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arXiv2016

Emergence of Sparsely Synchronized Rhythms and Their Responses to External Stimuli in An Inhomogeneous Small-World Complex Neuronal Network

We consider an inhomogeneous small-world network (SWN) composed of inhibitory short-range (SR) and long-range (LR) interneurons. By varying the fraction of LR interneurons $p_{long}$, we investigate the effect of network architecture on emergence of sparsely synchronized rhythms, and make comparison with that in the Watts-Strogatz SWN. Although SR and LR interneurons have the same average in- and out-degrees, their betweenness centralities (characterizing the potentiality in controlling communication between other interneurons) are distinctly different. Hence, in view of the betweenness, SWNs we consider are inhomogeneous, unlike the "canonical" Watts-Strogatz SWN with nearly same betweenness centralities. As $p_{long}$ is increased, the average path length becomes shorter, and the load of communication traffic is less concentrated on LR interneurons, which leads to better efficiency of global communication between interneurons. Eventually, when passing a critical value $p_{long}^{(c)}$ $(\simeq 0.16)$, sparsely synchronized rhythms are found to emerge. We also consider two cases of external time-periodic stimuli applied to sub-groups of LR and SR interneurons, respectively. Dynamical responses (such as synchronization suppression and enhancement) to these two cases of stimuli are studied and discussed in relation to the betweenness centralities of stimulated interneurons, representing the effectiveness for transfer of stimulation effect in the whole network.

q-bio.NC↗

arXiv2016

SMILE Microscopy : fast and single-plane based super-resolution volume imaging

Fast 3D super-resolution imaging is essential for decoding rapidly occurring biological processes. Encoding single molecules to their respective planes enable simultaneous multi-plane super-resolution volume imaging. This saves the data-acquisition time and as a consequence reduce radiation-dose that lead to photobleaching and other undesirable photochemical reactions. Detection and subsequent identification of the locus of individual molecule (both on the focal plane and off-focal planes) holds the key. Experimentally, this is achieved by accurate calibration of system PSF size and its natural spread in off-focal planes using sub-diffraction fluorescent beads. Subsequently the identification and sorting of single molecules that belong to different axial planes is carried out (by setting multiple cut-offs to respective PSFs). Simultaneous Multiplane Imaging based Localization Encoded (SMILE) microscopy technique eliminates the need for multiple z-plane scanning and thereby provides a truly simultaneous multiplane super-resolution imaging.

physics.bio-ph↗

arXiv2016

On the Application of Viscoelastic & Viscoplastic Constitutive Relations in the CFD Bio-Fluid Simulations

Considerations on implementation of the stress-strain constitutive relations applied in Computational Fluid dynamics (CFD) simulation of cardiovascular flows have been addressed extensively in the literature. However, the matter is yet controversial. The author suggests that the choice of non-Newtonian models and the consideration of non-Newtonian assumption versus the Newtonian assumption is very application oriented and cannot be solely dependent on the vessel size. In the presented work, where a renal disease patient-specific geometry is used, the non-Newtonian effects manifest insignificant, while the vessel is considered to be medium to small which, according to the literature, suggest a strict use of non-Newtonian formulation. The insignificance of the non-Newtonian effects specially manifests in Wall Shear Stress (WSS) along the walls of the numerical domain, where the differences between Newtonian calculated WSS and non-Newtonian calculated WSS is barely visible.

q-bio.QM↗

arXiv2016

Nonlinear Statistical Data Assimilation for HVC$_{\text{RA}}$ Neurons in the Avian Song System

With the goal of building a model of the HVC nucleus in the avian song system, we discuss in detail a model of HVC$_{\text{RA}}$ projection neurons comprised of a somatic compartment with fast Na$^+$ and K$^+$ currents and a dendritic compartment with slower Ca$^{2+}$ dynamics. We show this model qualitatively exhibits many observed electrophysiological behaviors. We then show in numerical procedures how one can design and analyze feasible laboratory experiments that allow the estimation of all of the many parameters and unmeasured dynamical variables, given observations of the somatic voltage $V_s(t)$ alone. A key to this procedure is to initially estimate the slow dynamics associated with Ca, blocking the fast Na and K variations, and then with the Ca parameters fixed, estimate the fast Na and K dynamics. This separation of time scales provides a numerically robust method for completing the full neuron model, and the efficacy of the method is tested by prediction when observations are complete. The simulation provides a framework for the slice preparation experiments and illustrates the use of data assimilation methods for the design of those experiments.

