Evidence map›Paper›PMID 38660554›Full record

ArticleWorld journal of clinical cases2024

Intestinal flora: New perspective of type 2 diabetes.

Yan Liu, Jun Chang, Li-Ding Bai

Open access · diamondAbstract read
In one paragraph

Article in World journal of clinical cases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 2 institutions in 1 country.

Yan LiuDepartment of Gastroenterology, Hospital of Integrated Chinese and Western Medicine, Tianjin, Tianjin 300100, China.
Jun ChangFirst Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300381, China. cj2020_91@163.com.
Li-Ding BaiAcademy of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China.
Tianjin University of Traditional Chinese Medicine · CNIntegrated Chinese Medicine (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes comprises a group of metabolic diseases characterized by hyperglycemia stemming from various factors. Current diabetes management primarily focuses on blood glucose control, yet it is inherently progressive, necessitating increased reliance on exogenous blood glucose control methods over time. Therefore, there is an urgent need to explore novel intervention strategies addressing both diabetes and its complications. The human intestinal microbiota, often referred to as the "second genome", exhibits significant diversity and plays a pivotal role in insulin resistance, glucose and lipid metabolism, and inflammatory response. Notably, Li and Guo have elucidated the involvement of intestinal flora in the pathogenesis of type 2 diabetes mellitus (T2DM) and proposed a novel therapeutic approach targeting intestinal microbes. This advancement enhances our comprehension of the multifaceted and multi-target regulation of T2DM by intestinal microflora, thereby offering fresh avenues for understanding its pathogenesis and clinical management. This letter briefly summarizes the role of intestinal flora in T2DM based on findings from animal experiments and clinical studies. Additionally, it discusses the potential clinical applications and challenges associated with targeting intestinal flora as therapeutic interventions.

Indexed as

Insulin resistanceIntestinal floraMicrobial metabolitesProbioticsType 2 diabetes

Identifiers

PMID38660554
PMCPMC11036511
OpenAlexW4394680329

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.