Mechanism-Driven Translation of Electroacupuncture for Depression: Bridging the Gap Between Preclinical and Clinical Research

基于机制的电针疗法治疗抑郁症转化研究:弥合临床前研究与临床研究之间的差距

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Abstract

Electroacupuncture (EA) has demonstrated multi‑level antidepressant effects, yet the strength of clinical evidence remains insufficient and its efficacy consistency is highly contested. The key bottlenecks include heterogeneous research designs, a lack of standardized stimulation parameters and acupoint selection, insufficient attention to disease biological subtyping, and a disconnect between mechanistic studies and clinical outcomes. To address these gaps, this review proposes a mechanism‑driven precision translation pathway centered on patient stratification. By integrating neural circuitry, immune‑inflammatory pathways, biomarkers, and multimodal assessment tools, we argue that the primary translational bottleneck is not a lack of mechanisms but the failure to systematically integrate them into a clinical decision‑oriented paradigm. Enhancing interpretability and clinical scalability through parameter optimization, targeted neural network modulation, and objective indicator integration may transform EA from a complementary therapy into a precision intervention with clear mechanisms and reliable evidence.

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