摘要
Background:Mammary health is important for transition dairy cows and has been well recognized to exert decisive effects on animal welfare.However,the factors influencing mammary health are still unclear.Differential somatic cell count(DSCC)could reflect the mastitis risk since it is the percentage of neutrophils plus lymphocytes in total somatic cells and could be reflective of mammary health of dairy cows.This work aimed to investigate the assessment and prognosis of the health of transition cows based on blood neutrophil extracellular traps(NETs).Results:Eighty-four transition Holstein dairy cows were selected.The serum was sampled in all the animals at week 1 pre-and postpartum,and milk was sampled at week 1 postpartum.Based on the DSCC in milk at week 1,cows with lower(7.4%±4.07%,n=15)and higher(83.3%±1.21%,n=15)DSCCs were selected.High DSCC cows had higher levels of red blood cell counts(P<0.05),hemoglobin(P=0.07),and hematocrit(P=0.05),higher concentrations of serum oxidative variables[reactive oxygen species(P<0.05),malondialdehyde(P<0.05),protein carbonyl(P<0.05),and 8-hydroxy-2-deoxyguanosine(P=0.07)],higher levels of serum and milk NETs(P<0.05)and blood-milk barrier indicators,including serumβ-casein(P=0.05)and milk immunoglobulin G2(P=0.09),than those of low DSCC cows.In addition,lower concentrations of serum nutrient metabolites(cholesterol and albumin)(P<0.05)and a lower level of serum deoxyribonuclease I(P=0.09)were observed in high DSCC cows than in low DSCC cows.Among the assessments performed using levels of the three prepartum serum parameters(NETs,deoxyribonuclease I andβ-casein),the area under the curve(0.973)of NETs was the highest.In addition,the sensitivity(1.00)and specificity(0.93)were observed for the discrimination of these cows using NETs levels with a critical value of 32.2 ng/mL(P<0.05).Conclusions:The formation of NETs in blood in transition dairy cows may damage the integrity of the blood-milk barrier and thereby increase the risk for mastitis in postpartum cows.
基金
financially supported by grants from the China-USA Intergovernmental Collaborative Project in S&T Innovation under the National Key R&D Program (No.2018YFE0111700,Beijing)。
