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Journal articles on the topic 'Structural cell model'

Author: Grafiati

Published: 28 June 2021

Last updated: 18 February 2022

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1

Watanabe, Hiroshi C., Kai Welke, Franziska Schneider, Satoshi Tsunoda, Feng Zhang, Karl Deisseroth, Peter Hegemann, and Marcus Elstner. "Structural Model of Channelrhodopsin." Journal of Biological Chemistry 287, no. 10 (January 11, 2012): 7456–66. http://dx.doi.org/10.1074/jbc.m111.320309.

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2

Drits, V. A., B. A. Sakharov, A. L. Salyn, and A. Manceau. "Structural Model for Ferrihydrite." Clay Minerals 28, no. 2 (June 1993): 185–207. http://dx.doi.org/10.1180/claymin.1993.028.2.02.

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AbstractThe structure of 6-line and 2-line ferrihydrite (Fh) has been reconsidered. X-ray diffraction (XRD) curves were first simulated for the different structural models so far proposed, and it is shown that neither of these corresponds to the actual structure of ferrihydrite. On the basis of agreement between experimental and simulated XRD curves it is shown that Fh is a mixture of three components: (i) Defect-free Fh consisting of anionic ABACA . . . close packing in which Fe atoms occupy only octahedral sites with 50% probability; the hexagonal unit-cell parameters are a = 2-96 Å and c = 9-40 Å, and the space group is P1c. (ii) Defective Fh in which Ac1Bc2A and Ab1Cb2A structural fragments occur with equal probability and alternate completely at random; Fe atoms within each of these fragments have identical ordered distribution with in the hexagonal super-cell with a = 5.26 Å. (iii) Ultradispersed hematite with mean dimension of coherent scattering domains (CSD) of 10-20 Å. The main structural difference between 6-line and 2-line Fh is the size of their CSD which is extremely small for the latter structure. Nearest Fe-Fe distances calculated for this new structural model are very close to those determined by EXAFS spectroscopy on the same samples.

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3

Wu, D. L. "Three-cell model and 5D braided structural composites." Composites Science and Technology 56, no. 3 (January 1996): 225–33. http://dx.doi.org/10.1016/0266-3538(95)00136-0.

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4

Rozhdestvenskaya, I. V., T. Kogure, E. Abe, and V. A. Drits. "A structural model for charoite." Mineralogical Magazine 73, no. 5 (October 2009): 883–90. http://dx.doi.org/10.1180/minmag.2009.073.2.883.

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AbstractThe crystal structure of charoite was investigated mainly by using selected-area electron diffraction (SAED), X-ray diffraction (XRD) and high-resolution electron microscopy (HREM). SAED and XRD patterns indicate that the structure has a monoclinic cell: a = 32.296, b = 19.651, c = 7.16 Å, β = 96.3° and V = 4517 Å3. The space group inferred from systematic absences and HREM images is P21/m. A model of the charoite structure is proposed that is based on the features of related Ca-alkaline silicate structures and HREM images. The structure of charoite consists of three different silicon-oxygen radicals (polymerized SiO4 tetrahedra) which are located between Ca polyhedra. Two of these radicals form continuous tubular structures comprising pectolite-like tetrahedral chains. Calcium polyhedra are joined to form blocks, each of which consists of four columns sharing edges and apices. Potassium and H2O molecules are probably located inside the tubular silicate radicals. From these results, a general formula is derived: K6-7(Ca,Na)18[(Si6O17)(Si12O30)(Si18O45)](OH,F)2.nH2O with two formula units in the unit cell (Z = 2).

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5

Ptitsyn, O. B., A. V. Finkelstein, and A. G. Murzin. "Structural model for interferons." FEBS Letters 186, no. 2 (July 8, 1985): 143–48. http://dx.doi.org/10.1016/0014-5793(85)80697-9.

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6

Kaduk, James A., and Thomas N. Blanton. "An improved structural model for cellulose II." Powder Diffraction 28, no. 3 (April 23, 2013): 194–99. http://dx.doi.org/10.1017/s0885715613000092.

