Risk prediction models for colorectal cancer in people with symptoms: a systematic review

Abstract Background Colorectal cancer (CRC) is the fourth leading cause of cancer-related death in Europe and the United States. Detecting the disease at an early stage improves outcomes. Risk prediction models which combine multiple risk factors and symptoms have the potential to improve timely diagnosis. The aim of this review is to systematically identify and compare the performance of models that predict the risk of primary CRC among symptomatic individuals. Methods We searched Medline and EMBASE to identify primary research studies reporting, validating or assessing the impact of models. For inclusion, models needed to assess a combination of risk factors that included symptoms, present data on model performance, and be applicable to the general population. Screening of studies for inclusion and data extraction were completed independently by at least two researchers. Results Twelve thousand eight hundred eight papers were identified from the literature search and three through citation searching. 18 papers describing 15 risk models were included. Nine were developed in primary care populations and six in secondary care. Four had good discrimination (AUROC > 0.8) in external validation studies, and sensitivity and specificity ranged from 0.25 and 0.99 to 0.99 and 0.46 depending on the cut-off chosen. Conclusions Models with good discrimination have been developed in both primary and secondary care populations. Most contain variables that are easily obtainable in a single consultation, but further research is needed to assess clinical utility before they are incorporated into practice

Risk prediction models for colorectal cancer in people with symptoms: a systematic review

Abstract Background Colorectal cancer (CRC) is the fourth leading cause of cancer-related death in Europe and the United States. Detecting the disease at an early stage improves outcomes. Risk prediction models which combine multiple risk factors and symptoms have the potential to improve timely diagnosis. The aim of this review is to systematically identify and compare the performance of models that predict the risk of primary CRC among symptomatic individuals. Methods We searched Medline and EMBASE to identify primary research studies reporting, validating or assessing the impact of models. For inclusion, models needed to assess a combination of risk factors that included symptoms, present data on model performance, and be applicable to the general population. Screening of studies for inclusion and data extraction were completed independently by at least two researchers. Results Twelve thousand eight hundred eight papers were identified from the literature search and three through citation searching. 18 papers describing 15 risk models were included. Nine were developed in primary care populations and six in secondary care. Four had good discrimination (AUROC > 0.8) in external validation studies, and sensitivity and specificity ranged from 0.25 and 0.99 to 0.99 and 0.46 depending on the cut-off chosen. Conclusions Models with good discrimination have been developed in both primary and secondary care populations. Most contain variables that are easily obtainable in a single consultation, but further research is needed to assess clinical utility before they are incorporated into practice

Modelling Herschel observations of infrared-dark clouds in the Hi-GAL survey

We demonstrate the use of the 3D Monte Carlo radiative transfer code PHAETHON to model infrared-dark clouds (IRDCs) that are externally illuminated by the interstellar radiation field (ISRF). These clouds are believed to be the earliest observed phase of high-mass star formation, and may be the high-mass equivalent of lower-mass prestellar cores. We model three different cases as examples of the use of the code, in which we vary the mass, density, radius, morphology and internal velocity field of the IRDC. We show the predicted output of the models at different wavelengths chosen to match the observing wavebands of Herschel and Spitzer. For the wavebands of the long- wavelength SPIRE photometer on Herschel, we also pass the model output through the SPIRE simulator to generate output images that are as close as possible to the ones that would be seen using SPIRE. We then analyse the images as if they were real observations, and compare the results of this analysis with the results of the radiative transfer models. We find that detailed radiative transfer modelling is necessary to accurately determine the physical parameters of IRDCs (e.g. dust temperature, density profile). This method is applied to study G29.55+00.18, an IRDC observed by the Herschel Infrared Galactic Plane survey (Hi-GAL), and in the future it will be used to model a larger sample of IRDCs from the same survey.Comment: MNRAS accepted, High resolution paper available at http://www.astro.cardiff.ac.uk/pub/Dimitrios.Stamatellos/Publications.htm

A curcumin direct protein biosensor for cell-free prototyping

In synthetic biology, biosensors are routinely coupled with a gene expression system for detecting small molecules and physical signals. We reveal a fluorescent complex, based on the interaction of an coli double bond reductase ( CurA), as a detection unit with its substrate curcumin-we call this a direct protein (DiPro) biosensor. Using a cell-free synthetic biology approach, we use the CurA DiPro biosensor to fine tune 10 reaction parameters (cofactor, substrate, and enzyme levels) for cell-free curcumin biosynthesis, assisted through acoustic liquid handling robotics. Overall, we increase CurA-curcumin DiPro fluorescence within cell-free reactions by 78-fold. This finding adds to the growing family of protein-ligand complexes that are naturally fluorescent and potentially exploitable for a range of applications, including medical imaging to engineering high-value chemicals

Nursing Care for Pregnant Adolescents

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73476/1/0884217503252191.pd

The ADDITION-Cambridge trial protocol: a cluster -- randomised controlled trial of screening for type 2 diabetes and intensive treatment for screen-detected patients.

