Impact on prime animal beef merit from breeding solely for lighter dairy cows.

As the proportion of prime carcasses originating from dairy herds increases, the focus is shifting to the beef merit of the progeny from dairy herds. Several dairy cow total merit indexes include a negative weight on measures of cow size. However, there is a lack of knowledge on the impact of genetic selection, solely for lighter or smaller-sized dairy cows, on the beef performance of their progeny. Therefore, the objective of this study was to quantify the genetic correlations among cow size traits (i.e., cow body weight (BW), cow carcass weight (CW)), cow body condition score (BCS), cow carcass conformation (CC), and cow carcass fat cover (CF), as well as the correlations between these cow traits and a series of beef performance slaughter-related traits (i.e., CW, CC, CF, and age at slaughter (AS)) in their progeny. After data editing, there were 52,950 cow BW and BCS records, along with 57,509 cow carcass traits (i.e., CW, CC, and CF); carcass records from 346,350 prime animals along with AS records from 316,073 prime animals were also used. Heritability estimates ranged from moderate to high (0.18 to 0.62) for all cow and prime animal traits. The same carcass trait in cows and prime animals were strongly genetically correlated with each other (0.76 to 0.85), implying that they are influenced by very similar genomic variants. Selecting exclusively for cows with higher BCS (i.e., fatter) will, on average, produce more conformed prime animals carcasses, owing to a moderate genetic correlation (0.30) between both traits. Genetic correlations revealed that selecting exclusively for lighter BW or CW cows will, on average, result in lighter prime animal carcasses of poor CC, while also delaying slaughter age. Nonetheless, selective breeding through total merit indexes should be successful in breeding for smaller dairy cows, and desirable prime animal carcass traits concurrently, because of the non-unity genetic correlations between the cow and prime animal traits; this will help to achieve a more ethical, environmentally sustainable, and economically viable dairy-beef industry.

The association between calf birth weight and the postcalving performance of its dairy dam in the absence of dystocia.

The objective of the study was to quantify the association between the birth weight of a calf and the subsequent performance of its dairy dam in the absence of any recorded calving assistance. A total of 11,592 lactation records from 4,549 spring-calving dairy cows were used. The association between a series of quantitative cow performance metrics (dependent variable) and calf birth weight (independent variable) was determined using linear mixed models; logistic regression was used where the dependent variable was binary. Nuisance factors in the models were calf sex, heterosis coefficient of both the cow and calf, dry period length immediately before the birth of the calf, cow age at calving relative to the median cow age per parity, breed proportion of the cow, cow live weight between 100 and 200 d of lactation relative to the mean cow weight per parity, and contemporary group. Calf birth weight was included in the model as either a continuous or a categorical variable. Primiparous and multiparous cows were analyzed separately. Mean (SD) calf birth weight was 36.2 (6.8) kg. In primiparous cows, calf birth weight was associated with milk yield in the first 60 d of lactation, calving to first service interval, calving body weight (BW), and both nadir BW and body condition score (BCS). In multiparous cows, calf birth weight was associated with total milk, fat, and protein yield in the first 60 and 305 d of lactation, peak milk yield, total milk solids, both calving and nadir BW, and BCS loss from calving to nadir. Relative to primiparous cows that gave birth to calves weighing 34 to 37 kg (i.e., population mean), their contemporaries who gave birth to calves that weighed 15 to 29 kg produced 9.82 kg more milk in the first 60 d of lactation, had a 2-d shorter interval to first service, and were 8.08 kg and 5.51 kg lighter at calving and nadir BW, respectively; the former was also 0.05 units lower in BCS (5-point scale, 1 = emaciated and 5 = obese) at nadir. Relative to multiparous cows that gave birth to calves that were 34 to 37 kg birth weight, multiparous cows that gave birth to calves that were 15 to 29 kg yielded 59.63 kg, 2.44 kg, and 1.76 kg less milk, fat, and protein, respectively, in the first 60 d of lactation; produced 17.69 kg less milk solids throughout the 305-d lactation; and were also 10.49 kg lighter at nadir and lost 0.01 units more BCS to nadir. In a separate series of analyses, sire breed was added to the model as a fixed effect with and without calf birth weight. When calf birth weight was not adjusted for, 60-d milk yield for multiparous cows who gave birth to calves sired by a traditional beef breed (i.e., Angus, Hereford) produced 59.63 kg more milk than multiparous cows who gave birth to calves sired by a Holstein-Friesian. Hence, calf birth weight is associated with some subsequent dam performance measures; however, where associations do exist, the effect is biologically small.

