Biosensors for On-Farm Diagnosis of Mastitis

Infrared Thermography as a Diagnostic Tool for the Assessment of Mastitis in Dairy Ruminants

Among the health issues of major concern in dairy ruminants, mastitis stands out as being associated with considerable losses in productivity and compromised animal health and welfare. Currently, the available methods for the early detection of mastitis are either inaccurate, requiring further validation, or expensive and labor intensive. Moreover, most of them cannot be applied at the point of care. Infrared thermography (IRT) is a rapid, non-invasive technology that can be used in situ to measure udder temperature and identify variations and inconsistencies thereof, serving as a benchmarking tool for the assessment of udders' physiological and/or health status. Despite the numerous applications in livestock farming, IRT is still underexploited due to the lack of standardized operation procedures and significant gaps regarding the optimum settings of the thermal cameras, which are currently exploited on a case-specific basis. Therefore, the objective of this review paper was twofold: first, to provide the state of knowledge on the applications of IRT for the assessment of udder health status in dairy ruminants, and second, to summarize and discuss the major strengths and weaknesses of IRT application at the point of care, as well as future challenges and opportunities of its extensive adoption for the diagnosis of udder health status and control of mastitis at the animal and herd levels.

Point-of-need mastitis pathogen biosensing in bovine milk: From academic sample preparation novelty to industry prototype field testing

Bovine mastitis is an inflammation of the mammary gland, and it is the most common infectious disease in dairy cattle. Mastitis reduces milk yield and quality, costing dairy farmers millions of dollars each year. The aim of this study was to develop a point-of-need test for identifying mastitis pathogens that is field portable, cost-effective and can be used with minimal training. Using a proprietary polymer-based milk sample preparation method to rapidly extract pathogen DNA in milk samples, we demonstrated quantitative Polymerase Chain Reaction (qPCR) assays for six common bovine bacterial mastitis pathogens: Staphylococcus aureus, Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Mycoplasma bovis and Escherichia coli. We also implemented this sample preparation method on a prototype point-of-need system in a proof-of-concept field trial to evaluate user experience. Importantly, the protype system enabled a sample-to-result turnaround time of within 70 min to quantitatively detect all six target pathogens. The key advantage of our point-of-need prototype system is being culture-independent yet providing automated milk sample preparation for molecular identification of key mastitis pathogens by non-expert users. Our point-of-need prototype system showed a good correlation to laboratory-based qPCR for target pathogen detection outcomes, thus potentially removing the need for milk samples to be transported off-site for laboratory testing. Above all, we successfully achieved our objective of developing a point-of-need biosensor technology for mastitis and increased its readiness level with industry partners towards technology commercialization.

Revealing microbial diversity in buffalo milk with high somatic cell counts: implications for mastitis diagnosis and treatment

Mastitis is one of the most serious diseases that threatens the health of dairy animals. The somatic cell count (SCC) in milk is widely used to monitor mastitis. This study aimed to reveal the diversity of microorganisms in buffalo milk with high somatic cell count (SCC ≥ 3 × 105 cells/mL, n = 30) and low somatic cell count (SCC ≤ 5 × 104 cells/mL, n = 10), and identify the dominant bacteria that cause mastitis in a local buffalo farm. We also investigated the potential method to treat bacterial mastitis. The V3-V4 region of 16 S rDNA was sequenced. Results showed that, compared to the milk with low SCC, the high SCC samples showed lower microbial diversity, but a high abundance of bacteria and operational taxonomic units (OTUs). By in vitro isolation and culture, Escherichia coli, Staphylococcus aureus, and Klebsiella pneumoniae were found to be the leading pathogens, which is consistent with the 16 S rDNA sequencing data. We further isolated 3 of the main pathogens and established a pathogen detection method based on ELISA. In addition, the antibacterial effects of 10 antimicrobials and 15 Chinese herbal extracts were also investigated. Results showed that the microbial has developed tolerance to several of the antimicrobials. While the water extracts of Chinese herbal medicine such as Galla Chinensis, Coptis chinensis Franch, Terminalia chebula Retz, and Sanguisorba officinalis L can effectively inhibit the growth of main pathogens. This study provides novel insight into the microbial diversity in buffalo milk and a reference for the prevention, diagnosis, and treatment of mastitis.

The prevalence and factors associated with mastitis in dairy cows kept by small-scale farmers in Dodoma, Tanzania

Bovine mastitis is among the major diseases of economic importance in the dairy industry worldwide. Hygienic conditions during milking and housing are important determinants of mastitis infections. However, arid and semi-arid areas have a scarcity of water, which is an essential component of cleanliness. Thus, the study determined the prevalence of mastitis and associated factors in Dodoma, a semi-arid region in Tanzania. Three hundred and sixty-eight lactating cows were selected randomly from 114 farms in the Dodoma urban district for mastitis determination based on clinical signs and the California Mastitis Test. About 59.8 % of the cows had mastitis, and the subclinical type dominated. Factors associated with mastitis prevalence were cleanliness (hand and udder washing before milking), farmers' awareness of mastitis, the cow's parity and lactation stage, and herd size. Milk yield was not associated with the mastitis status of the cow but was related to the breed of the cow, whether warm or cold water was used to wash the cow's udder, parity, and lactation stage. Improvement in education on the importance of hygiene is necessary, as 38.6 % of the farmers were unaware of mastitis. Further detailed studies on microbiology, such as bacteriologic culture and polymerase chain reaction, are recommended to formulate interventions.

Rapid and Online Microvolume Flow-Through Dialysis Probe for Sample Preparation in Veterinary Drug Residue Analysis

A rapid and online microvolume flow-through dialysis probe designed for sample preparation in the analysis of veterinary drug residues is introduced. This study addresses the need for efficient and green sample preparation methods that reduce chemical waste and reagent use. The dialysis probe integrates with liquid chromatography and mass spectrometry (LC-MS) systems, facilitating automated, high-throughput analysis. The dialysis method utilizes minimal reagent volumes per sample, significantly reducing the generation of solvent waste compared to traditional sample preparation techniques. Several veterinary drugs were spiked into tissue homogenates and analyzed to validate the probe's efficacy. A diagnostic sensitivity of >97% and specificity of >95% were obtained for this performance evaluation. The results demonstrated the effective removal of cellular debris and particulates, ensuring sample integrity and preventing instrument clogging. The automated dialysis probe yielded recovery rates between 27 and 77% for multiple analytes, confirming its potential to streamline veterinary drug residue analysis, while adhering to green chemistry principles. The approach highlights substantial improvements in both environmental impact and operational efficiency, presenting a viable alternative to conventional sample preparation methods in regulatory and research applications.

Staphylococcal mastitis in dairy cows

Bovine mastitis is one of the most common diseases of dairy cattle. Even though different infectious microorganisms and mechanical injury can cause mastitis, bacteria are the most common cause of mastitis in dairy cows. Staphylococci, streptococci, and coliforms are the most frequently diagnosed etiological agents of mastitis in dairy cows. Staphylococci that cause mastitis are broadly divided into Staphylococcus aureus and non-aureus staphylococci (NAS). NAS is mainly comprised of coagulase-negative Staphylococcus species (CNS) and some coagulase-positive and coagulase-variable staphylococci. Current staphylococcal mastitis control measures are ineffective, and dependence on antimicrobial drugs is not sustainable because of the low cure rate with antimicrobial treatment and the development of resistance. Non-antimicrobial effective and sustainable control tools are critically needed. This review describes the current status of S. aureus and NAS mastitis in dairy cows and flags areas of knowledge gaps.

