This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

BACKGROUND: The mechanisms distinguishing metabolically healthy from unhealthy phenotypes within the same BMI categories remain unclear. This study aimed to investigate the associations between regional fat distribution and metabolically unhealthy phenotypes in Chinese adults across different BMI categories. METHODS: This cross-sectional study involving 11833 Chinese adults aged 20 years and older. Covariance analysis, adjusted for age, compared the percentage of regional fat (trunk, leg, or arm fat divided by whole-body fat) between metabolically healthy and unhealthy participants. Trends in regional fat percentage with the number of metabolic abnormalities were assessed by the Jonckheere-Terpstra test. Odds ratios (ORs) and their 95% confidence intervals (CIs) were estimated by logistic regression models. All analyses were performed separately by sex. RESULTS: In non-obese individuals, metabolically unhealthy participants exhibited higher percent trunk fat and lower percent leg fat compared to healthy participants. Additionally, percent trunk fat increased and percent leg fat decreased with the number of metabolic abnormalities. After adjustment for demographic and lifestyle factors, as well as BMI, higher percent trunk fat was associated with increased odds of being metabolically unhealthy [highest vs. lowest quartile: ORs (95%CI) of 1.64 (1.35, 2.00) for men and 2.00 (1.63, 2.46) for women]. Conversely, compared with the lowest quartile, the ORs (95%CI) of metabolically unhealthy phenotype in the highest quartile for percent arm and leg fat were 0.64 (0.53, 0.78) and 0.60 (0.49, 0.74) for men, and 0.72 (0.56, 0.93) and 0.46 (0.36, 0.59) for women, respectively. Significant interactions between BMI and percentage of trunk and leg fat were observed in both sexes, with stronger associations found in individuals with normal weight and overweight. CONCLUSIONS Trunk fat is associated with a higher risk of metabolically unhealthy phenotype, while leg and arm fat are protective factors. Regional fat distribution assessments are crucial for identifying metabolically unhealthy phenotypes, particularly in non-obese individuals.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Young Adult ; Adipose Tissue ; Body Fat Distribution ; Body Mass Index ; China/epidemiology* ; Cross-Sectional Studies ; Health Surveys ; Phenotype

Objective:This study aims to investigate the differences in hemostatic efficacy and patient comfort between an innovative domestically produced biodegradable nasal packing sponge and a traditional absorbent sponge following endoscopic nasal surgery. Methods:A prospective, randomized controlled trial design was utilized, including 30 patients who were divided into two groups according to random allocation, each receiving one of the two types of nasal packing. The study assessed the hemostatic efficacy, comfort, and safety of the materials by comparing the rates of no bleeding within 24 hours after packing, re-bleeding rates after 48 hours, pain ratings in the head and nasal areas, scores on a visual analog scale for nasal ocular symptoms, and safety indicators between the two groups. Results:The rates of no bleeding within 24 hours post-packing were 73.33% for both the experimental and control groups, with a no-bleeding rate of 100% after 48 hours in both groups. The pain rating in the head and nasal areas at various times post-packing was Grade Ⅰ（100%） in both groups, with no statistically significant difference（P=1.000）. The experimental groups sneezing score on the day of packing was（0.73±1.03）, lower than the control groups（2.27±1.67）, （P=0.007）; after 48 hours, the experimental groups sneezing score was（0.67±0.98）, also lower than the control groups（1.67±1.18）, （P=0.019）. There was no significant difference between the two groups in the Lund-Kennedy scoring during endoscopic examinations at the screening period, 7 days, 1 month, and 3 months post-packing（P>0.05）. Laboratory tests for other examination indicators were normal in both groups. Conclusion:The innovative domestically produced biodegradable nasal packing sponge not only provides hemostatic efficacy comparable to imported materials but also significantly improves patient comfort after surgery. It represents an economical and effective choice for nasal packing materials.
Humans ; Prospective Studies ; Surgical Sponges ; Endoscopy/methods* ; Male ; Female ; Epistaxis/prevention & control* ; Middle Aged ; Nasal Surgical Procedures/methods* ; Adult

