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CORRECTION article

Front. Med., 19 November 2025

Sec. Rheumatology

Volume 12 - 2025 | https://doi.org/10.3389/fmed.2025.1741480

Correction: Identification of anoikis-related genes and immune infiltration characteristics in Sjögren's syndrome based on machine learning

This article is a correction to:

  1. Identification of anoikis-related genes and immune infiltration characteristics in Sjögren’s syndrome based on machine learning

    1. Read original article
Lei WangLei Wang1Ziqi XuZiqi Xu1Xinpeng ZhouXinpeng Zhou1Ying Liu Ying Liu1*Mengjie Wang, Mengjie Wang1,2*
  • 1Department of Rheumatology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
  • 2Institute of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, China

A Correction on
Identification of anoikis-related genes and immune infiltration characteristics in Sjögren's syndrome based on machine learning

by Wang, L., Zhou, Z., Zhou, X., Liu, Y., and Wang, M. (2025). Front. Med. 12:1661259. doi: 10.3389/fmed.2025.1661259

Author [Ziqi Xu] was erroneously spelled as [Ziqi Zhou].

In a published article, there is an error in the author name list. The second author is shown as “Ziqi Zhou”. Correctly expressed as “Ziqi Xu”.

The original version of this article has been updated.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Keywords: Sjögren's syndrome, anoikis, machine learning, ceRNA network, immune infiltration

Citation: Wang L, Xu Z, Zhou X, Liu Y and Wang M (2025) Correction: Identification of anoikis-related genes and immune infiltration characteristics in Sjögren's syndrome based on machine learning. Front. Med. 12:1741480. doi: 10.3389/fmed.2025.1741480

Received: 07 November 2025; Accepted: 10 November 2025;
Published: 19 November 2025.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2025 Wang, Xu, Zhou, Liu and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Mengjie Wang, d21qenkxOTk2QDE2My5jb20=; Ying Liu, bHl0dF8xOTk0QDE2My5jb20=

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.