Objective: To investigate the impact of RhE antigen-matched transfusion during liver transplantation on early postoperative recovery and complications. Methods: In this retrospective cohort study, ninety-five patients undergoing liver transplantation at Kunming First People's Hospital between January 2022 and July 2025 were enrolled. Patients were divided into two groups: Group 1 (RhE-mismatched transfusion, n=57) and Group 2 (RhE-matched transfusion, n=38). The baseline data, complete blood counts, hepatic and renal function, coagulation parameters, and complication rates between the two groups were compared at postoperative days 1, 3, 5, 7, and 10. Survival analysis was performed using the Kaplan-Meier method. Results: The baseline characteristics were well-balanced and comparable between the two groups (all P>0.05). The early postoperative mortality rate in the mismatched group (31.58%, 18/57) was significantly higher than that in the matched group (10.53%, 4/38) (P=0.017). The incidence of postoperative hepatic encephalopathy was significantly higher in the mismatched group (50.88%, 29/57) than in the matched group (10.53%, 4/38) (P<0.001). The incidence of postoperative haemorrhage in the mismatched group (24.56%, 14/57) was higher than that in the matched group (5.26%, 2/38), with a statistically significant difference (P=0.014). The incidence of perioperative infection in the mismatched group (28.07%, 16/57) was higher than that in the matched group (10.53%, 4/38), with a statistically significant difference (P=0.04). Corresponding odds ratios (OR) and 95% confidence intervals indicated a lower risk of these adverse events in the matched group. On postoperative day 1, the change in activated partial thromboplastin time (-1.6, 20.5) in the mismatched group was greater than in the matched group (-0.2, 5.5). The change in international normalised ratio (-0.56, 1.22) in the mismatched group was greater than in the matched group (-0.18, 0.32), while the change in albumin (-4.0, 4.8) was smaller in the mismatched group than in the matched group (-2.5, 8.8). On postoperative day 5, the change in albumin (-0.41±7.83) in the mismatched group was smaller than in the matched group (2.68±4.53). At postoperative day 7, the change in albumin in the mismatched group (-0.61±7.38) was smaller than that in the matched group (2.51±5.85), while the change in D-dimer in the mismatched group (0.73, 7.4) was greater than that in the matched group (-1.6, 4.3). On postoperative day 10, the mismatched group exhibited significantly higher fibrinogen levels (-1.21, 1.78) than the matched group (-0.49, 0.97), and significantly longer prothrombin times (-11.3, -2.7) than the matched group (-6.2, -0.8) (all P<0.05). The matched group exhibited a mean overall survival (OS) of 32.803 months (95% CI:29.171-36.436 months), significantly exceeding the mismatched group's 28.996 months (95% CI:24.202-33.790 months). The log-rank test yielded statistically significant results (χ =4.307, P=0.038). Conclusion: Implementing RhE blood group-matched transfusion during liver transplantation may help reduce early postoperative mortality and the incidence of major complication rates, promote faster recovery of coagulation and liver function, and thereby improve short-term patient outcomes.