Molecular and phenotypic identification of bacterial species isolated from cows with mastitis from three regions of Poland

BACKGROUND

Bovine mastitis is a widespread disease affecting dairy cattle worldwide and it generates substantial losses for dairy farmers. Mastitis may be caused by bacteria, fungi or algae. The most common species isolated from infected milk are, among others, Streptococcus spp., Escherichia coli, Staphylococcus aureus and non-aureus staphylococci and mammaliicocci. The aim of this paper is to determine the frequency of occurrence of bacterial species in milk samples from cows with mastitis from three regions of Poland: the north-east, the south-west and the south. To this end 203 milk samples taken from cows with a clinical form (CM) of mastitis (n = 100) and healthy animals (n = 103) were examined, which included culture on an appropriate medium followed by molecular detection of E. coli, S. aureus, Streptococcus agalactiae and Streptococcus uberis, as one of the most common species isolated from mastitis milk.

RESULTS

The results obtained indicated that S. uberis was the most commonly cultivated CM species (38%, n = 38), followed by S. aureus (22%, n = 22), E. coli (21%, n = 21) and S. agalactiae (18%, n = 18). Similar frequencies in molecular methods were obtained for S. uberis (35.1%) and S. aureus (28.0%). The variation of sensitivity of both methods may be responsible for the differences in the E. coli (41.0%, p = 0.002) and S. agalactiae (5.0%, p = 0.004) detection rates. Significant differences in composition of species between three regions of Poland were noted for E. coli incidence (p < 0.001), in both the culture and molecular methods, but data obtained by the PCR method indicated that this species was the least common in north-eastern Poland, while the culture method showed that in north-eastern Poland E. coli was the most common species. Significant differences for the molecular method were also observed for S. uberis (p < 0.001) and S. aureus (p < 0.001). Both species were most common in southern and south-western Poland.

CONCLUSIONS

The results obtained confirm the need to introduce rapid molecular tests for veterinary diagnostics, as well as providing important epidemiological data, to the best of our knowledge data on Polish cows in selected areas of Poland is lacking.

Unveiling the landscape of resistance against high priority critically important antimicrobials in food-producing animals across Africa: A scoping review

The rapid population growth in Africa is associated with an increasing demand for livestock products which in turn can lead to antimicrobial use. Antimicrobial usage in animals contributes to the emergence and selection of resistant bacteria which constitutes a serious public health threat. This study aims to review and summarize the available information on highest priority critically important antimicrobials (HPCIAs) resistance in livestock production in Africa. This work will help to inform future policies for controlling antimicrobial resistance (AMR) in the food production chain. A scoping review was conducted according to the Cochrane handbook and following PRISMA 2020 guidelines for reporting. Primary research studies published after 1999 and reporting resistance of Escherichia coli, Enterococcus spp, Staphylococcus aureus, Salmonella spp, and Campylobacter spp to HPCIAs in poultry, cattle, pigs, goats, and sheep in Africa were searched in four databases. A total of 312 articles were included in the review. The majority of the studies (40.7) were conducted in North African countries. More than 49.0% of included studies involved poultry and 26.2% cattle. Cephalosporins and quinolones were the most studied antimicrobial classes. Of the bacteria investigated in the current review, E. coli (41.7%) and Salmonella spp (24.9%) represented the most commonly studied. High levels of resistance against erythromycin in E. coli were found in poultry (MR 96.1%, IQR 83.3-100.0%), cattle (MR 85.7%, IQR 69.2-100.0%), and pigs (MR 94.0%, IQR 86.2-94.0%). In sheep, a high level of resistance was observed in E. coli against nalidixic acid (MR 87.5%, IQR 81.3-93.8%). In goats, the low level of sensibility was noted in S. aureus against streptomycin (MR 86.8%, IQR 19.4-99.0%). The study provides valuable information on HPCIAs resistance in livestock production in Africa and highlights the need for further research and policies to address the public health risk of AMR. This will likely require an investment in diagnostic infrastructure across the continent. Awareness on the harmful impact of AMR in African countries is a requirement to produce more effective and sustainable measures to curb AMR.

Identifying Predictive Biomarkers of Subclinical Mastitis in Dairy Cows through Urinary Metabotyping

Mastitis is a significant infectious disease in dairy cows, resulting in milk yield loss and culling. Early detection of mastitis-prone cows is crucial for implementing effective preventive measures before disease onset. Current diagnosis of subclinical mastitis (SCM) relies on somatic cell count assessment post-calving, lacking predictive capabilities. This study aimed to identify metabolic changes in pre-SCM cows through targeted metabolomic analysis of urine samples collected 8 wks and 4 wks before calving, using mass spectrometry. A nested case-control design was employed, involving a total of 145 multiparous dairy cows, with disease occurrence monitored pre- and postpartum. Among them, 15 disease-free cows served as healthy controls (CON), while 10 cows exclusively had SCM, excluding those with additional diseases. Urinary metabolite profiling revealed multiple alterations in acylcarnitines, amino acids, and organic acids in pre-SCM cows. Metabotyping identified 27 metabolites that distinguished pre-SCM cows from healthy CON cows at both 8 and 4 wks before parturition. However, only four metabolites per week showed significant alterations (p < 0.005). Notably, a panel of four serum metabolites (asymmetric dimethylarginine, proline, leucine, and homovanillate) at 8 wks prepartum, and another panel (asymmetric dimethylarginine, methylmalonate, citrate, and spermidine) at 4 wks prepartum, demonstrated predictive ability as urinary biomarkers for SCM risk (AUC = 0.88; p = 0.02 and AUC = 0.88; p = 0.03, respectively). In conclusion, our findings indicate that metabolite testing can identify cows at risk of SCM as early as 8 and 4 wks before parturition. Validation of the two identified metabolite panels is warranted to implement these predictive biomarkers, facilitate early intervention strategies, and improve dairy cow management to mitigate the impact of SCM. Further research is needed to confirm the efficacy and applicability of these biomarkers in practical farm settings.

Dual-Readout Ultrasensitive Lateral Flow Immunosensing of Salmonella typhimurium in Dairy Products by Doping Engineering-Powered Nanoheterostructure with Enhanced Photothermal Performance

The photothermal lateral flow immunoassay (LFIA) is of great significance to suitable for on-site semiquantitative detection, which has the upper hand in further constructing detection methods for low-concentration targets. Herein, we presented a doping engineering-powered nanoheterostructure with an enhanced photothermal performance strategy, employing bimetallic nanocuboid Pt3Sn (PSNCs) as a proof of concept. With the help of finite element simulation analysis, the contrast of direct temperature experiment, and the evaluation of photothermal conversion efficiency (η), the distinguished and enthusiastic photothermal feedback of PSNCs is proved. Based on steady bright black of colorimetric and superior photothermal performance, the PSNCs were employed to construct an ultrasensitive model LIFA for detecting Salmonella typhimurium (S. typhimurium), which achieved the double-signal semiquantitative detection, the detection limit reached 103 cfu mL-1 (colorimetric mode) and 102 cfu mL-1 (photothermal mode), which is 100 times higher than that of the traditional colloidal gold method. In addition, the method was effective for the detection of targets in dairy samples only through a simple dilution treatment, which was completed within 15 min. Meanwhile, this PSNCs dual-signal LFIA demonstrated the sensitive detection of S. typhimurium due to the excellent colorimetric signal and significant photothermal performance, which provides a broad spectrum for the future detection of foodborne pathogens.