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A sample of cellulose II, prepared by deacetylation of cellulose acetate, has permitted more precise determination of the unit-cell parameters by the Rietveld method. Cellulose II is monoclinic, with space group P21c-axis unique (or P1121) (No. 4) and refined unit-cell parameters a = 8.076(13), b = 9.144(10), c = 10.386(20) Å, γ = 117.00(8)°, and V = 683.5(18) Å3. A density functional geometry optimization using these fixed unit-cell parameters has resulted in an improved structural model for cellulose II. A powder pattern calculated from this new model has been submitted to the ICDD for inclusion in future releases of the Powder Diffraction File.

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7

Ishida, Hideki, and Yoshinobu Shigenaka. "Cell model contraction in the ciliatespirostomum." Cell Motility and the Cytoskeleton 9, no. 3 (1988): 278–82. http://dx.doi.org/10.1002/cm.970090310.

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8

Jones, P. M., and A. M. George. "A New Structural Model for P-Glycoprotein." Journal of Membrane Biology 166, no. 2 (November 15, 1998): 133–47. http://dx.doi.org/10.1007/s002329900455.

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9

Alaimo, Andrea, Federico Marino, and Stefano Valvano. "BCC lattice cell structural characterization." Reports in Mechanical Engineering 2, no. 1 (April 26, 2021): 77–85. http://dx.doi.org/10.31181/rme200102077v.

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In this work, a numerical characterization of BCC lattice cells is performed through the use of an homogenization approach. The main goal is to establish a relationship among those properties and the relative density of the cubic unit cell. The BCC cell struts diameter are the inputs parameters of the homogenization analysis campaing in order to vary the relative density of the unit cell. A linear periodic condition has been applied to the model in order to simulate a clear probing situation. Traction load tests are used in order to evaluate the Young modulus and the Poisson coefficient, differently a pure shear load case is employed for the evaluation of the shear modulus. Hence the final results will be presented in a graphic visualization.

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10

Rosich, Albert, Fatiha Nejjari, and Ramon Sarrate. "Fuel Cell System Diagnosis based on a Causal Structural Model." IFAC Proceedings Volumes 42, no. 8 (2009): 534–39. http://dx.doi.org/10.3182/20090630-4-es-2003.00089.

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11

Balan, Vladimir, and Ileana Rodica Nicola. "Linear and structural stability of a cell division process model." International Journal of Mathematics and Mathematical Sciences 2006 (2006): 1–15. http://dx.doi.org/10.1155/ijmms/2006/51848.

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The paper investigates the linear stability of mammalian physiology time-delayed flow for three distinct cases (normal cell cycle, a neoplasmic cell cycle, and multiple cell arrest states), for the Dirac, uniform, and exponential distributions. For the Dirac distribution case, it is shown that the model exhibits a Hopf bifurcation for certain values of the parameters involved in the system. As well, for these values, the structural stability of the SODE is studied, using the five KCC-invariants of the second-order canonical extension of the SODE, and all the cases prove to be Jacobi unstable.

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12

Rothbard, Jonathan B., Robert I. Lechler, Kevin Howland, Vineeta Bal, David D. Eckels, Rafick Sekaly, Eric O. Long, William R. Taylor, and Jonathan R. Lamb. "Structural model of HLA-DR1 restricted T cell antigen recognition." Cell 52, no. 4 (February 1988): 515–23. http://dx.doi.org/10.1016/0092-8674(88)90464-3.

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13

Wei, Zhen Hai, Meng Shu Wang, and Ding Li Zhang. "Unit Cell Orthogonal Model for Stable Soil Structure." Applied Mechanics and Materials 193-194 (August 2012): 584–91. http://dx.doi.org/10.4028/www.scientific.net/amm.193-194.584.

