Eric Sembrat's Test Bonanza

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Multicellular behavior in bacterial biofilms is intimately tied to the production of an extracellular polysaccharide (EPS) matrix that encases the cells and provides physical integrity to the colony as a whole.  As a colony grows from a few cells into a biofilm, a sudden increase in EPS production generates osmotic stresses that cause the biofilm to expand. Moreover, EPS production is triggered by a nutrient depletion gradient that develops in the biofilm due to diffusive mass transport limitations. These polymer physics based biofilm behaviors suggest that EPS production may have evolved in biofilms to beat the diffusion limit of nutrient transport into the colony, though no direct observation of nutrient transport has been observed previously. In this talk I will discuss measurements of nutrient transport into b. subtilis biofilms and show that when EPS production is up-regulated, the polymer sucks fluid into the colony with a characteristic time dependence like that of pressure driven flow.

In contrast to bacteria in biofilms, eukaryotic cell behavior in tissues is intimately tied to forces generated by molecular motor-driven contractions.  Contraction generated tensions are balanced by deformations in the cell's microenvironment, by internal cytoskeletal structures, and by the incompressible cytosolic fluid contained within the cell membrane.  However, contraction generated pressures cannot be supported by the cytosol if the cell membrane is adequately permeable.  Small, non-selective pores called gap junctions connect cells in a layer, allowing small molecules to pass between cells.  In the second half of this talk I will discuss measurements of contraction driven fluid movement across gap junctions connecting neighboring cells.  We observe contracting cells pushing fluid into their neighbors.  To study the mechanics of intercellular fluid flow, we apply biologically relevant pressures to large regions of cells in a monolayer with a micro-indentation system.  We directly measure indentation force and volume as a function of time to determine fluid flow rates and associated stresses between cells.  We find that gap-junction permeability does not limit fluid transport between cells, and that fluid flow is controlled by a balance of cytoskeletal tension throughout the cell monolayer.

 

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I will discuss three examples describing the utility of understanding and/or exploiting both epigenetic and genetic variability in populations of yeast cells. First, I describe an unappreciated and dominant role for cell-cycle phase on transcriptional variability and dynamics. We show that for a model “noisy” gene in S. cerevisiae, the common view that large variability observed in mRNA numbers is due to a transcriptional bursting, where a promoter undergoes random and intermittent periods of active transcription, is incomplete and possibly incorrect. Rather, variable mRNA distributions are largely driven by differences in transcriptional activity between G1 and S/G2/M phases of the cell cycle. The cell-cycle phase is also paramount when probing variability in the kinetics of gene activation, with early S/G2 appearing to be far more permissive for activation. This global cell-cycle dependence may be essential to consider when using stochastic models to predict the behavior of both natural and synthetically engineered gene networks, especially in conditions when growth rate changes.

Second, I describe how variable numbers of tandemly repeated “decoy” transcription factor (TF) binding sites that bind a cognate transcriptional activator can reduce expression at the activator’s target genes, qualitatively converting the dose-response from a linear to steeper sigmoidal-like threshold response. The results imply that 1) transcription factor (TF) / promoter binding may be weaker than expected in the context of gene expression and 2) there may be a previously unappreciated negative cooperativity in TF binding to clustered sites. Therefore, even small quantitative changes in the highly variable length of repetitive DNA containing TF binding sites found in eukaryotic genomes can have qualitative effects on gene expression, and perhaps ultimately phenotype.

Third, I describe a technique we have developed for the repeated and targeted in vivo mutagenesis of multiple genes in S. cerevisiae. We show selective damage of DNA and subsequent repair by error-prone homologous recombination pathways can lead to selective >800-fold increase in mutation rate in a user-defined 20 kb target region. We discuss applications of this method for the directed evolution of multigenic phenotypes. Deployment is simple and our constructs and protocols are available to interested researchers.

