Coherent information analysis of quantum channels in simple quantum systems

The coherent information concept is used to analyze a variety of simple quantum systems. Coherent information was calculated for the information decay in a two-level atom in the presence of an external resonant field, for the information exchange between two coupled two-level atoms, and for the information transfer from a two-level atom to another atom and to a photon field. The coherent information is shown to be equal to zero for all full-measurement procedures, but it completely retains its original value for quantum duplication. Transmission of information from one open subsystem to another one in the entire closed system is analyzed to learn quantum information about the forbidden atomic transition via a dipole active transition of the same atom. It is argued that coherent information can be used effectively to quantify the information channels in physical systems where quantum coherence plays an important role.Comment: 24 pages, 7 figs; Final versiob after minor changes, title changed; to be published in Phys. Rev. A, September 200

Quantum phase retrieval of a Rydberg wave packet using a half-cycle pulse

A terahertz half-cycle pulse was used to retrieve information stored as quantum phase in an $N$-state Rydberg atom data register. The register was prepared as a wave packet with one state phase-reversed from the others (the "marked bit"). A half-cycle pulse then drove a significant portion of the electron probability into the flipped state via multimode interference.Comment: accepted by PR

A Comparison of Oxidative Lactate Metabolism in Traumatically Injured Brain and Control Brain.

Metabolic abnormalities occur after traumatic brain injury (TBI). Glucose is conventionally regarded as the major energy substrate, although lactate can also be an energy source. We compared 3-13C lactate metabolism in TBI with "normal" control brain and muscle, measuring 13C-glutamine enrichment to assess tricarboxylic acid (TCA) cycle metabolism. Microdialysis catheters in brains of nine patients with severe TBI, five non-TBI brain surgical patients, and five resting muscle (non-TBI) patients were perfused (24 h in brain, 8 h in muscle) with 8 mmol/L sodium 3-13C lactate. Microdialysate analysis employed ISCUS and nuclear magnetic resonance. In TBI, with 3-13C lactate perfusion, microdialysate glucose concentration increased nonsignificantly (mean +11.9%, p = 0.463), with significant increases (p = 0.028) for lactate (+174%), pyruvate (+35.8%), and lactate/pyruvate ratio (+101.8%). Microdialysate 13C-glutamine fractional enrichments (median, interquartile range) were: for C4 5.1 (0-11.1) % in TBI and 5.7 (4.6-6.8) % in control brain, for C3 0 (0-5.0) % in TBI and 0 (0-0) % in control brain, and for C2 2.9 (0-5.7) % in TBI and 1.8 (0-3.4) % in control brain. 13C-enrichments were not statistically different between TBI and control brain, showing both metabolize 3-13C lactate via TCA cycle, in contrast to muscle. Several patients with TBI exhibited 13C-glutamine enrichment above the non-TBI control range, suggesting lactate oxidative metabolism as a TBI "emergency option."Medical Research Council (Grant Nos. G0600986 ID79068 and G1002277 ID98489) and National Institute for Health Research Biomedical Research Centre, Cambridge (Neuroscience Theme; Brain Injury and Repair Theme). Authors’ support: IJ – Medical Research Council (Grant no. G1002277 ID 98489) and National Institute for Health Research Biomedical Research Centre, Cambridge; KLHC – National Institute for Health Research Biomedical Research Centre, Cambridge (Neuroscience Theme; Brain Injury and Repair Theme); CG – the Canadian Institute of Health Research; AH – Medical Research Council/Royal College of Surgeons of England Clinical Research Training Fellowship (Grant no. G0802251) and Raymond and Beverly Sackler Fellowship; Royal College of Surgeons of England and the NIHR Cambridge Biomedical Research Centre; DKM and JDP – National Institute for Health Research Senior Investigator Awards; MPM - Medical Research Council UK (MC_U105663142) and a Wellcome Trust Investigator award (110159/Z/15/Z). PJH – National Institute for Health Research Professorship, Academy of Medical Sciences/Health Foundation Senior Surgical Scientist Fellowship and the National Institute for Health Research Biomedical Research Centre, Cambridge

Focally perfused succinate potentiates brain metabolism in head injury patients.

