Integrated Calendar

The Lindblad equation allows to explore general properties of open quantum systems. Whenever strong decoherence processes are present, one expects the system to become classical. Namely, the evolution of the surviving diagonal terms of the density matrix is Markovian. Surprisingly enough, many interesting aspects of the quantum system can be inferred from the classical limit. Among which we will explore some transport properties as well as a condensation transition for interacting quantum particles. Moreover, we will be interested in the quantum corrections to Fick’s law in diffusive systems

Information theory, originally developed for mathematical analysis of communication systems, has been applied to molecular biology for decades. In this context, the concept of entropy is utilized to measure the compositional complexity of genomes, wherein all of the hereditary information necessary to build and maintain an organism is stored. The recent explosion in the availability of genomic data, coupled with the considerable improvements in computational processing power, presents opportunities for investigating genomes far beyond the scope and depth previously achievable. In this work, we propose to characterize the informational properties of ~5000 genomes by assessing the statistical abundance and sequence space coverage of fixed-length substrings (known as ‘kmers’). Additionally, we aim to identify unique kmers that can be used as genome-specific markers for taxonomic profiling purposes.

The 100-year old Sabatier reaction, i.e. catalytic CO2 hydrogenation, is now seeing a renaissance due to its application in Power-to-Methane processes for electric grid stability and potential CO2 emission mitigation [1]. To date however, the fundamentals of this important catalytic reaction are still a matter of debate. This is partly due to the structure sensitive nature of CO2 hydrogenation: not all surface atoms of the active phase nanoparticles have the same specific activity. Recently, we have showed how the mechanism of catalytic CO2 methanation depends on Ni nanoparticle size using a unique set of well-defined silica-supported Ni nanoclusters (in the range 1-7 nm) and advanced characterization methods (i.e., operando FT-IR, and operando quick X-ray absorption spectroscopy) [2]. By utilizing fundamental theoretical concepts proving why CO2 is structure sensitive, and how CO2 is activated mechanistically and linking spectroscopic descriptors to these fundamental findings we ultimately leverage our understanding with a toolbox of structure sensitivity, and a library of reducible and non-reducible supports (SiO2, Al2O3, CeO2, ZrO2 and TiO2), tuning the selectivity and activity of methanation over Ni [3]. For example, we show that CO2 hydrogenation over Ni can and does form propane. This work contributes to our ability to produce “ideal” catalysts by improving the understanding of the catalytic sites and reaction pathways responsible for higher activity and even C-C coupling. This toolbox is thus not only useful for the highly active and selective production of methane within the Power-to-Methane concept, but also provides new insights for CO2 activation towards value-added chemicals thereby reducing the deleterious effects of this environmentally harmful molecule.

In this talk, I will review recent work by myself and others on Jewish population and medical genetics, focusing on Ashkenazi Jews (AJ). I will describe the mixture events of AJ in Europe, the founder event they have experienced in the late Middle Ages, and their connections to ancient populations of the Levant. I will then describe large-scale genomic databases that we have recently generated for AJ, and the opportunities they open in medical genetics given the unique AJ demographic history. I will describe a few medical genetics projects including carrier screening, genome-wide association studies of microbiome composition and other traits, and preimplantation genetic diagnosis.

Proteins are dynamic entities and function is often related to motions on time-scales from picoseconds to seconds. Understanding not only the backbone, but also the dynamics and interactions of side chains and ions within proteins is crucial, because side chains cover protein surfaces and are imperative for substrate recognition and both side chains and ions are key for most active sites in enzymes.
New NMR-based methods, anchored in 13C-direct-detection, to characterise the motions and interactions of functional side chains in large proteins will be presented. One class of experiments is aimed at arginine side chains and allows the strength of interactions formed via the guanidinium group to be quantified. NMR measurements of the solvent exchange rate of labile guanidinium protons as well as measurements of the rotational motion about the Nε-Cζ bond allows for such quantifications. Secondly, a new class of NMR experiments is presented, which relies on 13C-13C correlation spectra and allows a general quantification of motion and structure of side chains in large proteins. The new 13C-13C correlation spectra are applied to a 82 kDa protein, where well-resolved spectra with minimal overlap are obtained within a few hours.
NMR-based methods to characterise potassium binding in medium-large proteins will also be presented. Due to its size, 15N-ammonium can be used as a proxy for potassium to probe potassium binding in medium-large proteins. NMR pulse sequences will be presented to select specific spin density matrix elements of the 15NH4+ spin system and to measure their relaxation rates in order to characterise the rotational correlation time of protein-bound 15NH4+ as well as report on chemical exchange events of the 15NH4+ ion.