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*

OBJECTIVES: The study of medicine formulas is a core component of traditional Chinese medicine (TCM), yet traditional learning methods often lack interactivity and contextual understanding, making it challenging for beginners to grasp the intricate composition rules of formulas. To address this gap, we introduce Formula-S, a situated visualization method for TCM formula learning in augmented reality (AR) and evaluate its performance. This study aims to evaluate the effectiveness of Formula-S in enhancing TCM formula learning for beginners by comparing it with traditional text-based formula learning and web-based visualization. METHODS: Formula-S is an interactive AR tool designed for TCM formula learning, featuring three modes (3D, Web, and Table). The dataset included TCM formulas and herb properties extracted from authoritative references, including textbook and the SymMap database. In Formula-S, the hierarchical visualization of the formulas as herbal medicine compositions, is linked to the multidimensional herb attribute visualization and embedded in the real world, where real herb samples are presented. To evaluate its effectiveness, a controlled study (n=30) was conducted.Participants who had no formal TCM knowledge were tasked with herbal medicine identification, formula composition, and recognition. In the study, participants interacted with the AR tool through HoloLens 2. Data were collected on both task performance (accuracy and response time) and user experience, with a focus on task efficiency, accuracy, and user preference across the different learning modes. Results The situated visualization method of Formula-S had comparable accuracy to other methods but shorter response time for herbal formula learning tasks. Regarding user experience, our new approach demonstrated the highest system usability and lowest task load, effectively reducing cognitive load and allowing users to complete tasks with greater ease and efficiency. Participants reported that Formula-S enhanced their learning experience through its intuitive interface and immersive AR environment, suggesting this approach offers usability advantages for TCM education. CONCLUSIONS The situated visualization method in Formula-S offers more efficient and accurate searching capabilities compared to traditional and web-based methods. Additionally, it provides superior contextual understanding of TCM formulas, making it a promising new solution for TCM learning.
Medicine, Chinese Traditional/methods* ; Humans ; Learning ; Drugs, Chinese Herbal

OBJECTIVE To construct three-class （insufficient， normal， excessive） and two-class （insufficient， normal） models for predicting plasma concentration of valproic acid （VPA）， and compare the performance of these two models， with the aim of providing a reference for formulating clinical medication strategies. METHODS The clinical data of 480 patients who received VPA treatment and underwent blood concentration test at the Xi’an International Medical Center Hospital were collected from November 2022 to September 2024 （a total of 695 sets of data）. In this study， predictive models were constructed for target variables of three-class and two-class models. Feature ranking and selection were carried out using XGBoost scores. Twelve different machine learning algorithms were used for training and validation， and the performance of the models was evaluated using three indexes: accuracy， F1 score， and the area under the working characteristic curve of the subject （AUC）. RESULTS XGBoost feature importance scores revealed that in the three-class model， the importance ranking of kidney disease and electrolyte disorders was higher. However， in the two-class model， the importance ranking of these features significantly decreased， suggesting a close association with the excessive blood concentration of VPA. In the three-class model， Random Forest method performed best， with F1 score of 0.704 0 and AUC of 0.519 3 on the test set； while in the two-class model， CatBoost method performed optimally， with F1 score of 0.785 7 and AUC of 0.819 5 on the test set. CONCLUSIONS The constructed three-class model has the ability to predict excessive VPA blood concentration， but its prediction and model generalization abilities are poor； the constructed two-class model can only perform classification prediction for insufficient and normal blood concentration cases， but its model performance is stronger.

OBJECTIVE To provide standardized whole-process guidance on drug traceability codes for medical institutions in Sichuan province， ensuring medication safety and compliance with medical insurance supervision requirements. METHODS Based on evidence-based principles and expert consensus， Expert Consensus on Whole-process Management of Drug Traceability Codes in Medical Institutions of Sichuan Province （hereinafter referred to as the Consensus） was formulated through systematic literature review， field investigations， establishment of a multidisciplinary expert committee and multiple rounds of questionnare consultation via the modified Delphi method， and finalized through consensus meetings. RESULTS & CONCLUSIONS The Consensus clarifies key operating procedures for code verification， code assignment and code return， whole-process operational standards for drug warehouse acceptance and storage， drug warehouse outbound delivery and pharmacy acceptance check， drug distribution and dispensing in pharmacy and intravenous admixture center， medication administration in nursing units and examination departments， as well as drug return process. Key recommendations are proposed such as improving the core functions of the drug traceability system， unifying the hospital-wide traceability code database， strengthening the management of traceability codes for backup medications， establishing a management organization and institutional framework， and optimizing the architectural design and data governance requirements of the drug traceability system. The release of the Consensus will provide scientific， standardized and implementable practical guidelines for medical institutions of Sichuan province， helping to improve closed-loop management of the drug traceability system， strengthen medication safety and fulfil medical insurance fund supervision.

