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Journal articles on the topic 'Biophysical dynamics'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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1

Berendsen, H. J. C. "Biophysical applications of molecular dynamics." Computer Physics Communications 44, no. 3 (June 1987): 233–42. http://dx.doi.org/10.1016/0010-4655(87)90078-6.

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2

Nelson, David R. "Biophysical Dynamics in Disorderly Environments." Annual Review of Biophysics 41, no. 1 (June 9, 2012): 371–402. http://dx.doi.org/10.1146/annurev-biophys-042910-155236.

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3

Abarbanel, Henry D. I., Leif Gibb, R. Huerta, and M. I. Rabinovich. "Biophysical model of synaptic plasticity dynamics." Biological Cybernetics 89, no. 3 (September 1, 2003): 214–26. http://dx.doi.org/10.1007/s00422-003-0422-x.

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4

Sataric, M. V., and J. A. Tuszynski. "Nonlinear Dynamics of Microtubules: Biophysical Implications." Journal of Biological Physics 31, no. 3-4 (December 2005): 487–500. http://dx.doi.org/10.1007/s10867-005-7288-1.

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5

Su, Qian Peter, and Lining Arnold Ju. "Biophysical nanotools for single-molecule dynamics." Biophysical Reviews 10, no. 5 (August 18, 2018): 1349–57. http://dx.doi.org/10.1007/s12551-018-0447-y.

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6

Fernandez, Fernando R., Jordan D. T. Engbers, and Ray W. Turner. "Firing Dynamics of Cerebellar Purkinje Cells." Journal of Neurophysiology 98, no. 1 (July 2007): 278–94. http://dx.doi.org/10.1152/jn.00306.2007.

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Knowledge of intrinsic neuronal firing dynamics is a critical first step to establishing an accurate biophysical model of any neuron. In this study we examined cerebellar Purkinje cells to determine the bifurcations likely to underlie firing dynamics within a biophysically realistic and experimentally supported model. We show that Purkinje cell dynamics are consistent with a system undergoing a saddle-node bifurcation of fixed points in the transition from rest to firing and a saddle homoclinic bifurcation from firing to rest. Our analyses account for numerous observed Purkinje cell firing pro

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7

Flomenbom, Ophir. "Single File Dynamics Advances with a Focus on Biophysical Relevance." Biophysical Reviews and Letters 09, no. 04 (December 2014): 307–31. http://dx.doi.org/10.1142/s1793048014400013.

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In this review (appearing in the Special Issue on single file dynamics in biophysics and related extensions), three recently treated variants in file dynamics are presented: files with density that is not fixed, files with heterogeneous particles, and files with slow particles. The results in these files include:• In files with a density law that is not fixed, but decays as a power law with an exponent a the distance from the origin, the particle in the origin mean square displacement (MSD) scales like MSD ~ t[1+a]/2, with a Gaussian probability density function (PDF). This extends the scaling

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Sikosek, Tobias, and Hue Sun Chan. "Biophysics of protein evolution and evolutionary protein biophysics." Journal of The Royal Society Interface 11, no. 100 (November 6, 2014): 20140419. http://dx.doi.org/10.1098/rsif.2014.0419.

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The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance

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9

Tortora, Maxime MC, Hossein Salari, and Daniel Jost. "Chromosome dynamics during interphase: a biophysical perspective." Current Opinion in Genetics & Development 61 (April 2020): 37–43. http://dx.doi.org/10.1016/j.gde.2020.03.001.

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10

Chiu, Wah, and Keith Moffat. "Biophysical methods: structure, dynamics and gorgeous images." Current Opinion in Structural Biology 17, no. 5 (October 2007): 546–48. http://dx.doi.org/10.1016/j.sbi.2007.09.008.

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11

Miller, T. F., M. Eleftheriou, P. Pattnaik, A. Ndirango, D. Newns, and G. J. Martyna. "Symplectic quaternion scheme for biophysical molecular dynamics." Journal of Chemical Physics 116, no. 20 (May 22, 2002): 8649–59. http://dx.doi.org/10.1063/1.1473654.

