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The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. The aims of this study were to estimate the genetic parameters of clinical mastitis (CM) and SCS traits, and to compare the performance of genetic evaluations of CM traits using univariate and bivariate analyses (CM-SCS). Data were edited according to the Udder Health Golden Standard harmonization, and then 6 CM traits and 6 SCS traits were considered, as the result of combining 3 lactation classifications (1, 2, ≥3) and 2 milking periods (early, late). The linear mixed animal models included the ratio of period at risk as a covariate, herd-year of calving, month of calving, and lactation-age as fixed effects, and the permanent environmental effect for traits of ≥3 lactations. Prevalence of CM in early lactation was similar regardless the lactation number (5%–6%), and the estimated heritabilities were 0.01. Prevalences in late lactation ranged from 10% to 24% and heritabilities ranged from 0.03 to 0.05. Estimated heritabilities of SCS ranged from 0.06 to 0.16 with univariate analyses. Somatic cell count (therefore its log-transformation SCS) showed a higher probability of correctly identifying healthy cows than infected cows but there was still up to 36% of healthy cows for which CM was not detected by SCS. Genetic correlations between CM-SCS traits ranged from 0.36 to 0.95, and SCS in lactation 3 and later did not add extra information to SCS in the second lactation for predicting CM. Regarding reliabilities of EBVs for CM traits, bivariate CM-SCS analyses led to substantial increases with respect to the single-trait model for sires (7%–12% more in first lactation and 16%–28% more for second lactation). Sire's rank correlations for CM between univariate and bivariate analyses (0.47–0.92) suggest that discarding sires could be more accurate than selecting candidates for sires of dams. We can conclude that SCS in first lactation could be useful to supplement CM data in first and second lactations to improve udder health genetic evaluation. [ABSTRACT FROM AUTHOR]

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. Selective treatment of clinical mastitis (STCM) potentially reduces antimicrobial use without negative implications on cow's milk production or health. However, this approach comes with additional costs. The aim of this study was to evaluate the net cash impact (NCI) of implementing STCM compared with blanket treatment of clinical mastitis (BTCM) under different diagnostic test turnaround times (24 h, 14 h, and 8 h) using a stochastic partial budget analysis with Monte Carlo simulation. The target population was European commercial dairy herds; therefore, the model inputs were primarily from European sources. Additionally, variables associated with dairy management programs were obtained from USDA sources, worldwide multisite clinical trials, and expert opinion. The output was calculated by subtracting the cost of STCM from the cost of BTCM, and it represented the expected NCI if a herd switched from BTCM to STCM. Depending on the time-to-treatment efficiency and diagnostic test turnaround time, the expected mean NCI, assuming that STCM has no impact on the cow's future health or production, ranged from +€8.7 to +€12.4 per case with 72.4% to 84.8% of the iterations being ≥€0. Moreover, using the numerically favorable health and production effects of STCM reported in the literature, the expected mean NCI ranged from +€44.5 to +€48.1 per case with 93.6% to 95.4% of the iterations being ≥€0. The variables with the greatest contribution to NCI variance were the proportion of gram-positive cases (39.2% of the variance) and days out of the tank for treated cows (22.0%). However, if cows' future health and production were accounted for, culling risk (24.6%), recurrence risk (19.4%), and milk yield (10.6%) would have the greatest contribution to NCI. The sensitivity analysis indicated that farms with high clinical mastitis incidence, low proportion of gram-positive cases, large number of days out of the tank for treated cows, higher milking frequency or using automatic milking systems, not using the highest priced diagnostic tests, and having high antimicrobial treatment costs are the best candidates for STCM. Improving time-to-treatment efficiency, for example by using a rapid diagnostic test, leads to a favorable NCI, whereas high daily milk yield and milk price enhances the NCI in already positive scenarios. Finally, the cash flow entirely depends on cows' future health and milk yield. Overall, the results indicate that STCM is a practice that positively affects the NCI of many herds. [ABSTRACT FROM AUTHOR]

In India, where dairy production leads globally, infrared thermography (IRT) and short milking tube thermography specifically are vital for managing mastitis. Therefore, the present study focuses on thermal imaging of the udder and short milking tube (SMT) of the milking machine during the peak milking process of Sahiwal cows and Murrah buffaloes during winter, summer, rainy and autumn seasons to identify sub-clinical (SCM) and clinical mastitis (CM) cases using the Darvi DTL007 camera. The udder health was assessed using the California Mastitis Test, Somatic Cell Count (SCC) and IRT throughout the year. Log10SCC and thermogram analysis revealed a difference (p < 0.01) between healthy, SCM, and CM cases during different seasons in both breeds. Further results showed an increase (p < 0.01) in SMT thermograms of SCM and CM cases compared to healthy quarters in Sahiwal cows during winter, summer, rainy, and autumn were 4.26 and 7.51, 2.37 and 4.47, 2.20 and 3.64, 2.90 and 4.94 ºC, respectively and for Murrah buffaloes were 3.56 and 5.55, 2.70 and 3.81, 1.72 and 3.10, 3.14 and 4.42ºC, respectively. The highest degree of increase in milking udder skin surface temperature and SMT of SCM and CM cases compared to healthy quarters was observed during the winter and the least during the rainy season. Thus, regardless of the seasons examined in this study, SMT thermograms effectively assessed SCM and CM. [ABSTRACT FROM AUTHOR]

ABSTRACT: Selective treatment of clinical mastitis (STCM) potentially reduces antimicrobial use without negative implications on cow's milk production or health. However, this approach comes with additional costs. The aim of this study was to evaluate the net cash impact (NCI) of implementing STCM compared with blanket treatment of clinical mastitis (BTCM) under different diagnostic test turnaround times (24 h, 14 h, and 8 h) using a stochastic partial budget analysis with Monte Carlo simulation. The target population was European commercial dairy herds; therefore, the model inputs were primarily from European sources. Additionally, variables associated with dairy management programs were obtained from USDA sources, worldwide multisite clinical trials, and expert opinion. The output was calculated by subtracting the cost of STCM from the cost of BTCM, and it represented the expected NCI if a herd switched from BTCM to STCM. Depending on the time-to-treatment efficiency and diagnostic test turnaround time, the expected mean NCI, assuming that STCM has no impact on the cow's future health or production, ranged from +€8.7 to +€12.4 per case with 72.4% to 84.8% of the iterations being ≥€0. Moreover, using the numerically favorable health and production effects of STCM reported in the literature, the expected mean NCI ranged from +€44.5 to +€48.1 per case with 93.6% to 95.4% of the iterations being ≥€0. The variables with the greatest contribution to NCI variance were the proportion of gram-positive cases (39.2% of the variance) and days out of the tank for treated cows (22.0%). However, if cows' future health and production were accounted for, culling risk (24.6%), recurrence risk (19.4%), and milk yield (10.6%) would have the greatest contribution to NCI. The sensitivity analysis indicated that farms with high clinical mastitis incidence, low proportion of gram-positive cases, large number of days out of the tank for treated cows, higher milking frequency or using automatic milking systems, not using the highest priced diagnostic tests, and having high antimicrobial treatment costs are the best candidates for STCM. Improving time-to-treatment efficiency, for example by using a rapid diagnostic test, leads to a favorable NCI, whereas high daily milk yield and milk price enhances the NCI in already positive scenarios. Finally, the cash flow entirely depends on cows' future health and milk yield. Overall, the results indicate that STCM is a practice that positively affects the NCI of many herds.

ABSTRACT: The aims of this study were to estimate the genetic parameters of clinical mastitis (CM) and SCS traits, and to compare the performance of genetic evaluations of CM traits using univariate and bivariate analyses (CM-SCS). Data were edited according to the Udder Health Golden Standard harmonization, and then 6 CM traits and 6 SCS traits were considered, as the result of combining 3 lactation classifications (1, 2, ≥3) and 2 milking periods (early, late). The linear mixed animal models included the ratio of period at risk as a covariate, herd-year of calving, month of calving, and lactation-age as fixed effects, and the permanent environmental effect for traits of ≥3 lactations. Prevalence of CM in early lactation was similar regardless the lactation number (5%–6%), and the estimated heritabilities were 0.01. Prevalences in late lactation ranged from 10% to 24% and heritabilities ranged from 0.03 to 0.05. Estimated heritabilities of SCS ranged from 0.06 to 0.16 with univariate analyses. Somatic cell count (therefore its log-transformation SCS) showed a higher probability of correctly identifying healthy cows than infected cows but there was still up to 36% of healthy cows for which CM was not detected by SCS. Genetic correlations between CM-SCS traits ranged from 0.36 to 0.95, and SCS in lactation 3 and later did not add extra information to SCS in the second lactation for predicting CM. Regarding reliabilities of EBVs for CM traits, bivariate CM-SCS analyses led to substantial increases with respect to the single-trait model for sires (7%–12% more in first lactation and 16%–28% more for second lactation). Sire's rank correlations for CM between univariate and bivariate analyses (0.47–0.92) suggest that discarding sires could be more accurate than selecting candidates for sires of dams. We can conclude that SCS in first lactation could be useful to supplement CM data in first and second lactations to improve udder health genetic evaluation.

