integrative-multi-omics-analysis-buti-huatan-tang-chronic-obstructive

Integrative Multi-omics Analysis of Buti Huatan Tang in Chronic Obstructive Pulmonary Disease

This study utilized a multi-omics and computational biology framework to investigate the therapeutic potential of the Traditional Chinese Medicine (TCM) ...

The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine

Obesity is a common feature in women with polycystic ovary syndrome (PCOS) and potentially significantly influences reproductive function. However, opinions are divided as to which factor is a more appropriate obesity predictor of reproductive outcomes. The aim of this study was to investigate the discriminatory capability of anthropometric measures in predicting reproductive outcomes in Chinese women with PCOS.

The discriminatory capability of anthropometric measures in predicting reproductive outcomes in Chinese women with PCOS.

Capitatae Fructus (CF), an ethnomedicinal resource with both edible and medicinal values in Southwest China, has an incomplete quality evaluation system, and the regulatory mechanisms of environmental factors on its bioactive component accumulation remain unclear. In this study, 37 CF batches from 6 producing areas in Sichuan and Yunnan Provinces were analyzed. High-performance liquid chromatography (HPLC) was used to establish a fingerprint with good precision and reproducibility and conduct multi-component quantitative analysis, combined with hierarchical cluster analysis (HCA), Correlation analysis, principal component analysis (PCA), and hierarchical partitioning (HP) to investigate CF's chemical characteristics and environmental regulation patterns. Results showed an HPLC fingerprint of CF was successfully constructed, with 15 common peaks matched and 5 key bioactive compounds (gallic acid, hyperoside, isoquercitrin, quercitrin, quercetin) identified. HCA classified the samples into two distinct clusters: the first cluster covers low-, medium-, and high-altitude regions, among which the gallic acid contents (L26, L27) and quercetin content (L28) from Miyi County (low-altitude area) are higher than those of other sample batches. In contrast, the second cluster, concentrated in medium-altitude regions, generally exhibits lower contents of key components. Results from PCA show that sample L28 (Miyi County, low-altitude area) has the highest comprehensive score, which further confirms this altitude-related distribution characteristic of the compounds in CF. Correlation analysis was conducted to examine relationships between the 5 key compounds, showing that gallic acid was significantly positively correlated with hyperoside (r = 0.46, P < 0.01), and hyperoside was extremely significantly positively correlated with isoquercitrin (r = 0.91, P < 0.001). HP analysis was used to eliminate multicollinearity among environmental factors, confirming annual total solar radiation and annual cumulative ultraviolet radiation as core regulatory factors for CF component accumulation. Among the 5 compounds, gallic acid and hyperoside exhibited the highest sensitivity to environmental changes (R² = 0.76 and 0.71, respectively). Based on the above findings, Miyi County was identified as a high-quality producing area for CF, with gallic acid and hyperoside confirmed as the core quality indicators of CF. East longitude was determined to be the main environmental factor affecting CF component accumulation, while Annual Total Solar Radiation, Annual Cumulative Ultraviolet Radiation, and Annual Total Solar Radiation Difference were the synergistic driving factors. This study initially established a quality evaluation system for CF, providing support for its standardized development and sustainable utilization.

Article	Year
The discriminatory capability of anthropometric measures in predicting reproductive outcomes in Chinese women with PCOS. Journal of ovarian research\| PubMed ID: 39272150	2024
Quality evaluation of Capitatae Fructus from different geographical regions in China. Scientific reports\| PubMed ID: 41422318	2025

Qing Xia

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