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The problem of rock and soil structure has long been a major concern in the field of soil mechanics theory. Some literatures have made preliminary discussions of stable static soil structure. The structural and morphological diversity & complexity of rock and soil which is composed of large number of granules have been extensively recognized. We still only have a vague idea of the properties of rock and soil body with different structure and morphology. To further understand the effect of structure and morphology of rock and soil body on its properties, we established a unit cell orthogonal model. The properties of soil body under this structure and morphology were analyzed; the pattern of changes in some major performance parameters, especially in the presence of pores with different morphologies, was discussed. Analysis of unit cell orthogonal model indicated that the structural performance of rock and soil material was mainly affected by porosity, pore distribution, morphology and directionality. The related variation patterns are summarized as follows. The greater the pore area (volume) was, the greater its impact on structural performance would be; the impact of pore distribution relied on pore size. At a fixed porosity, the more scattered the pores were, i.e. the greater the number of pores was, the larger the pore surface area was, and the greater its impact on structural performance (stiffness) would be; on the contrary, the smaller the number of pores was, i.e. the more concentrated the pores were, the greater the soil stiffness would be. These results of analysis agreed well with our past experiences.

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Alimonti, Luca, Abderrazak Mejdi, and Andrea Parrinello. "SEA model for structural acoustic coupling by means of periodic finite element models of the structural subsystems." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 1 (August 1, 2021): 5301–9. http://dx.doi.org/10.3397/in-2021-3044.

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Statistical Energy Analysis (SEA) often relies on simplified analytical models to compute the parameters required to build the power balance equations of a coupled vibro-acoustic system. However, the vibro-acoustic of modern structural components, such as thick sandwich composites, ribbed panels, isogrids and metamaterials, is often too complex to be amenable to analytical developments without introducing further approximations. To overcome this limitation, a more general numerical approach is considered. It was shown in previous publications that, under the assumption that the structure is made of repetitions of a representative unit cell, a detailed Finite Element (FE) model of the unit cell can be used within a general and accurate numerical SEA framework. In this work, such framework is extended to account for structural-acoustic coupling. Resonant as well as non-resonant acoustic and structural paths are formulated. The effect of any acoustic treatment applied to coupling areas is considered by means of a Generalized Transfer Matrix (TM) approach. Moreover, the formulation employs a definition of pressure loads based on the wavenumber-frequency spectrum, hence allowing for general sources to be fully represented without simplifications. Validations cases are presented to show the effectiveness and generality of the approach.

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15

Petersen, Richard C. "Free-Radical Polymer Science Structural Cancer Model: A Review." Scientifica 2013 (2013): 1–17. http://dx.doi.org/10.1155/2013/143589.

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Polymer free-radical lipid alkene chain-growth biological models particularly for hypoxic cellular mitochondrial metabolic waste can be used to better understand abnormal cancer cell morphology and invasive metastasis. Without oxygen as the final electron acceptor for mitochondrial energy synthesis, protons cannot combine to form water and instead mitochondria produce free radicals and acid during hypoxia. Nonuniform bond-length shrinkage of membranes related to erratic free-radical covalent crosslinking can explain cancer-cell pleomorphism with epithelial-mesenchymal transition for irregular membrane borders that “ruffle” and warp over stiff underlying actin fibers. Further, mitochondrial hypoxic conditions produce acid that can cause molecular degradation. Subsequent low pH-activated enzymes then provide paths for invasive cell movement through tissue and eventually blood-born metastasis. Although free-radical crosslinking creates irregularly shaped membranes with structural actin-polymerized fiber extensions as filopodia and lamellipodia, due to rapid cell division the overall cell modulus (approximately stiffness) is lower than normal cells. When combined with low pH-activated enzymes and lower modulus cells, smaller cancer stem cells subsequently have a large advantage to follow molecular destructive pathways and leave the central tumor. In addition, forward structural spike-like lamellipodia protrusions can leverage to force lower-modulus cancer cells through narrow openings. By squeezing and deforming even smaller to allow for easier movement through difficult passageways, cancer cells can travel into adjacent tissues or possibly metastasize through the blood to new tissue.

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16

Szeto, W. Y., Bidisha Ghosh, Biswajit Basu, and Margaret O’Mahony. "Multivariate Traffic Forecasting Technique Using Cell Transmission Model and SARIMA Model." Journal of Transportation Engineering 135, no. 9 (September 2009): 658–67. http://dx.doi.org/10.1061/(asce)0733-947x(2009)135:9(658).