BACKGROUND: The increasing prevalence of type 2 diabetes poses a major public health challenge. Population-based screening and early treatment for type 2 diabetes could reduce this growing burden. However, the benefits of such a strategy remain uncertain. METHODS AND DESIGN: The ADDITION-Cambridge study aims to evaluate the effectiveness and cost-effectiveness of (i) a stepwise screening strategy for type 2 diabetes; and (ii) intensive multifactorial treatment for people with screen-detected diabetes in primary care. 63 practices in the East Anglia region participated. Three undertook the pilot study, 33 were allocated to three groups: no screening (control), screening followed by intensive treatment (IT) and screening plus routine care (RC) in an unbalanced (1:3:3) randomisation. The remaining 27 practices were randomly allocated to IT and RC. A risk score incorporating routine practice data was used to identify people aged 40-69 years at high-risk of undiagnosed diabetes. In the screening practices, high-risk individuals were invited to take part in a stepwise screening programme. In the IT group, diabetes treatment is optimised through guidelines, target-led multifactorial treatment, audit, feedback, and academic detailing for practice teams, alongside provision of educational materials for newly diagnosed participants. Primary endpoints are modelled cardiovascular risk at one year, and cardiovascular mortality and morbidity at five years after diagnosis of diabetes. Secondary endpoints include all-cause mortality, development of renal and visual impairment, peripheral neuropathy, health service costs, self-reported quality of life, functional status and health utility. Impact of the screening programme at the population level is also assessed through measures of mortality, cardiovascular morbidity, health status and health service use among high-risk individuals. DISCUSSION: ADDITION-Cambridge is conducted in a defined high-risk group accessible through primary care. It addresses the feasibility of population-based screening for diabetes, as well as the benefits and costs of screening and intensive multifactorial treatment early in the disease trajectory. The intensive treatment algorithm is based on evidence from studies including individuals with clinically diagnosed diabetes and the education materials are informed by psychological theory. ADDITION-Cambridge will provide timely evidence concerning the benefits of early intensive treatment and will inform policy decisions concerning screening for type 2 diabetes. TRIAL REGISTRATION: Current Controlled trials ISRCTN86769081.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Liquid racism and the Danish Prophet Muhammad cartoons

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2010 The Author.This article examines reactions to the October 2005 publication of the Prophet Muhammad cartoons in the Danish newspaper Jyllands-Posten. It does so by using the concept of ‘liquid racism’. While the controversy arose because it is considered blasphemous by many Muslims to create images of the Prophet Muhammad, the article argues that the meaning of the cartoons is multidimensional, that their analysis is significantly more complex than most commentators acknowledge, and that this complexity can best be addressed via the concept of liquid racism. The article examines the liquidity of the cartoons in relation to four readings. These see the cartoons as: (1) a criticism of Islamic fundamentalism; (2) blasphemous images; (3) Islamophobic and racist; and (4) satire and a defence of freedom of speech. Finally, the relationship between postmodernity and the rise of fundamentalism is discussed because the cartoons, reactions to them, and Islamic fundamentalism, all contain an important postmodern dimension.ESR

Preorganized tridentate analogues of mixed hydroxyoxime/carboxylate nickel extractants

Simple tridentate ligands can operate as Ni-extractants in the pH-dependent process: 2LHorg + NiSO4 ⇌ [(L)2Ni]org + H2SO4.</p

Risk-Driven Design Processes: Balancing Efficiency with Resilience in Product Design

Current design methods and approaches focus on increasing the efficiency of the product design system by, for example, eliminating waste and focusing on value creation. However, continuing failures in the development of complex, large scale products and systems point towards weaknesses in the existing approaches. We argue that product development organizations are hindered by the many uncertainties that are inherent in the process. Common management heuristics ignore uncertainty and thus overly simplify the decision making process. Creating transparency regarding uncertainties and the associated risks (i.e. effect of uncertainties on design objectives) is not seen as an explicit priority. Consequently organizations are unable to balance risk and return in their development choices. Product development processes do not emphasize reduction of risks, particularly those risks that are apparent early in the process. In addition, the resilience of the PD system, i.e. its ability to deliver on-target results under uncertainty, is not deliberately designed to match the level of residual uncertainty. This chapter introduces the notion of Risk-Driven Design and its four principles of 1. Creating transparency regarding design risks; 2. Risk-driven decision making; 3. Minimizing uncertainty; and 4. Creating resilience.Massachusetts Institute of Technology. Lean Advancement InitiativeCenter for Clean Water and Clean Energy at MIT and KFUP