Evidence map›Paper›PMID 31187384›Full record

SynthesisJournal of applied genetics2019

Prediction of key regulators and downstream targets of E. coli induced mastitis.

Somayeh Sharifi, Abbas Pakdel, Esmaeil Ebrahimie, Yalda Aryan, Mostafa Ghaderi Zefrehee, James M Reecy

Abstract readMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Journal of applied genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.7field-weighted citation impact, top 7% 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

11 citing papers in PubMed, 21 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

6 authors at 5 institutions in 3 countries.

Somayeh SharifiDepartment of Animal Science, College of Agriculture, Isfahan University of Technology, Isfahan, Iran. ss.sharifi2015@gmail.com.ORCID http://orcid.org/0000-0001-6003-8754
Abbas PakdelDepartment of Animal Science, College of Agriculture, Isfahan University of Technology, Isfahan, Iran.
Esmaeil EbrahimieSchool of Animal and Veterinary Sciences, The University of Adelaide, Adelaide, South Australia, Australia.
Yalda AryanComputer Engineering Payam Noor University, Tehran, Iran.
Mostafa Ghaderi ZefreheeDepartment of Animal Science, College of Agriculture, Yasouj University, Kohgiluyeh and Boyer-Ahmad, Iran.
James M ReecyDepartment of Animal Science, Iowa State University, 1221 Kildee Hall, Ames, IA, 50011-3150, USA. jreecy@iastate.edu.
Isfahan University of Technology · IRIowa State University · USLa Trobe University · AUPayame Noor University · IRYasouj University · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mastitis, an inflammatory response of mammary glands to invading bacteria, is one of the most economically costly diseases affecting dairy animals. Escherichia coli can be introduced as a major etiological agent of bovine mastitis in well-managed dairy farms. It is of great significance to understand the regulatory mechanisms by which the disease can be controlled. High-throughput technologies combined with novel computational systems biology tools have provided new opportunities for a better understanding of the molecular mechanisms that underlie disease. In the current study, the results of microarray meta-analysis research were used to perform a network analysis to potentially identify molecular mechanisms that regulate gene expression profile in response to E. coli mastitis. In our result, transcription factors, TP53, SP1, ligands, INS, IFNG, EGF, and protein kinases, MAPK1, MAPK14, AKT1, were identified as the key upstream regulators whereas protein kinases, MAPK3, MAPK8, MAPK14, ligands, VEGFA, IL10, an extracellular protein, MMP2, and a mitochondrial membrane protein, BCL2, were identified as the key downstream targets of differentially expressed genes. The results of this research revealed important genes that have the key functions in immune response, inflammation, or mastitis which can provide the basis for strategies to improve the diagnosis and treatment of mastitis in dairy cows.

Indexed as

AnimalsCattleComputational BiologyEscherichia coliEscherichia coli InfectionsFemaleGene Expression RegulationHumansMammary Glands, AnimalMastitis, BovineMilkTranscriptomeDairy cattleEscherichia coliFunctional genomicsGene networkSystem biologyTranscriptome

Identifiers

PMID31187384
OpenAlexW2949882086

What OpenQuestion holds

Textmetadata
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.