Joel Stavans

Stochastic Turing patterns in the development of a one-dimensional organism

Cells having the same genetic information can behave very differently, due to inevitable stochastic fluctuations in gene expression, known as noise. How do cells in multicellular organisms achieve high precision in their developmental fate in the presence of noise, in order to reap the benefits of division of labor? We address this fundamental question from Systems Biology and Statistical Physics perspectives, with Anabaena cyanobacterial filaments as a model system, one of the earliest examples of multicellular organisms in Nature. These filaments can form one-dimensional, nearly-regular patterns of cells of two types. The developmental program uses tightly regulated, non-linear processes that include activation, inhibition, and transport, in order to create spatial and temporal patterns of gene expression that we can follow in real time, at the level of individual cells. We study cellular decisions, properties of the genetic network behind pattern formation, and establish the spatial extent to which gene expression is correlated along filaments. Motivated by our experimental results, I will show that pattern formation in Anabaena can be described theoretically by a minimal, three-component model that exhibits a deterministic, diffusion-driven Turing instability in a small region of parameter space. Furthermore, I will discuss how noise can enhance considerably the robustness of the developmental program, by promoting the formation of stochastic patterns in regions of parameter space for which deterministic patterns do not form, suggesting a novel, much more robust mechanism for pattern formation in this and other systems.

Luis Amaral

Cultural Shock: Some vignettes in the life of a physicist studying biological phenomena

A critical aspect of the training of many physicists concerns the realization that the study of many phenomena can require an understanding of mechanisms relevant at different time and length scales. Biological phenomena are clearly a domain in which multiple time and length scales are critical. Biology extends all the way from the level of chemical reactions to the level of the emergence of new species. Remarkably, current biology has almost singly focused on the molecular to cellular level. In this talk, I will provide a couple of short vignettes illustrating how the lack of higher systems-level perspective had result in surprising outcomes.

Francois M. Peeters

Extraordinary properties of confined water

Water adsorbed in nanopores exhibits anomalous properties including fast flow in nanochannels, distinct melting points, structural phase transitions, layering, and ultra-low dielectric constant. In confining geometries, the polarization of water is different from bulk water which affects the water-mediated intermolecular forces and consequently changes hydration and solvation, as well as molecular transport properties.

Water confined between two layers with a separation of a few Angstrom forms a layered two-dimensional ice structure. Using large scale molecular dynamics simulations with the adoptable ReaxFF interatomic potential we found that monolayer ice with a rhombic-square structure nucleates between graphene layers which is non-polar and non-ferroelectric. We provide different energetic considerations and H-bonding results that explain the inter-layer and intra-layer properties of two-dimensional ice. The controversional AA-stacking found experimentally [G. Algara-Siller et al. Nature 519, 443445 (2015)] is discussed in light of our minimum energy crystal structure of bilayer ice. Furthermore, we predict that odd-number of layers of ice has the same lattice structure as monolayer ice, while even number of ice layers exhibit the square ice AA-stacking of bilayer ice.We predict that an in-plane electric field polarizes the water molecules resulting in distinct-ferroelectricity. Electrical hysteresis in the response of the total dipole moment of monolayer ice is found.

The rate of water flow through hydrophobic nanocapillaries is greatly enhanced as compared to that expected from macroscopic hydrodynamics. This phenomenon is usually described in terms of a relatively large slip length, which is in turn defined by such microscopic properties as the friction between water and capillary surfaces, and the viscosity of water. We show that the viscosity of water and, therefore, its flow rate are profoundly affected by the layered structure of confined water if the capillary size becomes less than 2 nm. To this end we study the structure and dynamics of water confined between two parallel graphene layers using equilibrium molecular dynamics simulations. We find that the shear viscosity is not only greatly enhanced for subnanometer capillaries, but also exhibits large oscillations that originate from commensurability between the capillary size and the size of water molecules. Such oscillating behavior of viscosity and, consequently, the slip length should be taken into account in designing and studying graphene-based and similar membranes for desalination and filtration.

The dielectric properties of confined water in channels is a subject of recent experimental and theoretical interest which is still controversial. For water confined in channels with heights smaller than h=8Å, we found an extraordinary decrease in the out-of-plane dielectric constant down to the limit of the dielectric constant of optical water. Spatial resolved polarization density data obtained from molecular dynamics simulations (MDS) are found to be anti-symmetric across the channel and are used as input in a mean field model for the dielectric constant as function of the height of the channel for h > 15Å. This asymmetry in spatial polarization density turns out to be crucial to understand the recent experimental data of the of out-of-plane dielectric constant of confined water [L. Fumagalli et al, Science 360, 1339 (2018)].

