Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session N14: Intrinsically Disordered Proteins and Non-equilibrium ProcessesFocus
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Sponsoring Units: DBIO Chair: Mohammad Nooranidoost, Florida State University Room: Room 206 |
Wednesday, March 8, 2023 11:30AM - 12:06PM |
N14.00001: Universality vs. Specificity in Synaptic Transmission Invited Speaker: Olga Dudko Rapid and precise neuronal communication is enabled through a highly synchronous release of signaling molecules neurotransmitters within just milliseconds of the action potential. Yet neurotransmitter release lacked a theoretical framework that would be both phenomenologically accurate and mechanistically realistic. We present a statistical-mechanical analytic theory of the action-potential-triggered neurotransmitter release at the chemical synapse. The theory is demonstrated to be in detailed quantitative agreement with existing data on a wide variety of synapses from electrophysiological recordings in vivo and fluorescence experiments in vitro. Despite up to ten orders of magnitude of variation in the release rates among different synapses, the theory reveals that synaptic transmission obeys a simple, universal scaling law. The universality is demonstrated through a collapse of experimental data from strikingly diverse synapses onto a single, unifying master curve. The theory allows one to extract, directly from the experimental data, the molecular parameters that uniquely identify each synapse. The theory shows how functional characteristics of synapses – plasticity, fidelity, and efficacy – emerge from molecular properties of neurotransmitter release machinery. |
Wednesday, March 8, 2023 12:06PM - 12:42PM |
N14.00002: Dynamics of water around intrinsically disordered proteins Invited Speaker: David M Leitner Water makes important contributions to protein dynamics, function and folding. While coupled water-structured protein dynamics has been studied for some time, less is known about dynamics of water around intrinsically disordered proteins (IDPs) and proteins with intrinsically disordered regions (IDRs). Results of several studies have indicated water dynamics around IDPs to be more restricted than around structured proteins of similar size, but reasons for this difference are less clear. I will discuss computational studies of water around several IDPs and structured proteins of similar size, and companion megahertz-to-terahertz dielectric spectroscopic measurements [1], which together provide a detailed picture of the extent to which dynamics of water around IDPs is more restricted as well as its origins. I will also discuss more recent computational studies of water around IDRs of a small ubiquitin-like modifier (SUMO-1) protein where we compare dynamics of water exposed to IDRs and structural elements of the protein. |
Wednesday, March 8, 2023 12:42PM - 12:54PM |
N14.00003: Physical characteristics of some intrinsically disordered proteins from simulation studies using mesoscale models Joshua L Ashby, Amrit Vignesh, Swarnadeep Seth, Aniket Bhattacharya Simulation studies using mesoscale models of Intrinsically Disordered Proteins (IDPs) can provide important information regarding their role in various disease. A key aspect of modeling is to identify parameters of the model(s) so that not only they match with the available experimental data but have a broader range of applicability. We will report our simulation results using coarse-grained models of IDPs. First, we will compare our results with the existing results published in the literature, and then extend our studies for a few specific IDPs important in the context of cancer1 and diabetes2. We will invoke polymer physics ideas to describe these IDPs. |
Wednesday, March 8, 2023 12:54PM - 1:06PM |
N14.00004: Emergent thermophoretic behavior in non-equilibrium chemical systems Daniel Maria Busiello, Shiling Liang, Paolo De Los Rios Exposing a solution to a temperature gradient can lead to the accumulation of particles on either the cold or warm side. This phenomenon is known as thermophoresis, and its microscopic origin is still debated. Here, we show that thermophoresis can be observed in any system having internal states with different transport properties, and temperature-modulated rates of transitions between the states. These internal degrees of freedom might be configurational, chemical or velocity states. We also derive an expression for the Soret coefficient, which decides whether particles accumulate on the cold or warm side. Our framework can be applied to any chemical reaction system diffusing in a temperature gradient. It also captures the possibility to observe a sign inversion of the Soret coefficient as the competition between chemical and velocity states. We establish thermophoresis as a genuine non-equilibrium effect, originating from internal microscopic currents consistent with the necessity of transporting heat from warm to cold regions. |
Wednesday, March 8, 2023 1:06PM - 1:18PM |
N14.00005: Searching for colored noise in enhanced diffusion Jin Tae Park, Tian Huang, Steve Granick If claims that chemical reactions can behave as active matter are correct, it should follow that chemical reactions will agitate passive tracers that are suspended in a chemically-reacting solution. We have tested this logic using optical tweezers, trapping colloidal particles in the range 1-4 micrometer diameter, in a homebuilt setup allowing us to resolve fluctuations at frequencies up to 70 MHz. Earlier reports of crossover from ballistic to diffusive motion are confirmed. Focusing on the “click” chemical reaction consisting of copper-catalyzed alkyne-azide cycloaddition, CuAAC, we confirm enhanced fluctuations of the colloidal particle uniformly at all frequencies – which amounts to a shift in the frequency of crossover from ballistic to diffusive motion. |
Wednesday, March 8, 2023 1:18PM - 1:30PM |
N14.00006: Stochastic thermodynamics of resetting with imperfections Kristian Stølevik Olsen, Francesco Mori, Supriya Krishnamurthy Over the past decade, stochastic processes with resetting has gained increased attention. Not only has resetting been shown to be of relevance to a myriad of systems, like extreme events in ecology and search processes, but it also facilitates the study of non-equilibrium steady states that are analytically attainable. Despite the wide range of relevancy to non-equilibrium systems, the thermodynamics of stochastic resetting is not yet fully understood. Fully developing stochastic thermodynamics for systems undergoing resetting has been difficult, as conventional resetting breaks microreversibility; time-reversed trajectories have vanishing probability. Two approaches that circumvent this issue are discussed. By allowing errors in the instantaneous resetting, time-reversed trajectories become well-defined. The full distribution of the entropy production is obtained in this case, which takes a large deviation form. Interesting phenomena like a condensation transition is discussed for certain resetting schemes. An alternate approach is to dynamically realize the resetting process over finite time, for example through switching on and off attractive potentials. Exact entropy production is derived for a large class of switching statistics, and the results are compared with that of instantaneous resetting with errors. |