q-bio.NC↗

arXiv2017

Photon-blockade induced photon anti-bunching in photosynthetic Antennas with cyclic structures

One of the important nonclassical effects in quantum optics is the anti-bunching, which has been observed in a large class of physical systems - including light-harvesting antennas with cyclic structures. The units of the ring couple with adjacent ones through dipole-dipole interactions. We show how this strong dipole-dipole interaction leads to photon-blockade resulting in the suppression of double excitation pathway and anti-bunching in photosynthesis systems. The robustness of the photon blockade is demonstrated against the disorder in the ring structures. We hypothesis that the effect may be utilized by light-harvesting systems to avoid damages from excess energy.

physics.chem-ph↗

arXiv2017

A boundary integral method with volume-changing objects for ultrasound-triggered margination of microbubbles

A variety of numerical methods exist for the study of deformable particles in dense suspensions. None of the standard tools, however, currently include volume-changing objects such as oscillating microbubbles in three-dimensional periodic domains. In the first part of this work, we develop a novel method to include such entities based on the boundary integral method. We show that the well-known boundary integral equation must be amended with two additional terms containing the volume flux through the bubble surface. We rigorously prove the existence and uniqueness of the solution. Our proof contains as a subset the simpler boundary integral equation without volume-changing objects (such as red blood cell or capsule suspensions) which is widely used but for which a formal proof in periodic domains has not been published to date. In the second part, we apply our method to study microbubbles for targeted drug delivery. The ideal drug delivery agent should stay away from the biochemically active vessel walls during circulation. However, upon reaching its target it should attain a near-wall position for efficient drug uptake. Though seemingly contradictory, we show that lipid-coated microbubbles in conjunction with a localized ultrasound pulse possess precisely these two properties. This ultrasound-triggered margination is due to hydrodynamic interactions between the red blood cells and the oscillating lipid-coated microbubbles which alternate between a soft and a stiff state. We find that the effect is very robust, existing even if the duration in the stiff state is more than three times lower than the opposing time in the soft state.

physics.bio-ph↗

arXiv2016

Protein Collapse is Encoded in the Folded State Architecture

Natural protein sequences that self-assemble to form globular structures are compact with high packing densities in the folded states. It is known that proteins unfold upon addition of denaturants, adopting random coil structures. The dependence of the radii of gyration on protein size in the folded and unfolded states obeys the same scaling laws as synthetic polymers. Thus, one might surmise that the mechanism of collapse in proteins and polymers ought to be similar. However, because the number of amino acids in single domain proteins is not significantly greater than about two hundred, it has not been resolved if the unfolded states of proteins are compact under conditions that favor the folded states - a problem at the heart of how proteins fold. By adopting a theory used to derive polymer-scaling laws, we find that the propensity for the unfolded state of a protein to be compact is universal and is encoded in the contact map of the folded state. Remarkably, analysis of over 2000 proteins shows that proteins rich in $β$-sheets have greater tendency to be compact than $α$-helical proteins. The theory provides insights into the reasons for the small size of single domain proteins and the physical basis for the origin of multi-domain proteins. Application to non-coding RNA molecules show that they have evolved to collapse sharing similarities to $β$-sheet proteins. An implication of our theory is that the evolution of natural foldable sequences is guided by the requirement that for efficient folding they should populate minimum energy compact states under folding conditions. This concept also supports the compaction selection hypothesis used to rationalize the unusually condensed states of viral RNA molecules.

q-bio.BM↗

arXiv2016

Modelling the effect of curvature on the collective behaviour of cells growing new tissue

The growth of several biological tissues is known to be controlled in part by local geometrical features, such as the curvature of the tissue interface. This control leads to changes in tissue shape that in turn can affect the tissue's evolution. Understanding the cellular basis of this control is highly significant for bioscaffold tissue engineering, the evolution of bone microarchitecture, wound healing, and tumour growth. While previous models have proposed geometrical relationships between tissue growth and curvature, the role of cell density and cell vigor remains poorly understood. We propose a cell-based mathematical model of tissue growth to investigate the systematic influence of curvature on the collective crowding or spreading of tissue-synthesising cells induced by changes in local tissue surface area during the motion of the interface. Depending on the strength of diffusive damping, the model exhibits complex growth patterns such as undulating motion, efficient smoothing of irregularities, and the generation of cusps. We compare this model with in-vitro experiments of tissue deposition in bioscaffolds of different geometries. By accounting for the depletion of active cells, the model is able to capture both smoothing of initial substrate geometry and tissue deposition slowdown as observed experimentally.

