ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

Eleven sesquiterpenoids were isolated from the petroleum ether and ethyl acetate extracted fraction of 95% ethanol extract of fresh Centipeda minima by using modern chromatographic separation techniques such as silica gel, MCI, gel, and semi-preparative liquid chromatography. Their structures were identified using spectroscopy and nuclear magnetic resonance(NMR) calculation as minimin A(1), brevilin A(2), minimolide L(3), minimolide A(4), minimolide B(5), arnicolide D(6), microhelenin C(7), 2β-hydroxyl-2,3-dihydrogen-6-O-angeloylplenolin(8), 11α,13-dihydroarnifolin(9),(1S,2R,5R,6S,7S,8S,10R)-6-hydroxy-2-ethoxy-4-oxopseudoguai-11(13)-en-12,8-olide(10), and pulchellin-2-O-isovalerate(11), among which compound 1 was a new compound, and compounds 9-11 were isolated from Centipeda for the first time. The evaluation results of in vitro anti-inflammatory activity showed that compounds 1-11 possessed significant anti-inflammatory activity, with IC_(50) values ranging from(0.13±0.03) to(13.11±0.17) μmol·L~(-1).
Sesquiterpenes/pharmacology* ; Animals ; Asteraceae/chemistry* ; Mice ; Drugs, Chinese Herbal/pharmacology* ; Molecular Structure ; Magnetic Resonance Spectroscopy ; Macrophages/immunology*

In this study, serum metabolomics techniques and molecular biology methods were used to investigate the intervention effect of kaji-ichigoside F1 on chronic unpredictable mild stress(CUMS) depression mouse model and its mechanism. The CUMS depression mouse model was constructed, and the mice were divided into blank group, model group, escitalopram(ESC, 10 mg·kg~(-1)) group, and low-dose, medium-dose, and high-dose kaji-ichigoside F1 groups(1, 2, and 4 mg·kg~(-1)). CUMS modeling was performed on all mice except the blank group, and the cycle was four weeks. At the end of modelling, ESC and kaji-ichigoside F1 were administered by gavage once a day for 28 days. After the end of the administration, behavioral testing(sucrose preference test, open field test, forced swimming test, and tail suspension test) was conducted to evaluate the improvement of depression symptoms of different doses of kaji-ichigoside F1 on CUMS depression mouse model. The morphology of neurons and the number of Nissl bodies in the hippocampus were observed by Nissl staining. Metabolomics technique was used to analyze the changes in serum differential metabolites in mice. Protein expression levels of P2X7 purinergic receptor(P2X7R), adenosine A1 receptor(A1R), and adenosine receptor A2A(A2AR) in mouse hippocampus were detected by Western blot. The results showed that compared with that in the blank group, the body weight of mice in the model group was significantly decreased, and the sucrose preference rate was significantly decreased. The immobility time was significantly increased in the forced swimming and tail suspension tests, and the total moving distance was significantly decreased in the open field test. The number of Nissl bodies was significantly decreased, and the depression-like behavior and the number of Nissl bodies in the hippocampus of mice were significantly improved after administration of kaji-ichigoside F1. In the metabonomics analysis, the purine metabolism of serum after kaji-ichigoside F1 administration was involved in the metabolic passage of depression, and Western blot analysis verified the expression of P2X7R, A1R, and A2AR proteins in purine metabolic pathways. The results show that kaji-ichigoside F1 significantly decreases the expression of P2X7R and A2AR proteins in the hippocampus of CUMS model mice and increases the expression level of A1R proteins. It is suggested that kaji-ichigoside F1 may play an antidepressant role by regulating the expression of P2X7R, A1R, and A2AR proteins in the purine metabolism pathway.
Animals ; Mice ; Antidepressive Agents/administration & dosage* ; Metabolomics ; Depression/genetics* ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Disease Models, Animal ; Hippocampus/metabolism* ; Behavior, Animal/drug effects* ; Humans

