Evidence map›Paper›PMID 38707406›Full record

ArticleHeliyon2024

Glycosylation in autoimmune diseases: A bibliometric and visualization study.

Guoqian Deng, Xinyi Chen, Le Shao, Qibiao Wu, Shenzhi Wang

Abstract read
In one paragraph

Article in Heliyon, 2024. 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
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.

  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

5 authors.

Guoqian DengHunan University of Chinese Medicine, Changsha, Hunan, China.
Xinyi ChenHunan University of Chinese Medicine, Changsha, Hunan, China.
Le ShaoThe First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China.
Qibiao WuState Key Laboratory of Quality Research in Chinese Medicines and Faculty of Chinese Medicine, Macau University of Science and Technology, Taipa, Macau, China.
Shenzhi WangThe First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An increasing amount of research has shown that glycosylation plays a crucial role in autoimmune diseases (ADs), prompting our interest in conducting research on the knowledge framework and hot topics in this field based on bibliometric analysis. Studies on glycosylation in the field of ADs from 2003 to 2023 were collected by searching the Web of Science Core Collection database. Bibliometric analysis was conducted using VOSviewer, CiteSpace, and Bibliometrix software. This study included a total of 530 studies. According to the H, G, and M indices, the United States has made the most contributions worldwide, with China making significant contributions in recent years. Leiden University from the Netherlands ranks among the top institutions in terms of publication and citation rankings, with the institution's author Manfred Wuhrer contributing the most to this field. Frontiers in Immunology is the journal with the highest H-index. Research in this field has focused on antibody glycosylation, particularly the specific glycosylation of IgG and IgA, and its role in various ADs. The application of glycoengineering glycosylated proteins in the synthesis of targeted monoclonal antibodies, drug delivery, and regenerative medical materials may be a new trend in the treatment of ADs. Artificial intelligence is an emerging tool in glycobiology. This study summarizes the objective data on glycosylation in the field of AD publications in recent years, providing a reference for researchers in this field.

Indexed as

Autoimmune diseasesBibliometricsBibliometrixGlycosylationVOSviewer

Identifiers

PMID38707406
PMCPMC11066412

What OpenQuestion holds

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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.