arXiv subjects

Gerardo Aquino

Publications and source records attributed to Gerardo Aquino.

At least 19 recordsLinked to original sources

arXiv2026

Noise-induced resonant acceleration of a charge in an intermittent magnetic field: an exact solution for ergodic and non-ergodic fluctuations

We study the diffusion of a charged particle in a magnetic field subject to stochastic dichotomous fluctuations. The associated induced electric field gives rise to non-trivial dynamical regimes. In particular, when the mean magnetic field vanishes, the particle remains confined within a finite radius, regardless of the fluctuation statistics. For a non-zero mean field, we show, using a density approach for Poissonian fluctuations, that the particle undergoes an exponential regime of accelerated diffusion. Crucially and more generally, adopting a trajectory-based formalism, we derive an exact analytical solution valid for arbitrary waiting-time distributions, including non-Poissonian and non-ergodic cases. Even rare, abrupt field reversal are shown to trigger exponential acceleration of the particle's diffusion. We demonstrate that this behaviour stems from noise exciting resonance bands present for periodic fluctuations, and we propose noise-induced resonant acceleration as a robust and efficient charge acceleration mechanism, potentially more effective than Fermi's classic model for cosmic acceleration.

cond-mat.dis-nn↗

arXiv2023

Noise-induced transitions in gene circuits: a perturbative approach for slow noise

We consider a generic class of gene circuits affected by nonlinear extrinsic noise. To address this nonlinearity we introduce a general perturbative methodology based on assuming timescale separation between noise and genes dynamics, with fluctuations exhibiting a large but finite correlation time. We apply this methodology to the case of the toggle switch, and by considering biologically relevant log-normal fluctuations, we find that the system exhibits noise-induced transitions. The system becomes bimodal in regions of the parameter space where it would be deterministically monostable. We show that by including higher order corrections our methodology allows one to obtain correct predictions for the occurrence of transitions even for not so large correlation time of the fluctuations, overcoming thereby limitations of previous theoretical approaches. Interestingly we find that at intermediate noise intensities the noise-induced transition in the toggle switch affects one of the genes involved, but not the other one.

q-bio.MN↗

arXiv2021

Effect of decreasing population growth-rate on deforestation and population sustainability

We consider the effect of non-constant parameters on the human-forest interaction logistic model coupled with human technological growth introduced in "Deforestation and world population sustainability: a quantitative analysis"[1]. In recent years in fact, a decrease in human population growth rate has emerged which can be measured to about 1.7% drop per year since 1960 value which coincides with latest UN projections for next decades up to year 2100 [2]. We therefore consider here the effect of decreasing human population growth-rate on the aforementioned model and we evaluate its effect on the probability of survival of human civilisation without going through a catastrophic collapse in population. We find that for realistic values of the human population carrying capacity of the earth (measured by parameter beta) this decrease would not affect previous results leading to a low probability of avoiding a catastrophic collapse. For larger more optimistic values of beta instead, a decrease in growth-rate would tilt the probability in favour of a positive outcome, i.e. from 10-20% up to even 95% likelihood of avoiding collapse.

q-bio.PE↗

arXiv2021

Effect of ergodic and non-ergodic fluctuations on a charge diffusing in a stochastic Magnetic Field

In this paper, we study the basic problem of a charged particle in a stochastic magnetic field. We consider dichotomous fluctuations of the magnetic field {where the sojourn time in one of the two states are distributed according to a given waiting time distribution either with Poisson or non-Poisson statistics, including as well the case of distributions with diverging mean time between changes of the field}, corresponding to an ergodicity breaking condition. We provide analytical and numerical results for all cases evaluating the average and the second moment of the position and velocity of the particle. We show that the field fluctuations induce diffusion of the charge with either normal or anomalous properties, depending on the statistics of the fluctuations, with distinct regimes from those observed, e.g., in standard Continuous Time Random Walk models.

cond-mat.dis-nn↗

arXiv2020

Bimodality in gene expression without feedback: From Gaussian white noise to log-normal coloured noise

