[Investigations of a controlled, decision tree based procedure for Selective Dry Cow Treatment in Bavarian dairy farms]

OBJECTIVE

Four parameters of a decision tree for Selective Dry Cow Treatment (SDCT), examined in a previous study, were analyzed regarding their efficacy in detecting cows for dry cow treatment (DCT, use of intramammary antimicrobials). This study set out to review wether all parameters (somatic cell count [SCC≥ 200 000 SC/ml 3 months' milk yield recordings prior dry off (DO)], clinical mastitis history during lactation [≥1 CM], culturing [14d prior DO, detection of major pathogens] and California-Mastitis-Test [CMT, > rate 1/+ at DO]) are necessary for accurate decision making, whether there are possible alternatives to replace culturing, and whether a simplified model could replace the decision tree.

MATERIAL AND METHODS

Records of 18 Bavarian dairy farms from June 2015 to August 2017 were processed. Data analysis was carried out by means of descriptive statistics, as well as employing a binary cost sensitive classification tree and logit-models. For statistical analyses the outcomes of the full 4-parameter decision tree were taken as ground truth.

RESULTS

848 drying off procedures in 739 dairy cows (CDO) were included. SCC and CMT selected 88.1%, in combination with CM 95.6% of the cows that received DCT (n=494). Without culturing, 22 (4.4%) with major pathogens (8x Staphylococcus [S.] aureus) infected CDO would have been misclassified as not needing DCT. The average of geometric mean SCC (within 100 d prior DO) for CDO with negative results in culturing was<100 000 SC/ml milk, 100 000-150 000 SC/ml for CDO infected with minor pathogens, and ≥ 150 000 SC/ml for CDO infected with major pathogens (excluding S.aureus). Using SCC during lactation (at least 1x > 200 000 SC/ml) and positive CMT to select CDO for DCT, contrary to the decision tree, 37 CDO (4.4%) would have been treated "incorrectly without" and 43 CDO (5.1%) "unnecessarily with" DCT. Modifications were identified, such as SCC<131 000 SC/ml within 100 d prior to DO for detecting CDO with no growth or minor pathogens in culturing. The best model for grading CDO for or against DCT (CDO without CM and SCC<200 000 SC/ml [last 3 months prior DO]) had metrics of AUC=0.74, Accuracy=0.778, balanced Accuracy=0.63, Sensitivity=0.92 and Specificity=0.33.

CONCLUSIONS

Combining the decision tree's parameters SCC, CMT and CM renders suitable selection criteria under the conditions of this study. When omitting culturing, lower thresholds for SCC should be considered for each farm individually to select CDO for DCT. Nonetheless, the most accurate model could not replace the full decision tree.

[Veterinary Herd Health Management and Selective Dry Cow Treatment in Germany - Results of a survey among farm veterinarians]

OBJECTIVE

The aim of the survey was to evaluate the development and implementation of Veterinary Herd Health Management (VHHM), as well as Selective Dry Cow Treatment (SDCT), in German veterinary practices and dairy farms. Furthermore, this survey set out to compare and contrast veterinary practitioners that utilize VHHM in relation to SDCT with those that do not.

MATERIAL AND METHODS

The survey (n=600) was distributed to veterinary livestock practitioners at 7 advanced training courses. Participation was voluntary and anonymous. Data analysis was carried out by means of descriptive statistics as well as by linear and logistic regression.

RESULTS

The response rate amounted to 39.3% (n=236). 54.2% (n=128) of the veterinarians reported that they conduct VHHM. Procedures for SDCT were used on farms overseen by 75% (n=177) of the vets. Different decision criteria applied at herd (81.6%, n=142) and at individual cow level (97.7%, n=172) respectively. A performance review of SDCT was carried out more frequently on farms of veterinarians that practice VHHM (66%, n=66) than those that do not (41%, n=28). An increase in the number of farms conducting VHHM was associated with an increase in the proportion of farms using SDCT. An increase of the probability of good udder health was associated with SDCT farms that also apply VHHM (OR: 1.025; p<0.05). The provision of consultation for problems arising during the dry period (OR: 3.639; p<0.05), the frequency of veterinarians addressing SDCT with farmers (OR: 1,595; p<0,05) and vice versa (OR: 1,538; p<0.05), as well as frequency of consultation for drying off management (OR: 1,608; p<0.05) had an positive impact on the likelihood of SDCT being implemented on a farm and whether this process was ultimately successful.

CONCLUSIONS

According to available data, both VHHM and SDCT are established parts of veterinary practice in bovine care. In practice, SDCT is partially conducted within the framework of a controlled procedure including a performance review. The implementation of VHHM has an effect on the number of farms performing SDCT as well as on udder health where VHHM and SDCT are combined on a farm. The range and frequency of consultation by veterinarians have a significant influence on a reduction of use of antibiotics by implementation of SDCT.

