Loading [MathJax]/jax/output/SVG/jax.js

Time Delay In Necrotic Core Formation

  • A simple model of avascular solid tumor dynamics is studied in the paper. The model is derived on the basis of reaction-diffusion dynamics and mass conservation law. We introduce time delay in a cell proliferation process. In the case studied in this paper, the model reduces to one ordinary functional-differential equation of the form that depends on the existence of necrotic core. We focus on the process of this necrotic core formation and the possible influence of delay on it. Basic mathematical properties of the model are studied. The existence, uniqueness and stability of steady state are discussed. Results of numerical simulations are presented.

    Citation: Marek Bodnar, Urszula Foryś. Time Delay In Necrotic Core Formation[J]. Mathematical Biosciences and Engineering, 2005, 2(3): 461-472. doi: 10.3934/mbe.2005.2.461

    Related Papers:

    [1] Vittoria Raimondi, Alessandro Grinzato . A basic introduction to single particles cryo-electron microscopy. AIMS Biophysics, 2022, 9(1): 5-20. doi: 10.3934/biophy.2022002
    [2] Joshua Holcomb, Nicholas Spellmon, Yingxue Zhang, Maysaa Doughan, Chunying Li, Zhe Yang . Protein crystallization: Eluding the bottleneck of X-ray crystallography. AIMS Biophysics, 2017, 4(4): 557-575. doi: 10.3934/biophy.2017.4.557
    [3] Stephanie H. DeLuca, Samuel L. DeLuca, Andrew Leaver-Fay, Jens Meiler . RosettaTMH: a method for membrane protein structure elucidation combining EPR distance restraints with assembly of transmembrane helices. AIMS Biophysics, 2016, 3(1): 1-26. doi: 10.3934/biophy.2016.1.1
    [4] Adam Redzej, Gabriel Waksman, Elena V Orlova . Structural studies of T4S systems by electron microscopy. AIMS Biophysics, 2015, 2(2): 184-199. doi: 10.3934/biophy.2015.2.184
    [5] Riyaz A. Mir, Jeff Lovelace, Nicholas P. Schafer, Peter D. Simone, Admir Kellezi, Carol Kolar, Gaelle Spagnol, Paul L. Sorgen, Hamid Band, Vimla Band, Gloria E. O. Borgstahl . Biophysical characterization and modeling of human Ecdysoneless (ECD) protein supports a scaffolding function. AIMS Biophysics, 2016, 3(1): 195-210. doi: 10.3934/biophy.2016.1.195
    [6] Angel Rivera-Calzada, Andrés López-Perrote, Roberto Melero, Jasminka Boskovic, Hugo Muñoz-Hernández, Fabrizio Martino, Oscar Llorca . Structure and Assembly of the PI3K-like Protein Kinases (PIKKs) Revealed by Electron Microscopy. AIMS Biophysics, 2015, 2(2): 36-57. doi: 10.3934/biophy.2015.2.36
    [7] Wei Zhang, Sheng Cao, Jessica L. Martin, Joachim D. Mueller, Louis M. Mansky . Morphology and ultrastructure of retrovirus particles. AIMS Biophysics, 2015, 2(3): 343-369. doi: 10.3934/biophy.2015.3.343
    [8] Jany Dandurand, Angela Ostuni, Maria Francesca Armentano, Maria Antonietta Crudele, Vincenza Dolce, Federica Marra, Valérie Samouillan, Faustino Bisaccia . Calorimetry and FTIR reveal the ability of URG7 protein to modify the aggregation state of both cell lysate and amylogenic α-synuclein. AIMS Biophysics, 2020, 7(3): 189-203. doi: 10.3934/biophy.2020015
    [9] Ta-Chou Huang, Wolfgang B. Fischer . Sequence–function correlation of the transmembrane domains in NS4B of HCV using a computational approach. AIMS Biophysics, 2021, 8(2): 165-181. doi: 10.3934/biophy.2021013
    [10] Davide Sala, Andrea Giachetti, Antonio Rosato . Molecular dynamics simulations of metalloproteins: A folding study of rubredoxin from Pyrococcus furiosus. AIMS Biophysics, 2018, 5(1): 77-96. doi: 10.3934/biophy.2018.1.77
  • A simple model of avascular solid tumor dynamics is studied in the paper. The model is derived on the basis of reaction-diffusion dynamics and mass conservation law. We introduce time delay in a cell proliferation process. In the case studied in this paper, the model reduces to one ordinary functional-differential equation of the form that depends on the existence of necrotic core. We focus on the process of this necrotic core formation and the possible influence of delay on it. Basic mathematical properties of the model are studied. The existence, uniqueness and stability of steady state are discussed. Results of numerical simulations are presented.