Mastitis remains a major challenge in the dairy sector, causing significant economic losses and impacting animal welfare globally. Early detection of sub-clinical (SCM) and clinical mastitis (CM) is crucial for effective management, particularly in varying environmental conditions. The current study aims at thermal imaging of the udder, teat, and short milking tube (SMT) of the milking machine across milking phases and seasons to assess SCM and CM via infra-red thermography (IRT) in a sub-tropical organised farm of Karnal, India. The udder health status of 98–117 lactating Holstein Friesian crossbred (HFCB) cows was screened monthly using IRT and further accessed using the California Mastitis Test (CMT) and somatic cell count (SCC). The thermal image analysis revealed a difference (p

Background: In China's expanding dairy industry, a lack of oversight regarding antimicrobial use and increasing antimicrobial resistance are evident. Selective treatments of dairy cows for clinical mastitis or dry cow therapy are proposed to promote judicious antimicrobial use without adversely impacting cattle health. These approaches have been successfully implemented on farms in other countries. Methods: On 28 October 2023, a 2-day in-person seminar was held in Beijing, China, on selective antimicrobial treatments of dairy cows for clinical mastitis or dry cow therapy on large Chinese dairy farms. Concurrently, a qualitative study involving 15 technical managers from the 13 largest Chinese dairy groups used focus group discussions and questionnaires to explore perspectives on selective treatments of dairy cows for clinical mastitis or dry cow therapy. The main outcomes assessed were opinions and concerns regarding implementing selective antimicrobial treatments. Results: Although there was diversity of cognition on AMR and selective treatments, the technical managers were generally positive regarding adoption of selective treatments. However, they expressed a need for more evidence and tools, including anticipated economic impacts, effects of delaying treatment until diagnosis, accurate interpretation of milk recording data, safe use of internal teat sealants, and spread of pathogens. Participants stressed the need for awareness, staff training, farm management, and China-specific standards, suggesting large-scale trials to assess efficacy of selective treatments. Conclusion: The findings revealed key challenges and barriers currently impeding selective AMU practices. These insights could inform efforts to promote judicious AMU on farms through targeted treatment regimens, reducing mounting selective pressure driving resistance. [ABSTRACT FROM AUTHOR]

Introduction: Clinical mastitis (CM) treatment decision-making is a multifaceted process that remains relatively understudied, despite CM being one of the most prevalent diseases on dairy farms worldwide, contributing greatly to the use of antimicrobials in the dairy industry. This study aimed to gain insights into decision-making mechanisms employed by dairy farmers in British Columbia and Alberta, Canada, when dealing with CM. Methods: Interviews were held with 15 dairy farmers in the Canadian provinces of British Columbia and Alberta and analyzed using reflexive thematic analysis to develop both the decision-pathway and overarching themes influencing the CM decisions by farmers in this region. Results and discussion: The analysis generated a decision-making process that begins with identification and classification of CM, guided by visual characteristics of milk and the udder, available milk production and quality data, presence of systemic signs, and additional diagnostics. Subsequently, CM cases are assessed based on the likelihood of cure, value of the cow, and herd goals to decide whether antimicrobial treatment is desired. Next, a treatment choice is made by evaluating severity and urgency of the case, availability of drugs and timing of the case. Finally, definition of treatment success and progression over time following the treatment decision guides the termination of treatment. Three overarching themes were generated that shape the decision-making process: 'Personal attributes', including personal approach and experiential knowledge; 'Inter-actor dynamics', such as shared decision-making and dynamics among producers, veterinarians, and milkers; and 'Moving beyond protocols', which highlights the dynamic nature of mastitis decision-making. These insights have the potential to inform the development of effective interventions to improve CM antimicrobial use that align with the reality of farming operations within Western Canada, and potentially beyond. [ABSTRACT FROM AUTHOR]

Bovine mastitis is a common and economically significant disease that affects dairy cows and buffaloes. Staphylococci are considered as a most common cause of bovine mastitis. The present research work was undertaken with the objective to isolate and identify coagulase-negative staphylococci (CoNS) by cultural, biochemical, and molecular methods from bovine mastitic milk samples, and to study their antimicrobial resistance patterns as well as the biofilm-producing ability. The investigation was carried out on 281 bovine clinical mastitis milk samples collected in and around Junagadh. Based on cultural and molecular methods, 34.87% (98/281) samples yielded Staphylococcus isolates. Through the conventional standard tube coagulation test, 16.72% (47/281) isolates were identified as CoNS. Mannitol fermentative patterns revealed 36.17% (17/47) CoNS isolates as fermentative, while 63.82% (30/47) CoNS isolates as non-fermentative. CoNS isolates showed high resistance against penicillin-G (64.95%), followed by erythromycin (57.34%), while the least resistance was observed against oxytetracycline (17.02%). Out of 47 CoNS isolates, 76.59% (36/47) were biofilm producers, while 23.40% (11/47) were non-biofilm producers. [ABSTRACT FROM AUTHOR]

To describe the incidence, aetiology, treatment, and outcomes of farmer-reported clinical mastitis on New Zealand dairy sheep farms. A prospective cohort study was conducted on 20 spring-lambing New Zealand sheep milking farms over the 2022–2023 season. Clinical mastitis was defined as a change in the appearance of milk and/or signs of inflammation in the gland. Farmers were required to report all cases of clinical mastitis and collect information on affected ewes' demographics, clinical features, treatments (where applicable), and outcomes. Milk samples from mastitic glands were submitted for microbiological culture and identification by matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF). Partial or complete clinical mastitis data were available for 236 cases from 221 ewes on 18/20 study farms. Clinical mastitis was diagnosed in 0–6% of ewes at the farm level, with an overall incidence of 1.8 (95% CI = 1.0–3.2)% using the study data, or 2.3 (95% CI = 1.6–3.3)% using the study data and farmer estimates that included unreported cases. Cases occurred mostly in early lactation, with 59% detected during the lambing period (August–October), at a median of 7 (IQR 3, 40) days in milk. The majority of cases featured clots in the milk (59%), swelling (55%), and unevenness (71%) of the glands. Pyrexia (rectal temperature $\ge$ ≥ 40.0°C) was diagnosed in 25% of cases and depression (lethargy, inappetence, or inability to stand) in 26% of cases. Treatment was given to 46% of cases, with tylosin being the most commonly used treatment (50% of treated cases). The most common outcome was immediate drying off to be culled without treatment (32%), followed by still milking and recovered but with lasting problems (25%). Nearly half of all the milk samples submitted were culture negative. Streptococcus uberis (14%), non-aureus staphylococci (12%), and Staphylococcus aureus (11%) were the most common isolates, found on 12, 8 and 8 of the 16 farms with microbiological data, respectively. Clinical mastitis affected up to 6% of ewes at the farm level. Systemic signs were observed in one quarter of affected ewes, suggesting a role for supportive treatment. Clinical mastitis can be severe and challenging to fully resolve in New Zealand dairy sheep. This is the first systematic study of clinical mastitis in New Zealand dairy ewes. It provides baseline information specific to New Zealand conditions for farmers, veterinarians, and other advisors to guide the management of mastitis for the relatively new dairy sheep industry in New Zealand. [ABSTRACT FROM AUTHOR]

Bovine clinical Mastitis (CM) is the most important disease in the dairy industry affecting both animal welfare and farm profitability. Therefore, early and accurate detection of the disease is a valuable timely intervention. In this article, six different machine learning classification algorithms were compared to obtain a prediction model for early detection of the disease. These algorithms are Support Vector Machine, Logistic Regression, Gaussian Naïve Bayes, K-Nearest Neighbor, Classification and Regression Decision Tree, and Random Forest. The algorithms are applied to the milk production of Holstein Friesian cows milked by an automated milking system using the dairy records and disease events. This includes 1493 cows with clinical Mastitis and 2387 healthy cows. The six models were evaluated based on five performance metrics criteria: accuracy, precision, recall, F1-score, and area under the curve (AUC). The accuracy rate ranged from 62% to 74%. The AUC is used to choose the best model. The Decision Tree algorithm and Gaussian Naïve Bayes scored the highest AUC of 71%. However, the Decision Tree algorithm is more stable with respect to other metrics (73% for accuracy and 64% for Precision, Recall, and F1-score). Hence, it can be considered the best predictive CM model with moderate accuracy. Out of the 15 input features, days in milk, age of the animal, lactation order, 305 days mature herd equivalent, and average daily milk yield were the only important features shared in establishing the Decision Tree model. [ABSTRACT FROM AUTHOR]

ABSTRACT Subclinical mastitis is an asymptomatic inflammatory condition that can be difficult to define and diagnose. In the dairy industry, subclinical mastitis is diagnosed by milk somatic cell counts (SCCs) of ≥250,000 cells mL−1. In this pilot study, we assessed the efficacy of this index to identify human subclinical mastitis by comparing SCC levels with the inflammatory response [interleukin-8 (IL-8) levels] in 37 samples from asymptomatic and 10 clinical mastitis (CM) lactating women. The milk microbiota was determined by 16S rRNA gene sequencing. The SCC of CM samples ranged from 310,000 to 6,600,000 cells mL−1. However, 14 of 37 (37.8%) asymptomatic samples had high SCC (250,000–460,000 cells mL−1), indicating subclinical mastitis. SCC levels significantly (P < 0.001) and positively correlated with milk IL-8 levels reflecting the escalating inflammatory response across subclinical and clinical mastitis samples. Samples with an SCC of ≥250,000 cells mL−1 showed significant increases in IL-8 responses when compared with milk samples from healthy women. The milk microbiome of CM samples was dominated by streptococcal and staphylococcal species (89.9% combined median relative abundance). In contrast, the combined median streptococcal/staphylococcal relative levels were 75.4% and 66.3% in milks from asymptomatic (subclinical mastitis) and healthy groups, respectively. The Streptococcus genus was increased in samples with an SCC of ≥250,000, although this should be interpreted with caution. Thus, the index of ≥250,000 somatic cells mL−1 could be a reliable indicator of subclinical mastitis in humans and should aid future studies investigating the impact of subclinical mastitis on maternal health, breastfeeding behaviors, infant health, and development.IMPORTANCEThis pilot study suggests that SCC at a level of (greater than or equal to) 250,000 cells mL−1, as used in the dairy industry, is a suitable index to identify asymptomatic subclinical mastitis in lactating women since it reflects a significant increase in the inflammatory response compared to milk samples from healthy women. Using this index should aid studies into the short- and long-term consequences of subclinical mastitis for mother and infant.

