In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

This study explored the active ingredients for anti-angiogenesis in Wenyujin Rhizoma Concisum. Ten sesquiterpenoids were isolated from Wenyujin Rhizoma Concisum by silica gel column chromatography, thin layer chromatography, and high performance liquid chromatography. According to the results of multiple spectroscopic methods and circular dichroism, they were identified as wenyujinlactam A(1),(4S,7S)11-hydroxycurdione(2), 8,9-seco-4β-hydroxy-1α,5βH-7(11)-guaen-8,10-olide(3), curcumadione(4), phaeocaulisin E(5), procurcumadiol(6), zedouronediol(7), epiprocurcumenol(8), gajutsulactone A(9), and(7Z)-1β,4α-dihydroxy-5α,8β(H)-eudesm-7(11)-en-8,12-olide(10). Compounds 1 and 2 were new sesquiterpenoids. Compounds 1, 6, 8, and 10 can inhibit human umbilical vein endothelial cells(HUVEC) proliferation with IC_(50) values of 38.83, 45.19, 32.12, and 37.80 μmol·L~(-1), respectively. Compounds 1 and 10 can inhibit HUVEC migration with IC_(50) values of 29.70 and 36.48 μmol·L~(-1), respectively.
Sesquiterpenes/isolation & purification* ; Humans ; Drugs, Chinese Herbal/isolation & purification* ; Rhizome/chemistry* ; Human Umbilical Vein Endothelial Cells/drug effects* ; Molecular Structure ; Cell Proliferation/drug effects*

OBJECTIVE: To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures. METHODS: Based on relevant inclusion and exclusion criteria, 14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed, comprising 3 males and 11 females(aged from 27 to 82 years). The data were assigned randomized identifiers. A senior orthopedic physician reviewed the films and measured the ulnar deviation angle, radial height, palmar inclination angle, intra-articular step, and intra-articular gap for each case on the hospital's imaging system. Based on the reduction standard for distal radius fractures, cases were divided into reduction group and non-reduction group. Then, the data were sequentially imported into a human-computer interaction intelligent software, where a junior orthopedic physician analyzed the same radiological parameters, categorized cases, and measured fracture details. The categorization results from the software were consistent with manual classifications (6 reduction cases and 8 non-reduction cases). For non-reduction cases, the software performed further analyses, including bone segmentation and fracture recognition, generating 8 diagnostic reports containing fracture recognition information. For the 6 reduction cases, the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software, respectively. Bone segments requiring reduction were identified, verified by two senior physicians, and measured for displacement and rotation along the X (inward and outward), Z (front and back), and Y (up and down) axes. The AI software generated comprehensive diagnostic reports for these cases, which included all measurements and fracture recognition details. RESULTS: Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups, with identical data distributions. A paired sample t-test revealed no statistically significant differences (P>0.05) between the manual and software-based measurements for ulnar deviation angle, radial ulnar bone height, palmar inclination angle, intra-articular step, and joint space. In fracture recognition, the AI software correctly identified 10 C-type fractures and 4 B-type fractures. For the 6 reduction cases, a total of 24 bone fragments were analyzed across both methods. After verification, it was found that the bone fragments identified by the two methods were consistent. A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X, Y, and Z axes were consistent between the two methods. No statistically significant differences(P>0.05) were found between manual and software measurements for these parameters. CONCLUSION Human-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in identifying and locating type C1 distal radius fractures on CT imaging.
Humans ; Male ; Female ; Radius Fractures/surgery* ; Middle Aged ; Adult ; Aged ; Aged, 80 and over ; Tomography, X-Ray Computed/methods* ; Retrospective Studies ; Software ; Wrist Fractures

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

BACKGROUND: Biomarkers-based prediction of long-term risk of acute coronary syndrome (ACS) is scarce. We aim to develop a risk score integrating clinical routine information (C) and plasma biomarkers (B) for predicting long-term risk of ACS patients. METHODS: We included 2729 ACS patients from the OCEA (Observation of cardiovascular events in ACS patients). The earlier admitted 1910 patients were enrolled as development cohort; and the subsequently admitted 819 subjects were treated as validation cohort. We investigated 10-year risk of cardiovascular (CV) death, myocardial infarction (MI) and all cause death in these patients. Potential variables contributing to risk of clinical events were assessed using Cox regression models and a score was derived using main part of these variables. RESULTS: During 16,110 person-years of follow-up, there were 238 CV death/MI in the development cohort. The 7 most important predictors including in the final model were NT-proBNP, D-dimer, GDF-15, peripheral artery disease (PAD), Fibrinogen, ST-segment elevated MI (STEMI), left ventricular ejection fraction (LVEF), termed as CB-ACS score. C-index of the score for predication of cardiovascular events was 0.79 (95% CI: 0.76-0.82) in development cohort and 0.77 (95% CI: 0.76-0.78) in the validation cohort (5832 person-years of follow-up), which outperformed GRACE 2.0 and ABC-ACS risk score. The CB-ACS score was also well calibrated in development and validation cohort (Greenwood-Nam-D'Agostino: P = 0.70 and P = 0.07, respectively). CONCLUSIONS CB-ACS risk score provides a useful tool for long-term prediction of CV events in patients with ACS. This model outperforms GRACE 2.0 and ABC-ACS ischemic risk score.

[This corrects the article DOI: 10.1016/j.apsb.2022.03.002.].

