Twelve perennial ryegrass (Lolium perenne L.) varieties of different ploidy and maturity classifications were compared under a frequent cutting management in their second harvest year, equivalent to the simulated rotational grazing system employed in UK testing protocols. Varietal differences in canopy structure (proportion of lamina, green leaf mass, sward surface height, extended tiller height, bulk density) and in herbage nutritive value factors (water-soluble carbohydrate content and proportion of linoleic and α-linolenic fatty acids) were assessed and their importance evaluated with reference to total herbage production. Significant variety variation (P<0·001) was recorded in the annual means of all the canopy structure characteristics. Significant differences associated with ploidy were also recorded, with tetraploid varieties having significantly higher values than diploids in most plant characters, indicating better intake characteristics for these grasses. Temporal patterns of variation associated with maturity were also observed in several characters, thus making it impossible to designate a single assessment that would be representative of the annual ranking of varieties. Water-soluble carbohydrate concentration differed significantly (P<0·001) between varieties and although the tetraploids tended to have high contents, the highest value of all was recorded in a diploid variety, which had been selectively bred for this trait. The varieties did not differ in total lipid content but there were significant differences in the proportion of linoleic acid between varieties (P<0·001) while the proportion of α-linolenic acid differed between varieties (P<0·001), ploidy (P<0·001) and maturity (P<0·05) classes.Overall evaluation of the extensive variety variation highlighted the need for better quantification of animal responses to differences of these magnitudes, before the high workload of including them in routine variety testing protocols could be justified. Potential for breeding improvement in these factors was also indicated and the future prospects for their use in farmer decision support systems was considered.

CSH is associated with a significantly increased risk of infection requiring hospitalization within 1 year following cardiac implantable electronic device surgery. Strategies aimed at reducing hematomas may decrease the long-term risk of infection. (Bridge or Continue Coumadin for Device Surgery Randomized Controlled Trial [BRUISE CONTROL]; NCT00800137).

BackgroundAtrial fibrillation (AF) is the most common sustained cardiac arrhythmia resulting in mortality and morbidity. Gaps in oral anticoagulation and education of patients regarding AF have been identified as areas that require improvement.Methods and ResultsA before‐and‐after study of 433 patients with newly diagnosed AF in the 3 emergency departments in Nova Scotia from January 1, 2011 until January 31, 2014 was performed. The “before” phase underwent the usual‐care pathway for AF management; the “after” phase was enrolled in a nurse‐run, physician‐supervised AF clinic. The primary outcome was a composite of death, cardiovascular hospitalization, and AF‐related emergency department visits. A propensity analysis was performed to account for differences in baseline characteristics.ResultsA total of 185 patients were enrolled into the usual‐care group, and 228 patients were enrolled in the AF clinic group. The mean age was 64±15 years and 44% were women. In a propensity‐matched analysis, the primary outcome occurred in 44 (26.2%) patients in the usual‐care group and 29 (17.3%) patients in the AF clinic group (odds ratio 0.71; 95% CI [0.59, 1]; P=0.049) at 12 months. Prescription of oral anticoagulation was increased in the CHADS 2 ≥2 group (88.4% in the AF clinic versus 58.5% in the usual‐care group, P<0.01).ConclusionsAdoption of this integrated management approach for the burgeoning population of AF may provide an overall benefit to cardiovascular morbidity and mortality.

Raman spectroscopy has been used for the first time to predict the FA composition of unextracted adipose tissue of pork, beef, lamb, and chicken. It was found that the bulk unsaturation parameters could be predicted successfully [R2 = 0.97, root mean square error of prediction (RMSEP) = 4.6% of 4 sigma], with cis unsaturation, which accounted for the majority of the unsaturation, giving similar correlations. The combined abundance of all measured PUFA (> or = 2 double bonds per chain) was also well predicted with R2 = 0.97 and RMSEP = 4.0% of 4 sigma. Trans unsaturation was not as well modeled (R2 = 0.52, RMSEP = 18% of 4 sigma); this reduced prediction ability can be attributed to the low levels of trans FA found in adipose tissue (0.035 times the cis unsaturation level). For the individual FA, the average partial least squares (PLS) regression coefficient of the 18 most abundant FA (relative abundances ranging from 0.1 to 38.6% of the total FA content) was R2 = 0.73; the average RMSEP = 11.9% of 4 sigma. Regression coefficients and prediction errors for the five most abundant FA were all better than the average value (in some cases as low as RMSEP = 4.7% of 4 sigma). Cross-correlation between the abundances of the minor FA and more abundant acids could be determined by principal component analysis methods, and the resulting groups of correlated compounds were also well-predicted using PLS. The accuracy of the prediction of individual FA was at least as good as other spectroscopic methods, and the extremely straightforward sampling method meant that very rapid analysis of samples at ambient temperature was easily achieved. This work shows that Raman profiling of hundreds of samples per day is easily achievable with an automated sampling system.

Raman spectroscopy has been used to predict the abundance of the FA in clarified butterfat that was obtained from dairy cows fed a range of levels of rapeseed oil in their diet. Partial least squares regression of the Raman spectra against FA compositions obtained by GC showed good prediction for the five major (abundance >5%) FA with R2 = 0.74-0.92 and a root mean SE of prediction (RMSEP) that was 5-7% of the mean. In general, the prediction accuracy fell with decreasing abundance in the sample, but the RMSEP was <10% for all but one of the 10 FA present at levels >1.25%. The Raman method has the best prediction ability for unsaturated FA (R2 = 0.85-0.92), and in particular trans unsaturated FA (best-predicted FA was 18:1 t delta9). This enhancement was attributed to the isolation of the unsaturated modes from the saturated modes and the significantly higher spectral response of unsaturated bonds compared with saturated bonds. Raman spectra of the melted butter samples could also be used to predict bulk parameters calculated from standard analyzes, such as iodine value (R2 = 0.80) and solid fat content at low temperature (R2 = 0.87). For solid fat contents determined at higher temperatures, the prediction ability was significantly reduced (R2 = 0.42), and this decrease in performance was attributed to the smaller range of values in solid fat content at the higher temperatures. Finally, although the prediction errors for the abundances of each of the FA in a given sample are much larger with Raman than with full GC analysis, the accuracy is acceptably high for quality control applications. This, combined with the fact that Raman spectra can be obtained with no sample preparation and with 60-s data collection times, means that high-throughput, on-line Raman analysis of butter samples should be possible.