Host DNA depletion methods and genome-centric metagenomics of bovine hindmilk microbiome

Bovine mastitis is a multi-etiological and complex disease, resulting in serious economic consequences for dairy farmers and industry. In recent years, the microbiological evaluation of raw milk has been investigated in-depth using next-generation sequencing approaches such as metataxonomic analysis. Despite this, host DNA is a major concern in the shotgun metagenomic sequencing of microbial communities in milk samples, and it represents a big challenge. In this study, we aimed to evaluate different methods for host DNA depletion and/or microbial DNA enrichment and assess the use of PCR-based whole genome amplification in milk samples with high somatic cell count (SCC) by using short- and long-read sequencing technologies. Our results evidenced that DNA extraction performed differently in terms of host DNA removal, impacting metagenome composition and functional profiles.. Moreover, the ratio of SCC/bacteria ultimately impacts microbial DNA yield, and samples with low SCC (SCC below 100,000 cells/mL) are the most problematic. When milk samples with high SCC (SCC above 200,000 cells/mL) underwent multiple-displacement amplification (MDA), we successfully recovered high-quality metagenome-assembled genomes (MAGs), and long-read sequencing was feasible even for samples with low DNA concentration. By associating MDA and short-read sequencing, we recovered two times more MAGs than in untreated samples, and an ongoing co-infection not reported by traditional methods was detected for mastitis pathogen. Overall, this new approach will improve the detection of mastitis-associated microorganisms and make it possible to examine host-microbiome interactions in bovine mastitis.IMPORTANCENext-generation sequencing technologies have been widely used to gain new insights into the diversity of the microbial community of milk samples and dairy products for different purposes such as microbial safety, profiling of starter cultures, and host-microbiome interactions. Milk is a complex food matrix, and additionally, the presence of host nucleic acid sequences is considered a contaminant in untargeted high-throughput sequencing studies. Therefore, genomic-centric metagenomic studies of milk samples focusing on the health-disease status in dairy cattle are still scarce, which makes it difficult to evaluate the microbial ecophysiology of bovine hindmilk. This study provides an alternative method for genome-centric metagenome studies applied to hindmilk samples with high somatic cell content, which is indispensable to examining host-microbiome interactions in bovine mastitis.

Rapid Detection and Identification of Vancomycin-Sensitive Bacteria Using an Electrochemical Apta-Sensor

In order to combat the complex and diverse infections caused by bacteria, it is essential to develop efficient diagnostic tools. Current techniques for bacterial detection rely on laborious multistep procedures, with high costs and extended time of analysis. To overcome these limitations, we propose here a novel portable electrochemical biosensor for the rapid detection and identification of Gram-positive bacteria that leverages the recognition capabilities of vancomycin and aptamers. A vancomycin-modified screen-printed carbon electrode was used to selectively capture Gram-positive bacteria susceptible to this antibiotic. Electrochemical impedance spectroscopy and scanning electron microscopy demonstrated that capture was achieved in 10 min, with a limit of detection of only 2 CFU/mL. We then tested the device's potential for aptamer-based bacterial identification using Staphylococcus aureus and Bacillus cereus as the test strains. Specifically, electrodes with captured bacteria were exposed to species-specific aptamers, and the resulting changes in current intensity were analyzed using differential pulse voltammetry. When used directly in untreated milk or serum, the system was able to successfully identify a small amount of S. aureus and B. cereus (100 CFU/mL) in less than 45 min. This novel biosensor has the potential to serve as an invaluable tool that could be used, even by inexperienced staff, in a broad range of settings including clinical diagnostics, food safety analysis, environmental monitoring, and security applications.

Basic concepts, recent advances, and future perspectives in the diagnosis of bovine mastitis

Mastitis is one of the most widespread infectious diseases that adversely affects the profitability of the dairy industry worldwide. Accurate diagnosis and identification of pathogens early to cull infected animals and minimize the spread of infection in herds is critical for improving treatment effects and dairy farm welfare. The major pathogens causing mastitis and pathogenesis are assessed first. The most recent and advanced strategies for detecting mastitis, including genomics and proteomics approaches, are then evaluated . Finally, the advantages and disadvantages of each technique, potential research directions, and future perspectives are reported. This review provides a theoretical basis to help veterinarians select the most sensitive, specific, and cost-effective approach for detecting bovine mastitis early.

Indirect Sensing of Subclinical Intramammary Infections in Dairy Herds with a Milking Robot

This study determined the impact of subclinical intramammary infections (IMIs), such as the major and minor udder pathogens (MaPs and MiPs), on the somatic cell count (SCC) in cow milk and investigated the possibilities of indirect sensing of the udder pathogens using the mastitis detection index (MDi) (DeLaval, Tumba, Sweden). The MDi incorporates quarter-level milk electrical conductivity, blood in milk, and milking interval. The case group (n = 21; MDi ≥ 1.4) was compared with the control group (n = 24; MDi < 1.4) for the presence of IMIs. The microbiological investigation of udder quarter foremilk samples was performed two times with an interval of 10 to 14 days. The case and control groups differed in terms of the occurrence of MaPs and MiPs in milk. During the continuous subclinical IMI and the episodic MaP infection, a higher SCC was detected compared with the episodic MiP infection or quarters without IMI. The novel finding of this study was that by using the milk quality sensor for the sensing of subclinical IMIs, there was an indication for the successful detection of episodic MaPs. However, the sensing of the continuous subclinical IMIs was not possible in the current study and still needs to be investigated.

Emergent Molecular Techniques Applied to the Detection of Porcine Viruses

Molecular diagnostic tests have evolved very rapidly in the field of human health, especially with the arrival of the recent pandemic caused by the SARS-CoV-2 virus. However, the animal sector is constantly neglected, even though accurate detection by molecular tools could represent economic advantages by preventing the spread of viruses. In this regard, the swine industry is of great interest. The main viruses that affect the swine industry are described in this review, including African swine fever virus (ASFV), porcine reproductive and respiratory syndrome virus (PRRSV), porcine epidemic diarrhea virus (PEDV), and porcine circovirus (PCV), which have been effectively detected by different molecular tools in recent times. Here, we describe the rationale of molecular techniques such as multiplex PCR, isothermal methods (LAMP, NASBA, RPA, and PSR) and novel methods such as CRISPR-Cas and microfluidics platforms. Successful molecular diagnostic developments are presented by highlighting their most important findings. Finally, we describe the barriers that hinder the large-scale development of affordable, accessible, rapid, and easy-to-use molecular diagnostic tests. The evolution of diagnostic techniques is critical to prevent the spread of viruses and the development of viral reservoirs in the swine industry that impact the possible development of future pandemics and the world economy.

Mastitis on selected farms in Wakiso district, Uganda: Burden, pathogens and predictors of infectivity of antimicrobial resistant bacteria in dairy herds

BACKGROUND

Mastitis and associated antimicrobial resistance (AMR) are major challenges to the dairy industry worldwide.

OBJECTIVE

This study aimed to expose the mastitis burden, causative bacteria and drivers for mastitis-causing multi-drug-resistant (MDR) Staphylococci infectivity in cows on dairy farms in Wakiso district, Uganda.

METHODS

On 22 farms, practices were documented using questionnaires, and 175 cows were screened by the California mastitis test. Composite milk samples from the positive reactors were submitted to the laboratory for bacterial culture testing. Antimicrobial sensitivity testing by the Kirby Bauer disc diffusion method was done only on Staphylococci with a panel of 10 antimicrobials of clinical relevance.

RESULTS

Mastitis was detected in 80.6% (n = 141) of the 175 sampled cows, of which sub-clinical mastitis (76.0%: n = 133) was predominant. The Chi-squared analysis hypothesized that cow age (p = 0.017), sub-county (p = 0.013), parity (p < 0.0001), sex of farm owner (p = 0.003), farm duration in dairy production (p = 0.048) and the use of milking salve (p = 0.006) were associated with mastitis. Coagulase-negative Staphylococci were the most prevalent (71.4%; n = 95), followed by Staphylococcus aureus (30.1%, n = 40). Staphylococci (76.3%; n = 135) were majorly resistant to penicillin and tetracycline. Only one isolate was phenotyped as a methicillin-resistant Staphylococcus specie (MRSS). The prevalences of MDR strains at cow and isolate level were 6.3% and 8.3%. The major MDR phenotype identified was penicillin-tetracycline-trimethoprim-sulphamethoxazole. The isolate detected as an MRSS exhibited the broadest MDR pattern. Cow parity was identified as a predictor of infectivity of mastitis-causing MDR Staphylococci in dairy herds.

