Evidence map›Paper›PMID 38849801›Full record

ArticleBMC veterinary research2024

Presence of pathogen DNA in milk harvested from quarters is associated to changes in cows' milk yield and composition.

Silvia Magro, Elena Visentin, Angela Costa, Mauro Penasa, Filippo Cendron, Paolo Moroni, Elena Chiarin, Martino Cassandro, Matteo Santinello, Massimo De Marchi

Abstract read
In one paragraph

Article in BMC veterinary research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Silvia MagroDepartment of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Legnaro, 35020, Italy.
Elena VisentinDepartment of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Legnaro, 35020, Italy.
Angela CostaDepartment of Veterinary Medical Sciences, Alma Mater Studiorum University of Bologna, Ozzano dell'Emilia, 40064, Italy. angela.costa2@unibo.it.
Mauro PenasaDepartment of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Legnaro, 35020, Italy.
Filippo CendronDepartment of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Legnaro, 35020, Italy.
Paolo MoroniDepartment of Veterinary Medicine and Animal Sciences, University of Milan, Lodi, 26900, Italy.
Elena ChiarinDepartment of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Legnaro, 35020, Italy.
Martino CassandroDepartment of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Legnaro, 35020, Italy.
Matteo SantinelloDepartment of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Legnaro, 35020, Italy.
Massimo De MarchiDepartment of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Legnaro, 35020, Italy.

Funding

Breeders Association of Veneto Region (ARAV) DOC-AR 2021
6 · The paper itself

Abstract

backgroundIntramammary infection is the result of invasion and multiplication of microorganisms in the mammary gland and commonly leads to mastitis in dairy animals. Although much has been done to improve cows' udder health, mastitis remains a significant and costly health issue for dairy farmers, especially if subclinical. In this study, quarter milk samples from clinically healthy cows were harvested to detect pathogens via quantitative PCR (qPCR) and evaluate changes in individual milk traits according to the number of quarters infected and the type of microorganism(s). A commercial qPCR kit was used for detection of Mycoplasma bovis, Mycoplasma spp., Staphylococcus aureus, coagulase-negative staphylococci (CNS), Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Prototheca spp., Escherichia coli, Klebsiella spp., Enterococcus spp. and Lactococcus lactis ssp. lactis. Quarter and pooled milk information of 383 Holstein, 132 Simmental, 129 Rendena, and 112 Jersey cows in 9 Italian single-breed herds was available.

resultsAmong the cows with pathogen(s) present in at least 1 quarter, CNS was the most commonly detected DNA, followed by Streptococcus uberis, Mycoplasma bovis, and Streptococcus agalactiae. Cows negative to qPCR were 206 and had the lowest milk somatic cell count. Viceversa, cows with DNA isolated in ≥ 3 quarters were those with the highest somatic cell count. Moreover, when major pathogens were isolated in ≥ 3 quarters, milk had the lowest casein index and lactose content. In animals with pathogen(s) DNA isolated, the extent with whom milk yield and major solids were impaired did not significantly differ between major and minor pathogens.

conclusionsThe effect of the number of affected quarters on the pool milk quality traits was investigated in clinically healthy cows using a commercial kit. Results remark the important negative effect of subclinical udder inflammations on milk yield and quality, but more efforts should be made to investigate the presence of untargeted microorganisms, as they may be potentially dangerous for cows. For a smarter use of antimicrobials, analysis of milk via qPCR is advisable - especially in cows at dry off - to identify quarters at high risk of inflammation and thus apply a targeted/tailored treatment.

Indexed as

Mastitis, BovineMilkAnimalsCattleDNA, BacterialFemaleLactationReal-Time Polymerase Chain ReactionStreptococcusDNA, BacterialIntramammary infectionqPCRSterile milk samplingUdder health

Identifiers

PMID38849801
PMCPMC11157801

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.