Extrinsic noise-induced transitions to bimodal dynamics have been largely investigated in a variety of chemical, physical, and biological systems. In the standard approach in physical and chemical systems, the key properties that make these systems mathematically tractable are that the noise appears linearly in the dynamical equations, and it is assumed Gaussian and white. In biology, the Gaussian approximation has been successful in specific systems, but the relevant noise being usually non-Gaussian, non-white, and nonlinear poses serious limitations to its general applicability. Here we revisit the fundamental features of linear Gaussian noise, pinpoint its limitations, and review recent new approaches based on nonlinear bounded noises, which highlight novel mechanisms to account for transitions to bimodal behaviour. We do this by considering a simple but fundamental gene expression model, the repressed gene, which is characterized by linear and nonlinear dependencies on external parameters. We then review a general methodology introduced recently, so-called nonlinear noise filtering, which allows the investigation of linear, nonlinear, Gaussian and non-Gaussian noises. We also present a derivation of it, which highlights its dynamical origin. Testing the methodology on the repressed gene confirms that the emergence of noise-induced transitions appears to be strongly dependent on the type of noise adopted, and on the degree of nonlinearity present in the system.

physics.bio-ph↗

arXiv2020

Deforestation and world population sustainability: a quantitative analysis

In this paper we afford a quantitative analysis of the sustainability of current world population growth in relation to the parallel deforestation process adopting a statistical point of view. We consider a simplified model based on a stochastic growth process driven by a continuous time random walk, which depicts the technological evolution of human kind, in conjunction with a deterministic generalised logistic model for humans-forest interaction and we evaluate the probability of avoiding the self-destruction of our civilisation. Based on the current resource consumption rates and best estimate of technological rate growth our study shows that we have very low probability, less than 10% in most optimistic estimate, to survive without facing a catastrophic collapse.

q-bio.PE↗

arXiv2019

Nonlinear Dynamic Models of Conflict via Multiplexed Interaction Networks

The risk of conflict is exasperated by a multitude of internal and external factors. Current multivariate analysis paints diverse causal risk profiles that vary with time. However, these profiles evolve and a universal model to understand that evolution remains absent. Most of the current conflict analysis is data-driven and conducted at the individual country or region level, often in isolation. Consistent consideration of multi-scale interactions and their non-linear dynamics is missing. Here, we develop a multiplexed network model, where each city is modelled as a non-linear bi-stable system with stable states in either war or peace. The causal factor categories which exasperate the risk of conflict are each modelled as a network layer. We consider 3 layers: (1) core geospatial network of interacting cities reflecting ground level interactions, (2) cultural network of interacting countries reflecting cultural groupings, and (3) political network of interacting countries reflecting alliances. Together, they act as drivers to push cities towards or pull cities away from war. Using a variety of data sources relative to 2002-2016, we show, that our model correctly predicts the transitions from war to peace and peace to war with F1 score of 0.78 to 0.92 worldwide at the city scale resolution. As many conflicts during this period are auto-regressive (e.g. the War on Terror in Afghanistan and Iraq, the Narco War across the Americas), we can predict the emergence of new war or new peace. We demonstrate successful predictions across a wide range of conflict genres and we perform causal discovery by identifying which model component led to the correct prediction. In the cases of Somalia (2008-13), Myanmar (2013-15), Colombia (2011-14), Libya (2014-16), and Yemen (2011-13) we identify the set of most likely causal factors and how it may differ across a country and change over time.

physics.soc-ph↗

arXiv2015

Know the single-receptor sensing limit? Think again

How cells reliably infer information about their environment is a fundamentally important question. While sensing and signaling generally start with cell-surface receptors, the degree of accuracy with which a cell can measure external ligand concentration with even the simplest device - a single receptor - is surprisingly hard to pin down. Recent studies provide conflicting results for the fundamental physical limits. Comparison is made difficult as different studies either suggest different readout mechanisms of the ligand-receptor occupancy, or differ on how ligand diffusion is implemented. Here we critically analyse these studies and present a unifying perspective on the limits of sensing, with wide-ranging biological implications.

physics.bio-ph↗

arXiv2015

Information transfer through a signaling module with feedback: a perturbative approach

Signal transduction in biological cells is effected by signaling pathways that typically include multiple feedback loops. Here we analyze information transfer through a prototypical signaling module with biochemical feedback. The module switches stochastically between an inactive and active state; the input to the module governs the activation rate while the output (i.e., the product concentration) perturbs the inactivation rate. Using a novel perturbative approach, we compute the rate with which information about the input is gained from observation of the output. We obtain an explicit analytical result valid to first order in feedback strength and to second order in the strength of input. The total information gained during an extended time interval is found to depend on the feedback strength only through the total number of activation/inactivation events.

