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Both blood- and milk-based biomarkers have been analysed for decades in research settings, although often only in one herd, and without focus on the variation in the biomarkers that are specifically related to herd or diet. Biomarkers can be used to detect physiological imbalance and disease risk and may have a role in precision livestock farming (PLF). For use in PLF, it is important to quantify normal variation in specific biomarkers and the source of this variation. The objective of this study was to estimate the between- and within-herd variation in a number of blood metabolites (β-hydroxybutyrate (BHB), non-esterified fatty acids, glucose and serum IGF-1), milk metabolites (free glucose, glucose-6-phosphate, urea, isocitrate, BHB and uric acid), milk enzymes (lactate dehydrogenase and N-acetyl-β-D-glucosaminidase (NAGase)) and composite indicators for metabolic imbalances (Physiological Imbalance-index and energy balance), to help facilitate their adoption within PLF. Blood and milk were sampled from 234 Holstein dairy cows from 6 experimental herds, each in a different European country, and offered a total of 10 different diets. Blood was sampled on 2 occasions at approximately 14 days-in-milk (DIM) and 35 DIM. Milk samples were collected twice weekly (in total 2750 samples) from DIM 1 to 50. Multilevel random regression models were used to estimate the variance components and to calculate the intraclass correlations (ICCs). The ICCs for the milk metabolites, when adjusted for parity and DIM at sampling, demonstrated that between 12% (glucose-6-phosphate) and 46% (urea) of the variation in the metabolites’ levels could be associated with the herd-diet combination. Intraclass Correlations related to the herd-diet combination were generally higher for blood metabolites, from 17% (cholesterol) to approximately 46% (BHB and urea). The high ICCs for urea suggest that this biomarker can be used for monitoring on herd level. The low variance within cow for NAGase indicates that few samples would be needed to describe the status and potentially a general reference value could be used. The low ICC for most of the biomarkers and larger within cow variation emphasises that multiple samples would be needed - most likely on the individual cows - for making the biomarkers useful for monitoring. The majority of biomarkers were influenced by parity and DIM which indicate that these should be accounted for if the biomarker should be used for monitoring.
Unmanned aerial vehicles (UAVs) are useful tools in ornithological studies. Importantly, though, UAV-caused disturbance has been noted to vary among species. This study evaluated guidelines for UAVs as a tool for researching geese. Twenty-four flocks of foraging geese were approached at an altitude of 50–100 m with a quadcopter UAV and disturbance effects were analysed across different horizontal distances between the UAV and the flocks. Geese were increasingly disturbed when approached by a UAV, with birds showing increased vigilance behaviour within approximately 300 m. Increasing UAV flight altitude as well as increasing take-off distance from the flocks both decreased the risk of bird flocks flushing. In conclusion, when monitoring geese using UAVs, flight altitudes of 100 m and take-off distances of ideally ∼500 m are recommended, to minimise initial disturbance and reducing the risk of birds flushing.
The COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) project is a large international collaborative effort to analyze individual-level phenotype data from twins in multiple cohorts from different environments. The main objective is to study factors that modify genetic and environmental variation of height, body mass index (BMI, kg/m2) and size at birth, and additionally to address other research questions such as long-term consequences of birth size. The project started in 2013 and is open to all twin projects in the world having height and weight measures on twins with information on zygosity. Thus far, 54 twin projects from 24 countries have provided individual-level data. The CODATwins database includes 489,981 twin individuals (228,635 complete twin pairs). Since many twin cohorts have collected longitudinal data, there is a total of 1,049,785 height and weight observations. For many cohorts, we also have information on birth weight and length, own smoking behavior and own or parental education. We found that the heritability estimates of height and BMI systematically changed from infancy to old age. Remarkably, only minor differences in the heritability estimates were found across cultural–geographic regions, measurement time and birth cohort for height and BMI. In addition to genetic epidemiological studies, we looked at associations of height and BMI with education, birth weight and smoking status. Within-family analyses examined differences within same-sex and opposite-sex dizygotic twins in birth size and later development. The CODATwins project demonstrates the feasibility and value of international collaboration to address gene-by-exposure interactions that require large sample sizes and address the effects of different exposures across time, geographical regions and socioeconomic status.
