Childhood simple obesity has become a significant public health issue in China. Modern medicine primarily relies on lifestyle interventions and often suffers from poor long-term compliance， while pharmacological options are limited and associated with potential adverse effects. Traditional Chinese Medicine （TCM） has a long history in the prevention and management of this condition， demonstrating eight distinct advantages， including systematic theoretical foundation， diversified therapeutic approaches， definite therapeutic efficacy， high safety profile， good patient compliance， comprehensive intervention strategies， emphasis on prevention， and stepwise treatment protocols. Additionally， TCM is characterized by six distinctive features： the use of natural medicinal substances， non-invasive external therapies， integration of medicinal dietetics， simple exercise regimens， precise syndrome differentiation， and diverse dosage forms. By combining internal and external treatments， TCM facilitates individualized regimen adjustment and holistic regulation， demonstrating remarkable effects in improving obesity-related metabolic indicators， regulating constitutional imbalance， and promoting healthy behaviors. However， challenges remain， such as inconsistent operational standards， insufficient high-quality clinical evidence， and a gap between basic research and clinical application. Future efforts should focus on accelerating the standardization of TCM diagnosis and treatment， conducting multicenter randomized controlled trials， and fostering interdisciplinary integration， so as to enhance the scientific validity and international recognition of TCM in the prevention and treatment of childhood obesity.

In this work,four salicylhydrazone compounds(L1?L4)were designed and synthesized by using vanillin derivatives as raw material.The structures were confirmed by nuclear magnetic resonance(NMR)and high-resolution mass spectrometry(HRMS).The optical experiments showed that probe L1 and probe L3 could be used as aluminium ion(Al3+)fluorescence probes.The fluorescence color of probe L1 solution changed from colorless to blue after adding Al3+,and the limit of detection was 25.1 nmol/L.Compared with probe L1,the fluorescence color of probe L3 solution changed from colorless to green after complexing with Al3+,and the limit of detection was 17.3 nmol/L.Probe L1 and probe L3 showed the advantages of fast response speed,high selectivity and good anti-interference.The mechanism of Al3+recognition was further demonstrated by HRMS and 1H NMR.Cell imaging experiments showed that probe L1 and L3 had low cytotoxicity and had great application potential in detection of Al3+in vivo.

Objective To construct a competency evaluation model for forensic practitioners,providing a reference for their training and assessment.Methods Based on the iceberg and onion models of com-petency,and with reference to Spencer's Competency Dictionary,literature research was conducted and focus group interviews were employed to preliminarily construct core indices and measurement items for evaluating the competency of forensic practitioners.The Delphi method was applied for two rounds of expert consultation to further refine the competency evaluation index system.The analytic hierarchy process(AHP)was used to calculate the weights of the indices.Results A competency evaluation model for forensic practitioners was constructed,consisting of 7 core indices,encompassing forensic skills,identification service capabilities,and the ability to apply relevant legal knowledge and 49 mea-surement items.The weights of the core indices and measurement items were determined.Conclusion The constructed competency evaluation model for forensic practitioners is scientifically sound and inno-vative,and has unique characteristics of forensic medicine compared with other medical models.

Objective To investigate the expression levels of serum miR-186-5p and miR-942-5p in patients with glioma and their clinical significance.Methods A total of 98 patients with glioma who were treated in this hospital from October 2019 to December 2021 were selected as the monitored group,and 101 healthy indi-viduals who underwent physical examinations a the same time were selected as the control group.Quantitative fluorescent PCR(qPCR)method was applied to detect the expression levels of miR-186-5p and miR-942-5p in serum,and multivariate COX regression was applied to analyze the prognostic factors of glioma patients.Re-ceiver operating characteristic(ROC)curve and area under curve(AUC)were used to analyze the diagnostic value of serum miR-186-5p and miR-942-5p in glioma.Kaplan-Meier survival curve was used to analyze the re-lationship between serum miR-186-5p and miR-942-5p expression and prognosis of patients.Results The ex-pression level of serum miR-186-5p in monitored group was lower than that in the control group(P＜0.05),and the expression level of miR-942-5p was higher than that in the control group(P＜0.05).The AUC of ser-um miR-186-5p and miR-942-5p in the diagnosis of glioma alone and in combination were 0.735,0.809 and 0.895,respectively.There were significant differences in the proportion of low miR-186-5p expression and high miR-942-5p expression in serum of patients with different preoperative Karnofsky performance status(KPS)scores,World Health Organization(WHO)grades and local infiltration(P＜0.05).The 2-year surviv-al rate of patients with high expression of miR-186-5p was higher than that of patients with low expression of miR-186-5p(x2=6.455,P=0.011).The 2-year survival rate of patients with high miR-942-5p expression was lower than that of patients with low miR-942-5p expression(x2=9.858,P=0.002).miR-186-5p was a protective factor for mortality in glioma patients(P＜0.05),while miR-942-5p was a risk factor(P＜0.05).Conclusion Serum miR-186-5p expression level decreases and miR-942-5p expression level increases in glioma patients,both of which have certain diagnostic value for the occurrence of glioma.

