Evidence map›Paper›PMID 38418860›Full record

ArticleScientific reports2024

Phenotypic characterisation of regulatory T cells in patients with gestational diabetes mellitus.

Ya-Nan Zhang, Qin Wu, Yi-Hui Deng

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
  6. Observational
  7. Genetic variants inFrontiers in endocrinology · 2025
    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.

Ya-Nan ZhangSchool of Integrated Chinese and Western Medicine, Hunan University of Chinese Medicine, Hunan, 410208, China.
Qin WuSchool of Integrated Chinese and Western Medicine, Hunan University of Chinese Medicine, Hunan, 410208, China.
Yi-Hui DengSchool of Chinese Medicine, Hunan University of Chinese Medicine, Hunan, 410208, China. 644138330@qq.com.

Funding

National Key Research and Development Program of China 2022YFC3501202Science and Technology Program of Hunan Province 2020RC4050
6 · The paper itself

Abstract

Gestational diabetes mellitus (GDM) is a common complication that occurs during pregnancy. Emerging evidence suggests that immune abnormalities play a pivotal role in the development of GDM. Specifically, regulatory T cells (Tregs) are considered a critical factor in controlling maternal-fetal immune tolerance. However, the specific characteristics and alterations of Tregs during the pathogenesis of GDM remain poorly elucidated. Therefore, this study aimed to investigate the changes in Tregs among pregnant women diagnosed with GDM compared to healthy pregnant women. A prospective study was conducted, enrolling 23 healthy pregnant women in the third trimester and 21 third-trimester women diagnosed with GDM. Participants were followed up until the postpartum period. The proportions of various Treg, including Tregs, mTregs, and nTregs, were detected in the peripheral blood of pregnant women from both groups. Additionally, the expression levels of PD-1, HLA-G, and HLA-DR on these Tregs were examined. The results revealed no significant differences in the proportions of Tregs, mTregs, and nTregs between the two groups during the third trimester and postpartum period. However, GDM patients exhibited significantly reduced levels of PD-1

Indexed as

Diabetes, GestationalFemaleHLA-G AntigensHumansPregnancyProgrammed Cell Death 1 ReceptorProspective StudiesT-Lymphocytes, RegulatoryHLA-G AntigensProgrammed Cell Death 1 Receptor

Identifiers

PMID38418860
PMCPMC10902321

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Registered trials

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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.