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See detailEstimation of degree-days for different climatic zones of North-East India
Borah, Pallavi; Singh, Manoj Kumar; Mahapatra, Sadhan

in Sustainable Cities and Society (2015), 14

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See detailEstimation of direct unit costs associated with non-vertebral osteoporotic fractures in five European countries
Bouee, S.; Lafuma, A.; Fagnani, F. et al

in Rheumatology International (2006), 26(12), 1063-1072

The objective of this study was to estimate the unit costs of non-vertebral osteoporotic fractures in five European countries based on the results of the SOTI and TROPOS clinical trials in postmenopausal ... [more ▼]

The objective of this study was to estimate the unit costs of non-vertebral osteoporotic fractures in five European countries based on the results of the SOTI and TROPOS clinical trials in postmenopausal osteoporotic women. The information recorded in the Case Report Forms was used. The perspective of third party payers was adopted. Hip fracture unit cost was the highest. The ranges of costs among countries was narrow for hip from 8,346 euro (Italy) to 9,907 euro (France), but wider for other fractures: 890 euro (Spain) to 2,022 euro (Italy) for wrist, 1,167 euro (Spain) to 3,268 euro (Italy) for pelvis, 837 euro (Spain) to 2,116 euro (Italy) for sternum/clavicle, 565 euro (Spain) to 908 euro (France) for rib, 1,518 euro (Spain) to 3,651 euro (Belgium) for humerus, 1,805 euro (Spain) to 3,521 euro (Italy) for leg. The costs of those fractures should be considered when estimating the cost of osteoporosis. [less ▲]

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See detailEstimation of direct unit costs associated with non-vertebral osteoporotic fractures in six European countries
Bouée, S.; Lafuma, A.; Fagnani, F. et al

in Osteoporosis International (2005, March), 16(Suppl.3), 13

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See detailEstimation of dominance variance for growth traits with sire-dam subclass effects in a crossbred population of pigs
Dufrasne, Marie ULg; Faux, Pierre ULg; Piedboeuf, Maureen et al

Poster (2014)

Nonadditive genetic effects may be not negligible but are often ignored in genetic evaluations. The most important nonadditive effect is probably dominance. Prediction of dominance effects should allow a ... [more ▼]

Nonadditive genetic effects may be not negligible but are often ignored in genetic evaluations. The most important nonadditive effect is probably dominance. Prediction of dominance effects should allow a more precise estimation of the total genetic merit, particularly in populations that use specialized sire and dam lines, and with large number of full-sibs, like pigs. Computation of the inverted dominance relationship matrix, D-1, is difficult with large datasets. But, D-1 can be replaced by the inverted sire-dam subclass relationship matrix F-1, which represents the average dominance effect of full-sibs. The aim of this study was to estimate dominance variance for longitudinal measurements of body weight (BW) in a crossbred population of pigs The dataset consisted of 20,120 BW measurements recorded between 50 and 210 d of age on 2,341 crossbred pigs (Piétrain X Landrace). A random regression model was used to estimate variance components. Fixed effects were sex and date of recording. Random effects were additive genetic, permanent environment, parental dominance and residual. Dominance variance represented 7 to 9% of the total variance and 11 to 30% of additive variance. Those results showed that dominance variance exists for growth traits in pigs and may be relatively large. The estimation of dominance effects may be useful for mate selection program to maximize genetic merit of progeny. [less ▲]

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See detailEstimation of dominance variance for live body weight in a crossbred population of pigs
Dufrasne, Marie ULg; Faux, Pierre ULg; Piedboeuf, Maureen et al

in Journal of Animal Science (2014), 92

The objective of this study was to estimate the dominance variance for repeated live BW records in a crossbred population of pigs. Data were provided by the Walloon Pig Breeding Association and included ... [more ▼]

The objective of this study was to estimate the dominance variance for repeated live BW records in a crossbred population of pigs. Data were provided by the Walloon Pig Breeding Association and included 22,197 BW records of 2,999 crossbred Piétrain × Landrace K+ pigs from 50 to 210 d of age. The BW records were standardized and adjusted to 210 d of age for analysis. Three single-trait random regression animal models were used: Model 1 without parental subclass effect, Model 2 with parental subclasses considered unrelated, and Model 3 with the complete parental dominance relationship matrix. Each model included sex, contemporary group, and heterosis as fixed effects as well as additive genetic, permanent environment, and residual as random effects. Variance components and their SE were estimated using a Gibbs sampling algorithm. Heritability tended to increase with age: from 0.50 to 0.64 for Model 1, from 0.19 to 0.42 for Model 2, and from 0.31 to 0.53 for Model 3. Permanent environmental variance tended to decrease with age and accounted for 29 to 44% of total variance with Model 1, 29 to 37% of total variance with Model 2, and 34 to 51% of total variance with Model 3. Residual variance explained <10% of total variance for the 3 models. Dominance variance was computed as 4 times the estimated parental subclass variance. Dominance variance accounted for 22 to 40% of total variance for Model 2 and 5 to 11% of total variance for Model 3, with a decrease with age for both models. Results showed that dominance effects exist for growth traits in pigs and may be reasonably large. The use of the complete dominance relationship matrix may improve the estimation of additive genetic variances and breeding values. Moreover, a dominance effect could be especially useful in selection programs for individual matings through the use of specific combining ability to maximize growth potential of crossbred progeny. [less ▲]

