Cultivation and anaerobic digestion of Scenedesmus spp. grown in a pilot-scale open raceway

Digestibility of a micro-algal mixture was evaluated by mesophilic anaerobic digestion in continuously-stirred tank reactors. The culture consisted primarily of Scenedesmus spp. continuously cultivated over a 6-month period in a 100 m2 raceway reactor instrumented to record pH, dissolved oxygen and temperature. The raceway received supplementary carbon in the form of flue gas from a diesel boiler (10% CO2) injected into a 1-m deep sump to control pH in the range 7.8–8.0. Dilution was optimised to biomass productivity and gave values of 10–15 and 20–25 g total suspended solids (TSS) m? 2 day? 1 in winter (December–February) and spring (April–May), respectively. The culture for the anaerobic digestion trial was harvested in February by centrifugation to give an algal paste containing 4.3% volatile solids (VS). Semi-continuous digestion at organic loading rates of 2.00, 2.75 and 3.50 g VS l? 1 day? 1 gave volumetric biogas productions of ~ 0.66, ~ 0.83 and ~ 0.99 l l? 1 day? 1, respectively. Specific methane yield ranged from 0.13 to 0.14 l CH4 g? 1 VSadded with biogas methane content ~ 62%. Overall the digestion process was stable, but only ~ 30% VS destruction was achieved indicating low biodegradability, due to the short retention times and the recalcitrant nature of this type of biomas

Personal and societal costs of multiple sclerosis in the UK: A population-based MS Registry study

ObjectivesTo investigate through survey and data linkage, healthcare resource use and costs (except drugs), including who bears the cost, of multiple sclerosis in the United Kingdom by disease severity and type.MethodsThe United Kingdom Multiple Sclerosis Register deployed a cost of illness survey, completed by people with multiple sclerosis and linked this with data within the United Kingdom Multiple Sclerosis Register and from their hospital records. Resource consumption was categorised as being medical or non-medical and costed by National Health Service and social services estimates for 2018.ResultsWe calculated £509,003 in non-medical costs over a year and £435,488 in medical costs generated over 3 months. People with multiple sclerosis reported self-funding 75% of non-medical costs with non-medical interventions having long-term potential benefits. Costs increased with disability as measured by patient-reported Expanded Disability Status Score and Multiple Sclerosis Impact Scale, with Multiple Sclerosis Impact Scale physical being a more powerful predictor of costs than the patient-reported Expanded Disability Status Score. Two distinct groups were identified: medical and non-medical interventions (n = 138); and medical interventions only (n = 399). The medical and non-medical group reported increased disease severity and reduced employment but incurred 80% more medical costs per person than the medical-only group.ConclusionsThe importance of disability in driving costs is illustrated with balance between medical and non-medical costs consistent with the United Kingdom health environment. People with multiple sclerosis and their families fund a considerable proportion of non-medical costs but non-medical interventions with longer term impact could affect future medical costs

Supporting well-being in retirement through meaningful social roles: Systematic review of intervention studies

Context The marked demographic change toward greater proportions of older people in developed nations poses significant challenges for health and social care. Several studies have demonstrated an association between social roles in later life and positive health and well-being outcomes. After retiring from work, people may lose roles that provide purpose and social contacts. The outcomes of interventions to promote social roles in retirement have not been systematically reviewed. Methods We examined three research questions: (1) What kinds of intervention have been developed to promote social roles in retirement? (2) How much have they improved perceived roles? (3) Have these roles improved health or well-being? We included those studies that evaluated the provision of social roles; used a control or comparison group; targeted healthy retirement-transition adults who were living in the community; provided an abstract written in English; took place in a highly developed nation; and reported social role, health, or well-being outcomes. We searched eight electronic databases and combined the results with hand searches. Findings Through our searches, we identified 9,062 unique publications and eleven evaluative studies of acceptable quality, which reported seven interventions that met our inclusion criteria. These interventions varied in year of inception and scope, but only two were based outside North America. The studies rarely reported the quality or meaning of roles. Only three studies used random allocation, thus limiting inferences of causality from these studies. Interventions providing explicit roles and using supportive group structures were somewhat effective in improving one or more of the following: life satisfaction, social support and activity, physical health and activity, functional health, and cognition. Conclusions Social role interventions may improve health and well-being for people in retirement transition. Future research should improve the quality of intervention and assessment and look at which interventions are most effective and acceptable in facilitating social roles for diverse older populations. © 2013 Milbank Memorial Fund

Data linkage in social care: a pilot project

ABSTRACT Background To build the complete picture of service provision there is a need to broaden the linked data available to include health, social service provision by Local Authorities, and provision of support by third sector organisations. Data Linkage in Social Care is a pilot project to test the feasibility of linking datasets from a local authority, the NHS and third sector organisations. The focus of this work is individual level data from adults who are referred to social services in order to avoid admission to hospital or to facilitate their discharge from hospital. The data linkage will include data from statutory and third sector organisations and services which provide interventions and support in community settings. Objectives The main aims of this research are to: 1. Test the feasibility of linking datasets from Local Authority, the NHS and third sector organisations. 2. Build a more complete picture of service provision using adults who have been referred to social services in order to avoid admission to hospital or to facilitate their discharge from hospital. 3. Assess the range and quality of data available in each of the relevant organisations providing services to those individuals. The research outcome is a better understanding of the utility of data linkage across statutory and third party organisations. Approach A Bangor University led research team partnered with the Gwynedd Local authority to explore the Governance Issues and practicalities of providing an anonymised dataset to the SAIL databank at Swansea. Two third sector agencies were also approached. With the various required Service Level Agreements in place, data were put through the tried and trusted SAIL process for analysis. Results Data relating to well over 20,000 referrals generated by 17,000+ social services clients in Gwynedd Local Authority from the period 2008 to 2015 were anonymised into the SAIL databank in Swansea, and linked to records from primary and secondary care. We will present results on the success of this process and on the emerging findings from the linked datasets