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17

Sohn, Shin-Young. "Structural Equation Model Related to Cell Phone Addiction in Korean Adolescents." Korean Journal of Health Service Management 10, no. 3 (September 30, 2016): 185–97. http://dx.doi.org/10.12811/kshsm.2016.10.3.185.

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18

Dorfmueller, Helge C., Andrew T. Ferenbach, Vladimir S. Borodkin, and Daan M. F. van Aalten. "A Structural and Biochemical Model of Processive Chitin Synthesis." Journal of Biological Chemistry 289, no. 33 (June 18, 2014): 23020–28. http://dx.doi.org/10.1074/jbc.m114.563353.

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19

Deshayes, Sébastien, Thomas Plénat, Gudrun Aldrian-Herrada, Gilles Divita, Christian Le Grimellec, and Frédéric Heitz. "Primary Amphipathic Cell-Penetrating Peptides: Structural Requirements and Interactions with Model Membranes†." Biochemistry 43, no. 24 (June 2004): 7698–706. http://dx.doi.org/10.1021/bi049298m.

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20

Ebihara, A., A. Shinkai, M. Kanagawa, Y. Agari, H. Iino, Y. Kitamura, K. Sakamoto, et al. "Structural and functional whole-cell project for the model organism,Thermus thermophilusHB8." Acta Crystallographica Section A Foundations of Crystallography 64, a1 (August 23, 2008): C361. http://dx.doi.org/10.1107/s0108767308088466.

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21

Reinsmoen, Nancy L., and Fritz H. Bach. "Structural model for T-cell recognition of HLA class II—associated alloepitopes." Human Immunology 27, no. 1 (January 1990): 51–72. http://dx.doi.org/10.1016/0198-8859(90)90095-7.

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22

Betts, Matthew J., and Robert B. Russell. "The hard cell: From proteomics to a whole cell model." FEBS Letters 581, no. 15 (May 30, 2007): 2870–76. http://dx.doi.org/10.1016/j.febslet.2007.05.062.

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23

Лихошвай, В. А., and V. A. Likhoshvai. "Phenotypic Variability of Bacterial Cell Cycle: Mathematical Model." Mathematical Biology and Bioinformatics 11, no. 1 (May 20, 2016): 91–113. http://dx.doi.org/10.17537/2016.11.91.

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The results of the study of mechanisms of different cell phenotypes occurrence in a genetically homogenous population using the bacterial cell cycle model are presented. It was shown that phenotypic variability represents an internal, immanent property of bacteria. The basis of this phenomenon is universal non-linear properties of the conjugated transcription-translation system, that controls all cellular processes. Phenotypic variability occurs in a simple, deterministic, self-reproducing system under the uniform transmission of the structural components to the daughter cells during division and in the absence of any special control mechanisms of molecular-genetic processes and enzymatic reactions.

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24

Garrido, Joaquín María, Daniel Ponce de León, Antonio Berruguete, Silvia Martínez, José Manuel, Lisardo Fort, Diego Yagüe, Jose Alberto González-Escrivá, and Josep R. Medina. "STUDY OF REFLECTION OF NEW LOW-REFLECTIVITY QUAY WALL CAISSON." Coastal Engineering Proceedings 1, no. 32 (January 31, 2011): 27. http://dx.doi.org/10.9753/icce.v32.structures.27.

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This paper presents a new low-reflectivity quay wall caisson based on the formation of cell circuits. The cell circuit lengths can be adapted to the specific wave climate conditions at the construction site to obtain the best performance. Results from physical model tests of conventional and cell circuit caissons are described, as well as the construction process and steel reinforcement, which turns out to be quite similar to highly reflective conventional caissons. Neural Network (NN) models are used to describe the nonlinear relationship observed between experimental coefficients of reflection (CR) and the structural and wave conditions for the new low reflectivity quay wall caisson.

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25

Zengqiong, Huang, and Zhang Gangsheng. "A new structural model of bivalve ligament from Solen grandis." Micron 42, no. 7 (October 2011): 706–11. http://dx.doi.org/10.1016/j.micron.2011.03.010.

