The MRC trial of assessment and management of older people in the community: objectives, design and interventions [ISRCTN23494848].

BACKGROUND: The benefit of regular multidimensional assessment of older people remains controversial. The majority of trials have been too small to produce adequate evidence to inform policy. Despite the lack of a firm evidence base, UK primary care practitioners (general practitioners) are required to offer an annual health check to patients aged 75 years and over. DESIGN: Cluster-randomised factorial trial in primary care comparing a package of assessments (i) universal versus targeted assessment and (ii) management by the primary care team (PC) or a multidisciplinary geriatric assessment team (GM). The unit of randomization is the general practice. METHODS: Older people aged 75 and over eligible for the over 75s health check and excluding those in nursing homes or terminally ill were invited to participate. All participants receive a brief assessment covering all areas of the over 75s check. In the universal arm all participants also receive a detailed health and social assessment by a study nurse while in the targeted arm only participants with a pre-determined number and range of problems at the brief assessment go on to have the detailed assessment. The study nurse follows a standard protocol based on results and responses in the detailed assessment to make referrals to (i) the randomised management team (PC or GM) (ii) other medical services, health care workers or agencies (iii) emergency referrals to the GP. The main outcomes are mortality, hospital and institutional admissions and quality of life. 106 practices and 33,000 older people have been recruited to the trial

A Novel Approach for the Colour Deconvolution of Multiple Histological Stains

Colour Deconvolution (CD) is a commonly used tool in histological medical image analysis that separates histochemical or immunohistochemical stains into their component parts. Traditional CD uses matrix inversion to change the Red, Green and Blue (RGB) channels of an image into a new domain that is representative of reference colours but this limits the total number of stains that can be separated. This is problematic for histological staining protocols that use more than three stains, such as FAST staining. This limitation has restricted the use of multicolour staining in light microscopy. To address this issue, this paper evaluates the use of Non Negative Matrix Factorisation (NNMF) and Non Negative Least Squares (NNLS) to enable the decomposition of multistained histological sections into its source components. It will be shown that NNLS is better suited to imaging modalities such as Whole Slide Image (WSI) scanners and that the multiple staining metrics produced from a single sample are analogous to those generated by applying single reagents to contiguous tissue sections

Stain guided mean-shift filtering in automatic detection of human tissue nuclei

Background: As a critical technique in a digital pathology laboratory, automatic nuclear detection has been investigated for more than one decade. Conventional methods work on the raw images directly whose color/intensity homogeneity within tissue/cell areas are undermined due to artefacts such as uneven staining, making the subsequent binarization process prone to error. This paper concerns detecting cell nuclei automatically from digital pathology images by enhancing the color homogeneity as a pre-processing step. Methods: Unlike previous watershed based algorithms relying on post-processing of the watershed, we present a new method that incorporates the staining information of pathological slides in the analysis. This pre-processing step strengthens the color homogeneity within the nuclear areas as well as the background areas, while keeping the nuclear edges sharp. Proof of convergence for the proposed algorithm is also provided. After pre-processing, Otsu's threshold is applied to binarize the image, which is further segmented via watershed. To keep a proper compromise between removing overlapping and avoiding over-segmentation, a naive Bayes classifier is designed to refine the splits suggested by the watershed segmentation. Results: The method is validated with 10 sets of 1000 × 1000 pathology images of lymphoma from one digital slide. The mean precision and recall rates are 87% and 91%, corresponding to a mean F-score equal to 89%. Standard deviations for these performance indicators are 5.1%, 1.6% and 3.2% respectively. Conclusion: The precision/recall performance obtained indicates that the proposed method outperforms several other alternatives. In particular, for nuclear detection, stain guided mean-shift (SGMS) is more effective than the direct application of mean-shift in pre-processing. Our experiments also show that pre-processing the digital pathology images with SGMS gives better results than conventional watershed algorithms. Nevertheless, as only one type of tissue is tested in this paper, a further study is planned to enhance the robustness of the algorithm so that other types of tissues/stains can also be processed reliably

Multi-touch table technology for enhancing collaborative programming and learning