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12

Nagel, Katherine I., and Rachel I. Wilson. "Biophysical mechanisms underlying olfactory receptor neuron dynamics." Nature Neuroscience 14, no. 2 (January 9, 2011): 208–16. http://dx.doi.org/10.1038/nn.2725.

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13

Munro, James B., and Kelly K. Lee. "Probing Structural Variation and Dynamics in the HIV-1 Env Fusion Glycoprotein." Current HIV Research 16, no. 1 (April 19, 2018): 5–12. http://dx.doi.org/10.2174/1570162x16666171222110025.

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Background: Recent advances in structural characterization of the HIV envelope glycoprotein (Env) have provided a high-resolution glimpse of the architecture of this target for neutralizing antibodies and the machinery responsible for mediating receptor binding and membrane fusion. These structures primarily capture the detailed organization of the receptor-naive, prefusion conformation of Env, but under native solution conditions Env is highly dynamic, sampling multiple conformational states as well as exhibiting local protein flexibility. Methods: Special emphasis is placed on the use of bio

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14

Tsegaye, Solomon, Gobena Dedefo, and Mohammed Mehdi. "Biophysical applications in structural and molecular biology." Biological Chemistry 402, no. 10 (July 7, 2021): 1155–77. http://dx.doi.org/10.1515/hsz-2021-0232.

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Abstract The main objective of structural biology is to model proteins and other biological macromolecules and link the structural information to function and dynamics. The biological functions of protein molecules and nucleic acids are inherently dependent on their conformational dynamics. Imaging of individual molecules and their dynamic characteristics is an ample source of knowledge that brings new insights about mechanisms of action. The atomic-resolution structural information on most of the biomolecules has been solved by biophysical techniques; either by X-ray diffraction in single cry

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15

Van Dyke, Chris. "Boxing daze – using state-and-transition models to explore the evolution of socio-biophysical landscapes." Progress in Physical Geography: Earth and Environment 39, no. 5 (May 17, 2015): 594–621. http://dx.doi.org/10.1177/0309133315581700.

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Critical physical geography (CPG) proposes to bridge the lingering gap between human and physical geographers. To rejuvenate conversations among different corners of the discipline about the possibility of trans-disciplinary collaboration, CPG must provide unique epistemological, methodological, and conceptual frameworks that human and physical geographers alike will find appealing, relevant, and timely. These should help them perceptively characterize, narrate, and anticipate changes in socio-biophysical landscapes. This paper outlines a conceptual framework that can be harnessed in future CP

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16

Spill, Fabian, and Muhammad H. Zaman. "Multiscale dynamics of the biophysical and biochemical microenvironment." Physics of Life Reviews 22-23 (December 2017): 127–29. http://dx.doi.org/10.1016/j.plrev.2017.07.004.

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17

Wang, Jun, Daniel Breen, Abraham Akinin, Frederic Broccard, Henry D. I. Abarbanel, and Gert Cauwenberghs. "Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI." IEEE Transactions on Biomedical Circuits and Systems 11, no. 6 (December 2017): 1258–70. http://dx.doi.org/10.1109/tbcas.2017.2776198.

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18

Forzieri, Giovanni, and Filippo Catani. "Scale-dependent relations in land cover biophysical dynamics." Ecological Modelling 222, no. 17 (September 2011): 3285–90. http://dx.doi.org/10.1016/j.ecolmodel.2011.06.010.

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19

Molines, Arthur T., Joel Lemiere, Claire H. Edrington, Chieh-Ting Hsu, Ida E. Steinmark, Klaus Suhling, Gohta Goshima, Liam J. Holt, Gary Brouhard, and Fred Chang. "Cytoplasm Biophysical Properties Limit Cytoskeleton Dynamics In Vivo." Biophysical Journal 120, no. 3 (February 2021): 347a. http://dx.doi.org/10.1016/j.bpj.2020.11.2159.

