5.
Appendix D Appendix E
65 65 70 74 78 82
85 85
47 47 54
23 23 31 39
Chapter 3. 1. Cons 2. The 3. The
Chapter 2. 1. Two 2. Calc
Existence truction of the Approximate Solutions Liapunov-Schmidt Reduction Method Reduced Problem
Chapter 1.
Preliminaries linear operators in half space ulating the heights of the spikes
This thesis is concerned with pattern formation in biological systems, in particular those having the property that they concentrate at a boundary point in a bounded smooth domain.
We study this problem within the framework of deterministic reaction-di usion systems. As a prototype system, which on the one hand captures the essential biological behavior and on the other hand is not too complex for a rigorous and explicit mathematical analysis, we consider the Gierer-Meinhardt system (see [29 a suitable rescaling, this system can be]). After written as follows: At=DaA A+HA2 >, A  0 in,  Ht=DhH H+A2 >, H0 in  ,(1.1) (GM) A=H= 0 on .
The unknownsA=A(x, t) andH=H(x, t) represent the concentrations of the biochemicals called activator and inhibitor, respectively, at a pointx R2and at a timet > coecien0, respectively; the di usion tsDa, Dh and the time relaxation constantare positive constants (independent of x andt >0) withDa<< Dhandindependent ofDa, Dh; we also use the notationDa=2andDh=D :=; Pj1=2x2j2is the Laplace operator in R2;  a smooth bounded domain in isR2;(x) is the outward unit normal vector atx ;denotes the normal derivative atx simplicity (for x we will mostly drop the indexx). To understand how (1.1) arises as a model of a biochemical reaction in a living organism note that there is an autocatalytic production of the activator Avia theAH2 inhibitorterm. TheHis activated byAdue to the termA2in the second equation, butHinhibits the production of the activatorAasHA2 5
decreases for increasingH summarizes the reaction part of the system.. This Addingthephysicalphenomenonofdi usiontothesystemwearriveat(1.1). The classical Turing type linearized analysis shows that the homogeneous steady states are unstable. In the present study we perform an analysis in the neighborhood of certain inhomogeneous steady states and prove their existence and (linearized) stability rigorously.
Thesystem(1.1)was rstintroducedbyA.GiererandH.Meinhardt,sci-entists at the Max-Planck Institute for Developmental Biology in Tubingen, to study the problem of formation of new heads for hydra, the orientation of the head and the arms/legs in embryotic growth, and lately the beautiful patterns on sea shells [49], [50]. It has been successfully used to predict patterns and understand the mechanism of their formation. Typically, in these examples the problem is posed in a two-dimensional domain (except in the study of sea shells which is considered as a system on a one-dimensional interval with the time axis corresponding to the direction of shell growth in time). Actually, they study the more general system
q, (GGM)tA==DaDHA H A+HAH+pHsr, ∂H A ∂t
p >1,
q >0 >, r0,
1r 0<p <1. q s+ Using the same mathematical methods but putting more e ort into the nota-tion one could generalize many of our results to this more general system. For example, the existence result, Theorem 1.1, can be extended to the general-izedsystemwithoutanytechnicaldiculty.Forthestabilityresult,Theorem 1.2, there should be some restrictions on (p, q, r, s [). See14], [57], [58], [75], and [87] for related studies on nonlocal eigenvalue problems (NLEPs). For simplicity and readability in this thesis we restrict our attention to the simpler system (1.1). Tostartthediscussionofthemathematicalbehaviorof(1.1),we rst recall Turing’s idea of adi usion-driven instability[65 rwestrefero,e.]hT
drop the di usion
terms and consider the kinetic system instead: AtHt==  HA++HA2,A2.
This system has a unique constant steady stateA1, H1. For 0<  <1 it is easy to see that the constant solutionA1, H1 is (linearly) stable as a steady state of (1.2). However, if in (1.1)DDahis small, then the constant steady stateA1, H example shows This1 becomes unstable. that in the case of a system of partial di eren tial equations di usion may lead to instability of homogeneous states contrary to the common knowledge that di usion is a smoothing and trivializing process. This intuition fails sincewedealwithasystemofpartialdi erentialequationsratherthana single equation. Therefore the maximum principle or energy methods are not available for the analysis. This example also shows that the size of the di usion coecien tsDaandDhis essential for the behavior of (1.1). Throughout this thesis we will assume thatDa=2is small. Furthermore, we will assume thatDh 1, where the notationABmeans that A = limBC >0. In this thesis, we will show that there is a critical growth rate for the inhibitor di usivit yDhgiven by
imDh=c 1 l0 0, 
such that there exists a steady state for (1.1) whose shape is given by a boundary spike the location of which is determined by the interaction of boundarycurvatureandGreensfunctione ects. Beforestatingtheresultinfulldetail,we rstintroducesomenotation forP , r(P):=(P)
with(P)denoting the tangential derivative with respect toPatP . We will sometimes drop the argumentPif this can be done without causing confusion. LetG0(x, ) be the Green function which satis es following the
nonlocal linear boundary value problem for : G0(x, ) |1 |+(x) = 0 forxin , R G0(x, )dx= 0, G0x,= 0 forxon x
Then log1P) Q, P, H0(Q, P) = 21|Q P|G0(Q, is the regular part of the Green function for which the limitH0(P, P) limQPH0(Q, P) exists. ForP behavior of theG0(Q, P de ne We t.) is di eren H0(Q, P) = 1 log|Q 1P|G0(Q, P), Q , P ,  and then the limitH0(P, P) = limQP,Q H0(Q, P) exists. Letwbe the unique solution inH1(R2) of the problem
1 w(w0) =w+amxwy2R=2w0,(y)>,ww0(yni)R02,as|y| → ∞.( .4) For existence and uniqueness of the solution of (1.4) we refer to [28] and [43 also recall that]. Wewis radially symmetric and
w(y) |y| 1/2e|y|
as|y| → ∞.
