Responsible agriculture must adapt to the wetland character of mid‐latitude peatlands

Drained, lowland agricultural peatlands are greenhouse gas (GHG) emission hotspots and a large but vulnerable store of irrecoverable carbon. They exhibit soil loss rates of ~2.0 cm yr−1 and are estimated to account for 32% of global cropland emissions while producing only 1.1% of crop kilocalories. Carbon dioxide emissions account for >80% of their terrestrial GHG emissions and are largely controlled by water table depth. Reducing drainage depths is, therefore, essential for responsible peatland management. Peatland restoration can substantially reduce emissions. However, this may conflict with societal needs to maintain productive use, to protect food security and livelihoods. Wetland agriculture strategies will, therefore, be required to adapt agriculture to the wetland character of peatlands, and balance GHG mitigation against productivity, where halting emissions is not immediately possible. Paludiculture may substantially reduce GHG emissions but will not always be viable in the current economic landscape. Reduced drainage intensity systems may deliver partial reductions in the rate of emissions, with smaller modifications to existing systems. These compromise systems may face fewer hurdles to adoption and minimize environmental harm until societal conditions favour strategies that can halt emissions. Wetland agriculture will face agronomic, socio-economic and water management challenges, and careful implementation will be required. Diversity of values and priorities among stakeholders creates the potential for conflict. Successful implementation will require participatory research approaches and co-creation of workable solutions. Policymakers, private sector funders and researchers have key roles to play but adoption risks would fall predominantly on land managers. Development of a robust wetland agriculture paradigm is essential to deliver resilient production systems and wider environmental benefits. The challenge of responsible use presents an opportunity to rethink peatland management and create thriving, innovative and green wetland landscapes for everyone's future benefit, while making a vital contribution to global climate change mitigation

Enhanced glycemic control with combination therapy for type 2 diabetes in primary care

Type 2 diabetes mellitus is an increasingly common medical problem for primary care clinicians to address. Treatment of diabetes has evolved from simple replacement of insulin (directly or through insulin secretagogs) through capture of mechanisms such as insulin sensitizers, alpha-glucosidase inhibitors, and incretins. Only very recently has recognition of the critical role of the gastrointestinal system as a major culprit in glucose dysregulation been established. Since glycated hemoglobin A1c reductions provide meaningful risk reduction as well as improved quality of life, it is worthwhile to explore evolving paths for more efficient use of the currently available pharmacotherapies. Because diabetes is a progressive disease, even transiently successful treatment will likely require augmentation as the disorder progresses. Pharmacotherapies with complementary mechanisms of action will be necessary to achieve glycemic goals. Hence, clinicians need to be well informed about the various noninsulin alternatives that have been shown to be successful in glycemic goal attainment. This article reviews the benefits of glucose control, the current status of diabetes control, pertinent pathophysiology, available pharmacological classes for combination, limitations of current therapies, and suggestions for appropriate combination therapies, including specific suggestions for thresholds at which different strategies might be most effectively utilized by primary care clinicians

Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases

Central corneal thickness (CCT) is a highly heritable trait associated with complex eye diseases such as keratoconus and glaucoma. We perform a genome-wide association meta-analysis of CCT and identify 19 novel regions. In addition to adding support for known connective tissue-related pathways, pathway analyses uncover previously unreported gene sets. Remarkably, >20% of the CCT-loci are near or within Mendelian disorder genes. These included FBN1, ADAMTS2 and TGFB2 which associate with connective tissue disorders (Marfan, Ehlers-Danlos and Loeys-Dietz syndromes), and the LUM-DCN-KERA gene complex involved in myopia, corneal dystrophies and cornea plana. Using index CCT-increasing variants, we find a significant inverse correlation in effect sizes between CCT and keratoconus (r =-0.62, P = 5.30 × 10-5) but not between CCT and primary open-angle glaucoma (r =-0.17, P = 0.2). Our findings provide evidence for shared genetic influences between CCT and keratoconus, and implicate candidate genes acting in collagen and extracellular matrix regulation

Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus.

BACKGROUND: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. METHOD: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. RESULTS: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. CONCLUSION: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk.UK funding includes Cancer Research UK and NIH.This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s13058-016-0718-

The Systems Biology Graphical Notation

Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling. © 2009 Nature America, Inc