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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 control of nutrient partitioning is complex and affected by many factors, among them physiological state and production potential. Therefore, the current model aims to provide for dairy cows a dynamic framework to predict a consistent set of reference performance patterns (milk component yields, body composition change, dry-matter intake) sensitive to physiological status across a range of milk production potentials (within and between breeds). Flows and partition of net energy toward maintenance, growth, gestation, body reserves and milk components are described in the model. The structure of the model is characterized by two sub-models, a regulating sub-model of homeorhetic control which sets dynamic partitioning rules along the lactation, and an operating sub-model that translates this into animal performance. The regulating sub-model describes lactation as the result of three driving forces: (1) use of previously acquired resources through mobilization, (2) acquisition of new resources with a priority of partition towards milk and (3) subsequent use of resources towards body reserves gain. The dynamics of these three driving forces were adjusted separately for fat (milk and body), protein (milk and body) and lactose (milk). Milk yield is predicted from lactose and protein yields with an empirical equation developed from literature data. The model predicts desired dry-matter intake as an outcome of net energy requirements for a given dietary net energy content. The parameters controlling milk component yields and body composition changes were calibrated using two data sets in which the diet was the same for all animals. Weekly data from Holstein dairy cows was used to calibrate the model within-breed across milk production potentials. A second data set was used to evaluate the model and to calibrate it for breed differences (Holstein, Danish Red and Jersey) on the mobilization/reconstitution of body composition and on the yield of individual milk components. These calibrations showed that the model framework was able to adequately simulate milk yield, milk component yields, body composition changes and dry-matter intake throughout lactation for primiparous and multiparous cows differing in their production level. [ABSTRACT FROM AUTHOR]

A minimally invasive biopsy technique was evaluated for udder tissue collection in dairy cows with Escherichia coli mastitis. Meanwhile, the effect of taking repeated liver and udder biopsies on the systemic and local acute phase response (APR) of the dairy cows was investigated during the disease. The cows were divided into a biopsy group (B) (n = 16) and a no-biopsy group (NB) (n = 16) and were sampled in the acute disease stage and in the recovery stage. The cows’ pre-disease period served as a control period for establishing baseline values for the investigated parameters. A total of 32 Holstein-Friesian cows were inoculated with 20 to 40 colony-forming units (cfu) of E. coli in one front quarter at 0 hour. Liver biopsies were collected at −144, 12, 24 and 192 h, and udder biopsies were collected at 24 and 192 h post E. coli inoculation (PI) using a minimally invasive biopsy technique. Effects of combined biopsying were investigated by recording production traits, clinical response, and measuring inflammatory milk and blood parameters: E. coli, somatic cell count, milk amyloid A (MAA) levels, white blood cell count, polymorphonuclear neutrophilic leukocyte numbers and serum amyloid A levels at several time points. E. coli inoculation changed all production parameters and the clinical and inflammatory response in all cows except one that was not infected. Combined biopsying had no constant or transient effect on the daily feed intake, the clinical responsiveness or the blood parameters, but affected the daily milk yield and some milk parameters transiently, that is, the presence of blood in milk, increased E. coli counts and MAA levels during the acute disease stage. Combined biopsying had no effect on the parameters in the recovery stage apart from the presence of blood in the milk. In conclusion, although, a minimally invasive biopsy technique was used, tissue damages could not be avoided when biopsying and they transiently affected the inflammatory parameters in the mammary gland. Nevertheless, we believe combined biopsying of liver and udder is as an acceptable approach to study the systemic and local APR in dairy cows during E. coli mastitis, if the timing of biopsying and other types of sampling is planned accordingly. [ABSTRACT FROM PUBLISHER]

Fast identification of pathogenic bacteria in milk samples from cows with clinical mastitis is central to proper treatment. In Denmark, time to bacterial di-agnosis is typically 24 to 48 h when using traditional culturing methods. The PCR technique provides a faster and highly sensitive identification of bacterial pathogens, although shipment of samples to diagnostic laboratories delays treatment decisions. Due to the lack of fast onsite tests that can identify the causative pathogens, antibiotic treatments are often initiated before bacterial identification. The present study describes a flow cytometry-based method, which can detect and distinguish gram-negative and gram-positive bacteria in mastitis milk samples. The differentiation was based on bacterial fluorescence intensities upon labeling with biotin-conjugated wheat germ agglutinin and acridine orange. Initially 19 in-house bacterial cultures (4 gram-negative and 15 gram-positive strains) were analyzed, and biotin-conjugated wheat germ agglutinin and acridine orange florescence intensities were determined for gram-negative and gram-positive bacteria, respectively. Fluorescence cut-off values were established based on receiver operating characteristic curves for the 19 bacterial cultures. The method was then tested on 53 selected mastitis cases obtained from the department biobank (milk samples from 6 gram-negative and 47 gram-positive mastitis cases). Gram-negative bacteria in milk samples were detected with a sensitivity of 1 and a specificity of 0.74, when classification was based on the previously established cut-off values. However, when receiver operating characteristic curves were constructed for the 53 mastitis cases, results indicate that a sensitivity and specificity of 1 could be reached if cut-off values were reduced. This flow cytometry-based technique could potentially provide dairy farmers and attending veterinarians with on-site information on bac-terial gram-type and prevent ineffective antimicrobial treatment in mastitis cases caused by gram-negative bacteria. [ABSTRACT FROM AUTHOR]