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See detailEstimation of dominance variance in purebred Yorkshire swine
Culbertson, M. S.; Mabry, J. W.; Misztal, I. et al

in Journal of Animal Science (1998), 76(2), 448-451

We used 179,485 Yorkshire reproductive and 239,354 Yorkshire growth records to estimate additive and dominance variances by Method Fraktur R. Estimates were obtained for number born alive (NBA), 21-d ... [more ▼]

We used 179,485 Yorkshire reproductive and 239,354 Yorkshire growth records to estimate additive and dominance variances by Method Fraktur R. Estimates were obtained for number born alive (NBA), 21-d litter weight (LWT), days to 104.5 kg (DAYS), and backfat at 104.5 kg (BF). The single-trait models for NBA and LWT included the fixed effects of contemporary group and regression on inbreeding percentage and the random effects mate within contemporary group, animal permanent environment, animal additive, and parental dominance. The single-trait models for DAYS and BF included the fixed effects of contemporary group, sex, and regression on inbreeding percentage and the random effects litter of birth, dam permanent environment, animal additive, and parental dominance. Final estimates were obtained from six samples for each trait. Regression coefficients for 10% inbreeding were found to be -.23 for NBA, -.52 kg for LWT, 2.1 d for DAYS, and 0 mm for BF. Estimates of additive and dominance variances expressed as a percentage of phenotypic variances were, respectively, 8.8 +/- .5 and 2.2 +/- .7 for NBA, 8.1 +/- 1.1 and 6.3 +/- .9 for LWT, 33.2 +/- .4 and 10.3 +/- 1.5 for DAYS, and 43.6 +/- .9 and 4.8 +/- .7 for BF. The ratio of dominance to additive variances ranged from .78 to .11. [less ▲]

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See detailEstimation of dominance variance with sire-dam subclass effects in a crossbred population of pigs
Dufrasne, Marie ULg; Faux, Pierre ULg; Piedboeuf, Maureen et al

Poster (2013, August 26)

Nonadditive genetic effects may be not negligible but are often ignored in genetic evaluations. The most important nonadditive effect is probably dominance. Prediction of dominance effects should allow a ... [more ▼]

Nonadditive genetic effects may be not negligible but are often ignored in genetic evaluations. The most important nonadditive effect is probably dominance. Prediction of dominance effects should allow a more precise estimation of the total genetic merit, particularly in populations that use specialized sire and dam lines, and with large number of full-sibs, like pigs. Computation of the inverted dominance relationship matrix, D-1, is difficult with large datasets. But, D-1 can be replaced by the inverted sire-dam subclass relationship matrix F-1, which represents the average dominance effect of full-sibs. The aim of this study was to estimate dominance variance for longitudinal measurements of body weight (BW) in a crossbred population of pigs, assuming unrelated sire-dam subclass effects. The edited dataset consisted of 20,120 BW measurements recorded between 50 and 210 d of age on 2,341 crossbred pigs from 89 Piétrain sires and 169 Landrace dams. A random regression model was used to estimate variance components. Fixed effects were sex and date of recording. Random effects were additive genetic, permanent environment, sire-dam subclass and residual. Random effects, except residual, were modeled with linear splines. Only full-sib contributions were considered by using uncorrelated sire-dam classes. Estimated heritability of BW increased with age from 0.40 to 0.60. Inversely, estimated dominance decreased with age, from 0.28 to 0.01. Ratio of dominance relative to additive variance was high at early age (58.3% at 50 d) and decreased with age (2.6% at 200 d). Those results showed that dominance effects might be important for early growth traits in pigs. However, this need to be confirmed and dominance relationships will be included in the next steps. [less ▲]

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See detailEstimation of dominance variance with sire-dam subclass effects in a crossbred population of pigs
Dufrasne, Marie ULg; Jaspart, Véronique; Wavreille, José et al

in Book of Abstract of the 64th Annual Meeting of the European Association of Animal Science (2013)

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See detailEstimation of effective and total erythropoiesis in myelodysplasia using serum transferrin receptor and erythropoietin concentrations, with automated reticulocyte parameters.
Bowen, D. T.; Culligan, D.; Beguin, Yves ULg et al

in Leukemia : Official Journal of the Leukemia Society of America, Leukemia Research Fund, U.K (1994), 8(1), 151-5