OBJECTIVE: To analyze the distribution characteristics of glucose-6-phosphate-dehydrogenase (G6PD) mutations and their enzyme activity in newborns patients with G6PD deficiency in Guilin region. METHODS: From July 2022 to July 2024, umbilical cord blood samples from 4 554 newborns in Guilin were analyzed for G6PD mutations using fluorescence PCR melting curve analysis. Enzyme activity was detected in 4 467 cases using the rate assay. RESULTS: Among 4 467 newborns who underwent G6PD activity testing, 162 newborns (3.63%) were identified as G6PD-deficient, including 142 males (6.04%) and 20 females (0.94%), the prevalence of G6PD deficiency was significantly higher in males than in females (P < 0.001). Genetic analysis of 4 554 newborns detected G6PD mutations in 410 cases (9%), including 171 males (7.13%) and 239 females (11.09%), with a significantly higher mutation detection rate in females than in males (P < 0.001). A total of nine single mutations and four compound heterozygous mutations were identified. The most common mutations were c.1388G>A (33.66%), c.1376G>T (23.66%) and c.95A>G (16.34%). Among newborns who underwent both enzyme activity and genetic mutation testing, males with G6PD mutations had significantly lower enzyme activity than that of females with G6PD mutations(P < 0.001). Specifically, among newborns carrying the mutations c.1388G>A, c.1376G>T, c.95A>G, c.1024C>T or c.871G>A, males consistently exhibited lower enzymatic activity than females with the same mutations (P < 0.001). Furthermore, in male G6PD-deficient newborns, the enzyme activity levels in those carrying c.1388G>A, c.1376G>T, c.95A>G, c.1024C>T, or c.871G>A were lower than those in both the control group and the c.519C>T group (P < 0.05). CONCLUSION This study provides a comprehensive profile of G6PD deficiency incidence and mutation spectrum in the Guilin region. By analyzing enzyme activity and genetic mutation results, this study provides insights into potential intervention strategies and personalized management approaches for the prevention and treatment of neonatal G6PD deficiency in the region.
Humans ; Infant, Newborn ; Glucosephosphate Dehydrogenase Deficiency/epidemiology* ; Glucosephosphate Dehydrogenase/genetics* ; Female ; Male ; Mutation ; China/epidemiology*

Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

Objective:Based on HyperArc stereotactic radiotherapy(SRT)technique,six-dimensional free bed combined with double mask fixation was used to treat intracranial tumors,and the positioning errors of within batch and between batches were analyzed,so as to provide basis for the accuracy of clinical treatment of this technique.Methods:A total of 13 patients with intracranial tumors who admitted to Peking Union Medical College Hospital from March to July 2023 were retrospectively selected,and they were treated by using HyperArc SRT technique.The validation images of cone-beam computed tomography(CBCT)of within batch and between batches during treatment were analyzed.The positioning errors of three translational direction[left and right(x),head and foot(y)and abdominal and dorsal(z)]and rotational direction were analyzed.The each positioning error was set as group A,and the remaining error after the positioning error was corrected through six-dimensional free bed was set as group B,and the error post treatment was set as group C.The difference between group B and group C was defined as the change of within batch.According to the margin formula,the positioning error of within batch was used to calculate the required range of margin.Results:Under the mode of six-dimensional free bed correction combined with double mask fixation,a total of 59 times of HyperArc SRT on head were performed.In the comparison of the average errors on the six-dimensional direction among groups A,B and C,the errors of group A on x direction and y direction were respectively(0.119±0.039)and(-0.133±0.047)cm,and the differences of them between group A and group B[(0.004±0.002)and(0.018±0.005)cm]were significant(t=2.890,-3.224,P<0.05).There were no significant differences on other directions between the two groups(P>0.05).The error of RX direction of group B was(0.033±0.021)°,and the difference of that between group B and group C[(0.122±0.045)°]was significant(t=-2.306,P<0.05),while there were no significant differences on other directions(P>0.05).In the margin of the design of the plan of intracranial tumors,the x,y and z directions were respectively 0.6,0.9 and 0.4 mm.Conclusion:In the radiotherapy of using HyperArc SRT technique for intracranial tumors,the use of six-dimensional free bed combined with double mask treatment can significantly shorten the margin,and ensure accurate irradiation for gross tumor volume(GTV)and simultaneously reduce the irradiation volume and dose of surrounding normal tissue.