The general models for intermediates quality analysis in the production process of Yaobitong capsule were established by near infrared spectroscopy (NIRS) combined with chemometrics, realizing the rapid determination of notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, ginsenoside Rd and moisture. The spray-dried fine powder and total mixed granule were selected as research objects. The contents of five saponins were determined by high performance liquid chromatography and the moisture content was determined by drying method. The measured contents were used as reference values. Meanwhile, NIR spectra were collected. After removing abnormal samples by Monte Carlo cross validation (MCCV), Monte Carlo uninformative variables elimination (MC-UVE) and competitive adaptive reweighted sampling (CARS) were used to select feature variables respectively. Based on the feature variables, quantitative models were established by partial least squares regression (PLSR), extreme learning machine (ELM) and ant lion optimization least squares support vector machine (ALO-LSSVM). The results showed that CARS-ALO-LSSVM model had the optimum effect. The correlation coefficients of the six index components were greater than 0.93, and the relative standard errors were controlled within 6%. ALO-LSSVM was more suitable for a large number of samples with rich information, and the prediction effect and stability of the model were significantly improved. The general models with good predicting effect can be used for the rapid quality determination of Yaobitong capsule intermediates.

Objective:To compare the clinical efficacy and safety of bronchial artery chemoembolization (BACE) combined with anlotinib (BACE+A) versus BACE alone in patients with stage III-IV non-small cell lung cancer (NSCLC).Methods:A total of 94 patients with advanced NSCLC treated at six interventional centers between November 2020 and November 2021 were retrospectively enrolled. Patients were divided into the BACE+A group ( n=46) and the BACE alone group ( n=48) based on treatment regimen. Baseline and perioperative clinical data were collected and compared between the two groups. Treatment response was evaluated using the modified Response Evaluation Criteria in Solid Tumors (mRECIST) at 1, 6, and 12 months after the first BACE procedure. Objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and treatment-related adverse events (AEs) were recorded. Kaplan-Meier survival curves were plotted to compare median OS and PFS between groups. Cox proportional hazards regression analysis was used to identify factors influencing OS and PFS. Results:The Kaplan-Meier analysis showed that the median OS was significantly longer in the BACE+A group (18.8 months, 95% CI 16.3-21.3) than in the BACE group (13.4 months, 95% CI 11.6-15.2) ( P=0.001). The median PFS was also significantly longer in the BACE+A group (9.0 months, 95% CI 7.3-10.7) compared to the BACE group (6.1 months, 95% CI 4.9-7.3) ( P=0.001). At 6 and 12 months post-first BACE, the ORR (43.5%, 40.0%) and DCR (89.1%, 83.3%) were significantly higher in the BACE+A group than in the BACE group (ORR: 20.8%, 14.8%; DCR: 66.7%, 59.3%) (all P<0.05). Multivariate Cox regression identified treatment with BACE+A ( HR=0.42, 95% CI 0.27-0.72, P=0.002), tumor stage ( HR=1.80, 95% CI 1.05-3.07, P=0.031), presence of pre-existing complications requiring intervention ( HR=2.72, 95% CI 1.65-4.50, P<0.001), and >2 BACE procedures ( HR=0.32, 95% CI 0.15-0.68, P=0.003) as independent factors influencing OS. Treatment with BACE+A ( HR=0.49, 95% CI 0.32-0.76, P=0.001), tumor stage ( HR=1.72, 95% CI 1.07-2.77, P=0.025), multi-arterial tumor blood supply ( HR=2.76, 95% CI 1.76-4.31, P<0.001), and>2 BACE procedures ( HR=0.40, 95% CI 0.22-0.71, P=0.002) were independent factors influencing PFS. There was no significant difference in BACE-related adverse events between the two groups (all P>0.05). Hypertension, fatigue, hand-foot syndrome, and anorexia were common anlotinib-specific adverse reactions in the combination group, but no grade 4 or higher adverse reactions were observed. Conclusions:BACE combined with anlotinib demonstrates superior efficacy compared to BACE alone in treating advanced NSCLC, significantly prolonging OS and PFS. The safety profile is manageable, with adverse events remaining within tolerable limits.

Thoracolumbar spine fracture often leads to severe pain, functional impairments, and neurological deficits, for which open reduction and internal fixation can effectively restore the spinal structural stability. Open decompression and reduction with internal fixation can help relieve spinal cord compression and improve spinal function in cases of concomitant cord injury. Although spinal stability can be restored through surgery, patients often face chronic pain and functional impairments postoperatively. A postoperative rehabilitation program is critical in optimizing therapeutic outcomes, reducing complications, and minimizing the risk of secondary injuries. However, current rehabilitation methods, such as physical therapy, functional training, and pain management, are confronted with problems in clinical practice, including significant variation in efficacy, poor patient adherence, and prolonged rehabilitation period. There is an urgent need for a unified rehabilitation strategy to address these problems. To this end, the Spinal Trauma Group of the Orthopedic Physicians Branch of the Chinese Medical Association and the Spine Health Professional Committee of the Chinese Human Health Technology Promotion Association organized experts from relevant fields to formulate Evidence-based guidelines for rehabilitation treatment after internal fixation of thoracolumbar spine fracture in adults ( version 2025) by integrating evidences from clinical researches and advanced rehabilitation concepts at home and abroad. A total number of 14 recommendations concerning the rehabilitation treatment with multimodal analgesia, psychological intervention, deep vein thrombosis prevention, core muscle and extremity exercise, appropriate use of braces, early weight-bearing, device-aided rehabilitation exercise, neuroregulatory therapy, rehabilitation team were put forward, aiming to standardize the post-operative rehabilitation process following internal fixation, promote the functional recovery, and enhance patients′ quality of life.