A rapid and multi-element method for the analysis of major nutrients in grass (Lolium perenne) using energy-dispersive X-ray fluorescence spectroscopy

peer-reviewedElemental analysis of grass (Lolium perenne) is essential in agriculture to ensure grass quality and animal health. Energy-dispersive X-ray fluorescence (EDXRF) spectroscopy is a rapid, multi-element alternative to current methods using acid digestion and inductively coupled plasma optical emission spectrometry (ICP-OES). Percentage phosphorus (P), potassium (K), magnesium (Mg) and calcium (Ca), determined from grass samples using EDXRF, were within 0.035, 0.319, 0.025 and 0.061, respectively, of ICP-OES values. Concordance correlation coefficients computed using agreement statistics ranged from 0.4379 to 0.9669 (values close to one indicate excellent agreement); however, the level of agreement for each element depended on the calibrations used in EDXRF. Empirical calibrations gave excellent agreement for percentage P, K and Ca, but moderate agreement for percentage Mg due to a weaker correlation between standards and intensities. Standardless calibration using the fundamental parameters (FP) approach exhibited bias, with consistently lower values reported for percentage P and Mg, when compared with ICP-OES methods. The relationship between the methods was plotted as scatter plots with the line of equality included, and although correlation coefficients indicated strong relationships, these statistics masked the effects of consistent bias in the data for percentage P and Mg. These results highlight the importance of distinguishing agreement from correlation when using statistical methods to compare methods of analysis. Agreement estimates improved when a matching library of grass samples was added to the FP method. EDXRF is a comparable alternative to conventional methods for grass analysis when samples of similar matrix type are used as empirical standards or as a matching library

Systematic review of antimicrobial drug prescribing in hospitals.

Prudent antibiotic prescribing to hospital inpatients has the potential to reduce the incidences of antimicrobial resistance and healthcare-associated infection. We reviewed the literature from January 1980 to November 2003 to identify rigorous evaluations of interventions to improve hospital antibiotic prescribing. We identified 66 studies with interpretable data of which 16 reported 20 microbiological outcomes: Gram negative resistant bacteria (GNRB), 10 studies; Clostridium difficile associated diarrhoea (CDAD), 5 studies; vancomycin resistant enterococci (VRE), 3 studies and methicillin resistant Staphylococcus aureus (MRSA), 2 studies. Four studies provide good evidence that the intervention changed microbial outcomes with low risk of alternative explanations, eight studies provide less convincing evidence and four studies were negative. The strongest and most consistent evidence was for CDAD but we were able to analyse only the immediate impact of interventions because of nonstandardised durations of follow up. The ability to compare results of studies could be substantially improved by standardising methodology and reporting

Pilot-scale ceramic membrane filtration of skim milk for the production of a 'humanised' protein base ingredient for infant milk formula

The protein composition of bovine skim milk was modified using pilot scale membrane filtration to produce a whey protein-dominant ingredient with a casein profile closer to human milk. Bovine skim milk was processed at low (8.9 °C) or high (50 °C) temperature using ceramic microfiltration (MF) membranes (0.1 μm mean pore diameter). The resulting permeate stream was concentrated using polyethersulfone ultrafiltration (UF) membranes (10 kDa cut-off). The protein profile of MF and UF retentate streams were determined using reversed phase-high performance liquid chromatography and polyacrylamide gel electrophoresis. Permeate from the cold MF process (8.9 °C) had a casein:whey protein ratio of ∼35:65 with no αS- or κ-casein present, compared with a casein:whey protein ratio of ∼10:90 at 50 °C. This study has demonstrated the application of cold membrane filtration (8.9 °C) at pilot scale to produce a dairy ingredient with a protein profile closer to that of human milk

Factors associated with milk processing characteristics predicted by mid-infrared spectroscopy in a large database of dairy cows

