Controlled Dephasing of Electrons by Non-Gaussian Shot Noise

In a 'controlled dephasing' experiment [1-3], an interferometer loses its coherence due to entanglement with a controlled quantum system ('which path' detector). In experiments that were conducted thus far in mesoscopic systems only partial dephasing was achieved. This was due to weak interactions between many detector electrons and the interfering electron, resulting in a Gaussian phase randomizing process [4-10]. Here, we report the opposite extreme: a complete destruction of the interference via strong phase randomization only by a few electrons in the detector. The realization was based on interfering edge channels (in the integer quantum Hall effect regime, filling factor 2) in a Mach-Zehnder electronic interferometer, with an inner edge channel serving as a detector. Unexpectedly, the visibility quenched in a periodic lobe-type form as the detector current increased; namely, it periodically decreased as the detector current, and thus the detector's efficiency, increased. Moreover, the visibility had a V-shape dependence on the partitioning of the detector current, and not the expected dependence on the second moment of the shot noise, T(1-T), with T the partitioning. We ascribe these unexpected features to the strong detector-interferometer coupling, allowing only 1-3 electrons in the detector to fully dephase the interfering electron. Consequently, in this work we explored the non-Gaussian nature of noise [11], namely, the direct effect of the shot noise full counting statistics [12-15].Comment: 14 pages, 4 figure

Analysis of optimal phenotypic space using elementary modes as applied to Corynebacterium glutamicum

BACKGROUND: Quantification of the metabolic network of an organism offers insights into possible ways of developing mutant strain for better productivity of an extracellular metabolite. The first step in this quantification is the enumeration of stoichiometries of all reactions occurring in a metabolic network. The structural details of the network in combination with experimentally observed accumulation rates of external metabolites can yield flux distribution at steady state. One such methodology for quantification is the use of elementary modes, which are minimal set of enzymes connecting external metabolites. Here, we have used a linear objective function subject to elementary modes as constraint to determine the fluxes in the metabolic network of Corynebacterium glutamicum. The feasible phenotypic space was evaluated at various combinations of oxygen and ammonia uptake rates. RESULTS: Quantification of the fluxes of the elementary modes in the metabolism of C. glutamicum was formulated as linear programming. The analysis demonstrated that the solution was dependent on the criteria of objective function when less than four accumulation rates of the external metabolites were considered. The analysis yielded feasible ranges of fluxes of elementary modes that satisfy the experimental accumulation rates. In C. glutamicum, the elementary modes relating to biomass synthesis through glycolysis and TCA cycle were predominantly operational in the initial growth phase. At a later time, the elementary modes contributing to lysine synthesis became active. The oxygen and ammonia uptake rates were shown to be bounded in the phenotypic space due to the stoichiometric constraint of the elementary modes. CONCLUSION: We have demonstrated the use of elementary modes and the linear programming to quantify a metabolic network. We have used the methodology to quantify the network of C. glutamicum, which evaluates the set of operational elementary modes at different phases of fermentation. The methodology was also used to determine the feasible solution space for a given set of substrate uptake rates under specific optimization criteria. Such an approach can be used to determine the optimality of the accumulation rates of any metabolite in a given network

The Interstellar Medium In Galaxies Seen A Billion Years After The Big Bang

Evolution in the measured rest frame ultraviolet spectral slope and ultraviolet to optical flux ratios indicate a rapid evolution in the dust obscuration of galaxies during the first 3 billion years of cosmic time (z>4). This evolution implies a change in the average interstellar medium properties, but the measurements are systematically uncertain due to untested assumptions, and the inability to measure heavily obscured regions of the galaxies. Previous attempts to directly measure the interstellar medium in normal galaxies at these redshifts have failed for a number of reasons with one notable exception. Here we report measurements of the [CII] gas and dust emission in 9 typical (~1-4L*) star-forming galaxies ~1 billon years after the big bang (z~5-6). We find these galaxies have >12x less thermal emission compared with similar systems ~2 billion years later, and enhanced [CII] emission relative to the far-infrared continuum, confirming a strong evolution in the interstellar medium properties in the early universe. The gas is distributed over scales of 1-8 kpc, and shows diverse dynamics within the sample. These results are consistent with early galaxies having significantly less dust than typical galaxies seen at z<3 and being comparable to local low-metallicity systems.Comment: Submitted to Nature, under review after referee report. 22 pages, 4 figures, 4 Extended Data Figures, 5 Extended Data table

Using a logical model to predict the growth of yeast

<p>Abstract</p> <p>Background</p> <p>A logical model of the known metabolic processes in <it>S. cerevisiae </it>was constructed from iFF708, an existing Flux Balance Analysis (FBA) model, and augmented with information from the KEGG online pathway database. The use of predicate logic as the knowledge representation for modelling enables an explicit representation of the structure of the metabolic network, and enables logical inference techniques to be used for model identification/improvement.</p> <p>Results</p> <p>Compared to the FBA model, the logical model has information on an additional 263 putative genes and 247 additional reactions. The correctness of this model was evaluated by comparison with iND750 (an updated FBA model closely related to iFF708) by evaluating the performance of both models on predicting empirical minimal medium growth data/essential gene listings.</p> <p>Conclusion</p> <p>ROC analysis and other statistical studies revealed that use of the simpler logical form and larger coverage results in no significant degradation of performance compared to iND750.</p

Single-Pair FRET Microscopy Reveals Mononucleosome Dynamics

We applied spFRET microscopy for direct observation of intranucleosomal DNA dynamics. Mononucleosomes, reconstituted with DNA containing a FRET pair at the dyad axis and exit of the nucleosome core particle, were immobilized through a 30 bp DNA tether on a polyethyleneglycol functionalized slide and visualized using Total Internal Reflection Fluorescence microscopy. FRET efficiency time-traces revealed two types of dynamics: acceptor blinking and intramolecular rearrangements. Both Cy5 and ATTO647N acceptor dyes showed severe blinking in a deoxygenated buffer in the presence of 2% βME. Replacing the triplet quencher βME with 1 mM Trolox eliminated most blinking effects. After suppression of blinking three subpopulations were observed: 90% appeared as dissociated complexes; the remaining 10% featured an average FRET efficiency in agreement with intact nucleosomes. In 97% of these intact nucleosomes no significant changes in FRET efficiency were observed in the experimentally accessible time window ranging from 10 ms to 10’s of seconds. However, 3% of the intact nucleosomes showed intervals with reduced FRET efficiency, clearly distinct from blinking, with a lifetime of 120 ms. These fluctuations can unambiguously be attributed to DNA breathing. Our findings illustrate not only the merits but also typical caveats encountered in single-molecule FRET studies on complex biological systems

Industrial Systems Biology of Saccharomyces cerevisiae Enables Novel Succinic Acid Cell Factory.

Saccharomyces cerevisiae is the most well characterized eukaryote, the preferred microbial cell factory for the largest industrial biotechnology product (bioethanol), and a robust commerically compatible scaffold to be exploitted for diverse chemical production. Succinic acid is a highly sought after added-value chemical for which there is no native pre-disposition for production and accmulation in S. cerevisiae. The genome-scale metabolic network reconstruction of S. cerevisiae enabled in silico gene deletion predictions using an evolutionary programming method to couple biomass and succinate production. Glycine and serine, both essential amino acids required for biomass formation, are formed from both glycolytic and TCA cycle intermediates. Succinate formation results from the isocitrate lyase catalyzed conversion of isocitrate, and from the alpha-keto-glutarate dehydrogenase catalyzed conversion of alpha-keto-glutarate. Succinate is subsequently depleted by the succinate dehydrogenase complex. The metabolic engineering strategy identified included deletion of the primary succinate consuming reaction, Sdh3p, and interruption of glycolysis derived serine by deletion of 3-phosphoglycerate dehydrogenase, Ser3p/Ser33p. Pursuing these targets, a multi-gene deletion strain was constructed, and directed evolution with selection used to identify a succinate producing mutant. Physiological characterization coupled with integrated data analysis of transcriptome data in the metabolically engineered strain were used to identify 2nd-round metabolic engineering targets. The resulting strain represents a 30-fold improvement in succinate titer, and a 43-fold improvement in succinate yield on biomass, with only a 2.8-fold decrease in the specific growth rate compared to the reference strain. Intuitive genetic targets for either over-expression or interruption of succinate producing or consuming pathways, respectively, do not lead to increased succinate. Rather, we demonstrate how systems biology tools coupled with directed evolution and selection allows non-intuitive, rapid and substantial re-direction of carbon fluxes in S. cerevisiae, and hence show proof of concept that this is a potentially attractive cell factory for over-producing different platform chemicals

IT-adoption and the interaction of task, technology and individuals: a fit framework and a case study

BACKGROUND: Factors of IT adoption have largely been discussed in the literature. However, existing frameworks (such as TAM or TTF) are failing to include one important aspect, the interaction between user and task. METHOD: Based on a literature study and a case study, we developed the FITT framework to help analyse the socio-organisational-technical factors that influence IT adoption in a health care setting. RESULTS: Our FITT framework ("Fit between Individuals, Task and Technology") is based on the idea that IT adoption in a clinical environment depends on the fit between the attributes of the individual users (e.g. computer anxiety, motivation), attributes of the technology (e.g. usability, functionality, performance), and attributes of the clinical tasks and processes (e.g. organisation, task complexity). We used this framework in the retrospective analysis of a three-year case study, describing the adoption of a nursing documentation system in various departments in a German University Hospital. We will show how the FITT framework helped analyzing the process of IT adoption during an IT implementation: we were able to describe every found IT adoption problem with regard to the three fit dimensions, and any intervention on the fit can be described with regard to the three objects of the FITT framework (individual, task, technology). We also derive facilitators and barriers to IT adoption of clinical information systems. CONCLUSION: This work should support a better understanding of the reasons for IT adoption failures and therefore enable better prepared and more successful IT introduction projects. We will discuss, however, that from a more epistemological point of view, it may be difficult or even impossible to analyse the complex and interacting factors that predict success or failure of IT projects in a socio-technical environment

Population Genetic Analysis Infers Migration Pathways of Phytophthora ramorum in US Nurseries

Recently introduced, exotic plant pathogens may exhibit low genetic diversity and be limited to clonal reproduction. However, rapidly mutating molecular markers such as microsatellites can reveal genetic variation within these populations and be used to model putative migration patterns. Phytophthora ramorum is the exotic pathogen, discovered in the late 1990s, that is responsible for sudden oak death in California forests and ramorum blight of common ornamentals. The nursery trade has moved this pathogen from source populations on the West Coast to locations across the United States, thus risking introduction to other native forests. We examined the genetic diversity of P. ramorum in United States nurseries by microsatellite genotyping 279 isolates collected from 19 states between 2004 and 2007. Of the three known P. ramorum clonal lineages, the most common and genetically diverse lineage in the sample was NA1. Two eastward migration pathways were revealed in the clustering of NA1 isolates into two groups, one containing isolates from Connecticut, Oregon, and Washington and the other isolates from California and the remaining states. This finding is consistent with trace forward analyses conducted by the US Department of Agriculture's Animal and Plant Health Inspection Service. At the same time, genetic diversities in several states equaled those observed in California, Oregon, and Washington and two-thirds of multilocus genotypes exhibited limited geographic distributions, indicating that mutation was common during or subsequent to migration. Together, these data suggest that migration, rapid mutation, and genetic drift all play a role in structuring the genetic diversity of P. ramorum in US nurseries. This work demonstrates that fast-evolving genetic markers can be used to examine the evolutionary processes acting on recently introduced pathogens and to infer their putative migration patterns, thus showing promise for the application of forensics to plant pathogens

Meningitic Escherichia coli K1 Penetration and Neutrophil Transmigration Across the Blood–Brain Barrier are Modulated by Alpha7 Nicotinic Receptor

Alpha7 nicotinic acetylcholine receptor (nAChR), an essential regulator of inflammation, is abundantly expressed in hippocampal neurons, which are vulnerable to bacterial meningitis. However, it is unknown whether α7 nAChR contributes to the regulation of these events. In this report, an aggravating role of α7 nAChR in host defense against meningitic E. coli infection was demonstrated by using α7-deficient (α7-/-) mouse brain microvascular endothelial cells (BMEC) and animal model systems. As shown in our in vitro and in vivo studies, E. coli K1 invasion and polymorphonuclear neutrophil (PMN) transmigration across the blood-brain barrier (BBB) were significantly reduced in α7-/- BMEC and α7-/- mice. Stimulation by nicotine was abolished in the α7-/- cells and animals. The same blocking effect was achieved by methyllycaconitine (α7 antagonist). The tight junction molecules occludin and ZO-1 were significantly reduced in the brain cortex of wildtype mice infected with E. coli and treated with nicotine, compared to α7-/- cells and animals. Decreased neuronal injury in the hippocampal dentate gyrus was observed in α7-/- mice with meningitis. Proinflammatory cytokines (IL-1β, IL-6, TNFα, MCP-1, MIP-1alpha, and RANTES) and adhesion molecules (CD44 and ICAM-1) were significantly reduced in the cerebrospinal fluids of the α7-/- mice with E. coli meningitis. Furthermore, α7 nAChR is the major calcium channel for nicotine- and E. coli K1-increased intracellular calcium concentrations of mouse BMEC. Taken together, our data suggest that α7 nAChR plays a detrimental role in the host defense against meningitic infection by modulation of pathogen invasion, PMN recruitment, calcium signaling and neuronal inflammation