Evaluation of Cow-Side Meters to Determine Somatic Cell Count in Individual Cow Quarter and Bulk-Tank Milk Samples

Intramammary infections, which cause mastitis, can increase treatment and labor costs, decrease milk production, and affect milk quality. Meters that measure quarter somatic cell count (SCC) could be used to make more informed dry cow therapy decisions. The objective of this study was to compare the RT-10 iPhone adapter (RT-10; Dairy Quality Inc., Newmarket, ON, Canada), DeLaval Cell Counter (DSCC; DeLaval, Gurnee, IL, USA), Porta Check Quick Test (PortaCheck, White City, OR, USA), California Mastitis Test (ImmuCell, Portland, ME USA), pH meter (Hanna Instruments, Smithfield, RI, USA), electrical conductivity meter (OHAUS, Parsippany, NJ, USA), and the dual laser infrared temperature thermometer (Klein Tools, Lincolnshire, IL, USA) for measuring SCC in individual Holstein mammary quarters in comparison to a reference standard, the Fourier Transform Spectrometer 600 Combi System (Combi; Bentley Instruments, Chaska, MN, USA). Meters were evaluated using 658 individual cow quarter samples and 100 bulk-tank samples to measure SCC. Individual quarter milk samples from 160 cows from four commercial dairy herds were collected just before dry off and tested within 4 h of collection. To test bulk-tank SCC, 100 bulk-tank milk samples (25 mL) were collected from UC Davis Veterinary Medicine Teaching and Research Milk Quality Lab. Meter SCC values were regressed on observed Combi SCC. Goodness of fit was then evaluated by partitioning the mean square predicted error (MSPE). For individual quarter SCC, RT-10 had the highest coefficient of determination (R² = 0.86), lowest MSPE, and highest proportion of MSPE due to random variation (96%). Both the RT-10 and DSCC had the highest sensitivity and specificity for identifying quarter SCC above and below 200,000 cells/mL. For bulk-tank SCC, DSCC had the highest coefficient of determination (R² = 0.45), lowest MSPE, and highest proportion of MSPE due to random variation (80%). The RT-10 and DSCC could be used to measure individual quarter SCC to determine which cows to treat at dry off potentially reducing antibiotic use.

Evaluation of test-day milk somatic cell count to predict intramammary infection in late lactation grazing dairy cows

Use of selective dry cow antimicrobial therapy requires to precisely differentiate cows with an intramammary infection (IMI) from uninfected cows close to drying-off to enable treatment allocation. Milk somatic cell count (SCC) is an indicator of an inflammatory response in the mammary gland and is usually associated with IMI. However, SCC can also be influenced by cow-level variables such as milk yield, lactation number and stage of lactation. In recent years, predictive algorithms have been developed to differentiate cows with IMI from cows without IMI based on SCC data. The objective of this observational study was to explore the association between SCC and subclinical IMI, taking cognizance of cow-level predictors on Irish seasonal spring calving, pasture-based systems. Additionally, the optimal test-day SCC cut-point (maximized sensitivity and specificity) for IMI diagnosis was determined. A total of 2,074 cows, across 21 spring calving dairy herds with an average monthly milk weighted bulk tank SCC of ≤200,000 cells/mL were enrolled in the study. Quarter-level milk sampling was carried out on all cows in late lactation (interquartile range = 240-261 d in milk) for bacteriological culturing. Bacteriological results were used to define cows with IMI, when ≥1 quarter sample resulted in bacterial growth. Cow-level test-day SCC records were provided by the herd owners. The ability of the average, maximum and last test-day SCC to predict infection were compared using receiver operator curves. Predictive logistic regression models tested included parity (primiparous or multiparous), yield at last test-day and a standardized count of high SCC test-days. In total, 18.7% of cows were classified as having an IMI, with first parity cows having a higher proportion of IMI (29.3%) compared with multiparous cows (16.1%). Staphylococcus aureus accounted for the majority of these infections. The last test-day SCC was the best predictor of infection with the highest area under the curve. The inclusions of parity, yield at last test-day, and a standardized count of high SCC test-days as predictors did not significantly improve the ability of last test-day SCC to predict IMI. The cut-point for last test-day SCC which maximized sensitivity and specificity was 64,975 cells/mL. This study indicates that in Irish seasonal pasture-based dairy herds,with low bulk tank SCC control programs, the last test-day SCC (interquartile range days in milk = 221-240) is the best predictor of IMI in late lactation.

Impact of Selective Dry Cow Therapy on Antimicrobial Consumption, Udder Health, Milk Yield, and Culling Hazard in Commercial Dairy Herds

The main objective of the study was to evaluate whether or not implementing selective dry cow therapy (SDCT) on commercial dairy farms reduces antimicrobial consumption without negatively affecting future performances when compared to blanket dry cow therapy (BDCT). Twelve commercial herds in the Flemish region of Belgium with overall good udder health management were enrolled in a randomized control trial, including 466 cows that were assigned to a BDCT (n = 244) or SDCT (n = 222) group within herds. Cows in the SDCT group were dried off with internal teat sealants combined or not with long-acting antimicrobials according to a predefined algorithm based on test-day somatic cell count (SCC) data. Total antimicrobial use for udder health between drying off and 100 days in milk was significantly lower in the SDCT group (i.e., a mean of 1.06 defined the course dose) compared to the BDCT group (i.e., a mean of 1.25 defined the course dose), although with substantial variation between herds. Test-day SCC values, milk yield, and the clinical mastitis and culling hazard in the first 100 days in milk did not differ between the BDCT and SDCT groups. SCC-based and algorithm-guided SDCT is suggested to decrease the overall use of antimicrobials without jeopardizing cows' udder health and milk yield.

