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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 R 2 of calibration of 0.55, 0.69, 0.49 and 0.77, and R 2 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. [ABSTRACT FROM AUTHOR]

The transport of lipids across mammary gland epithelial cells (MEC) determines milk lipid content and composition. We investigated the expression of lipid transporters and their regulators in comparison to blood metabolites during lactation and dry period (DP) in dairy cows. Repeated mammary gland biopsies and blood samples were taken from 10 animals at 7 stages of the pregnancy-lactation cycle. Expression levels of the specific mRNAs were determined by quantitative reverse transcription-PCR, whereas ABCA1 was localized by immunohistochemistry. Blood serum metabolites were determined by common enzymatic chemistries. Elevated mRNA profiles of ABCA1 and ABCA7 were found during DP as compared with lactation and were inversely associated with blood cholesterol levels. Elevated levels of ABCG2, NPC1, SREBP1, SREBP2, LXRα, and PPARγ were found postpartum, whereas ABCG1 did not differ between the functional stages of the mammary gland. The ABCA1 protein was localized in MEC and showed differential activity between DP and lactation suggesting a role of ABCA1 in the removal of excess cellular cholesterol from MEC during the DP. The expression profiles of ABCA7 and NPC1 may reflect a role of these transporters in the clearance of apoptotic cells and the intracellular redistribution of cholesterol, respectively. Regulation of lipid transporters in the mammary gland is partially associated with transcription factors that control lipid homeostasis. [ABSTRACT FROM AUTHOR]

Milk yield of the dairy cow follows a pattern termed the lactation curve. We have investigated the cellular background for this pattern. Seven mammary biopsies were obtained from each of 10 cows: at the end of lactation (d 347, equal to d 77 before next parturition); during the dry period at d 48 (4 d after dry off); 16 d before parturition; and during lactation at d 14, 42, 88, and 172. The fraction of proliferating (staining positive for Ki-67) alveolar cells was higher during the dry period (8.6%) than during lactation (0.5%). The fraction of apoptotic (staining positive by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling) alveolar cells was higher immediately after dry off (0.37%) and in early lactation (0.76%) than during other periods (0.15%). The enzyme activities of fatty acid synthetase, acetyl CoA-carboxylase, and galactosyl transferase were approximately 12-, 11-, and 4-fold higher, respectively, during lactation than during the dry period. In conclusion, mammary cell proliferation is substantial in a period near parturition but otherwise low, and apoptosis is elevated at dry off and in early lactation. The increase in apoptosis in early lactation may be due to discarding nonfunctional or senescent cells or to removal of a surplus of newly synthesized cells. The activity of selected enzymes central for milk synthesis is probably not limiting for milk production. [ABSTRACT FROM AUTHOR]

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.

Improving nitrogen use efficiency (NUE) at both the individual cow and the herd level has become a key target in dairy production systems, for both environmental and economic reasons. Cost-effective and large-scale phenotyping methods are required to improve NUE through genetic selection and by feeding and management strategies. The aim of this study was to evaluate the possibility of using mid-infrared (MIR) spectra of milk to predict individual dairy cow NUE during early lactation. Data were collected from 129 Holstein cows, from calving until 50 d in milk, in 3 research herds (Denmark, Ireland, and the UK). In 2 of the herds, diets were designed to challenge cows metabolically, whereas a diet reflecting local management practices was offered in the third herd. Nitrogen intake (kg/d) and nitrogen excreted in milk (kg/d) were calculated daily. Nitrogen use efficiency was calculated as the ratio between nitrogen in milk and nitrogen intake, and expressed as a percentage. Individual daily values for NUE ranged from 9.7 to 81.7%, with an average of 36.9% and standard deviation of 10.4%. Milk MIR spectra were recorded twice weekly and were standardized into a common format to avoid bias between apparatus or sampling periods. Regression models predicting NUE using milk MIR spectra were developed on 1,034 observations using partial least squares or support vector machines regression methods. The models were then evaluated through (1) a cross-validation using 10 subsets, (2) a cow validation excluding 25% of the cows to be used as a validation set, and (3) a diet validation excluding each of the diets one by one to be used as validation sets. The best statistical performances were obtained when using the support vector machines method. Inclusion of milk yield and lactation number as predictors, in combination with the spectra, also improved the calibration. In cross-validation, the best model predicted NUE with a coefficient of determination of cross-validation of 0.74 and a relative error of 14%, which is suitable to discriminate between low- and high-NUE cows. When performing the cow validation, the relative error remained at 14%, and during the diet validation the relative error ranged from 12 to 34%. In the diet validation, the models showed a lack of robustness, demonstrating difficulties in predicting NUE for diets and for samples that were not represented in the calibration data set. Hence, a need exists to integrate more data in the models to cover a maximum of variability regarding breeds, diets, lactation stages, management practices, seasons, MIR instruments, and geographic regions. Although the model needs to be validated and improved for use in routine conditions, these preliminary results showed that it was possible to obtain information on NUE through milk MIR spectra. This could potentially allow large-scale predictions to aid both further genetic and genomic studies, and the development of farm management tools., (The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

