To characterize the hits from a phenotypic neurotoxicity screen, we obtained transcriptomics data for valinomycin, diethylstilbestrol, colchicine, rotenone, 1-methyl-4-phenylpyridinium (MPP), carbaryl and berberine (Ber). For all compounds, the concentration triggering neurite degeneration correlated with the onset of gene expression changes. The mechanistically diverse toxicants caused similar patterns of gene regulation: the responses were dominated by cell de-differentiation and a triggering of canonical stress response pathways driven by ATF4 and NRF2. To obtain more detailed and specific information on the modes-of-action, the effects on energy metabolism (respiration and glycolysis) were measured. Ber, rotenone and MPP inhibited the mitochondrial respiratory chain and they shared complex I as the target. This group of toxicants was further evaluated by metabolomics under experimental conditions that did not deplete ATP. Ber (204 changed metabolites) showed similar effects as MPP and rotenone. The overall metabolic situation was characterized by oxidative stress, an over-abundance of NADH (>1000% increase) and a re-routing of metabolism in order to dispose of the nitrogen resulting from increased amino acid turnover. This unique overall pattern led to the accumulation of metabolites known as biomarkers of neurodegeneration (saccharopine, aminoadipate and branched-chain ketoacids). These findings suggest that neurotoxicity of mitochondrial inhibitors may result from an ensemble of metabolic changes rather than from a simple ATP depletion. The combi-omics approach used here provided richer and more specific MoA data than the more common transcriptomics analysis alone. As Ber, a human drug and food supplement, mimicked closely the mode-of-action of known neurotoxicants, its potential hazard requires further investigation.
The actin cortex is a thin layer of actin, myosin, and actin binding proteins that underlies the membrane of most animal cells. It is highly dynamic and can undergo remodelling on time-scales of tens of seconds thanks to protein turnover and myosin-mediated contractions. The cortex enables cells to resist external mechanical stresses, controls cell shape, and allows cells to exert forces on their neighbours. Thus, its mechanical properties are key to its physiological function. Here, we give an overview of how cortex composition, structure, and dynamics control cortex mechanics and cell shape. We use mitosis as an example to illustrate how global and local regulation of cortex mechanics give rise to a complex series of cell shape changes.
Cell migration is often accompanied by collisions with other cells, which can lead to cessation of movement, repolarization, and migration away from the contact site - a process termed contact inhibition of locomotion (CIL). During CIL, the coupling between actomyosin contractilityand cell-substrate adhesions is modified. However, mathematical models describing stochastic cell migration and collision outcomes as a result of the coupling remain elusive. Here, we extend our previously developed stochastic model of single cell migration to include CIL. Our simulation results explain, in terms of the modified contractility and adhesion dynamics, several experimentally observed findings regarding CIL. These include response modulation in the presence of an external cue and alterations of group migration in the absence of CIL. Together with our previous findings, our work is able to explain a wide range of observations about single and collective cell migration.
The binding affinity between the T-cell receptors (TCRs) and antigenic peptides mainly determines immunological recognition. It is not a trivial task that T cells identify the digital sequences of peptide amino acids by simply relying on the integrated binding affinity between TCRs and antigenic peptides. To address this problem, we examine whether the affinity-based discrimination of peptide sequences is learnable and generalizable by artificial neural networks (ANNs) that process the digital experimental amino acid sequence information of receptors and peptides. A pair of TCR and peptide sequences correspond to the input for ANNs, while the success or failure of the immunological recognition correspond to the output. The output is obtained by both theoretical model and experimental data. In either case, we confirmed that ANNs could learn the immunological recognition. We also found that a homogenized encoding of amino acid sequence was more effective for the supervised learning task.
Vyacheslav V. Kalashnikov, Stephan Dempe, Gerardo A. Pérez-Valdés
et al.
A great amount of new applied problems in the area of energy networks has recently arisen that can be efficiently solved only as mixed-integer bilevel programs. Among them are the natural gas cash-out problem, the deregulated electricity market equilibrium problem, biofuel problems, a problem of designing coupled energy carrier networks, and so forth, if we mention only part of such applications. Bilevel models to describe migration processes are also in the list of the most popular new themes of bilevel programming, as well as allocation, information protection, and cybersecurity problems. This survey provides a comprehensive review of some of the above-mentioned new areas including both theoretical and applied results.