q-bio.TO↗

arXiv2016

Neuronal Avalanches: Where Temporal Complexity and Criticality Meet

The model of the current paper is an extension of a previous publication, wherein we used the leaky integrate-and-fire model on a regular lattice with periodic boundary conditions, and introduced the temporal complexity as a genuine signature of criticality. In that work, the power-law distribution of neural avalanches was manifestation of supercriticality rather than criticality. Here, however, we show that continuous solution of the model and replacing the stochastic noise with a Gaussian zero-mean noise leads to the coincidence of power-law display of temporal complexity and spatiotemporal patterns of neural avalanches at the critical point. We conclude that the source of inconsistency may in fact be a numerical artifact originated by the discrete description of the model, which may imply slow numerical convergence of avalanche distribution compared to temporal complexity.

cond-mat.dis-nn↗

arXiv2017

Water-mediated correlations in DNA-enzyme interactions

In this paper we consider dipole-mediated correlations between DNA and enzymes in the context of their water environment. Such correlations emerge from electric dipole-dipole interactions between aromatic ring structures in DNA and in enzymes. We show that there are matching collective modes between DNA and enzyme dipole fields, and that a dynamic time-averaged polarization vanishes in the water dipole field only if either DNA, enzyme, or both are absent from the sample. This persistent field may serve as the electromagnetic image that, in popular colloquialisms about DNA biochemistry, allows enzymes to "scan" or "read" the double helix. Topologically nontrivial configurations in the coherent ground state requiring clamplike enzyme behavior on the DNA may stem, ultimately, from spontaneously broken gauge symmetries.

physics.bio-ph↗

arXiv2016

Bypassing damaged nervous tissue

We show the principal ability of bypassing damaged demyelinated portions of nervous tissue, thereby restoring its normal function for the passage of action potentials. We carry out a theoretical analysis on the basis of the synchronization mechanism of action potential propagation along a bundle of neurons, proposed recently in [1]. And we discuss the feasibility of implement a bypass to restore damaged nervous tissue and creating an artificial neuron network.

physics.bio-ph↗

arXiv2016

Creation of a tight PSF array for scanning structured illumination via phase retrieval

In this work, we propose a structured illumination (SI) method based on a two-photon excitation (TPE) scanning laser beam. Advantages of TPE methods include optical sectioning, low photo-toxicity, and robustness in the face of sample induced scattering. We designed a novel multi-spot point spread function (PSF) for a fast, two-photon scanning SIM microscope. Our multi-spot PSF is generated with a phase retrieval algorithm. We show how to obtain the phase distribution and then simulate the effect of this distribution on a spatial light modulator (SLM), which produces the multi-spot PSF in the object plane of the microscope. We produce simulations that show the viability of this method. The results are simulated and a multi-spot PSF scanning SIM microscope is proposed.

physics.bio-ph↗

arXiv2016

A phenomenological spatial model for macro-ecological patterns in species-rich ecosystems

Over the last few decades, ecologists have come to appreciate that key ecological patterns, which describe ecological communities at relatively large spatial scales, are not only scale dependent, but also intimately intertwined. The relative abundance of species, which informs us about the commonness and rarity of species, changes its shape from small to large spatial scales. The average number of species as a function of area has a steep initial increase, followed by decreasing slopes at large scales. Finally, if we find a species in a given location, it is more likely we find an individual of the same species close-by, rather than farther apart. Such spatial turnover depends on the geographical distribution of species, which often are spatially aggregated. This reverberates on the abundances as well as the richness of species within a region, but so far it has been difficult to quantify such relationships. Within a neutral framework, which considers all individuals competitively equivalent, we introduce a spatial stochastic model, which phenomenologically accounts for birth, death, immigration and local dispersal of individuals. We calculate the pair correlation function, which encapsulates spatial turnover, and the conditional probability to find a species with a certain population within a given circular area. Also, we calculate the macro-ecological patterns, which we have referred to above, and compare the analytical formulæ with the numerical integration of the model. Finally, we contrast the model predictions with the empirical data for two lowland tropical forest inventories, showing always a good agreement.