CONCLUSION

The high prevalence of mastitis and associated pathogen AMR found exposes possibilities of economic losses for the dairy sector warranting the need for farmer sensitization on the institution of proper mastitis prevention and control programs, with emphasis on milking hygiene practices and routine disease monitoring.

Longitudinal analysis of anti-SARS-CoV-2 neutralizing antibody (NAb) titers in vaccinees using a novel giant magnetoresistive (GMR) assay

The COVID-19 pandemic has highlighted the need to monitor important correlates of immunity on a population-wide level. To this end, we have developed a competitive assay to assess neutralizing antibody (NAb) titer on the giant magnetoresistive (GMR) biosensor platform. We compared the clinical performance of our biosensor with established techniques such as Ortho's VITROS Anti-SARS-CoV-2 IgG Quantitative Antibody test. Results obtained between the VITROS test and the GMR assay showed correlation (r = -0.93). We then validated the assay with patient plasma samples that had been tested using focus reduction neutralization testing (FRNT). The results obtained from our GMR assay exhibit a previously identified trend of increased NAb titers 2 weeks post-vaccination. We further evaluated NAb titers 6 months post-vaccination and observed waning neutralizing antibody titers over that time in vaccinated patients. In addition, we calibrated our assay to an arbitrary unit (IU/mL) using World Health Organization (WHO) reference plasma provided by the National Institute of Biological Standards and Control (NIBSC). Our biosensor provides highly specific and sensitive results in serum and plasma with analytical, clinical, and point-of-care (POC) applications due to quick turnaround times on samples and the cost-effectiveness of the platform.

Advances in point-of-care genetic testing for personalized medicine applications

Breakthroughs within the fields of genomics and bioinformatics have enabled the identification of numerous genetic biomarkers that reflect an individual's disease susceptibility, disease progression, and therapy responsiveness. The personalized medicine paradigm capitalizes on these breakthroughs by utilizing an individual's genetic profile to guide treatment selection, dosing, and preventative care. However, integration of personalized medicine into routine clinical practice has been limited-in part-by a dearth of widely deployable, timely, and cost-effective genetic analysis tools. Fortunately, the last several decades have been characterized by tremendous progress with respect to the development of molecular point-of-care tests (POCTs). Advances in microfluidic technologies, accompanied by improvements and innovations in amplification methods, have opened new doors to health monitoring at the point-of-care. While many of these technologies were developed with rapid infectious disease diagnostics in mind, they are well-suited for deployment as genetic testing platforms for personalized medicine applications. In the coming years, we expect that these innovations in molecular POCT technology will play a critical role in enabling widespread adoption of personalized medicine methods. In this work, we review the current and emerging generations of point-of-care molecular testing platforms and assess their applicability toward accelerating the personalized medicine paradigm.

Nanoarchitectonic E-Tongue of Electrospun Zein/Curcumin Carbon Dots for Detecting Staphylococcus aureusin Milk

We report a nanoarchitectonic electronic tongue made with flexible electrodes coated with curcumin carbon dots and zein electrospun nanofibers, which could detect Staphylococcus aureus(S. aureus) in milk using electrical impedance spectroscopy. Electronic tongues are based on the global selectivity concept in which the electrical responses of distinct sensing units are combined to provide a unique pattern, which in this case allowed the detection of S. aureus through non-specific interactions. The electronic tongue used here comprised 3 sensors with electrodes coated with zein nanofibers, carbon dots, and carbon dots with zein nanofibers. The capacitance data obtained with the three sensors were processed with a multidimensional projection technique referred to as interactive document mapping (IDMAP) and analyzed using the machine learning-based concept of multidimensional calibration space (MCS). The concentration of S. aureus could be determined with the sensing units, especially with the one containing zein as the limit of detection was 0.83 CFU/mL (CFU stands for colony-forming unit). This high sensitivity is attributed to molecular-level interactions between the protein zein and C-H groups in S. aureus according to polarization-modulated infrared reflection-absorption spectroscopy (PM-IRRAS) data. Using machine learning and IDMAP, we demonstrated the selectivity of the electronic tongue in distinguishing milk samples from mastitis-infected cows from milk collected from healthy cows, and from milk spiked with possible interferents. Calibration of the electronic tongue can also be reached with the MCS concept employing decision tree algorithms, with an 80.1% accuracy in the diagnosis of mastitis. The low-cost electronic tongue presented here may be exploited in diagnosing mastitis at early stages, with tests performed in the farms without requiring specialized laboratories or personnel.

Fabrication of spectroscopic microfluidic chips for mastitis detection in raw milk

Mastitis is a disease that directly affects the quantity and quality of milk produced by dairy cows, which can have a negative impact on the income generated from selling the milk. Severe inflammation caused by this mammary disease can result in up to 1 × 10⁶ white blood cells per milliliter of cow milk. Currently, the California mastitis test is a popular chemical inspection test, but its error rate of over 40% is a significant factor in the ongoing spread of mastitis. In this study, a new microfluidic device was designed and fabricated to identify normal, sub-clinical, and clinical mastitis. This portable device allows for precise and analysis of results within a second. The device was designed to screen somatic cells and a staining process was added to identify somatic cells using single-cell process analysis. The fluorescence principle was used to identify the infection status of the milk, which was analyzed using a mini-spectrometer. The accuracy of the device was tested, and it was found to determine the infection status with 95% accuracy, compared to the accuracy obtained using the Fossomatic machine. By introducing this new microfluidic device, it is believed that the spread of mastitis in dairy cows can be significantly reduced, leading to higher quality and more profitable milk production.

A scoping review of the testing of bulk milk to detect infectious diseases of dairy cattle: Diseases caused by bacteria

Testing of bulk milk (BM) samples is a convenient, cost-effective strategy that can easily be implemented as part of disease surveillance programs on dairy farms. Here, we performed a scoping review to summarize the literature reporting on the testing of BM samples to detect infectious diseases of dairy cattle caused by bacteria. We also provide a non-exhaustive, albeit significant, list of diagnostic tests that are marketed for BM samples, as well as a list of disease surveillance activities that included testing of BM samples. A literature search was carried out in 5 databases, yielding 8,829 records from which 474 were retained. Overall, 575 eligible bacterial pathogens were screened for using BM samples, ranging from 1 to 6 individual pathogens per study. Staphylococcus aureus, including methicillin-resistant Staph. aureus, were the most studied bacteria (n = 179 studies), followed by Streptococcus agalactiae (86), Mycobacterium avium ssp. paratuberculosis (79), Coxiella burnetii (79), and Mycoplasma spp. (67). Overall, culture-based protocols, ELISA, real-time PCR, and PCR were the most commonly adopted methodologies to screen BM samples. Sensitivity of BM testing for bovine paratuberculosis was generally low and varied greatly according to the ELISA cut-offs adopted and herd-level definition of disease. In general, protocols had low to moderate sensitivities (<50%), which increased for herds with high within-herd seroprevalence. Specificity of BM testing for paratuberculosis was generally high. With respect to mastitis pathogens, BM testing demonstrated high sensitivity and specificity for Strep. agalactiae, in general. However, we observed inconsistency among studies with respect to the sensitivity of BM culture to detect infected herds, which was notably higher if enrolled herds were heavily infected or had history of clinical disease. Among Salmonella spp. pathogens, Salmonella Dublin was the most frequently studied bacterium for which BM testing has been validated. Specificity of BM ELISA was high, ranging from 89.0 to 99.4. In contrast, sensitivity varied greatly among studies, ranging from 50.6% to 100%. Our findings support that one of most important factors affecting sensitivity of BM ELISA for Salmonella Dublin is whether nonlactating cattle are considered in the definition of herd infection status. In general, protocols analyzed in this review suffered from very low sensitivities, which hardly justifies their use as part of disease surveillance as single testing. Nevertheless, test sensitivity can be increased by the adoption of more inclusive definitions of disease-free herds. Further, low-sensitivity and high-specificity methods can be valuable tools for surveillance when used repeatedly over time.

