Evidence map›Paper›PMID 32426375›Full record

ArticleFrontiers in veterinary science2020

Multi-Platform Detection of Small Ruminant Lentivirus Antibodies and Provirus as Biomarkers of Production Losses.

Irache Echeverría, Ricardo De Miguel, Lorena De Pablo-Maiso, Idoia Glaria, Alfredo A Benito, Ignacio De Blas, Damián De Andrés, Lluís Luján, Ramsés Reina

Open access · goldAbstract read
In one paragraph

Article in Frontiers in veterinary science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.2field-weighted citation impact, top 12% of its field
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

15 citing papers in PubMed, 27 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Irache EcheverríaAnimal Health Department, Institute of Agrobiotechnology, CSIC-Government of Navarra, Mutilva, Spain.
Ricardo De MiguelDepartment of Animal Pathology, Instituto Universitario de Investigación Mixto Agroalimentario de Aragón (IA2), University of Zaragoza, Zaragoza, Spain.
Lorena De Pablo-MaisoAnimal Health Department, Institute of Agrobiotechnology, CSIC-Government of Navarra, Mutilva, Spain.
Idoia GlariaAnimal Health Department, Institute of Agrobiotechnology, CSIC-Government of Navarra, Mutilva, Spain.
Alfredo A BenitoMolecular and Cell Biology Department, EXOPOL SL, Zaragoza, Spain.
Ignacio De BlasDepartment of Animal Pathology, Instituto Universitario de Investigación Mixto Agroalimentario de Aragón (IA2), University of Zaragoza, Zaragoza, Spain.
Damián De AndrésAnimal Health Department, Institute of Agrobiotechnology, CSIC-Government of Navarra, Mutilva, Spain.
Lluís LujánDepartment of Animal Pathology, Instituto Universitario de Investigación Mixto Agroalimentario de Aragón (IA2), University of Zaragoza, Zaragoza, Spain.
Ramsés ReinaAnimal Health Department, Institute of Agrobiotechnology, CSIC-Government of Navarra, Mutilva, Spain.
Agrobiotechnology Institute · ESUniversidad de Zaragoza · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Small ruminant lentiviruses (SRLVs) are endemic in most areas of Europe, causing a chronic infection and a multisystemic disease affecting the udder, carpal joints, lungs, and central nervous system. Due to the lack of treatments and protective vaccination strategies, infection control is focused on the identification of infected animals through serological or molecular techniques. However, antigenic and genetic heterogeneity of SRLVs represent a clear drawback for diagnosis. Infected animals may present lower animal production parameters such as birth weight or milk production and quality, depending on productive systems considered and, likely, to the diagnostic method applied. In this study, four sheep flocks dedicated to dairy or meat production were evaluated using three different ELISA and two PCR strategies to classify animal population according to SRLV infection status. Productive parameters were recorded along one whole lactation or reproductive period and compared between positive and negative animals. SRLV was present in 19% of the total population, being unequally distributed in the different flocks. Less than half of the infected animals were detected by a single diagnostic method, highlighting the importance of combining different diagnostic techniques. Statistical analysis employing animal classification using all the diagnostic methods associated lambing size, lamb weight at birth, and daily weight gain with SRLV infection status in meat flocks. Milk production, somatic cell count, fat, and protein content in the milk were associated with SRLV infection in dairy flocks, to a greater extent in the flock showing higher seroprevalence. A multi-platform SRLV diagnostic strategy was useful for ensuring correct animal classification, thus validating downstream studies investigating production traits.

Indexed as

body weightdiagnosisELISAlambing sizemilk productionPCRsmall ruminant lentivirusessomatic cell count

Identifiers

PMID32426375
PMCPMC7204384
OpenAlexW3022310621

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.