Unbalanced metabolic status in the weeks after calving predisposes dairy cows to metabolic and infectious diseases. Blood glucose, IGF-I, non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) are used as indicators of the metabolic status of cows. This work aims to (1) evaluate the potential of milk mid-IR spectra to predict these blood components individually and (2) to evaluate the possibility of predicting the metabolic status of cows based on the clustering of these blood components. Blood samples were collected from 241 Holstein cows on six experimental farms, at days 14 and 35 after calving. Blood samples were analyzed by reference analysis and metabolic status was defined by k-means clustering (k=3) based on the four blood components. Milk mid-IR analyses were undertaken on different instruments and the spectra were harmonized into a common standardized format. Quantitative models predicting blood components were developed using partial least squares regression and discriminant models aiming to differentiate the metabolic status were developed with partial least squares discriminant analysis. Cross-validations were performed for both quantitative and discriminant models using four subsets randomly constituted. Blood glucose, IGF-I, NEFA and BHB were predicted with respective R2 of calibration of 0.55, 0.69, 0.49 and 0.77, and R2 of cross-validation of 0.44, 0.61, 0.39 and 0.70. Although these models were not able to provide precise quantitative values, they allow for screening of individual milk samples for high or low values. The clustering methodology led to the sharing out of the data set into three groups of cows representing healthy, moderately impacted and imbalanced metabolic status. The discriminant models allow to fairly classify the three groups, with a global percentage of correct classification up to 74%. When discriminating the cows with imbalanced metabolic status from cows with healthy and moderately impacted metabolic status, the models were able to distinguish imbalanced group with a global percentage of correct classification up to 92%. The performances were satisfactory considering the variables are not present in milk, and consequently predicted indirectly. This work showed the potential of milk mid-IR analysis to provide new metabolic status indicators based on individual blood components or a combination of these variables into a global status. Models have been developed within a standardized spectral format, and although robustness should preferably be improved with additional data integrating different geographic regions, diets and breeds, they constitute rapid, cost-effective and large-scale tools for management and breeding of dairy cows.
The initial period of lactation in domestic ruminants is usually characterised by both hyperphagia and negative energy balance (Barber et al, 1997). The factors regulating the hyperphagia of lactation are not well understood. Leptin is a peptide hormone which is secreted by adipocytes, and which acts on a number of neuropeptides and receptors in the hypothalamus to regulate appetite and energy balance (Spiegelman and Flier, 2001). The aim of this study was to investigate the role of leptin in the hyperphagia of lactation in sheep.
Genetic selection has greatly improved individual cow productivity. A high genetic merit Holstein Friesian cow will produce 10,000 of litres of milk in a 305 day lactation, those of lower genetic merit half this amount. Despite major research effort in generating these differences, quantitative biological description of what has been achieved is lacking. The aim of this study was to compare biological variables of relevance to milk synthesis in well defined high genetic merit and lower genetic merit dairy cows.
12 cows of high genetic merit (HGM: top 5% of UK national herd) and 12 of lower genetic merit (LGM: close to UK average) were purchased from the Blythbank and Langhill herds; the ontogeny of these selection lines has been described elsewhere (Woolliams et al, 1993). Mean parity was 3.7±0.3 and was balanced between HGM and LGM. Management of the two groups was identical. Measurements were made over a period of two weeks close to peak lactation. Milk yield was recorded at each milking. Plasma samples were collected and analysed for a variety of hormones by radioimmunoassay and metabolites by established spectrophotometric assays. Udder size was determined by a casting technique (Dewhurst et al., 1993) and mammary biopsies for key enzyme activities were obtained as described by Knight et. al. (1992). Differences between lines were analysed by analysis of variance (ANOVA).
We present an indentation-scope that interfaces with confocal microscopy, enabling direct observation of the three-dimensional (3D) microstructural response of coatings on substrates. Using this method, we compared microns-thick polymer coatings on glass with and without silica nanoparticle filler. Bulk force data confirmed the >30% modulus difference, while microstructural data further revealed slip at the glass-coating interface. Filled coatings slipped more and about two times faster, as reflected in 3D displacement and von Mises strain fields. Overall, these data indicate that silica-doping of coatings can dramatically alter adhesion. Moreover, this method compliments existing theoretical and modeling approaches for studying indentation in layered systems.
Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990–1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected.