Identification of Changes in Rumination Behavior Registered with an Online Sensor System in Cows with Subclinical Mastitis

The aim of the present study is to determine the relationship between subclinical mastitis and rumination behavior registered with an online sensor system. Based on the findings of the general clinical examination of 650 milking cows, 10 cows with subclinical mastitis (SCM) and 10 clinically healthy cows (HG) were selected (without clinical signs of any diseases). Rumination behavior biomarkers were registered with RumiWatch noseband sensors (RWS; ITIN + HOCH GmbH, Fütterungstechnik, Liestal, Switzerland). Sensors were implanted on the first day after calving. Data from the RWS 13 days before diagnosis of SCM and 13 days after diagnosis of SCM were compared with HG data from the same period. Healthy cows were checked alongside SCM cows on the same days. In our study, we found that healthy cows spent more time engaging in rumination and drinking (p < 0.05) and also had more boluses per rumination. Moreover, among cows with subclinical mastitis, rumination time from day 4 to day 0 decreased by 60.91%, drinking time decreased by 48.47%, and the number of boluses per rumination decreased by 8.67% (p < 0.05). The results indicate that subclinical affects time and rumination chews registered with sensor systems. However, additional studies with larger numbers of animals are required to confirm these results. Furthermore, the impact of heat stress, estrus, and other effects on rumination behavior biomarkers should be evaluated.

Invited review: Selective use of antimicrobials in dairy cattle at drying-off

Administering intramammary antimicrobials to all mammary quarters of dairy cows at drying-off [i.e., blanket dry cow therapy (BDCT)] has been a mainstay of mastitis prevention and control. However, as udder health has considerably improved over recent decades with reductions in intramammary infection prevalence at drying-off and the introduction of teat sealants, BDCT may no longer be necessary on all dairy farms, thereby supporting antimicrobial stewardship efforts. This narrative review summarizes available literature regarding current dry cow therapy practices and associated impacts of selective dry cow therapy (SDCT) on udder health, milk production, economics, antimicrobial use, and antimicrobial resistance. Various methods to identify infections at drying-off that could benefit from antimicrobial treatment are described for selecting cows or mammary quarters for treatment, including utilizing somatic cell count thresholds, pathogen identification, previous clinical mastitis history, or a combination of criteria. Selection methods may be enacted at the herd, cow, or quarter levels. Producers' and veterinarians' motivations for antimicrobial use are discussed. Based on review findings, SDCT can be adopted without negative consequences for udder health and milk production, and concurrent teat sealant use is recommended, especially in udder quarters receiving no intramammary antimicrobials. Furthermore, herd selection should be considered for SDCT implementation in addition to cow or quarter selection, as BDCT may still be temporarily necessary in some herds for optimal mastitis control. Costs and benefits of SDCT vary among herds, whereas impacts on antimicrobial resistance remain unclear. In summary, SDCT is a viable management option for maintaining udder health and milk production while improving antimicrobial stewardship in the dairy industry.

Potential impacts to antibiotics use around the dry period if selective dry cow therapy is adopted by dairy herds: An example of the western US

Mastitis is a prevalent and expensive disease in dairy herds worldwide. Blanket dry cow therapy (BDCT), in which all quarters of all cows are infused with antimicrobials at the dry-off, is a cornerstone for mastitis control in many countries. An alternative approach is the use of selective dry cow therapy (SDCT), in which only cows with high risk for intramammary infection (IMI) at dry-off receive antimicrobials. Our objectives in this cross-sectional study were to estimate the potential reduction in the use of antimicrobials if SDCT was adopted in the US by using cow-level dairy herd data and to describe the factors associated with cows being classified as high-risk for an IMI at dry-off. Besides, we aimed to describe the seasonality in IMI at dry-off. We used cow-level somatic cell score (SCS) test-day data from herds in the western US (DHIA, Dairy Herd Improvement Association, AgriTech, Visalia, CA) to create five scenarios to classify cows as high risk for IMI at dry-off. Associations between cow-level data and state were also used in logistic regression models. We also calculated the average animal-defined daily dosage of antimicrobials per cow per year around the dry period if a BDCT or SDCT approach is used, adjusting for the risk of cases of clinical mastitis in the next lactation for the SDCT approach. The point prevalence of IMI at the last test-day before dry-off varied between 15.0 % and 54 % for primiparous and 34.0 % and 85 % for multiparous cows, depending on the scenario. By extrapolating our results obtained from using data from dairies enrolled in the DHIA testing program for the western US, we demonstrated that regardless of the criteria used to classify cows as high risk of IMI at dry-off (scenarios 1-5), if selective dry cow therapy is adopted in the US, the dairy industry could reduce the use of antimicrobials around the dry-off between 31 % and 66 %. Multiparous cows had greater odds of being classified as high-risk than primiparous cows. Cows dried off in the spring, summer, and fall had lower odds of being classified as high-risk compared to cows dried off in the winter. Advanced days in milk at dry-off was associated with greater risk of IMI at dry-off. Greater milk yield and higher protein percentage at the last test-day before dry-off were associated with decreased odds of a cow being classified as high-risk at dry-off, cows in small herds had greater odds of being classified as high-risk at dry-off, and a variation among states was observed.

Herd Routines and Veterinary Advice Related to Dry-Cow Therapy and Treatment with Internal Teat Sealants in Dairy Cows

Simple Summary

At the end of lactation, antibiotics (DCT) or internal teat sealants (ITS) can be used to treat or prevent mastitis in dairy cows. Recommendations on how to perform such treatments are available, but little is known about how well these are followed by farmers and veterinarians. To increase this knowledge, questionnaires about farmer routines and veterinary advice were sent to 2472 farmers and 517 veterinarians in Sweden. Fourteen percent of the farmers and 25% of the veterinarians responded. Among the farmers, 81% used DCT to some cows, 3% used DCT to all cows, and 16% did not use DCT at all. Almost all veterinarians prescribed DCT, most only to some cows in a herd while 8% sometimes recommended DCT to all cows in a herd. Most of the farmers did not use ITS and half of the veterinarians never prescribed ITS. Milking system and milk production, and post-graduate training and number of mastitis cases per month were associated with several of the answers by the farmers and veterinarians, respectively. Overall, many farmers and veterinarians followed the recommendations, but it was also clear that more communication is needed as well as an up-date of the recommendations.