The battle against mastitis remains an enduring challenge in contemporary animal farming. This paper presents the frequency of bacterial pathogens isolated from milk samples collected on 3 farms with a previous history of clinical mastitis in the Mačva region during the year 2022. A total of 77 Simmental cows were enrolled in the study, ranging from the first to sixth lactation and managed in a tie-stall system. The results obtained indicate that the frequency of clinical mastitis in the animals considered was 16.9%. Of a total of 13 pathogenic isolates with clinically present mastitis, Staphylococcus aureus was recorded in 5 (38.4%), Streptococcus uberis in 3 (23.1%), Escherichia coli in 2 (15.4%), Klebsiella pneumoniae in 2 (15.4%), and Streptococcus dysagalactiae in 1 (7.7%). Notably, the largest number of clinical mastitis cases (namely 8, or 61.5%) was recorded during the winter period. Both cases of mastitis caused by K. pneumoniae were detected in the summer, the occurrence of which was implicated in changes in the bedding straw. According to the stage of lactation, the highest frequency of mastitis was found in the early stage of lactation totaling 8 cases (61.5%), followed by 4 (30.8%) in the middle phase of lactation, and only 1 (7.7%) in the late stage of lactation. The causative agents of the Streptococcus genus showed susceptibility to β lactamates in all the cases, whereas all of the E. coli and K. pneumoniae isolates were found resistant to ampicillin, amoxicillin with clavulanic acid.

Non- aureus staphylococci and mammaliicocci (NASM) are the most frequently isolated bacterial group from bovine milk samples. Most studies focus on subclinical mastitis caused by NASM; however, NASM can cause clinical mastitis (CM) as well. We evaluated retrospective data from 6 years (2017–2022) to determine the species and frequency of NASM isolated from quarter bovine CM. The data was comprised of microbiological results from quarter CM samples routinely submitted to Quality Milk Production Services at Cornell University for microbial identification by MALDI-TOF mass spectrometry. A total of 9,909 microbiological results from 410 dairy herds were evaluated. Our results showed that 29 distinct NASM species were identified, with the 8 most prevalent NASM species being Staphylococcus chromogenes, Staphylococcus haemolyticus, Staphylococcus simulans, Staphylococcus epidermidis, Staphylococcus sciuri (now Mammaliicoccus sciuri), Staphylococcus agnetis / Staphylococcus hyicus, Staphylococcus borealis , and Staphylococcus xylosus. The NASM distribution remained similar among seasons, but the frequency of NASM CM cases was higher during the summer. Our results showed different patterns of variations in the isolation frequency over time, depending on the bacterial species: increasing or decreasing trends, cyclic fluctuations, and, except for Staphylococcus borealis , a significant seasonality effect for our study's most prevalent NASM. This study showed that Staphylococcus chromogenes remains the most frequent (43%) NASM species identified from bovine CM, followed by Staphylococcus haemolyticus (18%), and Staphylococcus simulans (12%). [ABSTRACT FROM AUTHOR]

The purpose of this case report is to report a case of clinical mastitis in dairy cattle in Batu. One case was reported on this period. Anamnesis was carried out, the owner revealed that the cow did not produce milk and when milking the udder and nipples felt hard and the milk that wanted to come out seemed to be stuck. Physical examination was carried out, cow’s weight ±400 kg, body temperature 38.4 °C, the udder andnipple were swollen and inflamed, and decrease of milk production, mammae showed reddish and asymmetrical and painful when palpate. Based on the history and physical examination of the cow, it can be concluded that the cow was diagnosed with clinical mastitis with a fausta prognosis and the differential diagnosis was mammary tumour. The therapy given in this case was injection of the antibiotic Interspectin-L® 10 ml, the anti-inflammatory and antipyretic Tolfedine® 10 ml intramuscularly. [ABSTRACT FROM AUTHOR]

The serious drawback underlying the biological annotation of whole-genome sequence data is the p >> n problem, which means that the number of polymorphic variants (p) is much larger than the number of available phenotypic records (n). We propose a way to circumvent the problem by combining a LASSO logistic regression with deep learning to classify cows as susceptible or resistant to mastitis, based on single nucleotide polymorphism (SNP) genotypes. Among several architectures, the one with 204,642 SNPs was selected as the best. This architecture was composed of two layers with, respectively, 7 and 46 units per layer implementing respective drop-out rates of 0.210 and 0.358. The classification of the test data resulted in AUC = 0.750, accuracy = 0.650, sensitivity = 0.600, and specificity = 0.700. Significant SNPs were selected based on the SHapley Additive exPlanation (SHAP). As a final result, one GO term related to the biological process and thirteen GO terms related to molecular function were significantly enriched in the gene set that corresponded to the significant SNPs. Our findings revealed that the optimal approach can correctly predict susceptibility or resistance status for approximately 65% of cows. Genes marked by the most significant SNPs are related to the immune response and protein synthesis. [ABSTRACT FROM AUTHOR]

IntroductionClinical mastitis (CM) treatment decision-making is a multifaceted process that remains relatively understudied, despite CM being one of the most prevalent diseases on dairy farms worldwide, contributing greatly to the use of antimicrobials in the dairy industry. This study aimed to gain insights into decision-making mechanisms employed by dairy farmers in British Columbia and Alberta, Canada, when dealing with CM.MethodsInterviews were held with 15 dairy farmers in the Canadian provinces of British Columbia and Alberta and analyzed using reflexive thematic analysis to develop both the decision-pathway and overarching themes influencing the CM decisions by farmers in this region.Results and discussionThe analysis generated a decision-making process that begins with identification and classification of CM, guided by visual characteristics of milk and the udder, available milk production and quality data, presence of systemic signs, and additional diagnostics. Subsequently, CM cases are assessed based on the likelihood of cure, value of the cow, and herd goals to decide whether antimicrobial treatment is desired. Next, a treatment choice is made by evaluating severity and urgency of the case, availability of drugs and timing of the case. Finally, definition of treatment success and progression over time following the treatment decision guides the termination of treatment. Three overarching themes were generated that shape the decision-making process: ‘Personal attributes’, including personal approach and experiential knowledge; ‘Inter-actor dynamics’, such as shared decision-making and dynamics among producers, veterinarians, and milkers; and ‘Moving beyond protocols’, which highlights the dynamic nature of mastitis decision-making. These insights have the potential to inform the development of effective interventions to improve CM antimicrobial use that align with the reality of farming operations within Western Canada, and potentially beyond.

Comparative effectiveness of veterinary antimastitis drugs in the treatment of subclinical and clinical mastitis of dairy cows was studied. During the experiment, two treatment regimens were used. Cows from the 1st and 3rd experimental groups were treated according to the traditional scheme for this farm - intracisternal administration of Mastiet Forte; for the treatment of cows from the 2nd and 4th experimental groups, Mamikur was administered intracisternally. The effectiveness of therapy was assessed by clinical signs, by the number of somatic cells in milk, response to Kenotest and hematological parameters. It was established that the use of Mamikur as a monotherapy for serous-catarrhal clinical and subclinical mastitis in cows is well tolerated and gives a positive effect when administered intracisternally in the volume of one dosing syringe three times with an interval of 12 hours.