ObjectiveTo investigate the mechanism by which Wumeiwan suppresses the development and progression of colorectal cancer（CRC） through the regulation of fatty acid metabolic reprogramming， thereby providing new experimental evidence for the prevention and treatment of CRC. MethodsA total of 120 C57BL/6 mice were randomly divided into the blank group， model group， Wumeiwan high-， medium-， and low-dose groups（54， 27， 13.5 g·kg^-1）， and the mesalazine group（0.01 g·kg^-1）， with 20 mice in each group. Except for the blank group， all mice were subjected to azoxymethane（AOM）/dextran sulfate sodium（DSS） treatment to establish an inflammation-associated CRC model. One week after AOM injection， mice in the treatment groups received intragastric administration of the designated drugs， while the blank and model groups received an equal volume of purified water， continuing until 20 d after the intervention endpoint. Hematoxylin-eosin（HE） staining was used to observe colonic histopathological alterations， and immunohistochemistry for vascular endothelial growth factor（VEGF） was performed to evaluate neovascularization and tumor invasion. Metabolomics combined with Kyoto Encyclopedia of Genes and Genomes（KEGG） and metabolite set enrichment analysis（MSEA） was applied to identify key CRC-related metabolic pathways， which were further validated by transcriptomic Gene Ontology（GO） enrichment and gene heatmap analysis. Subsequently， Western blot was performed to determine the expression levels of core proteins in these pathways， and immunofluorescence was used to analyze their localization and co-expression patterns in tissues， thereby elucidating the mechanism of Wumeiwan from multiple biological dimensions. ResultsCompared with the blank group， mice in the model group exhibited a significant decrease in body weight and a significant increase in the disease activity index（DAI） score（P<0.05）， with pronounced colonic mucosal damage accompanied by aggravated tumor invasion. Compared with the model group， Wumeiwan intervention markedly improved body weight loss and reduced DAI score， attenuated mucosal injury， and significantly decreased VEGF expression level（P<0.05）. Multi-omics analysis revealed that differential metabolites and genes across groups were commonly enriched in fatty acid metabolism， fatty acid biosynthesis， and other lipid-related pathways. Relative to the blank group， the model group showed significant upregulation levels of fatty acid synthesis-related genes， including sterol regulatory element-binding protein 1（SREBP1）， fatty acid synthase（FASN）， stearoyl-CoA desaturase 1（SCD1）， as well as saturated fatty acids（P<0.05）. Compared with the model group， treatment with Wumeiwan significantly reduced the expression of key genes involved in fatty acid metabolic pathways， including SREBP1， FASN， and SCD1（P<0.05）. Western blot results further confirmed that proteins in this pathway were significantly elevated in the model group， whereas they were markedly downregulated following Wumeiwan treatment（P<0.05）. Immunofluorescence analysis demonstrated enhanced co-localization of SREBP1 with the cancer-associated fibroblast（CAF） marker α-smooth muscle actin（SMA） in the model group， whereas this co-localization signal was attenuated after Wumeiwan intervention（P<0.05）. ConclusionWumeiwan can improve survival outcomes and alleviate colonic pathological damage in CRC mice， its therapeutic mechanism may be closely associated with the regulation of fatty acid metabolic reprogramming mediated by the SREBP1/FASN/SCD1 signaling pathway.

ObjectiveTo investigate the influencing factors and independent risk factors for lower extremity deep vein thrombosis （DVT） in patients with acute necrotizing pancreatitis （ANP）， to analyze the effectiveness of three commonly used risk assessment models for thrombosis （Caprini score， Padua score， and Wells score）， and to provide a reference for clinical identification of high-risk individuals and optimization of prevention and treatment strategies. MethodsA retrospective analysis was performed for the clinical data of 320 patients with ANP who were admitted to Luzhou People’s Hospital and The Affiliated Hospital of Southwest Medical University from April 2013 to April 2024， and according to the presence or absence of DVT during hospitalization， the patients were divided into thrombosis group with 25 patients and control group with 295 patients. After propensity score matching， the two groups were compared in terms of past history and various examination results during hospitalization. The risk factors for lower extremity DVT in ANP patients during hospitalization were analyzed through univariate and multivariate Logistic regression， and a DVT risk prediction model was established based on independent influencing factors. The receiver operating characteristic （ROC） curve was used to assess the performance of models， and the DeLong test was used for comparison of the area under the ROC curve （AUC）， sensitivity， and specificity. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups； the chi-square test was used for comparison of categorical data between groups. ResultsAfter matching， the patients were divided into thrombosis group with 24 patients and control group with 112 patients. The clinical characteristics analysis showed that compared with the control group， the thrombosis group had significantly higher degree of pancreatic necrosis， D-dimer level， Bedside Index for Severity in Acute Pancreatitis （BISAP） score， and proportion of patients undergoing dialysis （all P<0.05）. The multivariable Logistic regression analysis showed that BISAP score， degree of pancreatic necrosis， and D-dimer level were independent risk factors for lower extremity DVT in ANP patients during hospitalization （all P<0.05）. The BISAP-Caprini score model had an AUC of 0.832 （95% confidence interval： 0.722 — 0.942， P<0.001） in predicting the risk of lower extremity DVT， with a Youden index of 1.661， an optimal cut-off value of 0.26， a sensitivity of 75.0%， and a specificity of 91.1%. ConclusionD-dimer， BISAP score， and the degree of pancreatic necrosis are independent risk factors for lower extremity DVT in patients with ANP during hospitalization， and the BISAP-Caprini score model can effectively predict the risk of DVT in ANP patients.