Pyroptosis is an identified programmed cell death that has been highly linked to endoplasmic reticulum (ER) dynamics. However, the crucial proteins for modulating dynamic ER membrane curvature change that trigger pyroptosis are currently not well understood. In this study, a biotin-labeled chemical probe of potent pyroptosis inducer α-mangostin (α-MG) was synthesized. Through protein microarray analysis, reticulon-4 (RTN4/Nogo), a crucial regulator of ER membrane curvature, was identified as a target of α-MG. We observed that chemically induced proteasome degradation of RTN4 by α-MG through recruiting E3 ligase UBR5 significantly enhances the pyroptosis phenotype in cancer cells. Interestingly, the downregulation of RTN4 expression significantly facilitated a dynamic remodeling of ER membrane curvature through a transition from tubules to sheets, consequently leading to rapid fusion of the ER with the cell plasma membrane. In particular, the ER-to-plasma membrane fusion process is supported by the observed translocation of several crucial ER markers to the "bubble" structures of pyroptotic cells. Furthermore, α-MG-induced RTN4 knockdown leads to pyruvate kinase M2 (PKM2)-dependent conventional caspase-3/gasdermin E (GSDME) cleavages for pyroptosis progression. In vivo, we observed that chemical or genetic RTN4 knockdown significantly inhibited cancer cells growth, which further exhibited an antitumor immune response with anti-programmed death-1 (anti-PD-1). In translational research, RTN4 high expression was closely correlated with the tumor metastasis and death of patients. Taken together, RTN4 plays a fundamental role in inducing pyroptosis through the modulation of ER membrane curvature remodeling, thus representing a prospective druggable target for anticancer immunotherapy.
Pyroptosis/immunology* ; Humans ; Endoplasmic Reticulum/immunology* ; Animals ; Nogo Proteins/antagonists & inhibitors* ; Mice ; Cell Line, Tumor ; Xanthones/pharmacology* ; Neoplasms/pathology* ; Mice, Nude

BACKGROUND:Proximal humeral fracture in older adults is one of the three major osteoporotic fractures.Anatomic locking plate fixation is the first choice for most scholars to treat difficult-to-reduce and complex fracture types.However,the probability of reduction failure after the operation is high,which seriously affects patients'quality of life. OBJECTIVE:To investigate the correlation between deltoid tuberosity index and postoperative reduction failure of proximal humeral fractures in the elderly,analyze and filter preoperative independent risk factors for reduction failure of proximal humeral fractures in the elderly,and construct and verify the effectiveness of a clinical prediction model. METHODS:The clinical data of 153 elderly patients with proximal humeral fractures who met the diagnosis and inclusion criteria and received open reduction and locking plate surgery in Foshan Hospital of TCM from June 2012 to June 2021 were collected.The patients were divided into the reduction failure subgroup and the reduction maintenance subgroup.The independent risk factors were selected by multivariate Logistic regression analysis,and the nomogram was constructed by R language.After 1000 times of resampling by Bootstrap method,the Hosmer-Lemeshow goodness of fit correlation test,receiver operating characteristic curve,calibration curve,clinical decision,and influence curve were plotted to evaluate its goodness of fit,discrimination,calibration ability,and clinical application value.Fifty-five elderly patients with proximal humeral fractures from June 2013 to August 2021 were selected as the model's external validation group to evaluate the prediction model's stability and accuracy. RESULTS AND CONCLUSION:(1)Of the 153 patients in the training group,44 patients met reduction failure after internal plate fixation.The prevalence of postoperative reduction failure was 28.8%.Multivariate Logistic regression analysis identified that deltoid tuberosity index[OR=9.782,95%CI(3.798,25.194)],varus displacement[OR=4.209,95%CI(1.472,12.031)],and medial metaphyseal comminution[OR=4.278,95%CI(1.670,10.959)]were independent risk factors for postoperative reduction failure of proximal humeral fractures in older adults(P<0.05).(2)A nomogram based on independent risk factors was then constructed.The Hosmer-Lemeshow test results for the model of the training group showed that χ2=0.812(P=0.976)and area under curve=0.830[95%CI(0.762,0.898)].The calibration plot results showed that the model's predicted risk was in good agreement with the actual risk.The decision and clinical influence curves showed good clinical applicability.(3)In the validation group,the accuracy rate in practical applications was 86%,area under curve=0.902[95%CI(0.819,0.985)].(4)It is concluded that deltoid tuberosity index<1.44,medial metaphyseal comminution,and varus displacement were independent risk factors for reduction failure.(5)The internal and external validation of the risk prediction model demonstrated high discrimination,accuracy,and clinical applicability could be used to individually predict and screen the high-risk population of postoperative reduction failure of proximal humeral fractures in the elderly.The predicted number of patients at high risk is highly matched to the actual number of patients who occur when the model's threshold risk probability is above 65%,and clinicians should use targeted treatment.

