Energy and protein interactions and their effect on nitrogen excretion in dairy cows

The principal driver of nitrogen (N) losses from the body including excretion and secretion in milk is N intake. However, other covariates may also play a role in modifying the partitioning of N. This study tests the hypothesis that N partitioning in dairy cows is affected by energy and protein interactions. A database containing 470 dairy cow observations was collated from calorimetry experiments. The data include N and energy parameters of the diet and N utilization by the animal. Univariate and multivariate meta-analyses that considered both within and between study effects were conducted to generate prediction equations based on N intake alone or with an energy component. The univariate models showed that there was a strong positive linear relationships between N intake and N excretion in faeces, urine and milk. The slopes were 0.28 faeces N, 0.38 urine N and 0.20 milk N. Multivariate model analysis did not improve the fit. Metabolizable energy intake had a significant positive effect on the amount of milk N in proportion to faeces and urine N, which is also supported by other studies. Another measure of energy considered as a covariate to N intake was diet quality or metabolizability (the concentration of metabolizable energy relative to gross energy of the diet). Diet quality also had a positive linear relationship with the proportion of milk N relative to N excreted in faeces and urine. Metabolizability had the largest effect on faeces N due to lower protein digestibility of low quality diets. Urine N was also affected by diet quality and the magnitude of the effect was higher than for milk N. This research shows that including a measure of diet quality as a covariate with N intake in a model of N execration can enhance our understanding of the effects of diet composition on N losses from dairy cows. The new prediction equations developed in this study could be used to monitor N losses from dairy systems.

Carbamazepine trifluoroacetic acid solvate

Carbamazepine forms a 1:1 solvate with trifluoroacetic acid (systematic name: 5H-dibenzo[b,f] azepine-5-carboxamide trifluoroacetic acid solvate), C(15)H(12)N(2)O center dot C(2)HF(3)O(2). The compound crystallizes with one molecule of carbamazepine and one of trifluoroacetic acid in the asymmetric unit to form an R(2)(2)(8) motif. The solvent molecule is disordered over two sites, with site-occupancy factors 0.53 (1) and 0.47 (1).

Differential effects of dairy snacks on appetite, but not overall energy intake

Dietary regulation of appetite may contribute to the prevention and management of excess body weight. The present study examined the effect of consumption of individual dairy products as snacks on appetite and subsequent ad libitum lunch energy intake. In a randomised cross-over trial, forty overweight men (age 32 (sd 9) years; BMI 27 (sd 2) kg/m2) attended four sessions 1 week apart and received three isoenergetic (841 kJ) and isovolumetric (410 ml) servings of dairy snacks or water (control) 120 min after breakfast. Appetite profile was determined throughout the morning and ad libitum energy intake was assessed 90 min after the intake of snacks. Concentrations of amino acids, glucose, insulin, ghrelin and peptide tyrosine tyrosine were measured at baseline (0 min) and 80 min after the intake of snacks. Although the results showed that yogurt had the greatest suppressive effect on appetite, this could be confounded by the poor sensory ratings of yogurt. Hunger rating was 8, 10 and 24 % (P < 0·001) lower after the intake of yogurt than cheese, milk and water, respectively. Energy intake was 11, 9 and 12 % (P < 0·02) lower after the intake of yogurt, cheese and milk, respectively, compared with water (4312 (se 226) kJ). Although there was no difference in the postprandial responses of hormones, alanine and isoleucine concentrations were higher after the intake of yogurt than cheese and milk (P < 0·05). In conclusion, all dairy snacks reduced appetite and lunch intake compared with water. Yogurt had the greatest effect on suppressing subjective appetite ratings, but did not affect subsequent food intake compared with milk or cheese.

The development of organized structures in polyethylene crystallized from a sheared melt, analyzed by WAXS and TEM

The development of global orientation and morphological features in linear polyethylene crystallizing from a sheared melt are studied using in-situ time-resolving wide angle X-ray scattering (WAXS) and ex-situ transmission electron microscopy. It is found that samples subjected to a shear rate above a critical value of ~1s-1 result in macroscopically oriented structures in the crystallized sample. This critical shear rate appears to be independent of the differences in molecular weight distribution of the samples studied although the morphologies which develop are sensitive to quite small differences in molecular weight distributions. The presence of shish kebabs in the morphology is shown to differ markedly according to variations in the upper molecular weight fraction of the molecular weight distribution, even though the resulting global orientation does not. The WAXS also reveals that areas which evidence no row nucleated structures still realize high degrees of molecular orientation. It is proposed that the formation of shish kebab or lamellar morphologies in these samples is dependent on the critical density of contiguous elongated crystallization nuclei rather than any specific global criteria.

Calibration and bias correction of climate projections for crop modelling: an idealised case study over Europe

Producing projections of future crop yields requires careful thought about the appropriate use of atmosphere-ocean global climate model (AOGCM) simulations. Here we describe and demonstrate multiple methods for ‘calibrating’ climate projections using an ensemble of AOGCM simulations in a ‘perfect sibling’ framework. Crucially, this type of analysis assesses the ability of each calibration methodology to produce reliable estimates of future climate, which is not possible just using historical observations. This type of approach could be more widely adopted for assessing calibration methodologies for crop modelling. The calibration methods assessed include the commonly used ‘delta’ (change factor) and ‘nudging’ (bias correction) approaches. We focus on daily maximum temperature in summer over Europe for this idealised case study, but the methods can be generalised to other variables and other regions. The calibration methods, which are relatively easy to implement given appropriate observations, produce more robust projections of future daily maximum temperatures and heat stress than using raw model output. The choice over which calibration method to use will likely depend on the situation, but change factor approaches tend to perform best in our examples. Finally, we demonstrate that the uncertainty due to the choice of calibration methodology is a significant contributor to the total uncertainty in future climate projections for impact studies. We conclude that utilising a variety of calibration methods on output from a wide range of AOGCMs is essential to produce climate data that will ensure robust and reliable crop yield projections.

Statistical decadal predictions for sea surface temperatures: a benchmark for dynamical GCM predictions

Accurate decadal climate predictions could be used to inform adaptation actions to a changing climate. The skill of such predictions from initialised dynamical global climate models (GCMs) may be assessed by comparing with predictions from statistical models which are based solely on historical observations. This paper presents two benchmark statistical models for predicting both the radiatively forced trend and internal variability of annual mean sea surface temperatures (SSTs) on a decadal timescale based on the gridded observation data set HadISST. For both statistical models, the trend related to radiative forcing is modelled using a linear regression of SST time series at each grid box on the time series of equivalent global mean atmospheric CO2 concentration. The residual internal variability is then modelled by (1) a first-order autoregressive model (AR1) and (2) a constructed analogue model (CA). From the verification of 46 retrospective forecasts with start years from 1960 to 2005, the correlation coefficient for anomaly forecasts using trend with AR1 is greater than 0.7 over parts of extra-tropical North Atlantic, the Indian Ocean and western Pacific. This is primarily related to the prediction of the forced trend. More importantly, both CA and AR1 give skillful predictions of the internal variability of SSTs in the subpolar gyre region over the far North Atlantic for lead time of 2 to 5 years, with correlation coefficients greater than 0.5. For the subpolar gyre and parts of the South Atlantic, CA is superior to AR1 for lead time of 6 to 9 years. These statistical forecasts are also compared with ensemble mean retrospective forecasts by DePreSys, an initialised GCM. DePreSys is found to outperform the statistical models over large parts of North Atlantic for lead times of 2 to 5 years and 6 to 9 years, however trend with AR1 is generally superior to DePreSys in the North Atlantic Current region, while trend with CA is superior to DePreSys in parts of South Atlantic for lead time of 6 to 9 years. These findings encourage further development of benchmark statistical decadal prediction models, and methods to combine different predictions.

Possible role of aerosol transmission in a hospital outbreak of influenza.

BACKGROUND: We examined the role of aerosol transmission of influenza in an acute ward setting. METHODS: We investigated a seasonal influenza A outbreak that occurred in our general medical ward (with open bay ward layout) in 2008. Clinical and epidemiological information was collected in real time during the outbreak. Spatiotemporal analysis was performed to estimate the infection risk among patients. Airflow measurements were conducted, and concentrations of hypothetical virus-laden aerosols at different ward locations were estimated using computational fluid dynamics modeling. RESULTS: Nine inpatients were infected with an identical strain of influenza A/H3N2 virus. With reference to the index patient's location, the attack rate was 20.0% and 22.2% in the "same" and "adjacent" bays, respectively, but 0% in the "distant" bay (P = .04). Temporally, the risk of being infected was highest on the day when noninvasive ventilation was used in the index patient; multivariate logistic regression revealed an odds ratio of 14.9 (95% confidence interval, 1.7-131.3; P = .015). A simultaneous, directional indoor airflow blown from the "same" bay toward the "adjacent" bay was found; it was inadvertently created by an unopposed air jet from a separate air purifier placed next to the index patient's bed. Computational fluid dynamics modeling revealed that the dispersal pattern of aerosols originated from the index patient coincided with the bed locations of affected patients. CONCLUSIONS: Our findings suggest a possible role of aerosol transmission of influenza in an acute ward setting. Source and engineering controls, such as avoiding aerosol generation and improving ventilation design, may warrant consideration to prevent nosocomial outbreaks.