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26

Nayar, Rajiv, Colin P. S. Tilcock, Michael J. Hope, Pieter R. Cullis, and Alan J. Schroit. "N-Succinyldioleoylphosphatidylethanolamine: structural preferences in pure and mixed model membranes." Biochimica et Biophysica Acta (BBA) - Biomembranes 937 (1988): 31–41. http://dx.doi.org/10.1016/0005-2736(88)90224-6.

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27

Villanelo, Felipe, Alexis Ordenes, Juan Brunet, Rosalba Lagos, and Octavio Monasterio. "A model for the Escherichia coli FtsB/FtsL/FtsQ cell division complex." BMC Structural Biology 11, no. 1 (2011): 28. http://dx.doi.org/10.1186/1472-6807-11-28.

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28

Pepe, Daniele, and Jin Hwan Do. "Comparison of Perturbed Pathways in Two Different Cell Models for Parkinson's Disease with Structural Equation Model." Journal of Computational Biology 23, no. 2 (February 2016): 90–101. http://dx.doi.org/10.1089/cmb.2015.0156.

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29

Yu, Hongtao. "Structural activation of Mad2 in the mitotic spindle checkpoint: the two-state Mad2 model versus the Mad2 template model." Journal of Cell Biology 173, no. 2 (April 24, 2006): 153–57. http://dx.doi.org/10.1083/jcb.200601172.

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The inheritance of a normal assortment of chromosomes during each cell division relies on a cell-cycle surveillance system called the mitotic spindle checkpoint. The existence of sister chromatids that do not achieve proper bipolar attachment to the mitotic spindle in a cell activates this checkpoint, which inhibits the ubiquitin ligase activity of the anaphase-promoting complex or cyclosome (APC/C) and delays the onset of anaphase. The mitotic arrest deficiency 2 (Mad2) spindle checkpoint protein inhibits APC/C through binding to its mitotic-specific activator, Cdc20. Binding of Mad2 to Cdc20 involves a large conformational change of Mad2 and requires the Mad1–Mad2 interaction in vivo. Two related but distinct models of Mad1-assisted activation of Mad2, the “two-state Mad2” and the “Mad2 template” models, have been proposed. I review the recent structural, biochemical, and cell biological data on Mad2, discuss the differences between the two models, and propose experiments that test their key principles.

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30

UGARTE, JUAN P., CATALINA TOBÓN, ANTÓNIO M. LOPES, and J. A. TENREIRO MACHADO. "A COMPLEX ORDER MODEL OF ATRIAL ELECTRICAL PROPAGATION FROM FRACTAL POROUS CELL MEMBRANE." Fractals 28, no. 06 (September 2020): 2050106. http://dx.doi.org/10.1142/s0218348x20501066.

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Cardiac tissue is characterized by structural and cellular heterogeneities that play an important role in the cardiac conduction system. Under persistent atrial fibrillation (persAF), electrical and structural remodeling occur simultaneously. The classical mathematical models of cardiac electrophysiological showed remarkable progress during recent years. Among those models, it is of relevance the standard diffusion mathematical equation, that considers the myocardium as a continuum. However, the modeling of structural properties and their influence on electrical propagation still reveal several limitations. In this paper, a model of cardiac electrical propagation is proposed based on complex order derivatives. By assuming that the myocardium has an underlying fractal process, the complex order dynamics emerges as an important modeling option. In this perspective, the real part of the order corresponds to the fractal dimension, while the imaginary part represents the log-periodic corrections of the fractal dimension. Indeed, the imaginary part in the derivative implies characteristic scales within the cardiac tissue. The analytical and numerical procedures for solving the related equation are presented. The sinus rhythm and persAF conditions are implemented using the Courtemanche formalism. The electrophysiological properties are measured and analyzed on different scales of observation. The results indicate that the complex order modulates the electrophysiology of the atrial system, through the variation of its real and imaginary parts. The combined effect of the two components yields a broad range of electrophysiological conditions. Therefore, the proposed model can be a useful tool for modeling electrical and structural properties during cardiac conduction.

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31

Friedl, Peter, and Katarina Wolf. "Plasticity of cell migration: a multiscale tuning model." Journal of Cell Biology 188, no. 1 (December 1, 2009): 11–19. http://dx.doi.org/10.1083/jcb.200909003.