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20

Sahu, Indra D., and Gary A. Lorigan. "Probing Structural Dynamics of Membrane Proteins Using Electron Paramagnetic Resonance Spectroscopic Techniques." Biophysica 1, no. 2 (March 30, 2021): 106–25. http://dx.doi.org/10.3390/biophysica1020009.

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Membrane proteins are essential for the survival of living organisms. They are involved in important biological functions including transportation of ions and molecules across the cell membrane and triggering the signaling pathways. They are targets of more than half of the modern medical drugs. Despite their biological significance, information about the structural dynamics of membrane proteins is lagging when compared to that of globular proteins. The major challenges with these systems are low expression yields and lack of appropriate solubilizing medium required for biophysical techniques.

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21

Sahu, Indra D., and Gary A. Lorigan. "Electron Paramagnetic Resonance as a Tool for Studying Membrane Proteins." Biomolecules 10, no. 5 (May 13, 2020): 763. http://dx.doi.org/10.3390/biom10050763.

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Membrane proteins possess a variety of functions essential to the survival of organisms. However, due to their inherent hydrophobic nature, it is extremely difficult to probe the structure and dynamic properties of membrane proteins using traditional biophysical techniques, particularly in their native environments. Electron paramagnetic resonance (EPR) spectroscopy in combination with site-directed spin labeling (SDSL) is a very powerful and rapidly growing biophysical technique to study pertinent structural and dynamic properties of membrane proteins with no size restrictions. In this review

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22

Skinner, F. K., J. Y. J. Chung, I. Ncube, P. A. Murray, and S. A. Campbell. "Using Heterogeneity to Predict Inhibitory Network Model Characteristics." Journal of Neurophysiology 93, no. 4 (April 2005): 1898–907. http://dx.doi.org/10.1152/jn.00619.2004.

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From modeling studies it has been known for >10 years that purely inhibitory networks can produce synchronous output given appropriate balances of intrinsic and synaptic parameters. Several experimental studies indicate that synchronous activity produced by inhibitory networks is critical to the production of population rhythms associated with various behavioral states. Heterogeneity of inputs to inhibitory networks strongly affect their ability to synchronize. In this paper, we explore how the amount of input heterogeneity to two-cell inhibitory networks affects their dynamics. Using numer

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23

Chignola, Roberto, Michela Sega, Sabrina Stella, Vladislav Vyshemirsky, and Edoardo Milotti. "From Single-Cell Dynamics to Scaling Laws in Oncology." Biophysical Reviews and Letters 09, no. 03 (September 2014): 273–84. http://dx.doi.org/10.1142/s1793048014300035.

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We are developing a biophysical model of tumor biology. We follow a strictly quantitative approach where each step of model development is validated by comparing simulation outputs with experimental data. While this strategy may slow down our advancements, at the same time it provides an invaluable reward: we can trust simulation outputs and use the model to explore territories of cancer biology where current experimental techniques fail. Here, we review our multi-scale biophysical modeling approach and show how a description of cancer at the cellular level has led us to general laws obeyed by

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24

Duarte, Jorge, Luís Silva, and J. Sousa Ramos. "Computation of the topological entropy in chaotic biophysical bursting models for excitable cells." Discrete Dynamics in Nature and Society 2006 (2006): 1–18. http://dx.doi.org/10.1155/ddns/2006/60918.

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One of the interesting complex behaviors in many cell membranes is bursting, in which a rapid oscillatory state alternates with phases of relative quiescence. Although there is an elegant interpretation of many experimental results in terms of nonlinear dynamical systems, the dynamics of bursting models is not completely described. In the present paper, we study the dynamical behavior of two specific three-variable models from the literature that replicate chaotic bursting. With results from symbolic dynamics, we characterize the topological entropy of one-dimensional maps that describe the sa

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25

Warshel, Arieh, and William W. Parson. "Dynamics of biochemical and biophysical reactions: insight from computer simulations." Quarterly Reviews of Biophysics 34, no. 4 (November 2001): 563–679. http://dx.doi.org/10.1017/s0033583501003730.

