pi-NN Coupling Constants from NN Elastic Data between 210 and 800 Mev

High partial waves for $pp$ and $np$ elastic scattering are examined critically from 210 to 800 MeV. Non-OPE contributions are compared with predictions from theory. There are some discrepancies, but sufficient agreement that values of the $\pi NN$ coupling constants $g_0^2$ for $\pi ^0$ exchange and $g^2_{c}$ for charged $\pi$ exchange can be derived. Results are $g^2_0 = 13.91 \pm 0.13 \pm 0.07$ and $g^2_c = 13.69 \pm 0.15 \pm 0.24$, where the first error is statistical and the second is an estimate of the likely systematic error, arising mostly from uncertainties in the normalisation of total cross sections and $d\sigma/d\Omega$.Comment: 21 pages of LaTeX, UI-NTH-940

Known or potential threats from pests and diseases to prospective tree species for high value timber plantings in northern Australia

The development of a high value timber industry in northern Australia requires high-level, long-term investment. To secure such a commitment, potential investors and growers must be confident of achieving high productivity and/or high quality end product. Pests and diseases, and their effect on tree health, can be major limiting factors to tree establishment and performance. This is especially true where native or endemic species are to be grown. Timber plantings in northern Australia are likely to be at risk from a number of pests and diseases. This includes both native and exotic species already present within the region, and species not yet present but which have potential to cause problems should they arrive. Existing and potential threats are listed and the more serious problems reviewed

Progress in developing a potato ontology for breeders.

The potato ontology is part of a community effort to establish a set of related crop ontologies. The advantage of an ontology is that both humans and software applications can understand a data domain. This will allow the application of numerical or data mining techniques that may help to uncover previously unknown correlations. Building on previous draft versions, here we focus on traits important to breeding: we identified so far 70 descriptors. These include: morphological (36), agronomical performance (7), resistance traits (7), biochemical (6), reaction to abiotic stresses (2), molecular (1 ) and post-harvest (9). We anticipate further refinements and cross-checks

Suboptimal blood pressure control in chronic kidney disease stage 3: baseline data from a cohort study in primary care

Background: poorly controlled hypertension is independently associated with mortality, cardiovascular risk and disease progression in chronic kidney disease (CKD). In the UK, CKD stage 3 is principally managed in primary care, including blood pressure (BP) management. Controlling BP is key to improving outcomes in CKD. This study aimed to investigate associations of BP control in people with CKD stage 3.Methods: 1,741 patients with CKD 3 recruited from 32 general practices for the Renal Risk in Derby Study underwent medical history, clinical assessment and biochemistry testing. BP control was assessed by three standards: National Institute for Health and Clinical Excellence (NICE), National Kidney Foundation Kidney Disease Outcome Quality Initiative (KDOQI) and Kidney Disease: Improving Global Outcomes (KDIGO) guidelines. Descriptive statistics were used to compare characteristics of people achieving and not achieving BP control. Univariate and multivariate logistic regression was used to identify factors associated with BP control.Results: the prevalence of hypertension was 88%. Among people with hypertension, 829/1426 (58.1%) achieved NICE BP targets, 512/1426 (35.9%) KDOQI targets and 859/1426 (60.2%) KDIGO targets. Smaller proportions of people with diabetes and/or albuminuria achieved hypertension targets. 615/1426 (43.1%) were only taking one antihypertensive agent. On multivariable analysis, BP control (NICE and KDIGO) was negatively associated with age (NICE odds ratio (OR) 0.27; 95% confidence interval (95% CI) 0.17-0.43) 70–79 compared to &lt;60), diabetes (OR 0.32; 95% CI 0.25-0.43)), and albuminuria (OR 0.56; 95% CI 0.42-0.74)). For the KDOQI target, there was also association with males (OR 0.76; 95% CI 0.60-0.96)) but not diabetes (target not diabetes specific). Older people were less likely to achieve systolic targets (NICE target OR 0.17 (95% CI 0.09,0.32) p?&lt;?0.001) and more likely to achieve diastolic targets (OR 2.35 (95% CI 1.11,4.96) p?&lt;?0.001) for people &gt;80 compared to?&lt;?60).Conclusions: suboptimal BP control was common in CKD patients with hypertension in this study, particularly those at highest risk of adverse outcomes due to diabetes and or albuminuria. This study suggests there is scope for improving BP control in people with CKD by using more antihypertensive agents in combination while considering issues of adherence and potential side effects.<br/

Integrating and sharing accession-level and omics-size genotype, phenotype and environmental data: Experiences at the International Potato Center (CIP).

Plant breeding consists in the creation and selection of new genotypes. This involves not only keeping records across generations and environments but also accommodating data of increasing resolution on genotypes, phenotypes, and growth environments. Some such high-resolution characterization methods are Near-Infrared spectroscopy, metabolomics, next-generation sequencing and high resolution spatial-temporal-spectral photos. A first need is the integration and retrieval of this information. Such an integrated and complete set can be described in breeder’s terms in six dimensions: a plant phenotype (P) is the result of a genotypes (G) interaction with its environment (E) given certain field management (M) practices. In addition, data on the administrative (A) context should be kept including staff involved, objectives and, if applicable, projects and donors; as well as on data documentation standards (S) like ontologies. The latter play an important part in exchanging and aggregating information. Here we describe the adoption of the ‘Biomart’ database for this purpose. While Biomart was developed originally to accommodate gene and sequencing data at a genomic scale we describe here how it can be used for breeding program data. This is being illustrated by current data warehousing in the potato breeding program at the International Potato Center (CIP). Particularly, genotype and phenotype can be transparently combined for further analysis in the decision process for the selection of new genotypes