Hospital Reservoirs of Multidrug Resistant Acinetobacter Species-The Elephant in the Room!

Environmental contamination is estimated to contribute to up to 20% of all hospital acquired infections. Acinetobacter baumannii is an example of one the most prevalent opportunistic pathogens causing severe and persistent infections in immunocompromised patients. It has proven ability to form biofilms, has significant associated multi-drug resistance and is able to transfer mobile genetic elements to other clinically relevant pathogens. All of these factors point to a definite utility of A. baumannii as an indicator organism for effectiveness of decontamination regimens as well as environmental screening. There is an increased cost, both financial and clinical, associated with multi drug resistant organisms, carbapenem resistant A. baumannii. With a dearth of new antimicrobials in development, now is the time to radically transform and lead the introduction of scientifically based environmental screening and microbiological verified decontamination to control the dissemination of further resistance.

Re-assessing the importance of linear type traits in predicting genetic merit for survival in an aging Holstein-Friesian dairy cow population.

The cumulative improvement achieved in the genetic merit for reproductive performance in dairy populations will likely improve dairy cow longevity; therefore, it is time to reassess whether linear type traits are still suitable predictors of survival in an aging dairy cow population. The objective of the present study was therefore to estimate the genetic correlations between linear type traits and survival from one parity to the next and, in doing so, evaluate if those genetic correlations change with advancing parity. After edits, 152,894 lactation survival records (first to ninth parity) were available from 52,447 Holstein-Friesian cows, along with linear type trait records from 52,121 Holstein-Friesian cows. A series of bivariate random regression models were used to estimate the genetic covariances between survival in different parities and each linear type trait. Heritability estimates for survival per parity ranged from 0.02 (SE = 0.004; first parity) to 0.05 (SE = 0.01; ninth parity). Pairwise genetic correlations between survival among different parities varied from 0.42 (first and ninth parity) to 1.00 (eighth to ninth parity), with the strength of these genetic correlations being inversely related to the interval between the compared parities. The genetic correlations between survival and the individual linear type traits varied across parities for 9 of the 20 linear type traits examined, but the correlations with only 3 of these linear type traits strengthened as the cows aged; these 3 traits were rear udder height, teat length, and udder depth. Given that linear type traits are frequently scored in first parity and are genetically correlated with survival in older parities, they may be suitable early predictors of survival, especially for later parity cows. Additionally, the direction of the genetic correlations between survival and rear udder height, teat length, and udder depth did not change between parities; hence, selection for survival in older parities using these linear type traits should not hinder genetic improvement for survival in younger parities.

Exploiting genetic variability in the trajectory of lactation yield and somatic cell score with each progressing parity.

