Martin Bjerring

Cytokine and acute phase protein gene expression in repeated liver biopsies of dairy cows with a lipopolysaccharide-induced mastitis

A minimally invasive liver biopsy technique was tested for its applicability to study the hepatic acute phase response (APR) in dairy cows with Escherichia coli lipopolysaccharide (LPS)-induced mastitis. The hepatic mRNA expression profiles of the inflammatory cytokines, tumor necrosis factor alpha (TNF-alpha), IL-1beta, IL-6, and IL-10, and the acute phase proteins serum amyloid A isoform 3 (SAA3), haptoglobin (Hp), and alpha(1)-acid glycoprotein (AGP) were determined by real-time reverse transcription-PCR. Fourteen primiparous cows in mid lactation were challenged with 200 microg of LPS (n = 8) or NaCl solution (n = 6) in 1 front quarter. Six repeated liver biopsies were collected at -22, 3, 6, 9, 12, and 48 h relative to LPS challenge in 4 LPS-infused cows and 3 NaCl-infused cows. The remaining cows had 3 liver biopsies taken at -22, 9, and 48 h. Production data and clinical signs were recorded and white blood cell counts and somatic cell counts (SCC) were analyzed to investigate the effect of repeated liver biopsies and verify the LPS model. Plasma concentrations of TNF-alpha, SAA3, Hp, and AGP were determined for comparison with the liver expression data. Repeated liver biopsies had no effects on the production data, clinical signs, or APR of dairy cows. Compared with the NaCl-infused cows the LPS-infused cows responded to the LPS treatment by increased body temperature (38.6 +/- 0.1 vs. 39.4 +/- 0.1 degrees C), short-term leukopenia followed by leukocytosis (6.44 +/- 0.4 vs. 5.69 +/- 0.3 x 10(6) cells/mL), an increased SCC (log(10) 2.1 +/- 0.1 vs. log(10) 2.8 +/- 0.1 x 10(3) cells/mL), heart rate (76 +/- 1 vs. 93 +/- 1 beats/min), and respiratory rate (32 +/- 2 vs. 36 +/- 1 breaths/min) in the acute phase of the disease. The LPS treatment upregulated the hepatic expression of TNF-alpha (103 +/- 24 vs. 255 +/- 18 units), IL-1beta (37 +/- 23 vs. 296 +/- 18 units), IL-6 (8 +/- 17 vs. 122 +/- 12 units), and IL-10 (130 +/- 66 vs. 541 +/- 50 units), and SAA3 (64 +/- 36 vs. 128 +/- 28 units) and Hp (9 +/- 82 vs. 762 +/- 65 units) reaching maximum levels at 3 to 6 h and 9 to 12 h postinfusion, respectively. Plasma concentrations of TNF-alpha (nondetectable vs. 1.9 +/- 0.3 ng/mL), SAA (19.8 +/- 19.4 vs. 149.7 +/- 15.5 microg/mL) and Hp (71.4 +/- 143.7 vs. 1,013.8 +/- 111.5 microg/mL) were elevated in the LPS-infused cows at 4 to 12 h, 8 to 120 h, and 24 to 120 h postinfusion, respectively. The hepatic expression of AGP and the AGP plasma concentration remained unaltered in LPS-induced cows. In conclusion, a minimally invasive liver biopsy technique can be used for studying the hepatic APR in diseased cattle. Lipopolysaccharide-induced mastitis resulted in a time-dependent production of inflammatory cytokines and SAA and Hp in the liver of dairy cows.

L-lactate dehydrogenase and N-acetyl-β-D-glucosaminidase activities in bovine milk as indicators of non-specific mastitis