    Means of different types play significant role in different fields of sciences through their applications. For instance it has been observed harmonic means have applications in electrical circuits theory. To be more precise, the total resistance of a set of parallel resistors is just half of harmonic means of the total resistors, for details, see [3]. Recently many researchers have extensively utilized different types of means in theory of convexity. Consequently a number of new and novel extensions of classical convexity have been proposed in the literature. For some recent studies, see [4,5,21,22]. We now recall some preliminary concepts and results pertaining to convexity and for its other extensions.

    Definition 1.1 ([18]). (AA-convex functions) A function X:CRR is said to be AA-convex, if

    (1μ)X(x)+μX(y)X((1μ)x+ty),x,yC,μ[0,1],

    where C is a convex set.

    Definition 1.2 ([18]). (GG-convex functions) A function X:GR+R+ is said to be GG-convex, if

    X1μ(x)Xμ(y)X(x1μyμ),x,yG,μ[0,1],

    where G is a geometric convex set.

    Definition 1.3 ([13]). (HH-convex functions) A function X:HR+R is said to be HH-convex, if

    X(x)X(y)μX(x)+(1μ)X(y)X(xy(1μ)x+ty),x,yH,μ[0,1],

    where H is a harmonic convex set.

    For some other useful details, see [18]. Convexity theory also played significant role in the development of theory of inequalities. Many known results are obtained directly using the functions having convexity property. Hermite and Hadamard presented independently a result which now a days known as Hermite-Hadamard's inequality. This result is very simple in nature but very powerful, as it provides us a necessary and sufficient condition for a function to be convex. It reads as: Let X:IRR be a convex function, then

    X(c+d2)1dcdcX(x)dxX(c)+X(d)2.

    Dragomir et al. [8] written a very interesting detailed monograph on Hermite-Hadamard's inequality and its applications. Interested readers may find useful details in it. In recent years several famously known researchers from all over the world have studied the result of Hermite and Hadamard intensively. For more details, see [4,6,7,9,10,17,20]. This result has also been generalized for other classes of convex functions, for instance, see [8,11,12,14,18,22].

    Fractional calculus [15,16] has played an important role in various scientific fields since it is a good tool to describe long-memory processes. Sarikaya et al. [24] used the concepts of fractional calculus and obtained new refinements of fractional Hermite-Hadamard like inequalities. This article of Sarikaya et al. opened a new venue of research. Consequently several new generalizations of Hermite-Hadamard's inequality have been obtained using the fractional calculus concepts.

    Recently many authors have shown their special interest in utilizing the concepts of quantum calculus for obtaining q-analogues of different integral inequalities. For some basic definitions and recent studies, see [1,2,19,23,25,26]. The main objective of this article is to introduce the notion of M-convex functions. This class can be viewed as novel extension of the classical definition of convexity. We link this class with Hermite-Hadamard's inequality and obtain several new variants of this famous result. We also obtain the fractional and quantum analogues of the obtained results. We expect that the results of this paper may stimulate further research in this direction.

    In this section, we introduce the notions of M-convex functions, log-M-convex and quasi M-convex functions. First of all for the sake of simplicity, we take G=cd and A=c+d2.

    Definition 2.1. A function X:DR+R+ is said to be M-convex function, if

    X((1μ)G+μA)(1μ)X(G)+tX(A),c,dD,μ[0,1].