The inclusion of reproductive performance in dairy cow breeding schemes has resulted in a cumulative improvement in genetic merit for reproductive performance; this improvement should manifest in longer productive lives through a reduced requirement for involuntary culling. Nonetheless, the average length of dairy cow productive life has not changed in most populations, suggesting that risk factors for culling, especially in older cows, are possibly more associated with lower yield or high somatic cell score (SCS) than compromised reproductive performance. The objective of the present study was to understand the dynamics of lactation yields and SCS in dairy cows across parities and, in doing so, quantify the potential to alter this trajectory through breeding. After edits, 3,470,520 305-d milk, fat, and protein yields, as well as milk fat and protein percentage and somatic cell count records from 1,162,473 dairy cows were available for analysis. Random regression animal models were used to identify the parity in which individual cows reached their maximum lactation yields, and highest average milk composition and SCS; also estimated from these models were the (co)variance components for yield, composition, and SCS per parity across parities. Estimated breeding values for all traits per parity were calculated for cows reaching ≥fifth parity. Of the cows included in the analyses, 91.0%, 92.2%, and 83.4% reached maximum milk, fat, and protein yield in fifth parity, respectively. Conversely, 95.9% of cows reached their highest average fat percentage in first parity and 62.9% of cows reached their highest average protein percentage in third parity. In contrast to both milk yield and composition traits, 98.4% of cows reached their highest average SCS in eighth parity. Individual parity estimates of heritability for milk yield traits, milk composition, and SCS ranged from 0.28 to 0.44, 0.47 to 0.69, and 0.13 to 0.23, respectively. The strength of the genetic correlations per trait among parities was inversely related to the interval between the parities compared; the weakest genetic correlation was 0.67 (standard error = 0.02) between milk yield in parities 1 and 8. Eigenvalues and eigenfunctions of the additive genetic covariance matrices for all investigated traits revealed potential to alter the trajectory of parity profiles for milk yield, milk composition, and SCS. This was further demonstrated when evaluating the trajectories of animal estimated breeding values per parity.

Are subjectively scored linear type traits suitable predictors of the genetic merit for feed intake in grazing Holstein-Friesian dairy cows?

Measuring dry matter intake (DMI) in grazing dairy cows using currently available techniques is invasive, time consuming, and expensive. An alternative to directly measuring DMI for use in genetic evaluations is to identify a set of readily available animal features that can be used in a multitrait genetic evaluation for DMI. The objectives of the present study were thus to estimate the genetic correlations between readily available body-related linear type traits and DMI in grazing lactating Holstein-Friesian cows, but importantly also estimate the partial genetic correlations between these linear traits and DMI, after adjusting for differences in genetic merit for body weight. Also of interest was whether the predictive ability derived from the estimated genetic correlations materialized upon validation. After edits, a total of 8,055 test-day records of DMI, body weight, and milk yield from 1,331 Holstein-Friesian cows were available, as were chest width, body depth, and stature from 47,141 first lactation Holstein-Friesian cows. In addition to considering the routinely recorded linear type traits individually, novel composite traits were defined as the product of the linear type traits as an approximation of rumen volume. All linear type traits were moderately heritable, with heritability estimates ranging from 0.27 (standard error = 0.14) to 0.49 (standard error = 0.15); furthermore, all linear type traits were genetically correlated (0.29 to 0.63, standard error 0.14 to 0.12) with DMI. The genetic correlations between the individual linear type traits and DMI, when adjusted for genetic differences in body weight, varied from -0.51 (stature) to 0.48 (chest width). These genetic correlations between DMI and linear type traits suggest linear type traits may be useful predictors of DMI, even when body weight information is available. Nonetheless, estimated genetic merit of DMI derived from a multitrait genetic evaluation of linear type traits did not correlate strongly with actual DMI in a set of validation animals; the benefit was even less if body weight data were also available.

Commercial beef farms excelling in terminal and maternal genetic merit generate more gross profit.

