Evidence map›Paper›PMID 32231686›Full record

ArticleFrontiers in genetics2020

Exploring Phenotypes for Disease Resilience in Pigs Using Complete Blood Count Data From a Natural Disease Challenge Model.

Xuechun Bai, Austin M Putz, Zhiquan Wang, Frédéric Fortin, John C S Harding, Michael K Dyck, Jack C M Dekkers, Catherine J Field, Graham S Plastow, PigGen Canada

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
6.4field-weighted citation impact, top 3% 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

19 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
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  3. Review
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  5. Review
  6. Article
  7. Selection for Resilience in Livestock Production Systems.International journal of molecular sciences · 2024
    Review
  8. Article
  9. Article
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  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. A Methodology to Quantify Resilience in Growing Pigs.Animals : an open access journal from MDPI · 2021
    Article
  17. Article
  18. Article
  19. Why breed disease-resilient livestock, and how?Genetics, selection, evolution : GSE · 2020
    Review
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 at 4 institutions in 2 countries.

Xuechun BaiLivestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.
Austin M PutzDepartment of Animal Science, Iowa State University, Ames, IA, United States.
Zhiquan WangLivestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.
Frédéric FortinCentre de Développement du Porc du Québec, Inc., Quebec City, QC, Canada.
John C S HardingDepartment of Large Animal Clinical Sciences, University of Saskatchewan, Saskatoon, SK, Canada.
Michael K DyckLivestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.
Jack C M DekkersDepartment of Animal Science, Iowa State University, Ames, IA, United States.
Catherine J FieldLivestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.
Graham S PlastowLivestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.
PigGen CanadaLivestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.
University of Alberta · CACentre de Développement du Porc du Québec · CAIowa State University · USUniversity of Saskatchewan · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Disease resilience is a valuable trait to help manage infectious diseases in livestock. It is anticipated that improved disease resilience will sustainably increase production efficiency, as resilient animals maintain their performance in the face of infection. The objective of this study was to identify phenotypes related to disease resilience using complete blood count (CBC) data from a wean-to-finish natural disease challenge model, established to mimic the disease pressure caused by many common pathogens at the commercial level of pig production. In total, 2433 F1 crossbred (Landrace × Yorkshire) barrows that went through the natural disease challenge model were classified into four groups (resilient, average, susceptible, and dead) based on their divergent responses in terms of growth and individual treatment. Three sets of blood samples for CBC analysis were drawn at 2-weeks before, and at 2- and 6-weeks after the challenge: Blood 1, Blood 3, and Blood 4 respectively. CBC of Blood 1 taken from healthy pigs before challenge did not show differences between groups. However, resilient animals were found to be primed to initiate a faster adaptive immune response and recover earlier following infection, with greater increases of lymphocyte concentration from Blood 1 to Blood 3 and for hemoglobin concentration and hematocrit from Blood 3 to Blood 4, but a lower neutrophil concentration from Blood 3 to Blood 4 than in susceptible and dead animals (

Indexed as

complete blood countdisease resiliencegenetic parametersnatural disease challenge modelpigs

Identifiers

PMID32231686
PMCPMC7083204
OpenAlexW3012448306

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.