Herpes zoster (HZ) is a localized, painful cutaneous eruption that occurs upon reactivation of the herpes virus.Postherpetic neuralgia (PHN) is the most common chronic Deep Treatment complication of HZ.In this study, we examined the metabolomic and proteomic signatures of disease progression in patients with HZ and PHN.We identified differentially expressed metabolites (DEMs), differentially expressed proteins (DEPs), and key signaling pathways that transition from healthy volunteers to the acute or/and chronic phases of herpetic neuralgia.
Moreover, some specific metabolites correlated with pain scores, disease duration, age, and pain in sex dimorphism.In addition, we developed and validated three optimal predictive models (AUC > 0.9) for classifying HZ and PHN from healthy individuals based on metabolic patterns and machine learning.These findings may reveal Stainless Steel Food Pan Covers the overall metabolomics and proteomics landscapes and proposed the optimal machine learning predictive models, which provide insights into the mechanisms of HZ and PHN.