Systematic factors affecting the activities of L-lactate dehydrogenase (LDH) and N-acetyl-beta-D-glucosaminidase (NAGase) and somatic cell count (SCC), the association between the activities of LDH and NAGase and SCC with respect to udder health status, and the ability of LDH and NAGase to classify cows in udder health categories for early detection of mastitis were studied. A dataset of records from 74 Danish Holstein, 76 Danish Red and 47 Jersey cows on one research farm was used. Cows were grouped into healthy and clinically mastitic. A healthy cow was defined as having no veterinary treatment and SCC<100,000 cells/ml. A clinically infected cow was one receiving veterinary treatment after showing clinical signs of mastitis and SCC >800,000 cells/ml. Breed, month of production, and days in milk significantly influenced (P<0.001) LDH activity, NAGase activity and SCC in both healthy and clinically mastitic cows. In healthy cows, LDH activity, NAGase activity and SCC started at a high level immediately after calving and decreased to low levels approximately 30-40 d post partum. All the three parameters increased due to clinical mastitis. NAGase activity had numerically higher variation in healthy cows than in clinically mastitic cows (CV=56.2% v. CV=53.5%). The relationship between LDH activity and SCC was stronger in milk from clinically mastitic than from healthy cows (r=0.76 v. r=0.48 and r=0.67 v. r=0.44 for correlation of observed values and residuals, respectively). LDH activity had higher sensitivity than NAGase activity (73-95% v. 35-77%) while specificities were in a similar range (92-99%). Further, sensitivities for LDH activity were more robust to changes in the threshold value than those for NAGase activity. Opportunities for automated, in-line real-time mastitis detection are discussed.

Improved Detection of Reproductive Status in Dairy Cows Using Milk Progesterone Measurements

This study tested a model for predicting reproductive status from in-line milk progesterone ;measurements. The model is that of Friggens and Chagunda [Theriogenology 64 (2005) 155]. Milk progesterone measurements (n = 55 036) representing 578 lactations from 380 cows were used to test the model. Two types of known oestrus were identified: (1) confirmed oestrus (at which insemination resulted in a confirmed pregnancy, n = 121) and (2) ratified oestrus (where the shape of the progesterone profile matched that of the average progesterone profile of a confirmed oestrus, n = 679). The model detected 99.2% of the confirmed oestruses. This included a number of cases (n = 16) where the smoothed progesterone did not decrease below 4 ng/ml. These cows had significantly greater concentrations of progesterone, both minimum and average, suggesting that between cow variation exists in the absolute level of the progesterone profile. Using ratified oestruses, model sensitivity was 93.3% and specificity was 93.7% for detection of oestrus. Examination of false positives showed that they were largely associated with low concentrations of progesterone, fluctuating around the 4 ng/ml threshold. The distribution of time from insemination until the model detected pregnancy failure had a median of 22 days post-insemination. In this test, the model was run using limited inputs, the potential benefits of including additional non-progesterone information were not evaluated. Despite this, the model performed at least as well as other oestrus detection systems.

Enzyme activity and acute phase proteins in milk utilized as indicators of acute clinical E. coli LPS-induced mastitis.

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 (23 780×), LDH (126×), NAGase (50×) and Hp (16×). 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.

Visual scoring of milk mixed with blood.

Sorting of normal and abnormal milk at time of milking is done visually for conventional milking systems, but more concrete standards are needed when milking is done in automatic milking systems (AMS). Several panel tests were carried out to find out how different consumer groups, milkers and advisors look at and respond to the visual appearance of milk mixed with blood, in order to set a limit for what they think is acceptable. It is concluded from the test panel results that milk samples with 0.4% or more of blood all will be scored as pink and samples with 0.1% blood (about 6 microM-haemoglobin or 100 mg/l) can be visually detected if they are compared with milk samples without blood. The consumer group scored fewer of the samples with 0-1% blood as normal than did the professional groups. The test panel scored 65% of the samples with 1% blood as normal when milk was presented in a black strip cup, which is the reference method when foremilking takes place in a conventional parlour. Only 2% of the milk samples with 2% blood (about 120 microM-haemoglobin or 2000 mg/l) were scored as normal in a black strip cup and should consequently be detected by conventional as well as automatic systems. One model of AMS was tested for its ability to detect and separate milk coloured by blood. The model separated milk with > or = 6 microM-haemoglobin. Milk mixed with blood injected into the milk stream for a short time at the beginning of milking was not separated. We lack data on how blood is naturally expelled into milk and in what amount. We propose that cow composite milk with > 6 microM-haemoglobin should be separated because at this level milk will have a red tinge.