SERS-based immunosensor for E. coli contaminants detection in milk using silver-coated nanoporous silicon substrates

The dairy sector is frequently affected by contagious and environmental factors that spread between animals by numerous means and induce the inflammatory disease of bovine mastitis (BM). Herein, silver decorated porous silicon (Ag-pSi) SERS platform was designed for rapid and reliable Escherichia coli (predominant BM pathogen) detection in various milk origins. The inherent surface void and pore morphology were physically optimized to augment the SERS effect using 4-aminothiphenol (4ATP) while achieving an enhancement factor >4.6 × 10⁷. An indirect immunoassay evaluated the residual unreacted antibodies using an optimized 4ATP/Ag-pSi SERS platform modified with secondary antibodies. Under optimized conditions, the porous substrate offered high sensitivity toward target bacteria detection of 3 CFU mL^-1 and linear response of 10¹-10⁵ CFU mL^-1. Moreover, the selectivity and specificity of the designed sensing platform were cross-validated against other interfering bacteria without compromising its performance efficiencies. Finally, the applicability of the developed system for real-life conditions was elucidated in different milk samples (bovine, goat, sheep) with recovery values of 78-115% compared to the conventional culture technique. Considering the complex media analysis, the miniaturized SERS platform is highly reliable, rapid and accurate that could be applicable for routine on-site analysis of various emerging pathogens relevant to BM management.

Innovations in Cattle Farming: Application of Innovative Technologies and Sensors in the Diagnosis of Diseases

Precision livestock farming has a crucial function as farming grows in significance. It will help farmers make better decisions, alter their roles and perspectives as farmers and managers, and allow for the tracking and monitoring of product quality and animal welfare as mandated by the government and industry. Farmers can improve productivity, sustainability, and animal care by gaining a deeper understanding of their farm systems as a result of the increased use of data generated by smart farming equipment. Automation and robots in agriculture have the potential to play a significant role in helping society fulfill its future demands for food supply. These technologies have already enabled significant cost reductions in production, as well as reductions in the amount of intensive manual labor, improvements in product quality, and enhancements in environmental management. Wearable sensors can monitor eating, rumination, rumen pH, rumen temperature, body temperature, laying behavior, animal activity, and animal position or placement. Detachable or imprinted biosensors that are adaptable and enable remote data transfer might be highly important in this quickly growing industry. There are already multiple gadgets to evaluate illnesses such as ketosis or mastitis in cattle. The objective evaluation of sensor methods and systems employed on the farm is one of the difficulties presented by the implementation of modern technologies on dairy farms. The availability of sensors and high-precision technology for real-time monitoring of cattle raises the question of how to objectively evaluate the contribution of these technologies to the long-term viability of farms (productivity, health monitoring, welfare evaluation, and environmental effects). This review focuses on biosensing technologies that have the potential to change early illness diagnosis, management, and operations for livestock.

Diagnostic Screening of Bovine Mastitis Using MALDI-TOF MS Direct-Spotting of Milk and Machine Learning

Novel strategies for diagnostic screening of animal and herd health are crucial to contain disease outbreaks, maintain animal health, and maximize production efficiency. Mastitis is an inflammation of the mammary gland in dairy cows, often resulting from infection from a microorganism. Mastitis outbreaks result in loss of production, degradation of milk quality, and the need to isolate and treat affected animals. In this work, we evaluate MALDI-TOF mass spectrometry as a diagnostic for the culture-less screening of mastitis state from raw milk samples collected from regional dairies. Since sample preparation requires only minutes per sample using microvolumes of reagents and no cell culture, the technique is promising for rapid sample turnaround and low-cost diagnosis. Machine learning algorithms have been used to detect patterns embedded within MALDI-TOF spectra using a training set of 226 raw milk samples. A separate scoring set of 100 raw milk samples has been used to assess the specificity (spc) and sensitivity (sens) of the approach. Of machine learning models tested, the gradient-boosted tree model gave global optimal results, with the Youden index of J = 0.7, sens = 0.89, and spc = 0.81 achieved for the given set of conditions. Random forest models also performed well, achieving J > 0.63, with sens = 0.83 and spc = 0.81. Naïve Bayes, generalized linear, fast large-margin, and deep learning models failed to produce diagnostic results that were as favorable. We conclude that MALDI-TOF MS combined with machine learning is an alternative diagnostic tool for detection of high somatic cell count (SCC) and subclinical mastitis in dairy herds.

A Lab-on-a-Chip Approach for the Detection of the Quarantine Potato Cyst Nematode Globodera pallida

The potato cyst nematode (PCN), Globodera pallida, has acquired significant importance throughout Europe due to its widespread prevalence and negative effects on potato production. Thus, rapid and reliable diagnosis of PCN is critical during surveillance programs and for the implementation of control measures. The development of innovative technologies to overcome the limitations of current methodologies in achieving early detection is needed. Lab-on-a-chip devices can swiftly and accurately detect the presence of certain nucleotide sequences with high sensitivity and convert the presence of biological components into an understandable electrical signal by combining biosensors with microfluidics-based biochemical analysis. In this study, a specific DNA-probe sequence and PCR primers were designed to be used in a magnetoresistive biosensing platform to amplify the internal transcribed spacer region of the ribosomal DNA of G. pallida. Magnetic nanoparticles were used as the labelling agents of asymmetric PCR product through biotin−streptavidin interaction. Upon target hybridization to sensor immobilized oligo probes, the fringe field created by the magnetic nanoparticles produces a variation in the sensor’s electrical resistance. The detection signal corresponds to the concentration of target molecules present in the sample. The results demonstrate the suitability of the magnetic biosensor to detect PCR target product and the specificity of the probe, which consistently distinguishes G. pallida (DV/V > 1%) from other cyst nematodes (DV/V < 1%), even when DNA mixtures were tested at different concentrations. This shows the magnetic biosensor’s potential as a bioanalytical device for field applications and border phytosanitary inspections.

Is AMR in Dairy Products a Threat to Human Health? An Updated Review on the Origin, Prevention, Treatment, and Economic Impacts of Subclinical Mastitis

Background

Bovine mastitis is the most frequent and costly illness impacting dairy herds worldwide. The presence of subclinical mastitis in dairy cows has an impact on the decreased output of milk and milk quality, culling of affected cows, mortality rate, as well as mastitis-related treatment expenses, generating significant financial loss to the dairy industry. The pathogenic bacteria invade through the mammary gland, which then multiply in the milk-producing tissues causing infection, and the presence of pathogenic bacteria in milk is concerning, jeopardizes human health, and also has public health consequences. Intervention to promote herd health is essential to protect public health and the economy.

Results

This review attempts to provide an overview of subclinical mastitis, including mastitis in different species, the effect of mastitis on human health and its pathogenic mechanism, the prevalence and incidence of subclinical mastitis, and current preventive, diagnostic, and treatment methods for subclinical mastitis. It also elaborates on the management practices that should be followed by the farms to improve herd immunity and health.

Conclusion

This review brings the importance of the threat of antimicrobial resistance organisms to the dairy industry. Furthermore, this review gives a glimpse of the economic consequences faced by the farmers and a futuristic mastitis market analysis in the dairy industry.