q-bio.PE↗

arXiv2017

Druse-Induced Morphology Evolution in Retinal Pigment Epithelium

The retinal pigment epithelium (RPE) is a key site of pathogenesis for many retina diseases. The formation of drusen in the retina is characteristic of retinal degeneration. We investigate morphological changes in the RPE in the presence of soft drusen using an integrated experimental and modeling approach. We collect RPE flat mount images from donated human eyes and develop 1) statistical tools to quantify the images and 2) a cell-based model to simulate the morphology evolution. We compare three different mechanisms of RPE repair evolution, cell apoptosis, cell fusion, and expansion, and Simulations of our RPE morphogenesis model quantitatively reproduce deformations of human RPE morphology due to drusen, suggesting that a purse-string mechanism is sufficient to explain how RPE heals cell loss caused by drusen-damage. We found that drusen beneath tissue promote cell death in a number that far exceeds the cell numbers covering the drusen. Tissue deformations are studied using area distributions, Voronoi domains and a texture tensor.

q-bio.TO↗

arXiv2016

Uncertainty of current understanding regarding OBT formation in plants

Radiological impact models are important tools that support nuclear safety. For tritium, a special radionuclide that readily enters the life cycle, the processes involved in its transport into the environment are complex and inadequately understood. For example, tritiated water (HTO) enters plants by leaf and root uptake and is converted to organically bound tritium (OBT) in exchangeable and non-exchangeable forms; however, the observed OBT/HTO ratios in crops exhibit large variability and contradict the current models for routine releases. Non-routine or spike releases of tritium further complicate the prediction of OBT formation. The experimental data for a short and intense atmospheric contamination of wheat are presented together with various models predictions. The experimental data on wheat demonstrate that the OBT formation is a long process, it is dependent on receptor location and stack dynamics, there are differences between night and day releases, and the HTO dynamics in leaf and ear is a very important contributor to OBT formation.

physics.bio-ph↗

arXiv2016

Ripping RNA by Force using Gaussian Network Models

Using force as a probe to map the folding landscapes of RNA molecules has become a reality thanks to major advances in single molecule pulling experiments. Although the unfolding pathways under tension are complicated to predict studies in the context of proteins have shown that topology plays is the major determinant of the unfolding landscapes. By building on this finding we study the responses of RNA molecules to force by adapting Gaussian network model (GNM) that represents RNAs using a bead-spring network with isotropic interactions. Cross-correlation matrices of residue fluctuations, which are analytically calculated using GNM even upon application of mechanical force, show distinct allosteric communication as RNAs rupture. The model is used to calculate the force-extension curves at full thermodynamic equilibrium, and the corresponding unfolding pathways of four RNA molecules subject to a quasi-statically increased force.Our study finds that the analysis using GNM captures qualitatively the unfolding pathway of \emph{T}. ribozyme elucidated by the optical tweezers measurement. However, the simple model is not sufficient to capture subtle features, such as bifurcation in the unfolding pathways or the ion effects, in the forced-unfolding of RNAs.

physics.bio-ph↗

arXiv2016

An Algebraic Solution for the Kermack-McKendrick Model

We present an algebraic solution for the Susceptible-Infective-Removed (SIR) model originally presented by Kermack-McKendrick in 1927. Starting from the differential equation for the removed subjects presented by them in the original paper, we re-write it in a slightly different form in order to derive formally the solution, unless one integration. Then, using algebraic techniques and some well justified numerical assumptions we obtain an analytic solution for the integral. Finally, we compare the numerical solution of the differential equations of the SIR model with the analytically solution here proposed, showing an excellent agreement.

physics.soc-ph↗

arXiv2017

Numerical and analytical approaches to an advection-diffusion problem at small Reynolds number and large Péclet number

Obtaining a detailed understanding of the physical interactions between a cell and its environment often requires information about the flow of fluid surrounding the cell. Cells must be able to effectively absorb and discard material in order to survive. Strategies for nutrient acquisition and toxin disposal, which have been evolutionarily selected for their efficacy, should reflect knowledge of the physics underlying this mass transport problem. Motivated by these considerations, in this paper we discuss the results from an undergraduate research project on the advection-diffusion equation at small Reynolds number and large Péclet number. In particular, we consider the problem of mass transport for a Stokesian spherical swimmer. We approach the problem numerically and analytically through a rescaling of the concentration boundary layer. A biophysically motivated first-passage problem for the absorption of material by the swimming cell demonstrates quantitative agreement between the numerical and analytical approaches. We conclude by discussing the connections between our results and the design of smart toxin disposal systems.

physics.bio-ph↗