BACKGROUND:Internal fixation and open reduction with locking plate is the main treatment for proximal humeral fractures with medial column instability.However,reduction failure is one of the main postoperative complications,and accurate risk factor assessment is beneficial for screening high-risk patients and clinical decision selection. OBJECTIVE:To construct four types of prediction models by different machine learning algorithms,compare the optimal model to analyze and sort the risk variables according to their weight scores on the impact of outcome,and explore their significance in guiding clinical diagnosis and treatment. METHODS:262 patients with proximal humeral fractures with medial column instability,aged(60.6±10.2)years,admitted to Foshan Hospital of Traditional Chinese Medicine between June 2012 and June 2022 were included.All patients underwent open reduction with locking plate surgery.According to the occurrence of reduction failure at 5-month follow-up,the patients were divided into a reduction failure group(n=64)and a reduction maintenance group(n=198).Clinical data of patients were collected,and model variables and their classification were determined.The data set was randomly divided into a training set and a test set according to a 7:3 ratio,and the optimal hyperparameters were obtained in the training set according to a 5-fold cross-over test.Four machine learning prediction models of logistic regression,random forest,support vector machine,and XGBoost were constructed,and the performance of different algorithms was observed in the test set using AUC,correctness,sensitivity,specificity,and F1 scores,so as to comprehensively evaluate the prediction performance of the models.The best-performing model was evaluated using SHAP to assess important risk variables and to evaluate its clinical guidance implications. RESULTS AND CONCLUSION:(1)There were significant differences between the two groups in deltoid tuberosity index,fracture type,fracture end with varus deformity before operation,fragment length of inferior metaphyseal of humerus,postoperative reduction,cortical support of medial column of proximal humerus,and insertion of calcar screw(P<0.05).(2)The best-combined performance of the four machine models was XGBoost.The AUC,accuracy,and F1 scores were 0.885,0.885,and 0.743,respectively;followed by random forest and support vector machine,with both models performing at approximately equal levels.Logistic regression had the worst combined performance.The SHAP interpretation tool was used in the optimal model and results showed that deltoid tuberosity index,medial humeral column cortical support,fracture type,fracture reduction quality,and the status of the calcar screw were important influencing fators for postoperative fracture reduction failure.(3)The accuracy of using machine learning to analyze clinical problems is superior to that of traditional logistic regression analysis methods.When dealing with high-dimensional data,the machine learning approach can solve multivariate interaction and covariance problems well.The SHAP interpretation tool can not only clarify the importance of individual variables but also obtain detailed information on the impact of dummy variables in each variable on the outcome.

AIM To analyze the component composition of Xeriga-4 Powder,and to determine the contents of phellodendrine,chlorogenic acid,gardenoside,berberine,rutin and curcumin.METHODS The high performance liquid chromatography-Q-exactive orbitrap mass spectrometry(HPLC-Q-Exactive-MS)qualitative analysis was performed on a 35℃thermostatic Agilent ZORBAX SB-Aq column(4.6 mm×150 mm,5 μm),with the mobile phase comprising of methanol-0.1%formic acid flowing at 0.35 mL/min in a gradient elution manner,and electron spray ionization source was adopted in positive and negative ion scanning.High performance liquid chromatography tandem mass spectrometry(HPLC-MS/MS)quantitative analysis was performed on a 35℃thermostatic Shim-pack GIST-HP C18 column(2.1 mm×100 mm,3 μm),with the mobile phase comprising of methanol-0.1%formic acid flowing at 0.25 mL/min in a gradient elution manner,and electron spray ionization source was adopted in positive and negative ion scanning with multiple reaction monitoring mode.RESULTS Total 65 constituents were identified,containing 19 alkaloids,13 organic acids,13 flavonoids,7 curcumins,6 iridoids,4 fatty acids,2 aldehydes,and 1 amino acid.Six constituents showed good linear relationships within their own ranges(r≥0.999 1),whose average recoveries were 96.44%-102.37%with the RSDs of 2.05%-3.74%.CONCLUSION This study can provide a reference for the quality control for Xieriga-4 Powder.

Objective To evaluate the long-term efficacy of transjugular intrahepatic portosystemic shunt(TIPS)with bare stents and Fluency covered stents in the treatment of portal hypertension,and to discuss its clinical value.Methods The clinical data of 29 patients with intractable ascites or esophagogastric fundus varices rupture and hemorrhage caused by cirrhotic portal hypertension,who received TIPS with bare stents and covered stents at the First Affiliated Hospital of Xinjiang Medical University of China(25 patients)and the Lishui Municipal Central Hospital of China(4 patients)between August 2012 and December 2017,were retrospectively analyzed.The patients were regularly followed up to check the survival status.The postoperative cumulative shunt patency rate and cumulative survival rate of the patients were analyzed by Kaplan-Meier method.Results The technical success rate of TIPS was 100％.The mean portal vein pressure was decreased from preoperative(40.21±3.24)cmH2O to postoperative(24.55±3.55)cmH2O(P＜0.05).The patients were followed up for 5.1-10.5 years.The postoperative 1-,3-,5-,7-year primary cumulative patency rates of the shunt were 89.7％,75.9％,75.9％ and 52.5％,respectively.The postoperative 5-,7-,9-and 10-year cumulative survival rates were 100％,66.9％,66.9％ and 33.4％,respectively.The incidence of hepatic encephalopathy was 13.8％(4/29).Conclusion Using bare stents combined with Fluency covered stents for TIPS is clinically safe and effective in the treatment of portal hypertension.This technique carries higher long-term shunt patency rate and low incidence of hepatic encephalopathy.Therefore,it can be used as a substitute for Viatorr stent when necessary.(J Intervent Radiol,2024,33:295-299)