physics.bio-ph↗

arXiv2015

Accurate encoding and decoding by single cells: amplitude versus frequency modulation

Cells sense external concentrations and, via biochemical signaling, respond by regulating the expression of target proteins. Both in signaling networks and gene regulation there are two main mechanisms by which the concentration can be encoded internally: amplitude modulation (AM), where the absolute concentration of an internal signaling molecule encodes the stimulus, and frequency modulation (FM), where the period between successive bursts represents the stimulus. Although both mechanisms have been observed in biological systems, the question of when it is beneficial for cells to use either AM or FM is largely unanswered. Here, we first consider a simple model for a single receptor (or ion channel), which can either signal continuously whenever a ligand is bound, or produce a burst in signaling molecule upon receptor binding. We find that bursty signaling is more accurate than continuous signaling only for sufficiently fast dynamics. This suggests that modulation based on bursts may be more common in signaling networks than in gene regulation. We then extend our model to multiple receptors, where continuous and bursty signaling are equivalent to AM and FM respectively, finding that AM is always more accurate. This implies that the reason some cells use FM is related to factors other than accuracy, such as the ability to coordinate expression of multiple genes or to implement threshold crossing mechanisms.

q-bio.SC↗

arXiv2014

Memory improves precision of cell sensing in fluctuating environments

Biological cells are often found to sense their chemical environment near the single-molecule detection limit. Surprisingly, this precision is higher than simple estimates of the fundamental physical limit, hinting towards active sensing strategies. In this work, we analyse the effect of cell memory, e.g. from slow biochemical processes, on the precision of sensing by cell-surface receptors. We derive analytical formulas, which show that memory significantly improves sensing in weakly fluctuating environments. However, surprisingly when memory is adjusted dynamically, the precision is always improved, even in strongly fluctuating environments. In support of this prediction we quantify the directional biases in chemotactic Dictyostelium discoideum cells in a flow chamber with alternating chemical gradients. The strong similarities between cell sensing and control engineering suggest universal problem-solving strategies of living matter.

physics.bio-ph↗

arXiv2013

Weakly driven anomalous diffusion in non-ergodic regime: an analytical solution

We derive the probability density of a diffusion process generated by nonergodic velocity fluctuations in presence of a weak potential, using the Liouville equation approach. The velocity of the diffusing particle undergoes dichotomic fluctuations with a given distribution $ψ(τ)$ of residence times in each velocity state. We obtain analytical solutions for the diffusion process in a generic external potential and for a generic statistics of residence times, including the non-ergodic regime in which the mean residence time diverges. We show that these analytical solutions are in agreement with numerical simulations.

cond-mat.dis-nn↗

arXiv2013

Dynamics of Natural Killer cell receptor revealed by quantitative analysis of photoswitchable protein

Natural Killer (NK) cell activation is dynamically regulated by numerous activating and inhibitory surface receptors that accumulate at the immune synapse. Quantitative analysis of receptor dynamics has been limited by methodologies which rely on indirect measurements such as fluorescence recovery after photobleaching. Here, we report a novel approach to study how proteins traffic to and from the immune synapse using NK cell receptors tagged with the photoswitchable fluorescent protein tdEosFP, which can be irreversibly photoswitched from a green to red fluorescent state by ultraviolet light. Thus, following a localized switching event, the movement of the photoswitched molecules can be temporally and spatially resolved by monitoring fluorescence in two regions of interest. By comparing images with mathematical models, we evaluated the diffusion coefficient of the receptor KIR2DL1 (0.23 +- 0.06 micron^2/s) and assessed how synapse formation affects receptor dynamics. Our data conclude that the inhibitory NK cell receptor KIR2DL1 is continually trafficked into the synapse and remains surprisingly stable there. Unexpectedly however, in NK cells forming synapses with multiple target cells simultaneously, KIR2DL1 at one synapse can relocate to another synapse. Thus, our results reveal a previously undetected inter-synaptic exchange of protein.

