Belowground DNA-based techniques: untangling the network of plant root interactions

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Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees

The spread of infectious diseases crucially depends on the pattern of contacts among individuals. Knowledge of these patterns is thus essential to inform models and computational efforts. Few empirical studies are however available that provide estimates of the number and duration of contacts among social groups. Moreover, their space and time resolution are limited, so that data is not explicit at the person-to-person level, and the dynamical aspect of the contacts is disregarded. Here, we want to assess the role of data-driven dynamic contact patterns among individuals, and in particular of their temporal aspects, in shaping the spread of a simulated epidemic in the population. We consider high resolution data of face-to-face interactions between the attendees of a conference, obtained from the deployment of an infrastructure based on Radio Frequency Identification (RFID) devices that assess mutual face-to-face proximity. The spread of epidemics along these interactions is simulated through an SEIR model, using both the dynamical network of contacts defined by the collected data, and two aggregated versions of such network, in order to assess the role of the data temporal aspects. We show that, on the timescales considered, an aggregated network taking into account the daily duration of contacts is a good approximation to the full resolution network, whereas a homogeneous representation which retains only the topology of the contact network fails in reproducing the size of the epidemic. These results have important implications in understanding the level of detail needed to correctly inform computational models for the study and management of real epidemics

The science of clinical practice: disease diagnosis or patient prognosis? Evidence about "what is likely to happen" should shape clinical practice.

BACKGROUND: Diagnosis is the traditional basis for decision-making in clinical practice. Evidence is often lacking about future benefits and harms of these decisions for patients diagnosed with and without disease. We propose that a model of clinical practice focused on patient prognosis and predicting the likelihood of future outcomes may be more useful. DISCUSSION: Disease diagnosis can provide crucial information for clinical decisions that influence outcome in serious acute illness. However, the central role of diagnosis in clinical practice is challenged by evidence that it does not always benefit patients and that factors other than disease are important in determining patient outcome. The concept of disease as a dichotomous 'yes' or 'no' is challenged by the frequent use of diagnostic indicators with continuous distributions, such as blood sugar, which are better understood as contributing information about the probability of a patient's future outcome. Moreover, many illnesses, such as chronic fatigue, cannot usefully be labelled from a disease-diagnosis perspective. In such cases, a prognostic model provides an alternative framework for clinical practice that extends beyond disease and diagnosis and incorporates a wide range of information to predict future patient outcomes and to guide decisions to improve them. Such information embraces non-disease factors and genetic and other biomarkers which influence outcome. SUMMARY: Patient prognosis can provide the framework for modern clinical practice to integrate information from the expanding biological, social, and clinical database for more effective and efficient care

The Lore of Low Methane Livestock:Co-Producing Technology and Animals for Reduced Climate Change Impact

Methane emissions from sheep and cattle production have gained increasing profile in the context of climate change. Policy and scientific research communities have suggested a number of technological approaches to mitigate these emissions. This paper uses the concept of co-production as an analytical framework to understand farmers’ evaluation of a 'good animal’. It examines how technology and sheep and beef cattle are co-produced in the context of concerns about the climate change impact of methane. Drawing on 42 semi-structured interviews, this paper demonstrates that methane emissions are viewed as a natural and integral part of sheep and beef cattle by farmers, rather than as a pollutant. Sheep and beef cattle farmers in the UK are found to be an extremely heterogeneous group that need to be understood in their specific social, environmental and consumer contexts. Some are more amenable to appropriating methane reducing measures than others, but largely because animals are already co-constructed from the natural and the technical for reasons of increased production efficiency

Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology

BACKGROUND: A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. METHODS AND RESULTS: In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. CONCLUSIONS: We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects

Study of the Decays B0 --> D(*)+D(*)-

The decays B0 --> D*+D*-, B0 --> D*+D- and B0 --> D+D- are studied in 9.7 million Y(4S) --> BBbar decays accumulated with the CLEO detector. We determine Br(B0 --> D*+D*-) = (9.9+4.2-3.3+-1.2)e-4 and limit Br(B0 --> D*+D-) < 6.3e-4 and Br(B0 --> D+D-) < 9.4e-4 at 90% confidence level (CL). We also perform the first angular analysis of the B0 --> D*+D*- decay and determine that the CP-even fraction of the final state is greater than 0.11 at 90% CL. Future measurements of the time dependence of these decays may be useful for the investigation of CP violation in neutral B meson decays.Comment: 21 pages, 5 figures, submitted to Phys. Rev.

Improved Measurement of the Pseudoscalar Decay Constant fDsf_{D_{s}}

We present a new determination of the Ds decay constant, f_{Ds} using 5 million continuum charm events obtained with the CLEO II detector. Our value is derived from our new measured ratio of widths for Ds -> mu nu/Ds -> phi pi of 0.173+/- 0.021 +/- 0.031. Taking the branching ratio for Ds -> phi pi as (3.6 +/- 0.9)% from the PDG, we extract f_{Ds} = (280 +/- 17 +/- 25 +/- 34){MeV}. We compare this result with various model calculations.Comment: 23 page postscript file, postscript file also available through http://w4.lns.cornell.edu/public/CLN

Measurement of B(/\c->pKpi)

The /\c->pKpi yield has been measured in a sample of two-jet continuum events containing a both an anticharm tag (Dbar) as well as an antiproton (e+e- -> Dbar pbar X), with the antiproton in the hemisphere opposite the Dbar. Under the hypothesis that such selection criteria tag e+e- -> Dbar pbar (/\c) X events, the /\c->pkpi branching fraction can be determined by measuring the pkpi yield in the same hemisphere as the antiprotons in our Dbar pbar X sample. Combining our results from three independent types of anticharm tags, we obtain B(/\c->pKpi)=(5.0+/-0.5+/-1.2)

Search for the Decays B^0 -> D^{(*)+} D^{(*)-}

Using the CLEO-II data set we have searched for the Cabibbo-suppressed decays B^0 -> D^{(*)+} D^{(*)-}. For the decay B^0 -> D^{*+} D^{*-}, we observe one candidate signal event, with an expected background of 0.022 +/- 0.011 events. This yield corresponds to a branching fraction of Br(B^0 -> D^{*+} D^{*-}) = (5.3^{+7.1}_{-3.7}(stat) +/- 1.0(syst)) x 10^{-4} and an upper limit of Br(B^0 -> D^{*+} D^{*-}) D^{*\pm} D^\mp and B^0 -> D^+ D^-, no significant excess of signal above the expected background level is seen, and we calculate the 90% CL upper limits on the branching fractions to be Br(B^0 -> D^{*\pm} D^\mp) D^+ D^-) < 1.2 x 10^{-3}.Comment: 12 page postscript file also available through http://w4.lns.cornell.edu/public/CLNS, submitted to Physical Review Letter