Evidence map›Paper›PMID 39872610›Full record

ArticleFrontiers in veterinary science2024

Determining causal pathogens and inflammatory state of mastitis in dairy cows via Gram staining of precipitates in milk.

Naoki Suzuki, Naoki Isobe

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
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

2 authors.

Naoki SuzukiGraduate School of Integrated Sciences for Life, Hiroshima University, Higashihiroshima, Hiroshima, Japan.
Naoki IsobeGraduate School of Integrated Sciences for Life, Hiroshima University, Higashihiroshima, Hiroshima, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early detection of bovine mastitis-causing pathogens is necessary for treatment. As culturing methods are time-consuming, a more rapid detection technique is required. This study investigated the sensitivity, specificity, and detection limit of Gram staining of milk precipitates (milk Gram stain, MGS) to detect bovine mastitis-causing pathogens in milk, as well as the potential of MGS to diagnose inflammation by counting polymorphonuclear leukocytes (PMN). MGS was performed on spontaneous mastitis cases. Culture methods were also used as reference standards to calculate the sensitivity, specificity, and bacterial load in milk to determine the detection limit of MGS. PMN in the mastitic milk were counted using Gram staining. Further, somatic cell counts (SCC), interleukin (IL)-6, IL-8, tumor necrosis factor (TNF)-α, IL-10 and serum amyloid A (SAA) concentrations in mastitic milk were measured using cell counting and enzyme-linked immunosorbent assay. The sensitivity and specificity for all pathogens were 0.62 and 0.90, for Gram-positive were 0.67 and 0.90, and for Gram-negative were 0.50 and 1.00, respectively. The detection limits for Gram-positive and Gram-negative bacteria were 1,560 and 4,680 cfu/mL, respectively. SCC were significantly positively correlated with PMN, milk IL-6, TNF-α, and SAA concentrations, whereas PMN were significantly negatively correlated with milk IL-10 concentration. Our results suggest that MGS may be applied as a rapid method to identify causal pathogens of mastitis before culture results are determined and may also estimate inflammatory status which cannot be detected with SCC. Further clinical trials are required to elucidate whether MGS is useful in clinical veterinary settings.

Indexed as

bovinediagnosisGram staininginflammationmastitis

Identifiers

PMID39872610
PMCPMC11770005

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.