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1.
J Ethnopharmacol ; 328: 118043, 2024 Jun 28.
Artigo em Inglês | MEDLINE | ID: mdl-38490289

RESUMO

ETHNOPHARMACOLOGICAL RELEVANCE: Perturbations in airway microbiota composition and disruption of microbe-metabolite interactions have been observed in respiratory infectious diseases (RIDs). The Yinhuang (YH) buccal tablet, as an ancient Chinese medicinal formula, has been traditionally employed for the management of upper RIDs. However, there is a lack of evidence for the effects of YH buccal tablets on upper respiratory tract microbiota and circulating metabolites. AIM OF THE STUDY: The aim of this study was to analyze the changes in respiratory microbiota composition and circulating metabolite profile after YH buccal tablets administration. MATERIALS AND METHODS: Throat swab samples and serum samples were collected from 60 healthy subjects for high-throughput 16S ribosomal RNA gene (16S rRNA) sequencing and non-targeted Ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) analysis. RESULTS: Airway microbial composition changed significantly after YH administration. The abundance of Actinomyces and Prevotella_7 increased, while the abundance of potentially pathogenic Pseudomonas and Corynebacterium decreased. A total of 168 significant HMDB taxonomic metabolites were identified in serum samples, of which lipid metabolites accounted for the largest proportion. Correlation analysis showed that circulatory metabolites were significantly correlated with changes in airway microbiota composition. CONCLUSIONS: YH buccal tablets can inhibit opportunistic pathogens, increase beneficial microorganisms in the upper respiratory tract, and regulate the body's metabolic pathways. These findings provide insights into the mechanism of action of YH buccal tablets in the treatment and prevention of respiratory diseases.


Assuntos
Medicamentos de Ervas Chinesas , Microbiota , Humanos , Cromatografia Líquida , RNA Ribossômico 16S/genética , Medicamentos de Ervas Chinesas/farmacologia , Medicamentos de Ervas Chinesas/metabolismo , Espectrometria de Massas em Tandem/métodos , Sistema Respiratório , Comprimidos
2.
Front Microbiol ; 13: 947112, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36090063

RESUMO

Severe influenza A virus infection leads to overwhelming inflammatory responses and cellular apoptosis, which causes lung injury and contributes to high mortality and morbidity. The gut microbiome altered in response to the infection might influence the disease progression and the treatment outcome. Cangma Huadu (CMHD) granules, an in-hospital preparation of traditional Chinese medicine, have been shown to be favorable in the clinical treatment of influenza. However, the effects and mechanisms of CMHD granules on severe influenza pneumonia and its mechanisms are not well-known. In this study, a lethal influenza A (H1N1) A/Puerto Rico/8/34 virus (PR8)-infected mice model was established, and the 16S ribosomal RNA (16S rRNA) V3-V4 region sequencing of the intestinal microbiome was conducted. We revealed that the oral administration of CMHD granules protects mice against higher mortality, enhanced weight loss, overwhelmed interferon-γ concentration, lung viral titers, and severe lung pathological injury in PR8-infected mice. CMHD granules' administration downregulated the levels of interleukin (IL)-1ß, tumor necrosis factor-α, and malondialdehyde, while it upregulated the levels of IL-10, superoxide dismutase, and glutathione peroxidase. Subsequently, it decreased the protein ratio of B-cell lymphoma-2/Bcl-2-associated X and the expression of cleaved caspase-3. The diversity and compositions of the gut microbes were altered profoundly after the administration of CMHD granules in PR8-infected mice. A higher abundance of Bifidobacterium, Parasutterella, Bacteroides, and Faecalibaculum was observed in the CMHD group, and a higher abundance of Lactobacillus and Turicibacter was observed in the positive drug Ribavirin group. The linear discriminant analysis effect size also revealed a higher proportion of Bacteroides and Bifidobacterium_pseudolongum characterized in the CMHD group. These results demonstrated that CMHD granules are a promising strategy for managing severe influenza and attenuating severe lung damage via reducing viral titer, inflammatory responses, and oxidative stress. The mechanisms are involved in repressed Bcl-2-regulated apoptosis and altered composition and diversity of the gut microbiome.

3.
Front Pharmacol ; 11: 584057, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33041827

RESUMO

The outbreak of coronavirus disease 2019 (COVID-19) has affected millions of people worldwide. Critically ill COVID-19 patients develop viral septic syndrome, including inflammatory damage, immune dysfunction, and coagulation disorder. In this study, we investigated ShenFuHuang formula (SFH), a traditional Chinese medicine, which has been widely used as complementary therapy for clinical treatment of COVID-19 in Wuhan, to understand its pharmacological properties. Results of systems pharmacology identified 49 active compounds of SFH and their 69 potential targets, including GSK3ß, ESR1, PPARG, PTGS2, AKR1B10, and MAPK14. Network analysis illustrated that the targets of SFH may be involved in viral disease, bacterial infection/mycosis, and metabolic disease. Moreover, signaling pathway analysis showed that Toll-like receptors, MAPK, PPAR, VEGF, NOD-like receptor, and NF-kappa B signaling pathways are highly connected with the potential targets of SFH. We further employed multiple zebrafish models to confirm the pharmacological effects of SFH. Results showed that SFH treatment significantly inhibited the inflammatory damage by reducing the generation of neutrophils in Poly (I:C)-induced viral infection model. Moreover, SFH treatment could improve the phagocytosis of macrophages and enhance the expression of immune genes in an immune deficiency model. Furthermore, SFH treatment exhibited promising anti-thrombosis effect in a thrombus model. This study provided additional evidence of SFH formula for treating COVID-19 patients with septic syndrome using multiple-scale estimation.

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