Search Results (72)

Mastitis, an inflammatory disease caused by the invasion of various pathogenic microorganisms into mammary gland tissue, is a core health issue plaguing the global dairy industry. The consequences of this disease are manifold. In addition to directly compromising the health and welfare of dairy cows, it also precipitates a substantial decline in lactation function, a precipitous drop in raw milk production, and alterations in milk composition (e.g., increased somatic cell counts and imbalanced ratios of milk protein to fat). These changes result in a marked degradation of milk quality and safety, and in turn, engender significant economic losses for the livestock industry. Therefore, the establishment and implementation of a comprehensive prevention and control system is a key strategy to effectively curb the occurrence of mastitis, reduce its incidence rate, and minimise economic losses. This review systematically explores the complex etiological factors and pathogenic mechanisms of mastitis in dairy cows, and summarises various diagnostic methods, including milk apparent indicators monitoring, pathogen detection, physiological parameter monitoring, omics technologies, and emerging technologies. Furthermore, it undertakes an analysis of treatment protocols for mastitis in dairy cows, with a particular emphasis on the significance of rational antibiotic use and alternative therapies. Moreover, it delineates preventive measures encompassing both environmental and hygiene management, and dairy cow health management. The objective of this paper is to provide a comprehensive and scientific theoretical basis and practical guidance for dairy farming practices. This will help to improve the health of dairy cows, ensure a stable supply of high-quality dairy products, and promote the sustainable and healthy development of the dairy farming industry. Full article

Bovine mastitis, particularly that caused by Staphylococcus aureus, presents a major challenge to dairy production worldwide due to its economic impact, animal welfare concerns, and zoonotic potential. This narrative review synthesizes current literature on the epidemiology, pathogenesis, resistance patterns, and control strategies related to S. aureus-associated mastitis in dairy cattle. It highlights the pathogen’s virulence mechanisms, such as biofilm formation, immune evasion, and toxin production, that facilitate persistent infections. The review compiles global prevalence data, revealing significant geographic variation and disparities between clinical and subclinical cases. Antimicrobial resistance, especially the emergence of methicillin-resistant S. aureus (MRSA), is extensively examined alongside resistance gene profiles. Diagnostic approaches, including culture, PCR, MALDI-TOF MS, and AI-based systems, are evaluated for their sensitivity and field applicability. Additionally, the review addresses public health implications, zoonotic risks, and One Health perspectives, culminating in an exploration of prevention strategies, including improved hygiene, vaccination, dry cow therapy, and AI-driven herd management. The findings emphasize the urgent need for integrated surveillance, precision diagnostics, and targeted interventions to mitigate the burden of S. aureus mastitis. Full article

Mastitis is a significant challenge in the buffalo industry, affecting both milk production and animal health and resulting in economic losses. This study presents the first fully automated AI-driven thermal imaging system integrated with robotic milking, specifically developed for the real-time, non-invasive monitoring of udder health in Italian Mediterranean buffalo. Unlike traditional approaches, the system leverages the synchronized acquisition of thermal images during milking and compensates for environmental variables through a calibrated weather station. A transformer-based neural network (SegFormer) segments the udder area, enabling the extraction of maximum udder skin surface temperature (USST), which is significantly correlated with somatic cell count (SCC). Initial trials demonstrate the feasibility of this approach in operational farm environments, paving the way for scalable, precision diagnostics of subclinical mastitis. This work represents a critical step toward intelligent, automated systems for early detection and intervention, improving animal welfare and reducing antibiotic use. Full article