The importance of non-visual and on-line monitoring of udder health increases as the contact between humans and animals decreases, for example, in robotic milking systems. Several indicator systems have been introduced commercially, and a number of techniques are currently in use. This study describes the kinetics of seven indigenous milk parameters for monitoring udder inflammation in an Escherichia coli lipopolysaccharide (LPS, endotoxin)-induced mastitis model. Proportional milk from LPS-infused quarters was compared with milk from parallel quarters, which were placebo-treated with sterile 0.9% NaCl solution. Somatic cell counts (SCCs), the acute phase proteins (APP), that is, milk amyloid A (MAA) and haptoglobin (Hp), and the enzymes N-acetyl-β-D-glucosaminidase (NAGase), lactate dehydrogenase (LDH), alkaline phosphatase (AP) and acid phosphatase (AcP) were measured at fixed intervals during the period from -2 to +5 days after LPS and NaCl infusions. All parameters responded significantly faster and were more pronounced to the LPS infusions compared with the NaCl infusions. All parameters were elevated in the proportional milk collected at the first milking 7 h after infusion and developed a monophasic response, except Hp and MAA that developed biphasic response. SCC, LDH, NAGase and Hp peaked at 21 h followed by AP, AcP and MAA peaking at 31 h with the highest fold changes seen for MAA (23 780x), LDH (126x), NAGase (50x) and Hp (16x). In the recovery phase, AP, AcP and Hp reached base levels first, at 117 h, whereas LDH, NAGase and MAA remained elevated following the pattern of SCC. Minor increases of the milk parameters were also seen in the neighboring (healthy) quarters. Distinction between inflamed and healthy quarters was possible for all the parameters, but only for a limited time frame for AP and AcP. Hence, when tested in an LPS mastitis model, the enzymes LDH, NAGase and AP in several aspects performed equally with SCC and APP as inflammatory milk indicators of mastitis. Furthermore, these enzymes appear potent in the assessment of a valuable time sequence of inflammation, a necessary ingredient in modeling of programs in in-line surveillance systems. [ABSTRACT FROM AUTHOR]

A simple method to predict the genetically driven pattern of body lipid change through pregnancy and lactation in dairy cattle is proposed. The rationale and evidence for genetically driven body lipid change have their basis in evolutionary considerations and in the homeorhetic changes in lipid metabolism through the reproductive cycle. The inputs required to predict body lipid change are body lipid mass at calving (kg) and the date of conception (days in milk). Body lipid mass can be derived from body condition score and live weight. A key assumption is that there is a linear rate of change of the rate of body lipid change (dL/dt) between calving and a genetically determined time in lactation (T') at which a particular level of body lipid (L') is sought. A second assumption is that there is a linear rate of change of the rate of body lipid change (dL/dt) between T' and the next calving. The resulting model was evaluated using 2 sets of data. The first was from Holstein cows with 3 different levels of body fatness at calving. The second was from Jersey cows in first, second, and third parity. The model was found to reproduce the observed patterns of change in body lipid reserves through lactation in both data sets. The average error of prediction was low, less than the variation normally associated with the recording of condition score, and was similar for the 2 data sets. When the model was applied using the initially suggested parameter values derived from the literature the average error of prediction was 0.185 units of condition score (± 0.086 SD). After minor adjustments to the parameter values, the average error of prediction was 0.118 units of condition score (± 0.070 SD). The assumptions on which the model is based were sufficient to predict the changes in body lipid of both Holstein and Jersey cows under different nutritional conditions and parities. Thus, the model presented here shows that it is possible to predict genetically driven... [ABSTRACT FROM AUTHOR]

An abstract of the article "Metabolic Challenges in Late Pregnancy in Multiparous Ewes Fed Silage or Hay," by P. Norgaard and colleagues is presented.

An abstract of the article "Infusion of Insulin in Dairy Cows Inhibitors Neutrophils Phagocytosis of Staphylococcus Aureus Ex Vivo," by C.M. Rontved, L.R. Norup, M. Mashek , Lotte Nielsen and K.L. Ingvartsen is presented.