Abstract

Dry-cow therapy with antibiotics (DCT) and treatment with internal teat sealants (ITS) are often used to control mastitis in dairy cows. However, the knowledge on farmer and veterinary compliance with recommendations for DCT and ITS is scarce. Thus, the main aim was to collect information on farmer routines and veterinary advice for such treatments. Associations with herd and veterinary variables were also studied. Web-based questionnaires including questions on demographics and the use of DCT and ITS were sent to 2472 farmers and 517 veterinarians in Sweden. The answers were summarized descriptively, and associations with demographics were evaluated using univariable regression models. The response rate was 14% for farmers and 25% for veterinarians. Among the farmers, 81% used selective DCT (SDCT), 3% used blanket DCT (BDCT), and 16% did not use DCT. Almost all (93%) veterinarians prescribed DCT and among those most recommended SDCT while 8% recommended BDCT. Eighty-two percent of the farmers did not use ITS and 45% of the veterinarians never prescribed ITS. Milking system and milk production, and post-graduate training and number of mastitis cases per month were associated with the largest numbers of farmer and veterinary answers, respectively. In conclusion, many farmer routines and veterinary advice complied with the recommendations available at the time, but a clear need for more education was also identified. The results also indicated that an up-date of the national recommendations was warranted.

Evaluation of sodium lauryl sulfate for the development of cow-side mastitis screening test

Background and Aim:

Subclinical mastitis (SCM) is an economically important disease for dairy cattle worldwide; therefore, regular screening is imperative to detect SCM at an early stage so as to control it. The study was conducted to compare the test characteristics of sodium lauryl sulfate (SLS) as a test reagent to detect SCM in dairy cows.

Materials and Methods:

First, 106 milk samples of dairy cows were subjected to available indirect screening tests (white side test [WST], surf field mastitis test, Leucocytest, and Immucell) considering somatic cell count (SCC) as gold standard test. Then 273 milk samples were allowed to react with different concentrations of SLS with or without sodium hydroxide (NaOH) and indicators (bromothymol blue [BTB] and bromocresol purple [BCP]).

Results:

SLS with or without NaOH yielded best reaction with the milk samples similar to Leucocytest. It was observed that the reaction of milk samples with SLS added with indicators (BTB and BCP) was easier to visualize than without indicators. SLS 3%+NaOH 1.5% with BTB and SLS 2% with BCP had high sensitivity, specificity, and substantial agreement with SCC. The area under the receiver operating characteristics curve of SLS 2% with BCP and SLS 3%+NaOH 1.5% with BTB was 0.917 and 0.875, respectively.

Conclusion:

It may be concluded that SLS 3%+NaOH 1.5% with BTB and SLS 2% with BCP may be the potential reagents for the development of an effective cow-side test to detect SCM, as the main ingredient SLS is considerably cheap and readily available in developing countries.

The Whole and the Parts—A New Perspective on Production Diseases and Economic Sustainability in Dairy Farming

The levels of production diseases (PD) and the cow replacement rate are high in dairy farming. They indicate excessive production demands on the cow and a poor state of animal welfare. This is the subject of increasing public debate. The purpose of this study was to assess the effect of production diseases on the economic sustainability of dairy farms. The contributions of individual culled cows to the farm’s economic performance were calculated, based on milk recording and accounting data from 32 farms in Germany. Cows were identified as ‘profit cows’ when they reached their individual ‘break-even point’. Data from milk recordings (yield and indicators for PD) were used to cluster farms by means of a principal component and a cluster analysis. The analysis revealed five clusters of farms. The average proportion of profit cows was 57.5%, 55.6%, 44.1%, 29.4% and 19.5%. Clusters characterized by a high proportion of cows with metabolic problems and high culling and mortality rates had lower proportions of profit cows, somewhat irrespective of the average milk-yield per cow. Changing the perception of PD from considering it as collateral damage to a threat to the farms’ economic viability might foster change processes to reduce production diseases.

Novel ways to use sensor data to improve mastitis management

Current sensor systems are used to detect cows with clinical mastitis. Although, the systems perform well enough to not negatively affect the adoption of automatic milking systems, the performance is far from perfect. An important advantage of sensor systems is the availability of multiple measurements per day. By clearly defining the need for detection of subclinical mastitis (SCM) and clinical mastitis (CM) from the farmers' management perspective, detection and management of SCM and CM may be improved. Sensor systems may also be used for other aspects of mastitis management. In this paper we have defined 4 mastitis situations that could be managed with the support of sensor systems. Because of differences in the associated management and the epidemiology of these specific mastitis situations, the required demands for performance of the sensor systems do differ. The 4 defined mastitis situations with the requirements of performance are the following: (1) Cows with severe CM needing immediate attention. Sensor systems should have a very high sensitivity (>95% and preferably close to 100%) and specificity (>99%) within a narrow time window (maximum 12 h) to ensure that close to all cows with true cases of severe CM are detected quickly. Although never studied, it is expected that because of the effects of severe CM, such a high detection performance is feasible. (2) Cows with mastitis that do not need immediate attention. Although these cows have a risk of progressing into severe CM or chronic mastitis, they should get the chance to cure spontaneously under close monitoring. Sensor alerts should have a reasonable sensitivity (>80%) and a high specificity (>99.5%). The time window may be around 7 d. (3) Cows needing attention at drying off. For selective dry cow treatment, the absence or presence of an intramammary infection at dry-off needs to be known. To avoid both false-positive and false-negative alerts, sensitivity and specificity can be equally high (>95%). (4) Herd-level udder health. By combining sensor readings from all cows in the herd, novel herd-level key performance indicators can be developed to monitor udder health status and development over time and raise alerts at significant deviances from predefined thresholds; sensitivity should be reasonably high, >80%, and because of the costs for further analysis of false-positive alerts, the specificity should be >99%. The development and validation of sensor-based algorithms specifically for these 4 mastitis situations will encourage situation-specific farmer interventions and operational udder health management.

