Stochastically Gating Ion Channels Enable Patterned Spike Firing through Activity-Dependent Modulation of Spike Probability

The transformation of synaptic input into patterns of spike output is a fundamental operation that is determined by the particular complement of ion channels that a neuron expresses. Although it is well established that individual ion channel proteins make stochastic transitions between conducting and non-conducting states, most models of synaptic integration are deterministic, and relatively little is known about the functional consequences of interactions between stochastically gating ion channels. Here, we show that a model of stellate neurons from layer II of the medial entorhinal cortex implemented with either stochastic or deterministically gating ion channels can reproduce the resting membrane properties of stellate neurons, but only the stochastic version of the model can fully account for perithreshold membrane potential fluctuations and clustered patterns of spike output that are recorded from stellate neurons during depolarized states. We demonstrate that the stochastic model implements an example of a general mechanism for patterning of neuronal output through activity-dependent changes in the probability of spike firing. Unlike deterministic mechanisms that generate spike patterns through slow changes in the state of model parameters, this general stochastic mechanism does not require retention of information beyond the duration of a single spike and its associated afterhyperpolarization. Instead, clustered patterns of spikes emerge in the stochastic model of stellate neurons as a result of a transient increase in firing probability driven by activation of HCN channels during recovery from the spike afterhyperpolarization. Using this model, we infer conditions in which stochastic ion channel gating may influence firing patterns in vivo and predict consequences of modifications of HCN channel function for in vivo firing patterns

Chlamydial Pre-Infection Protects From Subsequent Herpes Simplex Virus-2 Challenge in a Murine Vaginal Super-Infection Model

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Chlamydia trachomatis and Herpes Simplex Virus-2 (HSV-2) genital tract co-infections have been reported in humans and studied in vitro but the clinical consequences are unknown. Limited epidemiologic evidence suggests that these co-infections could be more severe than single infections of either pathogen, but the host-pathogen interactions during co-infection remain uncharacterized. To determine whether disease progression and/or pathogen shedding differs between singly-infected and super-infected animals, we developed an in vivo super-infection model in which female BALB/c mice were vaginally infected with Chlamydia muridarum (Cm) followed later by HSV-2. Pre-infection with Chlamydia 3 or 9 days prior to HSV-2 super-infection conferred significant protection from HSV-2-induced neurologic disease and significantly reduced viral recovery compared to HSV-2 singlyinfected controls. Neither protection from mortality nor reduced viral recovery were observed when mice were i) super-infected with HSV-2 on day 27 post Cm; ii) infected with UV-irradiated Cm and super-infected with HSV-2; or iii) azithromycin-treated prior to HSV-2 super-infection. Therefore, protection from HSV-2-induced disease requires active infection with viable chlamydiae and is not observed after chlamydial shedding ceases, either naturally or due to antibiotic treatment. Thus, Chlamydia-induced protection is transient and requires the continued presence of chlamydiae or their components. These data demonstrate that chlamydial pre-infection can alter progression of subsequent HSV-2 infection, with implications for HSV-2 transmission from co-infected humans

A pseudo‐transient optimization framework for periodic processes: Pressure swing adsorption and simulated moving bed chromatography

Periodic systems are widely used in separation processes and in reaction engineering. They are designed for and operated at a cyclic steady state (CSS). Identifying and optimizing the CSS has proven to be computationally challenging. A novel framework for equation-oriented simulation and optimization of cyclic processes is introduced. A two-step reformulation of the process model is proposed, comprising, (1) a full discretization of the time and spatial domains and (2) recasting the discretized model as a differential-algebraic equation system, for which theoretical stability guarantees are provided. Additionally, a mathematical, structural connection between the CSS constraints and material recycling is established, which allows us to deal with these conditions via a “tearing” procedure. These developments are integrated in a pseudo-transient design optimization framework and two extensive case studies are presented: a simulated moving bed chromatography system and a pressure swing adsorption process. © 2017 American Institute of Chemical Engineers AIChE J, 64: 2982–2996, 201

Properties of photon density waves in multiple-scattering media.

Amplitude-modulated light launched into multiple-scattering media, e.g., tissue, results in the propagation of density waves of diffuse photons. Photon density wave characteristics in turn depend on modulation frequency (omega) and media optical properties. The damped spherical wave solutions to the homogeneous form of the diffusion equation suggest two distinct regimes of behavior: (1) a high-frequency dispersion regime where density wave phase velocity V(p) has a radicalomega dependence and (2) a low-frequency domain where V(p), is frequency independent. Optical properties are determined for various tissue phantoms by fitting the recorded phase (?) and modulation (m) response to simple relations for theappropriate regime. Our results indicate that reliable estimates of tissue like optical properties can be obtained, particularly when multiple modulation frequencies are employed

Rate-based modeling and economic optimization of next-generation amine-based carbon capture plants

Amine scrubbing processes remain an important technology for mitigating the contribution of carbon emissions to global warming and climate change. Like other chemical processes, they can benefit from computer-aided optimization at the design stage, but systematic optimization procedures are rarely employed due to the challenges of simulating the requisite rate-based mass transfer and reaction models. This paper presents a novel approach for the simulation and optimization of rate-based columns, with specific application to the absorber and stripper columns found in (amine-) solvent-based carbon capture processes. The approach is based on pseudo-transient continuation, and the resulting column models are easily incorporated into large-scale process flowsheets with other previously developed pseudo-transient models. We demonstrate that the proposed approach allows for gradient-based optimization of next-generation amine scrubbing processes by considering a complex carbon capture process under three different operating conditions. The results provide general insight into the design of amine scrubbing processes, and shadow prices at the optimal point(s) suggest potential avenues for improving the process economics. The effects of carbon dioxide removal percentage and flue gas composition on process economics are briefly analyzed

Boundary conditions for the diffusion equation in radiative transfer.

Using the method of images, we examine the three boundary conditions commonly applied to the surface of a semi-infinite turbid medium. We find that the image-charge configurations of the partial-current and extrapolated-boundary conditions have the same dipole and quadrupole moments and that the two corresponding solutions to the diffusion equation are approximately equal. In the application of diffusion theory to frequency-domain photon-migration (FDPM) data, these two approaches yield values for the scattering and absorption coefficients that are equal to within 3%. Moreover, the two boundary conditions can be combined to yield a remarkably simple, accurate, and computationally fast method for extracting values for optical parameters from FDPM data. FDPM data were taken both at the surface and deep inside tissue phantoms, and the difference in data between the two geometries is striking. If one analyzes the surface data without accounting for the boundary, values deduced for the optical coefficients are in error by 50% or more. As expected, when aluminum foil was placed on the surface of a tissue phantom, phase and modulation data were closer to the results for an infinite-medium geometry. Raising the reflectivity of a tissue surface can, in principle, eliminate the effect of the boundary. However, we find that phase and modulation data are highly sensitive to the reflectivity in the range of 80-100%, and a minimum value of 98% is needed to mimic an infinite-medium geometry reliably. We conclude that noninvasive measurements of optically thick tissue require a rigorous treatment of the tissue boundary, and we suggest a unified partial-current--extrapolated boundary approach