The erythroid abnormality in patients with myelodysplasia (MDS) is multifactorial, with ineffective erythropoiesis and poor in vitro progenitor response to erythropoietin (EPO). Serum EPO concentration is ... [more ▼]

The erythroid abnormality in patients with myelodysplasia (MDS) is multifactorial, with ineffective erythropoiesis and poor in vitro progenitor response to erythropoietin (EPO). Serum EPO concentration is variable among patients for a given haemoglobin concentration. We studied 19 non-transfusion-dependent patients with MDS, and 13 healthy elderly control subjects in an attempt to define the factors governing variability in serum EPO and to further characterise the anaemia of MDS. Serum EPO concentration was appropriate for the degree of anaemia in 15/19 MDS patients, and was positively related to mean cell volume (MCV), mean cell haemoglobin (MCH), and percentage highly fluorescent reticulocytes (% HFR), but not to absolute or percentage reticulocyte count. Although the observed/predicted ratio for serum transferrin receptor (TfR) concentration was low in 12 of 19 MDS subjects, no relationship to haemoglobin concentration, reticulocytes or serum EPO was seen. Serum TfR was positively correlated with WBC and platelet counts. Serum TfR was higher in patients with sideroblastic anaemia than refractory anaemia. Standardized in vivo p50 was positively correlated to red cell 2,3 diphosphoglycerate concentration, although this was not the only factor influencing the oxygen dissociation curve. We conclude that effective erythroid output responsive to endogenous EPO drive in MDS is positively related to MCV, MCH and % HFR. Serum TfR may not represent effective output as precisely as % HFR, but may be proportional to total marrow erythropoietic activity. [less ▲]

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See detailEstimation of fatty acid profile in cow milk by mid-infrared spectrometry
Soyeurt, Hélène ULg; Dardenne, Pierre; Lognay, Georges ULg et al

in European seminar on infrared spectroscopy (2006)

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See detailEstimation of fatty acid profile in cow milk by mid-infrared spectrometry
Soyeurt, Hélène ULg; Dardenne, Pierre; Lognay, Georges ULg et al

Poster (2006, April 03)

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See detailEstimation of fructose, glucose and sucrose released by inulin hydrolysis during food processing.
Chevalier, Jean-Paul; Paquot, Michel; Fougnies, C. et al

Poster (2003, May)

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See detailEstimation of furan contamination across the Belgian food chain.
Scholl, Georges ULg; Scippo, Marie-Louise ULg; De Pauw, Edwin ULg et al

in Food Additives & Contaminants. Part A. Chemistry, Analysis, Control, Exposure & Risk Assessment (2012), 29(2), 172-9

This paper provides an estimate of the furan content of Belgian foods. The objective of the study was to achieve the best food chain coverage with a restricted number of samples (n = 496). The geographic ... [more ▼]

This paper provides an estimate of the furan content of Belgian foods. The objective of the study was to achieve the best food chain coverage with a restricted number of samples (n = 496). The geographic distribution, different market chains and labels, and consumption frequencies were taken into account in the construction of the sampling plan. Weighting factors such as contamination levels, consumption frequency and the diversity of food items were applied to set up the model. The very low detection capabilities (CC(beta)) of the analytical methods used (sub-ppb) allowed reporting of 78.2% of the overall dataset above CC(beta) and, in particular, 96.7% for the baby food category. The highest furan levels were found in powdered roasted bean coffee (1912 microg kg(-1)) with a mean of 756 microg kg(-1) for this category. Prepared meat, pasta and rice, breakfast cereals, soups, and baby food also showed high mean furan contents ranging from 16 to 43 microg kg(-1). Comparisons with contamination surveys carried out in other countries pointed out differences for the same food group and therefore contamination levels are related to the geographical origin of food items. [less ▲]

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See detailEstimation of genetic and crossbreeding parameters for daily milk yield of Ayrshire × Sahiwal × Ankole crossbred cows in Burundi
Hatungumukama, G.; Detilleux, Johann ULg

in Livestock Science (2008)

The pedigree of 317 cows of which 184 were controlled for milk production has been used to estimate crossbreeding parameters for daily milk yield of Ayrshire, Sahiwal and Ankole crosses in the Mahwa ... [more ▼]

The pedigree of 317 cows of which 184 were controlled for milk production has been used to estimate crossbreeding parameters for daily milk yield of Ayrshire, Sahiwal and Ankole crosses in the Mahwa station. Lactating cows belonged to one of 6 different genetic groups defined on the basis of the mating system used to produce them. REML estimates of the genetic parameters were obtained with a repeated animal model using daily milk records. Estimated heritability (h2) and repeatability (r2) were 0.27 and 0.36, respectively. The genetic group effects were used to estimate crossbreeding parameters following Dickerson's genetic model. Estimates for the additive effects for daily milk yield of Ankole, Sahiwal and Ayrshire breeds were − 1.66l, − 0.48l and 5.22l, respectively. Estimates of direct heterosis for daily milk yield for Sahiwal × Ankole, Ayrshire × Ankole, and Ayrshire × Sahiwal crosses were 1.97l, 2.30l and − 2.33l, respectively. [less ▲]

