Evidence map›Paper›PMID 23073762›Full record

ArticlemBio2012

Predicting the outcome of infectious diseases: variability among inbred mice as a new and powerful tool for biomarker discovery.

Miriam E Martin, Jacquelyn A Dieter, Zheng Luo, Nicole Baumgarth, Jay V Solnick

Open access · goldAbstract read
In one paragraph

Article in mBio, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 22% 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

5 citing papers in PubMed, 6 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

5 authors at 1 institution in 1 country.

Miriam E MartinThe Center for Comparative Medicine, University of California, Davis, California, USA.
Jacquelyn A Dieter
Zheng Luo
Nicole Baumgarth
Jay V Solnick
University of California, Davis · US

Funding

Staff InvestigatorsP30CA093373 · NCI · UNIVERSITY OF CALIFORNIA DAVIS · PI Laura Marcu · 2002 to 2026
$84.9M
Regulation of Humoral Immunity to Influenza VirusR01AI051354 · NIAID · UNIVERSITY OF CALIFORNIA DAVIS · PI BAUMGARTH, NICOLE · 2002 to 2012
$3.0M
Gene expression during H. pylori-host interactionsR01AI042081 · NIAID · UNIVERSITY OF CALIFORNIA DAVIS · PI SOLNICK, JAY V. · 1998 to 2007
$2.5M
Serum biomarkers for early detection of H. pylori-associated gastric cancerR01CA136647 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI SOLNICK, JAY V. · 2009 to 2013
$1.5M
Long-lived B cell Immunity in the Respiratory TractR01AI085568 · NIAID · UNIVERSITY OF CALIFORNIA AT DAVIS · PI BAUMGARTH, NICOLE · 2010 to 2013
$1.5M
Role of H. pylori Outer Membrane Proteins in Colonization and Host ResponseR01AI081037 · NIAID · UNIVERSITY OF CALIFORNIA AT DAVIS · PI SOLNICK, JAY V. · 2009 to 2013
$1.1M
NCI NIH HHS CA136647NCI NIH HHS P30 CA093373NCI NIH HHS R01 CA136647NIAID NIH HHS AI051354NIAID NIH HHS AI081037NIAID NIH HHS AI085568NIAID NIH HHS AI42081NIAID NIH HHS R01 AI042081NIAID NIH HHS R01 AI051354NIAID NIH HHS R01 AI081037NIAID NIH HHS R01 AI085568
6 · The paper itself

Abstract

Individuals respond differently to infectious diseases. Even among inbred mice that are presumed to be genetically identical, the response to a microbial pathogen is variable, which is generally thought to reflect experimental inconsistencies, technical errors, and stochastic processes. Here we describe the remarkable observation that the variability of Helicobacter pylori colonization density in the stomachs of experimentally infected C57BL/6J mice is tightly correlated with weight loss and viral load after a challenge with influenza virus, though H. pylori infection per se does not affect influenza and vice versa. Since these two infectious agents are found in different tissue compartments and are detected using unrelated methods, the correlation in microbial burden must represent a biological measure of disease susceptibility among genetically nearly identical individuals and not technical or stochastic factors. We hypothesize that inbred mice represent a powerful new tool for the identification of biomarkers to predict the outcome of infectious diseases.

Indexed as

BiomarkersDisease SusceptibilityAnimalsBacterial LoadBody WeightCommunicable DiseasesDisease Models, AnimalHelicobacter pyloriMiceMice, Inbred C57BLOrthomyxoviridaeTreatment OutcomeViral LoadBiomarkers

Identifiers

PMID23073762
PMCPMC3470649
OpenAlexW2147240250

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.