ArticleVeterinary sciences2023
Diagnostic Screening of Bovine Mastitis Using MALDI-TOF MS Direct-Spotting of Milk and Machine Learning.
Article in Veterinary sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 13 citations in OpenAlex.
- Mastitis-Associated Bacterial Isolates and Antimicrobial Resistance in a Single Dairy Herd in the Akmola Region, Kazakhstan.Antibiotics (Basel, Switzerland) · 2026Article
- Preventive Immunology for Livestock and Zoonotic Infectious Diseases in the One Health Era: From Mechanistic Insights to Innovative Interventions.Veterinary sciences · 2025Review
- Rapid and Online Microvolume Flow-Through Dialysis Probe for Sample Preparation in Veterinary Drug Residue Analysis.Sensors (Basel, Switzerland) · 2024Article
- A New Method to Detect Buffalo Mastitis Using Udder Ultrasonography Based on Deep Learning Network.Animals : an open access journal from MDPI · 2024Article
- Effect of Tryptic Digestion on Sensitivity and Specificity in MALDI-TOF-Based Molecular Diagnostics through Machine Learning.Sensors (Basel, Switzerland) · 2023Article
- A Systematic Review of the Recent Techniques Commonly Used in the Diagnosis ofPathogens (Basel, Switzerland) · 2023Review
- Advances in Diagnostic Approaches and Therapeutic Management in Bovine Mastitis.Veterinary sciences · 2023Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Novel strategies for diagnostic screening of animal and herd health are crucial to contain disease outbreaks, maintain animal health, and maximize production efficiency. Mastitis is an inflammation of the mammary gland in dairy cows, often resulting from infection from a microorganism. Mastitis outbreaks result in loss of production, degradation of milk quality, and the need to isolate and treat affected animals. In this work, we evaluate MALDI-TOF mass spectrometry as a diagnostic for the culture-less screening of mastitis state from raw milk samples collected from regional dairies. Since sample preparation requires only minutes per sample using microvolumes of reagents and no cell culture, the technique is promising for rapid sample turnaround and low-cost diagnosis. Machine learning algorithms have been used to detect patterns embedded within MALDI-TOF spectra using a training set of 226 raw milk samples. A separate scoring set of 100 raw milk samples has been used to assess the specificity (
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Registered trials
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