Protein modification and maintenance systems as biomarkers of ageing

Changes in the abundance and post-translational modification of proteins and accumulation of some covalently modified proteins have been proposed to represent hallmarks of biological ageing. Within the frame of the Mark-Age project, the workpackage dedicated to "markers based on proteins and their modifications" has been firstly focused on enzymatic and non-enzymatic post-translational modifications of serum proteins by carbohydrates. The second focus of the workpackage has been directed towards protein maintenance systems that are involved either in protein quality control (ApoJ/Clusterin) or in the removal of oxidatively damaged proteins through degradation and repair (proteasome and methionine sulfoxide reductase systems). This review describes the most relevant features of these protein modifications and maintenance systems, their fate during ageing and/or their implication in ageing and longevity

Responses to selection for lean growth in sheep

This paper reports the selection responses achieved, and related results, following 9 years of index selection for lean growth in Suffolk sheep. The breeding goal of the index used comprised carcass lean weight and carcass fat weight at a constant age, with relative economic values of + 3 and –1 per kg. The selection criteria were live weight (LWT), ultrasonic fat depth (UFD) and ultrasonic muscle depth (UMD) adjusted to a constant age of 150 days. By year 9, responses in LWT, UFD and UMD in both sexes, as judged by the divergence between selection and control line performance, amounted to 4·88 kg, –1·1 mm and 2·8 mm respectively; these responses are between 7 and 15% of the overall means of the traits concerned. Although selection was originally on index scores based on phenotypic records, the retrospective analyses reported here used the mixed model applications of residual maximum likelihood to estimate parameters and best linear unbiased prediction to predict breeding values. The statistical model comprised fixed effects plus random effects accounting for direct additive, maternal additive and temporary environmental variation. Estimated genetic trends obtained by regressing estimated breeding values on year of birth were similar to annual responses estimated by comparing selection and control line means. Estimates of direct heritabilities were 0·054, 0·177, 0·286, 0·561 and 0·410 for birth weight (BWT), weaning weight (WWT), LWT, UFD and UMD respectively. Corresponding estimates of maternal heritabilities were 0·287, 0·205, 0·160, 0·083 and 0·164. Phenotypic correlations between all pairs of traits were positive and usually moderately high. There were low negative direct additive correlations between BWT and WWT, and between BWT and LWT, but higher positive maternal additive correlations between all other pairs of weight traits

Application of machine learning techniques to support decision making under uncertainty in water resource management

Water companies in the UK are required to produce long-term plans of water resources for their supply area every five years, detailing how they will maintain secure, sustainable supplies , taking account of social and environmental impacts as well as economic costs. Extensive ensemble modelling of water resource systems underpins the production of these reports and the resulting investments chosen to maintain supplies into the future. Adoption of new guidance on the use of advanced Decision Making Methods (DMMs) and Risk Based Planning has demanded a more comprehensive modelling approach. Modelling and analytical efficiencies are increasingly required for their use and to realise their full benefits. Existing water resources, hydrological, groundwater, and demand models traditionally used by water companies are often not ideally suited for use in these DMMs. Consequently a toolset of approaches is evolving to enable UK water companies to undertake this more complex decision making. Key elements of this toolset include emulation modelling to complement computationally more expensive process models, machine learning techniques for groundwater assessment and to optimise reservoir control curves considering multiple objectives, and agent based models to explore the spatial and temporal pattern of demand over ensembles of plausible futures. These methods support the rapid simulation times required for applying the DMMs to provide a holistic view of system behaviour under large supply-side, demand-side and policy uncertainties. User-friendly tools and dashboards are being used to explore and communicate the outputs and facilitate effective decision-making, involving all stakeholders. This toolset of approaches is being increasingly adopted in the UK, demonstrating the potential for innovative methods to interpret and present complex modelling results. Due to the flexible structure of the tools, and the generic approaches used, these techniques can readily be applied to a wide range of settings. However, the absence of physical process representation in some of these methods, and associated implications, must be considered in their application and by planners when interpreting results. Methods in themselves are not a replacement for diligent water planning, but a tool to support it

Stakeholders understanding of the concept of benefit sharing in health research in Kenya: a qualitative study

