scholarly journals Association of bovine CXCL8 polymorphism with clinical mastitis and fertility trait in Polish HF cattle

2021 ◽  
Vol 3 (2) ◽  
pp. 9
Author(s):  
Urszula Czarnik ◽  
Marta Barcewicz ◽  
Mateusz Sachajko ◽  
Magdalena Herudzińska ◽  
Kacper Żukowski ◽  
...  
Keyword(s):  
Clinical Mastitis ◽  
Fertility Trait

Microbial Causes of She Camels’ Subclinical and Clinical Mastitis in South Sinai, Egypt

2020 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Marwa Abo Hashem ◽  
Sara Ibrahim ◽  
Azza Goda ◽  
Mohamed Enany
Keyword(s):  
Clinical Mastitis ◽  
South Sinai

Serum Metabolic Markers Pre and Postpartum in Holstein Cows According to the Mastitis Occurrence

2018 ◽  
Vol 46 (1) ◽  
Author(s):  
Elizabeth Schwegler ◽  
Augusto Schneider ◽  
Ana Rita Tavares Krause ◽  
Paula Montagner ◽  
Eduardo Schmitt ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Milk Production ◽  
Postpartum Period ◽  
Clinical Mastitis ◽  
Serum Markers ◽  
Holstein Cows ◽  
Economic Losses ◽  
Phosphorus Concentration ◽  
Extensive Management ◽  
Early Postpartum

 Background: Bovine mastitis causes major economic losses for milk producers by reducing the quantity and the quality of the milk or even leading to the complete loss of the mammary gland secretory capacity. During the transition period, dairy cows are susceptible to infectious diseases; therefore, markers that allow early identification of cows in higher risk of developing diseases are especially useful at this time. Therefore, the aim of this study was to evaluate serum markers in the pre and postpartum of multiparous dairy cows with clinical mastitis and with health condition in the postpartum period in a semi-extensive management system.Materials, Methods & Results: Thirty-Six Holstein cows were monitored daily during milking until 59 days postpartum and were categorized according to the pre-milking strip cup test into clinical mastitis (mastitis group (MG)) and absence of symptoms (control group (CG)) that were negative to the test, representing the health cows. All cows were reared as one group and maintained in a semi-extensive pasture-based system. Blood samples were collected weekly after morning milking via venipuncture of the coccinea vein into tubes without anticoagulant and grouped for prepartum (-21 to 0 days from calving), early postpartum (0 to 30 days from calving), and late postpartum (30 to 59 days from calving) periods. Milk production was recorded daily. The serum markers albumin, aspartate aminotransferase (AST), phosphorus, gamma-glutamyltransferase (GGT) and non-esterified fatty acids (NEFA) were measured. Statistical analyses were performed using SAS®. The cases of clinical mastitis occurred on average at 37.2 ± 4.9 days postpartum. Health cows (CG) had higher milk production compared to the mastitis group (MG) only in the late postpartum period (P < 0.05). There was no difference among groups for albumin and NEFA concentrations in all periods evaluated (P > 0.05). In the early postpartum period the AST activity was higher in CG than in MG (P = 0.02). The GGT enzyme tended to be more concentrated in the CG than in the MG during the early (P = 0.06) and late (P = 0.08) postpartum periods. Late postpartum phosphorus concentration was lower for MG than CG (P = 0.04). In the prepartum and early postpartum periods, there was no difference among groups for phosphorus concentration (P > 0.05).Discussion: A decrease in milk production in MG compared to CG observed in late postpartum period was due to the inci­dence of mastitis observed around 37 days postpartum. Cows that presented clinical mastitis in the postpartum period did not differ in the blood concentration of NEFA in the prepartum period. In the late postpartum period higher concentration of phosphorus was observed in the CG than in MG, indicating that animals affected by mastitis may be in the weakest energy status. Regarding liver health, the concentration of AST was higher in the recent postpartum period for CG, in disagree­ment with previous studies that related AST to tissue injury caused by mastitis. The GGT enzyme tended to had higher concentrations in CG than MG during the whole postpartum period and may be related to increased hepatic metabolism due to higher production. There were no changes in albumin levels among healthy and mastitis cows, indicating that this marker can not be used to predict clinical mastitis. There were no metabolic alterations in the prepartum period related to the occurrence of postpartum mastitis in multiparous cows in a semi-extensive management system.Keywords: AST, dairy cows, NEFA.