Mycoplasma bovis has recently been identified increasingly in dairy cows causing huge economic losses to the dairy industry. M. bovis is a causative agent for mastitis, pneumonia, endometritis, endocarditis, arthritis, otitis media, and many other clinical symptoms in cattle. However, some infected cows are asymptomatic or may not shed the pathogen for weeks to years. This characteristic of M. bovis, along with the lack of adequate testing and identification methods in many parts of the world until recently, has allowed the M. bovis to be largely undetected despite its increased prevalence in dairy farms. Due to growing levels of antimicrobial resistance among wild-type M. bovis isolates and lack of cell walls in mycoplasmas that enable them to be intrinsically resistant to beta-lactam antibiotics that are widely used in dairy farms, there is no effective treatment for M. bovis mastitis. Similarly, there is no commercially available effective vaccine for M. bovis mastitis. The major constraint to developing effective intervention tools is limited knowledge of the virulence factors and mechanisms of the pathogenesis of M. bovis mastitis. There is lack of quick and reliable diagnostic methods with high specificity and sensitivity for M. bovis. This review is a summary of the current state of knowledge of the virulence factors, pathogenesis, clinical manifestations, diagnosis, and control of M. bovis mastitis in dairy cows. [ABSTRACT FROM AUTHOR]

Simple Summary: The enhanced selection index proposed in the study incorporates new health disorder traits related to udder, claw, and reproduction in addition to the current selection traits. Genetic parameters and breeding values for the traits were evaluated using linear animal models and single-step genomic best linear unbiased prediction (ssGBLUP) methods. The economic weights (EWs) for the new health disorders were calculated using the enhanced bioeconomic model implemented in the computer programme EWDC (i.e., economic weights for dairy cattle), which is versatile and can be applied for various breeds, farm management, and conditions. The use of the enhanced selection index mostly allowed favourable selection progress in terms of the new and current breeding objective traits and could be acceptable for local breeders. The aim of this study was to construct an enhanced selection index using the genomic and economic parameters of new health disorders and current production and functional traits. Genomic evaluation for the incidence of clinical mastitis (CM), three claw disease traits, retained placenta (RET), metritis (MET), and cystic ovaries (CYS) was performed using linear animal models based on producer-recorded data. Good correlations among the health disorders were found, and their heritability estimates did not exceed 7%. Economic weights (EWs) for the health disorders were EUR −132.10 for CM, EUR −128.87 for overall claw diseases, EUR −52.10 for RET, EUR −80.48 for MET, and EUR −16.16 for CYS. These EWs indicate changes in the present value of the annual profit per cow when increasing the incidence of the traits by one case per cow year. Selection using the enhanced index resulted in favourable responses for most of the new health disorders (e.g., −0.001 and −0.006 cases of RET and MET per cow year, respectively), and also in the current breeding objective traits (+49 kg of milk, −0.02% of calf losses). An index contribution of 7% for the new health disorders was assessed as acceptable for the breeders. [ABSTRACT FROM AUTHOR]

Mastitis is a major health problem for bovines and can be categorized as nonsevere or severe, based on clinical symptoms. A severe case of clinical mastitis is usually defined by the cow being affected systemically. It is important to consider how to handle severe cases because these cases can be fatal and cause high production losses. However, there are generally few detailed treatment guidelines. By conducting a scoping review on the topic, we aimed to synthesize the information that is available on treatment and outcomes, as reported from clinical trials and observational studies. This was facilitated by following the PRISMA-guidelines with a stepwise systematic screening of scientific literature on the subject, retrieved via Pubmed and Web of Science, using pre-defined selection criteria. The results yielded a total of 14 reports of treatment and outcomes in cases of naturally occurring severe clinical mastitis. Cross-trial comparison was difficult due to the different exclusion criteria and outcome definitions. Many studies focused on cases caused by gram-negative bacteria treated with intensive antibiotic protocols, often containing antibiotics that are categorized as critical for human health. Few focused on severe cases caused by gram-positive bacteria or on the relative use of non-antibiotic treatment. In general, only a small number of statistically significant differences were found in trials comparing different treatment protocols, with no obvious trends across trials. Our findings emphasize the need for more research into the treatment efficacy of antibiotic and non-antibiotic options for clinically severe mastitis. Furthermore, consideration of how trial conditions relate to the practical circumstances in a field setting could improve the applicability of reported results. This could help to provide practitioners with the information needed to make evidence-based treatment decisions in cases of clinically severe mastitis. [ABSTRACT FROM AUTHOR]

Bovine mastitis, a growing issue in dairy farms, with Klebsiella species being associated with severe mastitis. This study was designed to evaluate the prevalence, biochemical changes, antibiogram susceptibility profile, and biofilm-producing capacity of Klebsiella pneumoniae isolated from Holstein cows with clinical mastitis at a private farm in Alexandria, Egypt. The overall isolation rate of Klebsiella species was 28%, which was further characterized by polymerase chain reaction (PCR) targeting the 16S-23S internal transcribed spacer gene as K. pneumoniae. Clinical mastitis significantly impacted milk composition and blood biochemistry, causing a decline in milk composition, reduction of antioxidant capacity, and increased enzymatic levels compared to normal controls. K. pneumoniae isolates showed 100% resistance to beta-lactam antibiotics, followed by resistance rates of 57, 43 and 43% to chloramphenicol, streptomycin, and sulfamethoxazole--trimethoprim, respectively, while ciprofloxacin and ceftriaxone showed complete susceptibility. The study found that all K. pneumoniae strains expressed the fimA, mrkA, and mrkD fimbrial genes, and the ecpA gene. The study highlights the high prevalence of multidrug-resistant and biofilm-producing K. pneumoniae strains in bovine clinical mastitis, emphasizing the need for improved antimicrobial usage and antibiofilm approaches to overcome the poor treatment response, as well as measuring antioxidant level and enzymatic activity in milk improved milk health screening. [ABSTRACT FROM AUTHOR]

ABSTRACT: The objective of this observational study was to describe variations in partial direct costs of clinical mastitis (CM) treatments among 37 dairy herds using data obtained from herd management records. Animal health and drug purchase records were retrospectively collected from 37 Wisconsin dairy herds for a period of 1 yr. Each farm was visited to verify case definitions, recording accuracy, and detection criteria of CM cases. Descriptive statistics were used to summarize cost of drugs and milk discard. Differences in costs among protocols, intramammary (IMM) products, parities, days in milk, and recurrence were analyzed using ANOVA. Of 20,625 cases of CM, 31% did not receive antimicrobial treatment. The average cost of drugs and milk discard (including cases that were not treated) was $192.36 ± 8.90 (mean ± SE) per case and ranged among farms from $118.13 to $337.25. For CM cases treated only with IMM antimicrobials, milk discard accounted for 87% of total costs and was highly influenced by duration of therapy. Differences in costs were observed among parities, recurrence, and stage of lactation at case detection. Eight different treatment protocols were observed, but 64% of cases were treated using only IMM antimicrobials. Treatment costs varied among protocols; however, cases treated using both IMM and injectable antimicrobials as well as supportive therapy had the greatest costs as they were also treated for the longest duration. Ceftiofur was used for 82% of cases that received IMM antimicrobials while ampicillin was used for 51% of cases treated using injectable antimicrobials. With the exception of ceftiofur and pirlimycin IMM products, many IMM products were given for durations that exceeded the maximum labeled duration. For cases treated using only IMM therapy, as compared with observed costs, we estimated that partial direct costs could be reduced by $65.20 per case if the minimum labeled durations were used. Overall, partial direct costs per case varied among herds, cow factors, and treatment protocols and were highly influenced by the duration of therapy.

Background: In China’s expanding dairy industry, a lack of oversight regarding antimicrobial use and increasing antimicrobial resistance are evident. Selective treatments of dairy cows for clinical mastitis or dry cow therapy are proposed to promote judicious antimicrobial use without adversely impacting cattle health. These approaches have been successfully implemented on farms in other countries. Methods: On 28 October 2023, a 2-day in-person seminar was held in Beijing, China, on selective antimicrobial treatments of dairy cows for clinical mastitis or dry cow therapy on large Chinese dairy farms. Concurrently, a qualitative study involving 15 technical managers from the 13 largest Chinese dairy groups used focus group discussions and questionnaires to explore perspectives on selective treatments of dairy cows for clinical mastitis or dry cow therapy. The main outcomes assessed were opinions and concerns regarding implementing selective antimicrobial treatments. Results: Although there was diversity of cognition on AMR and selective treatments, the technical managers were generally positive regarding adoption of selective treatments. However, they expressed a need for more evidence and tools, including anticipated economic impacts, effects of delaying treatment until diagnosis, accurate interpretation of milk recording data, safe use of internal teat sealants, and spread of pathogens. Participants stressed the need for awareness, staff training, farm management, and China-specific standards, suggesting large-scale trials to assess efficacy of selective treatments. Conclusion: The findings revealed key challenges and barriers currently impeding selective AMU practices. These insights could inform efforts to promote judicious AMU on farms through targeted treatment regimens, reducing mounting selective pressure driving resistance.

Mastitis is one of the main diseases that affects dairy cattle. It is characterized by a multifactorial disease with multiple etiologies including microorganisms such as bacteria, viruses, fungi, yeasts, and algae. Mastitis caused by Mycoplasma spp. results in a contagious nature of infection and has been studied much in Brazil. The objectives of this research were (1) to investigate in clinical mastitis milk samples, by conventional PCR, the presence of the following mycoplasma species: Mycoplasma (M.) bovis, M. bovirhinis, M. bovigenitalium, M. californicum, and M. alkalescens and (2) compare the PCR Mollicutes detection rates using previous concentration and homogenization steps of the milk samples. Of the 993 clinical mastitis milk samples analyzed, 13.7% (136/993) and 8.0% (80/993) were positive for the Mollicutes class after concentration and homogenization, respectively, and all of them were PCR-negative for the five species investigated. Of the 70 expansion milk tanks analyzed, all of them were PCR-negative for the Mollicutes class. The importance of the previous concentration of milk in the routine of molecular analysis was evidenced when compared to the results obtained only with homogenization.