Despite milk processing characteristics being important quality traits, little is known about the factors underlying their variability, due primarily to the resources required to measure these characteristics in a sufficiently large population. Cow milk coagulation properties (rennet coagulation time, curd-firming time, curd firmness 30 and 60 min after rennet addition), heat coagulation time, casein micelle size, and pH were generated from available mid-infrared spectroscopy prediction models. The prediction models were applied to 136,807 spectra collected from 9,824 Irish dairy cows from research and commercial herds. Sources of variation were investigated using linear mixed models that included the fixed effects of calendar month of test; milking time in the day; linear regressions on the proportion of Friesian, Jersey, Montb\ue9liarde, Norwegian Red, and \u201cother\u201d breeds in the cow; coefficients of heterosis and of recombination loss; parity; stage of lactation; and the 2-way interaction parity 7 stage of lactation. Withinand across-parity cow effects, contemporary group, and a residual term were also included as random effects in the model. Supplementary analyses considered the inclusion of either test-day milk yield or milk protein concentration as fixed-effects covariates in the multiple regression models. Milk coagulation properties were most favorable (i.e., short rennet coagulation time and strong curd firmness) for cheese manufacturing in early lactation, concurrent with the lowest values of both pH and casein micelle size. Milk coagulation properties and pH deteriorated in mid lactation but improved toward the end of lactation. In direct contrast, heat coagulation time was more favorable in mid lactation and less suitable (i.e., shorter) for high temperature treatments in both early and late lactation. Relative to multiparous cows, primiparous cows, on average, yielded milk with shorter rennet coagulation time and longer heat coagulation time. Milk from the evening milking session had shorter rennet coagulation time and greater curd firmness, as well as lower heat coagulation time and lower pH compared with milk from the morning session. Jersey cows, on average, yielded milk more suitable for cheese production rather than for milk powder production. When protein concentration was included in the model, the improvement of milk coagulation properties toward the end of lactation was no longer apparent. Results from the present study may aid in decisionmaking for milk manufacturing, especially in countries characterized by a seasonal supply of fresh milk

Effectiveness of mid-infrared spectroscopy to predict the color of bovine milk and the relationship between milk color and traditional milk quality traits

The color of milk affects the subsequent color features of the resulting dairy products; milk color is also related to milk fat concentration. The objective of the present study was to quantify the ability of mid-infrared spectroscopy (MIRS) to predict color-related traits in milk samples and to estimate the correlations between these color-related characteristics and traditional milk quality traits. Mid-infrared spectral data were available on 601 milk samples from 529 cows, all of which had corresponding gold standard milk color measures determined using a Chroma Meter (Konica Minolta Sensing Europe, Nieuwegein, the Netherlands); milk color was expressed using the CIELAB uniform color space. Separate prediction equations were developed for each of the 3 color parameters (L* = lightness, a* = greenness, b* = yellowness) using partial least squares regression. Accuracy of prediction was determined using both cross validation on a calibration data set (n = 422 to 457 samples) and external validation on a data set of 144 to 152 samples. Moderate accuracy of prediction was achieved for the b* index (coefficient of correlation for external validation = 0.72), although poor predictive ability was obtained for both a* and L* indices (coefficient of correlation for external validation of 0.30 and 0.55, respectively). The linear regression coefficient of the gold standard values on the respective MIRS-predicted values of a*, L*, and b* was 0.81, 0.88, and 0.96, respectively; only the regression coefficient on L* was different from 1. The mean bias of prediction (i.e., the average difference between the MIRS-predicted values and gold standard values in external validation) was not different from zero for any of 3 parameters evaluated. A moderate correlation (0.56) existed between the MIRS-predicted L* and b* indices, both of which were weakly correlated with the a* index. Milk fat, protein, and casein were moderately correlated with both the gold standard and MIRS-predicted values for b*. Results from the present study indicate that MIRS data provides an efficient, low-cost screening method to determine the b* color of milk at a population level

Novas Idéias Sobre os Mecanismos Eletrofisiológicos da Fibrilaçao Atrial suas Implicaçoes Terapêuticas

