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.

Gastroesophageal reflux is one of the most prevalent postoperative complications in patients with esophageal cancer, mainly manifested as heartburn and acid regurgitation. It can disturb sleep and trigger negative emotions, seriously impairing patients’ postoperative recovery process and long-term quality of life. This article reviews gastroesophageal reflux from five aspects: main clinical manifestations, hazards, assessment tools, influencing factors, and non-pharmacological interventions. It sorts out the advantages and disadvantages of existing assessment scales, analyzes risk factors related to surgery and individual patients, and summarizes the research status of non-pharmacological interventions including posture adjustment, diet modification and exercise. It aims to raise clinical healthcare professionals’ awareness of identifying and managing patients with postoperative reflux, and provide references for conducting assessments and formulating individualized comprehensive intervention schemes.

The recombinant human thyroid-stimulating hormone (rhTSH) can be used for differentiated thyroid cancer (DTC) preparation before ¹³¹I therapy, and follow-up. Since its approval by the American Food and Drug Administration (FDA) in 1998, rhTSH has been clinically used in European countries, the United States, and other countries for nearly 30 years. In April 2024, China’s first independently developed rhTSH agent was approved. Based on clinical experience and evidence from domestic and international studies, an expert consensus on the application of rhTSH has been developed following thorough consultations among experts. The consensus offers evidence-based recommendations to guide the appropriate use of rhTSH in clinical practice.

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Objective A Nomogram model of cognitive frailty was constructed and validated in hospitalized older adults,providing a reference for early screening,intervention and personalized management of cognitive frailty.Methods A convenience sampling approach was employed to recruit 322 elderly inpatients from a tertiary hospital in Beijing between October 2024 and February 2025 as study participants,and data were collected using the General Information Questionnaire,the Short Form-Mini-Nutritional Assessment,the Asens Insomnia Scale,the Activity of Daily Living Rating,the Self-Rating Anxiety Scale,the Geriatric Depression Scale-15,the Social Support Rating Scale,the Frailty Phenotype scale,the Subjective Cognitive Decline Questionnaire-9,the Mini-Mental State Examination,and the Clinical Dementia Rating.Lasso-Logistic regression was used to screen the variables,R software was used to draw the nomogram model;Bootstrap method was used for internal validation.Results Lasso-Logistic regression screened 8 predictors of age,depression,anxiety,support utilization,nutritional status,literacy,physical activity,and chronic pain,with an area under the subject operating characteristic curve of 0.830(95％CI:0.787-0.873),a sensitivity of 0.764,a specificity of 0.730,an accuracy of 0.748,and a calibrated curve,Brier score,and Hosmer-Lemeshow test(P=0.774)all showed that the model fit was good.Conclusion The Lasso-Logistic regression-based nomogram model of cognitive frailty in hospitalized older adults has good predictive performance and clinical utility,and can be used as a reference for early identification and intervention of cognitive decline in hospitalized older adults.

Objective:To investigate whether intermittent fasting alleviates insulin resistance in a polycystic ovary syndrome(PCOS) mouse model through the regulation of autophagy.Methods:Fifty 3-week-old female C57BL/6J mice were randomly assigned into the following groups using a random number table: normal control(NC) group( n=10), maintained on a standard chow diet; high-fat diet(HFD) group( n=10) fed a diet with 60% of calories derived from fat; and PCOS model group( n=30), established by combining a HFD with dehydroepiandrosterone(DHEA) administration. Successful modeling was confirmed by disrupted estrous cycles, hyperandrogenism, and polycystic ovarian morphology. The PCOS model mice were further divided into three groups: PCOS group( n=9), PCOS with intermittent fasting group(PCOS+ IF, n=9), and PCOS with intermittent fasting plus the autophagy inhibitor 3-methyladenine(3-MA) group(PCOS+ IF+ 3-MA, n=9). Autophagy levels were assessed by detecting markers LC3 and p62 and observing autophagosomes via transmission electron microscopy. Glucose tolerance test(GTT) and insulin tolerance test(ITT) were performed, and the area under the curve(AUC) was calculated to evaluate insulin resistance. Western blotting was used to detect phosphorylation levels of phosphatidylinositol 3-kinase(PI3K), protein kinase B(Akt), mammalian target of rapamycin(mTOR), and p70S6 kiase(p70S6K). Results:Compared with the NC group, the PCOS model group showed absent estrous cycles, significantly elevated serum testosterone, sex hormone binding globulin, and luteinizing hormone(LH) levels( P<0.001), and polycystic ovarian changes on hematoxylin-eosin staining, confirming successful model establishment. Immunohistochemistry, transmission electron microscopy, and Western blotting demonstrated that autophagy levels were increased in the PCOS+ IF group compared with the PCOS group, while 3-MA administration reduced the intermittent fasting - induced autophagy. The AUC values for both GTT and ITT were significantly lower in the PCOS+ IF group than those in the PCOS group( P<0.001, P=0.003), but increased in the PCOS+ IF+ 3-MA group compared to the PCOS+ IF group( P<0.001, P=0.020). Western blotting analysis showed that phosphorylation levels of PI3K, Akt, mTOR, and p70S6K were significantly decreased in the PCOS+ IF group compared with the PCOS group( P=0.002, P=0.001, P=0.001, and P<0.001, respectively), and increased in the PCOS+ IF+ 3-MA group compared with the PCOS+ IF group( P=0.021, P=0.041, P=0.047, and P=0.024, respectively). Conclusions:Intermittent fasting alleviates insulin resistance in a PCOS mouse model through inhibitiing PI3K/Akt/mTOR signaling pathway and promoting autophagy.

