Evidence map›Paper›PMID 24516725›Full record

ReviewEuropean journal of microbiology & immunology2011

Infection and autoimmunity: Lessons of animal models.

M Pásztói, P Misják, B György, B Aradi, T G Szabó, B Szántó, M Cs Holub, Gy Nagy, A Falus, E I Buzás

Open access · bronzeAbstract readReview
In one paragraph

Review in European journal of microbiology & immunology, 2011. 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, top 91% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. 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 2 institutions in 1 country.

M Pásztói
P Misják
B György
B Aradi
T G Szabó
B Szántó
M Cs Holub
Gy Nagy
A Falus
E I Buzás
Semmelweis University · HUHungarian Academy of Sciences · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While the key initiating processes that trigger human autoimmune diseases remain enigmatic, increasing evidences support the concept that microbial stimuli are among major environmental factors eliciting autoimmune diseases in genetically susceptible individuals. Here, we present an overview of evidences obtained through various experimental models of autoimmunity for the role of microbial stimuli in disease development. Disease onset and severity have been compared in numerous models under conventional, specific-pathogen-free and germ-free conditions. The results of these experiments suggest that there is no uniform scheme that could describe the role played by infectious agents in the experimental models of autoimmunity. While some models are dependent, others prove to be completely independent of microbial stimuli. In line with the threshold hypothesis of autoimmune diseases, highly relevant genetic factors or microbial stimuli induce autoimmunity on their own, without requiring further factors. Importantly, recent evidences show that colonization of germ-free animals with certain members of the commensal flora [such as segmented filamentous bacteria (SFB)] may lead to autoimmunity. These data drive attention to the importance of the complex composition of gut flora in maintaining immune homeostasis. The intriguing observation obtained in autoimmune animal models that parasites often confer protection against autoimmune disease development may suggest new therapeutic perspectives of infectious agents in autoimmunity.

Indexed as

autoimmunityinfectionmicrobemimicrymodel

Identifiers

PMID24516725
PMCPMC3906615
OpenAlexW1976108882

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.