Mendelian randomisation implicates hyperlipidaemia as a risk factor for colorectal cancer.

While elevated blood cholesterol has been associated with an increased risk of colorectal cancer (CRC) in observational studies, causality is uncertain. Here we apply a Mendelian randomisation (MR) analysis to examine the potential causal relationship between lipid traits and CRC risk. We used single nucleotide polymorphisms (SNPs) associated with blood levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) as instrumental variables (IV). We calculated MR estimates for each risk factor with CRC using SNP-CRC associations from 9,254 cases and 18,386 controls. Genetically predicted higher TC was associated with an elevated risk of CRC (odds ratios (OR) per unit SD increase = 1.46, 95% confidence interval [CI]: 1.20-1.79, P=1.68x10−4). The pooled ORs for LDL, HDL, and TG were 1.05 (95% CI: 0.92-1.18, P=0.49), 0.94 (95% CI: 0.84-1.05, P= 0.27), and 0.98 (95% CI: 0.85-1.12, P=0.75) respectively. A genetic risk score for 3-hydoxy-3-methylglutaryl-coenzyme A reductase (HMGCR) to mimic the effects of statin therapy was associated with a reduced CRC risk (OR=0.69, 95% CI: 0.49-0.99, P=0.046). This study supports a causal relationship between higher levels of TC with CRC risk, and a further rationale for implementing public health strategies to reduce the prevalence of hyperlipidaemia. This article is protected by copyright. All rights reserved

Variation at 2q35 (PNKD and TMBIM1) influences colorectal cancer risk and identifies a pleiotropic effect with inflammatory bowel disease

To identify new risk loci for colorectal cancer (CRC), we conducted a meta-analysis of seven genome-wide association studies (GWAS) with independent replication, totalling 13 656 CRC cases and 21 667 controls of European ancestry. The combined analysis identified a new risk association for CRC at 2q35 marked by rs992157 (P = 3.15 x 10(-8), odds ratio = 1.10, 95% confidence interval = 1.06-1.13), which is intronic to PNKD (paroxysmal non-kinesigenic dyskinesia) and TMBIM1 (transmembrane BAX inhibitor motif containing 1). Intriguingly this susceptibility single-nucleotide polymorphism (SNP) is in strong linkage disequilibrium (r(2) = 0.90, D' = 0.96) with the previously discovered GWAS SNP rs2382817 for inflammatory bowel disease (IBD). Following on from this observation we examined for pleiotropy, or shared genetic susceptibility, between CRC and the 200 established IBD risk loci, identifying an additional 11 significant associations (false discovery rate [FDR]) <0.05). Our findings provide further insight into the biological basis of inherited genetic susceptibility to CRC, and identify risk factors that may influence the development of both CRC and IBD.Peer reviewe

National Forest Programmes in Scandinavian Political Culture

National forest programme (NFP) as a new forest policy tool, was launched in the Rio Summit in 1992. It emphasizes participation, delegation and inter-sectoral coordination. The adaptation of these principles in the forest policy in Finland, Norway and Sweden are discussed in this paper. The stage of the NFP process in each of them is very different in spite of the common structural features in the political culture. Separate policy actions related to the identification of sustainable forest management were arranged in Finland (forest specific environmental program in 1994) and in Norway (Living Forests Program in 1998) whereas in Sweden a specific process has not been identifiable prior to Environmental Code 1999 and Quality Criteria. The compulsory process towards regional forest programs in Finland promoted delegation and regional participation. No NFP-specific revisions in delegation has been named in Norway or Sweden. The Finnish government had as incentive to start a participatory political process towards NFP in order to maintain and even increase public subsidies to timber management investments, whereas Norway and Sweden had already abandoned such subsidies

Heterogeneous farmland owners: two approaches for objective based classification

Landowner classifications based on their objectives have been used to describe the heterogeneous group of landowners. As the accurate information on landowners preferences is essential in policy planning and evaluation of the effects of various policy instruments, there is a need to develop feasible methods for classifying land owners. In this study we apply objective based classification to farmland owners using the data of Finnish farmland owners. We compare two classification methods, traditional cluster analysis and latent class analysis, in terms of their criterion validity. The comparison of criterion validity, consisting from convergent, concurrent, discriminant and predictive components of validity, revealed that latent class analysis was superior method. The analysis showed that objective grouping of farmland owners was relevant predictor of landowner behavior, and is thus valuable information for agricultural policy makers

Cost-Sharing and Private Timber Stand Improvements: A Two-Step Approach

The effects of cost-sharing and technical assistance on nonindustrial private forest owners' investment in timber stand improvements are analyzed using a two-step estimation method. We use survey data on Finnish NIPF owners' stand improvements, including precommercial thinnings and cleaning of seedling stands as well as restoration thinnings of overstocked juvenile stands in 1994-1998. The investment decision is theoretically considered in a two-period consumption-savings model with amenity values. To allow for the joint determination of participation in the cost-sharing program and the decision to invest, a two-step estimation method is used. The predicted probability of using public subsidy from the first-step model is included in the second-step model explaining the probability or relative extent of stand improvements. For robust inference, a quasi-maximum likelihood estimation technique and the Murphy-Topel correction are applied. Both public subsidy, personal assistance and forest planning expectedly increased the probability to invest. Especially public subsidy had substantial effects on the probability as well as extent of stand improvement. Besides overcoming the endogeneity of cost-sharing, the two-step approach showed that personal assistance also encourages stand improvements indirectly through its effect on the use of public subsid

Productisation:a review and research agenda

Abstract Productisation relates to the process of analysing a need, defining and combining suitable elements, tangible and/or intangible, into a product-like defined set of deliverables that is standardised, repeatable and comprehendible. This paper clarifies the concept of productisation by surveying the extant literature and reporting the origins, characteristics, benefits and features along with aiming to support future work. The analysed literature is categorised, its content is analysed, and the need for a clear framework is highlighted. The results indicate that productisation has a specific role in addressing the challenges of being able to describe and explain complex, often abstract offerings and producing them, involving activities both to ensure adequate standards and those activities leading to selling the products. A well productised product is easier to buy, sell and market, has stronger features and may enable benefits depending on the product type. Productisation has implications through having a complementary role amongst well established functions and in strengthening the linkage of market needs and engineering-oriented development. The concept requires further development. Potential future research directions are presented

Improved modelling of electric loads for enabling demand response by applying physical and data-driven models:project RESPONSE

Accurate load and response forecasts are a critical enabler for high demand response penetrations and optimization of responses and market actions. Project RESPONSE studies and develops methods to improve the forecasts. Its objectives are to improve 1) load and response forecast and optimization models based on both data-driven and physical modelling, and their hybrid models, 2) utilization of various data sources such as smart metering data, weather data, measurements from substations etc., and 3) performance criteria of load forecasting. The project applies, develops, compares, and integrates various modelling approaches including partly physical models, machine learning, modern load profiling, autoregressive models, and Kalman-filtering. It also applies non-linear constrained optimization to load responses. This paper gives an overview of the project and the results achieved so far.acceptedVersionPeer reviewe