Validation of beef total merit breeding indexes for improving performance and profitability has previously been undertaken at the individual animal level; however, no herd-level validation of beef genetic merit and profit has been previously investigated. The objective of the present study was to quantify the relationship between herd profitability and both herd-average terminal and maternal genetic merit across 1,311 commercial Irish beef herds. Herd-level physical and financial performance data were available from a financial benchmarking tool used by Irish farmers and their extension advisors. Animal genetic merit data originated from the Irish Cattle Breeding Federation who undertake the national beef and dairy genetic evaluations. Herd-average genetic merit variables included the terminal index of young animals, the maternal index of dams, and the terminal index of service sires. The herds represented three production systems: 1) cow-calf to beef, 2) cow-calf to weanling/yearling, and 3) weanling/yearling to beef. Associations between herd financial performance metrics and herd average genetic merit variables were quantified using a series of linear mixed models with year, production system, herd size, stocking rate, concentrate input, and the two-way interactions between production system and herd size, stocking rate, and concentrate input included as nuisance factors. Herd nested within the county of Ireland (n = 26) was included as a repeated effect. Herds with young cattle excelling in terminal index enjoyed greater gross and net profit per hectare (ha), per livestock unit (LU), and per kg net live-weight output. The change in gross profit per LU per unit change in the terminal index of young animals was €1.41 (SE = 0.23), while the respective regression coefficient for net profit per LU was €1.37 (SE = 0.30); the standard deviation of the terminal index is €37. Herd-average dam maternal index and sire terminal index were both independently positively associated with gross profit per ha and gross profit per LU. Each one unit increase in dam maternal index (standard deviation of €38) was associated with a €1.40 (SE = 0.48) and €0.76 (SE = 0.29) greater gross profit per ha and per LU, respectively. Results from the present study at the herd-level concur with previous validation studies at the individual animal level thus instilling further confidence among stakeholders as to the expected improvement in herd profitability with improving genetic merit.

Genetic and nongenetic factors associated with lactation length in seasonal-calving, pasture-based dairy cows.

Lactation yield estimates standardized to common lactation lengths of 270-d or 305-d equivalents are commonly used in management decision support tools and dairy cow genetic evaluations. The use of such measurements to quantify the (genetic) merit of individual cows fails to penalize cows that do not reach the standardized lactation length, or indeed reward cows that lactate for more than the standardized lactation length. The objective of the present study was to quantify the genetic and nongenetic factors associated with lactation length in seasonal-calving, pasture-based dairy cows. A total of 616,350 lactation length records from 285,598 Irish cows were used. Linear mixed models were used to quantify the associations between lactation length and calving month, parity, age at calving, previous dry period length, calving difficulty score, heterosis, recombination loss, breed, and herd size, as well as to estimate the genetic and residual variance components of lactation length. The median lactation length in the edited data set was 288 d, with 27% of cows achieving lactations of at least 305 d. Relative to cows calving in January, the lactations of cow calving in February, March, or April was, on average, 4.2, 12.7, and 21.9 d shorter, respectively. The lactation length of a first parity cow was, on average, 7.8, 8.6, and 8.4 d shorter than that of second, third, and fourth parity cows, respectively. Norwegian Red and Montbéliarde cows had, on average, a 4.7- and 1.6-d shorter lactation than Holstein-Friesian cows, respectively. The heritability estimate, coefficient of genetic variation, and repeatability estimate of lactation length were 0.02, 1.2%, and 0.04, respectively. Based on the genetic standard deviation for lactation length estimated in the present study (3.3 d), cows ranked in the top 20% for genetic merit for lactation length would be expected to have lactations 9.2 d longer than cows in the bottom 20%, demonstrating exploitable genetic variability. Given the vast array of genetic and nongenetic factors associated with lactation length, an approach which combines improved management practices and selective breeding may be an efficient and effective strategy to lengthen lactations.

Carbapenemase screening in an Irish tertiary referral hospital: Best practice, or can we do better?

BACKGROUND: Carbapenems are a family of end line antibiotics with increasing levels of resistance that are a cause for concern. AIM: To ascertain whether the CPE screening programme employed in an acute tertiary hospital is fit for purpose. METHOD: We outlined the current working algorithm employed using a universal screening programme over a 26-month screening period. Rectal swabs are cultured on arrival. Those with suspicious growth are further investigated using NG-Carba 5 lateral flow tests and Vitek 2.0 sensitivity cards. These practices were compared with NHS guidelines. FINDINGS & CONCLUSIONS: In all, 53 true positives were detected from 45 patients since the screening was implemented in early 2018 (46 OXA-48, 6 KPC, 1 NDM). As the rate of screening increased, the number of positive screens decreased over time. There were a lot of similarities between the HSE guidelines and the published NHS CPE toolkit. It was evident that there is no standard practice being employed across all hospitals. Comparing the MUH to national guidelines it appears to be quicker and more effective with universal screening in place at reducing the potential contacts and identifying carriers. Cost analysis indicates that the need to confirm all positive strains in a reference lab is costly, unnecessary and time consuming. There are adequate confirmatory tests available in-house for routine positive screens. It was concluded that infection prevention and control are key to identifying and controlling possible outbreaks in a hospital setting.