    Definition 2.2. A function X:DR+R+ is said to be log-M-convex function, if

    X((1μ)G+μA)X1μ(G)Xμ(A),c,dD,μ[0,1].

    Definition 2.3. A function X:DR+R+ is said to be quasi M-convex function, if

    X((1μ)G+μA)max{X(G),X(A)},c,dD,μ[0,1].

    We now derive a new auxiliary result which play a key role in the development of our coming results.

    Lemma 3.1. Let X:IR+R+ be a differentiable function on I, c,dI with c<d. If XL[c,d], then

    X(G)+X(A)22(dc)2AGX(x)dx=(dc)2410(12μ)X(μG+(1μ)A)dμ.

    Proof. It suffices to show that

    10(12μ)X(μG+(1μ)A)dμ=2X(G)+X(A)(dc)28(dc)4AGX(x)dx.

    This implies

    (dc)2410(12μ)X(μG+(1μ)A)dμ=X(G)+X(A)22(dc)2AGX(x)dx.

    This completes the proof.

    Now utilizing Lemma 3.1, we derive our next results.

    Theorem 3.2. Let X:IR+R+ be a differentiable function on I, c,dI with c<d and XL[c,d]. If |X| is M-convex function, then

    |X(G)+X(A)22(dc)2AGX(x)dx|(dc)216[|X(G)|+|X(A)|].

    Proof. Using Lemma 3.1, property of the modulus and the fact that |X| is M-convex function, we have

    |X(G)+X(A)22(dc)2AGX(x)dx|(dc)2410|12μ||X(μG+(1μ)A)|dμ(dc)2410|12μ|[μ|X(G)|+(1μ)|X(A)|]dμ=(dc)216[|X(G)|+|X(A)|].

    This completes the proof.

    If we apply Theorem 3.2 for log-M-convex functions, then

    Theorem 3.3. Let X:IR+R+ be a differentiable function on I, c,dI with c<d and XL[c,d], If |X| is decreasing and log-M-convex function, then

    |X(G)+X(A)22(dc)2AGX(x)dx|(dc)24[2+4w2wlogw+wlogwlogw2],

    where w=|X(G)||X(A)|.

    Theorem 3.4. Let X:IR+R+ be a differentiable function on I, c,dI with c<d and XL[c,d]. If |X|q, where 1p+1q=1 is M-convex function, then

    |X(G)+X(A)22(dc)2AGX(x)dx|(dc)24(1p+1)1p(|X(G)|q+|X(A)|q2)1q.

    Proof. Using Lemma 3.1, Holder's inequality and the fact that |X|q is M-convex functions, we have

    |X(G)+X(A)22(dc)2AGX(x)dx|(dc)24(10|12μ|pdμ)1p(10|X(μG+(1μ)A)|dμ)1q(dc)24(1p+1)1p(10[μ|X(G)|q+(1μ)|X(A)|q]dμ)1q=(dc)24(1p+1)1p(|X(G)|q+|X(A)|q2)1q.

    This completes the proof.

    Theorem 3.5. Let X:IR+R+ be a differentiable function on I, c,dI with c<d and XL[c,d]. If |X|q, where q1 is M-convex function, then

    |X(G)+X(A)22(dc)2AGX(x)dx|(dc)28(|X(G)|q+|X(A)|q2)1q.

    Proof. Using Lemma 3.1, power mean inequality and the fact that |X| is M-convex functions, we have

    |X(G)+X(A)22(dc)2AGX(x)dx|(dc)24(10|12μ|dμ)11q(10|12μ||X(μG+(1μ)A)|dμ)1q(dc)24(12)11q(10|12μ|[μ|X(G)|q+(1μ)|X(A)|q]dμ)1q=(dc)28(|X(G)|q+|X(A)|q2)1q.

    This completes the proof.

    In this section, we derive some fractional estimates of Hermite-Hadamard like inequalities using M-convex functions. Before that we recall basic definition of Riemann-Liouville fractional integrals.