Udder Health Monitoring for Prevention of Bovine Mastitis and Improvement of Milk Quality

To maximize milk production, efficiency, and profits, modern dairy cows are genetically selected and bred to produce more and more milk and are fed copious quantities of high-energy feed to support ever-increasing milk volumes. As demands for increased milk yield and milking efficiency continue to rise to provide for the growing world population, more significant stress is placed on the dairy cow's productive capacity. In this climate, which is becoming increasingly hotter, millions of people depend on the capacity of cattle to respond to new environments and to cope with temperature shocks as well as additional stress factors such as solar radiation, animal crowding, insect pests, and poor ventilation, which are often associated with an increased risk of mastitis, resulting in lower milk quality and reduced production. This article reviews the impact of heat stress on milk production and quality and emphasizes the importance of udder health monitoring, with a focus on the use of emergent methods for monitoring udder health, such as infrared thermography, biosensors, and lab-on-chip devices, which may promote animal health and welfare, as well as the quality and safety of dairy products, without hindering the technological flow, while providing significant benefits to farmers, manufacturers, and consumers.

Mastitis: What It Is, Current Diagnostics, and the Potential of Metabolomics to Identify New Predictive Biomarkers

Periparturient diseases continue to be the greatest challenge to both farmers and dairy cows. They are associated with a decrease in productivity, lower profitability, and a negative impact on cows’ health as well as public health. This review article discusses the pathophysiology and diagnostic opportunities of mastitis, the most common disease of dairy cows. To better understand the disease, we dive deep into the causative agents, traditional paradigms, and the use of new technologies for diagnosis, treatment, and prevention of mastitis. This paper takes a systems biology approach by highlighting the relationship of mastitis with other diseases and introduces the use of omics sciences, specifically metabolomics and its analytical techniques. Concluding, this review is backed up by multiple studies that show how earlier identification of mastitis through predictive biomarkers can benefit the dairy industry and improve the overall animal health.

Naked-eye detection of Staphylococcus aureus in powdered milk and infant formula using gold nanoparticles

Nonspecific binding of proteins from complex food matrices is a significant challenge associated with a biosensor using gold nanoparticles (AuNPs). To overcome this, we developed an efficient EDTA chelating treatment to denature milk proteins and prevent their adsorption on AuNPs. The use of EDTA to solubilize proteins enabled a sensitive label-free apta-sensor platform for colorimetric detection of Staphylococcus aureus in milk and infant formula. In the assay, S. aureus depleted aptamers from the test solution, and the reduction of aptamers enabled aggregation of AuNPs upon salt addition, a process characterized by a color change from red to purple. Under optimized conditions, S. aureus could be visually detected within 30 min with the detection limit of 7.5 × 10⁴ CFU/mL and 8.4 × 10⁴ CFU/mL in milk and infant formula, respectively. The EDTA treatment provides new opportunities for monitoring milk contamination and may prove valuable for biosensor point-of-need applications.

A sequential toggle cell-SELEX DNA aptamer for targeting Staphylococcus aureus, Streptococcus agalactiae, and Escherichia coli bacteria

BACKGROUND

Mastitis is an inflammation of the mammary glands caused by a microbial infection. The common bacteria causing this infection in dairy farms are Staphylococcus aureus, Streptococcus agalactiae, and Escherichia coli. The aptamer is a new biosensor platform for detecting pathogens; however, its use for simultaneous detection of S. aureus, S. agalactiae, and E. coli bacteria has not been reported. This study's objective is to isolate and characterize polyclonal DNA aptamer with broad reactivity to the mastitis bacteria S. aureus, S. agalactiae, and E. coli using a sequential toggle cell-SELEX.

METHODS AND RESULTS

The DNA aptamer pool from SELEX 15 was inserted into the pGEM-T easy plasmid. Furthermore, the transformant clones were selected by PCR colony, plasmid isolation, and sequencing. Six DNA aptamers, consisting of S15K3, S15K4, S15K6, S15K13, S15K15, and S15K20 with a constant region and the right size of 81 bp were derived from the sequencing analysis. The secondary structure of the DNA was predicted using Mfold software. The DNA was analyzed with binding characteristics, including binding capacity and affinity (Kd), using qPCR. The results indicated aptamer S15K15 has the highest binding ability into S. agalactiae, while S15K13 performed binding capacity most to E. coli EPEC 4, and S15K3 has the highest capacity of binding to S. aureus BPA-12.

CONCLUSION

Aptamer S15K3 has the best binding characteristics on all three bacterial targets.

Characterization and genome analysis of Pseudomonas aeruginosa phage vB_PaeP_Lx18 and the antibacterial activity of its lysozyme

A lytic Pseudomonas aeruginosa phage, vB_PaeP_Lx18 (Lx18), was isolated from the sewage of a dairy farm. Biological characterization revealed that Lx18 was stable from 40 °C to 60 °C and over a wide range of pH values from 4 to 10. It was able to lyse 63.6% (21/33) of the P. aeruginosa strains tested and was able to reduce and disperse biofilms, with a biofilm reduction rate of 76.8%. Whole-genome sequencing showed that Lx18 is a dsDNA virus with a genome of 42,735 bp and G+C content of 62.16%. The genome contains 54 open reading frames (ORFs), 28 of which have known functions, including DNA replication and modification, transcriptional regulation, structural and packaging proteins, and host cell lysis. No virulence or tRNA genes were identified. Phylogenetic analysis showed that phage Lx18 belongs to the genus Phikmvvirus. The lysozyme of Lx18, Lys18, was cloned and expressed. The combined action of Lys18 and ethylenediaminetetraacetic acid (EDTA) had antibacterial activity against Pseudomonas aeruginosa. The study of phage Lx18 and its lysozyme will provide basic information for further research on the treatment of Pseudomonas aeruginosa infections.

From saliva to SNP: non-invasive, point-of-care genotyping for precision medicine applications using recombinase polymerase amplification and giant magnetoresistive nanosensors

Genetic testing is considered a cornerstone of the precision medicine paradigm. Genotyping of single nucleotide polymorphisms (SNPs) has been shown to provide insights into several important issues, including therapy selection and drug responsiveness. However, a scarcity of widely deployable and cost-effective genotyping tools has limited the integration of precision medicine into routine clinical practice. The objective of our work was to develop a portable, cost-effective, and automated platform that performs SNP genotyping at the point-of-care (POC). Using recombinase polymerase amplification (RPA) and giant magnetoresistive (GMR) nanosensors, we present a highly automated and multiplexed point-of-care platform that utilizes direct saliva for the qualitative genotyping of four SNPs (rs4633, rs4680, rs4818, rs6269) along the catechol-O-methyltransferase gene (COMT), which is associated with the modulation of pain sensitivity and perioperative opioid use. Using this approach, we successfully amplify, detect, and genotype all four of the SNPs, demonstrating 100% accordance between the experimental results obtained using the automated RPA and GMR genotyping assay and the results obtained using a COMT PCR genotyping assay that was formerly validated using pyrosequencing. This automated, portable, and multiplexed RPA and GMR assay shows great promise as a solution for SNP genotyping at the POC and reinforces the broad applications of magnetic nanotechnology in biomedicine.

Biosensors, modern technology for the detection of cancer-associated bacteria

Cancer is undoubtedly one of the major human challenges worldwide. A number of pathogenic bacteria are deemed to be potentially associated with the disease. Accordingly, accurate and specific identification of cancer-associated bacteria can play an important role in cancer control and prevention. A variety of conventional methods such as culture, serology, and molecular-based methods as well as PCR and real-time PCR have been adopted to identify bacteria. However, supply costs, machinery fees, training expenses, consuming time, and the need for advanced equipment are the main problems with the old methods. As a result, advanced and modern techniques are being developed to overcome the disadvantages of conventional methods. Biosensor technology is one of the innovative methods that has been the focus of researchers due to its numerous advantages. The main purpose of this study is to provide an overview of the latest developed biosensors for recognizing the paramount cancer-associated bacteria.