OBJECTIVES: To explore the mediating role of sleep duration in the relationship between depression symptoms and myopia among middle school students. METHODS: This study was a cross-sectional research conducted using a stratified cluster random sampling method. A total of 1 728 middle school students were selected from two junior high schools and two senior high schools in certain urban areas and farms of the Xinjiang Production and Construction Corps. Questionnaire surveys and vision tests were conducted among the students. Spearman analysis was used to analyze the correlation between depression symptoms, sleep duration, and myopia. The Bootstrap method was employed to investigate the mediating effect of sleep duration between depression symptoms and myopia. RESULTS: The prevalence of myopia in the overall population was 74.02% (1 279/1 728), with an average sleep duration of (7.6±1.0) hours. The rate of insufficient sleep was 83.62% (1 445/1 728), and the proportion of students exhibiting depression symptoms was 25.29% (437/1 728). Correlation analysis showed significant negative correlations between visual acuity in both eyes and sleep duration with depressive emotions as measured by the Center for Epidemiologic Studies Depression Scale (with correlation coefficients of -0.064, -0.084, and -0.199 respectively; P<0.01), as well as with somatic symptoms and activities (with correlation coefficients of -0.104, -0.124, and -0.233 respectively; P<0.01) and interpersonal relationships (with correlation coefficients of -0.052, -0.059, and -0.071 respectively; P<0.05). The correlation coefficients for left and right eye visual acuity and sleep duration were 0.206 and 0.211 respectively (P<0.001). Sleep duration exhibited a mediating effect between depression symptoms and myopia (indirect effect=0.056, 95%CI: 0.029-0.088), with the mediating effect value for females (indirect effect=0.066, 95%CI: 0.024-0.119) being higher than that for males (indirect effect=0.042, 95%CI: 0.011-0.081). CONCLUSIONS Sleep duration serves as a partial mediator between depression symptoms and myopia in middle school students.
Humans ; Myopia/etiology* ; Male ; Female ; Depression/physiopathology* ; Cross-Sectional Studies ; Sleep ; Adolescent ; Students ; Child ; Time Factors ; Sleep Duration

Objective To investigate the effects of gut microbiota regulation combined with exercise rehabilitation on non-motor symptoms and neurological function in Parkinson's disease patients.Methods A total of 154 Parkinson's disease patients admitted to our hospital from January 2022 to January 2024 were selected as the subjects of the study.Using a random number table,these 154 patients were evenly divided into a control group and a treatment group,with 77 patients in each group.Both groups received standard treatments,but the control group also underwent exercise rehabilitation therapy,while the treatment group received probiotic supplementation and exercise rehabilitation therapy.The effectiveness of the two groups was then compared.Results Following the 12 weeks,24 weeks therapeutic regimen,The treatment group showed significantly better outcomes(P<0.05).Clinically meaningful reductions were observed in Hoehn-Yahr staging,alongside decreased scores on standardized instruments assessing psychiatric symptoms HAMA,HAMD,SCOPA-AUT,UPDRS Ⅰ-IV and PDSS(P<0.05).Concurrently,the study group exhibited enhanced MMSE(P<0.05).Fecal microbiome analyses revealed a favorable ecological shift characterized by increased colonization of beneficial genera Bifidobacterium and Lactobacillus,with concomitant suppression of pathobionts Enterococcus and Enterobacteriaceae.Gait analysis revealed increased step length,speed,and frequency in the treatment group(P<0.05).Conclusion Patients with Parkinson's disease who received probiotics combined with exercise rehabilitation treatment could effectively improve non-motor symptoms and neurological function,while promoting the balance of intestinal flora,and reduce clinical symptoms.