The somatic cell count (SCC) and differential somatic cell count (DSCC) are proxies for the udder health of dairy cattle, regarded as the criterion of mastitis identification with healthy, suspicious mastitis, mastitis, and chronic/persistent mastitis. However, SCC and DSCC are tested using flow cytometry, which is expensive and time-consuming, particularly for DSCC analysis. Mid-infrared spectroscopy (MIR) enables qualitative and quantitative analysis of milk constituents with great advantages, being cheap, non-destructive, fast, and high-throughput. The objective of this study is to develop a dairy cattle udder health status diagnostic model of MIR. Data on milk composition, SCC, DSCC, and MIR from 2288 milk samples collected in dairy farms were analyzed using the CombiFoss 7 DC instrument (FOSS, Hilleroed, Denmark). Three MIR spectral preprocessing methods, six modeling algorithms, and three different sets of MIR spectral data were employed in various combinations to develop several diagnostic models for mastitis of dairy cattle. The MIR diagnostic model of effectively identifying the healthy and mastitis cattle was developed using a spectral preprocessing method of difference (DIFF), a modeling algorithm of Random Forest (RF), and 1060 wavenumbers, abbreviated as “DIFF-RF-1060 wavenumbers”, and the AUC reached 1.00 in the training set and 0.80 in the test set. The other MIR diagnostic model of effectively distinguishing mastitis and chronic/persistent mastitis cows was “DIFF-SVM-274 wavenumbers”, with an AUC of 0.87 in the training set and 0.85 in the test set. For more effective use of the model on dairy farms, it is necessary and worthwhile to gather more representative and diverse samples to improve the diagnostic precision and versatility of these models. Full article

Background/Objectives: This review aimed to compare the efficacy of antibiotic treatment vs. non-antibiotic treatment in mild and moderate clinical mastitis in lactating dairy cows, categorized by the causative pathogen. Methods: The initial systematic review plan, which resulted in only four relevant articles, was altered due to limited available studies and significant heterogeneity among them. Consequently, five additional articles, closely meeting our criteria with minor differences, were included to ensure comprehensive analysis, resulting in nine included articles. Due to these pragmatic constraints, this review represents a hybrid between a systematic and a narrative review. The outcome of interest was the bacteriological cure (BC). Results: The findings revealed that antibiotic treatment resulted in improved BC rates for cases caused by Streptococci. For cases caused by Escherichia (E.) coli, antibiotic therapy showed no significant improvement in BC rates compared to non-antibiotic treatment, suggesting that antibiotics may be often unnecessary for these cases due to self-limiting tendencies. However, severe E. coli mastitis warrants systemic antibiotic treatment due to potentially life-threatening complications. Klebsiella spp. mastitis showed better cure rates with antibiotic therapy. Conclusions: This study underscores the importance of regular pathogen diagnostics to guide appropriate treatment, advocating for the use of on-farm rapid tests to reduce unnecessary antibiotic use while ensuring effective treatment outcomes. Full article

In recent decades, Blanket Dry Cow Therapy (BDCT) has been regarded as a cornerstone strategy for the control of mastitis in dairy cows during the dry period. However, concerns regarding the rising incidence of antibiotic resistance and the associated zoonotic risks have prompted a paradigm shift, leading to intensified research into alternative management approaches. In response, many countries have adopted a more targeted approach, known as Selective Dry Cow Therapy (SDCT), which focuses on the therapeutic use of antibiotics, administered only to cows or quarters that are either infected or at high risk of infection during the dry period. This review provides a comprehensive synthesis of the scientific literature regarding the main methods for selecting animals for SDCT, the impact of this strategy on udder health, milk production, farm economics, and antibiotic consumption, as well as the factors that may influence its effectiveness. Over time, a range of methods have been developed to identify infected animals, including bacteriological culture, somatic cell count (SCC), differential somatic cell count (DSCC), and the California Mastitis Test (CMT), which are often used alone or in combination with clinical mastitis history and/or parity. Among these methods, SCC has proven to be the most economically viable and best suited for practical use, while its combination with DSCC has been shown to significantly enhance diagnostic accuracy. According to the studies reviewed, SDCT is a safe and effective strategy for maintaining udder health and farm profitability, as long as infected cows are accurately identified, and internal teat sealants are used in quarters not treated with antibiotics during the dry period. However, since udder health is influenced by herd characteristics, management practices, and regional pathogens, the findings cannot be universally applied and must be adapted to each herd’s specific conditions. Full article

