UNASSIGNED: Beta-glucan (β-glucan) is a polysaccharide containing β-glycosidic bonds that is an important structure part of different yeast cells.
UNASSIGNED: The purpose of the study is to characterize β-glucan obtained from Candida albicans (C. albicans) isolated from caprine mastitis.
UNASSIGNED: The β-glucan was extracted by using utilizing an Alkaline-acidic extraction technique. The dry weight of extracted β-glucan was 7.47/150 g with 4.98%.
UNASSIGNED: The findings demonstrated that the extracted β-glucan had similarity in the primary peak 5.78 of liquid samples using the method of high-performance liquid chromatography when compared to the standard form of β-glucan. However, scanning electron microscopy studies revealed that the standard of β-glucan was distinct in morphology but similar to β-glucan isolated from C. albicans in terms of particle sizes in the range of 1.60-2.65 m and the lack of cell wall traces. The findings of an investigation using energy-dispersive X-ray fluorescence spectroscopy (EDS/EDX) of extracted and standard β-glucan, showed the principal elements discovered were carbon (C), oxygen (O), and nitrogen (N). Aluminum (Al), silicon (Si), nickel (Ni), and gold (Au) were also present, but in less amounts.
UNASSIGNED: The extracted β-glucan displayed a high degree of similarity and purity to the standard β-glucan, according to the findings of Fourier transform infrared spectroscopy (FT-IR) research.

Subclinical mastitis is a common and economically significant disease that affects dairy sheep production. Thermal imaging presents a promising avenue for non-invasive detection, but existing methodologies often rely on simplistic temperature differentials, potentially leading to inaccurate assessments. This study proposes an advanced algorithmic approach integrating thermal imaging processing with statistical texture analysis and t-distributed stochastic neighbor embedding (t-SNE). Our method achieves a high classification accuracy of 84% using the support vector machines (SVM) algorithm. Furthermore, we introduce another commonly employed evaluation metric, correlating thermal images with commercial California mastitis test (CMT) results after establishing threshold conditions on statistical features, yielding a sensitivity (the true positive rate) of 80% and a specificity (the true negative rate) of 92.5%. The evaluation metrics underscore the efficacy of our approach in detecting subclinical mastitis in dairy sheep, offering a robust tool for improved management practices.

BACKGROUND: Acinetobacter lwoffii (A. lwoffii) is a Gram-negative bacteria common in the environment, and it is the normal flora in human respiratory and digestive tracts. The bacteria is a zoonotic and opportunistic pathogen that causes various infections, including nosocomial infections. The aim of this study was to identify A. lwoffii strains isolated from bovine milk with subclinical mastitis in China and get a better understanding of its antimicrobial susceptibility and resistance profile. This is the first study to analyze the drug resistance spectrum and corresponding mechanisms of A. lwoffii isolated in raw milk.
RESULTS: Four A. lwoffii strains were isolated by PCR method. Genetic evolution analysis using the neighbor-joining method showed that the four strains had a high homology with Acinetobacter lwoffii. The strains were resistant to several antibiotics and carried 17 drug-resistance genes across them. Specifically, among 23 antibiotics, the strains were completely susceptible to 6 antibiotics, including doxycycline, erythromycin, polymyxin, clindamycin, imipenem, and meropenem. In addition, the strains showed variable resistance patterns. A total of 17 resistance genes, including plasmid-mediated resistance genes, were detected across the four strains. These genes mediated resistance to 5 classes of antimicrobials, including beta-lactam, aminoglycosides, fluoroquinolones, tetracycline, sulfonamides, and chloramphenicol.
CONCLUSIONS: These findings indicated that multi-drug resistant Acinetobacter lwoffii strains exist in raw milk of bovine with subclinical mastitis. Acinetobacter lwoffii are widespread in natural environmental samples, including water, soil, bathtub, soap box, skin, pharynx, conjunctiva, saliva, gastrointestinal tract, and vaginal secretions. The strains carry resistance genes in mobile genetic elements to enhance the spread of these genes. Therefore, more attention should be paid to epidemiological surveillance and drug resistant A. lwoffii.