Bayesian estimation of sensitivity and specificity of a rapid mastitis test kit, bacterial culture, and PCR for detection of Staphylococcus aureus, Streptococcus species, and coliforms in bovine milk samples

Our objectives were to evaluate the diagnostic accuracy of a rapid and novel immunochromatography-based mastitis kit that includes 3 independent tests to detect coliforms (Escherichia coli or Klebsiella pneumoniae), Streptococcus spp., and Staphylococcus aureus. The kit was developed to facilitate diagnostic-based mastitis treatment. Validation of the kit was based on 154 aseptically collected mastitis samples from 2 clinical herds (clinical population) and 120 milk samples from 3 nonclinical herds (nonclinical population) without clinical cases at the time of enrollment. One herd sampled at different times was common to both populations. A 3-test in 2-population Bayesian latent class model with uniform priors for all test parameters except specificity of culture, which was modeled informatively, was used to estimate sensitivity (Se) and specificity (Sp) of the test kit, culture, and PCR at the cow level. The mastitis test kit's 96.9% Sp for Streptococcus spp. had a low false positive percentage (3.1%), which, together with the kit's rapid turnaround time for results, makes it a suitable initial screening test that producers can use to identify clinical cows to treat based on Streptococcus spp. mastitis in kit-positive results. Due to the 60.4% kit Se, producers should follow up on Streptococcus spp. kit-negative cows using a confirmatory test such as PCR (Sp of 98.4%) or culture (Sp of 99.6%). In contrast, aerobic culture had Se of 76.5% and Sp of 99.6% for Streptococcus spp. Similarly, the Sp of the kit (98.2%) and culture (99.8%) for Staph. aureus were particularly high, and even though the kit's Se (61.0%) was lower than culture (88.4%; posterior probability of difference 98%), the kit could be beneficial before use of a confirmatory test for kit-negative samples due to its ease and rapid turnaround time. Mostly, quantitative real-time (q)PCR outperformed the kit's Se (37.7%) and Sp (92.9%) for coliforms, as well as the kit's Se (60.4%) for Streptococcus spp. However, qPCR may require more technical skills and turnaround time for final results. Use of the on-farm mastitis test kit evaluated in the present study could enhance sustainable antimicrobial drug use by rapidly identifying Streptococcus mastitis for targeted treatment. Furthermore, the kit may be used in a Staph. aureus outbreak where cows can be rapidly screened to identify cases for segregation or culling during an outbreak and kit-negative cows further confirmed by milk culture or qPCR. However, the cost-effectiveness of such an approach has not been investigated.

Relationship Between Somatic Cell Counts and Mammary Gland Parenchyma Ultrasonography in Buffaloes

The aim of the present study was to determine whether the echotextural features of the mammary gland parenchyma in buffaloes during lactation at different somatic cell levels could be used to diagnose mastitis. This study was divided into two parts. In the first experiment, experimental buffaloes (n = 65) with somatic cell counts (SCC) tests (n = 94) in different seasons, including spring (n = 22), summer (n = 24), autumn (n = 37), and winter (n = 11), were used to obtain ultrasonic variables for each quarter of mammary gland that could best explain the corresponding somatic cell level. In the second part of the study, the first part's experimental results were verified by subjecting at least one-quarter udder of eight buffaloes to ultrasonography seven times during mid-July to mid-August for obtaining ultrasonic values at different somatic cell levels. The echo textural characteristics [mean numerical pixel values (NPVs) and pixel heterogeneity (pixel standard deviation, PSD)] were evaluated using 16 ultrasonographic images of each buffalo with Image ProPlus software. The effects of SCC, days in milk (DIM), scanning order (SO), season, as well as the scanning plane and udder quarter (SP + UQ) on both the PSD and NPVs of the mammary gland were significant (p < 0.05). The correlation coefficient between pre-milking sagittal PSD and somatic cell score (SCS) was the highest (r = 0.4224, p < 0.0001) with fitted linear model: y = 0.19445x (dependent variable: SCS, independent variables: pre-milking sagittal PSD; R² = 0.84, p < 0.0001). In addition, SCC and ultrasonic of udder quarter were followed for 1 month, confirming that pre-milking sagittal PSD of mammary gland value could explain the SCC variation in milk. The current study demonstrated that the ultrasonographic examination of the udder could be one of the complementary tools for diagnosing subclinical mastitis in buffaloes.

Microbiological Diagnoses on Clinical Mastitis—Comparison between Diagnoses Made in Veterinary Clinics versus in Laboratory Applying MALDI-TOF MS

The present study compares the diagnoses on clinical bovine mastitis made in veterinary clinics using conventional diagnostic methods with diagnoses on the same samples made by a veterinary reference laboratory using MALDI-TOF MS as diagnostics. The study enables targeted and evidence-based consulting on prudent mastitis diagnostics and related antibiotic usage. In total, 492 samples from clinical mastitis were included. When applying MALDI-TOF MS as gold standard, only 90 out of 492 diagnoses made in veterinary clinics, equal to 18%, were correct. Four main findings were important: (1) the veterinary clinics overlooked contamination in mastitis samples; (2) the veterinary clinics only assigned 2 fully correct diagnoses out of 119 samples with mixed growth cultures; (3) the veterinary clinics made close to half of their diagnoses on pure culture erroneously; (4) the veterinary clinics applied a limited number of the relevant pathogen identifications on pure culture samples. Altogether, the present study shows that a large part of Danish clinical mastitis cases are misdiagnosed. Lack of correct diagnoses and diagnostic quality control may lead to the choice of wrong treatment and thus hamper prudent use of antibiotics. Hence, the present study warns a risk of overuse of antibiotics in Denmark. Consequently, the present study calls for training of veterinary clinics in diagnostics of mastitis pathogens and national guidelines on quality assurance of mastitis diagnostics.

A pump-free microfluidic device for fast magnetic labeling of ischemic stroke biomarkers

This research proposes a low-cost and simple operation microfluidic chip to enhance the magnetic labeling efficiency of two ischemic stroke biomarkers: cellular fibronectin (c-Fn) and matrix metallopeptidase 9 (MMP9). This fully portable and pump-free microfluidic chip is operated based on capillary attractions without any external power source and battery. It uses an integrated cellulose sponge to absorb the samples. At the same time, a magnetic field is aligned to hold the target labeled by the magnetic nanoparticles (MNPs) in the pre-concentrated chamber. By using this approach, the specific targets are labeled from the beginning of the sampling process without preliminary sample purification. The proposed study enhanced the labeling efficiency from 1 h to 15 min. The dynamic interactions occur in the serpentine channel, while the crescent formation of MNPs in the pre-concentrated chamber, acting as a magnetic filter, improves the biomarker-MNP interaction. The labeling optimization by the proposed device influences the dynamic range by optimizing the MNP ratio to fit the linear range across the clinical cutoff value. The limits of detection (LODs) of 2.8 ng/mL and 54.6 ng/mL of c-Fn measurement were achieved for undiluted and four times dilutions of MNP, respectively. While for MMP9, the LODs were 11.5 ng/mL for undiluted functionalized MNP and 132 ng/mL for four times dilutions of functionalized MNP. The results highlight the potential use of this device for clinical sample preparation and specific magnetic target labeling. When combined with a detection system, it could also be used as an integrated component of a point-of-care platform.

Evaluation of a rapid coliform detection kit from clinical mastitis milk using colloidal gold nanoparticle-based immunochromatographic strips

The accurate identification of mastitis‐causing bacteria assists in effective management by both dairy farmers and veterinarians and can be used to implement the selective use of antimicrobials for treatment. The purpose of this study was to evaluate the ability of our developed anti–ribosomal protein-L7/L12 antibody–coated immunochromatographic strip (ICS) test to detect coliforms in milk by comparing the results with the bacteriological culture method. We investigated the performance of the ICS test as compared with the bacteriological culture method using 308 milk samples from clinical bovine mastitis. First, to determine the optimal ICS test cutoff point for detecting coliform mastitis, we developed a receiver-operating characteristic curve. The result showed that the cutoff point was at 0.5 of our index. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value of the ICS test were 81.3%, 84.8%, 69.2%, and 91.54%, respectively. As the clinical signs increased in severity, the F-measure, a weighted harmonic mean of the sensitivity and overall PPV performance, increased. Because it is especially important to treat clinical mastitis appropriately in the early stages of detection, the ICS test, which can be used by both dairy farmers and veterinarians on dairy farms, is considered to be a useful tool for detecting coliform mastitis, which often presents with severe signs.