Erel Levine

Applications of graph neural networks to biological systems at different scales

It has long been realized that many biological systems can be described in terms of interaction networks. However, in many cases it is not clear how to practically use this framework to extract knowledge from complex large-scale experimental data. This may be because a network is only inferred at low confidence, because a network is extremely dense, or because the network nature of a problem is not transparent. In this talk I will describe the use of graph neural networks to address such issues in two problems at very different scale: a microbial gene network that controls an intestinal infection, and a graph structure of a bacterial small RNA.

Jorge Amin Seman Harutinian

Exploring fermionic superfluidity in Mexico: advances and perspectives

During the last decades, quantum gases have become a very active field of research. These systems represent an excellent scenario to study macroscopic quantum phenomena, such as superfluidity, Bose-Einstein condensation and collective quantum excitations. At the same time, thanks to the extraordinary degree of control that ultracold atoms offer, they have been used as ideal quantum simulators of many-body and condensed matter systems.

The case of ultra-cold fermions is especially interesting thanks to the possibility of creating atomic pairs by means of magnetic Feshbach resonances, giving the possibility of creating different superfluid regimes across the BEC-BCS crossover.

Very recently, at the Institute of Physics of the UNAM, we have created for the first time in Mexico ultracold quantum samples using fermionic atoms of Lithium-6. In this talk I will give a general overview of our experimental setup and the techniques used to produce these ultracold systems, with special emphasis on the generation of different superfluid states.

Later I will discuss the future perspectives of our laboratory giving details about some of the experiments that we are currently conducting in the generation and study of collective excitations and their temporal evolution.

Pablo Meyer Rojas

Interpretable models in biology: enzymatic reactions, cell death and psychophysics of olfaction

I am overall interested in how events at the molecular level and gene circuits determine mesoscopic or higher order phenomena in biology. The advent of large datasets has led to a proliferation of computational pipelines to analyze and predict biological phenomena, however the resulting models do not always include or advance the biological knowledge per se.

Citing three recent projects in my lab, I will try to exemplify how to push for interpretable models in biology. The first one consists of the analysis of trajectories of a condensate of enzymes inside a bacteria and its resulting phenotypes. The second describes how mitochondria determine the fraction of human cells prone to dying and lastly I will exemplify how an ML model can lead to new biological interpretations of human olfaction.

Jesús Carlos Ruiz Suárez

The anesthetic effect of xenon: in vivo and in silico

Plenty of molecules are employed in the medical practice to induce general anesthesia. The consensus among biologists and neuroscientists is that general anesthetics inhibit NMDA calcium channels by antagonizing the function of the neurotransmitter glycine. Yet, an important question remains: how this antagonism takes place if after all, anesthetics, due to their hydrophobic character, are not ligands in hydrophilic targets? During the last several years our group has been committed to understand this interesting riddle, perhaps with the naive view that it can be solved by physics (statistical physics, indeed) instead of using a pharmaceutical approach. As a model system, we use a chemically inert gas: xenon (Xe). Surprisingly, Xe is not only the simplest of all anesthetics but considered the anesthetic of the 21 century. Experimentally, we work with Daphnia magna, very small crustaceans with primitive brains. We built a device to observe the organisms under Xe pressure and assess how they respond to anesthesia. Thereafter, we carry out Molecular Dynamic Simulations to investigate the effects these atoms produce on lipid rafts –lipid phases where putative proteins involved in neurotransmission are believed to be anchored-.

Aurora Hernández Machado

Dynamic Wetting of Fluids at the Microscale: Drop Emission, Inertia and Microstructured Surface Effects

Controlling the advancement of fluids at the microscale is essential to successfully developed drop-producing microdevices. Drops in microfluidics could be used for drug delivery, cell carrier encapsulation and even logical bits manipulation. At these small scales surface to volume ratios are very large and capillary and wetting forces play a crucial role. We will describe wetting-induced fluid entrainment by advancing contact lines on surfaces by means of a phase-field mathematical model and experimentally. The destabilization mechanism leads to the periodic emission of droplets [1, 2]. A new phenomenon that we dub superconfinement will be discussed [3]. We will also study enhanced imbibitions by pulsatile forcing [4] and effects of microstructured surfaces in the front advancement [5].

[1] R. Ledesma-Aguilar, R. Nistal, A. Hernandez-Machado and I. Pagonabarraga, “Controlled drop emission by wetting properties in driven liquid filaments”, Nature Materials, Vol. 10, 367 (2011).