The aim of this updated guideline is to provide comprehensive recommendations for the management of gout in patients with common comorbidities, such as chronic kidney disease(CKD), cardiovascular disease(CVD), diabetes, osteoarthritis(OA), and gastrointestinal disorders. This guideline was developed by a multidisciplinary expert panel consisting of specialists in endocrinology, rheumatology, nephrology, cardiology, gastroenterology, and methodology. The development process adhered to standard methodologies, including PICO(population, intervention, comparator, and outcomes) question deconstruction, systematic literature review, the Grading of Recommendations Assessment, Development and Evaluation(GRADE) for evidence and recommendation evaluation, Delphi voting, and expert consensus. The guideline presents 26 evidence-based recommendations addressing 7 clinical questions for patients with hyperuricemia and gout in the context of comorbidities. Key recommendations include the maintenance of strict serum urate targets, particularly for patients with CKD stage≥3, chronic gouty arthritis, and OA, in order to prevent disease progression. In patients with CVD or diabetes, intra-articular triamcinolone is preferred over systemic glucocorticoids. Prioritized anti-inflammatory treatments for patients with CKD, gastrointestinal diseases and OA are recommended. The guideline also introduces emerging therapies, such as interleukin-1 inhibitors and selective urate transport inhibitors, as potential treatment options for refractory cases. The update offers a comprehensive, patient-centered approach to managing gout, particularly in individuals with associated comorbidities. Multidisciplinary collaboration and emerging new treatments and evidence ensure the optimization of the recommendations.

Objective To analyze dynamic contrast-enhanced MRI (DCE-MRI) radiomic features using machine learning algorithms, and to develop and validate a predictive model for HER-2 status in breast cancer. Methods The DCE-MRI images of 272 treatment-naive female patients with breast cancer between 2020 and 2022 were included in this study. Regions of interest (ROIs) were manually segmented using 3d-Slicer software, and radiomic features were extracted. All patients were randomly divided into training sets or validation sets at a ratio of 4∶1. The least absolute shrinkage and selection operator (LASSO) algorithm was used for feature screening on the training set, followed by the development of predictive models using six machine learning algorithms. Internal cross-validation was performed to compare the performance differences between the models. The best-performing model was selected, trained on the training set, and evaluated on the validation set. Evaluation metrics included area under the curve (AUC), sensitivity, specificity, precision, and recall rate. Results The clinical data of patients in the training set and validation set showed no significant differences. Five features were identified by the LASSO algorithm. With these features, six machine learning models were developed on the training set, and their predictive performance was internally cross-validated using the bagging method. XGBoost model had the highest mean AUC (0.696), followed by RF model (0.690); XGBoost model had the highest mean precision (0.756), followed by LR and RF models. Therefore, XGBoost was the optimal model. An HER-2 predictive model was built using the XGBoost algorithm on the training set and applied to the validation set. The AUC, precision, sensitivity, and specificity of the predictive model on the validation set were calculated, and ROC curves, precision-recall curves, calibration curves, and decision-making curves were plotted. Conclusion This study constructed and evaluated different DCE-MRI radiomics-based machine learning models for predicting HER-2 status in breast cancer. Among them, XGBoost algorithm performed the best and has the potential to become a new non-invasive method for preoperative prediction of HER-2 status, providing reliable evidence for personalized clinical diagnosis and treatment.