Evidence map›Paper›PMID 29896237›Full record

ArticleExperimental and therapeutic medicine2018

Effect of interleukin-31 on septic shock through regulating inflammasomes and interleukin-1β.

Xuyun Gu, Chen Wei, Xishan Zhu, Feiping Lu, Bo Sheng, Xuefeng Zang

Open access · diamondAbstract read
In one paragraph

Article in Experimental and therapeutic medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 27% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. IL-31: State of the Art for an Inflammation-Oriented Interleukin.International journal of molecular sciences · 2022
    Pooled it
  2. Article
  3. 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

6 authors at 3 institutions in 1 country.

Xuyun GuDepartment of Critical Care Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, P.R. China.
Chen WeiDepartment of Critical Care Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, P.R. China.
Xishan ZhuDepartment of Cancer Chemotherapy, Peking University First Hospital, Beijing 100038, P.R. China.
Feiping LuDepartment of Critical Care Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, P.R. China.
Bo ShengDepartment of Critical Care Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, P.R. China.
Xuefeng ZangDepartment of Critical Care Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, P.R. China.
Beijing Shijitan Hospital · CNCapital Medical University · CNPeking University First Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sepsis with severe systemic inflammation remains a great challenge for the intensive care unit in clinics. Although biomarkers have been identified to diagnose, monitor and predict these syndromes, novel therapeutic approaches are required for the amelioration of symptoms of sepsis and septic shock. The present study demonstrated that interleukin (IL)-31 was able reduce the mortality rate of lipopolysaccharide (LPS)-induced sepsis with the reduction of inflammatory cytokines in the sera. IL-31 also inhibited IL-1β production in the peritoneal lavage fluid in LPS-induced or cecal ligation and puncture-induced sepsis. The

Indexed as

inflammasomesinterleukin-1βinterleukin-31NLR familyNLRP3pyrin domain-containing 3sepsis

Identifiers

PMID29896237
PMCPMC5995029
OpenAlexW2804740166

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.