Visual appearance and CMT score of foremilk of individual quarters in relation to cell count of cows milked automatically

The objectives of the study were: to evaluate the interaction between visual appearance and California mastitis test (CMT) score of the foremilk in relation to the cell count of the milk; to evaluate the consequences of sorting milk according to these criteria; and to explore whether visual appearance and CMT score of foremilk depended on the time interval between milkings. Measuring somatic cell count (SCC) in composite milk only and discarding milk above certain thresholds will not ensure that milk from all cows with visually abnormal foremilk is withheld from delivery. Low thresholds of SCC will reduce the frequency of cows with abnormal milk but increase the discarding of milk from cows with visually normal foremilk. CMT score of foremilk differentiated better between cows with high and low SCC in composite milk than visual inspection of foremilk. CMT scores of foremilk decreased with increasing interval between milkings within cow, whereas the visual appearance was independent of the interval. We propose that visual appearance of the foremilk should be kept as a criterion for sorting milk at time of milking. For test purposes, the use of visual appearance of foremilk for differentiation between normal and abnormal milk has to be done on multiple milkings. Additionally, CMT scoring of foremilk improves correct classification of normal and abnormal quarters and especially when including data from the previous milking.

Monitoring individual cow udder health in automated milking systems using online somatic cell counts

This study presents and validates a detection and monitoring model for mastitis based on automated frequent sampling of online cell count (OCC). Initially, data were filtered and adjusted for sensor drift and skewed distribution using ln-transformation. Acceptable data were passed on to a time-series model using double exponential smoothing to estimate level and trends at cow level. The OCC levels and trends were converted to a continuous (0-1) scale, termed elevated mastitis risk (EMR), where values close to zero indicate healthy cow status and values close to 1 indicate high risk of mastitis. Finally, a feedback loop was included to dynamically request a time to next sample, based on latest EMR values or errors in the raw data stream. The estimated EMR values were used to issue 2 types of alerts, new and (on-going) intramammary infection (IMI) alerts. The new alerts were issued when the EMR values exceeded a threshold, and the IMI alerts were issued for subsequent alerts. New alerts were only issued after the EMR had been below the threshold for at least 8d. The detection model was evaluated using time-window analysis and commercial herd data (6 herds, 595,927 milkings) at different sampling intensities. Recorded treatments of mastitis were used as gold standard. Significantly higher EMR values were detected in treated than in contemporary untreated cows. The proportion of detected mastitis cases using new alerts was between 28.0 and 43.1% and highest for a fixed sampling scheme aiming at 24h between measurements. This was higher for IMI alerts, between 54.6 and 89.0%, and highest when all available measurements were used. The lowest false alert rate of 6.5 per 1,000 milkings was observed when all measurements were used. The results showed that a dynamic sampling scheme with a default value of 24h between measurements gave only a small reduction in proportion of detected mastitis treatments and remained at 88.5%. It was concluded that filtering of raw data combined with a time-series model was effective in detecting and monitoring mastitis status in dairy cows when based on IMI alerts, and by using a dynamically adjusting sampling scheme almost full performance was still obtainable. However, results were less desirable when based on new alerts most likely because of the used gold standard for mastitis, which may not necessarily reflect the onset of and IMI case in contrast to a new alert.

Short communication: Genetic variation in choice consistency for cows accessing automatic milking units

Dairy cows milked in automatic milking systems (AMS) with more than 1 milking box may, as individuals, have a preference for specific milking boxes if allowed free choice. Estimates of quantitative genetic variation in behavioral traits of farmed animals have previously been reported, with estimates of heritability ranging widely. However, for the consistency of choice in dairy cows, almost no published estimates of heritability exist. The hypothesis for this study was that choice consistency is partly under additive genetic control and partly controlled by permanent environmental (animal) effects. The aims of this study were to obtain estimates of genetic and phenotypic parameters for choice consistency in dairy cows milked in AMS herds. Data were obtained from 5 commercial Danish herds (I-V) with 2 AMS milking boxes (A, B). Milking data were only from milkings where both the present and the previous milkings were coded as completed. This filter was used to fulfill a criterion of free-choice situation (713,772 milkings, 1,231 cows). The lactation was divided into 20 segments covering 15d each, from 5 to 305d in milk. Choice consistency scores were obtained as the fraction of milkings without change of box [i.e., 1.0 - µ(box change)] for each segment. Data were analyzed for one part of lactation at a time using a linear mixed model for first-parity cows alone and for all parities jointly. Choice consistency was found to be only weakly heritable (heritability=0.02 to 0.14) in first as well as in later parities, and having intermediate repeatability (repeatability coefficients=0.27 to 0.56). Heritability was especially low at early and late lactation states. These results indicate that consistency, which is itself an indication of repeated similar choices, is also repeatable as a trait observed over longer time periods. However, the genetic background seems to play a smaller role compared with that of the permanent animal effects, indicating that consistency could also be a learned behavior. We concluded that consistency in choices are quantifiable, but only under weak genetic control.