Physiological imbalance (PI) is a situation in which physiological parameters deviate from the normal and cows consequently have an increased risk of developing production diseases and reduced production or reproduction. The objectives of this work were (1) to generate an index for PI based on several plasma metabolites and (2) to compare the use of this index with calculated energy balance (EBAL) and individual plasma metabolites in relation to risk of disease during early lactation. We used a total of 634 lactations from 317 cows consisting of 3 breeds ranging from a parity of 1 to 4. Weekly blood samples were analyzed for selected metabolites; that is, urea nitrogen, albumin, cholesterol, nonesterified fatty acids (NEFA), glucose, and β-hydroxybutyrate (BHBA). Energy intake and EBAL were calculated; veterinary treatment records and daily composite milk somatic cell counts were used to determine incidence of disease. Data were adjusted for numerous fixed effects (e.g., parity, breed, and week around calving) before further statistical analysis. The time of disease (TOD) was recorded as the day in which the signs of disease were observed (TOD = 0). The week before and after TOD was ± n wk relative to TOD = 0. Each week, all plasma metabolites were individually adjusted to an overall mean (=0) and variance (=1). The normalized variables were included in regression analyses by week of lactation to identify metabolites that explain the variation in calculated EBAL, as a reflection of degree of PI. Nonesterified fatty acids, BHBA, and glucose were weighted within each week based on regression coefficients (i.e., x1-x3 below) generated from a model to predict EBAL. Data from wk -1 relative to TOD were analyzed using a mixed linear model to relate degree of PI and metabolites in blood to risk of disease. The weekly PI index was defined as PI = (x1 x [NEFA]) + x2 x [BHBA] - x3 x [glucose])/3. For diseases that developed ≥2 wk after calving, no variables were associated with risk of disease. Prepartal PI and plasma NEFA were better predictors of disease (i.e., metritis, retained placenta, and milk fever) at wk 1 than EBAL and plasma BHBA and glucose. Examining the relationship between PI and milk constituents is needed for the development of an automated in-line and real-time surveillance system for early detection of risk animals on-farm. [ABSTRACT FROM AUTHOR]

The objective of this field study was to evaluate the effect of supplemental feeding with glycerol or propylene glycol to dairy cows in early lactation on metabolic status, body condition and milk yield. In total, 673 newly calved cows from 12 commercial Swedish dairy herds were randomized to daily supplementation with 450 g of glycerol (GLY), 300 g of propylene glycol (PG), or nothing (control, CON). Supplements were fed twice daily from 0 to 21 d in milk (DIM) as a top dress on concentrates. For each cow, data on parity, breed, calving date, monthly test-day milk yield, and cases of diseases were collected. Blood samples were taken at approximately 2, 5, and 8 wk postpartum (pp) and analyzed for glucose, β-hydroxybutyrate (BHBA), nonesterified fatty acids (NEFA), and insulin. Samples taken within 3 wk pp were also analyzed for insulin-like growth factor 1 (IGF-1). Measurements of body condition score (BCS) and heart girth (HG) were obtained at approximately 2 and 5 wk pp and at time of first insemination. The effects of supplemental feeding with GLY or PG on the plasma concentrations of glucose, NEFA, BHBA, insulin, and IGF-1, and BCS, HG, and occurrence of disease were analyzed. No differences in BCS or HG or in plasma concentrations of glucose, BHBA, NEFA, or IGF-1 were found between the control group and any of the treatment groups. Cows in the GLY group had lower plasma insulin concentrations during DIM 0 to 63 compared with group CON, but no difference in insulin was found between the PG group and the CON group. Cows supplemented with GLY had a higher milk yield (kg of milk and kg of energy-corrected milk) during the first 90 DIM. Cows in the PG group tended to yield more milk during the same period. No differences in the occurrence of diseases were seen between the groups. In conclusion, supplementation with GLY in early lactation did increase milk yield without a subsequent decrease of metabolic status, and supplementation with PG tended to do the same. [ABSTRACT FROM AUTHOR]

Steady-state levels of mRNA are often used to infer treatment effects on the levels of the corresponding protein. In addition, an internal standard RNA is usually measured to document specificity of treatment and to correct for intersample variation. Our objective was to evaluate whether glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and cyclophilin could be used as internal standards when studying changes in hepatic gene expression in dairy cows. Hepatic expression of GAPDH and cyclophilin was measured in 6 cows in late pregnancy (28 d prepartum) and early lactation (10 d postpartum). Each gene displayed 2- to 3-fold higher expression in early lactation than in late pregnancy. Next, we determined whether negative energy balance alone or in combination with exogenous growth hormone could mimic the effects of early lactation. Latelactating cows were fed 120% of predicted energy requirements or 33% of maintenance requirements. During each feeding period, cows were administered excipient or bovine somatotropin in a single-reversal design with 4-d periods separated by a 2-d interval. Underfeeding increased hepatic expression of GAPDH and cyclophilin by 1- to 2-fold, whereas bovine somatotropin had no effect. Finally, the effects of insulin were studied by performing hyperinsulinemic-euglycemic clamps in late pregnancy (28 d prepartum) and early lactation (28 d postpartum). Hyperinsulinemia reduced GAPDH expression in both states, and cyclophilin expression in early lactation. In conclusion, GAPDH and cyclophilin are regulated in the liver of dairy cows and should not be used to standardize hepatic gene expression in studies involving the transition period, undernutrition, and sustained changes in plasma insulin. [ABSTRACT FROM AUTHOR]