Evaluation of 4 predictive algorithms for intramammary infection status in late-lactation cows

The objective of this observational study was to compare 4 cow-level algorithms to predict cow-level intramammary infection (IMI) status (culture and MALDI-TOF) in late-lactation US dairy cows using standard measures of test performance. Secondary objectives were to estimate the likely effect of each algorithm, if used to guide selective dry cow therapy (SDCT), on dry cow antibiotic use in US dairy herds, and to investigate the importance of including clinical mastitis criteria in algorithm-guided SDCT. Cows (n = 1,594) from 56 US dairy herds were recruited as part of a previously published cross-sectional study of bedding management and IMI in late-lactation cows. Each herd was visited twice for sampling. At each farm visit, aseptic quarter-milk samples were collected from 20 cows approaching dry-off (>180 d pregnant), which were cultured using standard bacteriological methods and MALDI-TOF for identification of isolates. Quarter-level culture results were used to establish cow-level IMI status, which was considered the reference test in this study. Clinical mastitis records and Dairy Herd Improvement Association test-day somatic cell count data were extracted from herd records and used to perform cow-level risk assessments (low vs. high risk) using 4 algorithms that have been proposed for SDCT in New Zealand, the Netherlands, United Kingdom, and the United States. Agreement between aerobic culture (reference test; IMI vs. no-IMI) and algorithm status (high vs. low risk) was described using Cohen's kappa, test sensitivity, specificity, negative predictive value, and positive predictive value. The proportion of cows classified as high risk among the 4 algorithms ranged from 0.31 to 0.63, indicating that these approaches to SDCT could reduce antibiotic use at dry-off by 37 to 69% in the average US herd. All algorithms had poor agreement with IMI status, with kappa values ranging from 0.05 to 0.13. Sensitivity varied by pathogen, with higher values observed when detecting IMI caused by Streptococcus uberis, Streptococcus dysgalactiae, Staphylococcus aureus, and Lactococcus lactis. Negative predictive values were high for major pathogens among all algorithms (≥0.87), which may explain why algorithm-guided SDCT programs have been successfully implemented in field trials, despite poor agreement with overall IMI status. Removal of clinical mastitis criteria for each algorithm had little effect on the algorithm classification of cows, indicating that algorithms based on SCC alone may have similar performance to those based on SCC and clinical mastitis criteria. We recommend that producers implementing algorithm-guided SDCT use algorithm criteria that matches their relative aspirations for reducing antibiotic use (high specificity, positive predictive value) or minimizing untreated IMI at dry-off (high sensitivity, negative predictive value).

Detecting intramammary infection at the end of lactation in dairy cows

To reduce antimicrobial use, infusion of antimicrobials into only infected cows at the end of lactation (selective dry cow therapy) is preferable to infusion of every cow with antimicrobials. Use of selective dry cow antimicrobial therapy requires differentiation of probably infected from uninfected cows to enable treatment allocation. Milk somatic cell count (SCC) has been used to distinguish between cows with and without intramammary infection (IMI). However, SCC may be influenced by milk yield, stage of lactation, breed, and herd-level variables such as prevalence of infection. Cut points for SCC, to distinguish between cows with and without an IMI, may need to differ between cow age groups and breeds, or among herds. This study evaluated associations between SCC and major pathogen IMI in one or more quarters of 2,606 cows from 36 herds in 4 regions of New Zealand. In the last week of lactation, cows selected at random had milk samples collected from each quarter, and the teat-end condition and hygiene of the udder were scored. Herd- and cow-level data including age, breed, milk volume, and SCC at each production were recorded, and bulk tank milk SCC and volume of milk shipped were collated. At cow level, the association between average, maximum, and last cow-composite SCC, and presence of a major pathogen IMI in one or more quarters of cows, was examined using receiver operator curves. Predictive logistic regression models were then developed that included potential effect modifiers such as age, milk yield, and bulk tank milk SCC. The population average prevalence of major pathogen IMI was 7.2% of cows (95% confidence interval = 5.9-8.6), and this varied significantly between herds. The average, maximum, and last cow-composite SCC of lactation were all predictive of presence of a major pathogen IMI and did not differ in their ability to discriminate infected from uninfected cows. However, the optimal cut points for the last SCC, the maximum SCC, and average SCC were 108, 152, and 105 × 1,000 cells/mL, respectively. Inclusion of age, bulk tank SCC, and history of clinical mastitis improved overall model fit. However, inclusion of these variables did not improve the discriminatory power of maximum cow-composite SCC used alone. We conclude that cow-composite SCC on its own resulted in sensitivities and specificities of between 0.76 and 0.86, and 0.71 to 0.80, respectively, for determination of presence of major pattern IMI, and the predictive value was not improved by addition of other predictor variables.