The effect of concentrate supplementation on milk production and cow traffic in early and late lactation in a pasture-based automatic milking system.

The objective of this experiment was to establish the effect of low-concentrate (LC) and high-concentrate (HC) supplementation in the early and late periods of lactation on milk production and cow traffic in a pasture-based automatic milking (AM) system. In total, 40 cows (10 primiparous and 30 multiparous) were randomly assigned to one of the two treatments. The experimental periods for the early and late lactation trials extended from 23 February to 12 April 2015 and 31 August to 18 October 2015, respectively (49 days in each trial period). The early lactation supplement levels were 2.3 and 4.4 kg/cow per day for LC and HC, respectively, whereas the late lactation supplement levels were 0.5 and 2.7 kg/cow per day for LC and HC, respectively. Variables measured included milking frequency, milking interval, milking outcome and milking characteristics, milk yield/visit and per day, wait time/visit and per day, return time/visit and the distribution of gate passes. As the herd was seasonal (spring) calving, the experimental periods could not run concurrently and as a result no statistical comparison between the periods was conducted. There was no significant effect of treatment in the early lactation period on any of the milk production, milking characteristics or cow traffic variables. However, treatment did significantly affect the distribution of gate passes, with the HC cows recording significantly more gate passes in the hours preceding the gate time change such as hours 7 (P<0.01), 15 (P<0.05), 20, 21 (P<0.001), and 22 (P<0.05), whereas the LC treatment recorded significantly more gate passes in the hours succeeding the gate time change, such as time points 2 (P<0.01) and 10 (P<0.05). There was a significant effect of treatment in late lactation, with HC having a greater milk yield (P<0.01), milking duration and activity/day (P<0.05), while also having a significantly shorter milking interval (P<0.05) and return time/visit (P<0.01). The distribution of gate passes were similar to the early lactation period, with HC also recording a significantly greater number of gate passes during the early morning period (P<0.01) when visitations were at their lowest. Any decision regarding the supplementing of dairy cows with concentrates needs to be examined from an economic perspective, to establish if the milk production and cow traffic benefits displayed in late lactation outweigh the cost of the concentrate; thereby ensuring that the decision to supplement is financially prudent.

Daily and seasonal trends of electricity and water use on pasture-based automatic milking dairy farms.

The objective of this study was to identify the major electricity and water-consuming components of a pasture-based automatic milking (AM) system and to establish the daily and seasonal consumption trends. Electricity and water meters were installed on 7 seasonal calving pasture-based AM farms across Ireland. Electricity-consuming processes and equipment that were metered for consumption included milk cooling components, air compressors, AM unit(s), auxiliary water heaters, water pumps, lights, sockets, automatic manure scrapers, and so on. On-farm direct water-consuming processes and equipment were metered and included AM unit(s), auxiliary water heaters, tubular coolers, wash-down water pumps, livestock drinking water supply, and miscellaneous water taps. Data were collected and analyzed for the 12-mo period of 2015. The average AM farm examined had 114 cows, milking with 1.85 robots, performing a total of 105 milkings/AM unit per day. Total electricity consumption and costs were 62.6 Wh/L of milk produced and 0.91 cents/L, respectively. Milking (vacuum and milk pumping, within-AM unit water heating) had the largest electrical consumption at 33%, followed by air compressing (26%), milk cooling (18%), auxiliary water heating (8%), water pumping (4%), and other electricity-consuming processes (11%). Electricity costs followed a similar trend to that of consumption, with the milking process and water pumping accounting for the highest and lowest cost, respectively. The pattern of daily electricity consumption was similar across the lactation periods, with peak consumption occurring at 0100, 0800, and between 1300 and 1600 h. The trends in seasonal electricity consumption followed the seasonal milk production curve. Total water consumption was 3.7 L of water/L of milk produced. Water consumption associated with the dairy herd at the milking shed represented 42% of total water consumed on the farm. Daily water consumption trends indicated consumption to be lowest in the early morning period (0300-0600 h), followed by spikes in consumption between 1100 and 1400 h. Seasonal water trends followed the seasonal milk production curve, except for the month of May, when water consumption was reduced due to above-average rainfall. This study provides a useful insight into the consumption of electricity and water on a pasture-based AM farms, while also facilitating the development of future strategies and technologies likely to increase the sustainability of AM systems.