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1. Introduction 5632. Obtaining rate constants from molecular-dynamics simulations 5642.1 General relationships between quantum electronic structures and reaction rates 5642.2 The transition-state theory (TST) 5692.3 The transmission coefficient 5723. Simulating biological electron-transfer reactions 5753.1 Semi-classical surface-hopping and the Marcus equation 5753.2 Treating quantum mechanical nuclear tunneling by the dispersed-polaron/spin-boson method 5803.3 Density-matrix treatments 5833.4 Charge separation in photosynthetic bacterial reaction centers 5844. Light-induced photoisomerizatio

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26

Wang, Lili, Marco A. Allodi, and Gregory S. Engel. "Quantum coherences reveal excited-state dynamics in biophysical systems." Nature Reviews Chemistry 3, no. 8 (June 24, 2019): 477–90. http://dx.doi.org/10.1038/s41570-019-0109-z.

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27

Gerken, Thomas A. "Biophysical Approaches to Salivary Mucin Structure, Conformation and Dynamics." Critical Reviews in Oral Biology & Medicine 4, no. 3 (April 1993): 261–70. http://dx.doi.org/10.1177/10454411930040030201.

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Our understanding of the origins of the physical and biochemical properties of mucous glycoproteins is incomplete and not with out controversy. Recent molecular biological and biophysical studies revealing the architecture and solution structure and dynamics of a series of salivary mucins, invaluable toward resolving many of these questions, are discussed. Mucins are very large, structurally heterogeneous, and highly expanded molecules with the carbohydrate playing a key role in maintaining the extended mucin conformation.

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28

Saengpayab, Yaowapa, Pisan Kanthang, Stefan Schreier, Charin Modchang, Narin Nuttavut, Darapond Triampo, and Wannapong Triampo. "Biophysical approach to investigate temperature effects on protein dynamics." European Physical Journal Applied Physics 71, no. 3 (August 2015): 31201. http://dx.doi.org/10.1051/epjap/2015150180.

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29

Olson, Donald B. "Biophysical dynamics of western transition zones: a preliminary synthesis." Fisheries Oceanography 10, no. 2 (June 2001): 133–50. http://dx.doi.org/10.1046/j.1365-2419.2001.00161.x.

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30

Saini, Anuj, and Lydia Kisley. "Fluorescence microscopy of biophysical protein dynamics in nanoporous hydrogels." Journal of Applied Physics 126, no. 8 (August 28, 2019): 081101. http://dx.doi.org/10.1063/1.5110299.

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31

MORSHED, B. I., M. SHAMS, and T. MUSSIVAND. "DERIVING AN ELECTRIC CIRCUIT EQUIVALENT MODEL OF CELL MEMBRANE PORES IN ELECTROPORATION." Biophysical Reviews and Letters 08, no. 01n02 (June 2013): 21–32. http://dx.doi.org/10.1142/s1793048012500099.

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Electroporation is the formation of reversible pores in cell membranes under a brief pulse of high electric field. Dynamics of pore formation during electroporation suggests that the transmembrane potential would settle approximately at the threshold transmembrane potential and the transmembrane resistance would decrease significantly from the state of relaxation. The current electric circuit equivalent models for electroporation containing time-invariant, static and passive components are unable to capture the pore dynamics. A biophysically-inspired electric circuit equivalent model containin

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32

Sikora, Mateusz, Utz H. Ermel, Anna Seybold, Michael Kunz, Giulia Calloni, Julian Reitz, R. Martin Vabulas, Gerhard Hummer, and Achilleas S. Frangakis. "Desmosome architecture derived from molecular dynamics simulations and cryo-electron tomography." Proceedings of the National Academy of Sciences 117, no. 44 (October 16, 2020): 27132–40. http://dx.doi.org/10.1073/pnas.2004563117.