Purpose The purpose of this paper is to direct academic librarians to free data resources that support international relations research. This paper provides technical information so readers can download data from referenced sites for analysis. Proper citation of data sources is emphasized. Design/methodology/approach The resources were compiled from teaching information and statistical literacy to diplomacy undergraduate and graduate students. Data and data sets described are relevant to country research and sustainable development. Findings Academic librarians will help students identify if they are looking for data specific to an agency, indicator, initiative, or general topic. Statistical literacy is also an underlying goal for academic librarians. Key word searching is important for finding sources that may not surface through a simple Google search. Research limitations/implications The free services described may not answer all research queries. Librarians may need to use services such as Political Risk Service’s CountryData Online. Practical implications This is an excellent resource list of secondary data sources for academic librarians in areas that may not be their area of expertise or for those not at Tier 1 research institutions. Social implications Students internationally will have access to this data. This has implications for US college students who are competing with students overseas for jobs and will use data to help future employers make strategic decisions. Originality/value There has not been anything published recently in library literature about United Nations data resources. This article features commentary from two Seton Hall University Diplomacy faculty plus EDUCAUSE and UK researchers.
The dynamic interplay between collective cell movement and the various molecules involved in the accompanying cell signalling mechanisms plays a crucial role in many biological processes including normal tissue development and pathological scenarios such as wound healing and cancer. Information about the various structures embedded within these processes allows a detailed exploration of the binding of molecular species to cell-surface receptors within the evolving cell population. In this paper we establish a general spatio-temporal-structural framework that enables the description of molecular binding to cell membranes coupled with the cell population dynamics. We first provide a general theoretical description for this approach and then illustrate it with two examples arising from cancer invasion.
Purpose An interview with Pamela Skinner, Head of Collection Development, Smith College, USA. Design/methodology/approach Interview. Findings An interesting interview providing information about collection development in a private college that is part of a consortium. Originality/value This interview shows how Smith College Libraries is dealing with a changing collection development environment.
Noise induced excitability is studied in type I and II Morris-Lecar neurons subject to constant sub threshold input, where fluctuations arise from sodium and potassium ion channels. Ion channels open and close randomly, creating current fluctuations that can induce spontaneous firing of action potentials. Both noise sources are assumed to be weak so that spontaneous action potentials occur on a longer timescale than ion channel fluctuations. Asymptotic approximations of the stationary density function and most probable paths are developed to understand the role of channel noise in spontaneous excitability. Even though the deterministic dynamical behavior of type I and II action potentials differ, results show that a single mechanism explains how ion channel noise generates spontaneous action potentials.
Domenico Napoletani, Michele Signore, Daniele C. Struppa
We analyze and reinterpret experimental evidence from the literature to argue for an ability of tumor cells to self-regulate their aneuploidy rate. We conjecture that this ability is mediated by a diversification factor that exploits molecular mechanisms common to embryo stem cells and, to a lesser extent, adult stem cells, that is eventually reactivated in tumor cells. Moreover, we propose a direct use of the quasispecies model to cancer cells based on their significant genomic instability (i.e. aneuploidy rate), by defining master sequences lengths as the sum of all copy numbers of physically distinct whole and fragmented chromosomes. We compute an approximate error threshold such that any aneuploidy rate larger than the threshold would lead to a loss of fitness of a tumor population, and we confirm that highly aneuploid cancer populations already function with aneuploidy rates close to the estimated threshold.
Ezio Di Costanzo, Roberto Natalini, Luigi Preziosi
In this paper we propose a "discrete in continuous" mathematical model for the morphogenesis of the posterior lateral line system in zebrafishes. Our model follows closely the results obtained in recent biological experiments. We rely on a hybrid description: discrete for the cellular level and continuous for the molecular level. We prove the existence of steady solutions consistent with the formation of particular biological structure, the neuromasts. Dynamical numerical simulations are performed to show the behavior of the model and its qualitative and quantitative accuracy to describe the evolution of the cell aggregate.
M. A. Pedroza-Toscano, M. Rabelero-Velasco, R. Díaz de León
et al.
Precipitation of silver nanoparticles at 70°C was carried out by dosing a 1.3 M sodium borohydride aqueous solution over bicontinuous microemulsions formed with a mixture of sodium bis(2‐ethylhexyl) sulfosuccinate (AOT) and sodium dodecylsulfate (SDS) as surfactants, a 0.5 M silver nitrate aqueous solution, and toluene. Weight ratios of 2.5/1 and 3/1 AOT/SDS were used in the precipitation reactions. Silver nanoparticles were characterized by transmission electronic microscopy, X‐ray diffraction, and atomic absorption spectroscopy. A mixture of isolated spheroidal nanoparticles (≈15 wt.%) with an average diameter around 10 nm and wormlike structures (≈85 wt.%) with an average length close to 480 nm and an average diameter ca. 40 nm was obtained, regardless of the AOT/SDS ratio. Higher yields were obtained compared with those reported when reverse microemulsions were employed. Formation of wormlike structures was ascribed to one‐dimensional aggregation of crystal and particles within the channels of bicontinuous microemulsions, which performed as templates.
Marlo Flores, Thomas S. Shimuzu, Pieter Rein ten Wolde
et al.