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Cell migration underlies tissue formation, maintenance, and regeneration as well as pathological conditions such as cancer invasion. Structural and molecular determinants of both tissue environment and cell behavior define whether cells migrate individually (through amoeboid or mesenchymal modes) or collectively. Using a multiparameter tuning model, we describe how dimension, density, stiffness, and orientation of the extracellular matrix together with cell determinants—including cell–cell and cell–matrix adhesion, cytoskeletal polarity and stiffness, and pericellular proteolysis—interdependently control migration mode and efficiency. Motile cells integrate variable inputs to adjust interactions among themselves and with the matrix to dictate the migration mode. The tuning model provides a matrix of parameters that control cell movement as an adaptive and interconvertible process with relevance to different physiological and pathological contexts.

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32

Skinner, John J., Stacey Wood, James Shorter, S. Walter Englander, and Ben E. Black. "The Mad2 partial unfolding model: regulating mitosis through Mad2 conformational switching." Journal of Cell Biology 183, no. 5 (November 24, 2008): 761–68. http://dx.doi.org/10.1083/jcb.200808122.

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The metamorphic Mad2 protein acts as a molecular switch in the checkpoint mechanism that monitors proper chromosome attachment to spindle microtubules during cell division. The remarkably slow spontaneous rate of Mad2 switching between its checkpoint inactive and active forms is catalyzed onto a physiologically relevant time scale by a self–self interaction between its two forms, culminating in a large pool of active Mad2. Recent structural, biochemical, and cell biological advances suggest that the catalyzed conversion of Mad2 requires a major structural rearrangement that transits through a partially unfolded intermediate.

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33

Bull, Larry. "Evolving Boolean Networks with Structural Dynamism." Artificial Life 18, no. 4 (October 2012): 385–97. http://dx.doi.org/10.1162/artl_a_00073.

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This short article presents an abstract, tunable model of genomic structural change within the cell life cycle and explores its use with simulated evolution. A well-known Boolean model of genetic regulatory networks is extended to include changes in node connectivity based upon the current cell state to begin to capture some of the effects of transposable elements. The evolvability of such networks is explored using a version of the NK model of fitness landscapes with both synchronous and asynchronous updating. Structural dynamism is found to be selected for in nonstationary environments with both update schemes and subsequently shown capable of providing a mechanism for evolutionary innovation when such reorganizations are inherited. This is also found to be the case in stationary environments with asynchronous updating.

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34

Tikhonov, Denis B., and Boris S. Zhorov. "Structural Model for Dihydropyridine Binding to L-type Calcium Channels." Journal of Biological Chemistry 284, no. 28 (May 5, 2009): 19006–17. http://dx.doi.org/10.1074/jbc.m109.011296.

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35

Cheng, Ricky C. K., Denis B. Tikhonov, and Boris S. Zhorov. "Structural Model for Phenylalkylamine Binding to L-type Calcium Channels." Journal of Biological Chemistry 284, no. 41 (August 21, 2009): 28332–42. http://dx.doi.org/10.1074/jbc.m109.027326.

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36

KOSOWER, Edward M. "A structural and dynamic model for the nicotinic acetylcholine receptor." European Journal of Biochemistry 168, no. 2 (October 1987): 431–49. http://dx.doi.org/10.1111/j.1432-1033.1987.tb13437.x.

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37

Várkuti, Boglárka H., Zhenhui Yang, and Andras Malnasi-Csizmadia. "Structural Model of Weak Binding Actomyosin in the Prepowerstroke State." Journal of Biological Chemistry 290, no. 3 (November 21, 2014): 1679–88. http://dx.doi.org/10.1074/jbc.m114.606665.

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38

Harada, Yusuke, Nobuo Nishioka, Noritaka Saito, and Kunihiko Nakashima. "Structural Evaluation of Molten Aluminosilicate by Combining Impedance Measurements and Cell Model Calculations." ISIJ International 60, no. 1 (January 15, 2020): 42–50. http://dx.doi.org/10.2355/isijinternational.isijint-2019-132.