Subclinical mastitis (SM) is the most economically damaging yet often visually undetectable disease of dairy cows. Early detection and treatment can reduce the loss caused by the disease; thus, the continuous improvement of SM diagnostic methods is necessary. Although milk’s somatic cell count (SCC) is commonly measured for diagnostic purposes, its direct determination is not widely used in everyday practice. The primary objective of our work was to investigate whether the predictive value of SM diagnostics can be improved by training artificial neural networks (ANNs) on data generated using typical conventional milking systems. The best ANN classifier had a sensitivity of 0.54 and a specificity of 0.77, which is comparable to performances of various California Mastitis Tests (CMT) found in the literature. Combining two diagnostic tests, ANN and CMT, we concluded that the positive predictive value could be up to 50% higher than the value provided by the individual CMT. While implementing CMT is a labor-intensive process on herd-level, in milking machines where milk properties or milk yield data can be measured automatically, similar to our work, SCC-increase predictions for all individuals could be obtained daily basis. Full article

Background/Objectives: Bovine mastitis remains a challenge for the Irish dairy industry. This study aimed to explore the seasonality and antimicrobial resistance of mastitis pathogens obtained by the regional laboratories (RVL) of the Department of Agriculture, Food and the Marine. Methods: Seasonality of isolation of the most common bacterial species and antimicrobial resistance of those species repeatedly obtained in the same herds in different years were explored using the RVL diagnostic data. Additionally, whole genome sequencing (WGS) was employed to establish the persistency of Staphylococcus aureus strains within the same herd. Results: A clear seasonality was observed in the isolation of Staphylococcus aureus, Streptococcus uberis, and Escherichia coli from milk. Seasonal differences were statistically significant within and between bacterium. Persistence of resistance within herds was highest in S. aureus against penicillin (35.5% of herds) and in S. uberis against pirlimycin (14% of herds), while E. coli did not show persistence of resistance to any antimicrobials. Sequencing of S. aureus isolates revealed that the strains causing mastitis in ten out of twenty-one herds were similar genetically in different years. In seven of these herds, S. aureus was persistently resistant to penicillin. Isolates from two different herds were practically identical and carried the human immune evasion cluster genes (IEC, scn, sak, chp and sea) suggesting a recent human-bovine host switch event. Conclusions: These findings underscore the importance of implementing targeted biosecurity measures and monitoring programs to mitigate the spread of mastitis-causing pathogens and enhance antimicrobial stewardship in the Irish dairy industry, while it also highlights the significance of including a One Health perspective in surveillance programs. Full article

Staphylococcus aureus and Klebsiella pneumoniae are significant and prevalent pathogens associated with bovine mastitis on dairy farms worldwide, resulting in severe infections in both dairy cows and, subsequently, human beings. Fast and dependable pathogen diagnostics are essential to minimize the effects of cow mastitis and human infections. The aim of this research was to develop a duplex recombinase-aided amplification (RAA) combined with the lateral flow dipstick (LFD) method, which was used for rapid, simultaneous detection of S. aureus and K. pneumoniae. The SKII culture medium for S. aureus and K. pneumoniae cocultivation was developed in this study. By optimizing the duplex RAA–LFD reaction conditions in terms of primer concentration, amplification temperature, and reaction time, the duplex RAA–LFD assay could successfully detect S. aureus and K. pneumoniae when the reaction was conducted at 39 °C for 20 min. The duplex RAA–LFD method demonstrated good specificity, exhibiting no cross-reactivity with other pathogens. In addition, the detection limit of the duplex RAA–LFD for S. aureus and K. pneumoniae was 60 fg of genomic DNA and 1.78 × 10³ and 2.46 × 10³ CFU/mL of bacteria in pure culture. Moreover, the duplex RAA–LFD technique is capable of identifying S. aureus and K. pneumoniae in artificially spiked milk samples even at very low initial concentrations of 1.78 × 10¹ and 2.46 × 10⁰ CFU/mL, respectively, after 6 h of enrichment. The result of the actual samples showed that the total concordance rate of the duplex RAA–LFD method with the biochemical identification method and PCR method could reach 92.98~98.25% with high consistency. The results of this study indicated that the duplex RAA–LFD assay, which is a precise, sensitive, and simple field testing technique, can be used to identify S. aureus and K. pneumoniae and is expected to be used for disease diagnosis. Full article