Aptamer-based diagnostic and therapeutic approaches in animals: Current potential and challenges

Fast and precise diagnosis of infectious and non-infectious animal diseases and their targeted treatments are of utmost importance for their clinical management. The existing biochemical, serological and molecular methods of disease diagnosis need improvement in their specificity, sensitivity and cost and, are generally not amenable for being used as points-of-care (POC) device. Further, with dramatic changes in environment and farm management practices, one should also arm ourselves and prepare for emerging and re-emerging animal diseases such as cancer, prion diseases, COVID-19, influenza etc. Aptamer – oligonucleotide or short peptides that can specifically bind to target molecules – have increasingly become popular in developing biosensors for sensitive detection of analytes, pathogens (bacteria, virus, fungus, prions), drug residues, toxins and, cancerous cells. They have also been proven successful in the cellular delivery of drugs and targeted therapy of infectious diseases and physiological disorders. However, the in vivo application of aptamer-mediated biosensing and therapy in animals has been limited. This paper reviews the existing reports on the application of aptamer-based biosensors and targeted therapy in animals. It also dissects the various modifications to aptamers that were found to be successful in in vivo application of the aptamers in diagnostics and therapeutics. Finally, it also highlights major challenges and future directions in the application of aptamers in the field of veterinary medicine.

Bovine mastitis inflammatory assessment using silica coated ZnO-NPs induced fluorescence of NAGase biomarker assay

Bovine mastitis (BM) is the most common inflammatory disease in the dairy sector worldwide, originated from bacterial invasion onto the mammary gland. Early BM detection is crucial for identifying new pathogenic infections within the dairy herd, which can be alleviated by antimicrobial therapy. N-acetyl-β-D-glucosaminidase (NAGase) is a prominent BM inflammatory biomarker secreted onto the blood circulation upon pathogenesis and then released into milk, capable of separating healthy quarters from subclinical and clinical BM cases. Herein, we report on a sensitive differentiation assay of BM severity based on enhanced fluorescence emission of a conventional NAGase activity assay. The addition of silica-coated zinc oxide nanoparticles induces non-radiative energy transfer to the lysosomal reaction products, thus leading to enhanced fluorescence (above 3-fold). Various milk qualities within the entire inflammatory spectrum were evaluated by the modified fluorescence assay with respect to non-infected milk. The amplified emission values differentiate between two predominant BM causative pathogens (Streptococcus dysgalactiae and Escherichia coli) at various somatic cell counts. In general, the presented concept offers an efficient, simple, cost-effective fluorescence signal augmentation for mastitis identification, thus offering means to diagnose the severity of the associated disease.

MasPA: A Machine Learning Application to Predict Risk of Mastitis in Cattle from AMS Sensor Data

Mastitis is a common disease that prevails in cattle owing mainly to environmental pathogens; they are also the most expensive disease for cattle in dairy farms. Several prevention and treatment methods are available, although most of these options are quite expensive, especially for small farms. In this study, we utilized a dataset of 6600 cattle along with several of their sensory parameters (collected via inexpensive sensors) and their prevalence to mastitis. Supervised machine learning approaches were deployed to determine the most effective parameters that could be utilized to predict the risk of mastitis in cattle. To achieve this goal, 26 classification models were built, among which the best performing model (the highest accuracy in the shortest time) was selected. Hyper parameter tuning and K-fold cross validation were applied to further boost the top model’s performance, while at the same time avoiding bias and overfitting of the model. The model was then utilized to build a GUI application that could be used online as a web application. The application can predict the risk of mastitis in cattle from the inhale and exhale limits of their udder and their temperature with an accuracy of 98.1% and sensitivity and specificity of 99.4% and 98.8%, respectively. The full potential of this application can be utilized via the standalone version, which can be easily integrated into an automatic milking system to detect the risk of mastitis in real time.

Novel ways to use sensor data to improve mastitis management

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

Do we automatically detect health- or general welfare-related issues? A framework

The early detection of health disorders is a central goal in livestock production. Thus, a great demand for technologies enabling the automated detection of such issues exists. However, despite decades of research, precision livestock farming (PLF) technologies with sufficient accuracy and ready for implementation on commercial farms are rare. A central factor impeding technological development is likely the use of non-specific indicators for various issues. On commercial farms, where animals are exposed to changing environmental conditions, where they undergo different internal states and, most importantly, where they can be challenged by more than one issue at a time, such an approach leads inevitably to errors. To improve the accuracy of PLF technologies, the presented framework proposes a categorization of the aim of detection of issues related to general welfare, disease and distress and defined disease. Each decision level provides a different degree of information and therefore requires indicators varying in specificity. Based on these considerations, it becomes apparent that while most technologies aim to detect a defined health issue, they facilitate only the identification of issues related to general welfare. To achieve detection of specific issues, new indicators such as rhythmicity patterns of behaviour or physiological processes should be examined.

Bovine mastitis prevention and control in the post-antibiotic era

Mastitis is the most important disease in the dairy industry. Antibiotics are considered to be the first choice in the treatment of the disease. However, the problem of antibiotic residue and antimicrobial resistance, in addition to the impact of antibiotic abuse on public health, leads to many restrictions on uncontrolled antibiotic therapy in the dairy sector worldwide. Researchers have investigated novel therapeutic approaches to replace the use of antibiotics in mastitis control. These efforts, supported by the revolutionary development of nanotechnology, stem cell assays, molecular biological tools, and genomics, enabled the development of new approaches for mastitis-treatment and control. The present review discusses recent concepts to control mastitis such as breeding of mastitis-resistant dairy cows, the development of novel diagnostic and therapeutic tools, the application of communication technology as an educational and epidemiological tool, application of modern mastitis vaccines, cow drying protocols, teat disinfection, housing, and nutrition. These include the application of nanotechnology, stem cell technology, photodynamic and laser therapy or the use of traditional herbal medical plants, nutraceuticals, antibacterial peptides, bacteriocins, antibodies therapy, bacteriophages, phage lysins, and probiotics as alternatives to antibiotics.

Genes associated with somatic cell count index in Brown Swiss cattle

Subclinical mastitis (SM) is one of the most common diseases of cows in milk production herds caused by contagious and/or environmental pathogens. Since there are no visible abnormalities in the milk or udder, the detection of SM requires special diagnostic tests. Somatic cell count (SCC) is the most common test used to detect changes in milk due to the inflammatory process. Previously, we developed somatic cell count index (SCCI), a new method for the accurate prediction of milk yield losses caused by elevated SCC. The aim of this study was to identify new candidate genetic markers for SCCI in the Slovenian population of Brown Swiss (BS) cattle. For that purpose, we analyzed samples of BS cows, which were genotyped using single-nucleotide polymorphism (SNP) microarray ICBF International Dairy and Beef v3 (ICBF, Ireland) for a total of 53,262 SNP markers. After quality control, the set of 18,136 SNPs was used in association analysis. Our association analysis revealed that 130 SNPs were associated with SCCI, which were used for haplotype and overlap analysis. Haplotypes generated from the genotyped data for those 130 SNPs revealed 10 haplotype blocks among 22 SNPs. Additionally, all 130 SNPs, mastitis-related quantitative trait loci, and protein-coding genes are shown on the bovine genome. Overlap analysis shows that the majority of significantly associated SNPs (70) are intergenic, while 60 SNPs are mapped within, upstream, or downstream of the protein-coding genes. However, those genes can serve as strong candidate genes for the marker-assisted selection programs in our and possibly other populations of cattle.