    Definition 4.1 ([15]). Let XL[c,d], where c0. The Riemann-Liouville integrals Jνc+X and JνdX, of order ν>0, are defined by

    Jνc+X(x)=1Γ(ν)xc(xμ)ν1X(μ)dμ, for x>c

    and

    JνdX(x)=1Γ(ν)dx(μx)ν1X(μ)dμ, for x<d,

    respectively. Here, Γ(ν)=0eμμν1dμ is the Gamma function. We also make the convention

    J0c+X(x)=J0dX(x)=X(x).

    We now derive a new auxiliary result utilizing the definition of Riemann-Liouville fractional integrals.

    Lemma 4.1. Let X:IR+R+ be a differentiable function. If XL[c,d], then

    X(G)+X(A)22α1Γ(α+1)(dc)2[Jα(A)X(G)+Jα(G)+X(A)]=(dc)2410[(1μ)αμα]X(μG+(1μ)A)dμ.

    Proof. It suffices to show that

    I=10[(1μ)αμα]X(μG+(1μ)A)dμ=10(1μ)αX(μG+(1μ)A)dμ10μαX(μG+(1μ)A)dμ=I1I2. (4.1)

    Now using change of variable technique and definition of Riemann-Liouville fractional integrals, we have

    I1=10(1μ)αX(μG+(1μ)A)dμ=2(dc)2X(A)2α+1Γ(α+1)(dc)2(α+1)1Γ(α)AG(xG)α1X(x)dx=2(dc)2X(A)2α+1Γ(α+1)(dc)2(α+1)Jα(A)X(G). (4.2)

    Similarly

    I2=10μαX(μG+(1μ)A)dμ=2(dc)2X(G)+2α+1Γ(α+1)(dc)2(α+1)Jα(G)+X(A). (4.3)

    Combining (4.1), (4.2) and (4.3) completes the proof. Now using Lemma 4.1, we derive our next results.

    Theorem 4.2. Let X:IR+R+ be a differentiable function and XL[c,d]. If |X| is M-convex function, then

    |X(G)+X(A)22α1Γ(α+1)(dc)2[Jα(A)X(G)+Jα(G)+X(A)]|(dc)24(α+1)(112α)[|X(a)|+|X(b)|].

    Proof. Using Lemma 4.1 and the property of modulus, we have

    |X(G)+X(A)22α1Γ(α+1)(dc)2[Jα(A)X(G)+Jα(G)+X(A)]|10(dc)24|(1μ)αμα||X(μG+(1μ)A)|dμ.

    Since it is given that |X| is M-convex function, so we have

    |X(G)+X(A)22α1Γ(α+1)(dc)2[Jα(A)X(G)+Jα(G)+X(A)]|10(dc)24|(1μ)αμα|[μ|X(G)|+(1μ)|X(A)|]dμ=(dc)24[|X(G)|10μ|(1μ)αμα|dμ+|X(A)|10(1μ)|(1μ)αμα|dμ]=(dc)24(α+1)(112α)[|X(a)|+|X(b)|].

    This completes the proof.

    In this section, we derive some quantum analogues of Hermite-Hadamard like inequalities using M-convex functions. Before proceeding, let us recall some basics of quantum calculus. Tariboon et al. [25] defined the q-integral as follows:

    Definition 5.1 ([25]). Let X:IRR be a continuous function. Then q-integral on I is defined as:

    xaX(μ)adqμ=(1q)(xa)n=0qnX(qnx+(1qn)a), (5.1)

    for xJ.

    The following result will play significant role in main results of the section.

    Lemma 5.1 ([25]). Let αR{1}, then

    xa(μa)αadqμ=(1q1qα+1)(xa)α+1.

    Lemma 5.2. Let X:IR+R+ be a q-differentiable function on I, c,dI with c<d. If DqX is an integrable function with 0<q<1, then

    2(dc)2AGX(μ)dqμqf(G)+X(A)1+q=q(dc)22(1+q)10(1(1+q)μ)Dq((1μ)G+μA)dqμ.

