45,302 research outputs found
From a discrete model of chemotaxis with volume-filling to a generalized Patlak–Keller–Segel model
No full textWe present a discrete model of chemotaxis whereby cells responding to a chemoattractant are seen as individual agents whose movement is described through a set of rules that result in a biased random walk. In order to take into account possible alterations in cellular motility observed at high cell densities (i.e. volume-filling), we let the probabilities of cell movement be modulated by a decaying function of the cell density. We formally show that a general form of the celebrated Patlak–Keller–Segel (PKS) model of chemotaxis can be formally derived as the appropriate continuum limit of this discrete model. The family of steady-state solutions of such a generalized PKS model are characterized and the conditions for the emergence of spatial patterns are studied via linear stability analysis. Moreover, we carry out a systematic quantitative comparison between numerical simulations of the discrete model and numerical solutions of the corresponding PKS model, both in one and in two spatial dimensions. The results obtained indicate that there is excellent quantitative agreement between the spatial patterns produced by the two models. Finally, we numerically show that the outcomes of the two models faithfully replicate those of the classical PKS model in a suitable asymptotic regime
A stochastic individual-based model to explore the role of spatial interactions and antigen recognition in the immune response against solid tumours
No full textSpatial interactions between cancer and immune cells, as well as the recognition of tumour antigens by cells of the immune system, play a key role in the immune response against solid tumours. The existing mathematical models generally focus only on one of these key aspects. We present here a spatial stochastic individual-based model that explicitly captures antigen expression and recognition. In our model, each cancer cell is characterised by an antigen profile which can change over time due to either epimutations or mutations. The immune response against the cancer cells is initiated by the dendritic cells that recognise the tumour antigens and present them to the cytotoxic T cells. Consequently, T cells become activated against the tumour cells expressing such antigens. Moreover, the differences in movement between inactive and active immune cells are explicitly taken into account by the model. Computational simulations of our model clarify the conditions for the emergence of tumour clearance, dormancy or escape, and allow us to assess the impact of antigenic heterogeneity of cancer cells on the efficacy of immune action. Ultimately, our results highlight the complex interplay between spatial interactions and adaptive mechanisms that underpins the immune response against solid tumours, and suggest how this may be exploited to further develop cancer immunotherapies
Il PHerc. 1491
No full textIl lavoro illustra la scoperta di pezzi provenienti da vari rotoli (tra cui il De rhetorica di Filodemo), conservati come PHerc. 149
Modelling the Immune Response to Cancer: An Individual-Based Approach Accounting for the Difference in Movement Between Inactive and Activated T Cells
No full textA growing body of experimental evidence indicates that immune cells move in an unrestricted search pattern if they are in the pre-activated state, whilst they tend to stay within a more restricted area upon activation induced by the presence of tumour antigens. This change in movement is not often considered in the existing mathematical models of the interactions between immune cells and cancer cells. With the aim to fill such a gap in the existing literature, in this work we present a spatially structured individual-based model of tumour–immune competition that takes explicitly into account the difference in movement between inactive and activated immune cells. In our model, a Lévy walk is used to capture the movement of inactive immune cells, whereas Brownian motion is used to describe the movement of antigen-activated immune cells. The effects of activation of immune cells, the proliferation of cancer cells and the immune destruction of cancer cells are also modelled. We illustrate the ability of our model to reproduce qualitatively the spatial trajectories of immune cells observed in experimental data of single-cell tracking. Computational simulations of our model further clarify the conditions for the onset of a successful immune action against cancer cells and may suggest possible targets to improve the efficacy of cancer immunotherapy. Overall, our theoretical work highlights the importance of taking into account spatial interactions when modelling the immune response to cancer cells