Noise in transduction of chemotactic stimuli to the flagellar motor of E. coli will affect the random run-and-tumble motion of the cell and the ability to perform chemotaxis. Here we use numerical simulations to show that an intermediate level of noise in the slow methylation dynamics enhances drift while not compromising localisation near concentration peaks. A minimal model shows how such an optimal noise level arises from the interplay of noise and the dependence of the motor response on the network output. Our results suggest that cells can exploit noise to improve chemotactic performance.
Joanna Skommer, Subhadip Raychaudhuri, Donald Wlodkowic
The diversity of cell populations is regulated by extracellular and intracellular variability. The latter includes genetic, epigenetic and stochastic variability, all contributing to the experimentally observed heterogeneity in response to external death-inducing stimuli. Studies of sources and regulation of variability in commitment to apoptotic cancer cell death are likely to identify the fundamental features of apoptotic protein networks that are responsible for determining the ultimate cell fate. Systems biology approaches, involving computer simulations of the biochemical reactions accompanied, if possible, by experimental verification of selected components of the model, are proving useful in determining the origins of cell-to-cell variability in response to external stress stimuli. Here we summarize our current understanding of the origins of stochastic variability in cells' commitment to apoptosis, and its implications in the field on cancer therapy.
We describe a simple conductance-based model neuron that includes intra- and extra-cellular ion concentration dynamics and show that this model exhibits periodic bursting. The bursting arises as the fast spiking behavior of the neuron is modulated by the slow oscillatory behavior in the ion concentration variables, and vice versa. By separating these time scales and studying the bifurcation structure of the neuron, we catalog several qualitatively different bursting profiles that are strikingly similar to those seen in experimental preparations. Our work suggests that ion concentration dynamics may play an important role in modulating neuronal excitability in real biological systems.
We present models of dormancy in a planktonic culture and in biofilm, and examine the relative advantage of short dormancy versus long dormancy times in each case. Simulations and analyses indicate that in planktonic batch cultures and in chemostats, live biomass is maximized by the fastest possible exit from dormancy. The lower limit of time to reawakening is thus perhaps governed by physiological, biochemical or other constraints within the cells. In biofilm we see that the slower waker has a defensive advantage over the fast waker due to a larger amount of dormant biomass, without an appreciable difference in total live biomass. Thus it would seem that typical laboratory culture conditions can be unrepresentative of the natural state. We discuss the computational methods developed for this work.
The Wnt signalling pathway transducing the stabilization of beta-catenin is essential for metazoan embryo development and is misregulated in many diseases such as cancers. In recent years models have been proposed for the Wnt signalling pathway during the segmentation process in developing embryos. Many of these include negative feedback loops build around Axin2 regulation. In this article we propose a new negative feedback model for the Wnt pathway with Dickkopf1 (Dkk1) at its core. Dkk1 is a negative regulator of Wnt signalling. In chicken and mouse embryos there is a gradient of Wnt in the presomitic mesoderm (PSM) decreasing from the posterior to the anterior end. The formation of somites and the oscillations of Wnt target genes are controlled by this gradient. Here we incorporate a Wnt gradient and show that synchronization of neighbouring cells in the PSM is important in accordance with experimental observations.
Tijana T. Ivancevic, Murk J. Bottema, Lakhmi C. Jain
We propose a strange-attractor model of tumor growth and metastasis. It is a 4-dimensional spatio-temporal cancer model with strong nonlinear couplings. Even the same type of tumor is different in every patient both in size and appearance, as well as in temporal behavior. This is clearly a characteristic of dynamical systems sensitive to initial conditions. The new chaotic model of tumor growth and decay is biologically motivated. It has been developed as a live Mathematica demonstration, see Wolfram Demonstrator site: http://demonstrations.wolfram.com/ChaoticAttractorInTumorGrowth/ Key words: Reaction-diffusion tumor growth model, chaotic attractor, sensitive dependence on initial tumor characteristics
Tijana T. Ivancevic, Murk J. Bottema, Lakhmi C. Jain
This paper proposes a novel chaotic reaction-diffusion model of cellular tumor growth and metastasis. The model is based on the multiscale diffusion cancer-invasion model (MDCM) and formulated by introducing strong nonlinear coupling into the MDCM. The new model exhibits temporal chaotic behavior (which resembles the classical Lorenz strange attractor) and yet retains all the characteristics of the MDCM diffusion model. It mathematically describes both the processes of carcinogenesis and metastasis, as well as the sensitive dependence of cancer evolution on initial conditions and parameters. On the basis of this chaotic tumor-growth model, a generic concept of carcinogenesis and metastasis is formulated. Keywords: reaction-diffusion tumor growth model, chaotic attractor, sensitive dependence on initial tumor characteristics