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Desmosomes are cell–cell junctions that link tissue cells experiencing intense mechanical stress. Although the structure of the desmosomal cadherins is known, the desmosome architecture—which is essential for mediating numerous functions—remains elusive. Here, we recorded cryo-electron tomograms (cryo-ET) in which individual cadherins can be discerned; they appear variable in shape, spacing, and tilt with respect to the membrane. The resulting sub-tomogram average reaches a resolution of ∼26 Å, limited by the inherent flexibility of desmosomes. To address this challenge typical of dynamic biol

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33

Brown, Kathryn, and Andrew Hansen. "A Landscape Approach to Aspen Restoration: Understanding the Role of Biophysical Setting in Aspen Community Dynamics." UW National Parks Service Research Station Annual Reports 25 (January 1, 2001): 135–39. http://dx.doi.org/10.13001/uwnpsrc.2001.3479.

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The aim of this study is to better understand the relationship of biotic and abiotic variables to the distribution, performance, and rates of loss of aspen in the Greater Yellowstone Ecosystem. Aspen commumtles, though critically important for maintaining biodiversity, soil quality, and nutrient cycling, are declining rapidly in the Northern Rockies. Fire suppression, elk browsing, and climatic change are the most widely advanced explanations for this widespread loss of aspen. The role of biophysical factors (e.g. topography, climate, soils, and competing vegetation) in determining aspen perfo

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34

McPEAK, JOHN G., DAVID R. LEE, and CHRISTOPHER B. BARRETT. "Introduction: The dynamics of coupled human and natural systems." Environment and Development Economics 11, no. 1 (January 30, 2006): 9–13. http://dx.doi.org/10.1017/s1355770x05002664.

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This essay introduces a special section of this issue containing a set of papers on the dynamics of coupled human and natural systems. We frame this introduction by setting out some of the major issues confronting researchers who wish to incorporate both economic and biophysical dynamics in their analysis. We contrast the three papers contained in this section in terms of how they respond to these different issues. We conclude that these papers provide important new insights on both how to model and analyze dynamic coupled human and natural systems and how to define policies that will lead to

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35

Coombes, Stephen, Brent Doiron, Krešimir Josić, and Eric Shea-Brown. "Towards blueprints for network architecture, biophysical dynamics and signal transduction." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 364, no. 1849 (October 20, 2006): 3301–18. http://dx.doi.org/10.1098/rsta.2006.1903.

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We review mathematical aspects of biophysical dynamics , signal transduction and network architecture that have been used to uncover functionally significant relations between the dynamics of single neurons and the networks they compose. We focus on examples that combine insights from these three areas to expand our understanding of systems neuroscience. These range from single neuron coding to models of decision making and electrosensory discrimination by networks and populations and also coincidence detection in pairs of dendrites and dynamics of large networks of excitable dendritic spines.

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36

Yamamori, Yu, Kazuhiro Takemura, and Akio Kitao. "1PT174 Molecular Dynamics Simulation of Protein Using Robot Dynamics Algorithm(The 50th Annual Meeting of the Biophysical Society of Japan)." Seibutsu Butsuri 52, supplement (2012): S98. http://dx.doi.org/10.2142/biophys.52.s98_5.

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37

Lychko, V. "BIOPHYSICAL MARKERS OF ISCHEMIC STROKE." Eastern Ukrainian Medical Journal 8, no. 3 (2020): 334–38. http://dx.doi.org/10.21272/eumj.2020;8(3):334-338.

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An important and influential factor that directly affects the severity of ischemic stroke (IS) and determines its outcome is the functional state of the membrane-receptor complex (MRC) of cells. One of the most important criteria for assessing this parameter is the β‑adrenergic activity of cytoplasmic membranes (β‑ARM), which plays a leading role in the pathogenesis of IS. The article presents the results of a comprehensive study of the peculiarities of changes in the structural and functional characteristics of brain tissue and β‑adrenoceptors in the acute period of IS to optimize diagnosis.