Piglet mortality is a major problem in organic pig production affecting both farm economy and animal welfare. Knowledge is scarce on the risk factors of piglet mortality in Danish commercial organic pig production. The objectives of this study were to evaluate season, litter size, parity, sow body condition and stillborn littermates as risk factors for early piglet mortality and crushing of liveborn piglets from parturition until castration at day 3 to 5 postpartum (pp). The study was conducted over a 1-year period in nine commercial Danish organic pig herds practicing outdoor farrowing all year round. Data included recordings on 3393 farrowings with 50 284 liveborn piglets of which 14.8% died before castration. A subset of the dead piglets were collected and necropsied to identify crushed piglets. The average number of liveborn piglets per litter was 14.8 (SD=3.7) and the average time from parturition until castration was 4.1 (SD=1.7) days. A negative binomial regression analysis was used to model the effect of the predictive variables on the early piglet mortality accounting for different time periods from parturition to castration. An increase in maternal body condition score (BCS) and parity significantly increased the risk of dying between parturition and castration. Early mortality was found to be lowest during spring (March to May) and highest during summer (June to August). Being born into a litter with one or more stillborn littermates increased the risk of early mortality. The risk factors for crushing of piglets were evaluated using a logistic analysis. A significant effect of parity and litter size was found where the odds of at least one piglet in a litter with mortality was diagnosed as crushed increased with increasing parity and litter size. In conclusion, being born during summer (June to August), high parity and maternal BCS and stillborn littermates were found to be risk factors for piglet mortality between parturition and castration. In addition, parity and increasing litter size were found to be risk factors for crushing of piglets in litters with mortality.
In Danish organic pig production, one-third of total born piglets die before weaning, and stillbirth has previously crudely been estimated to account for 27% of the total preweaning mortality. The objective of this study was to evaluate season, litter size, parity and body condition of the sow as risk factors for stillbirth in nine commercial Danish organic pig herds. The study was conducted over a 1-year period, and the data included registrations on 5170 farrowings with 82 906 total born piglets. The average number of total born piglets per litter was 16.0, and the number of stillborn piglets per litter was 1.1. A significant effect of season was seen with an odds ratio for stillbirth of 1.15 during summer (May to August) compared with the remaining part of the year. A non-linear effect of litter size was seen where an increase in litter size from 11 to 16 resulted in an odds ratio of stillbirth of 1.11. An increase in litter size from 16 to 21 resulted in an odds ratio of stillbirth of 1.45. A significant interaction between body condition and parity was present. In first parity sows, an increase in body condition score from 2 (thin) to 3 (moderate) and from 3 to 4 (fat) increased the probability of stillbirth with an odds ratio of 1.23 and 1.36, respectively. In sows with parity above 4, an increase in body condition score from 2 to 3 and from 3 to 4 decreases the probability of stillbirth with an odds ratio of 0.68 and 0.79, respectively. In conclusion, increasing litter size and being born during the summer months of May to August were found to be risk factors for stillbirth. Furthermore, an interaction between body condition and parity showed that thin sows with parity above 4 had a substantially increased risk of stillbirth compared with normal and fat sows with parity above 4. In contrast, for parity 1 sows risk of stillbirth was increased in fat sows.
We tested the hypothesis that mating strategies with genomic information realise lower rates of inbreeding (∆F) than with pedigree information without compromising rates of genetic gain (∆G). We used stochastic simulation to compare ∆F and ∆G realised by two mating strategies with pedigree and genomic information in five breeding schemes. The two mating strategies were minimum-coancestry mating (MC) and minimising the covariance between ancestral genetic contributions (MCAC). We also simulated random mating (RAND) as a reference point. Generations were discrete. Animals were truncation-selected for a single trait that was controlled by 2000 quantitative trait loci, and the trait was observed for all selection candidates before selection. The criterion for selection was genomic-breeding values predicted by a ridge-regression model. Our results showed that MC and MCAC with genomic information realised 6% to 22% less ∆F than MC and MCAC with pedigree information without compromising ∆G across breeding schemes. MC and MCAC realised similar ∆F and ∆G. In turn, MC and MCAC with genomic information realised 28% to 44% less ∆F and up to 14% higher ∆G than RAND. These results indicated that MC and MCAC with genomic information are more effective than with pedigree information in controlling rates of inbreeding. This implies that genomic information should be applied to more than just prediction of breeding values in breeding schemes with truncation selection.
The aim was to explore the extent to which a Danish prevention centre catered to marginalised groups within the catchment area. We determined whether the district’s socio-economic vulnerability status and distance from the citizens’ residential sector to the centre influenced referrals of citizens to the centre, their attendance at initial appointment, and completion of planned activities at the centre.
Disparities in access to health care services is one among many aspects of inequality in health. There are multiple determinants within populations (socio-economic status, ethnicity, and education) as well as the health care systems (resource availability and cultural acceptability).