Following traumatic brain injury, complex cerebral energy perturbations occur. Correlating with unfavourable outcome, high brain extracellular lactate/pyruvate ratio suggests hypoxic metabolism and/or mitochondrial dysfunction. We investigated whether focal administration of succinate, a tricarboxylic acid cycle intermediate interacting directly with the mitochondrial electron transport chain, could improve cerebral metabolism. Microdialysis perfused disodium 2,3-13C2 succinate (12 mmol/L) for 24 h into nine sedated traumatic brain injury patients' brains, with simultaneous microdialysate collection for ISCUS analysis of energy metabolism biomarkers (nine patients) and nuclear magnetic resonance of 13C-labelled metabolites (six patients). Metabolites 2,3-13C2 malate and 2,3-13C2 glutamine indicated tricarboxylic acid cycle metabolism, and 2,3-13C2 lactate suggested tricarboxylic acid cycle spinout of pyruvate (by malic enzyme or phosphoenolpyruvate carboxykinase and pyruvate kinase), then lactate dehydrogenase-mediated conversion to lactate. Versus baseline, succinate perfusion significantly decreased lactate/pyruvate ratio (p = 0.015), mean difference -12%, due to increased pyruvate concentration (+17%); lactate changed little (-3%); concentrations decreased for glutamate (-43%) (p = 0.018) and glucose (-15%) (p = 0.038). Lower lactate/pyruvate ratio suggests better redox status: cytosolic NADH recycled to NAD+ by mitochondrial shuttles (malate-aspartate and/or glycerol 3-phosphate), diminishing lactate dehydrogenase-mediated pyruvate-to-lactate conversion, and lowering glutamate. Glucose decrease suggests improved utilisation. Direct tricarboxylic acid cycle supplementation with 2,3-13C2 succinate improved human traumatic brain injury brain chemistry, indicated by biomarkers and 13C-labelling patterns in metabolites.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Medical Research Council (Grant Nos. G0600986 ID79068 and G1002277 ID98489) and National Institute for Health Research Biomedical Research Centre, Cambridge (Neuroscience Theme; Brain Injury and Repair Theme). Authors’ support: IJ – Medical Research Council (Grant no. G1002277 ID 98489) and National Institute for Health Research Biomedical Research Centre, Cambridge; KLHC – National Institute for Health Research Biomedical Research Centre, Cambridge (Neuroscience Theme; Brain Injury and Repair Theme); CG – the Canadian Institute of Health Research; AH – Medical Research Council/Royal College of Surgeons of England Clinical Research Training Fellowship (Grant no. G0802251) and Raymond and Beverly Sackler Fellowship; DKM and JDP – National Institute for Health Research Senior Investigator Awards; PJH – National Institute for Health Research Professorship, Academy of Medical Sciences/Health Foundation Senior Surgical Scientist Fellowship and the National Institute for Health Research Biomedical Research Centre, Cambridge

Priority setting: what constitutes success? A conceptual framework for successful priority setting

BACKGROUND: The sustainability of healthcare systems worldwide is threatened by a growing demand for services and expensive innovative technologies. Decision makers struggle in this environment to set priorities appropriately, particularly because they lack consensus about which values should guide their decisions. One way to approach this problem is to determine what all relevant stakeholders understand successful priority setting to mean. The goal of this research was to develop a conceptual framework for successful priority setting. METHODS: Three separate empirical studies were completed using qualitative data collection methods (one-on-one interviews with healthcare decision makers from across Canada; focus groups with representation of patients, caregivers and policy makers; and Delphi study including scholars and decision makers from five countries). RESULTS: This paper synthesizes the findings from three studies into a framework of ten separate but interconnected elements germane to successful priority setting: stakeholder understanding, shifted priorities/reallocation of resources, decision making quality, stakeholder acceptance and satisfaction, positive externalities, stakeholder engagement, use of explicit process, information management, consideration of values and context, and revision or appeals mechanism. CONCLUSION: The ten elements specify both quantitative and qualitative dimensions of priority setting and relate to both process and outcome components. To our knowledge, this is the first framework that describes successful priority setting. The ten elements identified in this research provide guidance for decision makers and a common language to discuss priority setting success and work toward improving priority setting efforts

Consensus statement from the 2014 International Microdialysis Forum.

Microdialysis enables the chemistry of the extracellular interstitial space to be monitored. Use of this technique in patients with acute brain injury has increased our understanding of the pathophysiology of several acute neurological disorders. In 2004, a consensus document on the clinical application of cerebral microdialysis was published. Since then, there have been significant advances in the clinical use of microdialysis in neurocritical care. The objective of this review is to report on the International Microdialysis Forum held in Cambridge, UK, in April 2014 and to produce a revised and updated consensus statement about its clinical use including technique, data interpretation, relationship with outcome, role in guiding therapy in neurocritical care and research applications.We gratefully acknowledge financial support for participants as follows: P.J.H. - National Institute for Health Research (NIHR) Professorship and the NIHR Biomedical Research Centre, Cambridge; I.J. – Medical Research Council (G1002277 ID 98489); A. H. - Medical Research Council, Royal College of Surgeons of England; K.L.H.C. - NIHR Biomedical Research Centre, Cambridge (Neuroscience Theme; Brain Injury and Repair Theme); M.G.B. - Wellcome Trust Dept Health Healthcare Innovation Challenge Fund (HICF-0510-080); L. H. - The Swedish Research Council, VINNOVA and Uppsala Berzelii Technology Centre for Neurodiagnostics; S. M. - Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico; D.K.M. - NIHR Senior Investigator Award to D.K.M., NIHR Cambridge Biomedical Research Centre (Neuroscience Theme), FP7 Program of the European Union; M. O. - Swiss National Science Foundation and the Novartis Foundation for Biomedical Research; J.S. - Fondo de Investigación Sanitaria (Instituto de Salud Carlos III) (PI11/00700) co-financed by the European Regional Development; M.S. – NIHR University College London Hospitals Biomedical Research Centre; N. S. - Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico.This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s00134-015-3930-