A fibrilaçao atrial (FA) é a arritmia cardíaca sustentada mais frequente na prática clínica e está associada a morbidade e mortalidade significativas. Nos últimos anos, houve grandes progressos no entendimento dos vários mecanismos eletrofisiológicos envolvidos na gênese e perpetuaçao dessa arritmia. Observou-se que a FA pode ser desencadeada por mecanismos focais, localizados principalmente nas veias pulmonares. Evidências experimentais e clínicas sugerem que a FA promove alteraçoes anatômicas e elétricas nos átrios que favorecem a sua perpetuaçao. Esses novos conceitos têm redirecionado a abordagem terapêutica dos pacientes com FA. Vários métodos nao farmacológicos para o tratamento da FA estao em desenvolvimento, incluindo ablaçao por cateter com radiofrequência, marcapassos com dupla estimulaçao atrial e desfibriladores atriais implantáveis. Apesar de promissores, o valor e a aplicabilidade clínica desses métodos ainda nao foram definidos. A associaçao de modalidades terapêuticas com o objetivo de obter um efeito sinérgico pode contribuir favoravelmente para o tratamento da FA. Este artigo revisa os novos conceitos fisiopatológicos da FA e analisa o impacto desses avanços na abordagem terapêutica de pacientes com essa arritmia

Novas Idéias Sobre os Mecanismos Eletrofisiológicos da Fibrilaçao Atrial suas Implicaçoes Terapêuticas

A fibrilaçao atrial (FA) é a arritmia cardíaca sustentada mais frequente na prática clínica e está associada a morbidade e mortalidade significativas. Nos últimos anos, houve grandes progressos no entendimento dos vários mecanismos eletrofisiológicos envolvidos na gênese e perpetuaçao dessa arritmia. Observou-se que a FA pode ser desencadeada por mecanismos focais, localizados principalmente nas veias pulmonares. Evidências experimentais e clínicas sugerem que a FA promove alteraçoes anatômicas e elétricas nos átrios que favorecem a sua perpetuaçao. Esses novos conceitos têm redirecionado a abordagem terapêutica dos pacientes com FA. Vários métodos nao farmacológicos para o tratamento da FA estao em desenvolvimento, incluindo ablaçao por cateter com radiofrequência, marcapassos com dupla estimulaçao atrial e desfibriladores atriais implantáveis. Apesar de promissores, o valor e a aplicabilidade clínica desses métodos ainda nao foram definidos. A associaçao de modalidades terapêuticas com o objetivo de obter um efeito sinérgico pode contribuir favoravelmente para o tratamento da FA. Este artigo revisa os novos conceitos fisiopatológicos da FA e analisa o impacto desses avanços na abordagem terapêutica de pacientes com essa arritmia

Prediction of bovine milk technological traits from mid-infrared spectroscopy analysis in dairy cows

Rapid, cost-effective monitoring of milk technological traits is a significant challenge for dairy industries specialized in cheese manufacturing. The objective of the present study was to investigate the ability of mid-infrared spectroscopy to predict rennet coagulation time, curd-firming time, curd firmness at 30 and 60\u2005min after rennet addition, heat coagulation time, casein micelle size, and pH in cow milk samples, and to quantify associations between these milk technological traits and conventional milk quality traits. Samples (n\u2005=\u2005713) were collected from 605 cows from multiple herds; the samples represented multiple breeds, stages of lactation, parities, and milking times. Reference analyses were undertaken in accordance with standardized methods, and mid-infrared spectra in the range of 900 to 5,000\u2005cm 121 were available for all samples. Prediction models were developed using partial least squares regression, and prediction accuracy was based on both cross and external validation. The proportion of variance explained by the prediction models in external validation was greatest for pH (71%), followed by rennet coagulation time (55%) and milk heat coagulation time (46%). Models to predict curd firmness 60\u2005min from rennet addition and casein micelle size, however, were poor, explaining only 25 and 13%, respectively, of the total variance in each trait within external validation. On average, all prediction models tended to be unbiased. The linear regression coefficient of the reference value on the predicted value varied from 0.17 (casein micelle size regression model) to 0.83 (pH regression model) but all differed from 1. The ratio performance deviation of 1.07 (casein micelle size prediction model) to 1.79 (pH prediction model) for all prediction models in the external validation was <2, suggesting that none of the prediction models could be used for analytical purposes. With the exception of casein micelle size and curd firmness at 60\u2005min after rennet addition, the developed prediction models may be useful as a screening method, because the concordance correlation coefficient ranged from 0.63 (heat coagulation time prediction model) to 0.84 (pH prediction model) in the external validation