Our research goal is to provide a new use for multi-touch table technology by developing new resource software to be used as an environment for collaborative pair programming. Such a project will yield new opportunities and provide improved quality within the field of collaborative learning (Nosek 1998; Williams et al., 2000a, 2000b; Williams et al., 2001; Cockburn et al., 2000; Mcdowell et al. 2002; Gallis et al. 2003; Cao and Xu, 2005; Brereton et al., 2009; Sanjay and Goel and Kathuria, 2010; Rick et al., 2011). For instance, the proposed project (1) is time-effective and leads to a better product, (2) is more enjoyable for developers, (3) may increase work satisfaction, (4) promotes student learning, (5) leads to better student activity engagement, (6) contributes to enhancing the level of student understanding with regard to programming modules, which makes students more confident in their work and more positive about programming and, finally, and (7) supports the awareness of others’ actions and the ability to support concurrent input; it also encourages the development of problem-solving skills, efficiency, quality and teamwork. The project begins with a survey of the available tools for collaborative pair programming, such as Scratch Programming (Scratch, 2014), and then these tools will be evaluated to determine their suitability for use in multi-touch tables. The most suitable tool will then be selected for development to be run on a multi-touch table. Alternatively, new resource software will be created for the project. In the final stage, the usability of new software, in terms of collaborative pair programming, will be evaluated

Using a multi-touch table to develop collaborative teaching programming resources in the new computing curriculum

Information and communication technology (ICT) has been questioned extensively throughout recent years and is often considered unsatisfactory and antiquated (Society, 2012). However, a new computing curriculum will be incorporated into school systems in order to replace existing frameworks. This new paradigm focuses heavily on programing and critical thinking, largely at the primary level of schooling. The existing ICT curriculum was considered insufficient and unsatisfactory, consequently highlighting the need for change. Nonetheless, basic ICT applications need to be considered when producing new curriculum in order to expand on familiar principles that students utilize (Gov.uk, 2013). This project aims to develop a new resource to enhance collaborative programming in UK schools for pupils studying at Key Stage 3 level, i.e., 11–14 year olds. The project started with a review and evaluation of the available tools for collaborative pair programming, such as Scratch Programming (Scratch, 2014), in order to determine their suitability for use in multi-touch tables. Then, the tool Turtle Art (Turtle Art, 2014) was selected to receive further development to be run on a multi-touch table. In the final stage, the usability of the new software, in terms of collaborative pair programming, will be tested and evaluated against the project goals. The new resource software is intended to be used as an environment for collaborative learning and pair programming, and a number of studies have proven that these educational methods provide an improved quality of education within the curriculum of school systems (see, for example, Wilson et al., 1993; Yerion and Rinehart, 1995; and McKinney and Denton, 2006 for collaborative learning and Nosek, 1998; Williams et al., 2000a, 2000b; Cockburn et al., 2000; Williams et al., 2001; Mcdowell et al., 2002; Gallis et al., 2003; Cao and Xu, 2005; Brereton et al., 2009; Goel et al., 2010; Rick et al., 2011; and Harlow and Leak, 2014 for pair programming). Thus, the proposed resource software can be beneficial when used for collaborative learning and pair programming for many reasons such as the following: • It helps in collective decision-making and problem-solving, which leads to enhanced learning and development. • It focuses on the development of skills that are necessary for employment in contemporary industries. • It is more enjoyable for developers, increases work satisfaction, and promotes student learning. • It leads to better student activity engagement. • It contributes to enhancing the level of student understanding with regard to programming modules. • It makes students more confident in their work as well as more positive about programming. • It encourages the development of problem-solving aptitudes. • It provides more efficiency and quality in understanding the processes that one needs to go through in programing to solve problems. • It helps students create new ideas and ways to interact with new technologies. • It encourages participants to practice problem-solving skills in practical circumstances

Talking Head from Speech Audio using a Pre-trained Image Generator

We propose a novel method for generating high-resolution videos of talking-heads from speech audio and a single 'identity' image. Our method is based on a convolutional neural network model that incorporates a pre-trained StyleGAN generator. We model each frame as a point in the latent space of StyleGAN so that a video corresponds to a trajectory through the latent space. Training the network is in two stages. The first stage is to model trajectories in the latent space conditioned on speech utterances. To do this, we use an existing encoder to invert the generator, mapping from each video frame into the latent space. We train a recurrent neural network to map from speech utterances to displacements in the latent space of the image generator. These displacements are relative to the back-projection into the latent space of an identity image chosen from the individuals depicted in the training dataset. In the second stage, we improve the visual quality of the generated videos by tuning the image generator on a single image or a short video of any chosen identity. We evaluate our model on standard measures (PSNR, SSIM, FID and LMD) and show that it significantly outperforms recent state-of-the-art methods on one of two commonly used datasets and gives comparable performance on the other. Finally, we report on ablation experiments that validate the components of the model. The code and videos from experiments can be found at https://mohammedalghamdi.github.io/talking-heads-acm-mm

3D reconstruction of multiple stained histology images.