[2] R. Ledesma-Aguilar, A. Hernandez-Machado and I. Pagonabarraga “Theory of wetting-induced fluid entrainment by advancing contact lines on dry surfaces”, Physical Review Letters, Vol. 110, 264502 (2013).

[3] S.A. Setu, R.P.A. Dullens, A. Hernandez-Machado, I. Pagonabarraga, D.G.A.L. Aarts and R. Ledesma-Aguilar, “Superconfinement tailors fluid flow at microscales”, Nature Communications, Vol. 6,7297 (2015).

[4] J. Flores-Geronimo, A. Hernandez-Machado and E. Corvera Poire, “Enhanced imbibition from the cooperation between wetting and inertia via pulsatile forcing”, Phys. of Fluids, 31, 032107 (2019)

[5] I. Dominguez-Roman, R.A. Barrio and A. Hernandez-Machado, “Long lasting frictionless fluid fronts in hydrophilic structured microchannels”, Preprint (2019).

Rosario Moctezuma

Brownian motion in a granular two dimensional system

The understanding of non-equilibrium processes such as the slowing down of structural relaxations in a fluid as it is cooling down has been of interest for several decades. However, a direct microscopic description face complex and challenging technological problems, for instance, the time resolution and the capacity of tracking each particle involves high technology not yet developed. Here, we use a granular matter system, which serves as a macroscopic model for atomic and colloidal systems in the absence of hydrodynamics. In this system, the source of kinetic energy is an external magnetic field which maintains it in a dynamic steady state. We found that this system presents characteristics of Brownian motion, which can be described by the Ornstein-Uhlenbeck stochastic process model. We explore the dynamical and structural properties of the system when it is quenched at different cooling rates, taking it from a gas-like configuration to a glass-like or crystalline structure. The method introduced here to provide kinetic energy to the particles will allow us to explore a wide variety of possibilities which will serve as a guide to understand different phenomena in colloidal and atomic systems.

Yasmín A. Ríos-Solís

A surreal complex system: urban transport in Mexico

A transportation network is a perfect example of a complex system since it is composed of many components (lines, timetables, vehicles, drivers, users, traffic) which interact with each other. As any other complex system, its behavior is intrinsically difficult to model due to the dependencies, competitions, and the environment. Now, imagine the complexity of the surreal Mexican transport system!

The optimization of urban transport is a prolific research area that involves combinatorial optimization, artificial intelligence, big data and statistics. Since there are already many mathematical models for urban transport, the first thing that comes to mind is to implement in Mexico the models used by first world countries such as England, Netherlands or Germany. However, on repeated occasions we have seen that the tropicalization of these models fails flatly. Thus, new mathematical models and methodologies are needed for “flexible” transport networks such as the Mexican or the Latin American ones.

Clare McCabe

Understanding the Self-Assembly of Skin Lipids from Molecular Dynamics Simulations: A Multiscale Perspective

The outermost layer of the skin (the stratum corneum) consists of skin cells embedded in a rich lipid matrix, whose primary role is to provide a barrier to foreign agents entering the body and to water leaving the body. This lipid system is unique in biological membranes in that it is composed of ceramides, cholesterol, and free fatty acids, with phospholipids, which are the major components of most biological membranes, being completely absent. This unique composition enables the lipids of the stratum corneum form highly organized lamella, which in turn are believed to control barrier function. While much is known about the nature of the skin lipids from extensive experimental studies, a clear understanding of how and why these molecules assemble into the structures observed through microscopy and biophysical measurements does not yet exist. In order to probe lipid phase behavior and molecular level arrangement, we are performing molecular simulations with both atomistic and coarse-grained models of key stratum corneum lipids and water. The development and validation of the coarse-grained models will be presented alongside the results of simulation studies for simple mixed lipid systems that provide insight into the lamellar organization and enable us to validate the models developed while working towards the study of more complex stratum corneum systems.

Juan Rubén Gómez Solano

Self-propelled particles in complex fluids

Active particles, such as motile microorganisms, are soft matter systems of great current interest due to their ability to convert energy from their liquid surroundings into self-propelled motion [1]. In contrast to passive Brownian particles, directional motion plays a primordial role for such active systems, since their propulsion is strongly determined by a well-defined orientation. In addition, their natural habitat is often complex not only in geometrical aspects, but also because the fluid environment, due to presence of colloids and macromolecules, exhibits non-Newtonian behavior, thus resulting in a plethora of non-equilibrium effects ranging from intricate swimming patterns to emergent phenomena, which are absent under thermal equilibrium conditions [2].