Mastitis is considered one of the most widespread infectious disease of cattle and buffaloes, affecting dairy herds. The current study aimed to characterize the Staphylococcus aureus isolates recovered from subclinical mastitis animals in Pothohar region of the country. A total of 278 milk samples from 17 different dairy farms around two districts of the Pothohar region, Islamabad and Rawalpindi, were collected and screened for sub clinical mastitis using California Mastitis Test. Positive milk samples were processed for isolation of Staphylococcus aureus using mannitol salt agar. The recovered isolates were analyzed for their antimicrobial susceptibility and virulence genes using disc diffusion and PCR respectively. 62.2% samples were positive for subclinical mastitis and in total 70 Staphylococcus aureus isolates were recovered. 21% of these isolates were determined to be methicillin resistant, carrying the mecA gene. S. aureus isolates recovered during the study were resistant to all first line therapeutic antibiotics and in total 52% isolates were multidrug resistant. SCCmec typing revealed MRSA SCCmec types IV and V, indicating potential community-acquired MRSA (CA-MRSA) transmission. Virulence profiling revealed high prevalence of key genes associated with adhesion, toxin production, and immune evasion, such as hla, hlb, clfA, clfB and cap5. Furthermore, the Panton-Valentine leukocidin (PVL) toxin, that is often associated with recurrent skin and soft tissue infections, was present in 5.7% of isolates. In conclusion, the increased prevalence of MRSA in bovine mastitis is highlighted by this study, which also reveals a variety of virulence factors in S. aureus and emphasizes the significance of appropriate antibiotic therapy in combating this economically burdensome disease.

Mastitis represents the biggest threat to the health and productivity of dairy cows, leading to substantial economic losses in milk production. It manifests in two forms: clinical mastitis, easily diagnosed by visible symptoms, and subclinical mastitis (SCM), which lacks overt clinical signs. SCM\'s elusive nature often results in it going undetected, thus facilitating the spread of the disease-causing agent due to lack of treatment. Finding a reliable biomarker for early SCM would reduce the possibility of mastitis spreading in the herd, reduce the need for antibiotic use and ultimately reduce milk losses for producers. Utilizing state-of-the-art proteomics techniques, 138 milk samples from dairy cows in continental Croatia underwent analysis. These samples were categorized into four groups based on the Zagreb Mastitis Test (ZMT) and microbiological analysis: lowSCC- (n = 20), lowSCC + (n = 20), medSCC + (n = 79), and highSCC + (n = 19). A total of 386 proteins were identified and quantified, with 76 proteins showing significant differential abundances among the groups. Many of these proteins are linked to the innate immune system, as well as neutrophil and platelet degranulation processes. Through fold changes observed between groups, 15 proteins exhibiting biomarker characteristics for subclinical mastitis (SCM) were identified. Among these, five proteins-cathelicidins (-1, -4, and -7), lactoferrin, and haptoglobin-showed particular promise.

Mastitis is a global production disease that needs an intelligent solution to tackle effectively. Infrared Thermography (IRT) is a non-invasive technology that could be incorporated into routine day-to-day farm activities to monitor the health status of the animals. In this study, the udder health status was routinely monitored for 30 days among 41 Murrah buffaloes via IRT and the California Mastitis Test (CMT). Further, somatic cell count (SCC), microbial identification, and milk quality parameters were also estimated for representative samples. The thermal imaging data obtained was tabulated and back propagated from the 0th day to the -10th day and front propagated from the 0th day to +10th day for all the udder quarters. Results revealed that on the 0th day, the mean of udder skin surface temperature (USST) and teat skin surface temperature (TSST) showed a difference (p < 0.05) in the sub-clinical mastitis (SCM) and clinical mastitis (CM) affected quarters to the healthy quarters, and their degree of difference was the highest. The indication of infection was signaled during the -9th to -5th day to the 0th day in SCM and CM cases. There was a steep increment in the temperature from -2nd and -1st day to the 0th day of infection. Sometimes, some quarters show an increment in temperature due to mastitis during morning hours but recover by evening milking due to the animal\'s innate immune system. Thus, the initiation period in which the udder gets assaulted is crucial in the early assessment of SCM by monitoring temperature change using IRT.

The aim of the study was to investigate the effect of the immunostimulant Mycobacterium Cell Wall Fraction (MCWF) on the treatment of S. aureus SCM by intravenous application. The study included 45 HF dairy cows in 2nd and 3rd month after parturition divided into three groups (n = 15 per group): the MC + group - cows with S. aureus SCM treated with MCWF; the MC- group - cows with S. aureus SCM, with no treatment; and the C group - the control group of healthy cow with no treatment. Samples were collected 0th (I sample), 7th (II), and 14th day (III) from the day of SCM diagnosis and on day 21st (IV). A greater influx of leukocytes was confirmed into milk after 7 days after MCWF treatment in MC + group, which was followed by increase of WBC and LYM in blood. These results support the hypothesis of effective action of MCWF, and in quarters with lower-grade infection, bacteriological cure was achieved. The MC- group had a statistically higher concentration of TBARS and CAT activity in milk, while MC + group had lower blood serum LDH activity, which indicates a positive effect of the MCWF application and a lower exposure of the tissue to lipide peroxidation and inflammation caused by S. aureus. The application of MCWF would give new possibilities in the prevention and therapy of mammary gland diseases without fear of the presence of residues and the emergence of bacterial resistance. In future studies, the effects of local and systemic application of MCWF in the treatment of S. aureus SCM should be compared.