The ATP-binding cassette (ABC) transporters ABCA1 and ABCG1 play an important role in cellular cholesterol homeostasis, but their function in mammary gland (MG) tissue remains elusive. A bovine MG model that allows repeated MG sampling in identical animals at different functional stages was used to test whether 1) ABCA1 and ABCG1 protein expression and subcellular localization in mammary epithelial cells (MEC) change during the pregnancy-lactation cycle, and 2) these 2 proteins were present in milk fat globules (MFG). Expression and localization in MEC were investigated in bovine MG tissues at the end of lactation, during the dry period (DP), and early lactation using immunohistochemical and immunofluorescence approaches. The presence of ABCA1 and ABCG1 in MFG isolated from fresh milk was determined by immunofluorescence. The ABCA1 protein expression in MEC, expressed as arbitrary units, was higher during the end of lactation (12.2±0.24) and the DP (12.5±0.22) as compared with during early lactation (10.2±0.65). In contrast, no significant change in ABCG1 expression existed between the stages. Throughout the cycle, ABCA1 and ABCG1 were detected in the apical (41.9±24.8 and 49.0±4.96% of cows, respectively), basal (56.2±28.1 and 54.6±7.78% of cows, respectively), or entire cytoplasm (56.8±13.4 and 61.6±14.4% of cows, respectively) of MEC, or showed combined localization. Unlike ABCG1, ABCA1 was absent at the apical aspect of MEC during early lactation. Immunolabeling experiments revealed the presence of ABCA1 and ABCG1 in MFG membranes. Findings suggest a differential, functional stage-dependent role of ABCA1 and ABCG1 in cholesterol homeostasis of the MG epithelium. The presence of ABCA1 and ABCG1 in MFG membranes suggests that these proteins are involved in cholesterol exchange between MEC and alveolar milk., (Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Forty-eight heifers (3 mo old) were subjected for 35 wk to twice daily s.c. injections of saline or human somatotropin-releasing factor (5 microgram.kg-1 BW) and photoperiod of 8 h (short day) or 16 h (long day) of light daily according to a 2 X 2 factorial design. There was no treatment effect on slaughter weight, withers height, and carcass length. Somatotropin-releasing factor increased thymus weight, metacarpal length, and protein content of the carcass but decreased carcass fat content. Long day photoperiod increased chest girth, pituitary weight, and carcass yield. Effects of somatotropin-releasing factor and photoperiod were not additive on volume of mammary parenchymal tissue; there was also a treatment interaction on liver and lung weights. However, extraparenchymal mammary tissue was decreased by human somatotropin-releasing factor and short day photoperiod. In conclusion, use of somatotropin-releasing factor and photoperiod treatments affected carcass parameters and composition and mammary growth.

Nine pairs of identical twins were used to examine the effect of exogenous bovine somatotropin on mammary growth and development in dairy heifers. One twin received a daily subcutaneous injection of somatotropin (20 IU) and the other received excipient. Treatments commenced at 8.0 mo of age (179 kg live weight) and continued for 15.6 wk, at which time heifers were slaughtered and mammary development evaluated. Treatment with somatotropin resulted in an increase in mammary parenchyma and a decrease in extraparenchymal tissue and weight of mammary glands. Increases in parenchyma were 46% as determined by computer assisted x-ray tomography and 18% as determined by dissection. Differences between the two techniques related to the ability of computer assisted x-ray tomography technique to exclude fat deposits and connective tissue from parenchymal estimates. Chemical composition (39% water, 7% protein, and 54% fat) as well as histological and cytological appearance of the mammary parenchyma were not affected by the treatment. Therefore, treatment with exogenous somatotropin around puberty enhances the growth rate of mammary parenchymal tissue. Additional studies are required to examine whether this enhanced mammary development will increase milk yield during subsequent lactations.