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Record W4310196553 · doi:10.3390/ani12233288

Diagnosing Intramammary Infection: Meta-Analysis and Mapping Review on Frequency and Udder Health Relevance of Microorganism Species Isolated from Bovine Milk Samples

2022· review· en· W4310196553 on OpenAlexafffundabout
Daryna Kurban, Jean‐Philippe Roy, Fidèle Kabera, Annie Fréchette, Maryse Michèle Um, A. Albaaj, Sam Rowe, S. Godden, Pamela R. F. Adkins, John R. Middleton, Marie-Lou Gauthier, Greg Keefe, T.J. DeVries, D.F. Kelton, P. Moroni, Marcos Veiga dos Santos, Herman W. Barkema, Simon Dufour

Bibliographic record

VenueAnimals · 2022
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversity of Prince Edward IslandMinistère de l'Agriculture, des Pêcheries et de l'AlimentationUniversity of CalgaryUniversity of GuelphUniversité de Montréal
FundersAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsMicroorganismUdderStaphylococcus epidermidisMastitisStaphylococcusBovine milkBiologySomatic cell countMicrobiologyVeterinary medicineStaphylococcus aureusFood scienceMedicineIce calvingBacteriaLactationPregnancy

Abstract

fetched live from OpenAlex

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry provides accurate species-level identification of many, microorganisms retrieved from bovine milk samples. However, not all those microorganisms are pathogenic. Our study aimed to: (1) determine the species-specific prevalence of microorganisms identified in bovine milk of apparently healthy lactating quarters vs. quarters with clinical mastitis (CM); and (2) map current information and knowledge gaps on udder health relevance of microorganisms retrieved from bovine milk samples. A mixed study design (meta-analysis and mapping review) was chosen. We gathered several large Canadian, US and Brazilian data sets of MALDI-TOF results for organisms cultured from quarter milk samples. For meta-analysis, two datasets (apparently healthy quarters vs. CM samples) were organized. A series of meta-analyses was conducted to determine microorganisms’ prevalence. Then, each species reported was searched through PubMed to investigate whether inflammation (increased somatic cell count (SCC) or signs of CM) was associated with microorganism’s recovery from milk. A total of 294 different species of microorganisms recovered from milk samples were identified. Among 50,429 quarter-milk samples from apparently healthy quarters, the 5 most frequent species were Staphylococcus chromogenes (6.7%, 95% CI 4.5–9.2%), Aerococcus viridans (1.6%, 95% CI 0.4–3.5%), Staphylococcus aureus (1.5%, 95% CI 0.5–2.8%), Staphylococcus haemolyticus (0.9%, 95% CI 0.4–1.5%), and Staphylococcus epidermidis (0.7%, 95% CI 0.2–1.6%). Among the 43,924 quarter-milk CM samples, the 5 most frequent species were Escherichia coli (11%, 95% CI 8.1–14.3%), Streptococcus uberis (8.5%, 95% CI 5.3–12.2%), Streptococcus dysgalactiae (7.8%, 95% CI 4.9–11.5%), Staphylococcus aureus (7.8%, 95% CI 4.4–11.9%), and Klebsiella pneumoniae (5.6%, 95% CI 3.4–8.2%). When conducting the PubMed literature search, there were 206 species identified by MALDI-TOF for which we were not able to find any information regarding their association with CM or SCC. Some of them, however, were frequently isolated in our multi-country dataset from the milk of quarters with CM (e.g., Citrobacter koseri, Enterococcus saccharolyticus, Streptococcus gallolyticus). Our study provides guidance to veterinarians for interpretation of milk bacteriology results obtained using MALDI-TOF and identifies knowledge gaps for future research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.024
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.035
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.199
GPT teacher head0.328
Teacher spread0.129 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations40
Published2022
Admission routes3
Has abstractyes

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