Reusable, set-based selection algorithm for matched control groups

ABSTRACT Aims The wealth of data available in linked administrative datasets offers great potential for research, but researchers face methodological and computational challenges in data preparation, due to the size and complexity of the data. The creation of matched control groups in the Secure Anonymised Information Linkage (SAIL) Databank illustrates this point: SAIL contains multiple health datasets describing millions of individuals in Wales. The volume of data creates the potential for more precise matching, but only if an appropriate algorithm can be applied. We aimed to create such an algorithm for reuse by many research projects. Methods We developed set-based code in SQL that efficiently selects matches from millions of potential combinations in a relational database environment. It is parameterized to allow different matching criteria to be employed as needed, including follow-up time around an index event. A combinatorial optimisation problem occurs when a potential control could match more than one subject, which we solved by ranking potential match pairs first by subject with the fewest potential matches, then by closeness of the match. Results One example of the algorithm’s use was the Suicide Information Database Cymru, an electronic case-control study on suicide in Wales between 2003 and 2011. Subjects who had a cause of death recorded as self-harm were each matched to twenty controls who were alive at the subject’s date of death and had the same gender and similar birth week. The rate of matching success was >99.9%, with all subjects but one matching the full twenty controls. >99.99% of the matched controls had a week of birth that was identical to the subject. The second example was a matched cohort study looking at hospital admissions and type 1 diabetes, using the Brecon register of childhood diabetes in Wales, with matching based on week of birth within two weeks, gender, county of residence, deprivation quintile, and residence in Wales at time of diagnosis. This study had a matching rate of 98.9%; 97.5% of subjects matched to five controls, and 69.8% of matches had the same week of birth. Conclusions This algorithm provides good matching performance while executing efficiently and scalably on large datasets. Its implementation as reusable code will facilitate more efficient, high-quality research in SAIL. Instead of spending many hours developing a custom solution, analysts can execute parameterized code in a few minutes. We hope it to be useful more widely beyond SAIL as well

Data Safe Havens and Trust: Toward a Common Understanding of Trusted Research Platforms for Governing Secure and Ethical Health Research

In parallel with the advances in big data-driven clinical research, the data safe haven concept has evolved over the last decade. It has led to the development of a framework to support the secure handling of health care information used for clinical research that balances compliance with legal and regulatory controls and ethical requirements while engaging with the public as a partner in its governance. We describe the evolution of 4 separately developed clinical research platforms into services throughout the United Kingdom-wide Farr Institute and their common deployment features in practice. The Farr Institute is a case study from which we propose a common definition of data safe havens as trusted platforms for clinical academic research. We use this common definition to discuss the challenges and dilemmas faced by the clinical academic research community, to help promote a consistent understanding of them and how they might best be handled in practice. We conclude by questioning whether the common definition represents a safe and trustworthy model for conducting clinical research that can stand the test of time and ongoing technical advances while paying heed to evolving public and professional concerns

The streptococcal collagen-like protein-1 (Scl1) is a significant determinant for biofilm formation by group a Streptococcus

<p>Abstract</p> <p>Background</p> <p>Group A <it>Streptococcus </it>(GAS) is a human-specific pathogen responsible for a number of diseases characterized by a wide range of clinical manifestations. During host colonization GAS-cell aggregates or microcolonies are observed in tissues. GAS biofilm, which is an <it>in vitro </it>equivalent of tissue microcolony, has only recently been studied and little is known about the specific surface determinants that aid biofilm formation. In this study, we demonstrate that surface-associated streptococcal collagen-like protein-1 (Scl1) plays an important role in GAS biofilm formation.</p> <p>Results</p> <p>Biofilm formation by M1-, M3-, M28-, and M41-type GAS strains, representing an intraspecies breadth, were analyzed spectrophotometrically following crystal violet staining, and characterized using confocal and field emission scanning electron microscopy. The M41-type strain formed the most robust biofilm under static conditions, followed by M28- and M1-type strains, while the M3-type strains analyzed here did not form biofilm under the same experimental conditions. Differences in architecture and cell-surface morphology were observed in biofilms formed by the M1- and M41-wild-type strains, accompanied by varying amounts of deposited extracellular matrix and differences in cell-to-cell junctions within each biofilm. Importantly, all Scl1-negative mutants examined showed significantly decreased ability to form biofilm <it>in vitro</it>. Furthermore, the Scl1 protein expressed on the surface of a heterologous host, <it>Lactococcus lactis</it>, was sufficient to induce biofilm formation by this organism.</p> <p>Conclusions</p> <p>Overall, this work (i) identifies variations in biofilm formation capacity among pathogenically different GAS strains, (ii) identifies GAS surface properties that may aid in biofilm stability and, (iii) establishes that the Scl1 surface protein is an important determinant of GAS biofilm, which is sufficient to enable biofilm formation in the heterologous host <it>Lactococcus</it>. In summary, the GAS surface adhesin Scl1 may have an important role in biofilm-associated pathogenicity.</p