A total of 347 participants referred to the centre during a 10-month period were included. For each of 44 districts within the catchment area, the degree of socio-economic vulnerability was estimated based on the citizens’ educational level, ethnicity, income, and unemployment rate. A socio-economic vulnerability score (SE-score) was calculated. Logistic regression was used to calculate the probability that a person was referred to the centre, attended the initial appointment, and completed the planned activities, depending on sex, age, SE-score of district of residence, and distance to the centre.
Citizens from locations with a high socio-economic vulnerability had increased probability of being referred by general practitioners, hospitals, and job centres. Citizens living further away from the prevention centre had a reduced probability of being referred by their general practitioners. After referral, there was no difference in probability of attendance or completion as a function of SE-score or distance between the citizens’ district and the centre. In conclusion, the centre is capable of attracting referrals from districts where the need is likely to be relatively high in terms of socio-economic vulnerability, whereas distance reduced the probability of referral. No differences were found in attendance or completion.
We analyzed birth order differences in means and variances of height and body mass index (BMI) in monozygotic (MZ) and dizygotic (DZ) twins from infancy to old age. The data were derived from the international CODATwins database. The total number of height and BMI measures from 0.5 to 79.5 years of age was 397,466. As expected, first-born twins had greater birth weight than second-born twins. With respect to height, first-born twins were slightly taller than second-born twins in childhood. After adjusting the results for birth weight, the birth order differences decreased and were no longer statistically significant. First-born twins had greater BMI than the second-born twins over childhood and adolescence. After adjusting the results for birth weight, birth order was still associated with BMI until 12 years of age. No interaction effect between birth order and zygosity was found. Only limited evidence was found that birth order influenced variances of height or BMI. The results were similar among boys and girls and also in MZ and DZ twins. Overall, the differences in height and BMI between first- and second-born twins were modest even in early childhood, while adjustment for birth weight reduced the birth order differences but did not remove them for BMI.
Virtual reality surgical simulation of mastoidectomy is a promising training tool for novices. Final-product analysis for assessing novice mastoidectomy performance could be limited by a peak or ceiling effect. These may be countered by simulator-integrated tutoring.
Twenty-two participants completed a single session of self-directed practice of the mastoidectomy procedure in a virtual reality simulator. Participants were randomised for additional simulator-integrated tutoring. Performances were assessed at 10-minute intervals using final-product analysis.
In all, 45.5 per cent of participants peaked before the 60-minute time limit. None of the participants achieved the maximum score, suggesting a ceiling effect. The tutored group performed better than the non-tutored group but tutoring did not eliminate the peak or ceiling effects.
Timing and adequate instruction is important when using final-product analysis to assess novice mastoidectomy performance. Improved real-time feedback and tutoring could address the limitations of final product based assessment.
The gastrointestinal tract (GIT) microbiota has been identified as an important reservoir of antibiotic resistance genes (ARGs) that can be horizontally transferred to pathogenic species. Maternal GIT microbes can be transmitted to the offspring, and recent work indicates that such transfer starts before birth. We have used culture-independent genetic screenings to explore whether ARGs are already present in the meconium accumulated in the GIT during fetal life and in feces of 1-week-old infants. We have analyzed resistance to β-lactam antibiotics (BLr) and tetracycline (Tcr), screening for a variety of genes conferring each. To evaluate whether ARGs could have been inherited by maternal transmission, we have screened perinatal fecal samples of the 1-week-old babies’ mothers, as well as a mother–infant series including meconium, fecal samples collected through the infant’s 1st year, maternal fecal samples and colostrum. Our results reveal a high prevalence of BLr and Tcr in both meconium and early fecal samples, implying that the GIT resistance reservoir starts to accumulate even before birth. We show that ARGs present in the mother may reach the meconium and colostrum and establish in the infant GIT, but also that some ARGs were likely acquired from other sources. Alarmingly, we identified in both meconium and 1-week-olds’ samples a particularly elevated prevalence of mecA (>45%), six-fold higher than that detected in the mothers. The mecA gene confers BLr to methicillin-resistant Staphylococcus aureus, and although its detection does not imply the presence of this pathogen, it does implicate the young infant’s GIT as a noteworthy reservoir of this gene.