Mastitis is a major health problem for bovines and can be categorized as non-severe or severe, based on clinical symptoms. A severe case of clinical mastitis is usually defined by the cow being affected systemically. It is important to consider how to handle severe cases because these cases can be fatal and cause high production losses. However, there are generally few detailed treatment guidelines. By conducting a scoping review on the topic, we aimed to synthesize the information that is available on treatment and outcomes, as reported from clinical trials and observational studies. This was facilitated by following the PRISMA-guidelines with a stepwise systematic screening of scientific literature on the subject, retrieved via Pubmed and Web of Science, using pre-defined selection criteria. The results yielded a total of 14 reports of treatment and outcomes in cases of naturally occurring severe clinical mastitis. Cross-trial comparison was difficult due to the different exclusion criteria and outcome definitions. Many studies focused on cases caused by gram-negative bacteria treated with intensive antibiotic protocols, often containing antibiotics that are categorized as critical for human health. Few focused on severe cases caused by gram-positive bacteria or on the relative use of non-antibiotic treatment. In general, only a small number of statistically significant differences were found in trials comparing different treatment protocols, with no obvious trends across trials. Our findings emphasize the need for more research into the treatment efficacy of antibiotic and non-antibiotic options for clinically severe mastitis. Furthermore, consideration of how trial conditions relate to the practical circumstances in a field setting could improve the applicability of reported results. This could help to provide practitioners with the information needed to make evidence-based treatment decisions in cases of clinically severe mastitis.

The total milk production of India is 209.96 MT out of which 45% is contributed by the indigenous buffalo and due to their high producing virtue, the prevalence of mastitis is 5–20%. Despite the increasing level of technological advancement, mastitis is still an issue of concern for dairy industry in India as well as across the world. Therefore, the present study aimed to identify the SNPs and associate them with the incidence of clinical mastitis in Murrah buffalo using the ddRAD sequencing approach taking mastitis incidence data of 96 Murrah buffaloes. A total of 246 million quality controlled reads were obtained with an average alignment rate of 99.01% and at a read depth of 10, quality controlled SNPs obtained were 18,056. The logistic regression model was used and a total of seven SNPs were found significantly associated (p < 0.001) with mastitis incidence and seven genes were identified viz., NCBP1, FOXN3, TPK1, XYLT2, CPXM2, HERC1, and OPCML. The majority of them were having tumor suppressing action, related to immunogenetics or glycolytic and energy production. Conclusively, the SNPs identified in this study may be useful for future studies on mastitis incidence in Murrah buffalo and the SNP associations can be further validated. [ABSTRACT FROM AUTHOR]

Simple Summary: The study focused on improving the detection of clinical bovine mastitis, the inflammation of the udder in cows as a response to intramammary infection, which can be identified by the presence of clots in the milk. Currently, automated milking systems do not detect this important disease very accurately. To address this, we developed a clots detection program using a neural network. This neural network was trained to recognize clots in milk samples from dairy cows by using a large number of pictures of milk filter socks, some with and some without clots. These pictures were divided into different sets for training, validating, and testing the program, respectively. The settings of the neural network were optimized using a genetic algorithm. The program's interpretations were explained using a method called integrated gradients. The program was found to be 100% accurate in identifying clots in the test pictures. This suggests that the method could be very useful for automatically checking for clinical mastitis on dairy farms, although further field validation through integration into the existing systems is needed. Automated milking systems (AMSs) already incorporate a variety of milk monitoring and sensing equipment, but the sensitivity, specificity, and positive predictive value of clinical mastitis (CM) detection remain low. A typical symptom of CM is the presence of clots in the milk during fore-stripping. The objective of this study was the development and evaluation of a deep learning model with image recognition capabilities, specifically a convolutional neural network (NN), capable of detecting such clots on pictures of the milk filter socks of the milking system, after the phase in which the first streams of milk have been discarded. In total, 696 pictures were taken with clots and 586 pictures without. These were randomly divided into 60/20/20 training, validation, and testing datasets, respectively, for the training and validation of the NN. A convolutional NN with residual connections was trained, and the hyperparameters were optimized based on the validation dataset using a genetic algorithm. The integrated gradients were calculated to explain the interpretation of the NN. The accuracy of the NN on the testing dataset was 100%. The integrated gradients showed that the NN identified the clots. Further field validation through integration into AMS is necessary, but the proposed deep learning method is very promising for the inline detection of CM on AMS farms. [ABSTRACT FROM AUTHOR]

The objective of this observational study was to describe variations in partial direct costs of clinical mastitis (CM) treatments among 37 dairy herds using data obtained from herd management records. Animal health and drug purchase records were retrospectively collected from 37 Wisconsin dairy herds for a period of 1 yr. Each farm was visited to verify case definitions, recording accuracy, and detection criteria of CM cases. Descriptive statistics were used to summarize cost of drugs and milk discard. Differences in costs among protocols, intramammary (IMM) products, parities, days in milk, and recurrence were analyzed using ANOVA. Of 20,625 cases of CM, 31% did not receive antimicrobial treatment. The average cost of drugs and milk discard (including cases that were not treated) was $192.36 ± 8.90 (mean ± SE) per case and ranged among farms from $118.13 to $337.25. For CM cases treated only with IMM antimicrobials, milk discard accounted for 87% of total costs and was highly influenced by duration of therapy. Differences in costs were observed among parities, recurrence, and stage of lactation at case detection. Eight different treatment protocols were observed, but 64% of cases were treated using only IMM antimicrobials. Treatment costs varied among protocols; however, cases treated using both IMM and injectable antimicrobials as well as supportive therapy had the greatest costs as they were also treated for the longest duration. Ceftiofur was used for 82% of cases that received IMM antimicrobials while ampicillin was used for 51% of cases treated using injectable antimicrobials. With the exception of ceftiofur and pirlimycin IMM products, many IMM products were given for durations that exceeded the maximum labeled duration. For cases treated using only IMM therapy, as compared with observed costs, we estimated that partial direct costs could be reduced by $65.20 per case if the minimum labeled durations were used. Overall, partial direct costs per case varied among herds, cow factors, and treatment protocols and were highly influenced by the duration of therapy. [ABSTRACT FROM AUTHOR]

This study aimed to explore the occurrence and risk factors associated with clinical mastitis within the Hardhenu cattle herd over a span of 14 years (2008–2021). A comprehensive analysis of 1515 lactation records was conducted to ascertain the incidence of clinical mastitis. The investigation determined an overall incidence rate of 26.80% in the studied population. A significant relationship between the year and clinical mastitis incidence was established through Chi‐square analysis (p <.05). Temporal variations in clinical mastitis odds were apparent, with the highest odds (ranging from 0.91 to 1.00) observed during the initial years of 2008–2009 and 2009–2010. Logistic regression revealed that odds values for clinical mastitis incidence were highest in 2008–2009 (1.00), succeeded by 2009–2010 (0.91), 2012–2013 (0.88), 2018–2019 (0.67) and reaching the lowest in 2021–2022 (0.35). Subsequent rankings included 2010–2011 (0.39), 2014–2015 (0.43) and 2019–2020 (0.45). Parity was found to be significantly associated with clinical mastitis occurrence. When compared to Parity 3, both Parity 1 (odds ratio: 1.516, 95% confidence interval: 0.881–2.612) and Parity 2 (odds ratio: 2.626, 95% confidence interval: 1.568–4.398) exhibited higher odds values for clinical mastitis incidence. While the period of calving did not exert a significant influence on clinical mastitis incidence, a heightened occurrence was observed during the rainy season within the targeted population. These findings offer valuable insights into the patterns of incidence, temporal fluctuations, and non‐genetic determinants impacting clinical mastitis within the Hardhenu cattle. The implications of this study can facilitate the development of targeted strategies and management protocols aimed at enhancing udder health and overall productivity in dairy cattle. [ABSTRACT FROM AUTHOR]

ABSTRACT: Treatment of clinical mastitis (CM) and use of antimicrobials for dry cow therapy are responsible for the majority of animal-defined daily doses of antimicrobial use (AMU) on dairy farms. However, advancements made in the last decade have enabled excluding nonsevere CM cases from antimicrobial treatment that have a high probability of cure without antimicrobials (no bacterial causes or gram-negative, excluding Klebsiella spp.) and cases with a low bacteriological cure rate (chronic cases). These advancements include availability of rapid diagnostic tests and improved udder health management practices, which reduced the incidence and infection pressure of contagious CM pathogens. This review informed an evidence-based protocol for selective CM treatment decisions based on a combination of rapid diagnostic test results, review of somatic cell count and CM records, and elucidated consequences in terms of udder health, AMU, and farm economics. Relatively fast identification of the causative agent is the most important factor in selective CM treatment protocols. Many reported studies did not indicate detrimental udder health consequences (e.g., reduced clinical or bacteriological cures, increased somatic cell count, increased culling rate, or increased recurrence of CM later in lactation) after initiating selective CM treatment protocols using on-farm testing. The magnitude of AMU reduction following a selective CM treatment protocol implementation depended on the causal pathogen distribution and protocol characteristics. Uptake of selective treatment of nonsevere CM cases differs across regions and is dependent on management systems and adoption of udder health programs. No economic losses or animal welfare issues are expected when adopting a selective versus blanket CM treatment protocol. Therefore, selective CM treatment of nonsevere cases can be a practical tool to aid AMU reduction on dairy farms.