The impact of multi-generational genotype imputation strategies on imputation accuracy and subsequent genomic predictions.

The objective of the present study was to quantify, using simulations, the impact of successive generations of genotype imputation on genomic predictions. The impact of using a small reference population of true genotypes versus a larger reference population of imputed genotypes on the accuracy of genomic predictions was also investigated. After construction of a founder population, high-density (HD) genotypes ( = 43,500 single nucleotide polymorphisms, SNP) were simulated across 25 generations ( = 46,800 per generation); a low-density genotype panel ( = 3,000 SNP) was developed from these HD genotypes, which was then used to impute genotypes using 7 alternative imputation strategies. Both low (0.03) and moderately (0.35) heritable phenotypes were simulated. Direct genomic values (DGV) were estimated using imputed genotypes from the investigated scenarios and the accuracy of predicting the simulated true breeding values (TBV) were expressed relative to the accuracy when the true genotypes were used. Mean allele concordance rate and the rate of change in mean allele concordance per generation differed between the imputation strategies investigated. Imputation was most accurate when the true HD genotypes of sires and 50% of the dams of the generation being imputed were included in the reference population; the average allele concordance rate for this scenario across generations was 0.9707. The strongest correlation between the TBV and DGV of the last generation was when the reference population included sequentially imputed HD genotypes of all previous generations, plus the true HD genotypes of all sires of the previous generations (0.987 as efficient as when the true genotypes were used in the reference population). With a moderate heritability, the correlation between the TBV and the DGV using a small reference population of accurate genotypes were, on average, 0.07 units stronger compared to DGV generated using a larger population of imputed genotypes. When the heritability was low, the accuracy of genomic predictions benefited from a larger reference population, even if SNP were imputed. The impact on the accuracy of genomic predictions from the accumulation of imputation errors across generations indicates the need to routinely generate HD genotypes on influential animals to reduce the accumulation of imputation errors over generations.

Ultra-low-density genotype panels for breed assignment of Angus and Hereford cattle.

Angus and Hereford beef is marketed internationally for apparent superior meat quality attributes; DNA-based breed authenticity could be a useful instrument to ensure consumer confidence on premium meat products. The objective of this study was to develop an ultra-low-density genotype panel to accurately quantify the Angus and Hereford breed proportion in biological samples. Medium-density genotypes (13 306 single nucleotide polymorphisms (SNPs)) were available on 54 703 commercial and 4042 purebred animals. The breed proportion of the commercial animals was generated from the medium-density genotypes and this estimate was regarded as the gold-standard breed composition. Ten genotype panels (100 to 1000 SNPs) were developed from the medium-density genotypes; five methods were used to identify the most informative SNPs and these included the Delta statistic, the fixation (F st) statistic and an index of both. Breed assignment analyses were undertaken for each breed, panel density and SNP selection method separately with a programme to infer population structure using the entire 13 306 SNP panel (representing the gold-standard measure). Breed assignment was undertaken for all commercial animals (n=54 703), animals deemed to contain some proportion of Angus based on pedigree (n=5740) and animals deemed to contain some proportion of Hereford based on pedigree (n=5187). The predicted breed proportion of all animals from the lower density panels was then compared with the gold-standard breed prediction. Panel density, SNP selection method and breed all had a significant effect on the correlation of predicted and actual breed proportion. Regardless of breed, the Index method of SNP selection numerically (but not significantly) outperformed all other selection methods in accuracy (i.e. correlation and root mean square of prediction) when panel density was ⩾300 SNPs. The correlation between actual and predicted breed proportion increased as panel density increased. Using 300 SNPs (selected using the global index method), the correlation between predicted and actual breed proportion was 0.993 and 0.995 in the Angus and Hereford validation populations, respectively. When SNP panels optimised for breed prediction in one population were used to predict the breed proportion of a separate population, the correlation between predicted and actual breed proportion was 0.034 and 0.044 weaker in the Hereford and Angus populations, respectively (using the 300 SNP panel). It is necessary to include at least 300 to 400 SNPs (per breed) on genotype panels to accurately predict breed proportion from biological samples.