A trend toward greater body size in dizygotic (DZ) than in monozygotic (MZ) twins has been suggested by some but not all studies, and this difference may also vary by age. We analyzed zygosity differences in mean values and variances of height and body mass index (BMI) among male and female twins from infancy to old age. Data were derived from an international database of 54 twin cohorts participating in the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins), and included 842,951 height and BMI measurements from twins aged 1 to 102 years. The results showed that DZ twins were consistently taller than MZ twins, with differences of up to 2.0 cm in childhood and adolescence and up to 0.9 cm in adulthood. Similarly, a greater mean BMI of up to 0.3 kg/m2 in childhood and adolescence and up to 0.2 kg/m2 in adulthood was observed in DZ twins, although the pattern was less consistent. DZ twins presented up to 1.7% greater height and 1.9% greater BMI than MZ twins; these percentage differences were largest in middle and late childhood and decreased with age in both sexes. The variance of height was similar in MZ and DZ twins at most ages. In contrast, the variance of BMI was significantly higher in DZ than in MZ twins, particularly in childhood. In conclusion, DZ twins were generally taller and had greater BMI than MZ twins, but the differences decreased with age in both sexes.
For over 100 years, the genetics of human anthropometric traits has attracted scientific interest. In particular, height and body mass index (BMI, calculated as kg/m2) have been under intensive genetic research. However, it is still largely unknown whether and how heritability estimates vary between human populations. Opportunities to address this question have increased recently because of the establishment of many new twin cohorts and the increasing accumulation of data in established twin cohorts. We started a new research project to analyze systematically (1) the variation of heritability estimates of height, BMI and their trajectories over the life course between birth cohorts, ethnicities and countries, and (2) to study the effects of birth-related factors, education and smoking on these anthropometric traits and whether these effects vary between twin cohorts. We identified 67 twin projects, including both monozygotic (MZ) and dizygotic (DZ) twins, using various sources. We asked for individual level data on height and weight including repeated measurements, birth related traits, background variables, education and smoking. By the end of 2014, 48 projects participated. Together, we have 893,458 height and weight measures (52% females) from 434,723 twin individuals, including 201,192 complete twin pairs (40% monozygotic, 40% same-sex dizygotic and 20% opposite-sex dizygotic) representing 22 countries. This project demonstrates that large-scale international twin studies are feasible and can promote the use of existing data for novel research purposes.
Gut microbiota (GM) has previously been associated with alterations in rodent behaviour, and since the GM is affected by the diet, the composition of the diet may be an important factor contributing to behavioural changes. Interestingly, a magnesium restricted diet has been shown to induce anxiety and depressive-like behaviour in humans and rodents, and it could be suggested that magnesium deficiency may mediate the effects through an altered GM.
The present study therefore fed C57BL/6 mice with a standard diet or a magnesium deficient diet (MgD) for 6 weeks, followed by behavioural testing in the forced swim test (FST) to evaluate depressive-like behaviour. An intraperitoneal glucose tolerance test (GTT) was performed 2 day after the FST to assess metabolic alterations. Neuroinflammatory markers were analysed from hippocampus. GM composition was analysed and correlated to the behaviour and hippocampal markers.
It was found that mice exposed to MgD for 6 weeks were more immobile than control mice in the FST, suggesting an increased depressive-like behaviour. No significant difference was detected in the GTT. GM composition correlated positively with the behaviour of undisturbed C57BL/6 mice, feeding MgD diet altered the microbial composition. The altered GM correlated positively to the hippocampal interleukin-6.
In conclusion, we hypothesise that imbalances of the microbiota–gut–brain axis induced by consuming a MgD diet, contributes to the development of depressive-like behaviour.
This paper aims to contribute to the development of a cost-effective alternative to expensive on-farm animal-based welfare assessment systems. The objective of the study was to design an animal welfare index based on central database information (DBWI), and to validate it against an animal welfare index based on-farm animal-based measurements (AWI). Data on 63 Danish sow herds with herd-sizes of 80 to 2500 sows and an average herd size of 501 were collected from three central databases containing: Meat inspection data collected at animal level in the abattoir, mortality data at herd level from the rendering plants of DAKA, and medicine records at both herd and animal group level (sow with piglets, weaners or finishers) from the central database Vetstat. Selected measurements taken from these central databases were used to construct the DBWI. The relative welfare impacts of both individual database measurements and the databases overall were assigned in consultation with a panel consisting of 12 experts. The experts were drawn from production advisory activities, animal science and in one case an animal welfare organization. The expert panel weighted each measurement on a scale from 1 (not-important) to 5 (very important). The experts also gave opinions on the relative weightings of measurements for each of the three databases by stating a relative weight of each database in the DBWI. On the basis of this, the aggregated DBWI was normalized. The aggregation of AWI was based on weighted summary of herd prevalence’s of 20 clinical and behavioural measurements originating from a 1 day data collection. AWI did not show linear dependency of DBWI. This suggests that DBWI is not suited to replace an animal welfare index using on-farm animal-based measurements.