Objective To investigate the role and potential mechanism of secreted phosphoprotein 1 (SPP1)⁺ macrophages in the formation of chronic renal allograft fibrosis. Methods The expression features of SPP1⁺ macrophages in renal allografts of chronic allograft dysfunction (CAD) patients were analyzed based on single-cell transcriptome data of renal tissues from patients with CAD. Transcription factor VIPER analysis and DoRothEA transcription factor activity analysis were performed on the single-cell transcriptome data. Renal tissue samples were collected from kidney transplant recipients, including the CAD group (n=5) and the non-renal allograft fibrosis group (CTL group, n=5). A mouse model of chronic allograft rejection was established and divided into the allogeneic kidney transplantation group (CAD group, n=3) and the syngeneic kidney transplantation group (SYN group, n=3). Hematoxylin-eosin staining was used to detect renal tissue injury in mice, and Masson staining was used to detect renal tissue fibrosis. Immunofluorescence staining was performed to detect SPP1 expression in renal tissues of transplant recipients and mouse renal allografts. Bone marrow-derived macrophages (BMDMs) were extracted from mice and subjected to hypoxia stimulation. The expression of hypoxia-inducible factor (HIF)-1α and SPP1 was detected by Western blot, and SPP1 expression was detected by flow cytometry. BMDMs were transfected with HIF-1α overexpression plasmid and HIF-1α small interfering RNA (siRNA) followed by hypoxia intervention, and the expression of HIF-1α and SPP1 was detected by Western blot. Mouse aortic endothelial cells (MAECs) were co-cultured with the supernatant of BMDMs, and the expression of endothelial-mesenchymal transition (EndMT)-related markers was detected by Western blot and immunofluorescence. Results Single-cell transcriptome analysis showed that the proportion of SPP1⁺ macrophages in renal allograft tissues was significantly higher in the CAD group than in the CTL group (P<0.05). The renal injury score and the percentage of interstitial fibrotic area in the CAD group were significantly higher than those in the SYN group (both P<0.05). Immunofluorescence staining showed that the proportion of SPP1⁺ macrophages was increased in the CAD group compared with the CTL group, and also increased in the CAD group compared with the SYN group (both P<0.05). VIPER analysis and DoRothEA transcription factor activity analysis revealed activation of the hypoxia pathway and upregulated expression of transcription factors such as HIF-1α in SPP1⁺ macrophages. SPP1 expression was elevated in BMDMs under hypoxic conditions. Knockdown of HIF-1α inhibited hypoxia-induced SPP1 protein expression, whereas overexpression of HIF-1α upregulated SPP1 protein levels. After co-culture of hypoxia-induced BMDMs with MAECs, the expression levels of EndMT-related markers were increased. Conclusions SPP1⁺ macrophages differentiated under hypoxia are significantly infiltrated in the formation of chronic renal allograft fibrosis, and may promote renal allograft fibrosis by inducing EndMT in renal vascular endothelial cells.

