Journal of ethnopharmacology · 2026
Integrating machine learning and pharmacology reveals NF-κB-mediated inflammatory regulation by Shuanghuanglian injection in acute lung injury.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Liu Can, Qiao Ru, Tian Qiang, He Fuyuan
Аннотация
ETHNOPHARMACOLOGICAL RELEVANCE: Shuanghuanglian Injection (SHLI) is a traditional Chinese medicine formulation derived from Lonicerae Japonicae Flos, Scutellariae Radix, and Forsythiae Fructus and developed based on the TCM principle of heat-clearing and detoxifying. It has been widely used for respiratory infections and inflammatory disorders, but its protective mechanisms in acute lung injury (ALI) warrant further investigation.
AIM OF THE STUDY: To characterize the chemical profile of SHLI and delineate its pharmacological mechanisms in ALI, with particular attention to inflammatory regulation and the NF-κB signaling cascade.
MATERIALS AND METHODS: UPLC-MS/MS profiling defined the chemical components of SHLI. Candidate targets were retrieved from TCMSP, GeneCards, DisGeNET, and the Open Targets Platform, then organized into a protein-protein interaction network with subsequent enrichment analyses. Transcriptomic data from GEO provided differentially expressed genes, which were further refined using a combination of machine learning approaches (LASSO, random forest, SVM-RFE, and XGBoost) to prioritize key targets. Molecular docking assessed the binding affinity between representative compounds and targets. An LPS-induced ALI rat model was used to verify therapeutic effects through hematological indices, histopathology, RT-qPCR, ELISA, and Western blot assays.
RESULTS: 10 principal components were identified and quantified in SHLI, predominantly flavonoids and phenolic acids. Integrating network pharmacology with machine learning highlighted three genes (IL-1α, IL-1β and TNFAIP6) as central nodes. Docking analysis suggested that quercetin interacts stably with these key targets. In vivo, SHLI mitigated lung injury in a dose-dependent manner and partially restored disordered leukocyte responses while lowering pro-inflammatory cytokine levels. At the molecular level, SHLI modulated the transcription of IL-1α, IL-1β and TNFAIP6 and reduced the secretion of TNF-α, IL-1β and TNFAIP6. Concurrently, SHLI dampened NF-κB activation by limiting IκBα phosphorylation and restraining p65 activation.
CONCLUSION: SHLI protects against ALI through coordinated multi-component, multi-target interactions, with its core mechanism associated with the suppression of NF-κB mediated inflammatory responses.
AIM OF THE STUDY: To characterize the chemical profile of SHLI and delineate its pharmacological mechanisms in ALI, with particular attention to inflammatory regulation and the NF-κB signaling cascade.
MATERIALS AND METHODS: UPLC-MS/MS profiling defined the chemical components of SHLI. Candidate targets were retrieved from TCMSP, GeneCards, DisGeNET, and the Open Targets Platform, then organized into a protein-protein interaction network with subsequent enrichment analyses. Transcriptomic data from GEO provided differentially expressed genes, which were further refined using a combination of machine learning approaches (LASSO, random forest, SVM-RFE, and XGBoost) to prioritize key targets. Molecular docking assessed the binding affinity between representative compounds and targets. An LPS-induced ALI rat model was used to verify therapeutic effects through hematological indices, histopathology, RT-qPCR, ELISA, and Western blot assays.
RESULTS: 10 principal components were identified and quantified in SHLI, predominantly flavonoids and phenolic acids. Integrating network pharmacology with machine learning highlighted three genes (IL-1α, IL-1β and TNFAIP6) as central nodes. Docking analysis suggested that quercetin interacts stably with these key targets. In vivo, SHLI mitigated lung injury in a dose-dependent manner and partially restored disordered leukocyte responses while lowering pro-inflammatory cytokine levels. At the molecular level, SHLI modulated the transcription of IL-1α, IL-1β and TNFAIP6 and reduced the secretion of TNF-α, IL-1β and TNFAIP6. Concurrently, SHLI dampened NF-κB activation by limiting IκBα phosphorylation and restraining p65 activation.
CONCLUSION: SHLI protects against ALI through coordinated multi-component, multi-target interactions, with its core mechanism associated with the suppression of NF-κB mediated inflammatory responses.