In this paper， by referring to ancient and modern literature， the textual research of Inulae Flos has been conducted to clarify the name， origin， production area， quality evaluation， harvesting， processing and others， so as to provide reference and basis for the development and utilization of famous classical formulas containing this herb. After textual research， it could be verified that the medicinal use of Inulae Flos was first recorded in Shennong Bencaojing of the Han dynasty. In successive dynasties， Xuanfuhua has been taken as the official name， and it also has other alternative names such as Jinfeicao， Daogeng and Jinqianhua. The period before the Song and Yuan dynasties， the main origin of Inulae Flos was the Asteraceae plant Inula japonica， and from the Ming and Qing dynasties to the present， I. japonica and I. britannica are the primary source. In addition to the dominant basal species， there are also regional species such as I. linariifolia， I. helianthus-aquatili， and I. hupehensis. The earliest recorded production areas in ancient times were Henan， Hubei and other places， and the literature records that it has been distributed throughout the country since modern times. The medicinal part is its flower， the harvesting and processing method recorded in the past dynasties is mainly harvested in the fifth and ninth lunar months， and dried in the sun， and the modern harvesting is mostly harvested in summer and autumn when the flowers bloom， in order to remove impurities， dry in the shade or dry in the sun. In addition， the roots， whole herbs and aerial parts are used as medicinal materials. In ancient times， there were no records about the quality of Inulae Flos， and in modern times， it is generally believed that the quality of complete flower structure， small receptacles， large blooms， yellow petals， long filaments， many fluffs， no fragments， and no branches is better. Ancient processing methods primarily involved cleaning， steaming， and sun-drying， supplemented by techniques such as boiling， roasting， burning， simmering， stir-frying， and honey-processing. Modern processing focuses mainly on cleaning the stems and leaves before use. Regarding the medicinal properties， ancient texts describe it as salty and sweet in taste， slightly warm in nature， and mildly toxic. Modern studies characterize it as bitter， pungent， and salty in taste， with a slightly warm nature. Its therapeutic effects remain consistent across eras， including descending Qi， resolving phlegm， promoting diuresis， and stopping vomiting. Based on the research results， it is recommended that when developing famous classical formulas containing Inulae Flos， either I. japonica or I. britannica should be used as the medicinal source. Processing methods should follow formula requirements， where no processing instructions are specified， the raw products may be used after cleaning.

In this paper， by referring to ancient and modern literature， the textual research of Inulae Flos has been conducted to clarify the name， origin， production area， quality evaluation， harvesting， processing and others， so as to provide reference and basis for the development and utilization of famous classical formulas containing this herb. After textual research， it could be verified that the medicinal use of Inulae Flos was first recorded in Shennong Bencaojing of the Han dynasty. In successive dynasties， Xuanfuhua has been taken as the official name， and it also has other alternative names such as Jinfeicao， Daogeng and Jinqianhua. The period before the Song and Yuan dynasties， the main origin of Inulae Flos was the Asteraceae plant Inula japonica， and from the Ming and Qing dynasties to the present， I. japonica and I. britannica are the primary source. In addition to the dominant basal species， there are also regional species such as I. linariifolia， I. helianthus-aquatili， and I. hupehensis. The earliest recorded production areas in ancient times were Henan， Hubei and other places， and the literature records that it has been distributed throughout the country since modern times. The medicinal part is its flower， the harvesting and processing method recorded in the past dynasties is mainly harvested in the fifth and ninth lunar months， and dried in the sun， and the modern harvesting is mostly harvested in summer and autumn when the flowers bloom， in order to remove impurities， dry in the shade or dry in the sun. In addition， the roots， whole herbs and aerial parts are used as medicinal materials. In ancient times， there were no records about the quality of Inulae Flos， and in modern times， it is generally believed that the quality of complete flower structure， small receptacles， large blooms， yellow petals， long filaments， many fluffs， no fragments， and no branches is better. Ancient processing methods primarily involved cleaning， steaming， and sun-drying， supplemented by techniques such as boiling， roasting， burning， simmering， stir-frying， and honey-processing. Modern processing focuses mainly on cleaning the stems and leaves before use. Regarding the medicinal properties， ancient texts describe it as salty and sweet in taste， slightly warm in nature， and mildly toxic. Modern studies characterize it as bitter， pungent， and salty in taste， with a slightly warm nature. Its therapeutic effects remain consistent across eras， including descending Qi， resolving phlegm， promoting diuresis， and stopping vomiting. Based on the research results， it is recommended that when developing famous classical formulas containing Inulae Flos， either I. japonica or I. britannica should be used as the medicinal source. Processing methods should follow formula requirements， where no processing instructions are specified， the raw products may be used after cleaning.

