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.

Objective:To present a set of clinically representative quality assurance (QA) test cases for stereotactic radiosurgery (SRT) plans of multiple intracranial metastases, in order to assess the plan quality and machine execution capabilities.Methods:Based on the clinical characteristics of multiple brain metastases, four groups of test cases with three target volumes (TVs), six TVs, nine TVs, and TVs near organs at risk (OARs) were designed. For these cases, SRT plans were developed, and plan quality was assessed using metrics including the Radiation Therapy Oncology Group conformality index (RTOG CI), gradient index (GI), homogeneity index (HI), and the volume of normal brain tissue receiving a dose of 24 Gy ( V24 Gy), which was defined as the volume enclosed by the 24 Gy isodose line around the Brain-PTV ( V24 Gy of Brain-PTV). Verification plans were generated for each test case, including the verification of point doses, planar doses (PD), and SRS MapCHECK (SMC) semiconductor matrix planar doses. Compared with the calculated result of the treatment planning system (TPS), the criteria for the γ analysis of planar doses were set at 1 mm/2% and 2 mm/2%. Results:For the four groups of test cases, the mean CI, GI, HI, and V24 Gy of Brain-PTV were 1.04±0.03, 3.79±0.40, 0.73±0.01 and (7.46±3.80) cm 3, respectively. The mean deviations of the point doses were 0.88%±0.98%, 1.47%±0.79%, 1.52%± 0.76%, and 1.17% ± 0.38%, respectively. The mean γ passing rates of the single fields for PDs were greater than 98% at 2 mm/2% and exceeding 96% at 1 mm/2%, and the mean γ pass rates of the SMC semiconductor matrix for PDs were 97.75% ± 2.31% and 99.33% ± 0.62%, at 1 mm/2% and 2 mm/2% respectively. Conclusions:The proposed QA test cases for SRT of multiple intracranial metastases allow for the effective assessments of the plan quality and machine execution capabilities and, thus, can assist various centers in clinical applications.

Spectral computed tomography (CT) has triggered a technological revolution in radiodiagnosis while demonstrating its increasing application value in radiotherapy. Employing dual-energy techniques for material decomposition, spectral CT provides optimized solutions for several critical aspects of radiotherapy. Based on a review of the application situation of spectral CT in radiotherapy, this study delved into spectral CT′s significant advantages in image quality improvement, precise dose calculation, and comprehensive quantitative assessment. Furthermore, this study envisioned the development orientations and application prospects of spectral CT.

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.

Objective:To improve the risk management process for clinical trial projects using healthcare failure mode and effect analysis(HFMEA), for references for enhancing the risk identification and preventing capabilities of drug clinical trial institutions.Methods:From June to December 2022, this study focused on the project management process of a clinical trial centre in a tertiary public hospital. Following HFMEA procedures, a research team was established. Core processes prone to failure modes in the drug clinical trial project management and their potential failure modes were identified through group discussions, literature analysis, the Delphi method, and decision tree analysis. High-risk failure modes were screened via risk assessment, corresponding improvement measures were formulated and performed, and their effectiveness was validated.Results:The study identified 6 main processes, 17 sub-processes, and 102 potential failure modes. Delphi analysis confirmed 88 failure modes, with 19 having a failure risk priority number(RPN)≥8.00. Decision tree analysis identified 16 high-risk failure modes, involving 5 main processes and 10 sub-processes. Targeted improvements, such as adopting standardized hospital contract templates and setting deadlines for final payment settlement, etc., were implemented. One year post-implementation(January 2024), the RPN for all 16 high-risk failure modes were<8.00.Conclusions:HFMEA could help hospital clinical trial institutions comprehensively and systematically identify high-risk failure modes in the project management process, develop targeted improvement measures, and improve the level of drug clinical trial project management.

Objective:To evaluate the outcomes of minimally invasive therapy for aortic arch pathology after ascending aortic replacement.Methods:A retrospective analysis was conducted at the Department of Cardiovascular Surgery, West China Hospital of Sichuan University from 2016 to 2024. After multidisciplinary discussion, these included patients were evaluated to be at high risk for traditional open surgery. Various minimally invasive repair techniques were employed, including Ⅳb hybrid technique, physician-modified endograft and novel unibody endograft. The study outcomes were technical success, in-hospital and follow-up mortality, stroke, endoleak, and the patency of the supra-aortic vessels.Results:A total of 40 patients(32 males and 8 females) with a median age of 60 years old were included in this study. The technique success rate was 100%, with no deaths or strokes reported. The patency of the supra-aortic vessels was 100%. 10 patients underwent Type Ⅳb hybrid surgery without any endoleaks occurring. Among the 22 patients who received physician-modified endograft, endoleaks were observed in 2 cases. One of these type Ⅰc endoleaks persisted and underwent reintervention. One patient underwent femoral artery replacement due to vascular injury. For the 8 patients who received novel unibody endograft, one case required reintervention due to persistent type Ⅰc endoleaks.Conclusion:With the development of different endovascular techniques and novel branched endograft, patients with aortic arch pathology who are at high risk for redo open surgery can achieve favorable outcomes with various minimal invasive techniques. However, long-term and large-sample follow-up studies are needed for further evaluation.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

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