AbstractThe study was designed to determine the prevalence of bovine mastitis and its associated risk factors under different production systems in rural and peri-urban areas of Borena District, South Wollo Zone, Amhara Region, Ethiopia. A total of 180 households were interviewed using a semi-structured questionnaire concerning the different potential risk factors for mastitis prevalence, and 229 lactating cows were subjected to clinical examination and California Mastitis Test (CMT) screening to determine the prevalence of subclinical mastitis. The prevalence was determined in peri urban and mixed farming systems. The prevalence of mastitis was significantly higher in peri-urban production systems (87.0%) than in rural smallholder production systems (68.6%). The overall prevalence of bovine mastitis determined in the area was 73%, from which the subclinical mastitis accounts 55.5% and remaining 17.5% was clinical mastitis. Out of 916 examined quarters, 5.4% were clinically affected, 1.5% were blind, and 46.1% were CMT positive. In general, the prevalence of mastitis was high, with breed, stage of lactation, parity, and barn hygiene all playing significant roles. To overcome this problem, awareness creation among dairy cow owners on how to keep the udder clean, improving floor conditions through regular cleaning, and medical intervention are needed to improve mastitis prevention and control programs in the study areas.

The present study investigated the presence of CXCR1 gene polymorphisms and their association with clinical mastitis, reproductive disorders and performance traits in Hardhenu cattle. Genotyping of the targeted SNP rs211042414 (C>T) at the g.106216468 loci of the CXCR1 gene was performed through PCR amplification and Bsa1 restriction enzyme digestion. The genotypic frequencies revealed three genotypes: CC, CT and TT, with the C allele being the most prevalent. Significant associations were found between the targeted SNP and clinical mastitis occurrence using chi‐square and logistic regression analyses. The CC genotype showed higher susceptibility to clinical mastitis with a higher odds ratio of 3.47 compared to TT (1.00) and CT (2.90) genotypes (p <.05). Furthermore, least squares analysis revealed significant associations between genotypes and performance traits such as total milk yield, 305‐day milk yield and peak yield (p <.05). The CC genotype exhibited higher milk yields than CT and TT genotypes, indicating a positive association between the C allele and increased milk production. These findings have practical implications for the genetic improvement of Hardhenu cattle. Incorporating the identified CXCR1 gene polymorphisms into existing selection criteria can help enhance disease resistance and milk production traits. However, further validation with a larger sample size is necessary to strengthen the observed associations and ensure their practical applicability. [ABSTRACT FROM AUTHOR]

Introduction: The longevity of cows is crucial to the profitability of a dairy farm, and the culling of cows as a result of major health disorders is a significant risk that threatens production systems today. The possibility of taking diseases into account in the selection of dairy cows depends on the economic importance of the diseases. Mastitis and metritis are common diseases among dairy cows that are considered as risk factors for culling cows. The onset of these disorders can be attributed to factors such as environmental and managerial factors, but there is also evidence of a genetic component to each. Many genes are associated with resistance or susceptibility to mastitis and metritis in cattle, and their alleles have been reported. Subclinical mastitis seems to be one of the most important and damaging diseases threatening dairy cattle herds along with reproductive diseases, lameness and possibly some other common diseases such as Para-tuberculosis. Obviously, reducing production costs supports the profitability of dairy farms. By studying the relationship between the incidence rate and health disorders, in order to minimize the deaths due to health disorders, more emphasis has been placed on the health management of cows. The direct and adverse effects of mammary gland disorders (mastitis and nipple injury) on culling are well documented, while there are differences of results on the correlation between reproductive disorders and culling. Contradictory results may be due to differences in the purpose of the study, population, or the methods used. Many factors such as age, breed, production level, and calving season can play a role in the incidence of diseases. The purpose of this study is to report the prevalence of clinical mastitis and metritis, moreover to investigate environmental and genetic factors affecting these diseases, to estimate the heritability of disease traits and to measure the correlation between disease and production traits in a Holstein cattle herd. Due to the fact that health records are not recorded in the country's farms in a regular and uniform manner, conducting this research is an experiment to collect this type of information so that in the future models can be provided for all Holstein cows in Iran to consider disease relating traits. Material and methods: Data of 5052 milk yield from 1796 Holstein-Frisian cows has been gathered that had parturition from 2005 to 2009. In this study, using the 305-day milk production variables, parity, year of calving, the frequency of occurrence of clinical mastitis and metritis in cattle diseases using SAS software, using logistic procedure is estimated. The cows have been studied for all the diseases that occurred in all milking period. In logistic regression analysis, the effect of 305 days of milk and other factors in the occurrence of the disorder was investigated as a binary model. The effect of the lactation period in which the disorder was created was included in all analyzes and the fixed effects included milk for 305 days, calving period, calving year and calving season. Log [p. (1-p)] = b0 + b1 * milk305 + b2 * parity + b3 * calveyear + b4 * calve season A coefficient of b1 is assigned for the risk factor of milk production, a coefficient of b2 is assigned for the parturition, a coefficient of b3 is assigned for the factor of calving year and a coefficient of b4 is assigned for the factor of calving season. b0 is the logistic regression estimate if there is no predictor other than the response variable in the model. For each estimate of regression coefficients, the probability level, standard error and 95% confidence interval are also calculated. For a particular disease b1, b2, b3 and b4 are regression coefficients. Estimated genetic parameter in this research was heritability of diseases traits that has been done with ASReml software. Results and discussion: Metritis incidence rate is lower than mastitis. The percentage of animals with mastitis and metritisin the herd was 3.11% and 1.67%, respectively. The average calving interval for metritis incidence was 167.3 days and 129.5 days for mastitis. Data analysis of correspondence of metritis and 305 milk yield, parity, the year and the season of calving showed none of the risk factors had relation with the occurrence of clinical mastitis. The heritability of clinical mastitis and metritis were estimated to be 0.27 and 0.23, respectively. We could not find a relationship between milk production and metritis. Can we consider the increase in milk production as a risk factor for disease occurrence? It is very difficult to prove and explain this relationship and there are many contradictions between the results of other studies. From the lack of a proven correlation between milk production and the occurrence of diseases, it can be concluded that if proper management and nutrition provided based on the biological needs of high-yielding cows, then cows with high milk production will not necessarily suffer from diseases in comparison with low-yielding cows. Genetic studies have shown a positive correlation between mastitis and milk production. Erb (1987) and Dohoo and Martin (1984) concluded that high milk production could not be a risk factor for mastitis. A study of Ayrshire cows in Finland found that cows with higher milk production during the previous lactation period were at increased risk for mastitis (Grohn et al. 1989). There are few documented findings on the association between milk production and the incidence of disease. Of course, it should be borne in mind that "milk production" is not the only risk factor for the disease. Concerning diseases in Holstein dairy cattle it seems the occurrence of the disease can also be the result of breeding and nutrition conditions and management. However, identifying all relevant factors and determining their quality and relative importance is difficulty accessible. It is also not easy to estimate all possible interactions between production and disease traits, even with the efficiency of today's computer technology. Conclusion: In dairy cattle genetic improvement programs, we suggest to record and estimate the breeding values for disease traits and consider them in multi-trait selections among elite sires. The estimated heritability of metritis was lower than clinical mastitis. [ABSTRACT FROM AUTHOR]

Mastitis is one of the main diseases that affects dairy cattle. It is characterized by a multifactorial disease with multiple etiologies including microorganisms such as bacteria, viruses, fungi, yeasts, and algae. Mastitis caused by Mycoplasma spp. results in a contagious nature of infection and has been studied much in Brazil. The objectives of this research were (1) to investigate in clinical mastitis milk samples, by conventional PCR, the presence of the following mycoplasma species: Mycoplasma (M.) bovis, M. bovirhinis, M. bovigenitalium, M. californicum, and M. alkalescens and (2) compare the PCR Mollicutes detection rates using previous concentration and homogenization steps of the milk samples. Of the 993 clinical mastitis milk samples analyzed, 13.7% (136/993) and 8.0% (80/993) were positive for the Mollicutes class after concentration and homogenization, respectively, and all of them were PCR-negative for the five species investigated. Of the 70 expansion milk tanks analyzed, all of them were PCR-negative for the Mollicutes class. The importance of the previous concentration of milk in the routine of molecular analysis was evidenced when compared to the results obtained only with homogenization. [ABSTRACT FROM AUTHOR]