Objective To investigate the trends in the global burden due to cystic echinococcosis from 1990 to 2021, and to predict the global burden of cystic echinococcosis from 2022 to 2035, so as to provide insights into formulation of the cystic echinococcosis control strategy. Methods The global age-standardized prevalence, mortality, disability-adjusted life years (DALYs) rates and their 95% uncertainty intervals (UI) of cystic echinococcosis from 1990 to 2021 were captured from the Global Burden of Disease Study 2021 (GBD 2021) database, and the trends in the global burden of cystic echinococcosis from 1990 to 2021 were analyzed using the Joinpoint regression model. The associations between the global burden of cystic echinococcosis and socio-demographic index (SDI) were examined using a smoothing spline model and frontier analysis, and the global burden of cystic echinococcosis was projected from 2022 to 2035 using the Bayesian age-period-cohort (BAPC) model. Results The global agestandardized prevalence, mortality and DALYs rates of cystic echinococcosis were 7.69/10⁵ [95% UI: (6.27/10⁵, 9.51/10⁵)], 0.02/10⁵ [95% UI: (0.01/10⁵, 0.02/10⁵)], and 1.32/10⁵ [95% UI: (0.99/10⁵, 1.69/10⁵)] in 2021. The global age-standardized prevalence of cystic echinococcosis appeared a tendency towards a rise by 0.14% per year from 1990 to 2021, and the global age-standardized mortality and DALYs rates of cystic echinococcosis appeared a tendency towards a decline by 4.68% and 4.01% per year from 1990 to 2021, respectively. Joinpoint regression analysis showed that global age-standardized prevalence of cystic echinococcosis appeared a tendency towards a decline from 1990 to 2000 [annual percent change (APC) = −0.66%, 95% confidence interval (CI): (−0.70%, −0.61%)] and from 2005 to 2015 [APC = −0.88%, 95% CI: (−0.93%, −0.82%)], and towards a rise from 2000 to 2005 [APC = 3.68%, 95% CI: (3.49%, 3.87%)] and from 2015 to 2021 [APC=0.30%, 95%CI: (0.19%, 0.40%)].Theagestandardized prevalence (r = −0.17, P < 0.05), mortality (r = −0.67, P < 0.05) and DALYs rates of cystic echinococcosis (r = −0.60, P < 0.05) all correlated negatively with SDI across 21 geographical regions from 1990 to 2021, and the age-standardized mortality (r = −0.61, P < 0.05) and DALYs rates (r = −0.44, P < 0.05) both correlated negatively with SDI across 204 countries and territories in 2021. Frontier analysis revealed that the age-standardized DALYs rate of cystic echinococcosis was still not in line with the frontier in some high-SDI countries or territories. In addition, the global age-standardized prevalence was projected with the BAPC model to appear a tendency towards a rise among both men [estimated annual percent change (EAPC) = 0.18%, 95% CI: (0.13%, 0.23%)] and women [EAPC = 0.29%, 95% CI: (0.24%, 0.34%)] from 2022 to 2035, and the global age-standardized mortality [men: EAPC = −4.71%, 95% CI: (−4.71%, −4.37%); women: EAPC = −4.74%, 95% CI: (−4.74%, −4.74%)] and DALYs rates [men: EAPC = −3.35%, 95% CI: (−3.36%, −3.34%); women: EAPC = −3.17%, 95% CI: (−3.18%, −3.16%)] were projected to appear a tendency towards a decline among both men and women. Conclusions The global burden of cystic echinococcosis appeared an overall tendency towards a decline from 1990 to 2021; however, the global prevalence of cystic echinococcosis is projected to appear a tendency towards a rise from 2022 to 2035. Intensified cystic echinococcosis control programmes are recommended.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

Objective: Data on syncopal donation-related vasovagal reaction (DRVR) collected from 74 blood centers between 2020 and 2023 was statistically analyzed to provide a reference for developing preventive strategies against syncopal DRVR. Methods: Data on blood donation adverse reactions and basic information of donors from 2020 to 2023 were collected through the information management system at monitoring sentinel sites. Statistical analysis was performed on the following aspects of syncopal DRVR: characteristics of donors who experienced syncope, reported incidence, triggers, duration, presence and occurrence time of syncope-related trauma, clinical management including outpatient and inpatient treatment, and severity grading. Results: From 2020 to 2023, 45 966 donation-related adverse reactions were recorded. Of these, 1 665 (3.72%) cases were syncopal DRVR. The incidence of syncopal DRVR decreased with age, being the highest in the 18-22 age group. Incidence was significantly higher in female donors than male donors, in first-time donors than repeat donors, and in university and individual donors than group donors (all P<0.05). There was no statistically significant difference among different blood donation locations (P>0.05). The top three triggers were tension, fatigue, and needle phobia or fear of blood. Among syncopal DRVR cases, 60.36% occurred during blood collection, 87.63% lasted for less than 60 seconds, and 5.05% were accompanied by trauma. Notably, 57.14% of these traumas occurred after donor had left the blood collection site. Syncope severity was graded based on required treatment: grade 1 (fully recovered without treatment, 95.50%); grade 2 (recovered after outpatient treatment, 4.02%); and grade 3 (recovered after inpatient treatment, 0.48%). Conclusion: By analyzing the data of syncopal DRVR cases, it is possible to provide a reference for formulating blood donor safety policies.