This study explored the ability of an existing lifetime nutrient partitioning model for simulating individual variability in genetic potentials of dairy cows. Generally, the model assumes a universal trajectory of dynamic partitioning of priority between life functions and genetic scaling parameters are then incorporated to simulate individual difference in performance. Data of 102 cows including 180 lactations of 3 breeds: Danish Red, Danish Holstein, and Jersey, which were completely independent from those used previously for model development, were used. Individual cow performance records through sequential lactations were used to derive genetic scaling parameters for each animal by calibrating the model to achieve best fit, cow by cow. The model was able to fit individual curves of body weight, and milk fat, milk protein, and milk lactose concentrations with a high degree of accuracy. Daily milk yield and dry matter intake were satisfactorily predicted in early and mid lactation, but underpredictions were found in late lactation. Breeds and parities did not significantly affect the prediction accuracy. The means of genetic scaling parameters between Danish Red and Danish Holstein were similar but significantly different from those of Jersey. The extent of correlations between the genetic scaling parameters was consistent with that reported in the literature. In conclusion, this model is of value as a tool to derive estimates of genetic potentials of milk yield, milk composition, body reserve usage, and growth for different genotypes of cow. Moreover, it can be used to separate genetic variability in performance between individual cows from environmental noise. The model enables simulation of the effects of a genetic selection strategy on lifetime efficiency of individual cows, which has a main advantage of including the rearing costs, and thus, can be used to explore the impact of future selection on animal performance and efficiency. [ABSTRACT FROM AUTHOR]

Lameness is a frequent health problem in dairy cows. This preliminary study aimed to detect gait differences between healthy and lame walking cows using 3-dimensional force plates. We examined left-right leg symmetry changes of healthy and lame Holstein dairy cows following claw trimming. Gait scoring (GS) was performed on d -5, 0, 1, and 7 relative to claw trimming. Before the experiment, 5 cows walked normally (initial GS = 1) and 4 cows limped moderately on a hind leg (initial GS = 3). Gait was measured on d -2, -1, 0, 1, and 7 relative to trimming by obtaining ground reaction forces as cows walked repeatedly across 2 parallel 3-dimensional force plates. From the ground reaction forces, stance phase data were derived using computerized procedures. Left-right leg symmetries of entire curves in the 3 force directions were calculated. Effects of lameness and trimming were analyzed in a mixed model, using a low lameness threshold (GS > 1). One week after claw trimming, only one cow was mildly lame. In addition, the symmetries of all 3 dimensions were significantly improved shortly after trimming. Importantly, lameness significantly worsened vertical symmetry. Lame cows walked significantly more slowly than healthy cows. In conclusion, all force symmetries seemed capable of detecting gait responses to claw trimming. Although our results are based on a small number of animals, vertical leg symmetry was affected by lameness. [ABSTRACT FROM AUTHOR]

Identification of biomarkers for degree of physiological imbalance (PI), a situation in which physiological parameters deviate from normal, is needed to reduce disease risk and improve production and reproduction performance of cows. The objective was to describe the liver proteome in early and mid lactation for cows with different degrees of PI with a special focus on biomarkers and pathways involved in periparturient disease complexes. Twenty-nine cows in early [49 ± 22 d in milk (DIM); n = 14] and mid (159 ± 39 DIM; n = 15) lactation were nutrient restricted for 4 d to increase PI by supplementing the ration with 60% wheat straw. Liver biopsies were collected -1 and 3 d relative to restriction. Before restriction, an index for PI was calculated based on plasma nonesterified fatty acids, β-hydroxybutyrate, and glucose concentrations. Within E and M cows, a subsets of 6 cow was classified as having either the greatest (PI) or least (normal; N) degree of PI and were used for isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative profiling in liver using liquid chromatography-tandem mass spectrometry. We identified pyruvate carboxylase and isocitrate dehydrogenase as potential hepatic biomarkers for PI for cows during early lactation and alcohol dehydrogenase-4 and methylmalonate-semialdehyde dehydrogenase for cows in mid lactation. This preliminary study identified new biomarkers in liver for PI and provided a better understanding of the differences in coping strategies used for cows in PI. Despite the small sample size (n = 3/group), the results lay a foundation for future research focused on the usefulness of the hepatic biomarkers for predicting PI and thereby cows at risk for disease during lactation. [ABSTRACT FROM AUTHOR]