Clique-Finding for Heterogeneity and Multidimensionality in Biomarker Epidemiology Research: The CHAMBER Algorithm

Commonly-occurring disease etiology may involve complex combinations of genes and exposures resulting in etiologic heterogeneity. We present a computational algorithm that employs clique-finding for heterogeneity and multidimensionality in biomedical and epidemiological research (the "CHAMBER" algorithm).This algorithm uses graph-building to (1) identify genetic variants that influence disease risk and (2) predict individuals at risk for disease based on inherited genotype. We use a set-covering algorithm to identify optimal cliques and a Boolean function that identifies etiologically heterogeneous groups of individuals. We evaluated this approach using simulated case-control genotype-disease associations involving two- and four-gene patterns. The CHAMBER algorithm correctly identified these simulated etiologies. We also used two population-based case-control studies of breast and endometrial cancer in African American and Caucasian women considering data on genotypes involved in steroid hormone metabolism. We identified novel patterns in both cancer sites that involved genes that sulfate or glucuronidate estrogens or catecholestrogens. These associations were consistent with the hypothesized biological functions of these genes. We also identified cliques representing the joint effect of multiple candidate genes in all groups, suggesting the existence of biologically plausible combinations of hormone metabolism genes in both breast and endometrial cancer in both races.The CHAMBER algorithm may have utility in exploring the multifactorial etiology and etiologic heterogeneity in complex disease

Frequent traces of EBV infection in Hodgkin and non-Hodgkin lymphomas classified as EBV-negative by routine methods: expanding the landscape of EBV-related lymphoma

peer-reviewedThe Epstein–Barr virus (EBV) is linked to various B-cell lymphomas, including Burkitt lymphoma (BL), classical Hodgkin lymphoma (cHL) and diffuse large B-cell lymphoma (DLBCL) at frequencies ranging, by routine techniques, from 5 to 10% of cases in DLBCL to >95% in endemic BL. Using higher-sensitivity methods, we recently detected EBV traces in a few EBV-negative BL cases, possibly suggesting a “hit-and-run” mechanism. Here, we used routine and higher-sensitivity methods (qPCR and ddPCR for conserved EBV genomic regions and miRNAs on microdissected tumor cells; EBNA1 mRNA In situ detection by RNAscope) to assess EBV infection in a larger lymphoma cohort [19 BL, 34 DLBCL, 44 cHL, 50 follicular lymphomas (FL), 10 T-lymphoblastic lymphomas (T-LL), 20 hairy cell leukemias (HCL), 10 mantle cell lymphomas (MCL)], as well as in several lymphoma cell lines (9 cHL and 6 BL). qPCR, ddPCR, and RNAscope consistently documented the presence of multiple EBV nucleic acids in rare tumor cells of several cases EBV-negative by conventional methods that all belonged to lymphoma entities clearly related to EBV (BL, 6/9 cases; cHL, 16/32 cases; DLBCL, 11/30 cases), in contrast to fewer cases (3/47 cases) of FL (where the role of EBV is more elusive) and no cases (0/40) of control lymphomas unrelated to EBV (HCL, T-LL, MCL). Similarly, we revealed traces of EBV infection in 4/5 BL and 6/7 HL cell lines otherwise conventionally classified as EBV negative. Interestingly, additional EBV-positive cases (1 DLBCL, 2 cHL) relapsed as EBV-negative by routine methods while showing EBNA1 expression in rare tumor cells by RNAscope. The relapse specimens were clonally identical to their onset biopsies, indicating that the lymphoma clone can largely loose the EBV genome over time but traces of EBV infection are still detectable by high-sensitivity methods. We suggest EBV may contribute to lymphoma pathogenesis more widely than currently acknowledged

Probabilistic downscaling of remote sensing data with applications for multi-scale biogeochemical flux modeling

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes