2,140 research outputs found
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Cell-to-cell variability in cell death: can systems biology help us make sense of it all?
One of the most common observations in cell death assays is that not all cells die at the same time, or at the same treatment dose. Here, using the perspective of the systems biology of apoptosis and the context of cancer treatment, we discuss possible sources of this cell-to-cell variability as well as its implications for quantitative measurements and computational models of cell death. Many different factors, both within and outside of the apoptosis signaling networks, have been correlated with the variable responses to various death-inducing treatments. Systems biology models offer us the opportunity to take a more synoptic view of the cell death process to identify multifactorial determinants of the cell death decision. Finally, with an eye toward ‘systems pharmacology', we discuss how leveraging this new understanding should help us develop combination treatment strategies to compel cancer cells toward apoptosis by manipulating either the biochemical state of cancer cells or the dynamics of signal transduction
Wallerian degeneration: gaining perspective on inflammatory events after peripheral nerve injury
In this review, we first provide a brief historical perspective, discussing how peripheral nerve injury (PNI) may have caused World War I. We then consider the initiation, progression, and resolution of the cellular inflammatory response after PNI, before comparing the PNI inflammatory response with that induced by spinal cord injury (SCI)
Optically Induced Thermal Gradients for Protein Characterization in Nanolitre-scale Samples in Microfluidic Devices
Proteins are the most vital biological functional units in every living cell. Measurement of protein stability is central to understanding their structure, function and role in diseases. While proteins are also sought as therapeutic agents, they can cause diseases by misfolding and aggregation in vivo. Here we demonstrate a novel method to measure protein stability and denaturation kinetics, on unprecedented timescales, through optically-induced heating of nanolitre samples in microfluidic capillaries. We obtain protein denaturation kinetics as a function of temperature, and accurate thermodynamic stability data, from a snapshot experiment on a single sample. We also report the first experimental characterization of optical heating in controlled microcapillary flow, verified by computational fluid dynamics modelling. Our results demonstrate that we now have the engineering science in hand to design integrated all-optical microfluidic chips for a diverse range of applications including in-vitro DNA amplification, healthcare diagnostics, and flow chemistry
Non-equilibrium phase transitions in biomolecular signal transduction
We study a mechanism for reliable switching in biomolecular
signal-transduction cascades. Steady bistable states are created by system-size
cooperative effects in populations of proteins, in spite of the fact that the
phosphorylation-state transitions of any molecule, by means of which the switch
is implemented, are highly stochastic. The emergence of switching is a
nonequilibrium phase transition in an energetically driven, dissipative system
described by a master equation. We use operator and functional integral methods
from reaction-diffusion theory to solve for the phase structure, noise
spectrum, and escape trajectories and first-passage times of a class of minimal
models of switches, showing how all critical properties for switch behavior can
be computed within a unified framework
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Applying robust control theory to solve problems in bio-medical sciences: study of an apoptotic model
Biological models of an apoptotic process are studied using models describing a system of differential equations derived from reaction kinetics information. The mathematical model is re-formulated in a state-space robust control theory framework where parametric and dynamic uncertainty can be modelled to account for variations naturally occurring in biological processes. We propose to handle the nonlinearities using neural networks
The 2011 stripe rust epidemic in western Canada
Non-Peer Reviewe
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