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38

Yakushevich, L. V. "Nonlinear dynamics of biopolymers: theoretical models, experimental data." Quarterly Reviews of Biophysics 26, no. 2 (May 1993): 201–23. http://dx.doi.org/10.1017/s0033583500004078.

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Nonlinear dynamics of biopolymers is a new and rapidly developing field of biophysical science. It can be considered as a part of the general dynamics which deals with the internal mobility of biopolymers. Theoreticians define it also as the next (anharmonic or nonlinear) approximation after the first harmonic or linear one.

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39

Silveira, Célia M., María A. Castro, Joana M. Dantas, Carlos Salgueiro, Daniel H. Murgida, and Smilja Todorovic. "Structure, electrocatalysis and dynamics of immobilized cytochrome PccH and its microperoxidase." Physical Chemistry Chemical Physics 19, no. 13 (2017): 8908–18. http://dx.doi.org/10.1039/c6cp08361g.

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40

Drüke, Markus, Werner von Bloh, Stefan Petri, Boris Sakschewski, Sibyll Schaphoff, Matthias Forkel, Willem Huiskamp, Georg Feulner, and Kirsten Thonicke. "CM2Mc-LPJmL v1.0: biophysical coupling of a process-based dynamic vegetation model with managed land to a general circulation model." Geoscientific Model Development 14, no. 6 (July 1, 2021): 4117–41. http://dx.doi.org/10.5194/gmd-14-4117-2021.

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Abstract. The terrestrial biosphere is exposed to land-use and climate change, which not only affects vegetation dynamics but also changes land–atmosphere feedbacks. Specifically, changes in land cover affect biophysical feedbacks of water and energy, thereby contributing to climate change. In this study, we couple the well-established and comprehensively validated dynamic global vegetation model LPJmL5 (Lund–Potsdam–Jena managed Land) to the coupled climate model CM2Mc, the latter of which is based on the atmosphere model AM2 and the ocean model MOM5 (Modular Ocean Model 5), and name it CM2Mc

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41

AHN, Kang-Hun. "Biophysical Mechanism of Hearing: From Clinical Studies to Molecular Dynamics." Physics and High Technology 25, no. 10 (October 31, 2016): 13–17. http://dx.doi.org/10.3938/phit.25.051.

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42

Ribeiro-Oliveira, J. P., M. A. Ranal, and M. A. Boselli. "Water Dynamics on Germinating Diaspores: Physiological Perspectives from Biophysical Measurements." Plant Phenomics 2020 (December 6, 2020): 1–16. http://dx.doi.org/10.34133/2020/5196176.

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We demonstrated that classical biophysical measurements of water dynamics on germinating diaspores (seeds and other dispersal units) can improve the understanding of the germination process in a simpler, safer, and newer way. This was done using diaspores of cultivated species as a biological model. To calculate the water dynamics measurements (weighted mass, initial diffusion coefficient, velocity, and acceleration), we used the mass of diaspores recorded over germination time. Weighted mass of germinating diaspores has a similar pattern, independent of the physiological quality, species, or

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43

Chen, Xiaoli, and Jinqiao Duan. "Nonlocal Dynamics for Non-Gaussian Systems Arising in Biophysical Modeling." Communications on Applied Mathematics and Computation 2, no. 2 (September 23, 2019): 201–13. http://dx.doi.org/10.1007/s42967-019-00046-5.

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44

Porat, N., D. Gill, and A. H. Parola. "Adenosine deaminase in cell transformation. Biophysical manifestation of membrane dynamics." Journal of Biological Chemistry 263, no. 29 (October 1988): 14608–11. http://dx.doi.org/10.1016/s0021-9258(18)68077-9.

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45

Zdravković, S., M. Satarić, and J. Tuszyński. "Biophysical Implications of the Peyrard-BishopDauxois Model of DNA Dynamics." Journal of Computational and Theoretical Nanoscience 1, no. 2 (September 1, 2004): 169–79. http://dx.doi.org/10.1166/jctn.2004.013.

