לוח שנה משולב

The assembly of artificial cells capable of executing DNA programs has been an important goal for basic research and technology. We assemble 2D DNA compartments fabricated in silicon as ‘artificial cells’ capable of metabolism, programmable protein synthesis, and communication. We programmed gene expression cycles in separate compartments, as well as protein synthesis fronts propagating in a coupled 1D system of compartments. Gene expression in the DNA compartments reveals a rich, dynamic system that is controlled by geometry. The organization of matter in the compartment suggested conditions for controlled assembly of biological machines. This puts forth a man-made biological system with programmable information processing from the gene to a ‘cell’, and up to the ‘multicellular’ scale.


References:

A. Tayar, E. Karzbrun, V. Noireaux, R.H. Bar-Ziv, Propagating gene expression fronts in a one-dimensional coupled system of artificial cells. Nature Phys. 11, 1037–1041 (2015).
E. Karzbrun, A. M. Tayar, V. Noireaux, R.H. Bar-Ziv, Programmable on-chip DNA compartments as artificial cells. Science. 345, 829–832 (2014).
D. Bracha, E. Karzbrun, G. Shemer, P. A. Pincus, R.H. Bar-Ziv, Entropy-driven collective interactions in DNA brushes on a biochip. Proc. Natl. Acad. Sci. U. S. A. 110, 4534–8 (2013).
Y. Heyman, A. Buxboim, S. G. Wolf, S. S. Daube, R.H. Bar-Ziv, Cell-free protein synthesis and assembly on a biochip. Nature Nanotech. 7, 374–378 (2012).

The nature of the large-scale flow below the cloud level on Jupiter is still unknown. The observed surface wind might be confined to the upper layers, or be a manifestation of deep cylindrical flow. Moreover, it is possible that in the case where the observed wind is superficial, there exists deep flow that is completely separated from the surface. During the years 2016-17 Juno will both perform close flybys of Jupiter, obtaining a high precision gravity spectrum for the planet. This data can be used to estimate the depth of Jupiter observed cloud-level wind, and decipher a possible deep flow that is decoupled from the surface wind. In this talk I will discuss the Juno gravity experiment and the possible outcomes with regard to the flow on Jupiter.

We explore the possibility of complex wind dynamics that include both the upper-layer wind, and a deep flow that is completely detached from the flow above it. The surface flow is based on the observed cloud-level flow and is set to decay with depth. The deep flow is constructed synthetically to produce cylindrical structures with variable width and magnitude, thus allowing for a wide range of possible setups of the unknown deep flow. The combined 3D flow is then related to the density anomalies via a dynamical model and the resulting density field is then used to calculate the gravitational moments. An adjoint inverse model is constructed for the dynamical model, thus allowing backward integration of the dynamical model, from the expected observations of the gravity moments to the parameters controlling the setup of the deep and surface flows.

We show that the model can be used for examination of various scenarios, including cases in which the deep flow is dominating over the surface wind. The novelty of our adjoint based inversion approach is in the ability to identify complex dynamics including deep cylindrical flows that have no manifestation in the observed cloud-level wind. Furthermore, the flexibility of the adjoint method allows for a wide range of dynamical setups, so that when new observations and physical understanding will arise, these constraints could be easily implemented and used to better decipher Jupiter flow dynamics.

Cells of the immune system cooperate their activity by secreting small proteins – cytokines.
The cytokines binding to their receptors on a receiving cell causes a chain of signaling events that determine the fate of the cell: its survival, differentiation and proliferation. We argue that the competition between cytokine diffusion and
its consumption by a receiving cell sets a characteristic length that defines the spatial extent of cytokine communication.
On the example of interleukin-2 cytokine we demonstrate both in vitro and in vivo that the cytokine fields can be localized to the vicinity of the secreting cell, and we find that a simple diffusion/consumption mechanism provides an adequate explanation for such localization.

Machine technology frequently
puts magnetic or electrostatic
repulsive forces to practical use,
as in maglev trains, vehicle
suspensions or non-contact
bearings. In contrast, materials
design overwhelmingly focuses
on attractive interactions, such
as in the many advanced
polymer-based composites, where inorganic fillers interact with a polymer matrix to improve
mechanical properties. However, articular cartilage strikingly illustrates how electrostatic repulsion
can be harnessed to achieve unparalleled functional efficiency: it permits virtually frictionless
mechanical motion within joints, even under high compression. Here we describe a composite
hydrogel with anisotropic mechanical properties dominated by electrostatic repulsion between
negatively charged unilamellar titanate nanosheets embedded within it. Crucial to the behaviour of this
hydrogel is the serendipitous discovery of cofacial nanosheet alignment in aqueous colloidal
dispersions subjected to a strong magnetic field, which maximizes electrostatic repulsion6 and thereby
induces a quasi-crystalline structural ordering over macroscopic length scales and with uniformly
large face-to-face nanosheet separation. We fix this transiently induced structural order by
transforming the dispersion into a hydrogel using light-triggered in situ vinyl polymerization. The
resultant hydrogel, containing charged inorganic structures that align cofacially in a magnetic flux,
deforms easily under shear forces applied parallel to the embedded nanosheets yet resists compressive
forces applied orthogonally. We anticipate that the concept of embedding anisotropic repulsive
electrostatics within a composite material, inspired by articular cartilage, will open up new
possibilities for developing soft materials with unusual functions.

Resilience is a system's ability to cope with change, or to bounce back after stress. The loss of resilience in a natural system occurs when the stress exceeds a certain threshold, beyond which the system loses its ability to bounce back and retain proper functionality. For instance, when the loss of trees in a forest (deforestation) crosses a tipping point and the forest turns barren, or when the load on the electrical power grid becomes too high and a massive power failure emerges. The challenge is that most complex systems are multidimensional, disordered and described by nonlinear dynamics - characteristics that firmly avoid analytical treatment. We address this challenge by showing how to map a complex system into an effective one dimensional equation, exposing the universal patterns of resilience exhibited by diverse systems, from ecological to technological networks. Along the way we will understand why systems lose resilience all of a sudden, learn how to predict such resilience loss and show how to fortify a system to become more resilient.


J. Gao, B. Barzel, A-L Barabasi, Nature 530, 307 (2016).