Re-framing student academic freedom: a capability perspective
No full textThe scholarly debate about academic freedom focuses almost exclusively on the rights of academic faculty. Student academic freedom is rarely discussed and is normally confined to debates connected with the politicisation of the curriculum. Concerns about (student) freedom of speech reflect the dominant role of negative rights in the analysis of academic freedom representing ‘threats’ to academic freedom in terms of rights which may be taken away from a person rather than conferred on them. This paper draws on the distinction between negative and positive rights and the work of Sen (1999) to re-frame student academic freedom as capability. It is argued that capability deprivation has a negative impact on the extent to which students can exercise academic freedom in practice and that student capability can be enhanced through a liberal education that empowers rather than domesticates students
Phytoseius intermedius Evans & MacFarlane
No full textPhytoseius intermedius Evans & MacFarlane Phytoseius (Dubininellus) intermedius Evans & MacFarlane, 1962: 588. Phytoseius (Phytoseius) intermedius.— Ehara, 1972: 170. Phytoseius intermedius.— Moraes et al., 2004: 242; Chant & McMurtry, 2007: 129; Ueckermann et al., 2007: 12; Demite et al., 2008 a: 17. Phytoseius (Phytoseius) yira Pritchard & Baker, 1962: 227 (synonymy according to Denmark, 1966). Specimens examined: Macaubal: P. guajava, XII- 2007 (2); Sales: H. brevispira, IX- 2007 (1); Sto. Antônio do Aracanguá: Miconia sp. 2, XII- 2007 (2); Turmalina: G. ulmifolia, XII- 2007 (2), III- 2008 (11), H. lhotzkyana, XII- 2007 (1), T. casaretti, VII- 2008 (1); União Paulista: C. sellowiana, VI- 2007 (1), IX- 2007 (2), M. fistulifera, VI- 2007 (1), III- 2008 (1). Previous records: Benin (Ueckermann et al., 2007), Burundi (Ueckermann et al., 2007), Brazil (Demite et al., 2008 a), Cape Verde, Democratic Republic of Congo (Ueckerman et al., 2007), India, Japan, Madagascar, Malawi (Ueckermann et al., 2007), Mozambique (Ueckermann et al., 2007), Philippines, Reunion Islands, Rwanda (Ueckermann et al., 2007) and Zimbabwe.Published as part of Demite, Peterson R., Lofego, Antonio C. & Feres, Reinaldo J. F., 2011, Phytoseiidae (Acari) in forest fragments in the State of São Paulo, Brazil, pp. 31-56 in Zootaxa 3086 on page 47, DOI: 10.5281/zenodo.20537
A hybrid discrete-continuum approach to model Turing pattern formation
No full textSince its introduction in 1952, with a further refinement in 1972 by Gierer and Meinhardt, Turing's (pre-)pattern theory (the chemical basis of morphogenesis) has been widely applied to a number of areas in developmental biology, where evolving cell and tissue structures are naturally observed. The related pattern formation models normally comprise a system of reaction-diffusion equations for interacting chemical species (morphogens), whose heterogeneous distribution in some spatial domain acts as a template for cells to form some kind of pattern or structure through, for example, differentiation or proliferation induced by the chemical pre-pattern. Here we develop a hybrid discrete-continuum modelling framework for the formation of cellular patterns via the Turing mechanism. In this framework, a stochastic individual-based model of cell movement and proliferation is combined with a reaction-diffusion system for the concentrations of some morphogens. As an illustrative example, we focus on a model in which the dynamics of the morphogens are governed by an activator-inhibitor system that gives rise to Turing pre-patterns. The cells then interact with the morphogens in their local area through either of two forms of chemically-dependent cell action: Chemotaxis and chemically-controlled proliferation. We begin by considering such a hybrid model posed on static spatial domains, and then turn to the case of growing domains. In both cases, we formally derive the corresponding deterministic continuum limit and show that that there is an excellent quantitative match between the spatial patterns produced by the stochastic individual-based model and its deterministic continuum counterpart, when sufficiently large numbers of cells are considered. This paper is intended to present a proof of concept for the ideas underlying the modelling framework, with the aim to then apply the related methods to the study of specific patterning and morphogenetic processes in the future
Bridging the gap between individual-based and continuum models of growing cell populations