The aim of this cross-sectional study was to investigate associated factors of the severity of clinical mastitis (CM). Milk samples of 249 cases of CM were microbiologically examined, of which 27.2% were mild, 38.5% moderate, and 34.3% severe mastitis. The samples were incubated aerobically and anaerobically to investigate the role of aerobic and anaerobic microorganisms. In addition, the pathogen shedding was quantitatively examined, and animal individual data, outside temperature and relative humidity, were collected to determine associated factors for the severity of CM. The pathogen isolated the most was Escherichia coli (35.2%), followed by Streptococcus spp. (16.4%). Non-aureus staphylococci (NaS) (15.4%) and other pathogens (e.g., Staphylococcus aureus, coryneforms) (15.4%) were the pathogens that were isolated the most for mild mastitis. Moderate mastitis was mostly caused by E. coli (38%). E. coli was also the most common pathogen in severe mastitis (50.6%), followed by Streptococcus spp. (16.4%), and Klebsiella spp. (10.3%). Obligate anaerobes (Clostridium spp.) were isolated in one case (0.4%) of moderate mastitis. The mortality rate (deceased or culled due to the mastitis in the following two weeks) was 34.5% for severe mastitis, 21.7% for moderate mastitis, and 4.4% for mild mastitis. The overall mortality rate of CM was 21.1%. The pathogen shedding (back logarithmized) was highest for severe mastitis (55,000 cfu/mL) and E. coli (91,200 cfu/mL). High pathogen shedding, low previous somatic cell count (SCC) before mastitis, high outside temperature, and high humidity were associated with severe courses of mastitis. [ABSTRACT FROM AUTHOR]

Bovine lymphocyte antigen (BoLA) DRB3 locus in healthy and mastitis affected cattle has been genotyped by a polymerase chain reaction and restriction fragment length polymorphisms (PCR-RLFP) using RsaI restriction enzyme, followed by sequencing. In 130 farm animals, 25 BoLA DRB3 alleles have been detected by PCR-RFLP. Three distinct allelic patterns significantly associated with mastitis in Karan Fries crossbred and Sahiwal indicus cattle have been identified, whereas, four other allelic patterns were significantly high in frequency among healthy animals. Sequencing of RFLP genotypes revealed 25 and 47 alleles among healthy Sahiwal and Karan Fries, respectively, while 17 and 38 patterns observed in mastitis affected Sahiwal and Karan Fries animals, respectively. From Tajima's D-test of neutrality, it was concluded that alleles associated with mastitis were expanding in the population, whereas those of healthy were under contraction. Phylogenetic analysis carried out to delineate the evolutionary relationship of the farm and field animals at DRB3 locus, differentiating allelic patterns into six different clusters. Among the phylogenetic lineages, five patterns DRB3*028:01, DRB3*011:03, DRB3*031:01, DRB3*001:01 and DRB3*043:01, were previously reported, whereas one novel allelic variant was observed in indicus and crossbred cattle. This information will help in further exploring the association between BoLA-DRB3 genetic diversity and disease resistance in distinct cattle breeds, important in designing breeding strategies for increasing the distribution of favorable alleles. [ABSTRACT FROM AUTHOR]

Simple Summary: Clinical mastitis (CM) is one of the most prevalent diseases in cows. Anemoside B4, the main active ingredient in P. chinensis, has been shown to reduce the concentration of pro-inflammatory cytokines and is effective in cows with CM. However, the changes in the metabolic profile of cows with CM after treatment with anemoside B4 remain unclear. This study aimed to investigate how anemoside B4 affects the plasma metabolic profile in cows with CM and to provide a theoretical basis for its effects in veterinary practice. Anemoside B4 has a good curative effect on cows with CM; however, its impact on their metabolic profiles is unclear. Based on similar somatic cell counts and clinical symptoms, nine healthy dairy cows and nine cows with CM were selected, respectively. Blood samples were collected from cows with mastitis on the day of diagnosis. Cows with mastitis were injected with anemoside B4 (0.05 mL/kg, once daily) for three consecutive days, and healthy cows were injected with the same volume of normal saline. Subsequently, blood samples were collected. The plasma metabolic profiles were analyzed using untargeted mass spectrometry, and the concentrations of interleukin (IL)-1β, IL-6, and tumor necrosis factor-α (TNF-α) in serum were evaluated via ELISA. The cows with CM showed increased concentrations of IL-1β, IL-6, and TNF-α (p < 0.05). After treatment with anemoside B4, the concentrations of IL-1β, IL-6, and TNF-α were significantly decreased (p < 0.01). Untargeted metabolomics analysis showed that choline, glycocholic acid, PC (18:0/18:1), 20-HETE, PGF3α, and oleic acid were upregulated in cows with CM. After treatment with anemoside B4, the concentrations of PC (16:0/16:0), PC (18:0/18:1), linoleic acid, eicosapentaenoic acid, phosphorylcholine, and glycerophosphocholine were downregulated, while the LysoPC (14:0), LysoPC (18:0), LysoPC (18:1), and cis-9-palmitoleic acid were upregulated. This study indicated that anemoside B4 alleviated the inflammatory response in cows with CM mainly by regulating lipid metabolism. [ABSTRACT FROM AUTHOR]

ABSTRACT: Treatment of clinical mastitis (CM) contributes to antimicrobial use on dairy farms. Selective treatment of CM based on bacterial diagnosis can reduce antimicrobial use, as not all cases of CM will benefit from antimicrobial treatment, e.g., mild and moderate gram-negative infections. However, impacts of selective CM treatment on udder health and culling are not fully understood. A systematic search identified 13 studies that compared selective versus blanket CM treatment protocols. Reported outcomes were synthesized with random-effects models and presented as risk ratios or mean differences. Selective CM treatment protocol was not inferior to blanket CM treatment protocol for the outcome bacteriological cure. Noninferiority margins could not be established for the outcomes clinical cure, new intramammary infection, somatic cell count, milk yield, recurrence, or culling. However, no differences were detected between selective and blanket CM treatment protocols using traditional analyses, apart from a not clinically relevant increase in interval from treatment to clinical cure (0.4 d) in the selective group and higher proportion of clinical cure at 14 d in the selective group. The latter occurred in studies co-administering nonsteroidal anti-inflammatories only in the selective group. Bias could not be ruled out in most studies due to suboptimal randomization, although this would likely only affect subjective outcomes such as clinical cure. Hence, findings were supported by a high or moderate certainty of evidence for all outcome measures except clinical cure. In conclusion, this review supported the assertion that a selective CM treatment protocol can be adopted without adversely influencing bacteriological and clinical cure, somatic cell count, milk yield, and incidence of recurrence or culling.

Abstract Background Bovine mastitis continues to remain as the most challenging disease in dairy cattle, as a result improvement of selection methods has great economic relevance while a deeper understanding of the genetic mechanisms regulating milk production traits and mastitis is of general scientific interest. Objectives This study aimed to evaluate the association of SNPs of the LAP3 and SIRT1 genes with estimated breeding values (EBVs) of milk production traits and clinical mastitis in dairy cattle of Indian origin. Methods DNA samples from 263 animals (Sahiwal and Karan Fries cattle) were genotyped by PCR‐RFLP to assess their pattern of genetic variation. EBVs of milk production traits and phenotypic records of incidences of clinical mastitis were used for association analysis. Results A total of 9 SNPs were identified, including three (rs110932626: A>G, rs716493845: C>T and rs43702363: C>T) in intron 12, four (g.24904G>C, rs110839532: G>T, rs43702361: T>C and rs41255599: C>T) in exon 13 and within 3’UTR of LAP3 gene and two (rs110250233: G>A and rs42140046: C>G) in the promoter region of SIRT1 gene. Eight of these identified SNPs were chosen for subsequent genotyping and association analyses. Association analysis revealed that SNP rs41255599: C>T was significantly associated with lactation milk yield, 305‐day milk yield, 305‐day fat yield, 305‐day solid not fat yield, lactation length and incidence of clinical mastitis (p G and rs43702363: C>T showed significant association with 305‐day milk yield. Conclusion Overall, these findings provide evidence for association of the LAP3 gene with milk production traits and clinical mastitis in dairy cattle, indicating the potential role of LAP3 variants in these traits.

Treatment of clinical mastitis (CM) and use of antimicrobials for dry cow therapy are responsible for the majority of animal-defined daily doses of antimicrobial use (AMU) on dairy farms. However, advancements made in the last decade have enabled excluding nonsevere CM cases from antimicrobial treatment that have a high probability of cure without antimicrobials (no bacterial causes or gram-negative, excluding Klebsiella spp.) and cases with a low bacteriological cure rate (chronic cases). These advancements include availability of rapid diagnostic tests and improved udder health management practices, which reduced the incidence and infection pressure of contagious CM pathogens. This review informed an evidence-based protocol for selective CM treatment decisions based on a combination of rapid diagnostic test results, review of somatic cell count and CM records, and elucidated consequences in terms of udder health, AMU, and farm economics. Relatively fast identification of the causative agent is the most important factor in selective CM treatment protocols. Many reported studies did not indicate detrimental udder health consequences (e.g., reduced clinical or bacteriological cures, increased somatic cell count, increased culling rate, or increased recurrence of CM later in lactation) after initiating selective CM treatment protocols using on-farm testing. The magnitude of AMU reduction following a selective CM treatment protocol implementation depended on the causal pathogen distribution and protocol characteristics. Uptake of selective treatment of nonsevere CM cases differs across regions and is dependent on management systems and adoption of udder health programs. No economic losses or animal welfare issues are expected when adopting a selective versus blanket CM treatment protocol. Therefore, selective CM treatment of nonsevere cases can be a practical tool to aid AMU reduction on dairy farms. [ABSTRACT FROM AUTHOR]

