Integrated Calendar

MONTHLY SEMINAR ON SYSTEMS BIOLOGY
CO-SPONSORED BY THE CENTER FOR SYSTEMS BIOLOGY and BigRoc

Social interactions and learning in single neurons of the primate amygdala
Uri Livneh Dept of Neurobiology
Social interactions are a hallmark of primate evolution, yet the brain mechanisms that underlie these processes remain vague. These social interactions underlie the basis for emotions and learning of emotional stimuli by observation of facial expressions. We developed a model for emotional learning in non-human primates and show how neurons in the amygdala acquire and retain this information. We then developed a model for social interactions, by seating two monkeys facing one another and recording neural activity during different facial interactions. Finally, we suggest to expand and to combine the two models by investigating learning of emotional stimuli by observation of facial information.

Prediction of microRNA targets by functional distinction between changes in pre-mRNA and mRNA abundance
Natali Molotski Dept of Biological Chemistry
Amit Zeisel Dept of Physics of Complex Systems
MicroRNAs are noncoding, ~21 nucleotide-long RNAs that regulate tissue morphogenesis and homeostasis in animals and plants by effecting the stability of their target mRNAs. Here we propose a simple method for identifying functional microRNA targets and distinguishing
direct from indirect targets based on genome-wide differential analysis of microRNA- mediated changes in the levels of exons (mRNA) versus introns (pre-mRNA).

Servant of two masters: Design-principles of immune cell circuits that employ pleiotropic signals
Yuval Hart Dept of Molecular Cell Biology
While design principles of molecular control circuits in gene and metabolic networks are well studied, much less is known on control circuits of communicating cells. We aim to study models of immune circuits in which a few cell types interact by means of signalling molecules. Interestingly, these interactions are characterized by pleiotropic signals, meaning ligands with dual (and even paradoxical) role in the circuit.

I will discuss a new approach that enables strong, coherent coupling
between a single electronic spin qubit associated with a nitrogen-vacancy (NV) impurity in diamond and the motion of a magnetized nano-mechanical resonator. Specifically, I describe and experimentally demonstrate a novel method for the detection of mechanical motion using a single NV center.
The method utilizes nanoscale magnetic sensing of the a.c. magnetic field created by resonator motion to detect both the driven and Brownian motion of an MFM cantilever at room temperature. Potential applications of this approach to the realization of quantum spin transducers based on nano-electro-mechanical resonators are discussed.

EMT was first recognized as a distinct process in embryonic development and describes the process whereby epithelial cells lose epithelial properties and undergo changes to acquire mesenchymal characteristics to become migratory and invasive. This concept has been applied to a SIMILAR process that occurs in cancer progression that enables metastasis. Applying our knowledge of EMT to explain metastasis is an attempt to better understand the phenomenon of metastasis. However, cancer cells that undergo an apparent EMT do not all metastasize. Metastasis may occur in a way that looks like EMT but in fact involves other or additional mechanisms not involved in EMT. By confining our search for the causes of metastasis to the field of EMT, we narrow the field of our understanding.

One of the most efficient ways to treat interacting many-body systems in one-dimension is to

express its low-lying dynamics as excitations of a bosonic field. The paradigm is that bosonizing interacting electrons,

described in terms of Luttinger liquids, leads to a quadratic Hamiltonian which can be solved exactly.

When the many-body system is driven out of equilibrium, bosonization will give rise to a quadratic

bosonic Hamiltonian, but the ensuing action will not be quadratic—the paradigm is broken. What can be done

then? I will describe how the problem ( a large class of out-of-equilibrium systems) is essentially solved , and how the underlying physics is connected

to concepts at the core of quantum solid state: Fermi edge singularity, counting statistics, electron fractionalization etc.