Current research aims to generate an alternative model to classical methods in the determination of subclinical mastitis at 4 levels (healthy, suspicious, subclinical, and clinical). For this purpose, multilayer perceptron (MLP) artificial neural networks (ANN) was developed as test model. 5 variables from the physical properties of milk somatic cell count (SCC), electrical conductivity (EC), pH, density, and temperature at fore milking (TFM) were included in the model in the classification of mastitis. Model performance was validated on test data (%25) and compared with the multinomial logistic regression (MNLR). MLP model has shown a satisfactory performance with an accuracy of 95.14% and - 141 of AIC score better than the control model (MNLR) of 80.27% and - 133 AIC despite using higher number of parameters (104). Since the main problem is to diagnose subclinical mastitis, which does not cause any visible symptoms, it was important to distinguish between absolute subclinical (suspicious excluded positives) and absolute healthy (suspicious included positives) ones. Therefore, optimum cut-off threshold was evaluated for these two different scenarios with only variable SCC the gold standard indicator of subclinical mastitis and results were compared in the interpretation of model performance. The results show that the 5-variable MLP model exhibits a high sensitivity of 93.22% (AUC = 0.95 for healthy ones) at low cutoff thresholds as well. New studies should provide a better understanding by evaluating economics, sustainability, animal welfare and health aspects together to determine the optimal threshold value.

Mastitis is a common mammary gland disease of dairy cattle caused by a wide range of organisms including bacteria, fungi and algae. Mastitis contributes to economic losses of dairy farms due to reduced yield and poor quality of milk. Since the correct identification of pathogens responsible for the development of mastitis is crucial to the success of treatment, it is necessary to develop a quick and accurate test to distinguish the main pathogens causing this disease. In this paper, we describe the development of a test based on the multiplex polymerase chain reaction (PCR) method allowing for the identification of Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis and Staphylococcus aureus. When creating our test, we relied on the results from new generation sequencing (NGS) for accurate determination of species affiliation. The multiplex PCR test was verified on 100 strains including veterinary samples, ATCC and Polish Collection of Microorganisms (PCM) reference strains. The obtained results indicate that this test is accurate and displays high specificity. It may serve as a valuable molecular tool for the detection of major mastitis pathogens.

This study investigates the relationships between subclinical mastitis and milk quality with selected microRNAs in cow milk. California Mastitis Test (CMT)-positive (n = 20) and negative (n = 20) samples were compared (Experiment I). Additionally, samples with CMT-positive but microbiological-negative, as well as positive for only Staphylococcus subspecies (Staph spp.) and only Streptococcus subspecies (Strep spp.) were examined (Experiment II). Four groups were formed in Experiment II: Group I (CMT and microbiological-negative) (n = 20), Group II (CMT-positive but microbiological-negative) (n = 10), Group III (Staph spp.) (n = 5), Group IV (Strep spp.) (n = 5). While electrical conductivity, somatic cell count (SCC), malondialdehyde (MDA) increased, miR-27a-3p and miR-223 upregulated and miR-125b downregulated in the CMT-positive group in Experiment I. SCC and MDA were higher in CMT-positive groups. miR-27a-3p and miR-223 upregulated in Groups III and IV. While miR-155 is upregulated, miR-125b downregulated in Group IV. Milk fat is positively correlated with miR-148a and miR-223. As miR-27a-3p positively correlated with SCC and MDA, miR-125b negatively correlated with electrical conductivity and SCC. miR-148a and MDA were positively correlated. miR-155 was correlated with fat-free dry matter, protein, lactose, and freezing point. miR-223 was positively correlated with SCC and miR-148a. Results particularly highlight miR-27a-3p and miR-223 as potential biomarkers in subclinical mastitis, especially those caused by Staph spp. and Strep spp., while miR-148a, miR-155, and miR-223 stand out in determining milk quality.