@article{RUAN2026, 
author = {Cailian RUAN and Xueting YANG and Jingyi ZHANG and Tongjie TENG and Zhenghao CHEN and Yuhan LIU and Ying YANG and Yayun WANG},
title = {Chronic pain: from central sensitization to network homeostasis imbalance},
year = {2026},
journal = {Journal of Southern Medical University},
volume = {46},
number = {10},
pages = {2575-2590},
keywords = {chronic pain, central sensitization, network homeostasis imbalance, neuroimmune interaction, epigenetic regulation, precision analgesia},
url = {https://www.sciopen.com/article/10.12122/j.issn.1673-4254.2026.10.24},
doi = {10.12122/j.issn.1673-4254.2026.10.24},
abstract = {Following a "mechanism-technology-translation" framework and focusing on high-quality studies published between 2023 and 2025, this review critically synthesizes representative findings on network-level remodeling in central sensitization, the neuroimmune axis, energy metabolism and mitochondrial homeostasis, epigenetic reprogramming, and clinical translation in chronic pain. The onset and maintenance of chronic pain involve multi-level coupling among neurons, glial cells, the immune system, and epigenetic regulatory mechanisms. The core pathological feature can be characterized as the deviation of pain-regulatory networks from their normal functional range across molecular, cellular, and circuit levels, resulting in a self-sustaining abnormal steady state-termed "network homeostasis imbalance. " Major bottlenecks include the absence of integrative network-level pathological models, systematic discrepancies between animal models and clinical phenotypes, insufficient cross-cohort reproducibility of biomarkers, and inadequate translational pathways from basic discoveries to clinical validation. Chronic pain research and management need to shift from a "single-target, single-pathway" paradigm toward network-level systems analysis. Establishing actionable linkages among mechanistic analysis, technological validation, and clinical implementation is key to advancing chronic pain management from empirical analgesia toward precision intervention.}
}