Dynamical correlations in electronic transport through a system of coupled quantum dots

Current auto- and cross-correlations are studied in a system of two capacitively coupled quantum dots. We are interested in a role of Coulomb interaction in dynamical correlations, which occur outside the Coulomb blockade region (for high bias). After decomposition of the current correlation functions into contributions between individual tunneling events, we can show which of them are relevant and lead to sub-/supper-Poissonian shot noise and negative/positive cross-correlations. The results are differentiated for a weak and strong inter-dot coupling. Interesting results are for the strong coupling case when electron transfer in one of the channel is strongly correlated with charge drag in the second channel. We show that cross-correlations are non-monotonic functions of bias voltage and they are in general negative (except some cases with asymmetric tunnel resistances). This is effect of local potential fluctuations correlated by Coulomb interaction, which mimics the Pauli exclusion principle

CMB Temperature Polarization Correlation and Primordial Gravitational Waves

We examine the use of the CMB's TE cross correlation power spectrum as a complementary test to detect primordial gravitational waves (PGWs). The first method used is based on the determination of the lowest multipole, $\ell_0$, where the TE power spectrum, $C_{\ell}^{TE}$, first changes sign. The second method uses Wiener filtering on the CMB TE data to remove the density perturbations contribution to the TE power spectrum. In principle this leaves only the contribution of PGWs. We examine two toy experiments (one ideal and another more realistic) to see their ability to constrain PGWs using the TE power spectrum alone. We found that an ideal experiment, one limited only by cosmic variance, can detect PGWs with a ratio of tensor to scalar metric perturbation power spectra $r=0.3$ at 99.9% confidence level using only the TE correlation. This value is comparable with current constraints obtained by WMAP based on the $2\sigma$ upper limits to the B-mode amplitude. We demonstrate that to measure PGWs by their contribution to the TE cross correlation power spectrum in a realistic ground based experiment when real instrumental noise is taken into account, the tensor-to-scalar ratio, $r$, should be approximately three times larger.Comment: 13 pages, 13 figures, version matches published version. Combined with 0710.365

Charge fluctuations and feedback effect in shot noise in a Y-terminal system

We investigate a dynamical Coulomb blockade effect and its role in the enhancement of current-current correlations in a three-terminal device with a multilevel splitter, as well as with two quantum dots. Spectral decomposition analysis shows that in the Y-terminal system with a two level ideal splitter, charge fluctuations at a level with a lowest outgoing tunneling rate are responsible for a super-Poissonian shot noise and positive cross-correlations. Interestingly, for larger source-drain voltages, electrons are transferred as independent particles, when three levels participate in transport, and double occupancy is allowed. We can explain compensation of the current correlations as the interplay between different bunching and antibunching processes by performing a spectral decomposition of the correlation functions for partial currents flowing through various levels. In the system with two quantum dots acting as a splitter, a long range feedback effect of fluctuating potentials leads to the dynamical Coulomb blockade and an enhancement of shot noise.Comment: 15 pages, 8 figure

Intranasal multivalent adenoviral-vectored vaccine protects against replicating and dormant M.tb in conventional and humanized mice

Viral-vectored vaccines are highly amenable for respiratory mucosal delivery as a means of inducing much-needed mucosal immunity at the point of pathogen entry. Unfortunately, current monovalent viral-vectored tuberculosis (TB) vaccine candidates have failed to demonstrate satisfactory clinical protective efficacy. As such, there is a need to develop next-generation viral-vectored TB vaccine strategies which incorporate both vaccine antigen design and delivery route. In this study, we have developed a trivalent chimpanzee adenoviral-vectored vaccine to provide protective immunity against pulmonary TB through targeting antigens linked to the three different growth phases (acute/chronic/dormancy) of Mycobacterium tuberculosis (M.tb) by expressing an acute replication-associated antigen, Ag85A, a chronically expressed virulence-associated antigen, TB10.4, and a dormancy/resuscitation-associated antigen, RpfB. Single-dose respiratory mucosal immunization with our trivalent vaccine induced robust, sustained tissue-resident multifunctional CD4(+) and CD8(+) T-cell responses within the lung tissues and airways, which were further quantitatively and qualitatively improved following boosting of subcutaneously BCG-primed hosts. Prophylactic and therapeutic immunization with this multivalent trivalent vaccine in conventional BALB/c mice provided significant protection against not only actively replicating M.tb bacilli but also dormant, non-replicating persisters. Importantly, when used as a booster, it also provided marked protection in the highly susceptible C3HeB/FeJ mice, and a single respiratory mucosal inoculation was capable of significant protection in a humanized mouse model. Our findings indicate the great potential of this next-generation TB vaccine strategy and support its further clinical development for both prophylactic and therapeutic applications.Immunogenetics and cellular immunology of bacterial infectious disease

A novel, fast, HMM-with-Duration implementation – for application with a new, pattern recognition informed, nanopore detector

<p>Abstract</p> <p>Background</p> <p>Hidden Markov Models (HMMs) provide an excellent means for structure identification and feature extraction on stochastic sequential data. An HMM-with-Duration (HMMwD) is an HMM that can also exactly model the hidden-label length (recurrence) distributions – while the regular HMM will impose a best-fit geometric distribution in its modeling/representation.</p> <p>Results</p> <p>A Novel, Fast, HMM-with-Duration (HMMwD) Implementation is presented, and experimental results are shown that demonstrate its performance on two-state synthetic data designed to model Nanopore Detector Data. The HMMwD experimental results are compared to (i) the ideal model and to (ii) the conventional HMM. Its accuracy is clearly an improvement over the standard HMM, and matches that of the ideal solution in many cases where the standard HMM does not. Computationally, the new HMMwD has all the speed advantages of the conventional (simpler) HMM implementation. In preliminary work shown here, HMM feature extraction is then used to establish the first pattern recognition-informed (PRI) sampling control of a Nanopore Detector Device (on a "live" data-stream).</p> <p>Conclusion</p> <p>The improved accuracy of the new HMMwD implementation, at the same order of computational cost as the standard HMM, is an important augmentation for applications in gene structure identification and channel current analysis, especially PRI sampling control, for example, where speed is essential. The PRI experiment was designed to inherit the high accuracy of the well characterized and distinctive blockades of the DNA hairpin molecules used as controls (or blockade "test-probes"). For this test set, the accuracy inherited is 99.9%.</p

Mathematical modeling of intracellular signaling pathways

Dynamic modeling and simulation of signal transduction pathways is an important topic in systems biology and is obtaining growing attention from researchers with experimental or theoretical background. Here we review attempts to analyze and model specific signaling systems. We review the structure of recurrent building blocks of signaling pathways and their integration into more comprehensive models, which enables the understanding of complex cellular processes. The variety of mechanisms found and modeling techniques used are illustrated with models of different signaling pathways. Focusing on the close interplay between experimental investigation of pathways and the mathematical representations of cellular dynamics, we discuss challenges and perspectives that emerge in studies of signaling systems

Oxygen dependence of metabolic fluxes and energy generation of Saccharomyces cerevisiae CEN.PK113-1A

<p>Abstract</p> <p>Background</p> <p>The yeast <it>Saccharomyces cerevisiae </it>is able to adjust to external oxygen availability by utilizing both respirative and fermentative metabolic modes. Adjusting the metabolic mode involves alteration of the intracellular metabolic fluxes that are determined by the cell's multilevel regulatory network. Oxygen is a major determinant of the physiology of <it>S. cerevisiae </it>but understanding of the oxygen dependence of intracellular flux distributions is still scarce.</p> <p>Results</p> <p>Metabolic flux distributions of <it>S. cerevisiae </it>CEN.PK113-1A growing in glucose-limited chemostat cultures at a dilution rate of 0.1 h^-1with 20.9%, 2.8%, 1.0%, 0.5% or 0.0% O₂in the inlet gas were quantified by ¹³C-MFA. Metabolic flux ratios from fractional [U-¹³C]glucose labelling experiments were used to solve the underdetermined MFA system of central carbon metabolism of <it>S. cerevisiae</it>.</p> <p>While ethanol production was observed already in 2.8% oxygen, only minor differences in the flux distribution were observed, compared to fully aerobic conditions. However, in 1.0% and 0.5% oxygen the respiratory rate was severely restricted, resulting in progressively reduced fluxes through the TCA cycle and the direction of major fluxes to the fermentative pathway. A redistribution of fluxes was observed in all branching points of central carbon metabolism. Yet only when oxygen provision was reduced to 0.5%, was the biomass yield exceeded by the yields of ethanol and CO₂. Respirative ATP generation provided 59% of the ATP demand in fully aerobic conditions and still a substantial 25% in 0.5% oxygenation. An extensive redistribution of fluxes was observed in anaerobic conditions compared to all the aerobic conditions. Positive correlation between the transcriptional levels of metabolic enzymes and the corresponding fluxes in the different oxygenation conditions was found only in the respirative pathway.</p> <p>Conclusion</p> <p>¹³C-constrained MFA enabled quantitative determination of intracellular fluxes in conditions of different redox challenges without including redox cofactors in metabolite mass balances. A redistribution of fluxes was observed not only for respirative, respiro-fermentative and fermentative metabolisms, but also for cells grown with 2.8%, 1.0% and 0.5% oxygen. Although the cellular metabolism was respiro-fermentative in each of these low oxygen conditions, the actual amount of oxygen available resulted in different contributions through respirative and fermentative pathways.</p

Nitrogen sources on TPOMW valorization through solid state fermentation performed by Yarrowia lipolytica

This manuscript reports the valorization of two-phase olive mill waste (TPOMW) as raw material and carbon source for solid state fermentation using Yarrowia lipolytica as biocatalyst. Due to its chemical characteristics, a combination of different raw materials (TPOMW and wheat bran, WB) was evaluated and two distinct nitrogen sources were applied as supplementation for lipase production. A TPOMW/WB ratio of 1:1 and supplementation with ammonium sulfate was chosen as the best condition. The productivity in 24 h reached 7.8 U/gh and, after four days of process, only decreased about 35%. Process pH ranged from 5.5-5.9, remaining in an acid range. Thus, the successful use of TPOMW, a watery solid by-product with high content of lipids, as raw material for Yarrowia lipolytica growth and lipase production provided an environmental friendly alternative to valorize such waste.The authors kindly acknowledge the financial aid and research scholarships given by CAPES. Maria Alice Zarur Coelho thanks CNPq (Proc. 308890/ 2013-2)

Socially and biologically inspired computing for self-organizing communications networks

The design and development of future communications networks call for a careful examination of biological and social systems. New technological developments like self-driving cars, wireless sensor networks, drones swarm, Internet of Things, Big Data, and Blockchain are promoting an integration process that will bring together all those technologies in a large-scale heterogeneous network. Most of the challenges related to these new developments cannot be faced using traditional approaches, and require to explore novel paradigms for building computational mechanisms that allow us to deal with the emergent complexity of these new applications. In this article, we show that it is possible to use biologically and socially inspired computing for designing and implementing self-organizing communication systems. We argue that an abstract analysis of biological and social phenomena can be made to develop computational models that provide a suitable conceptual framework for building new networking technologies: biologically inspired computing for achieving efficient and scalable networking under uncertain environments; socially inspired computing for increasing the capacity of a system for solving problems through collective actions. We aim to enhance the state-of-the-art of these approaches and encourage other researchers to use these models in their future work

Human germline heterozygous gain-of-function STAT6 variants cause severe allergic disease

sharma et al. define a new primary atopic disorder caused by heterozygous gain-of-function variants in STAT6. this results in severe, early-onset allergies, and is seen in 16 patients from 10 families. Anti-IL-4R &amp; alpha; antibody and JAK inhibitor treatment were highly effective.STAT6 (signal transducer and activator of transcription 6) is a transcription factor that plays a central role in the pathophysiology of allergic inflammation. we have identified 16 patients from 10 families spanning three continents with a profound phenotype of early-life onset allergic immune dysregulation, widespread treatment-resistant atopic dermatitis, hypereosinophilia with esosinophilic gastrointestinal disease, asthma, elevated serum IgE, IgE-mediated food allergies, and anaphylaxis. the cases were either sporadic (seven kindreds) or followed an autosomal dominant inheritance pattern (three kindreds). all patients carried monoallelic rare variants in STAT6 and functional studies established their gain-of-function (GOF) phenotype with sustained STAT6 phosphorylation, increased STAT6 target gene expression, and T(H)2 skewing. Precision treatment with the anti-IL-4R &amp; alpha; antibody, dupilumab, was highly effective improving both clinical manifestations and immunological biomarkers. this study identifies heterozygous GOF variants in STAT6 as a novel autosomal dominant allergic disorder. We anticipate that our discovery of multiple kindreds with germline STAT6 GOF variants will facilitate the recognition of more affected individuals and the full definition of this new primary atopic disorder