66,172 research outputs found
Identifying feasible operating regimes for early T-cell recognition: The speed, energy, accuracy trade-off in kinetic proofreading and adaptive sorting
In the immune system, T cells can quickly discriminate between foreign and
self ligands with high accuracy. There is evidence that T-cells achieve this
remarkable performance utilizing a network architecture based on a
generalization of kinetic proofreading (KPR). KPR-based mechanisms actively
consume energy to increase the specificity beyond what is possible in
equilibrium.An important theoretical question that arises is to understand the
trade-offs and fundamental limits on accuracy, speed, and dissipation (energy
consumption) in KPR and its generalization. Here, we revisit this question
through numerical simulations where we simultaneously measure the speed,
accuracy, and energy consumption of the KPR and adaptive sorting networks for
different parameter choices. Our simulations highlight the existence of a
'feasible operating regime' in the speed-energy-accuracy plane where T-cells
can quickly differentiate between foreign and self ligands at reasonable energy
expenditure. We give general arguments for why we expect this feasible
operating regime to be a generic property of all KPR-based biochemical networks
and discuss implications for our understanding of the T cell receptor circuit.Comment: 14 pages, 8 figure
Renormalization of radiobiological response functions by energy loss fluctuations and complexities in chromosome aberration induction: deactivation theory for proton therapy from cells to tumor control
We employ a multi-scale mechanistic approach to investigate radiation induced
cell toxicities and deactivation mechanisms as a function of linear energy
transfer in hadron therapy. Our theoretical model consists of a system of
Markov chains in microscopic and macroscopic spatio-temporal landscapes, i.e.,
stochastic birth-death processes of cells in millimeter-scale colonies that
incorporates a coarse-grained driving force to account for microscopic
radiation induced damage. The coupling, hence the driving force in this
process, stems from a nano-meter scale radiation induced DNA damage that
incorporates the enzymatic end-joining repair and mis-repair mechanisms. We use
this model for global fitting of the high-throughput and high accuracy
clonogenic cell-survival data acquired under exposure of the therapeutic
scanned proton beams, the experimental design that considers -H2AX as
the biological endpoint and exhibits maximum observed achievable dose and LET,
beyond which the majority of the cells undergo collective biological
deactivation processes. An estimate to optimal dose and LET calculated from
tumor control probability by extension to cells per -size voxels
is presented. We attribute the increase in degree of complexity in chromosome
aberration to variabilities in the observed biological responses as the beam
linear energy transfer (LET) increases, and verify consistency of the predicted
cell death probability with the in-vitro cell survival assay of approximately
100 non-small cell lung cancer (NSCLC) cells
Characterizing mixed mode oscillations shaped by noise and bifurcation structure
Many neuronal systems and models display a certain class of mixed mode
oscillations (MMOs) consisting of periods of small amplitude oscillations
interspersed with spikes. Various models with different underlying mechanisms
have been proposed to generate this type of behavior. Stochastic versions of
these models can produce similarly looking time series, often with noise-driven
mechanisms different from those of the deterministic models. We present a suite
of measures which, when applied to the time series, serves to distinguish
models and classify routes to producing MMOs, such as noise-induced
oscillations or delay bifurcation. By focusing on the subthreshold
oscillations, we analyze the interspike interval density, trends in the
amplitude and a coherence measure. We develop these measures on a biophysical
model for stellate cells and a phenomenological FitzHugh-Nagumo-type model and
apply them on related models. The analysis highlights the influence of model
parameters and reset and return mechanisms in the context of a novel approach
using noise level to distinguish model types and MMO mechanisms. Ultimately, we
indicate how the suite of measures can be applied to experimental time series
to reveal the underlying dynamical structure, while exploiting either the
intrinsic noise of the system or tunable extrinsic noise.Comment: 22 page
Persistence and survival in equilibrium step fluctuations
Results of analytic and numerical investigations of first-passage properties
of equilibrium fluctuations of monatomic steps on a vicinal surface are
reviewed. Both temporal and spatial persistence and survival probabilities, as
well as the probability of persistent large deviations are considered. Results
of experiments in which dynamical scanning tunneling microscopy is used to
evaluate these first-passage properties for steps with different microscopic
mechanisms of mass transport are also presented and interpreted in terms of
theoretical predictions for appropriate models. Effects of discrete sampling,
finite system size and finite observation time, which are important in
understanding the results of experiments and simulations, are discussed.Comment: 30 pages, 12 figures, review paper for a special issue of JSTA
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