Investment appraisal of automatic milking and conventional milking technologies in a pasture-based dairy system.

The successful integration of automatic milking (AM) systems and grazing has resulted in AM becoming a feasible alternative to conventional milking (CM) in pasture-based systems. The objective of this study was to identify the profitability of AM in a pasture-based system, relative to CM herringbone parlors with 2 different levels of automation, across 2 farm sizes, over a 10-yr period following initial investment. The scenarios which were evaluated were (1) a medium farm milking 70 cows twice daily, with 1 AM unit, a 12-unit CM medium-specification (MS) parlor and a 12-unit CM high-specification (HS) parlor, and (2) a large farm milking 140 cows twice daily with 2 AM units, a 20-unit CM MS parlor and a 20-unit CM HS parlor. A stochastic whole-farm budgetary simulation model combined capital investment costs and annual labor and maintenance costs for each investment scenario, with each scenario evaluated using multiple financial metrics, such as annual net profit, annual net cash flow, total discounted net profitability, total discounted net cash flow, and return on investment. The capital required for each investment was financed from borrowings at an interest rate of 5% and repaid over 10-yr, whereas milking equipment and building infrastructure were depreciated over 10 and 20 yr, respectively. A supporting labor audit (conducted on both AM and CM farms) showed a 36% reduction in labor demand associated with AM. However, despite this reduction in labor, MS CM technologies consistently achieved greater profitability, irrespective of farm size. The AM system achieved intermediate profitability at medium farm size; it was 0.5% less profitable than HS technology at the large farm size. The difference in profitability was greatest in the years after the initial investment. This study indicated that although milking with AM was less profitable than MS technologies, it was competitive when compared with a CM parlor of similar technology.

Evaluation of developed low-density genotype panels for imputation to higher density in independent dairy and beef cattle populations.

The objective of this study was to develop, using alternative algorithms, low-density SNP genotyping panels (384 to 12,000 SNP), which can be accurately imputed to higher-density panels across independent cattle populations. Single nucleotide polymorphisms were selected based on genomic characteristics (i.e., linkage disequilibrium [LD], minor allele frequency [MAF], and genomic distance) in a population of 1,267 Holstein-Friesian animals genotyped on the Illumina Bovine50 Beadchip (54,001 SNP). Single nucleotide polymorphism selection methods included 1) random; 2) equidistant location; 3) combination of SNP MAF and LD structure while maintaining relatively equal genomic distance between adjacent SNP; 4) a combination of high MAF, genomic distance between selected and candidate SNP, and correlation between genotypes of selected and candidate SNP; and 5) a machine learning algorithm. The panels were validated separately in 1) a population of 750 Holstein-Friesian animals with masked genotypes to reflect the lower-density SNP densities under investigation (1,249 animals with complete genotypes included in reference population) and 2) a population of 359 Limousin and Charolais cattle with high (777,962 SNP)-density genotypes (1,918 animals with complete genotypes included in the reference population). Irrespective of SNP selection method, imputation accuracy in both populations improved at a diminishing rate as the number of SNP included in the lower-density genotype panel increased. Additionally, the variability in mean imputation accuracy per individual decreased as the panel density increased. The SNP selection method had a major impact on the mean allele concordance rate, although its impact diminished as the panel density increased. Imputation accuracy for SNP selected using a combination of high SNP MAF, LD structure, and relatively equal genomic distance between SNP outperformed all other selection methods in densities < 12,000 SNP. Using this method of SNP selection, the correlation between the imputed and actual genotypes for the 3,000 SNP panel was 0.90 and 0.96 when applied to the beef and dairy populations, respectively; the respective correlations for the 6,000 SNP panel were 0.95 and 0.98. It is necessary to include between 3,000 and 6,000 SNP in a low-density panel to achieve adequate imputation accuracy to either medium density (approximately 50,000 SNP in the dairy population) or high density (approximately 700,000 SNP in the beef population) across diverse and independent populations.