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See detailEstimation of genetic correlations among countries in international dairy sire evaluations with structural models.
Leclerc, H.; Minery, S.; Delaunay, I. et al

in Journal of Dairy Science (2006), 89(5), 1792-803

The increase in the number of participating countries and the lack of genetic ties between some countries has lead to statistical and computational difficulties in estimating the genetic (co)variance ... [more ▼]

The increase in the number of participating countries and the lack of genetic ties between some countries has lead to statistical and computational difficulties in estimating the genetic (co)variance matrix needed for international sire evaluation of milk yield and other traits. Structural models have been proposed to reduce the number of parameters to estimate by exploiting patterns in the genetic correlation matrix. Genetic correlations between countries are described as a simple function of unspecified country characteristics that can be mapped in a space of limited dimensions. Two link functions equal to the exponential of minus the Euclidian distance between the coordinates of two countries and the exponential of minus the square of this Euclidian distance were used for the study on international simulated and field data. On simulated data, it was shown that structural models might allow an easier estimation of genetic correlations close to the border of the parameter space. This is not always possible with an unstructured model. On milk yield data, genetic correlations obtained from 22 countries for structural models based on 2 and 7 dimensions, respectively, were analyzed. Only a structural model with a large number of axes gave reasonable estimates of genetic correlations compared with correlations obtained for an unstructured model: 76.7% of correlations deviated by less than 0.030. Such a model reduces the number of parameters from 231 genetic correlations to 126 coordinates. On foot angle data, large deviations were observed between genetic correlations estimated with an unstructured model and correlations estimated with a structural model, regardless of the number of axes taken into account. [less ▲]

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See detailEstimation of genetic covariances with Method R
Druet, Tom ULg; Misztal, I.; Duangjinda, M. et al

in Journal of Animal Science (2001), 79(3), 605-615

Method R is a simple and computationally inexpensive method for estimating (co)variances. The objective of the study was to investigate properties of Method R for estimation of (co)variance components ... [more ▼]

Method R is a simple and computationally inexpensive method for estimating (co)variances. The objective of the study was to investigate properties of Method R for estimation of (co)variance components with emphasis on covariance estimation. Theoretical Method R formulas were developed for simplified single-variate and bivariate models. In single-trait models, the curve of the regression of Method R was continuous and monotonic and its slope depended on the amount of information on each animal and on the variance ratio. The curve became steeper as the number of records per animal decreased. For covariance, the curve of the regression was monotonic but not continuous. However, a regression coefficient of 1 still corresponded to the correct covariance. Similar curves were observed in analyses of simulated data sets. Because of the observed discontinuity, algorithms implementing Method R that require a continuous regression curve would not work in models with: covariances. An alternative algorithm was based on a transformation matrix obtained by multiplying a matrix of numerators with the inverse of a matrix of denominators of the regression factors. Such an algorithm converged reliably for all models tested. Method R can be modified to estimate covariances in models too large for other methods. [less ▲]

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See detailEstimation of genetic parameters and genome scan for 15 semen characteristics traits of Holstein bulls.
Druet, Tom ULg; Fritz, S.; Sellem, E. et al

in Journal of Animal Breeding & Genetics (2009), 126(4), 269-77

A QTL detection experiment was performed in French dairy cattle to search for QTL related to male fertility. Ten families, involving a total of 515 bulls, were phenotyped for ejaculated volume and sperm ... [more ▼]

A QTL detection experiment was performed in French dairy cattle to search for QTL related to male fertility. Ten families, involving a total of 515 bulls, were phenotyped for ejaculated volume and sperm concentration, number of spermatozoa, motility, velocity, percentage of motile spermatozoa after thawing and abnormal spermatozoa. A set of 148 microsatellite markers were used to realize a genome scan. First, genetic parameters were estimated for all traits. Semen production traits were found to have moderate heritabilities (from 0.15 to 0.30) while some of the semen quality traits such as motility had high heritabilities (close to 0.60). Genetic correlations among traits showed negative relationships between volume and concentration and between volume and most quality traits such as motility or abnormal sperm while correlations between concentration and these traits were rather favourable. Percentages of abnormal sperm were negatively related to quality traits, especially with motility and velocity of spermatozoa. Three QTL related to abnormal sperm frequencies were significant at p < 0.01. In total, 11 QTL (p < 0.05) were detected. However, the number of QTL detected was within the range of expected false positives. Because of the lack of power to find QTL in this design further analyses are required to confirm these QTL. [less ▲]

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