A quantitative evaluation of some factors affecting the non-fatty solids of cow's milk

1960 ◽  
Vol 27 (1) ◽  
pp. 19-32 ◽  
Author(s):  
W. H. Alexander ◽  
F. B. Leech
Keyword(s):  
Cell Count ◽  
Residual Effect ◽  
Clinical Mastitis ◽  
High Cell ◽  
Factors Affecting ◽  
Stage Of Lactation ◽  
Cell Counts ◽  
Satisfactory Analysis ◽  
The Difference ◽  
Image Position

SummaryTen farms in the county of Durham took part in a field study of the effects of feeding and of udder disease on the level of non-fatty solids (s.n.f.) in milk. Statistical analysis of the resulting data showed that age, pregnancy, season of the year, and total cell count affected the percentage of s.n.f. and that these effects were additive and independent of each other. No effect associated with nutritional changes could be demonstrated.The principal effects of the factors, each one freed from effects of other factors, were as follows:Herds in which s.n.f. had been consistently low over a period of years were compared with herds in which s.n.f. had been satisfactory. Analysis of the data showed that about 70% of the difference in s.n.f. between these groups could be accounted for by differences in age of cow, stage of lactation, cell count and breed.There was some evidence of a residual effect following clinical mastitis that could not be accounted for by residual high cell counts.The within-cow regression of s.n.f. on log cell count calculated from the Durham data and from van Rensburg's data was on both occasions negative.The implications of these findings are discussed, particularly in relation to advisory work.

scholarly journals An Untargeted Metabolomics Investigation of Milk from Dairy Cows with Clinical Mastitis by 1H-NMR

Foods ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1707
Author(s):  
Chenglin Zhu ◽  
Kaiwei Tang ◽  
Xuan Lu ◽  
Junni Tang ◽  
Luca Laghi
Keyword(s):  
Dairy Cows ◽  
1H Nmr ◽  
Tricarboxylic Acid Cycle ◽  
Tca Cycle ◽  
Quantitative Information ◽  
Clinical Mastitis ◽  
Economic Losses ◽  
Resonance Spectroscopy ◽  
Mastitic Milk ◽  
Chemical Groups

Mastitis is one of the diseases with the highest incidence in dairy cows, causing huge economic losses to the dairy industry all over the world. The aim of the study was to characterize mastitic milk metabolome through untargeted nuclear magnetic resonance spectroscopy (1H-NMR). Taking advantage of the high reproducibility of 1H-NMR, we had the opportunity to provide quantitative information for all the metabolites identified. Fifty-four molecules were characterized, sorted mainly into the chemical groups, namely amino acids, peptides and analogues, carbohydrates and derivates, organic acids and derivates, nucleosides, nucleotides and analogues. Combined with serum metabolomic investigations, several pathways were addressed to explain the mechanisms of milk metabolome variation affected by clinical mastitis, such as tricarboxylic acid cycle (TCA cycle) and phenylalanine, tyrosine and tryptophan biosynthesis. These results provide a further understanding of milk metabolome altered by clinical mastitis, which can be used as a reference for the further milk metabolome investigations.

scholarly journals Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alexandre Maciel-Guerra ◽  
Necati Esener ◽  
Katharina Giebel ◽  
Daniel Lea ◽  
Martin J. Green ◽  
...  
Keyword(s):  
Machine Learning ◽  
Mass Spectrometry ◽  
Treatment Success ◽  
Clinical Mastitis ◽  
Supervised Machine Learning ◽  
Structural Protein ◽  
Cohen’S Kappa ◽  
Maldi Tof ◽  
Streptococcus Uberis ◽  
Cohen's Kappa

AbstractStreptococcus uberis is one of the leading pathogens causing mastitis worldwide. Identification of S. uberis strains that fail to respond to treatment with antibiotics is essential for better decision making and treatment selection. We demonstrate that the combination of supervised machine learning and matrix-assisted laser desorption ionization/time of flight (MALDI-TOF) mass spectrometry can discriminate strains of S. uberis causing clinical mastitis that are likely to be responsive or unresponsive to treatment. Diagnostics prediction systems trained on 90 individuals from 26 different farms achieved up to 86.2% and 71.5% in terms of accuracy and Cohen’s kappa. The performance was further increased by adding metadata (parity, somatic cell count of previous lactation and count of positive mastitis cases) to encoded MALDI-TOF spectra, which increased accuracy and Cohen’s kappa to 92.2% and 84.1% respectively. A computational framework integrating protein–protein networks and structural protein information to the machine learning results unveiled the molecular determinants underlying the responsive and unresponsive phenotypes.

Detection of virulence-associated genes in Staphylococcus aureus isolated from bovine clinical mastitis milk samples in Guangxi

2012 ◽  
Vol 44 (8) ◽  
pp. 1821-1826 ◽  
Author(s):  
Feng Li Yang ◽  
Xiao Shan Li ◽  
Xian Wei Liang ◽  
Xiu Fang Zhang ◽  
Guang Sheng Qin ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Clinical Mastitis ◽  
Milk Samples
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