BACKGROUND: The concept of benefit sharing to enhance the social value of global health research in resource poor settings is now a key strategy for addressing moral issues of relevance to individuals, communities and host countries in resource poor settings when they participate in international collaborative health research.The influence of benefit sharing framework on the conduct of collaborative health research is for instance evidenced by the number of publications and research ethics guidelines that require prior engagement between stakeholders to determine the social value of research to the host communities. While such efforts as the production of international guidance on how to promote the social value of research through such strategies as benefit sharing have been made, the extent to which these ideas and guidelines have been absorbed by those engaged in global health research especially in resource poor settings remains unclear. We examine this awareness among stakeholders involved in health related research in Kenya. METHODS: We conducted in-depth interviews with key informants drawn from within the broader health research system in Kenya including researchers from the mainstream health research institutions, networks and universities, teaching hospitals, policy makers, institutional review boards, civil society organisations and community representative groups. RESULTS: Our study suggests that although people have a sense of justice and the moral aspects of research, this was not articulated in terms used in the literature and the guidelines on the ethics of global health research. CONCLUSION: This study demonstrates that while in theory several efforts can be made to address the moral issues of concern to research participants and their communities in resource poor settings, quick fixes such as benefit sharing are not going to be straightforward. We suggest a need to pay closer attention to the processes through which ethical principles are enacted in practice and distil lessons on how best to involve individuals and communities in promoting ethical conduct of global health research in resource poor settings

Use of agent-based modelling to validate hurricane evacuation planning

Justification for evacuation and evacuation planning is sometimes questioned and there is a need develop approaches which justify the planning and associated expenditure. To this end, it was decided to carry out a pilot evaluation of the impact of a Hurricane Storm surge flooding on Brunswick, GA using a dynamic Agent Based Model that represents people's interaction with a flood and provides estimates of the number of people that are likely to be killed as a result of a flood event, as well as the time that is required for them to evacuate the area at risk. Climate change increase of 3ft in mean sea level would increase the population at risk in Brunswick by 20% for a category 4 hurricane. The modelling shows that for a category 4 hurricane managed evacuation can significantly reduce the number of fatalities

SPIDERS: Selection of spectroscopic targets using AGN candidates detected in all-sky X-ray surveys

SPIDERS (SPectroscopic IDentification of eROSITA Sources) is an SDSS-IV survey running in parallel to the eBOSS cosmology project. SPIDERS will obtain optical spectroscopy for large numbers of X-ray-selected AGN and galaxy cluster members detected in wide area eROSITA, XMM-Newton and ROSAT surveys. We describe the methods used to choose spectroscopic targets for two sub-programmes of SPIDERS: X-ray selected AGN candidates detected in the ROSAT All Sky and the XMM-Newton Slew surveys. We have exploited a Bayesian cross-matching algorithm, guided by priors based on mid-IR colour-magnitude information from the WISE survey, to select the most probable optical counterpart to each X-ray detection. We empirically demonstrate the high fidelity of our counterpart selection method using a reference sample of bright well-localised X-ray sources collated from XMM-Newton, Chandra and Swift-XRT serendipitous catalogues, and also by examining blank-sky locations. We describe the down-selection steps which resulted in the final set of SPIDERS-AGN targets put forward for spectroscopy within the eBOSS/TDSS/SPIDERS survey, and present catalogues of these targets. We also present catalogues of ~12000 ROSAT and ~1500 XMM-Newton Slew survey sources which have existing optical spectroscopy from SDSS-DR12, including the results of our visual inspections. On completion of the SPIDERS program, we expect to have collected homogeneous spectroscopic redshift information over a footprint of ~7500 deg$^2$ for >85 percent of the ROSAT and XMM-Newton Slew survey sources having optical counterparts in the magnitude range 17<r<22.5, producing a large and highly complete sample of bright X-ray-selected AGN suitable for statistical studies of AGN evolution and clustering.Comment: MNRAS, accepte

Models of everywhere revisited: a technological perspective

The concept ‘models of everywhere’ was first introduced in the mid 2000s as a means of reasoning about the environmental science of a place, changing the nature of the underlying modelling process, from one in which general model structures are used to one in which modelling becomes a learning process about specific places, in particular capturing the idiosyncrasies of that place. At one level, this is a straightforward concept, but at another it is a rich multi-dimensional conceptual framework involving the following key dimensions: models of everywhere, models of everything and models at all times, being constantly re-evaluated against the most current evidence. This is a compelling approach with the potential to deal with epistemic uncertainties and nonlinearities. However, the approach has, as yet, not been fully utilised or explored. This paper examines the concept of models of everywhere in the light of recent advances in technology. The paper argues that, when first proposed, technology was a limiting factor but now, with advances in areas such as Internet of Things, cloud computing and data analytics, many of the barriers have been alleviated. Consequently, it is timely to look again at the concept of models of everywhere in practical conditions as part of a trans-disciplinary effort to tackle the remaining research questions. The paper concludes by identifying the key elements of a research agenda that should underpin such experimentation and deployment