Postcalving udder health and productivity in cows approaching dry-off with intramammary infections caused by non-aureus Staphylococcus, Aerococcus, Enterococcus, Lactococcus, and Streptococcus species

The objective of this prospective cohort study was to explore associations between intramammary infection (IMI) in late-lactation cows and postcalving udder health and productivity. Cows (n = 2,763) from 74 US dairy herds were recruited as part of a previously published cross-sectional study of bedding management and IMI in late-lactation cows. Each herd was visited twice for sampling. At each visit, aseptic quarter milk samples were collected from 20 cows approaching dry-off (>180 d pregnant), which were cultured using standard bacteriological methods and MALDI-TOF for identification of isolates. Quarter-level culture results were used to establish cow-level IMI status at enrollment. Cows were followed from enrollment until 120 d in milk (DIM) in the subsequent lactation. Herd records were used to establish whether subjects experienced clinical mastitis or removal from the herd, and DHIA test-day data were used to record subclinical mastitis events (somatic cell count >200,000 cells/mL) and milk yield (kg/d) during the follow-up period. Cox regression and generalized estimating equations were used to evaluate the associations between IMI and the outcome of interest. The presence of late-lactation IMI caused by major pathogens was positively associated with postcalving clinical mastitis [hazard ratio = 1.5, 95% confidence interval (CI): 1.2, 2.0] and subclinical mastitis (risk ratio = 1.5, 95% CI: 1.3, 1.9). Species within the non-aureus Staphylococcus (NAS) group varied in their associations with postcalving udder health, with some species being associated with increases in clinical and subclinical mastitis in the subsequent lactation. Late-lactation IMI caused by Streptococcus and Streptococcus (Strep)-like organisms, other than Aerococcus spp. (i.e., Enterococcus, Lactococcus, and Streptococcus spp.) were associated with increases in postcalving clinical and subclinical mastitis. Test-day milk yield from 1 to 120 DIM was lower (-0.9 kg, 95% CI: -1.6, -0.3) in late-lactation cows with any IMI compared with cows without IMI. No associations were detected between IMI in late lactation and risk for postcalving removal from the herd within the first 120 DIM. Effect estimates reported in this study may be less than the underlying quarter-level effect size for IMI at dry-off and postcalving clinical and subclinical mastitis, because of the use of late-lactation IMI as a proxy for IMI at dry-off and the use of cow-level exposure and outcome measurements. Furthermore, the large number of models run in this study (n = 94) increases the chance of identifying chance associations. Therefore, confirmatory studies should be conducted. We conclude that IMI in late lactation may increase risk of clinical and subclinical mastitis in the subsequent lactation. The relationship between IMI and postcalving health and productivity is likely to vary among pathogens, with Staphylococcus aureus, Streptococcus spp., Enterococcus spp., and Lactococcus spp. being the most important pathogens identified in the current study.

Dry cow therapy and early lactation udder health problems-Associations and risk factors

Mastitis remains the most expensive disease of dairy cows, and antibiotic dry cow therapy (DCT) at dry-off is an important part of mastitis control. Regardless of the infection status, blanket DCT is administered to all quarters of all cows, which is controversial due to the worldwide problem of antimicrobial resistance. Even though selective DCT of only infected cows is a more sustainable approach, choosing animals for treatment is not always straightforward. Our aim was to evaluate whether the herd-level DCT approach is associated with early lactation udder health problems, taking into account the cow characteristics. The information source was 2015-2017 Dairy Herd Improvement data with 7461 multiparous cows from 241 Finnish dairy herds. Information on the herd-level DCT approach was obtained from farmers' questionnaire responses in 2017, and the three different approaches were selective DCT, blanket DCT, and no DCT. The statistical tool for the data analysis was a generalized linear mixed model with a random herd effect for binary outcomes and a linear mixed model with a random herd effect for a continuous outcome. The two binary outcomes were the odds of having high milk somatic cell count (SCC ≥ 200 000 cells/mL) on the first test-day within 5-45 days in milk (DIM) and the odds of mastitis treatment in early lactation up to 45 DIM. The third outcome was the mean milk lnSCC (× 1000 cells/mL) within 120 DIM. Selective DCT was the prevailing treatment practice in our data. Blanket DCT was associated with lower SCC after calving. Cows more likely to have high SCC after calving were older cows, cows with high average SCC during the previous lactation, and cows with high milk yield near dry-off. A mastitis treatment in the early lactation was more likely if, during the previous lactation, the cow had high average SCC, high peak milk production, or high milk yield near dry-off. Our findings indicate that DCT is still effective in mastitis control. Cows with high milk yield, especially near dry-off, and cows with persistently high SCC require attention when considering next lactation udder health.

Rumen and Hindgut Bacteria Are Potential Indicators for Mastitis of Mid-Lactating Holstein Dairy Cows

Mastitis is one of the major problems for the productivity of dairy cows and its classifications have usually been based on milk somatic cell counts (SCCs). In this study, we investigated the differences in milk production, rumen fermentation parameters, and diversity and composition of rumen and hindgut bacteria in cows with similar SCCs with the aim to identify whether they can be potential microbial biomarkers to improve the diagnostics of mastitis. A total of 20 dairy cows with SCCs over 500 × 10³ cells/mL in milk but without clinical symptoms of mastitis were selected in this study. Random forest modeling revealed that Erysipelotrichaceae UCG 004 and the [Eubacterium] xylanophilum group in the rumen, as well as the Family XIII AD3011 group and Bacteroides in the hindgut, were the most influential candidates as key bacterial markers for differentiating "true" mastitis from cows with high SCCs. Mastitis statuses of 334 dairy cows were evaluated, and 96 in 101 cows with high SCCs were defined as healthy rather than mastitis according to the rumen bacteria. Our findings suggested that bacteria in the rumen and hindgut can be a new approach and provide an opportunity to reduce common errors in the detection of mastitis.

