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Droplet digital PCR quantification of selected microRNAs in raw mastitic cow’s milk from the west of Poland Cover

Droplet digital PCR quantification of selected microRNAs in raw mastitic cow’s milk from the west of Poland

Journal of Veterinary Research
Volume 67 (2023): Issue 4 (December 2023)
By: Sebastian Smulski,  Marcin Pszczoła,  Monika Stachowiak,  Adrianna Bilińska and  Izabela Szczerbal  
Open Access
|Dec 2023

Figures & Tables

Fig. 1.

Correlation between log(SCC) and concentrations of miR-21a, miR-92a and miR-146a in healthy and mastitic milk samples. The grey area below the figures indicates the 95% confidence interval. Low – somatic cell count < 200,000/mL; Medium – 200,000/mL ≤ somatic cell count < 1,000,000/mL; High – somatic cell count ≥ 1,000,000/mL
Correlation between log(SCC) and concentrations of miR-21a, miR-92a and miR-146a in healthy and mastitic milk samples. The grey area below the figures indicates the 95% confidence interval. Low – somatic cell count < 200,000/mL; Medium – 200,000/mL ≤ somatic cell count < 1,000,000/mL; High – somatic cell count ≥ 1,000,000/mL

Fig. 2.

Correlation between log(SCC) and the relative expression levels of miR-21a and miR-146a in healthy and mastitic milk samples. The grey area below the figures indicates the 95% confidence interval. Low – somatic cell count < 200,000/mL; Medium – 200,000/mL ≤ somatic cell count < 1,000,000/mL; High – somatic cell count ≥ 1,000,000/mL
Correlation between log(SCC) and the relative expression levels of miR-21a and miR-146a in healthy and mastitic milk samples. The grey area below the figures indicates the 95% confidence interval. Low – somatic cell count < 200,000/mL; Medium – 200,000/mL ≤ somatic cell count < 1,000,000/mL; High – somatic cell count ≥ 1,000,000/mL

Fig. 3.

Relative expression levels of miR-21a and miR-146a in three groups based on somatic cell counts and presence of a mastitoge. a, b – significant differences (P-value < 0.05)
Relative expression levels of miR-21a and miR-146a in three groups based on somatic cell counts and presence of a mastitoge. a, b – significant differences (P-value < 0.05)

Prevalence of pathogens isolated from mastitic-quarter milk samples

PathogennPrevalence (%)
Streptococcus uberis69.23
Streptococcus dysgalactiae11.54
Staphylococcus aureus11.54
Coagulase-negative staphylococci46.15
Escherichia coli11.54
Klebsiella spp.23.08
No growth3350.77
Contamination1726.15

Performance of the K-nearest neighbour regression model, by somatic cell count class in healthy and mastitic milk samples

ParameterThree-class analysisTwo-class analysis
LowMediumHighLow
Sensitivity0.670.670.820.98
Specificity0.850.750.980.95
Positive predictive value0.630.620.950.98
Negative predictive value0.870.790.910.95
Balanced accuracy0.760.710.900.97
DOI: https://doi.org/10.2478/jvetres-2023-0062 | Journal eISSN: 2450-8608
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Language: English
Page range: 583 - 591
Submitted on: Jun 15, 2023
|
Accepted on: Oct 27, 2023
|
Published on: Dec 19, 2023
Published by: National Veterinary Research Institute in Pulawy
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
biomarker,
bovine mastitis,
ddPCR,
microRNA,
raw milk
Related subjects:
Life sciences,
Molecular biology,
Microbiology and virology,
Life sciences, other,
Medicine,
Veterinary medicine

© 2023 Sebastian Smulski, Marcin Pszczoła, Monika Stachowiak, Adrianna Bilińska, Izabela Szczerbal, published by National Veterinary Research Institute in Pulawy
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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