Logistic regression has similar performance to optimised machine learning algorithms in a clinical setting: application to the discrimination between type 1 and type 2 diabetes in young adults

This is the final version. Available from the publisher via the DOI in this record.The data that support the findings of this study are available from University of Exeter Medical School/Oxford University but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of University of Exeter Medical School/Oxford University. R code is made available in supplementary file (see Additional file 2).Background: There is much interest in the use of prognostic and diagnostic prediction models in all areas of clinical medicine. The use of machine learning to improve prognostic and diagnostic accuracy in this area has been increasing at the expense of classic statistical models. Previous studies have compared performance between these two approaches but their findings are inconsistent and many have limitations. We aimed to compare the discrimination and calibration of seven models built using logistic regression and optimised machine learning algorithms in a clinical setting, where the number of potential predictors is often limited, and externally validate the models. Methods: We trained models using logistic regression and six commonly used machine learning algorithms to predict if a patient diagnosed with diabetes has type 1 diabetes (versus type 2 diabetes). We used seven predictor variables (age, BMI, GADA islet-autoantibodies, sex, total cholesterol, HDL cholesterol and triglyceride) using a UK cohort of adult participants (aged 18–50 years) with clinically diagnosed diabetes recruited from primary and secondary care (n = 960, 14% with type 1 diabetes). Discrimination performance (ROC AUC), calibration and decision curve analysis of each approach was compared in a separate external validation dataset (n = 504, 21% with type 1 diabetes). Results: Average performance obtained in internal validation was similar in all models (ROC AUC ≥ 0.94). In external validation, there were very modest reductions in discrimination with AUC ROC remaining ≥ 0.93 for all methods. Logistic regression had the numerically highest value in external validation (ROC AUC 0.95). Logistic regression had good performance in terms of calibration and decision curve analysis. Neural network and gradient boosting machine had the best calibration performance. Both logistic regression and support vector machine had good decision curve analysis for clinical useful threshold probabilities. Conclusion: Logistic regression performed as well as optimised machine algorithms to classify patients with type 1 and type 2 diabetes. This study highlights the utility of comparing traditional regression modelling to machine learning, particularly when using a small number of well understood, strong predictor variables.National Institute for Health Research (NIHR

Distributing workflows over a ubiquitous P2P network

This paper discusses issues in the distribution of bundled workflows across ubiquitous peer-to-peer networks for the application of music information retrieval. The underlying motivation for this work is provided by the DART project, which aims to develop a novel music recommendation system by gathering statistical data using collaborative filtering techniques and the analysis of the audio itsel, in order to create a reliable and comprehensive database of the music that people own and which they listen to. To achieve this, the DART scientists creating the algorithms need the ability to distribute the Triana workflows they create, representing the analysis to be performed, across the network on a regular basis (perhaps even daily) in order to update the network as a whole with new workflows to be executed for the analysis. DART uses a similar approach to BOINC but differs in that the workers receive input data in the form of a bundled Triana workflow, which is executed in order to process any MP3 files that they own on their machine. Once analysed, the results are returned to DART's distributed database that collects and aggregates the resulting information. DART employs the use of package repositories to decentralise the distribution of such workflow bundles and this approach is validated in this paper through simulations that show that suitable scalability is maintained through the system as the number of participants increases. The results clearly illustrate the effectiveness of the approach

Improving marine disease surveillance through sea temperature monitoring, outlooks and projections

To forecast marine disease outbreaks as oceans warm requires new environmental surveillance tools. We describe an iterative process for developing these tools that combines research, development and deployment for suitable systems. The first step is to identify candidate host-pathogen systems. The 24 candidate systems we identified include sponges, corals, oysters, crustaceans, sea stars, fishes and sea grasses (among others). To illustrate the other steps, we present a case study of epizootic shell disease (ESD) in the American lobster. Increasing prevalence of ESD is a contributing factor to lobster fishery collapse in southern New England (SNE), raising concerns that disease prevalence will increase in the northern Gulf of Maine under climate change. The lowest maximum bottom temperature associated with ESD prevalence in SNE is 12 degrees C. Our seasonal outlook for 2015 and long-term projections show bottom temperatures greater than or equal to 12 degrees C may occur in this and coming years in the coastal bays of Maine. The tools presented will allow managers to target efforts to monitor the effects of ESD on fishery sustainability and will be iteratively refined. The approach and case example highlight that temperature-based surveillance tools can inform research, monitoring and management of emerging and continuing marine disease threats

Irresponsiveness of two retinoblastoma cases to conservative therapy correlates with up- regulation of hERG1 channels and of the VEGF-A pathway

<p>Abstract</p> <p>Background</p> <p>Treatment strategies for Retinoblastoma (RB), the most common primary intraocular tumor in children, have evolved over the past few decades and chemoreduction is currently the most popular treatment strategy. Despite success, systemic chemotherapeutic treatment has relevant toxicity, especially in the pediatric population. Antiangiogenic therapy has thus been proposed as a valuable alternative for pediatric malignancies, in particolar RB. Indeed, it has been shown that vessel density correlates with both local invasive growth and presence of metastases in RB, suggesting that angiogenesis could play a pivotal role for both local and systemic invasive growth in RB. We present here two cases of sporadic, bilateral RB that did not benefit from the conservative treatment and we provide evidence that the VEGF-A pathway is significantly up-regulated in both RB cases along with an over expression of hERG1 K⁺channels.</p> <p>Case presentation</p> <p>Two patients showed a sporadic, bilateral RB, classified at Stage II of the Reese-Elsworth Classification. Neither of them got benefits from conservative treatment, and the two eyes were enucleated. In samples from both RB cases we studied the VEGF-A pathway: VEGF-A showed high levels in the vitreous, the <it>vegf-a, flt-1, kdr</it>, and <it>hif1-α </it>transcripts were over-expressed. Moreover, both the transcripts and proteins of the hERG1 K⁺channels turned out to be up-regulated in the two RB cases compared to the non cancerous retinal tissue.</p> <p>Conclusions</p> <p>We provide evidence that the VEGF-A pathway is up-regulated in two particular aggressive cases of bilateral RB, which did not experience any benefit from conservative treatment, showing the overexpression of the <it>vegf-a</it>, <it>flt-1</it>, <it>kdr </it>and <it>hif1-α </it>transcripts and the high secretion of VEGF-A. Moreover we also show for the first time that the <it>herg1 </it>gene transcripts and protein are over expressed in RB, as occurs in several aggressive tumors. These results further stress the relevance of the VEGF-A pathway in RB and the correlation with hERG1, making aggressive and recurrent RB cases good candidates for antiangiogenesis therapies based on the targeting of VEGF-A.</p