Evaluation of the new differential somatic cell count parameter as a rapid and inexpensive supplementary tool for udder health management through regular milk recording

Mastitis, particularly in its subclinical form, is the costliest disease in milk production causing substantial financial losses to the dairy industry, impairing animal welfare, and one of the main reasons for treating dairy cows with antimicrobials. Somatic cell count (SCC) is broadly used as an indicator for mastitis or intramammary infection (IMI) and is the basis for udder health management programmes, e.g., through monthly dairy herd improvement (DHI) testing. While SCC shows the total number of cells in milk, the new Differential SCC (DSCC) shows also the combined proportion of polymorphonuclear neutrophils (PMN) and lymphocytes as a percentage of the total SCC. In this study, we investigated the test characteristics of DSCC as a new supplementary indicator for mastitis screening. We collaborated with 11 herds totalling 969 dairy cows and collected metered DHI samples once a month over four months. The IMI status was assessed through analysis of aseptic composite hand-stripped samples using culture and followed by species identification using MALDI-ToF. The pathogens detected were categorised as 'no', 'minor', 'major', or 'other' pathogens. The results of our study showed that the DSCC parameter was significantly associated with the IMI status and the cow's parity but not with days in milk or test-day milk weight. On the other hand, SCC was associated with all these four factors. DSCC counts were significantly higher in samples of cows with IMI caused by major pathogens as compared to cows with no IMI or IMI by minor or other pathogens. SCC alone, DSCC alone, and the combination of DSCC and SCC were further compared based on test characteristics using exemplary cut-offs. For example, working with a cut-off of 200,000 cells/ for SCC alone compared to working with the combination of DSCC of 65 % and/or 200,000 cells/mL to classify cows as infected by major pathogens, the sensitivity increased from 78 % to 92 % and the specificity decreased from 87 % to 66 %. With the combination, the positive predictive value changed from 52 % to 34 %, and the negative predictive value stayed at the same level (96 % vs 98 %). In summary, our study provides first insights on test characteristics of the DSCC parameter used in combination with the well-established SCC for monitoring udder health using DHI testing. This combination opens up the possibility to further improve udder health monitoring programmes (e.g., improved identification of IMI caused by major pathogens) but more work on the subject is needed.

MicroRNA Milk Exosomes: From Cellular Regulator to Genomic Marker

Recent advances in ruminants' milk-derived exosomes (EXO) have indicated a role of microRNAs (miRNAs) in cell-to-cell communication in dairy ruminants. The miRNAs EXO retain peculiar mechanisms of uptake from recipient cells, which enables the selective delivery of cargos, with a specific regulation of target genes. Although many studies have been published on the miRNAs contained in milk, less information is available on the role of miRNAs EXO, which are considered stable over time and resistant to digestion and milk processing. Several miRNAs EXO have been implicated in the cellular signaling pathway, as in the regulation of immune response. Moreover, they exert epigenetic control, as extenuating the expression of DNA methyltransferase 1. However, the study of miRNAs EXO is still challenging due to the difficulty of isolating EXO. In fact, there are not agreed protocols, and different methods, often time-consuming, are used, making it difficult to routinely process a large number of samples. The regulation of cell functions in mammary glands by miRNAs EXO, and their applications as genomic markers in livestock, is presented.

Randomized controlled non-inferiority trial investigating the effect of 2 selective dry-cow therapy protocols on antibiotic use at dry-off and dry period intramammary infection dynamics

Selective dry-cow therapy (SDCT) could be used to reduce antibiotic use on commercial dairy farms in the United States but is not yet widely adopted, possibly due to concerns about the potential for negative effects on cow health. The objective of this study was to compare culture- and algorithm-guided SDCT programs with blanket dry-cow therapy (BDCT) in a multi-site, randomized, natural exposure, non-inferiority trial for the following quarter-level outcomes: antibiotic use at dry-off, dry period intramammary infection (IMI) cure risk, dry period new IMI risk, and IMI risk at 1 to 13 d in milk (DIM). Two days before planned dry-off, cows in each of 7 herds were randomly allocated to BDCT, culture-guided SDCT (cult-SDCT), or algorithm-guided SDCT (alg-SDCT). At dry-off, BDCT cows received an intramammary antibiotic (500 mg of ceftiofur hydrochloride) in all 4 quarters. Antibiotic treatments were selectively allocated to quarters of cult-SDCT cows by treating only quarters from which aseptically collected milk samples tested positive on the Minnesota Easy 4Cast plate (University of Minnesota, St. Paul, MN) after 30 to 40 h of incubation. For alg-SDCT cows, antibiotic treatments were selectively allocated at the cow level, with all quarters receiving antibiotic treatment if the cow had either a Dairy Herd Improvement Association test somatic cell count >200,000 cells/mL during the current lactation or 2 or more clinical mastitis cases during the current lactation. All quarters of all cows were treated with an internal teat sealant. Intramammary infection status at enrollment and at 1 to 13 DIM was determined using standard bacteriological methods. The effect of treatment group on dry period IMI cure, dry period new IMI, and IMI risk at 1 to 13 DIM was determined using generalized linear mixed models (logistic), with marginal standardization to derive risk difference (RD) estimates. Quarter-level antibiotic use at dry-off for each group was BDCT (100%), cult-SDCT (45%), and alg-SDCT (45%). The crude dry period IMI cure risk for all quarters was 87.5% (818/935), the crude dry period new IMI risk was 20.1% (764/3,794), and the prevalence of IMI at 1 to 13 DIM was 23% (961/4,173). Non-inferiority analysis indicated that culture- and algorithm-guided SDCT approaches performed at least as well as BDCT for dry period IMI cure risk. In addition, the final models indicated that the risks for each of the 3 IMI measures were similar between all 3 treatment groups (i.e., RD estimates and 95% confidence intervals all close to 0). These findings indicate that under the conditions of this trial, culture- and algorithm-guided SDCT can substantially reduce antibiotic use at dry-off without negatively affecting IMI dynamics.