Mastitis is the leading cause of economic losses in dairy farming, significantly impairing animal welfare and the quality and quantity of milk production. MicroRNAs are increasingly gaining attention, in both human and veterinary medicine, as biomarkers for various diseases. This study evaluated the diagnostic potential of four circulating microRNAs (miR-26-5p, miR-142-5p, miR-146a, and miR-223-3p) by examining changes in their expression in milk samples from dairy cows at different immune-cell subpopulations correlated to different stage of mastitis with a validated method. Additionally, this study has analyzed the possible source of these circulating microRNAs by the measurement of their secretion from activated immune cells (lymphocytes, monocytes, and neutrophils). miR-223-3p has been significantly expressed in an acute stage of mastitis (p < 0.01) but not in the chronic or susceptible stages. Conversely, mir-26-5p has been significantly reduced in acute, chronic, and susceptible groups of animals. In immune-cell cultures, miR-26 has been shown to be down-regulated in lipopolysaccharide (LPS)-stimulated neutrophils, while miR-223 has been shown to be up-regulated in phytohemagglutinin (PHA)-stimulated lymphocytes. The differential expression of miR-223-3p and miR-26-5p, combined with differential and total somatic cell count, could serve as a useful tool for identifying the evolutionary stage of mastitis-related inflammatory pathology. Full article

Background/Objectives: Pasteurella multocida commonly colonizes the bovine respiratory tract and can occasionally cause intramammary infections. Here, eight P. multocida isolates from clinical cases of bovine mastitis were investigated for their molecular characteristics as well as phenotypic and genotypic antimicrobial resistance (AMR) properties. Methods: The isolates originated from quarter milk samples obtained in Germany for diagnostic purposes. Antimicrobial susceptibility testing (AST) by broth microdilution was performed according to the Clinical and Laboratory Standards Institute. Closed whole-genome sequences were generated by hybrid assembly of Illumina MiSeq short-reads and Oxford Nanopore MinION long-reads, followed by consecutive sequence analysis. Results: The P. multocida isolates belonged either to capsular:lipopolysaccharide type A:3 (n = 7) or A:6 (n = 1), and multi-locus sequence types 1 (n = 7) or 7 (n = 1). Seven isolates carried AMR genes, such as mef(C), mph(G), strA, strB, aphA1, aadA31, tet(H), tet(Y), floR, catA3, and sul2, as part of an integrative and conjugative element (ICE). These mobile genetic elements, 58,382–78,401 bp in size, were highly similar to the ICEs Tn7406 or Tn7407 that have been previously described in bovine Mannheimia haemolytica and P. multocida, respectively. Moreover, the isolates showed elevated minimal inhibitory concentrations corresponding to the identified AMR determinants. Conclusions: Molecular typing and ICE organization suggest the bovine respiratory tract as reservoir of the investigated mastitis-associated P. multocida. Horizontal cross-genus transfer of multidrug-resistance-mediating ICEs seems to occur under in vivo conditions among different pathogens from cattle in Germany, which underlines the importance of pathogen identification followed by AST for successful bovine mastitis therapy. Full article

Granulomatous mastitis (GM) is a rare, benign, but chronic and recurrent inflammatory breast disease that significantly impacts physical and psychological well-being. It often presents symptoms such as pain, swelling, and discharge, leading to diagnostic confusion with malignancy. The etiology of GM remains unclear, though autoimmune and multifactorial components are suspected. This study aimed to explore the genetic underpinnings of GM using whole-exome sequencing (WES) on 22 GM patients and 52 healthy controls to identify single nucleotide variants (SNVs) and copy number variations (CNVs) potentially linked to the disease. WES analysis revealed novel SNVs in six genes: BRCA2 (rs169547), CFTR (rs4727853), NCF1 (rs10614), PTPN22 (rs2476601), HLA-DRB1 (seven variants), and C3 (rs406514). Notably, most of these variants are associated with immune regulation and inflammatory pathways, supporting the hypothesis that GM is an autoimmune disease. However, all identified variants were classified as benign according to the American College of Medical Genetics and Genomics (ACMG) guidelines, necessitating further investigation into their potential functional effects. Despite conducting CNV analysis, no significant variations were identified. This study represents a foundational step in linking genetic predisposition to GM and highlights the need for integrating genetic, clinical, and functional data to better understand GM’s pathophysiology. Future research should focus on larger cohorts, functional studies, and exploring multifactorial contributors to GM, including hormonal and environmental factors. Full article