No full textContinuum models for the spatial dynamics of growing cell populations have been widely used to investigate the mechanisms underpinning tissue development and tumour invasion. These models consist of nonlinear partial differential equations that describe the evolution of cellular densities in response to pressure gradients generated by population growth. Little prior work has explored the relation between such continuum models and related single-cell-based models. We present here a simple stochastic individual-based model for the spatial dynamics of multicellular systems whereby cells undergo pressure-driven movement and pressure-dependent proliferation. We show that nonlinear partial differential equations commonly used to model the spatial dynamics of growing cell populations can be formally derived from the branching random walk that underlies our discrete model. Moreover, we carry out a systematic comparison between the individual-based model and its continuum counterparts, both in the case of one single cell population and in the case of multiple cell populations with different biophysical properties. The outcomes of our comparative study demonstrate that the results of computational simulations of the individual-based model faithfully mirror the qualitative and quantitative properties of the solutions to the corresponding nonlinear partial differential equations. Ultimately, these results illustrate how the simple rules governing the dynamics of single cells in our individual-based model can lead to the emergence of complex spatial patterns of population growth observed in continuum models
1993-1994 T. R. Pearson
No full textT. R. Pearson, a.k.a. Rick Gavin, was born in Winston-Salem, North Carolina. He was a student at North Carolina State University, where he gained a B.A. and M.A. in English. He was the first recipient of the John and Renée Grisham Writer in Residence Fellowship. He is the acclaimed author of fourteen novels, including A Short History of a Small Place and Warwolf, and a dozen screenplays. Top of the Rock is his fifth nonfiction book. He lives in Virginia and Brooklyn, New York. (Photo credit: Marian Young)https://egrove.olemiss.edu/grisham_res/1026/thumbnail.jp
(Invited) Ionic Liquids for Rechargeable Metal Batteries
No full textThe emergence of global warming driven by greenhouse gases has put tremendous emphasis on the need to develop improved large scale energy storage systems including low-cost, and high energy density batteries such as rechargeable metal batteries. Batteries in which metals such as lithium (Li), magnesium (Mg), sodium (Na) and zinc (Zn) act as the electroactive species offer great potential in these applications. Room temperature ionic liquids (RTILs) that are, generally, non-volatile, non-flammable and thermally stable have recently been shown to enhance the electrochemical characteristics and long-term cycling of some of these metals[
1
]. For example, Figure 1 below compares the charging behaviour of a Li|LiCoO2 cell in conventional organic electrolyte (solid bold line) to that of RTIL (dashed line)[
2
]. The high rate charging behaviour is substantially improved in the latter electrolyte due to the high solubility of Li ions in the RTIL. The thermal stability of RTILs is also becoming very significant in offering improved safety with these large-scale batteries.
Recent work has demonstrated the importance of functional groups in the RTIL cations and anions [
3
] and the role of additives[
4
] in influencing speciation and electrochemical behaviour. These functionalised ILs are providing a pathway towards cheaper, rechargeable batteries such as those based on zinc[
5
] and magnesium[
6
].
This talk will discuss recent work from our group, and others, in these areas.
Figure 1: 1 C to 5 C charging profiles of organic liquid electrolyte [1M LiPF6, EC:DMC = 50:50 vol.%] (Solid bold line) and 3.2 mol.kg-1 LiFSI in C3mpyrFSI (Dashed line). (Reproduced from ref [
2
]).
[1] a) M. Kar, T. J. Simons, M. Forsyth, D. MacFarlane, Phys. Chem. Chem. Phys.
2014, 16, 18658-18674; b) D. R. MacFarlane, M. Forsyth, P. Howlett, M. Kar, S. Passerini, J. Pringle, H. Ohno, M. Watanabe, F. Yan, W. Zheng, S. Zhang, J. Zhang, Nature Review Materials
2016 - in press.
[2] H. Yoon, P. C. Howlett, A. S. Best, M. Forsyth, D. R. MacFarlane, J. Electrochem. Soc.
2013, 160, A1629-A1637.
[3] M. Kar, B. Winther-Jensen, M. Forsyth, D. R. MacFarlane, Phys. Chem. Chem. Phys.
2013, 15, 7191-7197.
[4] T. J. Simons, A. A. J. Torriero, P. C. Howlett, D. R. MacFarlane, M. Forsyth, Electrochem. Commun.
2012, 18, 119-122.
[5] a) M. Kar, T. J. Simons, B. Winther-Jensen, M. Forsyth, M. Armand, D. MacFarlane, Electrochim. Acta
2014; b) T. J. Simons, M. Salsamendi, P. C. Howlett, M. Forsyth, D. R. Macfarlane, C. Pozo-Gonzalo, ChemElectroChem
2015.
[6] M. Kar, Ma, Z., Chen, K, Azofra, L. M, Forysth, M, MacFarlane, D.R., Chem Comm - submmitted
2015.
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