Time-based Chern number in periodically driven systems in the adiabatic limit

To define the topology of driven systems, recent works have proposed synthetic dimensions as a way to uncover the underlying parameter space of topological invariants. Using time as a synthetic dimension, together with a momentum dimension, gives access to a synthetic two-dimensional (2D) Chern number. It is, however, still unclear how the synthetic 2D Chern number is related to the Chern number that is defined from a parametric variable that evolves with time. Here we show that in periodically driven systems in the adiabatic limit, the synthetic 2D Chern number is a multiple of the Chern number defined from the parametric variable. The synthetic 2D Chern number can thus be engineered via how the parametric variable evolves in its own space. We justify our claims by investigating Thouless pumping in two one-dimensional (1D) tight-binding models, a three-site chain model, and a two-1D-sliding-chains model. The present findings could be extended to higher dimensions and other periodically driven configurations

Interaction and filling induced quantum phases of dual Mott insulators of bosons and fermions

Many-body effects are at the very heart of diverse phenomena found in condensed-matter physics. One striking example is the Mott insulator phase where conductivity is suppressed as a result of a strong repulsive interaction. Advances in cold atom physics have led to the realization of the Mott insulating phases of atoms in an optical lattice, mimicking the corresponding condensed matter systems. Here, we explore an exotic strongly-correlated system of Interacting Dual Mott Insulators of bosons and fermions. We reveal that an inter-species interaction between bosons and fermions drastically modifies each Mott insulator, causing effects that include melting, generation of composite particles, an anti-correlated phase, and complete phase-separation. Comparisons between the experimental results and numerical simulations indicate intrinsic adiabatic heating and cooling for the attractively and repulsively interacting dual Mott Insulators, respectively

Development of an AAV-based microRNA gene therapy to treat Machado-Joseph disease

Spinocerebellar ataxia type 3 (SCA3) or Machado-Joseph disease (MJD) is a progressiveneurodegenerative disorder caused by a CAG expansion in the ATXN3 gene. The expanded CAGrepeat is translated into a prolonged polyglutamine repeat in the ataxin-3 protein and accumulateswithin inclusions, acquiring toxic properties, which results in degeneration of the cerebellum and brainstem.In the current study, a non-allele specific ATXN3 silencing approach was investigated using artificialmicroRNAs engineered to target various regions of the ATXN3 gene (miATXN3). The miATXN3candidates were screened in vitro based on their silencing efficacy on a luciferase reporter co-expressing ATXN3. The three best miATXN3 candidates were further tested for target engagement andpotential off-target activity in induced-pluripotent stem cells (iPSC) differentiated into frontal brain-like neurons and in a SCA3 knock-in mouse model. Besides a strong reduction of ATXN3 mRNA andprotein, small RNA sequencing revealed efficient guide strand processing without passenger strandsbeing produced. We used different methods to predict alteration of off-target genes upon AAV5-miATXN3 treatment and found no evidence for unwanted effects. Furthermore, we demonstrated in alarge animal model, the minipig, that intrathecal delivery of AAV5 can transduce the main areasaffected in SCA3 patients. These results proved a strong basis to move forward to investigatedistribution, efficacy and safety of AAV5-miATXN3 in large animals.</p

Dynamical Mean-Field Theory

The dynamical mean-field theory (DMFT) is a widely applicable approximation scheme for the investigation of correlated quantum many-particle systems on a lattice, e.g., electrons in solids and cold atoms in optical lattices. In particular, the combination of the DMFT with conventional methods for the calculation of electronic band structures has led to a powerful numerical approach which allows one to explore the properties of correlated materials. In this introductory article we discuss the foundations of the DMFT, derive the underlying self-consistency equations, and present several applications which have provided important insights into the properties of correlated matter.Comment: Chapter in "Theoretical Methods for Strongly Correlated Systems", edited by A. Avella and F. Mancini, Springer (2011), 31 pages, 5 figure

PirB regulates a structural substrate for cortical plasticity

Experience-driven circuit changes underlie learning and memory. Monocular deprivation (MD) engages synaptic mechanisms of ocular dominance (OD) plasticity and generates robust increases in dendritic spine density on L5 pyramidal neurons. Here we show that the paired immunoglobulin-like receptor B (PirB) negatively regulates spine density, as well as the threshold for adult OD plasticity. In PirB(-/-) mice, spine density and stability are significantly greater than WT, associated with higher-frequency miniature synaptic currents, larger long-term potentiation, and deficient long-term depression. Although MD generates the expected increase in spine density in WT, in PirB(-/-) this increase is occluded. In adult PirB(-/-), OD plasticity is larger and more rapid than in WT, consistent with the maintenance of elevated spine density. Thus, PirB normally regulates spine and excitatory synapse density and consequently the threshold for new learning throughout life

A Unique Radiation Scheme for the Treatment of High-Grade Non-Metastatic Soft Tissue Sarcoma: The Detroit Medical Center Experience

Purpose:This is the initial report on the utilization of combined photon irradiation followed by a neutron boost irradiation for the initial management of patients with high-grade non-metastatic soft tissue sarcoma (STS). We present data on local control, complications, disease-free survival and overall survival in patients at high risk for local relapse

Extensive microbial and functional diversity within the chicken cecal microbiome

Chickens are major source of food and protein worldwide. Feed conversion and the health of chickens relies on the largely unexplored complex microbial community that inhabits the chicken gut, including the ceca. We have carried out deep microbial community profiling of the microbiota in twenty cecal samples via 16S rRNA gene sequences and an in-depth metagenomics analysis of a single cecal microbiota. We recovered 699 phylotypes, over half of which appear to represent previously unknown species. We obtained 648,251 environmental gene tags (EGTs), the majority of which represent new species. These were binned into over two-dozen draft genomes, which included Campylobacter jejuni and Helicobacter pullorum. We found numerous polysaccharide- and oligosaccharide-degrading enzymes encoding within the metagenome, some of which appeared to be part of polysaccharide utilization systems with genetic evidence for the co-ordination of polysaccharide degradation with sugar transport and utilization. The cecal metagenome encodes several fermentation pathways leading to the production of short-chain fatty acids, including some with novel features. We found a dozen uptake hydrogenases encoded in the metagenome and speculate that these provide major hydrogen sinks within this microbial community and might explain the high abundance of several genera within this microbiome, including Campylobacter, Helicobacter and Megamonas