Evidence map›Paper›PMID 25360076›Full record

ArticleImmune network2014

TRIF Deficiency does not Affect Severity of Ovalbumin-induced Airway Inflammation in Mice.

Tae-Hyoun Kim, Dong-Jae Kim, Jae-Hak Park, Jong-Hwan Park

Open access · hybridAbstract read
In one paragraph

Article in Immune network, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 88% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
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

4 authors at 3 institutions in 1 country.

Tae-Hyoun KimLaboratory Animal Medicine, College of Veterinary Medicine, Seoul National University, Seoul 151-742, Korea.
Dong-Jae KimDepartment of Biochemistry, College of Medicine, Konyang University, Daejeon 302-718, Korea.
Jae-Hak ParkLaboratory Animal Medicine, College of Veterinary Medicine, Seoul National University, Seoul 151-742, Korea.
Jong-Hwan ParkDepartment of Laboratory Animal Medicine, College of Veterinary Medicine, Chonnam National University, Gwangju 500-757, Korea.
Seoul National University · KRChonnam National University · KRKonyang University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Allergic asthma is a chronic pulmonary inflammatory disease characterized by reversible airway obstruction, hyperresponsiveness and eosinophils infiltration. Toll-like receptors (TLRs) signaling are closely associated with asthma and have emerged as a novel therapeutic target in allergic disease. The functions of TLR3 and TLR4 in allergic airway inflammation have been studied; however, the precise role of TIR-domain-containing adapter-inducing interferon-β (TRIF), the adaptor molecule for both TLR3 and TLR4, is not yet fully understood. To investigate this, we developed a mouse model of OVA-induced allergic airway inflammation and compared the severity of allergic airway inflammation in WT and TRIF(-/-) mice. Histopathological assessment revealed that the severity of inflammation in airway inflammation in TRIF-deficient mice was comparable to that in WT mice. The total number of cells recovered from bronchoalveolar lavage fluid did not differ between WT and TRIF-deficient mice. Moreover, TRIF deficiency did not affect Th1 and Th2 cytokine production in lung tissue nor the level of serum OVA-specific IgE, IgG1 and IgG2c. These findings suggest that TRIF-mediated signaling may not be critical for the development of allergic airway inflammation.

Indexed as

Allergic airway inflammationTh2TRIF

Identifiers

PMID25360076
PMCPMC4212086
OpenAlexW2046575627

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.