Related Experiment Video
Updated: Sep 25, 2026

Evaluating the Anti-depression Effect of Xiaoyaosan on Chronically-stressed Mice
Published on: January 7, 2019
Xiaoyao San Alleviates Depression-Associated Dry Eye via the LncRNA-Nespas/TAK1 Axis by Suppressing Central and
Jun Peng1,2, Junyao Li1, Ying Ni3
1College of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China.
Abstract:
Depression commonly manifests alongside dry eye disease (DED), and effective targeted treatments for this comorbid disorder are currently limited. Xiaoyao San (XYP), a traditional Chinese herbal formulation, is widely applied for the management of mood disturbances. This study explored the therapeutic effects and underlying molecular mechanism of XYP against depression-associated DED. A mouse model of comorbid depression and DED was generated by exposing animals to chronic unpredictable mild stress in a low-humidity environment. XYP notably ameliorated depressive-like phenotypes, restored tear secretion, and relieved corneal injury (p < 0.05 or p < 0.01). Molecular analyses revealed that XYP suppressed TAK1 expression and p38/NF-κB phosphorylation, and strengthened the interaction between lncRNA-Nespas and TAK1 in vivo. These regulatory effects were recapitulated in LPS/ATP-challenged BV2 microglia and hyperosmotic stress-exposed human corneal epithelial cells. Of note, genetic silencing of lncRNA-Nespas significantly reversed the anti-inflammatory actions of XYP. Collectively, XYP alleviates depression-associated DED by targeting the lncRNA-Nespas/TAK1 signaling axis, which suppresses inflammation in both the central nervous system and ocular tissues.
Related Concept Videos
Depression: Overview
Depressive Disorders: Etiology
Biological Factors in Depression
Biological predispositions significantly influence the risk of developing depressive disorders. Genetic studies highlight the role of variations in the serotonin transporter...
Long-term Depression
Long-term Depression
Calcium Ion Concentration Mechanism
If over time, all...