Ethnobotanical study on herbal tea drinks in Guangxi, China.

BACKGROUND: Herbal tea drinks, different from classical Camellia beverages, are a wide variety of herbal drinks consumed for therapeutic purposes or health promotion. Herbal tea is widely consumed in Guangxi. However, the documentation on the plants for herbal tea and their related health benefits is still limited. METHODS: An ethnobotanical survey was conducted in 52 villages and 21 traditional markets in Guangxi from 2016 to 2021. Semi-structured interviews, key informant interviews, and structured questionnaires were applied to obtain ethnobotanical information of herbal tea, in which 463 informants had participated. Relative frequency of citation (RFC) and cultural food significance index (CFSI) were used to evaluate the most culturally significant herbal tea plants, and informant consensus factor (ICF) was applied to assess the agreement among informants. RESULTS: This study recorded 155 herbal tea species belonging to 49 families. The most commonly used parts included leaf (27.61%), whole plant (22.09%), branch and leaf (19.02%), and flower (13.50%). The most frequent preparation method of herbal tea was decoction. Herbal tea was very popular in Guangxi, attributing to its therapeutic value, special odor, and good taste. There are 41 health benefits classified into eight categories. Among them, clearing heat was the most medicinal effects. Local people had high consistency in tonic, removing cold and cough, improving blood circulation, and clearing heat away. Based on CFSI values of each species, the most culturally significant herbal tea species were Siraitia grosvenorii (Swingle) C. Jeffrey ex A. M. Lu & Zhi Y. Zhang, Plantago asiatica L., Gynostemma pentaphyllum (Thunb.) Makino, Zingiber officinale Roscoe, Pholidota chinensis Lindl., and Morus alba L. CONCLUSION: Herbal tea is a valuable heritage that carries the local people's traditional knowledge, like health care and religious belief. The recorded herbal tea species in this study possess tremendous potential for local economic development in the future. Further research on efficacy evaluation and product development of herbal tea species is necessary.

UPLC-QTOF-MS-based metabolomics and chemometrics studies of geographically diverse Acer truncatum leaves: A traditional herbal tea in Northern China.

Traditionally in Northern China, Acer truncatum leaves (ATL) have been used as herbal tea, now consumed worldwide. Few studies have reported ATL metabolites from different areas and their correlation with the environment. Thus, metabolomic analyses were conducted on ATL collected from twelve locations throughout four environmental zones in Northern China to understand the phytochemical differences with regards to environmental conditions. Sixty-four compounds, mostly flavonoids (FLAs) and gallic acid-containing natural products (GANPs), were characterized, including 34 previously unreported constituents from A. truncatum. Twenty-two markers were useful to differentiate ATL from the four environmental zones. Humidity, temperature, and sunshine duration are the predominant factors affecting FLAs and GANPs levels. Sunshine duration was positively correlated with eriodictyol (r = 0.994, p < 0.01), and humidity negatively with epicatechin gallate (r = -0.960, p < 0.05). These findings provide insights into ATL phytochemistry, aiding cultivation of A. truncatum tea with higher potential health benefits.

Deep Segmentation Feature-Based Radiomics Improves Recurrence Prediction of Hepatocellular Carcinoma.

Objective and Impact Statement. This study developed and validated a deep semantic segmentation feature-based radiomics (DSFR) model based on preoperative contrast-enhanced computed tomography (CECT) combined with clinical information to predict early recurrence (ER) of single hepatocellular carcinoma (HCC) after curative resection. ER prediction is of great significance to the therapeutic decision-making and surveillance strategy of HCC. Introduction. ER prediction is important for HCC. However, it cannot currently be adequately determined. Methods. Totally, 208 patients with single HCC after curative resection were retrospectively recruited into a model-development cohort (n=180) and an independent validation cohort (n=28). DSFR models based on different CT phases were developed. The optimal DSFR model was incorporated with clinical information to establish a DSFR-C model. An integrated nomogram based on the Cox regression was established. The DSFR signature was used to stratify high- and low-risk ER groups. Results. A portal phase-based DSFR model was selected as the optimal model (area under receiver operating characteristic curve (AUC): development cohort, 0.740; validation cohort, 0.717). The DSFR-C model achieved AUCs of 0.782 and 0.744 in the development and validation cohorts, respectively. In the development and validation cohorts, the integrated nomogram achieved C-index of 0.748 and 0.741 and time-dependent AUCs of 0.823 and 0.822, respectively, for recurrence-free survival (RFS) prediction. The RFS difference between the risk groups was statistically significant (P<0.0001 and P=0.045 in the development and validation cohorts, respectively). Conclusion. CECT-based DSFR can predict ER in single HCC after curative resection, and its combination with clinical information further improved the performance for ER prediction.