[Objective] To explore the clinical significance and application value of establishing a database for red blood cell alloantibody detection. [Methods] Patients who were scheduled for blood transfusion in our hospital from January 1, 2020 to May 1, 2024 were selected as the research subjects. A red blood cell alloantibody detection database was established using Microsoft Office Excel software to register the detection data of patients' alloantibodies and antibodies of undetermined specificity (AUS). A retrospective analysis was conducted on the clinical characteristics, antibody distribution, antibody decay and repeat positivity of the patients in the database. The LISS-IAT method was routinely used for antibody screening and identification. [Results] Among the alloantibodies, the Rh blood group system had the highest detection rate, followed by antibodies of the MNS blood group system and the Lewis blood group system. The predominant antibody in the Rh blood group system was anti-E. In the univariate analysis, the positivity of antibody was significantly associated with the patient's gender, age, blood transfusion history, pregnancy history and type of disease (all P<0.001). In the database, 48 patients experienced antibody decay, accounting for 15.24%(48/315), with an average time span of antibody decay ranging from 22 to 1 324 days. Six cases showed repeat positivity after decay, which were related to blood transfusions. The shortest interval between blood transfusions that led to antibody repeat positivity was 3 days, and the longest interval was 427 days. Among 58 cases with AUS, 3 converted into alloantibodies, among which 2 were anti-E and 1 was anti-Lea. [Conclusion] Establishing a red blood cell alloantibody detection database is an effective way to guide ambiguous cross-matching in clinical practice and is also an effective measure for the management of transfusion risks.

The traditional Chinese medicine(TCM) industry is a crucial part of China's pharmaceutical sector and plays a strategic role in ensuring public health and promoting economic and social development. In response to the practical demand for high-quality development of the TCM industry, this paper focused on the bottlenecks encountered during the digital and intelligent transformation of TCM production systems. Specifically, it explored technical strategies and methodologies for constructing the best TCM production mode. An innovative artificial intelligence(AI)-centered technical architecture for TCM production was proposed, focusing on key aspects of production management including process modeling, state evaluation, and decision optimization. Furthermore, a series of critical technologies were developed to realize the best TCM production mode. Finally, a novel AI-driven TCM production mode characterized by a closed-loop system of "measurement-modeling-decision-execution" was presented through engineering case studies. This study is expected to provide a technological pathway for developing new quality productive forces within the TCM industry.
Artificial Intelligence ; Drugs, Chinese Herbal ; Medicine, Chinese Traditional/methods* ; Humans

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*

In recent years, there have been frequent adverse reactions/events associated with traditional Chinese medicine(TCM), especially liver injury related to traditional non-toxic TCM, which requires adequate attention. Liver injury related to traditional non-toxic TCM is characterized by its sporadic and insidious nature and is influenced by various factors, making its detection and identification challenging. There is an urgent need to develop a strategy and method for early detection and recognition of traditional non-toxic TCM-related liver injury. This study was based on national adverse drug reaction monitoring center big data, integrating methodologies such as reporting odds ratio(ROR), network toxicology, and computational chemistry, so as to systematically research the risk signal identification and evaluation methods for TCM-related liver injury. The optimized ROR method was used to discover potential TCM with a risk of liver injury, and network toxicology and computational chemistry were used to identify potentially high-risk TCM. Additionally, typical clinical cases were analyzed for confirmation. An integrated strategy of "discovery via big data, identification via dry/wet method, confirmation via typical cases, and precise risk prevention and control" was developed to identify the risk of TCM-related liver injury. Corydalis Rhizoma was identified as a TCM with high risk, and its toxicity-related substances and potential toxicity mechanisms were analyzed. The results revealed that liver injury is associated with components such as tetrahydropalmatine and tetrahydroberberine, with potential mechanisms related to immune-inflammatory pathways such as the tumor necrosis factor signaling pathway, interleukin-17 signaling pathway, and Th17 cell differentiation. This paper innovatively integrated real-world evidence and computational toxicology methods, offering insights and technical support for establishing a risk discovery and identification strategy for TCM-related liver injury based on real-world big data, providing innovative ideas and strategies for guiding the safe and rational use of medication in clinical practices.
Corydalis/adverse effects* ; Drugs, Chinese Herbal/adverse effects* ; Humans ; Chemical and Drug Induced Liver Injury/etiology* ; Medicine, Chinese Traditional/adverse effects* ; Rhizome/adverse effects* ; Male ; Female

Direct compression is an ideal method for tablet preparation, but it requires the powder's high functional properties. The functional properties of the powder during compression directly affect the quality of the tablet. 15 parameters such as Py, FES-8KN, FES-12KN, FES-16KN, CR-8KN, CR-12KN, and CR-16KN were used as the characteristic variables in this paper. Unsupervised learning methods like principal component analysis, cluster analysis, and factor analysis were applied to analyze and classify the compression behavior data of 36 traditional Chinese medicine powders. The results showed that both different dimensionality reduction classification methods could effectively differentiate the compression behavior characteristics of 36 traditional Chinese medicine compound powders. The hierarchical cluster analysis results showed a better agreement with the actual compression phenomena of the powders, where group 1 was high elasticity and low compressibility, group 2 was easily compressed and hard to break, group 3 was excellent compressibility and compactibility. This study is expected to provide references and ideas for predicting the behavior of traditional Chinese medicine powders and the screening of tablet formulations.

As global greenhouse gases continue rising, the urgency of more ambitious action is clearer than ever before. China is the world's biggest emitter of greenhouse gases and one of the countries affected most by climate change. The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts. This article aimed to review the evidence of environmental damages and health risks posed by climate change and to provide a new science-based perspective for the delivery of sustainable development goals. Over recent decades, China has experienced a strong warming pattern with a growing frequency of extreme weather events, and the impacts of climate change on China's environment and human health have been consistently observed, with increasing O ₃ air pollution, decreases in water resources and availability, land degradation, and increased risks for both communicable and non-communicable diseases. Therefore, China's climate policy should target the key factors driving climate change and scale up strategic measures to curb carbon emissions and adapt to inevitable increasing climate impacts. It provides new insights for not only China but also other countries, particularly developing and emerging economies, to ensure climate and environmental sustainability whilst pursuing economic growth.
Climate Change ; China ; Humans ; Greenhouse Gases ; Air Pollution ; Sustainable Development ; Environment