q-bio.CB↗

arXiv2011

Transmission of Information between Complex Networks: 1/f-Resonance

We study the transport of information between two complex networks with similar properties. Both networks generate non-Poisson renewal fluctuations with a power-law spectrum 1/f^(3-μ), the case μ= 2 corresponding to ideal 1/f-noise. We denote by μ_S and μ_P the power-law indexes of the network "system" of interest S and the perturbing network P respectively. By adopting a generalized fluctuation-dissipation theorem (FDT) we show that the ideal condition of 1/f-noise for both networks corresponds to maximal information transport. We prove that to make the network S respond when μ_S < 2 we have to set the condition μ_P < 2. In the latter case, if μ_P < μ_S, the system S inherits the relaxation properties of the perturbing network. In the case where μ_P > 2, no response and no information transmission occurs in the long-time limit. We consider two possible generalizations of the fluctuation-dissipation theorem and show that both lead to maximal information transport in the condition of 1/f-noise.

cond-mat.stat-mech↗

arXiv2011

Optimal receptor-cluster size determined by intrinsic and extrinsic noise

Biological cells sense external chemical stimuli in their environment using cell-surface receptors. To increase the sensitivity of sensing, receptors often cluster, most noticeably in bacterial chemotaxis, a paradigm for signaling and sensing in general. While amplification of weak stimuli is useful in absence of noise, its usefulness is less clear in presence of extrinsic input noise and intrinsic signaling noise. Here, exemplified on bacterial chemotaxis, we combine the allosteric Monod-Wyman- Changeux model for signal amplification by receptor complexes with calculations of noise to study their interconnectedness. Importantly, we calculate the signal-to-noise ratio, describing the balance of beneficial and detrimental effects of clustering for the cell. Interestingly, we find that there is no advantage for the cell to build receptor complexes for noisy input stimuli in absence of intrinsic signaling noise. However, with intrinsic noise, an optimal complex size arises in line with estimates of the sizes of chemoreceptor complexes in bacteria and protein aggregates in lipid rafts of eukaryotic cells.

physics.bio-ph↗

arXiv2010

Increased accuracy of ligand sensing by receptor diffusion on cell surface

The physical limit with which a cell senses external ligand concentration corresponds to the perfect absorber, where all ligand particles are absorbed and overcounting of same ligand particles does not occur. Here we analyze how the lateral diffusion of receptors on the cell membrane affects the accuracy of sensing ligand concentration. Specifically, we connect our modeling to neurotransmission in neural synapses where the diffusion of glutamate receptors is already known to refresh synaptic connections. We find that receptor diffusion indeed increases the accuracy of sensing for both the glutamate AMPA and NDMA receptors, although the NMDA receptor is overall much noiser. We propose that the difference in accuracy of sensing of the two receptors can be linked to their different roles in neurotransmission. Specifically, the high accuracy in sensing glutamate is essential for the AMPA receptor to start membrane depolarization, while the NMDA receptor is believed to work in a second stage as a coincidence detector, involved in long-term potentiation and memory.

q-bio.SC↗

arXiv2010

Beyond the Death of Linear Response: 1/f optimal information transport

Non-ergodic renewal processes have recently been shown by several authors to be insensitive to periodic perturbations, thereby apparently sanctioning the death of linear response, a building block of nonequilibrium statistical physics. We show that it is possible to go beyond the ``death of linear response" and establish a permanent correlation between an external stimulus and the response of a complex network generating non-ergodic renewal processes, by taking as stimulus a similar non-ergodic process. The ideal condition of 1/f-noise corresponds to a singularity that is expected to be relevant in several experimental conditions.

cond-mat.stat-mech↗

arXiv2010

Increased accuracy of ligand sensing by receptor internalization

Many types of cells can sense external ligand concentrations with cell-surface receptors at extremely high accuracy. Interestingly, ligand-bound receptors are often internalized, a process also known as receptor-mediated endocytosis. While internalization is involved in a vast number of important functions for the life of a cell, it was recently also suggested to increase the accuracy of sensing ligand as the overcounting of the same ligand molecules is reduced. Here we show, by extending simple ligand-receptor models to out-of-equilibrium thermodynamics, that internalization increases the accuracy with which cells can measure ligand concentrations in the external environment. Comparison with experimental rates of real receptors demonstrates that our model has indeed biological significance.

physics.bio-ph↗