A Bayesian approach to detect QTL affecting a simulated binary and quantitative trait

Background - We analyzed simulated data from the 14th QTL-MAS workshop using a Bayesian approach implemented in the program iBay. The data contained individuals genotypes for 10,031 SNPs and phenotyped for a quantitative and a binary trait. Results - For the quantitative trait we mapped 8 out of 30 additive QTL, 1 out of 3 imprinted QTL and both epistatic pairs of QTL successfully. For the binary trait we mapped 11 out of 22 additive QTL successfully. Four out of 22 pleiotropic QTL were detected as such. Conclusions - The Bayesian variable selection method showed to be a successful method for genome-wide association. This method was reasonably fast using dense marker map

A single-photon transistor using nano-scale surface plasmons

It is well known that light quanta (photons) can interact with each other in nonlinear media, much like massive particles do, but in practice these interactions are usually very weak. Here we describe a novel approach to realize strong nonlinear interactions at the single-photon level. Our method makes use of recently demonstrated efficient coupling between individual optical emitters and tightly confined, propagating surface plasmon excitations on conducting nanowires. We show that this system can act as a nonlinear two-photon switch for incident photons propagating along the nanowire, which can be coherently controlled using quantum optical techniques. As a novel application, we discuss how the interaction can be tailored to create a single-photon transistor, where the presence or absence of a single incident photon in a ``gate'' field is sufficient to completely control the propagation of subsequent ``signal'' photons.Comment: 20 pages, 4 figure

High-fidelity quantum driving

The ability to accurately control a quantum system is a fundamental requirement in many areas of modern science such as quantum information processing and the coherent manipulation of molecular systems. It is usually necessary to realize these quantum manipulations in the shortest possible time in order to minimize decoherence, and with a large stability against fluctuations of the control parameters. While optimizing a protocol for speed leads to a natural lower bound in the form of the quantum speed limit rooted in the Heisenberg uncertainty principle, stability against parameter variations typically requires adiabatic following of the system. The ultimate goal in quantum control is to prepare a desired state with 100% fidelity. Here we experimentally implement optimal control schemes that achieve nearly perfect fidelity for a two-level quantum system realized with Bose-Einstein condensates in optical lattices. By suitably tailoring the time-dependence of the system's parameters, we transform an initial quantum state into a desired final state through a short-cut protocol reaching the maximum speed compatible with the laws of quantum mechanics. In the opposite limit we implement the recently proposed transitionless superadiabatic protocols, in which the system perfectly follows the instantaneous adiabatic ground state. We demonstrate that superadiabatic protocols are extremely robust against parameter variations, making them useful for practical applications.Comment: 17 pages, 4 figure

Pharmacologic targeting of renal ischemia-reperfusion injury using a normothermic machine perfusion platform.

Normothermic machine perfusion (NMP) is an emerging modality for kidney preservation prior to transplantation. NMP may allow directed pharmacomodulation of renal ischemia-reperfusion injury (IRI) without the need for systemic donor/recipient therapies. Three proven anti-IRI agents not in widespread clinical use, CD47-blocking antibody (αCD47Ab), soluble complement receptor 1 (sCR1), and recombinant thrombomodulin (rTM), were compared in a murine model of kidney IRI. The most effective agent was then utilized in a custom NMP circuit for the treatment of isolated porcine kidneys, ascertaining the impact of the drug on perfusion and IRI-related parameters. αCD47Ab conferred the greatest protection against IRI in mice after 24 hours. αCD47Ab was therefore chosen as the candidate agent for addition to the NMP circuit. CD47 receptor binding was demonstrated by immunofluorescence. Renal perfusion/flow improved with CD47 blockade, with a corresponding reduction in oxidative stress and histologic damage compared to untreated NMP kidneys. Tubular and glomerular functional parameters were not significantly impacted by αCD47Ab treatment during NMP. In a murine renal IRI model, αCD47Ab was confirmed as a superior anti-IRI agent compared to therapies targeting other pathways. NMP enabled effective, direct delivery of this drug to porcine kidneys, although further efficacy needs to be proven in the transplantation setting