    Proof. It suffices to show that

    10(1(1+q)μ)Dq((1μ)G+μA)dqμ=2(dc)210(X((1μ)G+μA)X((1qμ)G+qμA)(1q)μ)dqμ2(1+q)(dc)210μ(X((1μ)G+μA)X((1qμ)G+qμA)(1q)μ)dqμ=2(dc)2[n=0X((1qn)G+qnA)n=0X((1qn+1)G+qn+1A)]2(1+q)(dc)2[n=0qnX((1qn)G+qnA)n=0qnX((1qn+1)G+qn+1A)]=2(dc)2[X(A)X(G)]2(1+q)(dc)2n=0qnX((1qn)G+qnA)+2(1+q)q(dc)2n=1qnX((1qn)G+qnA)=2(dc)2[X(A)X(G)]2(1+q)(dc)2n=0qnX((1qn)G+qnA)+2(1+q)q(dc)2[X(A)X(A)+n=1qnX((1qn)G+qnA)]=2q(dc)2[qf(G)+X(A)]+4(1+q)q(dc)4AGX(μ)dqμ.

    This completes the proof.

    Now using Lemma 5.2, we derive our next results.

    Theorem 5.3. Let X:IR+R+ be a q-differentiable function on I, c,dI with c<d and DqX is an integrable function with 0<q<1. If |DqX| is M-convex, then

    |2(dc)2AGX(μ)dqμqf(G)+X(A)1+q|q(dc)22(1+q)4(1+q+q2){(1+3q2+2q3)|DqX(G)|+(1+4q+q2)|DqX(A)|}.

    Proof. Using Lemma 5.2 and the given hypothesis of the theorem, we have

    |2(dc)2AGX(μ)dqμqf(G)+X(A)1+q|=|q(dc)22(1+q)10(1(1+q)μ)DqX((1μ)G+μA)dqμ|q(dc)22(1+q)10|1(1+q)μ|[(1μ)|DqX(G)|+μDq|DqX(A)|]dqμ=q(dc)22(1+q){|DqX(G)|10(1μ)|1(1+q)μ|dqμ+|DqX(A)|10μ|1(1+q)μ|dqμ}=q(dc)22(1+q)4(1+q+q2){(1+3q2+2q3)|DqX(G)|+(1+4q+q2)|DqX(A)|}.

    This completes the proof.

    Theorem 5.4. Let X:IR+R+ be a q-differentiable function on I, c,dI with c<d and DqX is an integrable function with 0<q<1. If |DqX|r is M-convex, where r>1, then

    |2(dc)2AGX(μ)dqμqf(G)+X(A)1+q|q(dc)22(1+q)(2q(1+q)2)11r(q(1+3q2+2q3)(1+q)3(1+q+q2)|DqX(G)|r+q(1+4q+q2)(1+q)3(1+q+q2)|DqX(A)|r)1r.

    Proof. Using Lemma 5.2, power-mean inequality and the given hypothesis of the theorem, we have

    |2(dc)2AGX(μ)dqμqf(G)+X(A)1+q|=|q(dc)22(1+q)10(1(1+q)μ)DqX((1μ)G+μA)dqμ|q(dc)22(1+q)(10|1(1+q)μ|dqμ)11r×(10|1(1+q)μ|[(1μ)|DqX(G)|r+μ|DqX(A)|r]dqμ)1r=q(dc)22(1+q)(2q(1+q)2)11r(q(1+3q2+2q3)(1+q)3(1+q+q2)|DqX(G)|r+q(1+4q+q2)(1+q)3(1+q+q2)|DqX(A)|r)1r.

    This completes the proof.

    In this article, we have introduced the notions of M-convex functions, log-M-convex functions and quasi M-convex functions. We have discussed these classes in context with integral inequalities of Hermite-Hadamard type. We have also obtained some new fractional and quantum versions of these results. It is worth to mention here that essentially using the techniques of this article one can easily obtain extensions of Iynger type inequalities using the class of quasi M-convex functions. We hope that the ideas and techniques of this paper will inspire interested readers working in the field.

    Authors are thankful to the editor and anonymous referees for their valuable comments and suggestions. First and second authors are thankful for the support of HEC project (No. 8081/Punjab/NRPU/R&D/HEC/2017).

    The authors declare no conflicts of interest.

  • This article has been cited by:

    1. Xuekui Yu, Jonathan Jih, Jiansen Jiang, Z. Hong Zhou, Atomic structure of the human cytomegalovirus capsid with its securing tegument layer of pp150, 2017, 356, 0036-8075, eaam6892, 10.1126/science.aam6892
    2. Hua Jin, Yong-Liang Jiang, Feng Yang, Jun-Tao Zhang, Wei-Fang Li, Ke Zhou, Jue Ju, Yuxing Chen, Cong-Zhao Zhou, Capsid Structure of a Freshwater Cyanophage Siphoviridae Mic1, 2019, 27, 09692126, 1508, 10.1016/j.str.2019.07.003
    3. Joshua M. Hardy, Rhys A. Dunstan, Rhys Grinter, Matthew J. Belousoff, Jiawei Wang, Derek Pickard, Hariprasad Venugopal, Gordon Dougan, Trevor Lithgow, Fasséli Coulibaly, The architecture and stabilisation of flagellotropic tailed bacteriophages, 2020, 11, 2041-1723, 10.1038/s41467-020-17505-w
    4. Yanting Tang, An Mu, Yuying Zhang, Shan Zhou, Weiwei Wang, Yuezheng Lai, Xiaoting Zhou, Fengjiang Liu, Xiuna Yang, Hongri Gong, Quan Wang, Zihe Rao, Cryo-EM structure of Mycobacterium smegmatis DyP-loaded encapsulin, 2021, 118, 0027-8424, e2025658118, 10.1073/pnas.2025658118
    5. James M. Polson, Edgar J. Garcia, Alexander R. Klotz, Flatness and intrinsic curvature of linked-ring membranes, 2021, 17, 1744-683X, 10505, 10.1039/D1SM01307F
    6. Ning Cui, Feng Yang, Jun-Tao Zhang, Hui Sun, Yu Chen, Rong-Cheng Yu, Zhi-Peng Chen, Yong-Liang Jiang, Shu-Jing Han, Xudong Xu, Qiong Li, Cong-Zhao Zhou, Rebecca Ellis Dutch, Capsid Structure of Anabaena Cyanophage A-1(L) , 2021, 95, 0022-538X, 10.1128/JVI.01356-21
    7. Jing Zheng, Wenyuan Chen, Hao Xiao, Fan Yang, Xiaowu Li, Jingdong Song, Lingpeng Cheng, Hongrong Liu, A Capsid Structure of Ralstonia solanacearum podoviridae GP4 with a Triangulation Number T = 9, 2022, 14, 1999-4915, 2431, 10.3390/v14112431
    8. Jennifer M. Podgorski, Krista Freeman, Sophia Gosselin, Alexis Huet, James F. Conway, Mary Bird, John Grecco, Shreya Patel, Deborah Jacobs-Sera, Graham Hatfull, Johann Peter Gogarten, Janne Ravantti, Simon J. White, A structural dendrogram of the actinobacteriophage major capsid proteins provides important structural insights into the evolution of capsid stability, 2023, 31, 09692126, 282, 10.1016/j.str.2022.12.012
    9. Hao Pang, Fenxia Fan, Jing Zheng, Hao Xiao, Zhixue Tan, Jingdong Song, Biao Kan, Hongrong Liu, Three-dimensional structures of Vibrio cholerae typing podophage VP1 in two states, 2024, 09692126, 10.1016/j.str.2024.10.005
    10. Michael Woodson, Nikolai S. Prokhorov, Seth D. Scott, Wei Zhao, Wei Zhang, Kyung H. Choi, Paul J. Jardine, Marc C. Morais, Phi29 assembly intermediates reveal how scaffold interactions with capsid protein drive capsid construction and maturation, 2025, 11, 2375-2548, 10.1126/sciadv.adk8779
  • Reader Comments
  • © 2005 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(3027) PDF downloads(569) Cited by(43)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog