Coherent coupling of two quantum dots embedded in an Aharonov-Bohm ring

We define two laterally gated small quantum dots (~ 15 electrons) in an Aharonov-Bohm geometry in which the coupling between the two dots can be broadly changed. For weakly coupled quantum dots we find Aharonov-Bohm oscillations. In an intermediate coupling regime we concentrate on the molecular states of the double dot and extract the magnetic field dependence of the coherent coupling.Comment: 6 pages, 4 figure

Elevated plasma galectin-3 is associated with near-term rehospitalization in heart failure:A pooled analysis of 3 clinical trials

BackgroundRehospitalization is a major cause for heart failure (HF)–related morbidity and is associated with considerable loss of quality of life and costs. The rate of unplanned rehospitalization in patients with HF is unacceptably high; current risk stratification to identify patients at risk for rehospitalization is inadequate. We evaluated whether measurement of galectin-3 would be helpful in identifying patients at such risk.MethodsWe analyzed pooled data from patients (n = 902) enrolled in 3 cohorts (COACH, n = 592; PRIDE, n = 181; and UMD H-23258, n = 129) originally admitted because of HF. Mean patient age was between 61.6 and 72.9 years across the cohorts, with a wide range of left ventricular ejection fraction. Galectin-3 levels were measured during index admission. We used fixed and random-effects models, as well as continuous and categorical reclassification statistics to assess the association of baseline galectin-3 levels with risk of postdischarge rehospitalization at different time points and the composite end point all-cause mortality and rehospitalization.ResultsCompared with patients with galectin-3 concentrations less than 17.8 ng/mL, those with results exceeding this value were significantly more likely to be rehospitalized for HF at 30, 60, 90, and 120 days after discharge, with odds ratios (ORs) of 2.80 (95% CI 1.41-5.57), 2.61 (95% CI 1.46-4.65), 3.01 (95% CI 1.79-5.05), and 2.79 (95% CI 1.75-4.45), respectively. After adjustment for age, gender, New York Heart Association class, renal function (estimated glomerular filtration rate), left ventricular ejection fraction, and B-type natriuretic peptide, galectin-3 remained an independent predictor of HF rehospitalization. The addition of galectin-3 to risk models significantly reclassified patient risk of postdischarge rehospitalization and fatal event at each time point (continuous net reclassification improvement at 30 days of +42.6% [95% CI +19.9%-65.4%], P < .001).ConclusionsAmong patients hospitalized for HF, plasma galectin-3 concentration is useful for the prediction of near-term rehospitalization

Electron transport through double quantum dots

Electron transport experiments on two lateral quantum dots coupled in series are reviewed. An introduction to the charge stability diagram is given in terms of the electrochemical potentials of both dots. Resonant tunneling experiments show that the double dot geometry allows for an accurate determination of the intrinsic lifetime of discrete energy states in quantum dots. The evolution of discrete energy levels in magnetic field is studied. The resolution allows to resolve avoided crossings in the spectrum of a quantum dot. With microwave spectroscopy it is possible to probe the transition from ionic bonding (for weak inter-dot tunnel coupling) to covalent bonding (for strong inter-dot tunnel coupling) in a double dot artificial molecule. This review on the present experimental status of double quantum dot studies is motivated by their relevance for realizing solid state quantum bits.Comment: 32 pages, 31 figure

Genosenor Technology Development

Contains table of contents for Part IV, table of contents for Section 1, and reports on two research projects.Genometrix, Inc. Contract GMX-GH00776-04Defense Advanced Research Projects AgencyU.S. Air Force - Office of Scientific Researc

Correlation and symmetry effects in transport through an artificial molecule

Spectral weights and current-voltage characteristics of an artificial diatomic molecule are calculated, considering cases where the dots connected in series are in general different. The spectral weights allow us to understand the effects of correlations, their connection with selection rules for transport, and the role of excited states in the experimental conductance spectra of these coupled double dot systems (DDS). An extended Hubbard Hamiltonian with varying interdot tunneling strength is used as a model, incorporating quantum confinement in the DDS, interdot tunneling as well as intra- and interdot Coulomb interactions. We find that interdot tunneling values determine to a great extent the resulting eigenstates and corresponding spectral weights. Details of the state correlations strongly suppress most of the possible conduction channels, giving rise to effective selection rules for conductance through the molecule. Most states are found to make insignificant contributions to the total current for finite biases. We find also that the symmetry of the structure is reflected in the I-V characteristics, and is in qualitative agreement with experiment.Comment: 25 figure files - REVTEX - submitted to PR

Conductance oscillations in tunnel-coupled quantum dots in the quantum Hall regime

We present measurements of transport through two tunnel-coupled quantum dots of different sizes connected in series in a strong, variable, perpendicular magnetic field. Double dot conductance was measured both as a function of magnetic field, which was varied across the filling factor nu = 4 quantum Hall plateau, and as a function of charge induced evenly on the two dots. The conductance peaks undergo position shifts and height modulations as the magnetic field is varied. These shifts and modulations form a pattern that repeats over large ranges of magnetic field and with the addition of double dot charge. The robust pattern repetition is consistent with a frequency locking effect.Comment: 12 pages, 4 figure

Candidate Proteins, Metabolites and Transcripts in the Biomarkers for Spinal Muscular Atrophy (BforSMA) Clinical Study

Spinal Muscular Atrophy (SMA) is a neurodegenerative motor neuron disorder resulting from a homozygous mutation of the survival of motor neuron 1 (SMN1) gene. The gene product, SMN protein, functions in RNA biosynthesis in all tissues. In humans, a nearly identical gene, SMN2, rescues an otherwise lethal phenotype by producing a small amount of full-length SMN protein. SMN2 copy number inversely correlates with disease severity. Identifying other novel biomarkers could inform clinical trial design and identify novel therapeutic targets.To identify novel candidate biomarkers associated with disease severity in SMA using unbiased proteomic, metabolomic and transcriptomic approaches.A cross-sectional single evaluation was performed in 108 children with genetically confirmed SMA, aged 2-12 years, manifesting a broad range of disease severity and selected to distinguish factors associated with SMA type and present functional ability independent of age. Blood and urine specimens from these and 22 age-matched healthy controls were interrogated using proteomic, metabolomic and transcriptomic discovery platforms. Analyte associations were evaluated against a primary measure of disease severity, the Modified Hammersmith Functional Motor Scale (MHFMS) and to a number of secondary clinical measures.A total of 200 candidate biomarkers correlate with MHFMS scores: 97 plasma proteins, 59 plasma metabolites (9 amino acids, 10 free fatty acids, 12 lipids and 28 GC/MS metabolites) and 44 urine metabolites. No transcripts correlated with MHFMS.In this cross-sectional study, "BforSMA" (Biomarkers for SMA), candidate protein and metabolite markers were identified. No transcript biomarker candidates were identified. Additional mining of this rich dataset may yield important insights into relevant SMA-related pathophysiology and biological network associations. Additional prospective studies are needed to confirm these findings, demonstrate sensitivity to change with disease progression, and assess potential impact on clinical trial design.Clinicaltrials.gov NCT00756821

The art and practice of systems biology in medicine: Mapping patterns of relationships

Systems biology has developed in recent years from a technology-driven enterprise to a new strategic tool in Life Sciences, particularly for innovative drug discovery and drug development. Combining the ultimate in systems phenotyping with in-depth investigations of biomolecular mechanisms will enable a revolution in our understanding of disease pathology and will advance translational medicine, combination therapies, integrative medicine, and personalized medicine. A prerequisite for deriving the benefits of such a systems approach is a reliable and well-validated bioanalytical platform across complementary measurement modalities, especially transcriptomics, proteomics, and metabolomics, that operates in concert with a megavariate integrative biostatistical/bioinformatics platform. The applicable bioanalytical methodologies must undergo an intense development trajectory to reach an optimal level of reliable performance and quantitative reproducibility in daily practice. Moreover, to generate such enabling systems information, it is essential to design experiments based on an understanding of the complexity and statistical characteristics of the large data sets created. Novel insights into biology and system science can be obtained by evaluating the molecular connectivity within a system through correlation networks, by monitoring the dynamics of a system, or by measuring the system responses to perturbations such as drug administration or challenge tests. In addition, cross-compartment communication and control/feed-back mechanisms can be studied via correlation network analyses. All these data analyses depend critically upon the generation of high-quality bioanalytical platform data sets. The emphasis of this paper is on the characteristics of a bioanalytical platform that we have developed to generate such data sets. The broad applicability of Systems Biology in pharmaceutical research and development is discussed with examples in disease biomarker research, in pharmacology using system response monitoring, and in cross-compartment system toxicology assessment. © 2007 American Chemical Society