Direct experimental evidence that early-life farm environment influences regulation of immune responses

Background: In mammals, early-life environmental variations appear to affect microbial colonization and therefore competent immune development, and exposure to farm environments in infants has been inversely correlated with allergy development. Modelling these effects using manipulation of neonatal rodents is difficult due to their dependency on the mother, but the relatively independent piglet is increasingly identified as a valuable translational model for humans. This study was designed to correlate immune regulation in piglets with early-life environment. Methods: Piglets were nursed by their mother on a commercial farm, while isolatorreared siblings were formula fed. Fluorescence immunohistology was used to quantify T-reg and effector T-cell populations in the intestinal lamina propria and the systemic response to food proteins was quantified by capture ELISA. Results: There was more CD4+ and CD4+CD25+ effector T-cell staining in the intestinal mucosa of the isolator-reared piglets compared with their farm-reared counterparts. In contrast, these isolator-reared piglets had a significantly reduced CD4+CD25+Foxp3+ regulatory T-cell population compared to farm-reared littermates, resulting in a significantly higher T-reg-to-effector ratio in the farm animals. Consistent with these findings, isolator-reared piglets had an increased serum IgG anti-soya response to novel dietary soya protein relative to farm-reared piglets. Conclusion: Here, we provide the first direct evidence, derived from intervention, that components of the early-life environment present on farms profoundly affects both local development of regulatory components of the mucosal immune system and immune responses to food proteins at weaning. We propose that neonatal piglets provide a tractable model which allows maternal and treatment effects to be statistically separated.

Modelling the economics of farm-based anaerobic digestion in a UK whole-farm context

Anaerobic digestion (AD) technologies convert organic wastes and crops into methane-rich biogas for heating, electricity generation and vehicle fuel. Farm-based AD has proliferated in some EU countries, driven by favourable policies promoting sustainable energy generation and GHG mitigation. Despite increased state support there are still few AD plants on UK farms leading to a lack of normative data on viability of AD in the whole-farm context. Farmers and lenders are therefore reluctant to fund AD projects and policy makers are hampered in their attempts to design policies that adequately support the industry. Existing AD studies and modelling tools do not adequately capture the farm context within which AD interacts. This paper demonstrates a whole-farm, optimisation modelling approach to assess the viability of AD in a more holistic way, accounting for such issues as: AD scale, synergies and conflicts with other farm enterprises, choice of feedstocks, digestate use and impact on farm Net Margin. This modelling approach demonstrates, for example, that: AD is complementary to dairy enterprises, but competes with arable enterprises for farm resources. Reduced nutrient purchases significantly improve Net Margin on arable farms, but AD scale is constrained by the capacity of farmland to absorb nutrients in AD digestate.

An industry viewpoint on the role of farm assurance in delivering food safety to the consumer: the case of the dairy sector in England and Wales

Food safety, alongside food quality, remains a primary concern of both consumers and those along the whole food supply chain, leading to regulation by government alongside private third party certification. Much has been written about the value of these systems primarily from the perception of the consumer. This paper reports on a study that examined industry perceptions on the regulatory and assurance systems within the dairy sector of England and Wales. It found that the primary producer found value in both systems, although from a food hygiene focus regulation was seen to be more rigorous. Other stakeholders along the dairy food supply chain saw the assurance scheme as more rigorous. All stakeholders recognised the need to reduce duplication in delivering food safety through combining key elements of both systems with the added potential for better communication of both food safety and quality to the final consumer.

Sequence analysis of a CTX-M-1 IncI1 plasmid found in Salmonella enterica 4,5,12,i:-, Escherichia coli and Klebsiella pneumoniae on a single UK pig farm

OBJECTIVES: In 2009, CTX-M Enterobacteriaceae and Salmonella isolates were recovered from a UK pig farm, prompting studies into the dissemination of the resistance and to establish any relationships between the isolates. METHODS: PFGE was used to elucidate clonal relationships between isolates whilst plasmid profiling, restriction analysis, sequencing and PCR were used to characterize the CTX-M-harbouring plasmids. RESULTS: Escherichia coli, Klebsiella pneumoniae and Salmonella 4,5,12:i:- and Bovismorbificans resistant to cefotaxime (n = 65) were recovered and 63 were shown by PCR to harbour a group 1 CTX-M gene. The harbouring hosts were diverse, but the group 1 CTX-M plasmids were common. Three sequenced CTX-M plasmids from E. coli, K. pneumoniae and Salmonella enterica serotype 4,5,12:i:- were identical except for seven mutations and highly similar to IncI1 plasmid ColIb-P9. Two antimicrobial resistance regions were identified: one inserted upstream of yacABC harbouring ISCR2 transposases, sul2 and floR; and the other inserted within shfB of the pilV shufflon harbouring the ISEcp1 transposase followed by blaCTX-M-1. CONCLUSIONS: These data suggest that an ST108 IncI1 plasmid encoding a blaCTX-M-1 gene had disseminated across multiple genera on this farm, an example of horizontal gene transfer of the blaCTX-M-1 gene.

An aggregated wind power generation model based on MERRA reanalysis data: MATLAB model and example data for the April 2014 wind farm distribution of Great Britain.

The MATLAB model is contained within the compressed folders (versions are available as .zip and .tgz). This model uses MERRA reanalysis data (>34 years available) to estimate the hourly aggregated wind power generation for a predefined (fixed) distribution of wind farms. A ready made example is included for the wind farm distribution of Great Britain, April 2014 ("CF.dat"). This consists of an hourly time series of GB-total capacity factor spanning the period 1980-2013 inclusive. Given the global nature of reanalysis data, the model can be applied to any specified distribution of wind farms in any region of the world. Users are, however, strongly advised to bear in mind the limitations of reanalysis data when using this model/data. This is discussed in our paper: Cannon, Brayshaw, Methven, Coker, Lenaghan. "Using reanalysis data to quantify extreme wind power generation statistics: a 33 year case study in Great Britain". Submitted to Renewable Energy in March, 2014. Additional information about the model is contained in the model code itself, in the accompanying ReadMe file, and on our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/

Farmers' interest in growing GM crops in the UK, in the context of a range of on-farm coexistence issues

Although no GM crops currently are licensed for commercial production in the UK, as opposition to GM crops by consumers softens, this could change quickly. Although past studies have examined attitudes of UK farmers toward GM technologies in general, there has been little work on the impact of possible coexistence measures on their attitudes toward GM crop production. This could be because the UK Government has not engaged in any public dialogue on the coexistence measures that might be applied on farms. Based on a farm survey, this article examines farmers’ attitudes toward GM technologies and planting intentions for three crops (maize, oilseed rape, and sugar beet) based on a GM availability scenario. The article then nuances this analysis with a review of farmer perceptions of the level of constraint associated with a suite of notional farm-level coexistence measures and issues, based on current European Commission guidelines and practice in other EU Member States.