1,008 research outputs found

    Antenatal couples' counselling in Uganda (ACCU): study protocol for a randomised controlled feasibility trial.

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    BACKGROUND: Common avoidable factors leading to maternal, perinatal and neonatal deaths include lack of birth planning (and delivery in an inappropriate place) and unmet need for contraception. Progress has been slow because routine antenatal care has focused only on women. Yet, in Uganda, many women first want the approval of their husbands. The World Health Organization recommends postpartum family planning (PPFP) as a critical component of health care. The aim of this trial is to test the feasibility of recruiting and retaining participants in a trial of a complex community-based intervention to provide counselling to antenatal couples in Uganda. METHODS: This is a two-group, non-blinded cluster-randomised controlled feasibility trial of a complex intervention. Primary health centres in Uganda will be randomised to receive the intervention or usual care provided by the Ministry of Health. The intervention consists of training village health teams to provide basic counselling to couples at home, encouraging men to accompany their wives to an antenatal clinic, and secondly of training health workers to provide information and counselling to couples at antenatal clinics, to facilitate shared decision-making on the most appropriate place of delivery, and postpartum contraception. We aim to recruit 2 health centres in each arm, each with 10 village health teams, each of whom will aim to recruit 35 pregnant women (a total of 700 women per arm). The village health teams will follow up and collect data on pregnant women in the community up to 12 months after delivery and will directly enter the data using the COSMOS software on a smartphone. DISCUSSION: This intervention addresses two key avoidable factors in maternal, perinatal and neonatal deaths (lack of family planning and inappropriate place of delivery). Determining the acceptability and feasibility of antenatal couples' counselling in this study will inform the design of a fully randomised controlled clinical trial. If this trial demonstrates the feasibility of recruitment and delivery, we will seek funding to conduct a fully powered trial of the complex intervention for improving uptake of birth planning and postpartum family planning in Uganda. TRIAL REGISTRATION: Pan African Clinical Trials Registry PACTR202102794681952 . Approved on 10 February 2021. ISRCTN Registry ISRCTN97229911. Registered on 23 September 2021

    Thermodynamic analysis of inverted bifurcation

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    We present a thermodynamic analysis of inverted bifurcation in binary mixtures heated from below. From this analysis it follows that an inverted bifurcation is caused by the competition between a stabilizing effect with a long relaxation time and a destabilizing effect with a short relaxation time. These conditions are precisely the same as those that give rise to overstability. This might explain why overstability and inverted bifurcation occur in the same systems

    Selecting patients for randomized trials: a systematic approach based on risk group

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    BACKGROUND: A key aspect of randomized trial design is the choice of risk group. Some trials include patients from the entire at-risk population, others accrue only patients deemed to be at increased risk. We present a simple statistical approach for choosing between these approaches. The method is easily adapted to determine which of several competing definitions of high risk is optimal. METHOD: We treat eligibility criteria for a trial, such as a smoking history, as a prediction rule associated with a certain sensitivity (the number of patients who have the event and who are classified as high risk divided by the total number patients who have an event) and specificity (the number of patients who do not have an event and who do not meet criteria for high risk divided by the total number of patients who do not have an event). We then derive simple formulae to determine the proportion of patients receiving intervention, and the proportion who experience an event, where either all patients or only those at high risk are treated. We assume that the relative risk associated with intervention is the same over all choices of risk group. The proportion of events and interventions are combined using a net benefit approach and net benefit compared between strategies. RESULTS: We applied our method to design a trial of adjuvant therapy after prostatectomy. We were able to demonstrate that treating a high risk group was superior to treating all patients; choose the optimal definition of high risk; test the robustness of our results by sensitivity analysis. Our results had a ready clinical interpretation that could immediately aid trial design. CONCLUSION: The choice of risk group in randomized trials is usually based on rather informal methods. Our simple method demonstrates that this decision can be informed by simple statistical analyses

    UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

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    Background: Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Results: Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. Conclusions: The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.The National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0310-1004)

    Multi-Gene Expression Predictors of Single Drug Responses to Adjuvant Chemotherapy in Ovarian Carcinoma: Predicting Platinum Resistance

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    Despite advances in radical surgery and chemotherapy delivery, ovarian cancer is the most lethal gynecologic malignancy. Standard therapy includes treatment with platinum-based combination chemotherapies yet there is no biomarker model to predict their responses to these agents. We here have developed and independently tested our multi-gene molecular predictors for forecasting patients' responses to individual drugs on a cohort of 55 ovarian cancer patients. To independently validate these molecular predictors, we performed microarray profiling on FFPE tumor samples of 55 ovarian cancer patients (UVA-55) treated with platinum-based adjuvant chemotherapy. Genome-wide chemosensitivity biomarkers were initially discovered from the in vitro drug activities and genomic expression data for carboplatin and paclitaxel, respectively. Multivariate predictors were trained with the cell line data and then evaluated with a historical patient cohort. For the UVA-55 cohort, the carboplatin, taxol, and combination predictors significantly stratified responder patients and non-responder patients (p = 0.019, 0.04, 0.014) with sensitivity = 91%, 96%, 93 and NPV = 57%, 67%, 67% in pathologic clinical response. The combination predictor also demonstrated a significant survival difference between predicted responders and non-responders with a median survival of 55.4 months vs. 32.1 months. Thus, COXEN single- and combination-drug predictors successfully stratified platinum resistance and taxane response in an independent cohort of ovarian cancer patients based on their FFPE tumor samples