Three dimensional (3D) tissue reconstructions from the histology images with different stains allows the spatial alignment of structural and functional elements highlighted by different stains for quantitative study of many physiological and pathological phenomena. This has significant potential to improve the understanding of the growth patterns and the spatial arrangement of diseased cells, and enhance the study of biomechanical behavior of the tissue structures towards better treatments (e.g. tissue-engineering applications)

Validation of two generic patient-reported outcome measures in patients with type 2 diabetes

<p>Abstract</p> <p>Background</p> <p>Prior to using a generic patient-reported outcome measure (PRO), the measure should be validated within the target population. The purpose of the current study was to validate two generic measures in patients with type 2 diabetes.</p> <p>Methods</p> <p>Patients with type 2 diabetes in Scotland and England completed two generic measures: EQ-5D and Psychological General Well-Being Index (PGWB). Two diabetes-specific measures were administered: ADS and DSC-R. Analyses assessed reliability and validity.</p> <p>Results</p> <p>There were 130 participants (53 Scotland; 77 England; 64% male; mean age = 55.7 years). Responses on the EQ-5D and PGWB reflected moderate impairment consistent with previous diabetes samples: mean EQ-5D Index score, 0.75; EQ-5D VAS, 68.8; PGWB global score, 67.9. All scales of the PGWB demonstrated good internal consistency reliability (Cronbach's alpha = 0.77 to 0.97). The EQ-5D and PGWB demonstrated convergent validity through significant correlations with the ADS (r = 0.48 to 0.61), DSC-R scales (r = 0.33 to 0.81 except ophthalmology subscale), and Body Mass Index (r = 0.15 to 0.38). The EQ-5D and PGWB discriminated between groups of patients known to differ in diabetes-related characteristics (e.g., history of hypoglycemia).</p> <p>Conclusion</p> <p>Results support the use of the EQ-5D and PGWB among patients with type 2 diabetes, possibly in combination with condition-specific measures.</p

Is blood pressure reduction a valid surrogate endpoint for stroke prevention? an analysis incorporating a systematic review of randomised controlled trials, a by-trial weighted errors-in-variables regression, the surrogate threshold effect (STE) and the biomarker-surrogacy (BioSurrogate) evaluation schema (BSES)

<p>Abstract</p> <p>Background</p> <p>Blood pressure is considered to be a leading example of a valid surrogate endpoint. The aims of this study were to (i) formally evaluate systolic and diastolic blood pressure reduction as a surrogate endpoint for stroke prevention and (ii) determine what blood pressure reduction would predict a stroke benefit.</p> <p>Methods</p> <p>We identified randomised trials of at least six months duration comparing any pharmacologic anti-hypertensive treatment to placebo or no treatment, and reporting baseline blood pressure, on-trial blood pressure, and fatal and non-fatal stroke. Trials with fewer than five strokes in at least one arm were excluded. Errors-in-variables weighted least squares regression modelled the reduction in stroke as a function of systolic blood pressure reduction and diastolic blood pressure reduction respectively. The lower 95% prediction band was used to determine the minimum systolic blood pressure and diastolic blood pressure difference, the surrogate threshold effect (STE), below which there would be no predicted stroke benefit. The STE was used to generate the surrogate threshold effect proportion (STEP), a surrogacy metric, which with the R-squared trial-level association was used to evaluate blood pressure as a surrogate endpoint for stroke using the Biomarker-Surrogacy Evaluation Schema (BSES3).</p> <p>Results</p> <p>In 18 qualifying trials representing all pharmacologic drug classes of antihypertensives, assuming a reliability coefficient of 0.9, the surrogate threshold effect for a stroke benefit was 7.1 mmHg for systolic blood pressure and 2.4 mmHg for diastolic blood pressure. The trial-level association was 0.41 and 0.64 and the STEP was 66% and 78% for systolic and diastolic blood pressure respectively. The STE and STEP were more robust to measurement error in the independent variable than R-squared trial-level associations. Using the BSES3, assuming a reliability coefficient of 0.9, systolic blood pressure was a B + grade and diastolic blood pressure was an A grade surrogate endpoint for stroke prevention. In comparison, using the same stroke data sets, no STEs could be estimated for cardiovascular (CV) mortality or all-cause mortality reduction, although the STE for CV mortality approached 25 mmHg for systolic blood pressure.</p> <p>Conclusions</p> <p>In this report we provide the first surrogate threshold effect (STE) values for systolic and diastolic blood pressure. We suggest the STEs have face and content validity, evidenced by the inclusivity of trial populations, subject populations and pharmacologic intervention populations in their calculation. We propose that the STE and STEP metrics offer another method of evaluating the evidence supporting surrogate endpoints. We demonstrate how surrogacy evaluations are strengthened if formally evaluated within specific-context evaluation frameworks using the Biomarker- Surrogate Evaluation Schema (BSES3), and we discuss the implications of our evaluation of blood pressure on other biomarkers and patient-reported instruments in relation to surrogacy metrics and trial design.</p