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Motivated by issues related to treating certain neurological diseases such as Parkinson’s disease by a method called electrical deep brain stimulation, we consider applying optimal control methods to both mathematical models of neurons and in vitro neurons. Patients suffering from Parkinson’s disease experience involuntary tremors that typically affect the distal portion of their upper limbs. It has been hypothesized that these tremors are associated with simultaneous spiking of a cluster of neurons in the thalamus and basal ganglia regions of the brain. In a healthy situation, the periodic firing of neurons is not synchronized, but they can engage in a pathological synchrony and all fire at the same time which results in release of strong action potentials that trigger the downstream muscles with periodic shocks, manifested as tremors.

In this talk, we investigate the control of different neuronal systems using methods of optimal control. The neuronal systems considered range from simple one-dimensional phase models to multi-dimensional conductance-based models, both on a single neuron level and on a population level. The optimal control methods considered produce event-based, continuous-time, typically bounded input stimuli that can optimally achieve the desired control objective. The optimality criterion considered is minimum energy. The control objectives of interest are the interspike interval for single neurons and desynchrony for populations of neurons. The applicability of the interspike interval controller is shown in practice by testing it on single in vitro pyramidal neurons in the CA1 region of rat hippocampus.
 

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I present a new numerical code constructed to obtain accurate simulations of encounters between a star and a massive black hole. The relativistic tidal interaction is calculated in \emph{Fermi normal coordinates} (FNC). This formalism allows the addition of an arbitrary number of terms in the tidal expansion. Although Newtonian hydrodynamics and self-gravity is assumed for the star, there are several significant terms in the expansion that should be retained. I give the relevant orbital post-Newtonian terms. The three-dimensional parallel (MPI) code includes a PPMLR hydrodynamics module to treat the gas dynamics and a Fourier transform-based method to calculate the self-gravity. Results are given for a white dwarf ($n=1.5$ polytrope) with comparisons between simulations and predictions from the linear theory of tidal encounters. The encounters are at the threshold of disruption ($\eta=1-6$) for white dwarf to black hole mass ratios $\mu \sim 10^{-5}-10^{-3}$. It is shown that the inclusion of the octupole ($l=3$) tidal term will cause the center of mass of the star to deviate from the origin of the FNC. Also shown is a relativistic suppression in the amount of energy deposited onto the star. Finally, I estimate the new orbital parameters for the star after it passes by the black hole.

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Dr. Robert Liu trained as a condensed matter experimentalist working on quantum transport and noise in mesoscopic semiconductors, but always believed that the true value of a physics doctorate was in learning how to think through and solve problems. As a graduate student at Stanford, he became fascinated with questions about the brain and memory, and decided to apply his quantitative training from physics to the study of neuroscience. He moved to the University of California at San Francisco’s Sloan-Swartz Center for Theoretical Neurobiology to begin postdoctoral work on studying the neural code used in sensory systems. What is the brain signaling about the outside world? How are stimuli that are behaviorally relevant to us represented in neural activity? How do we evaluate this code quantitatively? Is it efficient? These are some of the questions that initially drew his curiosity, and he pursued a principled approach to addressing them grounded in studying how natural stimuli are processed in the brain. At UCSF, he collaborated with others to develop a mouse electrophysiology preparation to study these in the context of auditory processing of natural communication sounds. He expanded this work from an anesthetized mouse preparation to recordings in awake mice.

He will discuss both his own scientific trajectory and some selected results at the intersection of interests from both neuroscience and physics perspectives.

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Galaxy collisions and mergers are a common consequence of the structure formation in the universe. We know that they happen because we see a number of beautiful examples on the sky through the "eyes" of many astronomical observatories. It is also thought that almost every galaxy (including our own, the Milky Way) harbors a supermassive black hole at its center. I will discuss the "knowns" and "unknowns" in the evolution of supermassive black hole pairs that form in collisions of their host galaxies and end their cosmic journey when the two black
holes merge due to the emission of gravitational waves.