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39

Cañadas, Patrick, Sylvie Wendling-Mansuy, and Daniel Isabey. "Frequency Response of a Viscoelastic Tensegrity Model: Structural Rearrangement Contribution to Cell Dynamics." Journal of Biomechanical Engineering 128, no. 4 (December 29, 2005): 487–95. http://dx.doi.org/10.1115/1.2205867.

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In an attempt to understand the role of structural rearrangement onto the cell response during imposed cyclic stresses, we simulated numerically the frequency-dependent behavior of a viscoelastic tensegrity structure (VTS model) made of 24 elastic cables and 6 rigid bars. The VTS computational model was based on the nonsmooth contact dynamics (NSCD) method in which the constitutive elements of the tensegrity structure are considered as a set of material points that mutually interact. Low amplitude oscillatory loading conditions were applied and the frequency response of the overall structure was studied in terms of frequency dependence of mechanical properties. The latter were normalized by the homogeneous properties of constitutive elements in order to capture the essential feature of spatial rearrangement. The results reveal a specific frequency-dependent contribution of elastic and viscous effects which is responsible for significant changes in the VTS model dynamical properties. The mechanism behind is related to the variable contribution of spatial rearrangement of VTS elements which is decreased from low to high frequency as dominant effects are transferred from mainly elastic to mainly viscous. More precisely, the elasticity modulus increases with frequency while the viscosity modulus decreases, each evolution corresponding to a specific power-law dependency. The satisfactorily agreement found between present numerical results and the literature data issued from in vitro cell experiments suggests that the frequency-dependent mechanism of spatial rearrangement presently described could play a significant and predictable role during oscillatory cell dynamics.

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40

Endicott, J. A., P. Nurse, and L. N. Johnson. "Mutational analysis supports a structural model for the cell cycle protein kinase p34." "Protein Engineering, Design and Selection" 7, no. 2 (1994): 243–57. http://dx.doi.org/10.1093/protein/7.2.243.

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41

Candi, E., and G. Melino. "The human squamous epithelial cell envelope: the structural model by Peter M Steinert." Cell Death & Differentiation 20, no. 8 (July 8, 2013): 965–66. http://dx.doi.org/10.1038/cdd.2013.58.

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42

Barreto, Sara, Casper H. Clausen, Cecile M. Perrault, Daniel A. Fletcher, and Damien Lacroix. "A multi-structural single cell model of force-induced interactions of cytoskeletal components." Biomaterials 34, no. 26 (August 2013): 6119–26. http://dx.doi.org/10.1016/j.biomaterials.2013.04.022.

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43

Sandersius, Sebastian A., and Timothy J. Newman. "Modeling cell rheology with the Subcellular Element Model." Physical Biology 5, no. 1 (April 10, 2008): 015002. http://dx.doi.org/10.1088/1478-3975/5/1/015002.

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Santana Bonilla, Alejandro, Rafael Gutierrez, Leonardo Medrano Sandonas, Daijiro Nozaki, Alessandro Paolo Bramanti, and Gianaurelio Cuniberti. "Structural distortions in molecular-based quantum cellular automata: a minimal model based study." Phys. Chem. Chem. Phys. 16, no. 33 (2014): 17777–85. http://dx.doi.org/10.1039/c4cp02458c.

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Molecular-based quantum cellular automata (m-QCA) offer a novel alternative in which binary information can be encoded in the molecular charge configuration of a cell and propagated via nearest-neighbor Coulombic cell–cell interactions. Structural distortions of the cells may have however a sensitive influence on the m-QCA response and thus, potentially alter its functionality.

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Pokutta, Sabine, Frauke Drees, Soichiro Yamada, W. James Nelson, and William I. Weis. "Biochemical and structural analysis of α-catenin in cell–cell contacts." Biochemical Society Transactions 36, no. 2 (March 20, 2008): 141–47. http://dx.doi.org/10.1042/bst0360141.