Laboratory studies on the effect of temperature on epizootic shell disease in the American lobster, Homarus americanus

Epizootic shell disease (ESD) is a persistent threat to the population of American lobsters, Homarus americanus H. Milne-Edwards, 1837, in Long Island Sound and off southern New England, USA. ESD is caused by a bacterial dysbiosis that occurs in association with increased water temperature and exposure to anthropogenic stressors. Temperature is a leading factor driving the severity and incidence of ESD. Our objective was to quantify disease progression and dynamics in relation to host molting and mortality at three rigorously controlled temperatures (6, 12, and 18 °C) over a 5–6-mo period. Lobsters were photographed at various time points and image analysis was used to examine changes in lesion development over time. The disease progressed at all three experimental temperatures, but it had a significantly faster growth rate at 18 °C. Mean progression rates varied from 8.6–10.4 mm2 d–1 at the lower temperatures to \u3e25.6 mm2 d–1 at 18 °C. The mean daily growth rates give conservative estimates for individual progression from light to moderate disease states; i.e., approximately 233 d at 6 °C and 95 d at 18 °C. We show that increased temperature leads to rapid progression of ESD, but individual variation, presumably modulated through immune defenses, can slow the disease and possibly enhance survival of affected lobsters

Qualitatively understanding patients' and health professionals' experiences of the BRECONDA breast reconstruction decision aid

Copyright © 2016 John Wiley & Sons, Ltd. Objective: Women diagnosed with breast cancer or ductal carcinoma in situ and those with a genetic susceptibility to developing this disease face the challenging decision of whether or not to undergo breast reconstruction following mastectomy. As part of a large randomized controlled trial, this qualitative study examined women's experiences of using the Breast RECONstruction Decision Aid (BRECONDA) and health professionals' feedback regarding the impact of this resource on patients' knowledge and decision making about breast reconstruction. Method: Semistructured interviews were conducted with women who accessed the BRECONDA intervention (N=36) and with their healthcare providers (N=6). All interviews were transcribed verbatim and subjected to thematic analysis by 3 independent coders. Results: Participants reported an overall positive impression, with all interviewees endorsing this decision aid as a useful resource for women considering reconstructive surgery. Thematic analysis of patient interviews revealed 4 themes: overall impressions and aesthetics; personal relevance and utility; introducing BRECONDA; and advantages and suggested improvements. Analysis of health professionals' interviews also revealed 4 themes: need for BRECONDA, impact of BRECONDA, potential difficulties that may arise in using the decision aid, and recommending BRECONDA to patients. Patients indicated that they derived benefit from this resource at all stages of their decision-making process, with the greatest perceived benefit being for those early in their breast reconstruction journey. Conclusion: These findings support the use of BRECONDA as an adjunct to clinical consultation and other information sources

Facilitators and barriers to co-research by people with dementia and academic researchers: findings from a qualitative study

Background Public and patient involvement (PPI) is now established in dementia research. Barriers and facilitators to engagement from family carers and people in early stages of dementia have been explored. However, specific barriers and facilitators to co‐research with people with dementia have not previously been investigated. Objective To discover the facilitators of, and barriers to, involving people with dementia as co‐researchers, from the perspectives of people with dementia, gatekeepers (family caregivers, ethics committee members, service providers) and researchers. Design Thematic analysis of data from individual interviews about the co‐research experience. Results Four themes emerged from interviews with 19 participants (five people with dementia): “getting one's head round it” (assumptions about research and dementia; different forms of language); practicalities (eg transport; accessibility of communication); “this feeling of safety” (perceptions of danger, protectiveness and opportunities for building trust); and motivations (“making a difference” and “keeping doing”). Conclusions Findings both replicate and extend previous knowledge on PPI in dementia. Cognitive capacity of potential co‐researchers with dementia is only a part of the picture, with attitudes and expectations of researchers, gatekeepers and people with dementia also forming barriers. Researcher education, adequate resourcing, and both creativity and flexibility are needed to support recruitment of co‐researchers with dementia and to enable meaningful co‐research

Resonance fluorescence from a telecom-wavelength quantum dot

© 2016 Author(s).We report on resonance fluorescence from a single quantum dot emitting at telecom wavelengths. We perform high-resolution spectroscopy and observe the Mollow triplet in the Rabi regime - a hallmark of resonance fluorescence. The measured resonance-fluorescence spectra allow us to rule out pure dephasing as a significant decoherence mechanism in these quantum dots. Combined with numerical simulations, the experimental results provide robust characterisation of charge noise in the environment of the quantum dot. Resonant control of the quantum dot opens up new possibilities for the on-demand generation of indistinguishable single photons at telecom wavelengths as well as quantum optics experiments and direct manipulation of solid-state qubits in telecom-wavelength quantum dots