Paraplegia caused by spinal cord injury is a serious neurological complication, for which surgery is currently the main treatment method. Due to different surgical approaches, patients are usually expected to maintain a passive prone position for a long time or switch between the supine and prone positions. Affected by multiple factors such as neurogenic sensory disorders, pathological changes in muscle tone and operative duration, the risk of intraoperative acquired pressure injury (IAPI) is significantly increased. Current clinical prevention strategies for IAPI in these patients predominantly focus on localized pressure relief during positioning, lacking systematic, standardized comprehensive prevention protocols or evidence-based guidelines. To address it, Department of Nursing, Orthopedics Branch, China International Exchange and Promotive Association for Medical and Health Care, Spinal Trauma Professional Committee, Orthopedics Branch, Chinese Medical Doctor Association, Nursing Group of Spine and Spinal Cord Professional Committee of Chinese Association of Rehabilitation Medicine organized experts in relevant fields to formulate Guideline for the prevention of intraoperative acquired pressure injury in paraplegic patients with spinal cord injury ( version 2025), based on evidence-based medical evidence and latest research results and clinical practice at home and abroad. Eleven recommendations were put forward from the aspects of preoperative risk assessment, intraoperative prevention strategies, postoperative handover and monitoring, and supportive mechanisms for IAPI prevention, aiming to standardize the prevention measures and management strategies of IAPI in paraplegic patients with spinal cord injury and accelerate the recovery of patients and improve the therapeutic effect.

Objective To analyze the lung function condition and the prevalence of pulmonary ventilation disorders in the occupational population of Wuhan, and to explore their influencing factors. Methods Physical examination data from the Wuhan Prevention and Treatment Center for Occupational Diseases were used in this study, and finally 9499 people were selected as the study subjects. The linear regression model and logistic regression model were used to analyze the influencing factors of pulmonary ventilation function and pulmonary dysfunction. The restricted cubic spline was used to explore the nonlinear relationship. Results The prevalence of pulmonary ventilation disorders was 1.7%, and the lung function indexes FVC, FEV1, and FEV1/FVC were significantly lower in the population aged >27 years than in the population aged <27 years (P<0.001). The lung function indexes FVC and FEV1 were significantly lower in females than in males (P<0.001). The lung function indexes FVC and FEV1 were significantly lower in underweight occupational groups than in normal-weight groups (P<0.001), and FVC and FEV1 were significantly lower in dust-exposed occupational groups than in groups without dust exposure(P<0.05). Restricted cubic spline plots showed a nonlinear relationship between age and lung function indexes FVC and FEV1 (P_nonlinear< 0.05). Age and BMI were the risk factors for pulmonary ventilation disorders. Conclusion Age, gender, BMI, and dust exposure are risk factors for decreased FVC and FEV1. Age is the risk factor for decreased FEV1/FVC. Age and BMI are the risk factors for pulmonary ventilation disorders.

Objective To identify potential drug target genes associated with idiopathic pulmonary fibrosis(IPF)and predict therapeutic candidates using a two-sample Mendelian randomization(MR)approach across the druggable genome.Methods Druggable genome data from the DGIdb database and Finan were integrated to identify overlapping genes.A two-sample MR analysis was performed to infer causal relationships between genes and IPF.Functional enrichment analyses,including Gene Ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG),were conducted to explore biological pathways.Drug-target interactions were predicted via DSigDB database screening,followed by molecular docking simulations to evaluate binding affinities.Results Among the 2588 overlapping druggable genes,thirty exhibited significant causal associations with IPF(P＜0.05).Four hub genes(NOD2,LATS2,LTA,and TCF7L2)were enriched in IPF-related pathways,notably Hippo and TNF signaling.Six potential therapeutics were identified:oxyphenbutazone,moexipril,α-galactosylceramide,GSK429286A,CGP74514A,and JW-7-24-1.Molecular docking confirmed strong binding affinities between these drugs and their targets.Conclusion This study has identified thirty druggable gene targets and six candidate drugs for IPF.The enrichment of hub genes in key pathways and validated drug-target interactions provide insights into IPF therapies.