The quality control processes for herbal medicines have been problematic. Flavonoids are the major active components of Huangqin Tang (HQT, a traditional Chinese medicine formula). In this study, we used a combinative method approach consisting of chromatographic fingerprinting (high performance liquid chromatography; HPLC), quantitative methods and a pharmacodynamic evaluation model to analyze the flavonoids of HQT obtained from different sources. Ten batches of HQT were analyzed by the HPLC fingerprinting method and 26 common peaks were detected, of which 23 peaks corresponded with the chemical profile of HQT. In addition, 11 major compounds were identified by LC-MS analysis (liquid chromatography-tandem mass spectrometer; LC-MS (n) ) and quantified by the HPLC quantitative method approach. The studied 10 batches of HQT were found to be homogeneous in their composition with a similarity between 0.990 and 1.000. The distribution of the 11 identified compounds was found to be very similar among the batches. Only slight pharmacodynamic differences were detected between the different batches, confirming the homogeneity of HQT. The results of this study prove that the combination of chromatographic fingerprinting and quantitative analysis can be readily used for comprehensive quality control of herbal medicines.

Neuropathic pain (NP) is a type of chronic pain resulting from injury or dysfunction of the nerves or spinal cord. Previous studies have shown that the combination of ligustrazine (LGZ) and sinomenine (SIN) exerts a synergistic antinociceptive effect in peripheral and central NP models. On this basis, a comprehensive analgesic evaluation was performed in a chronic constriction injury (CCI)-induced NP model in rats. Sciatic nerve histopathological changes were observed, and 22 cytokines and chemokines levels were analyzed. We also combined network pharmacology and metabolomics to explore their molecular mechanisms. Results showed that the combination of LGZ and SIN significantly alleviated the pain-like behaviors in CCI rats in a time- and dose-dependent manner, demonstrating superior therapeutic effects compared to LGZ or SIN alone. It also improved pathological damage to sciatic nerves and regulated inflammatory cytokine levels. Network pharmacology identified shared and distinct pain-related targets for LGZ and SIN, while metabolomics revealed 54 differential metabolites in plasma, and 17 differential metabolites in CSF were associated with the combined intervention of LGZ and SIN. Finally, through an integrated analysis of the core targets and differential metabolites, tyrosine metabolism, phenylalanine metabolism, and arginine and proline metabolism were identified as potential key metabolic pathways underlying the therapeutic effects of LGZ and SIN in CCI treatment. In conclusion, our study provides evidence to support the clinical application of LGZ and SIN in the treatment of NP.

Background: Chronic insomnia is an important global health concern, but its molecular heterogeneity remains incompletely understood. Objective biomarkers may help characterize chronic insomnia and its traditional Chinese medicine (TCM) syndrome patterns. Methods: We applied a Public Evidence-informed Prioritization–Multi-omics Discovery–Targeted Validation (PMT) framework integrating public transcriptomic datasets with serum profiles from healthy controls and patients with chronic insomnia classified as excess (Shi) or deficiency (Xu) syndrome. Analyses included transcriptomic data processing and machine learning-based gene prioritization, serum metabolomics and lipidomics, targeted neurotransmitter quantification, bile acid profiling, and pathway-level comparison across omics datasets. Results: Transcriptomic analysis and weighted gene co-expression network analysis identified a phenotype-associated module containing 178 differentially expressed genes (DEGs), and three machine learning methods prioritized 11 candidate genes. Compared with controls, the Shi group had 53 differential metabolites and 87 differential lipids, whereas the Xu group had 49 differential metabolites and 80 differential lipids. Serum analyses revealed syndrome-associated differences in N-acetylated amino acids, lipid species, neurotransmitter-related metabolites, and bile acids. Kyoto Encyclopedia of Genes and Genomes (KEGG)-based integrative analysis identified shared pathways linking transcriptomic alterations with serum metabolomic and lipidomic changes, highlighting pathway-level convergence across the three omics layers. Cross-validated receiver operating characteristic analyses showed variable discriminatory performance, generally stronger for insomnia identification than for differentiation between Shi and Xu syndromes. Conclusions: Using the PMT framework, this study delineated distinct gene–metabolite–lipid signatures of chronic insomnia and its major TCM syndromes, providing a molecular basis for objective diagnosis, syndrome differentiation, and precision intervention.

