Electro-extractive fermentation for efficient biohydrogen production

Electrodialysis, an electrochemical membrane technique, was found to prolong and enhance the production of biohydrogen and purified organic acids via the anaerobic fermentation of glucose by Escherichia coli. Through the design of a model electrodialysis medium using cationic buffer, pH was precisely controlled electrokinetically, i.e. by the regulated extraction of acidic products with coulombic efficiencies of organic acid recovery in the range 50–70% maintained over continuous 30-day experiments. Contrary to\ud previous reports, E. coli produced H2 after aerobic growth in minimal medium without inducers and with a mixture of organic acids dominated by butyrate. The selective separation of organic acids from fermentation provides a potential nitrogen-free carbon source for further biohydrogen production in a parallel photofermentation. A parallel study incorporated this fermentation system into an integrated biohydrogen refinery (IBR) for the conversion of organic waste to hydrogen and energy

The Early Positive Approaches to Support (E-PAtS) study: study protocol for a feasibility cluster randomised controlled trial of a group programme (E-PAtS) for family caregivers of young children with intellectual disability

Background: Children with intellectual disability have an IQ < 70, associated deficits in adaptive skills and are at increased risk of having clinically concerning levels of behaviour problems. In addition, parents of children with intellectual disability are likely to report high levels of mental health and other psychological problems. The Early Positive Approaches to Support (E-PAtS) programme for family caregivers of young children (5 years and under) with intellectual and developmental disabilities is a group-based intervention which aims to enhance parental psychosocial wellbeing and service access and support positive development for children. The aim of this study is to assess the feasibility of delivering E-PAtS to family caregivers of children with intellectual disability by community parenting support service provider organisations. The study will inform a potential, definitive RCT of the effectiveness and cost-effectiveness of E-PAtS. / Methods: This study is a feasibility cluster randomised controlled trial, with embedded process evaluation. Up to 2 family caregivers will be recruited from 64 families with a child (18 months to 5 years) with intellectual disability at research sites in the UK. Participating families will be allocated to intervention: control on a 1:1 basis; intervention families will be offered the E-PAtS programme immediately, continuing to receive usual practice, and control participants will be offered the opportunity to attend the E-PAtS programme at the end of the follow-up period and will continue to receive usual practice. Data will be collected at baseline, 3 months post-randomisation and 12 months post-randomisation. The primary aim is to assess feasibility via the assessment of: recruitment of service provider organisations; participant recruitment; randomisation; retention; intervention adherence; intervention fidelity and the views of participants, intervention facilitators and service provider organisations regarding intervention delivery and study processes. The secondary aim is preliminary evaluation of a range of established outcome measures for individual family members, subsystem relationships and overall family functioning, plus additional health economic outcomes for inclusion in a future definitive trial. / Discussion: The results of this study will inform a potential future definitive trial, to evaluate the effectiveness and cost-effectiveness of the E-PAtS intervention to improve parental psychosocial wellbeing. Such a trial would have significant scientific impact internationally in the intellectual disability field. / Trial registration: ISRCTN7041947

Early Positive Approaches to Support (E-PAtS) for Families of Young Children With Intellectual Disability: A Feasibility Randomised Controlled Trial

Background: Parents of children with intellectual disabilities are likely to experience poorer mental well-being and face challenges accessing support. Early Positive Approaches to Support (E-PAtS) is a group-based programme, co-produced with parents and professionals, based on existing research evidence and a developmental systems approach to support parental mental well-being. The aim of this study was to assess the feasibility of community service provider organisations delivering E-PAtS to parents/family caregivers of young children with intellectual disability, to inform a potential definitive randomised controlled trial of the effectiveness and cost-effectiveness of E-PAtS. Methods: This study was a feasibility cluster randomised controlled trial, with embedded process evaluation. Up to two parents/family caregivers of a child (18 months to <6 years old) with intellectual disability were recruited at research sites and allocated to intervention (E-PAtS and usual practise) or control (usual practise) on a 1:1 basis at cluster (family) level. Data were collected at baseline and 3 and 12 months' post-randomisation. The following feasibility outcomes were assessed: participant recruitment rates and effectiveness of recruitment pathways; retention rates; intervention adherence and fidelity; service provider recruitment rates and willingness to participate in a future trial; barriers and facilitating factors for recruitment, engagement, and intervention delivery; and feasibility of collecting outcome measures. Results: Seventy-four families were randomised to intervention or control (n = 37). Retention rates were 72% at 12 months post-randomisation, and completion of the proposed primary outcome measure (WEMWBS) was 51%. Recruitment of service provider organisations and facilitators was feasible and intervention implementation acceptable. Adherence to the intervention was 76% and the intervention was well-received by participants; exploratory analyses suggest that adherence and attendance may be associated with improved well-being. Health economic outcome measures were collected successfully and evidence indicates that linkage with routine data would be feasible in a future trial. Conclusions: The E-PAtS Feasibility RCT has demonstrated that the research design and methods of intervention implementation are generally feasible. Consideration of the limitations of this feasibility trial and any barriers to conducting a future definitive trial, do however, need to be considered by researchers. Clinical Trial Registration: https://www.isrctn.com, identifier: ISRCTN70419473

A DELPHI study priority setting the remaining challenges for the use of routinely collected data in trials: COMORANT-UK