Objective To systematically evaluate the efficacy and safety of proximal gastrectomy (PG) versus total gastrectomy (TG) for the treatment of Siewert type Ⅱ/Ⅲ adenocarcinoma of the esophagogastric junction (AEG). Methods PubMed, The Cochrane Library, Web of Science, EMbase, CNKI, Wanfang, and VIP databases were searched for literature comparing the efficacy and safety of PG and TG for the treatment of Siewert type Ⅱ/Ⅲ AEG. The search period was from database inception to March 2023. Meta-analysis was performed using Review Manager 5.4 software. Results A total of 23 articles were included, including 16 retrospective cohort studies, 5 prospective cohort studies, and 2 randomized controlled trials. The total sample size was 2 826 patients, with 1 389 patients undergoing PG and 1 437 patients undergoing TG. Meta-analysis results showed that compared with TG, PG had less intraoperative blood loss [MD=−19.85, 95%CI (−37.20, −2.51), P=0.02] and shorter postoperative hospital stay [MD=−1.23, 95%CI (−2.38, −0.08), P=0.04]. TG had a greater number of lymph nodes dissected [MD=−6.20, 95%CI (−7.68, −4.71), P<0.001] and a lower incidence of reflux esophagitis [MD=3.02, 95%CI (1.24, 7.34), P=0.01]. There were no statistically significant differences between the two surgical approaches in terms of operative time, postoperative survival rate (1-year, 3-year, 5-year), and postoperative overall complications (P>0.05). Conclusion PG has advantages in terms of intraoperative blood loss and postoperative hospital stay, while TG has advantages in terms of the number of lymph nodes dissected and the incidence of reflux esophagitis. There is no significant difference in long-term survival between the two surgical approaches.