Background: Long-term benzodiazepine use can lead to dependence and clinically significant withdrawal following discontinuation, highlighting the need to identify effective interventions for withdrawal-associated abnormalities. Methods: High-resolution mass spectrometry was used to characterize the constituents of a Panax quinquefolius-containing herbal extract (JYF) and evaluate their in vivo exposure in rats. Sixty-five C57BL/6 mice were randomly assigned to control, model, and low-, medium-, and high-dose JYF groups. Diazepam withdrawal was induced after 28 days of subcutaneous diazepam administration (12 mg/kg), and JYF was administered orally during the peri-withdrawal period for 7 days, beginning 4 days before diazepam discontinuation. Behavioral assessments, electroencephalographic/electromyographic (EEG/EMG) recordings, histopathological analysis, and neurochemical measurements were performed. Network proximity analysis, widely targeted metabolomics, targeted neurotransmitter quantification, and integrated pathway analysis were subsequently performed. Results: A total of 61 constituents were identified in JYF, of which 44 were detected in serum and 34 in brain tissue. Network proximity analysis highlighted genistein, columbamine, jatrorrhizine, and berberine as candidate constituents associated with withdrawal, anxiety/depression and sleep-related modules. JYF attenuated diazepam withdrawal-associated weight loss, anxiety-like behavior, sleep fragmentation, abnormal EEG activity, and elevations in corticosterone and orexin A. Metabolomic analyses revealed disturbances in lipid, energy, and amino acid metabolism, with tryptophan and phenylalanine metabolism emerging as prominent pathways associated with JYF intervention. Diazepam withdrawal also disrupted cerebral monoamine homeostasis, as reflected by increased serotonin and norepinephrine and decreased dopamine levels; these alterations generally shifted toward control levels after JYF intervention. Conclusions: JYF alleviates behavioral and sleep-related abnormalities associated with diazepam withdrawal. Its effects may be associated with alterations in brain metabolic homeostasis, including tryptophan- and phenylalanine-related metabolism and monoaminergic neurotransmission. Genistein and berberine were identified as candidate active constituents that warrant further experimental validation.

Polygonum capitatum (PC) is an ethnomedicine with reported antibacterial and anti-inflammatory activities and has been clinically used in urinary tract infection (UTI)-related disorders. However, its in vivo exposure characteristics and metabolically associated therapeutic mechanisms in acute pyelonephritis (AP) remain insufficiently understood. To address this issue, this study aimed to evaluate the therapeutic effects of PC in an Escherichia coli (E. coli)-induced rat model of AP and to explore constituents and metabolic pathways associated with its activity. Different PC extracts were screened for antibacterial and anti-inflammatory activities, and the 70% ethanol extract was selected for further study. Seven major compounds were quantified by HPLC. In AP rats, the pharmacokinetic profiles of these compounds in plasma and the renal cortex were analyzed by microdialysis-coupled HPLC-MS/MS. Pharmacodynamic evaluation included urinary bacterial load, urinalysis, renal function, inflammatory cytokines, and renal histopathology. Exploratory PK–PD analysis, untargeted renal metabolomics, and targeted metabolomics of the tryptophan–kynurenine (Trp–Kyn) pathway were also performed. The 70% ethanol extract of PC exhibited the strongest antibacterial and anti-inflammatory activities. The total content of seven active compounds was 3.85%, with gallic acid being the predominant compound (3.42%). Pharmacokinetic analysis revealed that gallic acid, protocatechuic acid, methyl gallate, and quercitrin achieved relatively high systemic exposure and renal distribution. In AP rats, the pharmacokinetic profiles of several compounds were altered, with increased plasma exposure of protocatechuic acid, vanillic acid, ethyl gallate, and syringic acid, while protocatechuic acid also showed higher exposure in the renal cortex. PC treatment reduced urinary bacterial load, improved renal function and urinalysis parameters, alleviated histopathological injury, and decreased inflammatory mediator levels, particularly in renal tissue. Exploratory PK–PD correlations were observed between several compounds and selected pharmacodynamic indicators. Metabolomic analysis suggested disturbances in glycerophospholipid metabolism and the Trp–Kyn pathway in AP rats, some of which were partially reversed after PC treatment. PC showed antibacterial and anti-inflammatory effects in AP rats. Gallic acid, protocatechuic acid, methyl gallate, and quercitrin may be candidate constituents associated with the therapeutic effects of PC, while modulation of glycerophospholipid metabolism and the Trp–Kyn pathway may be involved in its action against AP. These findings provide preclinical pharmacological evidence supporting the therapeutic potential of PC in AP.