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.

BACKGROUND:Curcumin is the main active ingredient of turmeric and has significant medicinal value in anti-tumor,anti-inflammatory,antioxidant and other aspects.However,its poor water solubility,unstable chemical properties and easy decomposition lead to difficulty in extracting curcumin and low extraction yield.Therefore,it is particularly important to optimize the curcumin extraction method.OBJECTIVE:To enhance the extraction yield and utilization value of curcumin and optimize the curcumin extraction process and curcumin nanoparticle preparation process.METHODS:Curcumin was extracted from turmeric by ethanol extraction,ultrasonic extraction,ionic liquid extraction,enzyme extraction,and ionic liquid combined with ultrasonic assisted enzyme extraction.The curcumin extraction yield was detected by high performance liquid chromatography;the best extraction method was determined,and subsequent process optimization experiments were carried out.The curcumin extraction yield was the response value with the type of ionic liquid,reaction temperature,ultrasonic time,liquid-to-solid ratio,ionic liquid concentration,and enzyme-drug mass ratio as parameters.The optimal production process of ionic liquid combined with ultrasonic assisted enzyme extraction was determined by single factor combined response surface experiment.The optimal process for preparing curcumin nanoparticles by ionic crosslinking method was determined by single factor combined response surface experiment with acetic acid concentration,chitosan to sodium tripolyphosphate mass ratio,stirring rate,curcumin mass concentration,sodium tripolyphosphate mass concentration,and chitosan mass concentration as parameters,and drug encapsulation efficiency as response value.Curcumin nanoparticles were prepared under the optimal process,and the particle size,polydispersity index,Zata potential value,drug loading,stability,hemolysis rate,and antioxidant capacity in vivo and in vitro of the nanoparticles were detected.RESULTS AND CONCLUSION:(1)Among the five extraction methods,the curcumin yield of ionic liquid combined with ultrasound-assisted enzyme extraction was the highest,and this method was selected as the curcumin extraction method for subsequent experiments.The results of single factor combined response surface experiment showed that the optimal process for curcumin extraction was:ionic liquid selected 1-hexyl-3-methylimidazolium chloride,reaction temperature 55 ℃,liquid-to-solid ratio 40 mL/g,ultrasound time 57 minutes,ionic liquid concentration 57％,enzyme-drug mass ratio 3.5:10,and the obtained turmeric extraction yield was 3.10％.The optimal preparation process of curcumin nanoparticles was:glacial acetic acid concentration 0.5％,chitosan and sodium tripolyphosphate mass ratio 5.0:1,stirring speed 150 r/min,curcumin mass concentration 2.23 mg/mL,sodium tripolyphosphate mass concentration 1.45 mg/mL,chitosan mass concentration 3.63 mg/mL,and the obtained drug encapsulation efficiency was 90.61％.(2)The drug loading of curcumin nanoparticles was(14.49±0.23)％,the average particle size was(76.95±1.65)nm,the polydispersity coefficient was 0.15±0.02,and the Zata potential value was(32.37±1.46)mV.The curcumin nanoparticles had good stability and blood compatibility,did not induce hemolysis,and had stronger antioxidant capacity in vivo and in vitro than free curcumin.(3)The results show that the process optimization not only solves the problems of low extraction yield,poor solubility,and low bioavailability of curcumin,but also enhances its antioxidant activity in vivo and in vitro.