Finally, we introduce two negative constants
respectively. Nowour st
1= 31ZRw(yy11,0)!2dy1<0 2 y1
2= 16| |ZR2(y)dy, w3 +
2which are given
main result, which is on existence, may be stated as follows:
 1 =c0,
,we de ne
F(P) =1h(P) +c02H0(P, P),
wherehdenotes the curvature of atP,H0(P, P)denotes the regular part of the Green function, and1and2,7)1.d(an6)1.(niden ederew respectively. Suppose thatP0is a nondegenerate critical point ofF(P)along the bound-ary, i.e. forP=P0, r(P0)F(P0) = 0,
(r(P0))2F(P0))6= 0.
Then, forsmall enough, problem (GM) has a steady state(A, H)with the following properties: (1)A(x) =(w(x P) +O())uniformly forx   (2)H(x) =(1 +O())uniformly forx , wherewwas de ne in (1.4) and d 2R2| w2|(y)dy+O 1lo1.(1.9) g = 
Next, we study the stability or instability of the boundary peak solutions constructed in Theorem 1.1. To this end, we need to study the following eigenvalue problem 2 L =1 12  + 2 AH+2 AHA22 =,(1.10)
where (A, H) is the solution constructC, ed Theorem 1.1 andthe set of complex numbers. We say that the steady state (A, H) islinearly stableif the spectrum (L) ofLlies in the left half plane{C: Re()<0}. The steady state (A, H) is calledlinearly unstableif there exists an eigenvalueof Lwith Re()>0. (Fromwe use the notations linearly stable and now on,  linearly unstable as de ned above.) Our second main result, which is on stability, is stated as follows.
Theorem1.2.LetP0be a nondegenerate critical point ofF boundary, i.e.,r(P0)F(P0) = 0. Assume further that
along the
P0is a nondegenerate local maximum point ofF(P),
i.e.,(r(P0))2F(P0)<0 there exists a unique. Then1>0such that for  < 1the steady state(A, H)introduced in Theorem 1.1 is linearly stable, while for  >1it is linearly unstable. Moreover, if0, then we have the following asymptotic behavior of  : 
where 1  0=RR+2∂w12dy>0, ∂y the eigenfunction corresponding tosatis es  P =r(P)wx+o(1), 
Remark.The condition () on the locationP0arises in the study of small (o continuous function The(1)) eigenvalues.F(P) obviously attains its global maximum atP for any smooth bounded domain R2 this. If global maximum point is also a nondegenerate critical point, then condition () is satis ed for this global maximum point. We believe that forgeneric domains this global maximum pointP0is nondegenerate. The rst term inF(P) is related to the local geometry of nearP andentersintotheanalysisthroughthe rstequationof(GM),whereas the second term is related to the global geometry of  and enters into the analysis through the second equation. Let us mention that to our knowledge
this result is the rst of its kind for reaction-di usion systems, where the boundary curvature and the Green function interact in such an additive way. We are not aware of results of such a coupling phenomenon in the setting of a single second-order elliptic partial di eren tial equation. Thus it appears
that this coupling behavior is typical for systems but does not arise for a single equation. This two-dimensional result is potentially important for applications in mathematical biology, for which the Gierer-Meinhardt has been designed.
The key references for this thesis are [77], where to the best of our knowl-edgeLiapunov-Schmidtreductionwasusedforthe rsttimetoconstruct boundary spikes for a nonlinear elliptic partial di eren tial equation in higher dimensions, and [82], where the existence and stability of (interior) multiple spike solutions for the Gierer-Meinhardt system were established. We com-bine those two approaches to construct steady states with a single boundary spike and prove their (in)stability. Now we comment on some related work. Numerical studies by Meinhardt [49] and more recently by Holloway [36] and Maini and McInerney [48] have revealed that whenis small andDis
nite, (GM) seems to have stable stationary solutions with the property that theactivatorislocalizedarounda nitenumberofpointsin .Moreover,as 0, the pattern exhibits a“point condensation phenomenon”. By this we mean that the activator is localized in narrower and narrower regions of size O() around these points and eventually shrinks to the set of points itself as  the maximum value of the activator and the inhibitor,0. Furthermore, respectively, diverges to +. Although it has been observed numerically that these patterns are stable, until recently it has been an open problem to give a rigorous proof of these facts. Namely, how can one rigorously construct these solutions? Where are the spikes located? Are these solutions stable? Recall that the stationary system for (GM) is the following system of elliptic equations: 2A A+AH2= 0, A >0 in  , DhH H+A2= 0, H >0 in  ,(1.14)
A=H= 0 on . There are a number of recent results for interior spikes solutions for this system in the case R2 [. In80], for the strong-coupling case, i.e.,Dh