Evaluation of rapid culture, a predictive algorithm, esterase somatic cell count and lactate dehydrogenase to detect intramammary infection in quarters of dairy cows at dry-off

Our objective was to compare four tests to standard milk culture followed by MALDI-ToF in quarters of cows at dry-off. Cows (n = 432) were randomly selected from seven U.S. dairy herds already participating in a multi-site clinical trial in summer 2018. Aseptic foremilk samples were collected from quarters (n = 1728) two days prior to dry-off, and subjected to index and reference tests. The four index tests included rapid culture, a predictive algorithm, an esterase strip test measuring somatic cell count (SCC) and a cow-side lactate dehydrogenase (LDH) test. Rapid culture was performed by inoculating quarter milk samples onto a commercial rapid culture plate. Plates were evaluated by technicians after 30-40 h of incubation at 37 ± 2 °C. Quarters were classified as infected if any bacterial growth was observed. For the algorithm test method, all quarters were classified as infected if the cow met any of the following criteria: 1) any Dairy Herd Improvement Association (DHIA) test with a SCC > 200,000 cells / ml during the current lactation or 2) two or more clinical mastitis cases during the current lactation. Esterase-SCC and cow-side LDH tests involved adding milk to the test strip and reading for color changes. For esterase-SCC and cow-side LDH tests, low (≥250 cells / ml and ≥100 U / L) and high (≥500 cells / ml and ≥200 U / L) thresholds were used to classify quarters as infected or not. Composite samples (4 × 2 mL quarter-milk samples commingled) were also tested for rapid culture, esterase-SCC and cow-side LDH tests, such that if a composite sample was positive, then all quarters contributing to that sample were classified as infected. The reference test was traditional aerobic culture conducted in an accredited laboratory using MALDI-ToF for identification of isolates. Traditional culture was only conducted on quarter-milk samples, and consequently, IMI was always considered at the quarter-level. Unconditional logistic regression was used to estimate sensitivity (SE), specificity (SP), apparent prevalence, positive predictive values (PPV) and negative predictive values (NPV) for each index test. Cohen's Kappa (κ) was used to measure agreement between tests. Algorithm, esterase-SCC and cow-side LDH tests had poor agreement with the reference test (κ ranging from 0.01 to 0.12), while rapid culture had fair agreement (κ = 0.28). No test had concurrently high SE and SP. Negative predictive values were moderate to high for all tests.

Investigation of differential somatic cell count as a potential new supplementary indicator to somatic cell count for identification of intramammary infection in dairy cows at the end of the lactation period

The objective of this study was to investigate the new differential somatic cell count (DSCC) as a supplementary indicator to SCC for the identification of intramammary infection (IMI) in dairy cows at the end of the lactation period. Different approaches for identification of cows with IMI (i.e. often based on SCC) and targeted antimicrobial treatment of those rather than of all cows have been developed (i.e. selective dry cow treatment). Recently, DSCC representing the proportion of polymorphonuclear neutrophils and lymphocytes, has been introduced as an additional indicator for the presence of IMI. We used the last dairy herd improvement (DHI) samples taken within 42 d prior to dry-off as well as hand-stripped samples collected within 5 days prior to dry-off to measure DSCC and SCC. The bacteriological status was determined using quarter foremilk samples collected close to drying off. In total, 582 cows were dried off during our study but not all of them could be included in the data analysis for different reasons (e.g. incomplete data, samples too old for reliable determination of SCC and DSCC, contamination). Eventually, the final data set comprised of 310 cows of which 64 and 149 were infected with major and minor pathogens, respectively, and 97 were uninfected. The area under receiver-operating characteristics curves (AUC) were calculated to compare the diagnostic abilities of the different parameters. The AUC for identification of IMI by major pathogens when using the combination of DSCC and SCC was 0.64 compared to 0.62 for SCC alone and 0.62 for DSCC alone. The different parameters were further compared based on test characteristics and predictive values. For example, classifying cows as infected based on a cut-off of 200,000 cells/ml for SCC alone and in terms of using DSCC combined with SCC based on either >60% and/or >200,000 cells/ml, the sensitivity changed from 47 to 66% and the specificity from 74 to 54%. At the same time, the negative predictive value changed from 84 to 86% and the positive predictive value from 32 to 27%. Test characteristics and predictive values of the parameters DSCC and SCC were similar using DHI and hand-stripped samples. In conclusion, our study provides first indications on test characteristics and predictive values for the combination of DSCC and SCC. However, more work on this subject and the actual practical application is needed.