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46

Lin, Congping, Yiwei Zhang, Imogen Sparkes, and Peter Ashwin. "Structure and Dynamics of ER: Minimal Networks and Biophysical Constraints." Biophysical Journal 107, no. 3 (August 2014): 763–72. http://dx.doi.org/10.1016/j.bpj.2014.06.032.

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47

Jussupow, Alexander, Ana C. Messias, Ralf Stehle, Arie Geerlof, Sara M. Ø. Solbak, Cristina Paissoni, Anders Bach, Michael Sattler, and Carlo Camilloni. "The dynamics of linear polyubiquitin." Science Advances 6, no. 42 (October 2020): eabc3786. http://dx.doi.org/10.1126/sciadv.abc3786.

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Polyubiquitin chains are flexible multidomain proteins, whose conformational dynamics enable them to regulate multiple biological pathways. Their dynamic is determined by the linkage between ubiquitins and by the number of ubiquitin units. Characterizing polyubiquitin behavior as a function of their length is hampered because of increasing system size and conformational variability. Here, we introduce a new approach to efficiently integrating small-angle x-ray scattering with simulations allowing us to accurately characterize the dynamics of linear di-, tri-, and tetraubiquitin in the free sta

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48

Hinrichsen, Hans-Harald, Mark Dickey-Collas, Martin Huret, Myron A. Peck, and Frode B. Vikebø. "Evaluating the suitability of coupled biophysical models for fishery management." ICES Journal of Marine Science 68, no. 7 (April 21, 2011): 1478–87. http://dx.doi.org/10.1093/icesjms/fsr056.

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Abstract Hinrichsen, H-H., Dickey-Collas, M., Huret, M., Peck, M. A., and Vikebø, F. B. 2011. Evaluating the suitability of coupled biophysical models for fishery management. – ICES Journal of Marine Science, 68: 1478–1487. The potential role of coupled biophysical models in enhancing the conservation, management, and recovery of fish stocks is assessed, with emphasis on anchovy, cod, herring, and sprat in European waters. The assessment indicates that coupled biophysical models are currently capable of simulating transport patterns, along with temperature and prey fields within marine ecosyst

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49

King, Michael R., Kevin G. Phillips, Annachiara Mitrugno, Tae-Rin Lee, Adelaide M. E. de Guillebon, Siddarth Chandrasekaran, Matthew J. McGuire, et al. "A physical sciences network characterization of circulating tumor cell aggregate transport." American Journal of Physiology-Cell Physiology 308, no. 10 (May 15, 2015): C792—C802. http://dx.doi.org/10.1152/ajpcell.00346.2014.

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Circulating tumor cells (CTC) have been implicated in the hematogenous spread of cancer. To investigate the fluid phase of cancer from a physical sciences perspective, the multi-institutional Physical Sciences-Oncology Center (PS-OC) Network performed multidisciplinary biophysical studies of single CTC and CTC aggregates from a patient with breast cancer. CTCs, ranging from single cells to aggregates comprised of 2–5 cells, were isolated using the high-definition CTC assay and biophysically profiled using quantitative phase microscopy. Single CTCs and aggregates were then modeled in an in vitr

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50

Sekhar, Ashok, and Lewis E. Kay. "An NMR View of Protein Dynamics in Health and Disease." Annual Review of Biophysics 48, no. 1 (May 6, 2019): 297–319. http://dx.doi.org/10.1146/annurev-biophys-052118-115647.

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Abstract:

Biological molecules are often highly dynamic, and this flexibility can be critical for function. The large range of sampled timescales and the fact that many of the conformers that are continually explored are only transiently formed and sparsely populated challenge current biophysical approaches. Solution nuclear magnetic resonance (NMR) spectroscopy has emerged as a powerful method for characterizing biomolecular dynamics in detail, even in cases where excursions involve short-lived states. Here, we briefly review a number of NMR experiments for studies of biomolecular dynamics on the micro

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