OBJECTIVE To get the current situation of healthcare associated infection(HAI)and implement targe-ted management through analyzing the trends of HAI incidence rate,the distribution of clinical departments,the sites of HAI and the composition of pathogens in a children's hospital in a five-year period.METHODS Data on HAI cases were collected from all inpatients in Children's Hospital of Soochow University from 2019 to 2023 through the real-time monitoring system of XINGLIN Healthcare acquired Infection Surveillance;Cochran-Armit-age test was used to check for the significant changes of distribution of HAI cases.RESULTS A total of 383,376 hospitalized patients were monitored from 2019 to 2023,of which HAI occurred on 6670 cases and 7209 case-times with an incidence rate of 1.74%and an incidence case rate of 1.88%.The top five departments of HAI inci-dence rates were cardiac,neonatal,surgical and pediatric intensive care unit and department of hematology.HAI mainly occurred in blood and alimentary system,upper and lower respiratory tract.A total of 2668 strains of path-ogenic bacteria were isolated,of which 1346 strains were gram-negative bacteria,1140 strains were gram-positive bacteria and 182 strains were fungi.The top three gram-negative bacteria were Klebsiella pneumoniae,Escherich-ia coli and Pseudomonas aeruginosa;the top three gram-negative pathogens were Streptococcus,Staphylococcus aureus and Staphylococcus epidermidis;and the top three fungi were Candida albicans,Candida parapsilosis and Candida tropicalis.CONCLUSIONS The HAI incidence rate of this hospital steadily declines in the past five years,however the same changes are not observed in the departments with high incidence of HAI.Attention should be paid to the raising bloodstream infections and detection rate of S.epidermidis.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

ObjectiveTo explore the pathological mechanism-syndrome-treatment patterns of approved Chinese patent medicines （CPMs） that treat collateral disorders， providing a reference for the principle of "treating different diseases with the same therapy" in collateral pathology. MethodsCPMs that apply treatment strategies based on collateral disorders were identified from the Pharmacodia database by extracting information from the "efficacy" or "indications" sections of drug package inserts. A database was established to extract the names and compositions of the CPMs， as well as their indications， related traditional Chinese medicine （TCM） symptoms， disease locations （affected areas）， and pathological factors. Frequency statistics were performed. Using the Apriori algorithm， an association rule analysis was conducted on CPMs and disease-location combinations related to the top three most frequent pathological factor combinations. Core formulas for these combinations were identified and analyzed through drug network analysis and MCODE module clustering. ResultsA total of 660 CPMs targeting collateral disorders were retrieved， involving 299 indications， 323 TCM symptoms， 21 disease locations， 19 pathological factors， and 124 pathological factor combinations. The most frequent pathological factor combinations were blood stasis （involved in 109 CPMs， 16.52%）， exogenous wind （外风） -cold-dampness （involved in 43 CPMs， 6.52%）， and qi deficiency-blood stasis （involved in 42 CPMs， 6.36%）. Analysis of the core formulas for these combinations revealed common ingredients such as Honghua （Carthami Flos）， Chuanxiong （Chuanxiong Rhizoma）， Danggui （Angelicae Sinensis Radix）， and Dilong （Pheretima）. ConclusionCollateral disorders involve a wide range of pathogenesis and represent a fundamental mechanism in the onset and development of various diseases， characterized by obstruction and stagnation. The primary therapeutic principle is unblocking of the collaterals. Blood stasis obstructing the collaterals is the core pathological basis， and the strategy of activating blood circulation and resolving stasis to unblock the collaterals should be central to the treatment. The core medication pattern involves combining blood-activating and stasis-resolving herbs with insect-derived medicinals that unblock collaterals. Exogenous wind is often the initiating patholo-gical factor in colla-teral disorders， and the appropriate addition of wind-dispelling herbs can enrich the treatment strategies for such conditions.

Objective:To identify the serotype and genotype characteristics of the first cluster infection of Brucella in Nujiang Lisu Autonomous Prefecture of Yunnan Province. Methods:The information of seven suspected cluster brucellosis cases reported in Lanping County, Nujiang Lisu Autonomous Prefecture in April 2023 were collected, blood samples were collected, and the strains were isolated and cultured. Serological methods were employed for brucellosis diagnosis, bacterial species identification was performed using BCSP31-PCR and AMOS-PCR. Multilocus locus variable-number tandem repeat analysis (MLVA) was conducted for strain genotyping, followed by phylogenetic analysis comparing the strains with those from other regions of China.Results:All seven cases were diagnosed with brucellosis, they were all villagers from the same village and had daily contact with sheeps. Four suspected Brucella strains were isolated, identified as Brucella melitensis biotype by BCSP31-PCR and AMOS-PCR. The four isolated strains exhibited identical MLVA-16 genotype, with MLVA-8 genotype 42 and MLVA-11 genotype 180, belonging to the Eastern Mediterranean lineage. Compared with the MLVA-16 of the isolated strains from other regions of China, the four isolated strains formed an independent cluster. Conclusion:The first cluster infection of Brucella in Nujiang Lisu Autonomous Prefecture of Yunnan Province is caused by Brucella melitensis biotype, and the four isolated strains have showed unique MLVA genotype.