Recently, these out-of-equilibrium systems have attracted tremendous interest in various scientific communities to design their artificial counterparts, which are able to mimic autonomous biolocomotion. Here, I will present some experiments with colloidal microswimmers moving in viscoelastic media, such as polymer solutions [3,4], dense colloidal suspensions [5], and under various geometrical constraints [6]. Self-propulsion of the particles is achieved by local demixing of a critical binary mixture induced by laser illumination [7]. We observe a number of novel effects without counterpart in Newtonian fluids, such as a pronounced enhancement of rotational diffusion with increasing propulsion velocity, as well as the emergence of persistent rotational motion of individual self-propelled particles and collective behavior of confined multiparticle active systems. Such unexpected phenomena originate from a strong coupling between the orientation of the active particle and the slow mechanical response of the surrounding medium, which can be well described by simple effective models. In particular, our results suggest that self-propelled particles can be employed as probes for the micromechanical characterization of complex materials.

[1] C. Bechinger, R. Di Leonardo, H. Löwen, C. Reichhardt, G. Volpe, and G. Volpe, Rev. Mod. Phys. 88, 045006 (2016).

[2] E. Fodor and M C. Marchetti, Physica A 504, 106 (2018).

[3] J. R. Gomez-Solano, A. Blokhuis, and C. Bechinger, Phys. Rev. Lett. 116, 138301 (2016).

[4] N Narinder, C. Bechinger, and J. R. Gomez-Solano, Phys. Rev. Lett. 121, 078003 (2018).

[5] C. Lozano, J. R. Gomez-Solano, C. Bechinger, Nature Materials (2019).

[6] J. R. Gomez-Solano, S. Samin, C. Lozano, P. Ruedas-Batuecas, R. van Roij, and C. Bechinger, Sci. Rep. 7, 14891 (2017).

[7] N Narinder, J. R. Gomez-Solano, and C. Bechinger, New J. Phys. (accepted 2019).

Rafael Barrio Paredes

Quantification of the morphological characteristics of Human Embryonic Stem Cell Colonies

The maintenance of the pluripotent state in human embryonic stem cells (hESCs) is highly crucial for their application in the laboratory as a tool for drug testing and the study of cell based therapies. In this work we detect the self-organization of the cells in the colonies using tools from granular media, through their segregation in terms of their nucleus sizes. Our results suggests that newly divided (smallest cells) cluster together in patches separated from larger cells at the final stages of the cell cycle. This must influence directly the clonality and community effects within the colonies, since the segregation induced by size differences allows the continuous interchange of neighbours as the cells grow and divide.

Pavel Castro Villarreal

Stochastic curvature of enclosed semiflexible polymers

The conformational states of a semiflexible polymer enclosed in a compact domain of typical size a are studied as stochastic realizations of paths defined by the Frenet equations under the assumption that stochastic “curvature” satisfies a white noise fluctuation theorem. This approach allows us to derive the Hermans-Ullman equation, where we exploit a multipolar decomposition that allows us to show that the positional probability density function is well described by a telegrapher’s equation whenever 2a/l_p > 1, where l_p is the persistence length. We also develop a Monte Carlo algorithm for use in computer simulations in order to study the conformational states in a compact domain. In addition, the case of a semiflexible polymer enclosed in a square domain of side a is presented as an explicit example of the formulated theory and algorithm. In this case, we show the existence of a polymer shape transition similar to the one found by Spakowitz and Wang [Phys. Rev. Lett. 91, 166102 (2003)] where in this case the critical persistence length is l^∗_p ≃ a/8 such that the mean-square end-to-end distance exhibits an oscillating behavior for values l_p > l^∗_p, whereas for l_p < l^∗_p it behaves monotonically increasing. Finally, our approach can be extended in various directions. For instance, the whole formulation can be extended easily to semiflexible polymers in three dimensions. In addition, the approach developed here can also be extended to the case where the semiflexible polymer wraps a curved surface.

Pavel Castro-Villarreal and J. E. Ramírez Phys. Rev. E 100, 012503 (2019)

David P. Sanders

Introduction to Julia for statistical physics

I give an introduction to the modern programming language Julia (www.julialang.org), and show how it may be used for simulations in statistical physics. I will show how to think about code and structure it using types, objects and multiple dispatch.

You will need some basic programming knowledge, but no prior experience with Julia is necessary.