Wednesday, March 8, 2023 1:30PM - 1:42PM |
N14.00007: Thermodynamic Trade-off Relation in Stochastic Resetting Process Jae Sung Lee, Priyo Pal, Hyunggyu Park We consider a paradigm of overdamped Brownian particle undergoing a stochastic resetting process in a thermal environment. In contrast to the usual set-up of stochastic resetting, here the |
Wednesday, March 8, 2023 1:42PM - 1:54PM |
N14.00008: Highly Nonequilibrium Steady State Induced by a Locally Nonchaotic Energy Barrie Yu Qiao, Zhaoru Shang In this research, we investigate the concept of locally nonchaotic energy barrier, e.g., a narrow step in an external force field. The step width is much less than the nominal mean free path of the particles, so that the particle trajectories inside the step tend to be nonchaotic. Our analyses suggest that under the condition of local nonchaoticity, the steady-state particle distribution cannot reach thermodynamic equilibrium. It has interesting effects: When the energy barrier is varied in an isothermal cycle, the produced work at the low-potential shelf is more than the consumed work at the high-potential shelf; when the step forms an asymmetric couple with a wide ramp, at the steady state, the particle velocity distribution may be anisotropic. |
Wednesday, March 8, 2023 1:54PM - 2:06PM |
N14.00009: Heterogeneous Particle Dynamics Driving Macroscopic Degradation in Porous Electrodes Debbie Zhuang, Martin Z Bazant A Fokker-Planck model that describes the resistance evolution of a population of battery particles is formulated from the idea of a fitness landscape, borrowed from ideas in population genetics. This model incorporates of particle size and heterogeneous degradation accumulates in the particles as the battery is cycled, where resistance formation, surface blockage, and loss of lithium capacity mechanisms are accounted for. A non-homogeneous amount of resistance buildup is formed on the particles which is dependent on the size of the particles, which eventually builds up to rollover failure. Contributions from the heterogeneous degradation, especially at the smaller particles, are observed to contribute to the nonlinear behavior of degradation. It is observed that different degradation mechanisms result in different shapes of the capacity loss curve in the electrode. Macroscopic voltage curves and capacity loss information can give insight into the dominance of different degradation mechanisms. |
Wednesday, March 8, 2023 2:06PM - 2:18PM |
N14.00010: Neuron Operations Compatible with the Physics of a Super-Turing Computational Model Emmett R Redd A. Newell developed an early cognition theory which he completely described in a 1990 book. He realized that brain modeling needed to have an uncountably infinite state space that is unavailable with the countably unbounded space of a Universal Turing Machine (UTM). H. Siegelmann proved that three recurrent neural networks supply a state space beyond that of a UTM. One of them embodies the constraints of the physical universe. It assumes rational weights and stochastic signals. Correspondingly, the universe supplies quantized charges and noise sources. Neurons trigger on finite number of discrete charges or neurotransmitter packets. Through those, neurons have rational weights. They also work in a noisy environment. Consistent with the BPP/log* complexity level proven by Siegelmann, biological neurons can compute in an uncountably infinite state space. Recent noise-enhanced digital (rational) neural network simulations have shown the best noise magnitudes that allow them to mimic chaos. This showed consistency with super-Turing operation. Neurons appear to have found a super-Turing complexity level that makes our brains more creative and versatile than computers. Low-power micro-controllers can simulate the analog input and spiking output(s) of a neuron. Computer simulations of small networks using Hebbian learning are in progress. |
Wednesday, March 8, 2023 2:18PM - 2:30PM |
N14.00011: Connecting structure of individual networks to dynamics in oscillator systems Lyle E Muller, Roberto Budzinski, Alexandra Busch, Gabriel Benigno, Ján Minác New developments in connectomic reconstruction are rapidly increasing the ability to map connection patterns in neural systems, ranging from the microscopic synaptic connection patterns between individual neurons to the macroscopic connectivity patterns between cortical areas. The pace of these developments is increasing with time due to experimental support from programs such as the B.R.A.I.N. Initiative. At the same time, however, a challenge commonly arises: even if we knew the complete connectivity diagram for a single model organism, how could we understand anything about the resulting nonlinear dynamics? Here, we present a new mathematical approach to go from the connectivity of an individual network - for example the realization of a random graph on an individual trial or the precise connection patterns in an experimental reconstruction - to the spatiotemporal pattern of oscillations in a neural system. By introducing a complex-valued matrix formulation for the Kuramoto model, we develop an analytical approach to study the transient behavior arising from the precise topology of a single network. This approach allows us to analytically study the collective behavior of oscillator networks and offers a new, geometric perspective of synchronization phenomena in terms of the spectrum of the network's adjacency matrix. We then use this novel approach to study two important dynamical phenomena in neural systems: (1) the emergence of synchronous oscillations and complex spatiotemporal patterns like chimera states, and (2) patterns of neural activity important for working memory, a short-term store in the brain that is dynamic, flexible, and modifiable online. These results provide new analytical insight into how sophisticated spatiotemporal dynamics arise from specific connection patterns in neural systems. |
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