Vancomycin-resistant enterococci carriage in an acute Irish hospital.

BACKGROUND: Ireland has been shown to have the highest rate of vancomycin-resistant enterococci (VRE) in cases of bacteraemia in Europe, according to a report in 2014 from the European Antimicrobial Resistance Surveillance System Network. AIM: To investigate the prevalence of VRE gut colonization in a cohort of patients in 2014 at Cork University Hospital (CUH) by performing a cross-sectional study using faecal samples submitted to the microbiology laboratory for routine investigation from both hospital inpatients and community-based patients. METHODS: Faeces were examined for VRE colonization using selective cultivation, antimicrobial susceptibility testing, and speciation using matrix-assisted laser desorption ionization time-of-flight mass spectrometry. All VRE isolates were evaluated by molecular means for resistance determinants, type, and Insertion Sequence 16 as an indicator of Clonal Complex 17 (CC17). FINDINGS: From the 350 specimens investigated, 67 (19.1%) specimens were positive for VRE [95% confidence interval (CI): 15.0-23.2]. The prevalence of VRE colonization among CUH patients tested in this study (N = 194) was 31.4% (95% CI: 24.7-38.1). By contrast, the general practitioner patient samples (N=29) showed a prevalence of 0%, whereas 22.2% of samples from other hospitals (N=27) were positive for VRE. All isolates were Enterococcus faecium (VREfm) and were indicated to contain CC17, though with considerable heterogeneity among the isolates. CONCLUSION: This high prevalence goes some way towards providing an explanation for the current high rates of VRE bacteraemia in Ireland, as well as highlighting the benefits of screening and enhanced infection control practices by all hospitals to control the high rates of VRE observed.

Draft Genome Sequences of Six Different Staphylococcus epidermidis Clones, Isolated Individually from Preterm Neonates Presenting with Sepsis at Edinburgh's Royal Infirmary.

Herein, we report the draft genome sequences of six individual Staphylococcus epidermidis clones, cultivated from blood taken from different preterm neonatal sepsis patients at the Royal Infirmary, Edinburgh, Scotland, United Kingdom.

Draft Genome Sequence of a Pantoea sp. Isolated from a Preterm Neonatal Blood Sepsis Patient.

Herein, we report the draft genome sequence of Pantoea sp. ED-NGS-1003, cultivated from a blood sample taken from a neonatal sepsis patient at the Royal Infirmary, Edinburgh, Scotland, United Kingdom.

Draft Genome Sequence of a Staphylococcus aureus Isolate Taken from the Blood of a Preterm Neonatal Blood Sepsis Patient.

Herein, we report the draft genome sequence of Staphylococcus aureus ED-NGS-1006, cultivated from a blood sample taken from a neonatal sepsis patient at the Royal Infirmary in Edinburgh, Scotland, United Kingdom.

Draft Genome Sequence of an Enterococcus faecalis Strain Isolated from a Neonatal Blood Sepsis Patient.

Herein, we report the draft genome sequence of Enterococcus faecalis ED-NGS-1009, cultivated from a blood sample taken from a neonatal sepsis patient at the Royal Infirmary in Edinburgh, Scotland, United Kingdom.