Objective To analyze the epidemiological characteristics and disease burden of liver cancer in Guangdong Province in 2020, and to provide a scientific foundation for the development of regionalized prevention and control strategies for liver cancer. Methods According to the cancer registry data of Guangdong Province, the incidence, mortality and age-standardized rate by Chinese standard population in 2020 were calculated to analyze the epidemiological characteristics of liver cancer. The disability adjusted life years (DALYs), year of life loss (YLL), year of lived with disability (YLD), and cause-eliminated life expectancy were used to assess the disease burden of liver cancer. Results In 2020, the crude incidence rate and the age-standardized incidence rate of liver cancer in Guangdong Province were 27.79/100 000 and 20.84/100 000，respectively, and the crude mortality rate and the age-standardized mortality rate of liver cancer were 25.49/100,000 and 17.64/100 000, respectively. The total DALY and DALY rate of liver cancer in Guangdong Province were 515 311 person-years and 513.83/100 000, respectively. After eliminating the causes of death from liver cancer, the life expectancy in Guangdong Province increased from 84.60 years to 84.99 years. All indicators consistently demonstrated that the burden of liver cancer was higher in males than that in females, and the burden of liver cancer was higher in rural areas than that in urban areas. Conclusion Liver cancer in Guangdong Province exhibits a high incidence, mortality and disease burden level in 2020. There are obvious differences of gender, age and region in cancer burden. It is necessary to strengthen liver cancer screening and diagnosis and treatment in men, the elderly and those in rural areas to reduce the burden of liver cancer gradually in Guangdong Province.

Objective: To develop a smart blood donation service assistant for popularizing donation-related knowledge to blood donors via intelligent Q&A support, thereby enabling precise service delivery. Methods: Based on the operational scenarios of the Zhejiang Provincial Blood Center, the system utilized the open-source Dify platform for agent orchestration, and integrated with the DeepSeek model as the language processing engine to support online real-time interaction. External tools, including the Amap API and MySQL database queries, were encapsulated via the Model Context Protocol (MCP). A professional blood knowledge base for Retrieval-Augmented Generation (RAG) was constructed using the BGE-M3 embedding model. An innovative dual-large language model collaborative verification mechanism was introduced to design the overall framework. The system was deployed privately using Docker containerization, and offline closed-loop optimization was achieved through customized Python scripts. Results: An interactive interface for blood donors was developed by integrating the chatflow Web component from Dify. The intelligent assistant Agent can recommend optimal blood donation sites and navigation routes by invoking the Amap API based on the donor's location. The Blood Donation Knowledge Agent enables timely responses to inquiries, along with reasonable suggestions and reminders. This agent specializes in the field of voluntary blood donation, empowering the assistant to answer doubts and questions for blood donors in the form of intelligent question-and-answer interaction. It also guides users through preliminary self-assessments, helping potential donors identify eligibility issues beforehand, thereby effectively increasing the on-site success rate of blood donation and reducing resource waste. Conclusion: The smart blood donation assistant validates the feasibility of the "Dify+MCP+RAG" technical architecture within the blood transfusion informatization field. The assistant not only improves the service experience for blood donors, but also, ensures the sustainable evolution of the system through its modular design and closed-loop optimization mechanism, thus providing valuable insights for the intelligent transformation of traditional blood donation service systems.

Ovarian cancer （OC） is one of the most common malignant tumors in women， with the mortality rate being the highest among gynaecological malignant tumors. As the atypical symptoms of OC are difficult to be detected in the early stage， most patients are already in the advanced stage when being diagnosed. As a result， the clinical treatment has limited effects. Currently， the main therapies for OC are surgery and chemotherapy， while their drug resistance and adverse reactions seriously reduce the quality of life of patients. In recent years， traditional Chinese medicine （TCM） has attracted the attention of clinicians and researchers because of its high efficacy， low toxicity， and mild side effects. According to the TCM philosophy of treatment based on syndrome differentiation， the Chinese medicines with multiple targets， wide range， and mild side effects can be screened based on the molecular targets involved in the occurrence and development of OC， which can bring out the unique advantages of TCM in the treatment of OC. Modern studies have shown that the occurrence and development of OC are closely related to the abnormal expression of multiple signaling pathways. The continued abnormal activation of the signal transducer and activator of transcription 3 （STAT3） signaling pathway can lead to abnormal proliferation and malignancy of OC. cause abnormal proliferation and malignant transformation of OC， which is closely related to the development of OC. In addition， studies have shown that Chinese medicine can inhibit the proliferation， angiogenesis， invasion， and metastasis and promote the autophagy and apoptosis of OC cells by regulating the Janus kinase 2 （JAK2）/STAT3 signaling pathway， providing new therapeutic strategies and ideas for the prevention and treatment of OC. This paper summarizes the role of JAK2/STAT3 signaling pathway in OC development by reviewing the relevant articles and reviews the mechanism and research progress of active components and compound prescriptions of Chinese medicine intervening in OC development by regulating the JAK2/STAT3 signaling pathway. This review is expected to provide a systematic reference for clinical research and drug development of OC.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.