    Foot health education for people with rheumatoid arthritis : the practitioner's perspective

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    Background: Patient education is considered to be a key role for podiatrists in the management of patients with rheumatoid arthritis (RA). Patient education has undoubtedly led to improved clinical outcomes, however no attempts have been made to optimise its content or delivery to maximise benefits within the context of the foot affected by rheumatoid arthritis. The aim of this study was to identify the nature and content of podiatrists' foot health education for people with RA. Any potential barriers to its provision were also explored. Methods: A focus group was conducted. The audio dialogue was recorded digitally, transcribed verbatim and analysed using a structured, thematic approach. The full transcription was verified by the focus group as an accurate account of what was said. The thematic analysis framework was verified by members of the research team to ensure validity of the data. Results: Twelve members (all female) of the north west Podiatry Clinical Effectiveness Group for Rheumatology participated. Six overarching themes emerged: (i) the essence of patient education; (ii) the content; (iii) patient-centred approach to content and timing; (iv) barriers to provision; (v) the therapeutic relationship; and (vi) tools of the trade. Conclusion: The study identified aspects of patient education that this group of podiatrists consider most important in relation to its: content, timing, delivery and barriers to its provision. General disease and foot health information in relation to RA together with a potential prognosis for foot health, the role of the podiatrist in management of foot health, and appropriate self-management strategies were considered to be key aspects of content, delivered according to the needs of the individual. Barriers to foot health education provision, including financial constraints and difficulties in establishing effective therapeutic relationships, were viewed as factors that strongly influenced foot health education provision. These data will contribute to the development of a patient-centred, negotiated approach to the provision of foot health education for people with RA

    Human α2β1HI CD133+VE epithelial prostate stem cells express low levels of active androgen receptor

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    Stem cells are thought to be the cell of origin in malignant transformation in many tissues, but their role in human prostate carcinogenesis continues to be debated. One of the conflicts with this model is that cancer stem cells have been described to lack androgen receptor (AR) expression, which is of established importance in prostate cancer initiation and progression. We re-examined the expression patterns of AR within adult prostate epithelial differentiation using an optimised sensitive and specific approach examining transcript, protein and AR regulated gene expression. Highly enriched populations were isolated consisting of stem (α(2)β(1)(HI) CD133(+VE)), transiently amplifying (α(2)β(1)(HI) CD133(-VE)) and terminally differentiated (α(2)β(1)(LOW) CD133(-VE)) cells. AR transcript and protein expression was confirmed in α(2)β(1)(HI) CD133(+VE) and CD133(-VE) progenitor cells. Flow cytometry confirmed that median (±SD) fraction of cells expressing AR were 77% (±6%) in α(2)β(1)(HI) CD133(+VE) stem cells and 68% (±12%) in α(2)β(1)(HI) CD133(-VE) transiently amplifying cells. However, 3-fold lower levels of total AR protein expression (peak and median immunofluorescence) were present in α(2)β(1)(HI) CD133(+VE) stem cells compared with differentiated cells. This finding was confirmed with dual immunostaining of prostate sections for AR and CD133, which again demonstrated low levels of AR within basal CD133(+VE) cells. Activity of the AR was confirmed in prostate progenitor cells by the expression of low levels of the AR regulated genes PSA, KLK2 and TMPRSS2. The confirmation of AR expression in prostate progenitor cells allows integration of the cancer stem cell theory with the established models of prostate cancer initiation based on a functional AR. Further study of specific AR functions in prostate stem and differentiated cells may highlight novel mechanisms of prostate homeostasis and insights into tumourigenesis

    The geography of recent genetic ancestry across Europe

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    The recent genealogical history of human populations is a complex mosaic formed by individual migration, large-scale population movements, and other demographic events. Population genomics datasets can provide a window into this recent history, as rare traces of recent shared genetic ancestry are detectable due to long segments of shared genomic material. We make use of genomic data for 2,257 Europeans (the POPRES dataset) to conduct one of the first surveys of recent genealogical ancestry over the past three thousand years at a continental scale. We detected 1.9 million shared genomic segments, and used the lengths of these to infer the distribution of shared ancestors across time and geography. We find that a pair of modern Europeans living in neighboring populations share around 10-50 genetic common ancestors from the last 1500 years, and upwards of 500 genetic ancestors from the previous 1000 years. These numbers drop off exponentially with geographic distance, but since genetic ancestry is rare, individuals from opposite ends of Europe are still expected to share millions of common genealogical ancestors over the last 1000 years. There is substantial regional variation in the number of shared genetic ancestors: especially high numbers of common ancestors between many eastern populations likely date to the Slavic and/or Hunnic expansions, while much lower levels of common ancestry in the Italian and Iberian peninsulas may indicate weaker demographic effects of Germanic expansions into these areas and/or more stably structured populations. Recent shared ancestry in modern Europeans is ubiquitous, and clearly shows the impact of both small-scale migration and large historical events. Population genomic datasets have considerable power to uncover recent demographic history, and will allow a much fuller picture of the close genealogical kinship of individuals across the world.Comment: Full size figures available from http://www.eve.ucdavis.edu/~plralph/research.html; or html version at http://ralphlab.usc.edu/ibd/ibd-paper/ibd-writeup.xhtm
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