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Hair serves important physiological functions, including temperature regulation and scalp protection. However, excessive shedding not only impacts these functions but can also significantly affect mental health and quality of life. Tianma Gouteng decoction (TGD) is a traditional Chinese medicine used for the treatment of various conditions, including hair loss. However, the associated mechanism underlying its anti-alopecia effect remains unknown. Therefore, this study aims to elucidate these mechanisms by employing systematic biology approaches, as well as in vitro and in vivo experimental validation. The chemical constituents of Tianma Gouteng decoction were identified using UHPLC-MS/MS, from which 39 potential bioactive components were screened, while an additional 131 putative Tianma Gouteng decoction beneficial components were extracted from the Traditional Chinese Medicine Database and Analysis Platform (TCMSP) database. We then applied a dual-dimensional network pharmacology approach to analyze the data, followed by validation studies combining molecular docking techniques with in vivo and in vitro experiments. From the 39 bioactive components, including quercetin, luteolin, fisetin, wogonin, oroxylin A, boldine, tetrahydroalstonine, and galangin A, 782 corresponding targets were identified. In particular, GSK3β and β-catenin exhibited strong binding activity with the bioactive compounds. Hence, construction of a bioactive component-target network revealed that the mechanism underlying the anti-alopecia mechanism of Tianma Gouteng decoction primarily involved the Wnt/β-catenin signaling pathway. Moreover, C57BL/6J mice exhibited measurable improvements in hair follicle regeneration following treatment with Tianma Gouteng decoction. Additionally, β-catenin and p-GSK3β levels were upregulated, while GSK3β was downregulated in Tianma Gouteng decoction-treated animals and dermal papilla cells compared to control group. These in vivo and in vitro outcomes validated the targets and pathways predicted in the network pharmacology analysis of Tianma Gouteng decoction. This study provides a systematic analysis approach to identify the underlying anti-alopecia mechanisms of Tianma Gouteng decoction, further providing theoretical support for clinical assessment of Tianma Gouteng decoction.

Background: Emergence agitation (EA) is very common in paediatric patients during recovery from general anaesthesia, but underlying mechanisms remain unknown. This prospective study was designed to profile preoperative urine metabolites and identify potential biomarkers that can predict the occurrence of EA.Methods: A total of 224 patients were screened for recruitment; of those, preoperative morning urine samples from 33 paediatric patients with EA and 33 non-EA gender- and age-matched patients after being given sevoflurane general anaesthesia were analysed by ultra-high-performance liquid chromatography (UHPLC) coupled with a Q Exactive Plus mass spectrometer. Univariate analysis and orthogonal projection to latent structures squares-discriminant analysis (OPLS-DA) were used to analyse these metabolites. The least absolute shrinkage and selection operator (LASSO) regression was used to identify predictive variables. The predictive model was evaluated through the receiver operating characteristic (ROC) analysis and then further assessed with 10-fold cross-validation.Results: Seventy-seven patients completed the study, of which 33 (42.9%) patients developed EA. EA and non-EA patients had many differences in preoperative urine metabolic profiling. Sixteen metabolites including nine aromatic amino acid metabolites, acylcarnitines, pyridoxamine, porphobilinogen, 7-methylxanthine, and 5′-methylthioadenosine were found associated with an increased risk of EA, and they all exhibited higher levels in the EA group than in the non-EA group. The main metabolic pathways involved in these metabolic changes included phenylalanine, tyrosine and tryptophan metabolisms. Among these potential biomarkers, L-tyrosine had the best predictive value with an odds ratio (OR) (95% CI) of 5.27 (2.20–12.63) and the AUC value of 0.81 (0.70–0.91) and was robust with internal 10-fold cross-validation.Conclusion: Urinary aromatic amino acid metabolites are closely associated with EA in paediatric patients, and further validation with larger cohorts and mechanistic studies is needed.Clinical Trial Registration:clinicaltrials.gov, identifier NCT04807998