A First Investigation into the Use of Differential Somatic Cell Count as a Predictor of Udder Health in Sheep.
Marco ToloneSalvatore MastrangeloMaria Luisa ScatassaMaria Teresa SardinaSilvia RiggioAngelo MoscarelliAnna Maria SuteraBaldassare PortolanoRiccardo NegriniPublished in: Animals : an open access journal from MDPI (2023)
Differential somatic cell count (DSCC), the percentage of somatic cell count (SCC) due to polymorphonuclear leukocytes (PMNs) and lymphocytes (LYMs), is a promising effective diagnostic marker for dairy animals with infected mammary glands. Well-explored in dairy cows, DSCC is also potentially valid in sheep, where clinical and subclinical mastitis outbreaks are among the principal causes of culling. We pioneered the application of DSCC in dairy ewes by applying receiver-operating characteristic (ROC) curve analysis to define the most accurate thresholds to facilitate early discrimination of sheep with potential intramammary infection (IMI) from healthy animals. We tested four predefined SCC cut-offs established in previous research. Specifically, we applied SCC cut-offs of 265 × 10 3 cells/mL, 500 × 10 3 cells/mL, 645 × 10 3 cells/mL, and 1000 × 10 3 cells/mL. The performance of DSCC as a diagnostic test was assessed by examining sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), and area under curve (AUC) analyses. The designated threshold value for DSCC in the detection of subclinical mastitis is established at 79.8%. This threshold exhibits Se and Sp of 0.84 and 0.81, accompanied by an AUC of 0.88. This study represents the inaugural exploration of the potential use of DSCC in sheep's milk as an early indicator of udder inflammation.
Keyphrases
- induced apoptosis
- cell cycle arrest
- dairy cows
- single cell
- peripheral blood
- cell therapy
- healthcare
- oxidative stress
- endoplasmic reticulum stress
- cell death
- gene expression
- mental health
- dna methylation
- signaling pathway
- mesenchymal stem cells
- mass spectrometry
- social media
- climate change
- health information
- infectious diseases