Patient-powered research networks: building capacity for conducting patient-centered clinical outcomes research.

The Patient-Centered Outcomes Research Institute (PCORI) recently launched PCORnet to establish a single inter-operable multicenter data research network that will support observational research and randomized clinical trials. This paper provides an overview of the patient-powered research networks (PPRNs), networks of patient organizations focused on a particular health condition that are interested in sharing health information and engaging in research. PPRNs will build on their foundation of trust within the patient communities and draw on their expertise, working with participants to identify true patient-centered outcomes and direct a patient-centered research agenda. The PPRNs will overcome common challenges including enrolling a diverse and representative patient population; engaging patients in governance; designing the data infrastructure; sharing data securely while protecting privacy; prioritizing research questions; scaling small networks into a larger network; and identifying pathways to sustainability. PCORnet will be the first distributed research network to bring PCOR to national scale

Recovering star formation histories: Integrated-light analyses vs stellar colour-magnitude diagrams

Accurate star formation histories (SFHs) of galaxies are fundamental for understanding the build-up of their stellar content. However, the most accurate SFHs - those obtained from colour-magnitude diagrams (CMDs) of resolved stars reaching the oldest main sequence turnoffs (oMSTO) - are presently limited to a few systems in the Local Group. It is therefore crucial to determine the reliability and range of applicability of SFHs derived from integrated light spectroscopy, as this affects our understanding of unresolved galaxies from low to high redshift. To evaluate the reliability of current full spectral fitting techniques in deriving SFHs from integrated light spectroscopy by comparing SFHs from integrated spectra to those obtained from deep CMDs of resolved stars. We have obtained a high signal--to--noise (S/N $\sim$ 36.3 per \AA) integrated spectrum of a field in the bar of the Large Magellanic Cloud (LMC) using EFOSC2 at the 3.6 meter telescope at La Silla Observatory. For this same field, resolved stellar data reaching the oMSTO are available. We have compared the star formation rate (SFR) as a function of time and the age-metallicity relation (AMR) obtained from the integrated spectrum using {\tt STECKMAP}, and the CMD using the IAC-star/MinnIAC/IAC-pop set of routines. For the sake of completeness we also use and discuss other synthesis codes ({\tt STARLIGHT} and {\tt ULySS}) to derive the SFR and AMR from the integrated LMC spectrum. We find very good agreement (average differences $\sim$ 4.1 $\%$) between the SFR(t) and the AMR obtained using {\tt STECKMAP} on the integrated light spectrum, and the CMD analysis. {\tt STECKMAP} minimizes the impact of the age-metallicity degeneracy and has the advantage of preferring smooth solutions to recover complex SFHs by means of a penalized $\chi^2$. [abridged]Comment: 23 pages, 24 figures. Accepted for publication in A&A (6 Sep 2015

Evidence-based prescribing: combining network meta-analysis with multicriteria decision analysis to choose among multiple drugs

What is the drug of choice for condition x? is among the most commonly asked questions in primary care.1 Reflecting the complexity of prescribing decisions, answering this question requires a difficult trade-off between the benefits and harms of multiple drugs for a given condition. The principles of evidence-based medicine suggest that prescribing decisions should be guided by an objective benchmark, namely scientific evidence.2 Such evidence is particularly important when choosing a first-line treatment among multiple alternatives. Unfortunately, existing clinical evidence on benefits and harms is rarely adequate to inform prescribing decisions. A randomized controlled trial comparing all relevant drugs would provide such information. However, clinical trials are often designed for regulatory purposes and, therefore, include selective patient populations and do not include all available comparator drugs.3,4 To obtain insight into the comparative benefits and harms of multiple drugs, prescribers turn to summaries of evidence to discern the most promising drugs from their less effective comparators. Recent methods used to synthesize existing evidence provide much-needed information on the comparative benefits and harms of multiple drugs. Network meta-analysis is one such method that allows for the combination of direct and indirect evidences from randomized trials, facilitating the comparison of all relevant drugs even when they are not directly compared with each other in clinical trials.5 The recent surge in the number of network meta-analyses in the general medical literature is a testament to the increasing need for comparative evidence in prescribing decisions

Launching PCORnet, a national patient-centered clinical research network

The Patient-Centered Outcomes Research Institute (PCORI) has launched PCORnet, a major initiative to support an effective, sustainable national research infrastructure that will advance the use of electronic health data in comparative effectiveness research (CER) and other types of research. In December 2013, PCORI's board of governors funded 11 clinical data research networks (CDRNs) and 18 patient-powered research networks (PPRNs) for a period of 18 months. CDRNs are based on the electronic health records and other electronic sources of very large populations receiving healthcare within integrated or networked delivery systems. PPRNs are built primarily by communities of motivated patients, forming partnerships with researchers. These patients intend to participate in clinical research, by generating questions, sharing data, volunteering for interventional trials, and interpreting and disseminating results. Rapidly building a new national resource to facilitate a large-scale, patient-centered CER is associated with a number of technical, regulatory, and organizational challenges, which are described here

Metallic atomically-thin layered silicon epitaxially grown on silicene/ZrB2

Using low energy electron diffraction (LEED) and scanning tunnelling microscopy (STM), we observe a new two-dimensional (2D) silicon crystal that is formed by depositing additional Si atoms onto spontaneously-formed epitaxial silicene on a ZrB2 thin film. From scanning tunnelling spectroscopy (STS) studies, we find that this atomically-thin layered silicon has distinctly different electronic properties. Angle resolved photoelectron spectroscopy (ARPES) reveals that, in sharp contrast to epitaxial silicene, the layered silicon exhibits significantly enhanced density of states at the Fermi level resulting from newly formed metallic bands. The 2D growth of this material could allow for direct contacting to the silicene surface and demonstrates the dramatic changes in electronic structure that can occur by the addition of even a single monolayer amount of material in 2D systems

Discrete and continuous time simulations of spatial ecological processes predict different final population sizes and interspecific competition outcomes

Cellular automata (CAs) are commonly used to simulate spatial processes in ecology. Although appropriate for modelling events that occur at discrete time points, they are also routinely used to model biological processes that take place continuously. We report on a study comparing predictions of discrete time CA models to those of their continuous time counterpart. Specifically, we investigate how the decision to model time discretely or continuously affects predictions regarding long-run population sizes, the probability of extinction and interspecific competition. We show effects on predicted ecological outcomes, finding quantitative differences in all cases and in the case of interspecific competition, additional qualitative differences in predictions regarding species dominance. Our findings demonstrate that qualitative conclusions drawn from spatial simulations can be critically dependent on the decision to model time discretely or continuously. Contrary to our expectations, simulating in continuous time did not incur a heavy computational penalty. We also raise ecological questions on the relative benefits of reproductive strategies that take place in discrete and continuous time