Background: Researchers are increasingly seeking to use routinely collected data to support clinical trials. This approach has the potential to transform the way clinical trials are conducted in the future. The availability of routinely collected data for research, whether healthcare or administrative, has increased, and infrastructure funding has enabled much of this. However, challenges remain at all stages of a trial life cycle. This study, COMORANT-UK, aimed to systematically identify, with key stakeholders across the UK, the ongoing challenges related to trials that seek to use routinely collected data. Methods: This three-step Delphi method consisted of two rounds of anonymous web-based surveys and a virtual consensus meeting. Stakeholders included trialists, data infrastructures, funders of trials, regulators, data providers and the public. Stakeholders identified research questions or challenges that they considered were of particular importance and then selected their top 10 in the second survey. The ranked questions were taken forward to the consensus meeting for discussion with representatives invited from the stakeholder groups. Results: In the first survey, 66 respondents yielded over 260 questions or challenges. These were thematically grouped and merged into a list of 40 unique questions. Eighty-eight stakeholders then ranked their top ten from the 40 questions in the second survey. The most common 14 questions were brought to the virtual consensus meeting in which stakeholders agreed a top list of seven questions. We report these seven questions which are within the following domains: trial design, Patient and Public Involvement, trial set-up, trial open and trial data. These questions address both evidence gaps (requiring further methodological research) and implementation gaps (requiring training and/or service re-organisation). Conclusion: This prioritised list of seven questions should inform the direction of future research in this area and should direct efforts to ensure that the benefits in major infrastructure for routinely collected data are achieved and translated. Without this and future work to address these questions, the potential societal benefits of using routinely collected data to help answer important clinical questions will not be realised

Getting our ducks in a row:The need for data utility comparisons of healthcare systems data for clinical trials

BACKGROUND: Better use of healthcare systems data, collected as part of interactions between patients and the healthcare system, could transform planning and conduct of randomised controlled trials. Multiple challenges to widespread use include whether healthcare systems data captures sufficiently well the data traditionally captured on case report forms. "Data Utility Comparison Studies" (DUCkS) assess the utility of healthcare systems data for RCTs by comparison to data collected by the trial. Despite their importance, there are few published UK examples of DUCkS.METHODS-AND-RESULTS: Building from ongoing and selected recent examples of UK-led DUCkS in the literature, we set out experience-based considerations for the conduct of future DUCkS. Developed through informal iterative discussions in many forums, considerations are offered for planning, protocol development, data, analysis and reporting, with comparisons at "patient-level" or "trial-level", depending on the item of interest and trial status.DISCUSSION: DUCkS could be a valuable tool in assessing where healthcare systems data can be used for trials and in which trial teams can play a leading role. There is a pressing need for trials to be more efficient in their delivery and research waste must be reduced. Trials have been making inconsistent use of healthcare systems data, not least because of an absence of evidence of utility. DUCkS can also help to identify challenges in using healthcare systems data, such as linkage (access and timing) and data quality. We encourage trial teams to incorporate and report DUCkS in trials and funders and data providers to support them.</p

Getting our ducks in a row: The need for data utility comparisons of healthcare systems data for clinical trials

Background: Better use of healthcare systems data, collected as part of interactions between patients and the healthcare system, could transform planning and conduct of randomised controlled trials. Multiple challenges to widespread use include whether healthcare systems data captures sufficiently well the data traditionally captured on case report forms. “Data Utility Comparison Studies” (DUCkS) assess the utility of healthcare systems data for RCTs by comparison to data collected by the trial. Despite their importance, there are few published UK examples of DUCkS. // Methods-and-Results: Building from ongoing and selected recent examples of UK-led DUCkS in the literature, we set out experience-based considerations for the conduct of future DUCkS. Developed through informal iterative discussions in many forums, considerations are offered for planning, protocol development, data, analysis and reporting, with comparisons at “patient-level” or “trial-level”, depending on the item of interest and trial status. // Discussion: DUCkS could be a valuable tool in assessing where healthcare systems data can be used for trials and in which trial teams can play a leading role. There is a pressing need for trials to be more efficient in their delivery and research waste must be reduced. Trials have been making inconsistent use of healthcare systems data, not least because of an absence of evidence of utility. DUCkS can also help to identify challenges in using healthcare systems data, such as linkage (access and timing) and data quality. We encourage trial teams to incorporate and report DUCkS in trials and funders and data providers to support them

Getting our ducks in a row:The need for data utility comparisons of healthcare systems data for clinical trials

BACKGROUND: Better use of healthcare systems data, collected as part of interactions between patients and the healthcare system, could transform planning and conduct of randomised controlled trials. Multiple challenges to widespread use include whether healthcare systems data captures sufficiently well the data traditionally captured on case report forms. "Data Utility Comparison Studies" (DUCkS) assess the utility of healthcare systems data for RCTs by comparison to data collected by the trial. Despite their importance, there are few published UK examples of DUCkS.METHODS-AND-RESULTS: Building from ongoing and selected recent examples of UK-led DUCkS in the literature, we set out experience-based considerations for the conduct of future DUCkS. Developed through informal iterative discussions in many forums, considerations are offered for planning, protocol development, data, analysis and reporting, with comparisons at "patient-level" or "trial-level", depending on the item of interest and trial status.DISCUSSION: DUCkS could be a valuable tool in assessing where healthcare systems data can be used for trials and in which trial teams can play a leading role. There is a pressing need for trials to be more efficient in their delivery and research waste must be reduced. Trials have been making inconsistent use of healthcare systems data, not least because of an absence of evidence of utility. DUCkS can also help to identify challenges in using healthcare systems data, such as linkage (access and timing) and data quality. We encourage trial teams to incorporate and report DUCkS in trials and funders and data providers to support them.</p