This study aimed to investigate the incidence of subclinical mastitis (SCM), the implicated pathogens, and their impact on milk quality in dairy sheep in Greece. Furthermore, we preliminarily evaluated infrared thermography and the application of AI tools for the early, non-invasive diagnosis of relevant cases. In total, 660 milk samples and over 2000 infrared thermography images were obtained from 330 phenotypically healthy ewes. Microbiological investigations, a somatic cell count (SCC), and milk chemical analyses were performed. Infrared images were analyzed using the FLIR Research Studio software (version 3.0.1). The You Only Look Once version 8 (YOLOv8) algorithm was employed for the automatic detection of the udder’s region of interest. A total of 157 mammary glands with SCM were identified in 122/330 ewes (37.0%). The most prevalent pathogen was staphylococci (136/160, 86.6%). Considerable resistance was detected to tetracycline (29.7%), ampicillin (28.6%), and sulfamethoxazole–trimethoprim (23.6%). SCM correlated with high total mesophilic count (TMC) values and decreased milk fat, lactose, and protein content. A statistically significant variation (p < 0.001) was identified in the unilateral SCM cases by evaluating the mean temperatures of the udder region between the teats in the thermal images. Finally, the YOLOv8 algorithm was employed for the automatic detection of the udder’s region of interest (ROI), achieving 84% accuracy in defining the ROI in this preliminary evaluation. This demonstrates the potential of infrared thermography combined with AI tools for the diagnosis of ovine SCM. Nonetheless, more extensive sampling is essential to optimize this diagnostic approach. Full article

This study introduces an innovative on-site diagnostic method for rapidly detecting the Streptococcus bovis/Streptococcus equinus complex (SBSEC), crucial for livestock health and food safety. Through a comprehensive genomic analysis of 206 genomes, this study identified genetic markers that improved classification and addressed misclassifications, particularly in genomes labeled S. equinus and S. lutetiensis. These markers were integrated into a portable quantitative polymerase chain reaction (qPCR) that can detect SBSEC species with high sensitivity (down to 10¹ or 10⁰ colony-forming units/mL). The portable system featuring a flat chip and compact equipment allows immediate diagnosis within 30 min. The diagnostic method was validated in field conditions directly from cattle udders, farm environments, and dairy products. Among the 100 samples, 51 tested positive for bacteria associated with mastitis. The performance of this portable qPCR was comparable to laboratory methods, offering a reliable alternative to whole-genome sequencing for early detection in clinical, agricultural, and environmental settings. Full article

Early detection and comprehensive diagnostic approaches for breast cancer are essential for improving prognosis. When it comes to changes in the skin of the breast or the nipple–areola complex (NAC), particularly if they are unilateral, it is essential to be vigilant, as these changes could be an early sign of underlying malignancy or other pathologies. Primary breast malignancies, such as mammary Paget’s disease (MPD), can manifest as erythema, scaling, or ulceration of the NAC, while secondary cutaneous metastases from other breast carcinomas may present as nodules, erythematous plaques, or inflammatory reactions. Non-malignant inflammatory conditions, including eczema or mastitis, can also mimic these changes; histologic evaluation is the gold-standard diagnostic tool. The usefulness of conventional diagnostic techniques breast lesions has been confirmed, but in recent years, reflectance confocal microscopy (RCM) and optical coherence tomography (OCT) have emerged as additional tools to diagnose cases characterized by cutaneous changes; they may, therefore, result in new perspectives on the non-invasive diagnosis of MPD. RCM is a non-invasive diagnostic technique that allows high-resolution images of the skin at microscopic level in real time, offering a promising approach to the non-invasive diagnosis of MPD, particularly when a lesion is not clinically evident and may mimic other benign or inflammatory conditions. We describe an atypical clinical presentation of mammary Paget’s disease diagnosed early by reflectance confocal microscopy evaluation and confirmed histologically. Full article