171 research outputs found
Management of diabetic neuropathic foot and ankle malunions and nonunions
The management of diabetic neuropathic foot and ankle malunions and/or nonunions is often complicated by the presence of broken or loosened hardware, Charcot joints, infection, osteomyelitis, avascular bone necrosis, unstable deformities, bone loss, disuse and pathologic osteopenia, and ulcerations. The author discusses a rational approach to functional limb salvage with various surgical techniques that are aimed at achieving anatomic alignment, long-term osseous stability, and adequate soft tissue coverage. Emphasis is placed on techniques to overcome the inherent challenges that are encountered when surgically managing a diabetic nonunion and/or malunion. Particular attention is directed to the management of deep infection and Charcot neuroarthropathy in the majority of the cases presented
Factor structure and construct validity of the Adult Social Care Outcomes Toolkit for Carers (ASCOT-Carer)
Background: The ASCOT-Carer is a self-report instrument designed to measure social care-related quality of life (SCRQoL). This article presents the psychometric testing and validation of the ASCOT-Carer four response-level interview (INT4) in a sample of unpaid carers of adults who receive publicly-funded social care services in England.
Methods: Unpaid carers were identified through a survey of users of publicly-funded social care services in England. 387 carers completed a face-to-face or telephone interview. Data on variables hypothesised to be related to SCRQoL (for example, characteristics of the carer, cared-for person and care situation) and measures of carer experience, strain, health-related quality of life and overall QoL were collected. Relationships between these variables and overall SCRQoL score were evaluated through correlation, ANOVA and regression analysis to test the construct validity of the scale. Internal reliability was assessed using Cronbach’s alpha and feasibility by the number of missing responses.
Results: The construct validity was supported by statistically significant relationships between SCRQoL and scores on instruments of related constructs, as well as with characteristics of the carer and care recipient in univariate and multivariate analyses. A Cronbach’s alpha of 0.87 (7 items) indicates that the internal reliability of the instrument is satisfactory and a low number of missing responses (<1%) indicates a high level of acceptance.
Conclusions: The results provide evidence to support the construct validity, factor structure, internal reliability and feasibility of the ASCOT-Carer INT4 as an instrument for measuring social care-related quality of life of unpaid carers who care for adults with a variety of long-term conditions, disability or problems related to old age
An empirical Bayes model for gene expression and methylation profiles in antiestrogen resistant breast cancer
<p>Abstract</p> <p>Background</p> <p>The nuclear transcription factor estrogen receptor alpha (ER-alpha) is the target of several antiestrogen therapeutic agents for breast cancer. However, many ER-alpha positive patients do not respond to these treatments from the beginning, or stop responding after being treated for a period of time. Because of the association of gene transcription alteration and drug resistance and the emerging evidence on the role of DNA methylation on transcription regulation, understanding of these relationships can facilitate development of approaches to re-sensitize breast cancer cells to treatment by restoring DNA methylation patterns.</p> <p>Methods</p> <p>We constructed a hierarchical empirical Bayes model to investigate the simultaneous change of gene expression and promoter DNA methylation profiles among wild type (WT) and OHT/ICI resistant MCF7 breast cancer cell lines.</p> <p>Results</p> <p>We found that compared with the WT cell lines, almost all of the genes in OHT or ICI resistant cell lines either do not show methylation change or hypomethylated. Moreover, the correlations between gene expression and methylation are quite heterogeneous across genes, suggesting the involvement of other factors in regulating transcription. Analysis of our results in combination with H3K4me2 data on OHT resistant cell lines suggests a clear interplay between DNA methylation and H3K4me2 in the regulation of gene expression. For hypomethylated genes with alteration of gene expression, most (~80%) are up-regulated, consistent with current view on the relationship between promoter methylation and gene expression.</p> <p>Conclusions</p> <p>We developed an empirical Bayes model to study the association between DNA methylation in the promoter region and gene expression. Our approach generates both global (across all genes) and local (individual gene) views of the interplay. It provides important insight on future effort to develop therapeutic agent to re-sensitize breast cancer cells to treatment.</p
An open toolkit for tracking open science partnership implementation and impact.
Serious concerns about the way research is organized collectively are increasingly being raised. They include the escalating costs of research and lower research productivity, low public trust in researchers to report the truth, lack of diversity, poor community engagement, ethical concerns over research practices, and irreproducibility. Open science (OS) collaborations comprise of a set of practices including open access publication, open data sharing and the absence of restrictive intellectual property rights with which institutions, firms, governments and communities are experimenting in order to overcome these concerns. We gathered two groups of international representatives from a large variety of stakeholders to construct a toolkit to guide and facilitate data collection about OS and non-OS collaborations. Ultimately, the toolkit will be used to assess and study the impact of OS collaborations on research and innovation. The toolkit contains the following four elements: 1) an annual report form of quantitative data to be completed by OS partnership administrators; 2) a series of semi-structured interview guides of stakeholders; 3) a survey form of participants in OS collaborations; and 4) a set of other quantitative measures best collected by other organizations, such as research foundations and governmental or intergovernmental agencies. We opened our toolkit to community comment and input. We present the resulting toolkit for use by government and philanthropic grantors, institutions, researchers and community organizations with the aim of measuring the implementation and impact of OS partnership across these organizations. We invite these and other stakeholders to not only measure, but to share the resulting data so that social scientists and policy makers can analyse the data across projects
Influence of folate status on genomic DNA methylation in colonic mucosa of subjects without colorectal adenoma or cancer
DNA hypomethylation may increase the risk of colorectal cancer. The main aim of this study was to assess the influence of folate status (serum and erythrocyte folate and plasma homocysteine concentrations) on DNA methylation. Methylenetetrahydrofolate reductase (MTHFR 677C → T and 1298A → C), methionine synthase (MS 2756A → G) and cystathionine synthase (CBS 844ins68) polymorphisms were measured to account for potential confounding effects on folate status and DNA methylation. A total of 68 subjects (33 men and 35 women, 36–78 years) free from colorectal polyps or cancer were recruited in a cross-sectional study. Tissue biopsies were obtained at colonoscopy for the determination of DNA methylation in colonic mucosa using an in vitro radiolabelled methyl acceptance assay. Serum and erythrocyte folate were inversely correlated with plasma homocysteine (r=−0.573, P<0.001 and r=−0.307, P=0.01 respectively) and DNA hypomethylation in colonic mucosa (r=−0.311, P=0.01 and r=−0.356, P=0.03). After adjusting for gender, age, body mass index, smoking and genotype, there were weak negative associations between serum and erythrocyte folate and colonic DNA hypomethylation (P=0.07 and P=0.08, respectively)
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