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Registry-based trials have emerged as a potentially cost-saving study methodology. Early estimates of cost savings, however, conflated the benefits associated with registry utilisation and those associated with other aspects of pragmatic trial designs, which might not all be as broadly applicable. In this study, we sought to build a practical tool that investigators could use across disciplines to estimate the ranges of potential cost differences associated with implementing registry-based trials versus standard clinical trials.
We built simulation Markov models to compare unique costs associated with data acquisition, cleaning, and linkage under a registry-based trial design versus a standard clinical trial. We conducted one-way, two-way, and probabilistic sensitivity analyses, varying study characteristics over broad ranges, to determine thresholds at which investigators might optimally select each trial design.
Registry-based trials were more cost effective than standard clinical trials 98.6% of the time. Data-related cost savings ranged from $4300 to $600,000 with variation in study characteristics. Cost differences were most reactive to the number of patients in a study, the number of data elements per patient available in a registry, and the speed with which research coordinators could manually abstract data. Registry incorporation resulted in cost savings when as few as 3768 independent data elements were available and when manual data abstraction took as little as 3.4 seconds per data field.
Registries offer important resources for investigators. When available, their broad incorporation may help the scientific community reduce the costs of clinical investigation. We offer here a practical tool for investigators to assess potential costs savings.
We present a multi-frequency study of the intermediate spiral SAB(r)bc type galaxy NGC 6744, using available data from the Chandra X-Ray telescope, radio continuum data from the Australia Telescope Compact Array and Murchison Widefield Array, and Wide-field Infrared Survey Explorer infrared observations. We identify 117 X-ray sources and 280 radio sources. Of these, we find nine sources in common between the X-ray and radio catalogues, one of which is a faint central black hole with a bolometric radio luminosity similar to the Milky Way’s central black hole. We classify 5 objects as supernova remnant (SNR) candidates, 2 objects as likely SNRs, 17 as H ii regions, 1 source as an AGN; the remaining 255 radio sources are categorised as background objects and one X-ray source is classified as a foreground star. We find the star-formation rate (SFR) of NGC 6744 to be in the range 2.8–4.7 M⊙~yr − 1 signifying the galaxy is still actively forming stars. The specific SFR of NGC 6744 is greater than that of late-type spirals such as the Milky Way, but considerably less that that of a typical starburst galaxy.
We agree with Rahnev & Denison (R&D) that to understand perception at a process level, we must investigate why performance sometimes deviates from idealised decision models. Recent research reveals that such deviations from optimality are pervasive during perceptual development. We argue that a full understanding of perception requires a model of how perceptual systems become increasingly optimised during development.
The Detroit Lakes chain of lakes consists of five basins in northwest Minnesota adjacent to the town of Detroit Lakes. Flowering rush has been established in these basins since the 1960s. We evaluated the distribution of flowering rush in the five basins using a point intercept method, with 830 points distributed in a grid with points 150 m apart. These data were analyzed to determine whether invasive and native species frequencies were different between 2010 and 2011. We also assessed co-occurrence of flowering rush with native hardstem bulrush. The distribution of both flowering rush and hardstem bulrush was unchanged from 2010 to 2011. Flowering rush is invading areas with native plants and not establishing in unvegetated areas. Although flowering rush is found as deep as 4.5 m, it is most frequent at a depth of 1.3 m. We also examined the distribution of biomass and growth across a depth gradient from 0.3 to 3.0 m in 0.3-m intervals. At each 0.3-m interval, three biomass samples were collected at each of 10 transects for a total of 30 samples per depth interval or 300 biomass samples. At each point, leaf height, emergent leaf height, water depth, number of ramets, and number of rhizome buds were counted. Biomass samples were collected in a 0.018-m2 core sampler, sorted to shoots and belowground biomass. We found that flowering rush height and biomass peaked at 1.3 m and declined with greater depth. Bud density was negatively related to water depth. Bud density averaged 300 buds m–2, which was three times the average ramet density (100 ramets m–2).
Comprehensive characterization of materials suggests measuring their different properties for optimal use in technological applications and this task becomes more challenging as size of related structures decreases and their complexity increases. At smaller scales Atomic Force Microscopy (AFM) enables visualization of structures and quantitative measurements of their mechanical and electric properties. So far, several properties such as elastic modulus and work of adhesion, surface potential and dielectric permittivity can be extracted from the results obtained in various AFM modes. More complicated are the AFM experiments and their analysis in case of viscoelastic, piezoelectric and thermoelectric properties. Several examples of quantitative characterization of neat polymers will be given. In many cases the dissimilarity of the components’ properties is employed for their recognition in heterogeneous systems such as polymer blends, block copolymers and metal alloys. The confined geometries, which are common for small-scale structures, might restrict such identification and a combination of AFM with spectral methods such as Raman scattering will be helpful. Achievements and challenges of compositional mapping will be illustrated on several complex materials.
Guanidinoacetic acid (GAA) is the natural biosynthetic precursor of creatine, in a metabolic reaction that requires only a methyl group transfer. The use of GAA as a food additive for restoring creatine load in human tissues is rather unexplored and data on efficacy and safety are limited. In particular, an increase in serum homocysteine after GAA administration can be regarded as critical and should be prevented. The present study evaluated the effects of orally administered GAA with and without methyl group donors on serum and urine creatine concentrations, and the occurrence of adverse events during an intervention in healthy human subjects. A total of twenty male and female volunteers were randomised in a double-blind design to receive either GAA (2·4 g/d) or GAA with methyl donors (2·4 g/d of GAA and 1·6 g/d of betaine HCl, 5 μg/d of vitamin B12, 10 mg/d of vitamin B6 and 600 μg/d of folic acid) by oral administration for 8 weeks. Serum and urine creatine increased significantly from before to after administration in both groups (P< 0·001). The proportion of participants who reported minor adverse events was 33·3 % in the GAA group, and 10·0 % in the GAA with methyl donors group (P= 0·30). Hyperhomocysteinaemia was found in 55·6 % of participants supplemented with GAA, while no participant experienced hyperhomocysteinaemia in the group supplemented with GAA and methyl donors (P= 0·01). In summary, both interventions strongly influenced creatine metabolism, resulting in a significant increase in fasting serum creatine. The concomitant supplementation of methyl donors along with GAA largely precluded the elevation of serum homocysteine caused by GAA administration alone.
This chapter provides an overview of Earth system models, the various model ‘flavours’, their state of development including model evaluation, benchmarking and optimization against observational data and their application to climate change issues.
The Earth system can be conceptualized as a suite of interacting physical, chemical, biological and anthropogenic processes that regulate the planet’s low of matter and energy. Earth system models (ESMs; Box 5.1 ) are built to mirror these processes. In fact, ESMs are the only tool available to the scientific community to investigate the system properties of the Earth, as we do not have an alternative planet to manipulate that could serve as a scientist’s laboratory.
The term ‘Earth system model’ is commonly used to describe coupled land–ocean–atmosphere models that include interactive biogeochemical components. Such models have developed progressively from the physical climate models first created in the 1960s and 1970s. Conventional climate models apply physical laws to simulate the general circulation of atmosphere and ocean. As our understanding of the natural and anthropogenic controls on climate has grown, and given the steady advances in computing power, global climate models have been extended to include more comprehensive representations of biological and geochemical processes, involving the addition of the various interacting components of the Earth system with their own feedback mechanisms. Figure 5.1 shows the conceptual differences between a conventional global coupled atmosphere–ocean general circulation model (AOGCM) and an ESM. In terms of the coupling between components, ESMs are more complex, and they have correspondingly higher computational demands.