A two step Bayesian approach for genomic prediction of breeding values

<p>Abstract</p> <p>Background</p> <p>In genomic models that assign an individual variance to each marker, the contribution of one marker to the posterior distribution of the marker variance is only one degree of freedom (df), which introduces many variance parameters with only little information per variance parameter. A better alternative could be to form clusters of markers with similar effects where markers in a cluster have a common variance. Therefore, the influence of each marker group of size <it>p </it>on the posterior distribution of the marker variances will be <it>p </it>df.</p> <p>Methods</p> <p>The simulated data from the 15^thQTL-MAS workshop were analyzed such that SNP markers were ranked based on their effects and markers with similar estimated effects were grouped together. In step 1, all markers with minor allele frequency more than 0.01 were included in a SNP-BLUP prediction model. In step 2, markers were ranked based on their estimated variance on the trait in step 1 and each 150 markers were assigned to one group with a common variance. In further analyses, subsets of 1500 and 450 markers with largest effects in step 2 were kept in the prediction model.</p> <p>Results</p> <p>Grouping markers outperformed SNP-BLUP model in terms of accuracy of predicted breeding values. However, the accuracies of predicted breeding values were lower than Bayesian methods with marker specific variances.</p> <p>Conclusions</p> <p>Grouping markers is less flexible than allowing each marker to have a specific marker variance but, by grouping, the power to estimate marker variances increases. A prior knowledge of the genetic architecture of the trait is necessary for clustering markers and appropriate prior parameterization.</p

Retrivability in The Danish National Hospital Registry of HIV and hepatitis B and C coinfection diagnoses of patients managed in HIV centers 1995–2004

<p>Abstract</p> <p>Background</p> <p>Hospital-based discharge registries are used increasingly for longitudinal epidemiological studies of HIV. We examined completeness of registration of HIV infections and of chronic hepatitis B (HBV) and hepatitis C (HCV) coinfections in the Danish National Hospital Registry (DNHR) covering all Danish hospitals.</p> <p>Methods</p> <p>The Danish HIV Cohort Study (DHCS) encompasses all HIV-infected patients treated in Danish HIV clinics since 1 January 1995. All 2,033 Danish patients in DHCS diagnosed with HIV-1 during the 10-year period from 1 January 1995 to 31 December 2004 were included in the current analysis. We used the DHCS as a reference to examine the completeness of HIV and of HBV and HCV coinfections recorded in DNHR. Cox regression analysis was used to estimate hazard ratios of time to diagnosis of HIV in DNHR compared to DHCS.</p> <p>Results</p> <p>Of the 2,033 HIV patients in DHCS, a total of 2,006 (99%) were registered with HIV in DNHR. Of these, 1,888 (93%) were registered in DNHR within one year of their first positive HIV test. A CD4 < 200 cells/μl, a viral load >= 100,000 copies/ml and being diagnosed after 1 January 2000, were associated with earlier registration in DNHR, both in crude and adjusted analyses. Thirty (23%) HIV patients registered with chronic HBV (n = 129) in DHCS and 126 (48%) of HIV patients with HCV (n = 264) in DHCS were registered with these diagnoses in the DNHR. Further 17 and 8 patients were registered with HBV and HCV respectively in DNHR, but not in DHCS. The positive predictive values of being registered with HBV and HCV in DHCS were thereby estimated to 0.88 and 0.97 and in DNHR to 0.32 and 0.54.</p> <p>Conclusion</p> <p>The study demonstrates that secondary data from national hospital databases may be reliable for identification of patients diagnosed with HIV infection. However, the predictive value of co-morbidity data may be low.</p

Patient-reported utilities in advanced or metastatic melanoma, including analysis of utilities by time to death

Background: Health-related quality of life is often collected in clinical studies, and forms a cornerstone of economic evaluation. This study had two objectives, firstly to report and compare pre- and post-progression health state utilities in advanced melanoma when valued by different methods and secondly to explore the validity of progression-based health state utility modelling compared to modelling based upon time to death. Methods: Utilities were generated from the ipilimumab MDX010-20 trial (Clinicaltrials.gov Identifier: NCT00094653) using the condition-specific EORTC QLQ-C30 (via the EORTC-8D) and generic SF-36v2 (via the SF-6D) preference-based measures. Analyses by progression status and time to death were conducted on the patient-level data from the MDX010-20 trial using generalised estimating equations fitted in Stata®, and the predictive abilities of the two approaches compared. Results: Mean utility showed a decrease on disease progression in both the EORTC-8D (0.813 to 0.776) and the SF-6D (0.648 to 0.626). Whilst higher utilities were obtained using the EORTC-8D, the relative decrease in utility on progression was similar between measures. When analysed by time to death, both EORTC-8D and SF-6D showed a large decrease in utility in the 180 days prior to death (from 0.831 to 0.653 and from 0.667 to 0.544, respectively). Compared to progression status alone, the use of time to death gave similar or better estimates of the original data when used to predict patient utility in the MDX010-20 study. Including both progression status and time to death further improved model fit. Utilities seen in MDX010-20 were also broadly comparable with those seen in the literature. Conclusions: Patient-level utility data should be analysed prior to constructing economic models, as analysis solely by progression status may not capture all predictive factors of patient utility and time to death may, as death approaches, be as or more important. Additionally this study adds to the body of evidence showing that different scales lead to different health state values. Further research is needed on how different utility instruments (the SF-6D, EORTC-8D and EQ-5D) relate to each other in different disease areas