Prediction of bovine milk technological traits from mid-infrared spectroscopy analysis in dairy cows

peer-reviewedRapid, cost-effective monitoring of milk technological traits is a significant challenge for dairy industries specialized in cheese manufacturing. The objective of the present study was to investigate the ability of mid-infrared spectroscopy to predict rennet coagulation time, curd-firming time, curd firmness at 30 and 60 min after rennet addition, heat coagulation time, casein micelle size, and pH in cow milk samples, and to quantify associations between these milk technological traits and conventional milk quality traits. Samples (n = 713) were collected from 605 cows from multiple herds; the samples represented multiple breeds, stages of lactation, parities, and milking times. Reference analyses were undertaken in accordance with standardized methods, and mid-infrared spectra in the range of 900 to 5,000 cm−1 were available for all samples. Prediction models were developed using partial least squares regression, and prediction accuracy was based on both cross and external validation. The proportion of variance explained by the prediction models in external validation was greatest for pH (71%), followed by rennet coagulation time (55%) and milk heat coagulation time (46%). Models to predict curd firmness 60 min from rennet addition and casein micelle size, however, were poor, explaining only 25 and 13%, respectively, of the total variance in each trait within external validation. On average, all prediction models tended to be unbiased. The linear regression coefficient of the reference value on the predicted value varied from 0.17 (casein micelle size regression model) to 0.83 (pH regression model) but all differed from 1. The ratio performance deviation of 1.07 (casein micelle size prediction model) to 1.79 (pH prediction model) for all prediction models in the external validation was <2, suggesting that none of the prediction models could be used for analytical purposes. With the exception of casein micelle size and curd firmness at 60 min after rennet addition, the developed prediction models may be useful as a screening method, because the concordance correlation coefficient ranged from 0.63 (heat coagulation time prediction model) to 0.84 (pH prediction model) in the external validation

Processing characteristics of dairy cow milk are moderately heritable.

Milk processing attributes represent a group of milk quality traits that are important to the dairy industry to inform product portfolio. However, because of the resources required to routinely measure such quality traits, precise genetic parameter estimates from a large population of animals are lacking for these traits. Milk processing characteristics considered in the present study—rennet coagulation time, curd-firming time, curd firmness at 30 and 60 min after rennet addition, heat coagulation time, casein micelle size, and milk pH—were all estimated using mid-infrared spectroscopy prediction equations. Variance components for these traits were estimated using 136,807 test-day records from 5 to 305 d in milk (DIM) from 9,824 cows using random regressions to model the additive genetic and within-lactation permanent environmental variances. Heritability estimates ranged from 0.18 ± 0.01 (26 DIM) to 0.38 ± 0.02 (180 DIM) for rennet coagulation time; from 0.26 ± 0.02 (5 DIM) to 0.57 ± 0.02 (174 DIM) for curd-firming time; from 0.16 ± 0.01 (30 DIM) to 0.56 ± 0.02 (271 DIM) for curd firmness at 30 min; from 0.13 ± 0.01 (30 DIM) to 0.48 ± 0.02 (271 DIM) for curd firmness at 60 min; from 0.08 ± 0.01 (17 DIM) to 0.24 ± 0.01 (180 DIM) for heat coagulation time; from 0.23 ± 0.02 (30 DIM) to 0.43 ± 0.02 (261 DIM) for casein micelle size; and from 0.20 ± 0.01 (30 DIM) to 0.36 ± 0.02 (151 DIM) for milk pH. Within-trait genetic correlations across DIM weakened as the number of days between compared intervals increased but were mostly >0.4 except between the peripheries of the lactation. Eigenvalues and associated eigenfunctions of the additive genetic covariance matrix for all traits revealed that at least the 80% of the genetic variation among animals in lactation profiles was associated with the height of the lactation profile. Curd-firming time and curd firmness at 30 min were weakly to moderately genetically correlated with milk yield (from 0.33 ± 0.05 to 0.59 ± 0.05 for curd-firming time, and from −0.62 ± 0.03 to −0.21 ± 0.06 for curd firmness at 30 min). Milk protein concentration was strongly genetically correlated with curd firmness at 30 min (0.84 ± 0.02 to 0.94 ± 0.01) but only weakly genetically correlated with milk heat coagulation time (−0.27 ± 0.07 to 0.19 ± 0.06). Results from the present study indicate the existence of exploitable genetic variation for milk processing characteristics. Because of possible indirect deterioration in milk processing characteristics due to selection for greater milk yield, emphasis on milk processing characteristics is advised