Evidence map›Paper›PMID 31934590›Full record

ArticleJournal of diabetes research2019

TAK-875 Mitigates

Xide Chen, Yuanli Yan, Zhiyan Weng, Chao Chen, Miaoru Lv, Qingwen Lin, Qiuxia Du, Ximei Shen, Liyong Yang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of diabetes research, 2019. 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
2.1field-weighted citation impact, top 13% 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, 17 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

9 authors at 1 institution in 1 country.

Xide ChenEndocrinology Department, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005 Fujian, China.
Yuanli YanEndocrinology Department, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005 Fujian, China.ORCID https://orcid.org/0000-0002-0217-1554
Zhiyan WengEndocrinology Department, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005 Fujian, China.
Chao ChenEndocrinology Department, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005 Fujian, China.
Miaoru LvEndocrinology Department, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005 Fujian, China.
Qingwen LinEndocrinology Department, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005 Fujian, China.
Qiuxia DuEndocrinology Department, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005 Fujian, China.
Ximei ShenEndocrinology Department, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005 Fujian, China.ORCID https://orcid.org/0000-0003-0598-366X
Liyong YangEndocrinology Department, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005 Fujian, China.ORCID https://orcid.org/0000-0003-0693-9206
Fujian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic inflammatory damage, characterized by Toll-like receptor 4 (TLR4) signaling activation, is a major mechanism underlying lipotoxicity-induced

Indexed as

AnimalsBenzofuransCell Line, TumorDiet, High-FatInflammationInsulin-Secreting CellsMaleMiceObesityRatsRats, Sprague-DawleyReceptors, G-Protein-CoupledSignal TransductionSulfonesToll-Like Receptor 4Transcription Factor RelABenzofuransG-protein-coupled receptor 40, ratReceptors, G-Protein-CoupledSulfonesTAK-875Toll-Like Receptor 4Transcription Factor RelA

Identifiers

PMID31934590
PMCPMC6942802
OpenAlexW2995825478

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.