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Cadherins are transmembrane adhesion molecules that mediate homotypic cell–cell contact. In adherens junctions, the cytoplasmic domain of cadherins is functionally linked to the actin cytoskeleton through a series of proteins known as catenins. E-cadherin binds to β-catenin, which in turn binds to α-catenin to form a ternary complex. α-Catenin also binds to actin, and it was assumed previously that α-catenin links the cadherin–catenin complex to actin. However, biochemical, structural and live-cell imaging studies of the cadherin–catenin complex and its interaction with actin show that binding of β-catenin to α-catenin prevents the latter from binding to actin. Biochemical and structural data indicate that α-catenin acts as an allosteric protein whose conformation and activity changes depending on whether or not it is bound to β-catenin. Initial contacts between cells occur on dynamic lamellipodia formed by polymerization of branched actin networks, a process controlled by the Arp2/3 (actin-related protein 2/3) complex. α-Catenin can suppress the activity of Arp2/3 by competing for actin filaments. These findings lead to a model for adherens junction formation in which clustering of the cadherin–β-catenin complex recruits high levels of α-catenin that can suppress the Arp2/3 complex, leading to cessation of lamellipodial movement and formation of a stable contact. Thus α-catenin appears to play a central role in cell–cell contact formation.

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Holwill, Michael E. J., and Peter Satir. "Physical model of axonemal splitting." Cell Motility and the Cytoskeleton 27, no. 4 (1994): 287–98. http://dx.doi.org/10.1002/cm.970270402.

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KÜRTEN, KARL E., and FILIPPO CASTIGLIONE. "A DYNAMICAL MODEL OF B–T CELL REGULATION." International Journal of Modern Physics C 12, no. 03 (March 2001): 367–75. http://dx.doi.org/10.1142/s0129183101001766.

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We present a minimal regulatory model for the dynamics of the humoral immune response of two lymphocytes populations (B and T helper) interacting with a specific antigen pool (bacterium). Stability analysis reveals that the system accounts for the occurrence of multiple steady states in the absence as well as in the presence of the antigen population. The model exhibits (i) a state of immune memory, (ii) one state with high antigen and low helper concentration (disease), and (iii) one state with low antigen and high helper concentration (tolerance). The latter state allows oscillatory behavior. Injection of high antigen doses as well as minimal changes of structural parameters provoke the system to jump from the state of disease to the state of tolerance. This is reminiscent of therapies where the patient is treated with allergen, immuno-suppressants or drugs.

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Hsu, Chang-Fu, Rong-Kwei Li, He-Yau Kang, and Amy H. I. Lee. "A Systematic Evaluation Model for Solar Cell Technologies." Mathematical Problems in Engineering 2014 (2014): 1–16. http://dx.doi.org/10.1155/2014/542351.

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Fossil fuels, including coal, petroleum, natural gas, and nuclear energy, are the primary electricity sources currently. However, with depletion of fossil fuels, global warming, nuclear crisis, and increasing environmental consciousness, the demand for renewable energy resources has skyrocketed. Solar energy is one of the most popular renewable energy resources for meeting global energy demands. Even though there are abundant studies on various solar technology developments, there is a lack of studies on solar technology evaluation and selection. Therefore, this research develops a model using interpretive structural modeling (ISM), benefits, opportunities, costs, and risks concept (BOCR), and fuzzy analytic network process (FANP) to aggregate experts' opinions in evaluating current available solar cell technology. A case study in a photovoltaics (PV) firm is used to examine the practicality of the proposed model in selecting the most suitable technology for the firm in manufacturing new products.

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Zaltash, Shahparak, Marie Palmblad, Tore Curstedt, Jan Johansson, and Bengt Persson. "Pulmonary surfactant protein B: a structural model and a functional analogue." Biochimica et Biophysica Acta (BBA) - Biomembranes 1466, no. 1-2 (June 2000): 179–86. http://dx.doi.org/10.1016/s0005-2736(00)00199-1.

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Lieckfeldt, Renate, Jose Villalain, Juan Carmelo Gomez-Fernandez, and Geoffrey Lee. "Diffusivity and structural polymorphism in some model stratum corneum lipid systems." Biochimica et Biophysica Acta (BBA) - Biomembranes 1150, no. 2 (August 1993): 182–88. http://dx.doi.org/10.1016/0005-2736(93)90088-h.

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