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Since the discovery of superconductivity - the ability of certain materials to conduct electricity without dissipation - at the laboratory of Kamerlingh Onnes in 1911, the phenomenon has become ubiquitous in Nature. Over the span of a century, innumerous superconductor s – also called charged superfluids - have been discovered starting from the element Mercury to more complex materials such as Copper Oxides.  In addition, several neutral superfluids were discovered ranging from liquid Helium to ultra-cold atoms.   A key characteristic of neutral or charged superfluids is that they allow the flow of energy through the material without dissipation.  Such exotic property has been found in certain metals, neutron stars, nuclei and ultra-cold atoms, but they are still of limited use.  In order to engineer superfluid systems and take advantage of their properties, it is necessary to understand them and learn how to control them – a task that requires time, substantial investments, extensive research, and often good luck. Over the last several decades, scientists made important fundamental and technological advances that made possible the control of some desirable properties of charged and neutral superfluids, which can now be used in medical imaging, levitating trains, submarine propulsion, generators, gyroscopes and space applications.  Calibri;mso-fareast-theme-font:minor-latin;mso-hansi-theme-font:minor-latin;
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Do you think Physics is only about stars and mad scientists? Come to this event and you will discover a new Physics world where fundamental physics knowledge is used “as simply as possible but not simpler” to build atom by atom the technology of future.  Come and learn how we make the smallest electronic circuits in the world, how we can build devices that power your cell phone while you walk in the streets, or how we pull single DNA molecules to understand the secrets of life.

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Rhythms abound in the natural world. Spontaneous rhythmic coordination can be essential: our beating heart cells must synchronize precisely – or else! Sometimes, too much coordination is disastrous: brain seizures can occur as a result of abnormally high levels of synchronous neuronal activity. Examples of spontaneous synchronization are found in every branch of science, from the beautiful nightly light shows of firefly swarms to the synchronized swinging of pendulum clocks. Researchers the world over are trying to understand how coordinated rhythms arise and trying to discover ways to control them. An array of applications awaits: faster computers, brighter lasers, collision- avoiding cars; new strategies for treating heart and brain disorders; even an end to the devastation of periodic locust swarms.

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In recent years, experiments with ultracold atoms [1,2,3,4] have investigated transport properties of one-dimensional (1D) Bose gases in optical lattices and shown that the transport in 1D is drastically suppressed even in the superfluid state compared to that in higher dimensions. Motivated by the experiments, we study superfluid transport of 1D Bose gases. In 1D, superflow at zero temperature can decay via quantum nucleation of phase slips even when the flow velocity is much smaller than the critical velocity predicted by mean-field theories. Using instanton techniques, we calculate the nucleation rate \Gamma_{prd} of a quantum phase slip for a 1D superfluid in a periodic potential and show that it increases in a power-law with the flow momentum p, as \Gamma_{prd} ~ p^{2K-2}, when p is much smaller than the critical momentum [5]. Here, L and K denote the system size and the Luttinger parameter. To make a connection with the experiments, we simulate the dipole oscillations of 1D Bose gases in the presence of a trapping potential with use of the quasi-exact numerical method of time-evolving block decimation. From the simulations, we relate the nucleation rate with the damping rate of dipole oscillations, which is a typical experimental observable [1,3], and show that the damping rate indeed obeys the power-law, meaning that the suppression of the transport in 1D is due to quantum phase slips.  We also suggest a way to identify the superfluid-insulator transition point from the dipole oscillations.

 

References:

[1] C. D. Fertig et al., Phys. Rev. Lett. 94, 120403 (2005).

[2] J. Mun et al., Phys. Rev. Lett. 99, 150604 (2007).

[3] E. Haller et al., Nature 466, 597 (2010).

[4] B. Gadway et al., Phys. Rev. Lett. 107, 145306 (2011).

[5] I. Danshita and A. Polkovnikov, Phys. Rev. A 85, 023638 (2012).

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