Objective To investigate the clinical value of 3.0 T functional magnetic resonance imaging in evaluating postoperative recurrence and treatment efficacy of glioma. Methods A retrospective analysis was conducted on the general clinical data of 67 patients who underwent glioma surgery at the Second Affiliated Hospital of Xingtai Medical University. All patients received chemotherapy for more than one month post-surgery. Recurrence of glioma was diagnosed based on secondary surgery or pathological biopsy results as the gold standard. From 3 to 6 months post-surgery, computerized tomography was used to measure cerebral blood volume (CBV), three-dimensional arterial spin labeling was used to measure cerebral blood flow (CBF) and relative CBF (rCBF), and diffusion-weighted imaging with and without contrast enhancement was used to measure apparent diffusion coefficient (ADC). Data were analyzed using SPSS 26.0 statistical software, and the t test or χ² test was used for inter-group comparisons based on data type. The receiver operating characteristic (ROC) curve was applied to evaluate the value of CBV, rCBF, and ADC in assessing postoperative recurrence and treatment efficacy of glioma. Results Patients with high-grade gliomas showed significantly higher CBV and rCBF and significantly lower ADC compared to those with low-grade gliomas (P < 0.05). The area under the ROC curve (AUC) of CBV, rCBF, and ADC in combination for grading glioma was 0.960, which was higher than those of individual indicators (0.790, 0.955, and 0.795, P < 0.05). The recurrence group had significantly higher CBV and rCBF and lower ADC compared to the non-recurrence group (P < 0.05). The AUC of CBV, rCBF, and ADC in combination for predicting postoperative glioma recurrence was 0.965, which was significantly higher than those of individual indicators (0.729, 0.929, and 0.941, P < 0.05). CBV and rCBF were lower and ADC was higher in the effective treatment group than in the ineffective treatment group (P < 0.05). The AUC of CBV, rCBF, and ADC in combination for evaluating glioma treatment efficacy was 0.985, which was higher than those of individual indicators (0.842, 0.898, and 0.961, P < 0.05). Conclusion The CBV, rCBF, and ADC in combination has shown high diagnostic accuracy and predictive efficacy in the evaluation of postoperative recurrence and treatment efficacy of glioma, which has important clinical application value.

This article systematically reviews and verifies the historical evolution of Stemonae Radix from the aspects of name， origin， harvesting and processing， quality and others by consulting ancient and modern literature， in order to provide reference for the development and utilization of famous classical formulas containing this medicinal herb. Stemonae Radix has a long history of application， and it derives its name from its distinctive growth pattern， featuring clusters of ten to several dozen underground tuberous roots. This morphology resembles that of certain plants in the genus Asparagus， leading to historical instances where tuberous roots from genus Asparagus were mistakenly used as Stemonae Radix. After the research， it can be concluded that Stemonae Radix was first recorded in Mingyi Bielu， and throughout history， Baidu has been recognized as its official name， though it also bears alternative names such as Baibing， Pofucao and Ye Tianmendong. The mainstream sources used throughout history have been the dried tuberous roots of Stemona sessilifolia， S. japonica or S. tuberosa from the family Stemonaceae. This aligns with the 2025 edition of Pharmacopoeia of the People's Republic of China（hereinafter referred to as Chinese Pharmacopoeia）. Additionally， Asparagus filicinus and A. officinalis from the genus Asparagus are common sources of confusion with Stemonae Radix. The three primitive plants are mainly distributed in the Yangtze River basin and southern China， exhibiting a wide distribution. Historically， wild harvesting was predominant， but cultivation is now established. In ancient times， the harvesting time was mostly in the second， third， and eighth lunar months， when roots were harvested and dried. Nowadays， it is more common to pick and excavate in the spring and autumn seasons. After excavation， the roots are washed， fibrous roots removed， briefly blanched in boiling water or steamed until no white core remains， and then sun-dried or oven-dried. In ancient times， the processing of Stemonae Radix primarily involved roasting（stir-frying）， wine roasting， or raw materials. Modern mainstream processing specifications include two types of raw and honey-roasted products. In terms of quality evaluation of the medicinal materials， ancient criteria of "preferring plump and moist roots" align with modern requirement favoring "thick， robust stems with firm texture". Evaluating quality with authenticity， since the Song dynasty， it has been highly praised to produce in Chuzhou and Hengyang as the best. It was an ancient method of fixing the production area to stabilize the medicinal origin， reflecting the ancient recognition of the therapeutic efficacy of plants belonging to the genus Stemona. The main functions of Stemonae Radix remain consistent throughout history， including relieving coughs， eliminating phlegm and parasites. Based on the research results， it is recommended that when developing famous classical formulas containing the medicinal material Stemonae Radix， the botanical source specified in the 2025 edition of Chinese Pharmacopoeia should be selected. The specific species can be determined according to the distribution of resources and the main production areas， and the origin and corresponding botanical source should be fixed. Processing methods should be chosen based on the prescription requirements. It is recommended to use raw products without specified requirements.