BACKGROUND:Curcumin is the main active ingredient of turmeric and has significant medicinal value in anti-tumor,anti-inflammatory,antioxidant and other aspects.However,its poor water solubility,unstable chemical properties and easy decomposition lead to difficulty in extracting curcumin and low extraction yield.Therefore,it is particularly important to optimize the curcumin extraction method.OBJECTIVE:To enhance the extraction yield and utilization value of curcumin and optimize the curcumin extraction process and curcumin nanoparticle preparation process.METHODS:Curcumin was extracted from turmeric by ethanol extraction,ultrasonic extraction,ionic liquid extraction,enzyme extraction,and ionic liquid combined with ultrasonic assisted enzyme extraction.The curcumin extraction yield was detected by high performance liquid chromatography;the best extraction method was determined,and subsequent process optimization experiments were carried out.The curcumin extraction yield was the response value with the type of ionic liquid,reaction temperature,ultrasonic time,liquid-to-solid ratio,ionic liquid concentration,and enzyme-drug mass ratio as parameters.The optimal production process of ionic liquid combined with ultrasonic assisted enzyme extraction was determined by single factor combined response surface experiment.The optimal process for preparing curcumin nanoparticles by ionic crosslinking method was determined by single factor combined response surface experiment with acetic acid concentration,chitosan to sodium tripolyphosphate mass ratio,stirring rate,curcumin mass concentration,sodium tripolyphosphate mass concentration,and chitosan mass concentration as parameters,and drug encapsulation efficiency as response value.Curcumin nanoparticles were prepared under the optimal process,and the particle size,polydispersity index,Zata potential value,drug loading,stability,hemolysis rate,and antioxidant capacity in vivo and in vitro of the nanoparticles were detected.RESULTS AND CONCLUSION:(1)Among the five extraction methods,the curcumin yield of ionic liquid combined with ultrasound-assisted enzyme extraction was the highest,and this method was selected as the curcumin extraction method for subsequent experiments.The results of single factor combined response surface experiment showed that the optimal process for curcumin extraction was:ionic liquid selected 1-hexyl-3-methylimidazolium chloride,reaction temperature 55 ℃,liquid-to-solid ratio 40 mL/g,ultrasound time 57 minutes,ionic liquid concentration 57％,enzyme-drug mass ratio 3.5:10,and the obtained turmeric extraction yield was 3.10％.The optimal preparation process of curcumin nanoparticles was:glacial acetic acid concentration 0.5％,chitosan and sodium tripolyphosphate mass ratio 5.0:1,stirring speed 150 r/min,curcumin mass concentration 2.23 mg/mL,sodium tripolyphosphate mass concentration 1.45 mg/mL,chitosan mass concentration 3.63 mg/mL,and the obtained drug encapsulation efficiency was 90.61％.(2)The drug loading of curcumin nanoparticles was(14.49±0.23)％,the average particle size was(76.95±1.65)nm,the polydispersity coefficient was 0.15±0.02,and the Zata potential value was(32.37±1.46)mV.The curcumin nanoparticles had good stability and blood compatibility,did not induce hemolysis,and had stronger antioxidant capacity in vivo and in vitro than free curcumin.(3)The results show that the process optimization not only solves the problems of low extraction yield,poor solubility,and low bioavailability of curcumin,but also enhances its antioxidant activity in vivo and in vitro.

Objective: Scutellarin in Shuganning injection has potential allergenicity and is prone to causing anaphylactoid reactions. There is an urgent need to establish a simple and rapid chromatographic quantitative method to achieve the limit control of scutellarin in Shuganning injection.
Methods: For scutellarin, HPLC method was used in the quantitative analysis using a Shim-pack GIS C₁₈ (2.1 mm×150 mm, 5 μm) column. The mobile phase was a blend of 0.1% trifluoroacetic acid in water and acetonitrile, and gradient elution progress was applied for the whole process. The flow rate was 0.3 mL·min^-1 and the column temperature was maintained at 37 ℃. The detecting wavelength was 320 nm.
Results: The linear regression equation was y=51 456x-27 352, the correlation coefficient r=0.999 8, namely the calibration curve was linear in the range of 1.02-102.00 μg·mL^-1; the average recovery was 103.76%; the detection and quantification limit for determining scutellarin was 0.16 μg·mL^-1 and 0.57 μg·mL^-1, respectively; the injection sample was stable at room temperature for 48 h.
Conclusion: This method is easy to operate, reproducible and has high accuracy, thus can be used for quality control of Shuganning injection.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Background: Maturity-onset diabetes of the young (MODY) due to variants of hepatocyte nuclear factor 1-beta (HNF1β) (MODY5) has not been well studied in the Chinese population. This study aimed to estimate its prevalence and evaluate the application of a clinical screening method (Faguer score) in Chinese early-onset diabetes (EOD) patients. Methods: Among 679 EOD patients clinically diagnosed with type 2 diabetes mellitus (age at diagnosis ≤40 years), the exons of HNF1β were sequenced. Functional impact of rare variants was evaluated using a dual-luciferase reporter system. Faguer scores ≥8 prompted multiplex ligation-dependent probe amplification (MLPA) for large deletions. Pathogenicity of HNF1β variants was assessed following the American College of Medical Genetics and Genomics (ACMG) guidelines. Results: Two rare HNF1β missense mutations (E105K and G454R) were identified by sequencing in five patients, showing functional impact in vitro. Another patient was found to have a whole-gene deletion by MLPA in 22 patients with the Faguer score above 8. Following ACMG guidelines, six patients carrying pathogenic or likely pathogenic variant were diagnosed with MODY5. The estimated prevalence of MODY5 in Chinese EOD patients was approximately 0.9% or higher. Conclusion MODY5 is not uncommon in China. The Faguer score is helpful in deciding whether to perform MLPA analysis on patients with negative sequencing results.