In this study, we developed a machine learning framework to detect clinical mastitis (CM) at the current milking (i.e., the same milking) and predict CM at the next milking (i.e., one milking before CM occurrence) at the quarter level. Time series quarter-level milking data were extracted from an automated milking system (AMS). For both CM detection and prediction, the best classification performance was obtained from the decision tree–based ensemble models. Moreover, applying models on a data set containing data from the current milking and past 9 milkings before the current milking showed the best accuracy for detecting CM; modeling with a data set containing data from the current milking and past 7 milkings before the current milking yielded the best results for predicting CM. The models combined with oversampling methods resulted in specificity of 95 and 93% for CM detection and prediction, respectively, with the same sensitivity (82%) for both scenarios; when lowering specificity to 80 to 83%, undersampling techniques facilitated models to increase sensitivity to 95%. We propose a feasible machine learning framework to identify CM in a timely manner using imbalanced data from an AMS, which could provide useful information for farmers to manage the negative effects of CM. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus (S. aureus), the bacteria most frequently associated with mastitis in cattle and buffalo, has a large number of genes connected to antibiotic resistance. The objective of the current research was to determine the erythromycin and macrolide resistance of S. aureus isolated from mastitic milk of cattle and buffalo, particularly resistance-related genes (ermA, ermB, ermC, ermT, and msrA). Therefore, 150 dairy cattle and 135 dairy buffalo bred by small farmers in various governorates of Egypt (Cairo, Giza, Kalyobia, Fayoum, and Kafr El-Sheikh) provided a total of 285 milk samples. Inspection revealed that a total of 34 (22.7%) and 36 (26.7%) milk samples from cattle and buffalo, respectively, had clinical mastitis. With a total recovery of 31 (44.3%) S. aureus isolates. Bacterial isolation and identification of S. aureus verified the isolation and identification of 14 (41.2%) and 17 (47.2%) S. aureus isolates from cattle and buffalo, respectively. Utilizing a TaqMan probe-based real-time PCR method that targets the nuc gene, all S. aureus isolates were verified. In instances of bovine mastitis in India and Kenya, conventional PCR targeting the nuc gene, followed by DNA sequencing and phylogenetic analysis, revealed a high homology (100%) with that of S. aureus strains isolated from milk. For the tested genes, the prevalence of resistant strains was 9.6% (ermA), 64.5% (ermB), 70.9% (ermC), 19.3% (ermT), and 9.6%. (msrA). Therefore, effective control measures should be adopted to stop the spread of drug-resistant S. aureus to humans. [ABSTRACT FROM AUTHOR]

Compost-bedded pack barns (CB) are receiving increasing attention as a housing system that can potentially improve the welfare of dairy cows. This study characterized the frequency and profile of pathogens isolated from clinical (CM) and subclinical (SCM) mastitis in dairy cows housed in CB. It evaluated the association between mastitis occurrence and bedding characteristics in CB systems. Over six months, seven dairy herds were visited monthly for milk and bedding sample collections. Milk samples from mastitis cases were submitted to microbiological identification by matrix-assisted laser desorption ionization-time of flight (MALDI-TOF MS). Bedding samples were submitted to physical-chemical (pH, organic matter, moisture, and carbon to nitrogen ratio) and microbiological counting (total bacterial counts, coliforms, streptococci, and staphylococci) analyses. Regression analysis was used to determine the association between mastitis occurrence and CB characteristics. Our results showed that Escherichia coli and environmental streptococci were the most frequently isolated pathogens from CM cases, while Staphylococcus chromogenes and contagious pathogens (Staphylococcus aureus and Streptococcus agalactiae) were the most commonly isolated from SCM cases. Bedding moisture content was positively associated with the incidence of CM. The bedding carbon to nitrogen ratio was negatively associated with the incidence of SCM, and the bedding total bacteria counts tended to be associated with the incidence of SCM. Bedding counts of coliforms positively associated with the prevalence of SCM. Our results can support decision-makers in the dairy industry seeking strategies for bedding management and mastitis control. [ABSTRACT FROM AUTHOR]

IntroductionStreptococci are the major etiology in mastitis in dairy cattle, a cause of huge economic losses in the dairy industries. This study was aimed to determine the diversity of Streptococcus spp. isolated from clinical mastitis of cattle reared in Bangladesh.MethodsA total of 843 lactating cattle reared in four prominent dairy farms and one dairy community were purposively included in this study where 80 cattle were positive to clinical mastitis (CM) based on gross changes in the udder (redness, swelling, and sensitive udder) and/or milk (flakes and/or clots). Milk samples were collected from all the eighty cattle with clinical mastitis (CCM) and twenty five apparently healthy cattle (AHC). Samples were enriched in Luria Bertani broth (LB) and one hundred microliter of the enrichment culture was spread onto selective media for the isolation of Staphylococcus spp., Streptococcus spp., Enterococcus spp., Escherichia coli and Corynebacterium spp., the major pathogen associated with mastitis. Isolates recovered from culture were further confirmed by species specific PCR.Results and DiscussionOut of 105 samples examined 56.2% (59/105), 17.14% (18/105), 9.52% (10/105) and 22.9% (24/105) samples were positive for Staphylococcus, Streptococcus, Enterococcus faecalis and E. coli, respectively. This study was then directed to the determination of diversity of Streptococcus spp. through the sequencing of 16S rRNA. A total of eighteen of the samples from CCM (22.5%) but none from the AHC were positive for Streptococcus spp. by cultural and molecular examination. Sequencing and phylogenetic analysis of 16S rRNA identified 55.6, 33.3, 5.6 and 5.6% of the Streptococcus isolates as Streptococcus uberis, Streptococcus agalactiae, Streptococcus hyovaginalis and Streptococcus urinalis, respectively. Considering the high prevalence and worldwide increasing trend of S. uberis in mastitis, in-depth molecular characterization of S. uberis was performed through whole genome sequencing. Five of the S. uberis strain isolated in this study were subjected to WGS and on analysis two novel ST types of S. uberis were identified, indicating the presence of at least two different genotypes of S. uberis in the study areas. On virulence profiling, all the isolates harbored at least 35 virulence and putative virulence genes probably associated with intramammary infection (IMI) indicating all the S. uberis isolated in this study are potential mastitis pathogen. Overall findings suggest that Streptococcus encountered in bovine mastitis is diverse and S. uberis might be predominantly associated with CM in the study areas. The S. uberis genome carries an array of putative virulence factors that need to be investigated genotypically and phenotypically to identify a specific trait governing the virulence and fitness of this bacterium. Moreover, the genomic information could be used for the development of new genomic tools for virulence gene profiling of S. uberis.

The aim of this study was to construct an enhanced selection index using the genomic and economic parameters of new health disorders and current production and functional traits. Genomic evaluation for the incidence of clinical mastitis (CM), three claw disease traits, retained placenta (RET), metritis (MET), and cystic ovaries (CYS) was performed using linear animal models based on producer-recorded data. Good correlations among the health disorders were found, and their heritability estimates did not exceed 7%. Economic weights (EWs) for the health disorders were EUR −132.10 for CM, EUR −128.87 for overall claw diseases, EUR −52.10 for RET, EUR −80.48 for MET, and EUR −16.16 for CYS. These EWs indicate changes in the present value of the annual profit per cow when increasing the incidence of the traits by one case per cow year. Selection using the enhanced index resulted in favourable responses for most of the new health disorders (e.g., −0.001 and −0.006 cases of RET and MET per cow year, respectively), and also in the current breeding objective traits (+49 kg of milk, −0.02% of calf losses). An index contribution of 7% for the new health disorders was assessed as acceptable for the breeders.

BackgroundBovine mastitis is one of the most common and prevalent diseases affecting dairy cattle worldwide. It adversely affects the quality and quantity of milk production and leads to a significant economic loss for the farmers.MethodsThis article aimed to estimate the prevalence of clinical mastitis (CM) infection in mainland China using a systematic review and meta-analysis. The research reports published during 1983–2022 in English or Chinese from databases (PubMed, Google Scholar, Cochrane Library, Science Direct, Web of Science, VIP Database for Chinese Technical Periodicals (VIP), Chinese National Knowledge Infrastructure (CNKI), and Wan Fang database) were identified after reviewing the relevant scientific literature. Based on our inclusion criteria, this study analyzed the prevalence of CM in 47 published studies prevalence extracted the total number of cattle infected with CM from the available studies, allowing us to estimate the prevalence of CM infection among these in mainland China.ResultsThe pooled prevalence with the 95% CI for the clinical mastitis was 10% (95% CI: 9.00, 12.00). The majority of CM was associated with lactation, parity, and age, with higher prevalence observed in late lactation 15% (95% CI: 11.00, 18.00) and mid-lactation 10% (95% CI: 6.00, 13.00) in comparison to early lactation 8% (95% CI: 5.00, 10.00). The incidence of CM increased significantly with the increase of parity and age, and the highest incidence rates were 19% (95% CI: 15.00, 23.00) and 16% (95% CI: 12.00, 19.00) at parity and age ≥7, respectively. Among the seasons, the highest prevalence of CM infection was found in autumn 9% (95% CI: 2.00, 17.00). Interestingly, no significant effects were evident regarding the influence of quarter on the prevalence of CM.ConclusionThus, estimating the prevalence of CM among cattle in mainland China. through meta-analysis can provide adequate measures to control CM, reduce economic losses, and prevent the spread and transmission of CM in Chinese herds.