ObjectiveBy exploring the influencing factors of readmission in patients with stable angina of coronary heart disease （CHD） based on real-world clinical data， to establish a risk prediction model of integrated traditional Chinese and western medicine， in order to provide a basis for early identification of high-risk populations and reducing readmission rates. MethodsA prospective clinical study was conducted involving patients with stable angina pectoris of CHD， who were divided into a training set and a validation set at a 7∶3 ratio. General information， traditional Chinese medicine （TCM）-related data， and laboratory test results were uniformly collected. After a one-year follow-up， patients were classified into a readmission group and a non-readmission group based on whether they were readmitted. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for readmission. A risk prediction model of integrated traditional Chinese and western medicine was constructed and visualized using a nomogram. The model was validated and evaluated in terms of discrimination， calibration， and clinical decision curve analysis. ResultsA total of 682 patients were included， with 477 in the training set and 205 in the validation set， among whom 89 patients were readmitted. Multivariate logistic regression analysis identified heart failure history ［OR = 6.93， 95% CI （1.58， 30.45）］， wiry pulse ［OR = 2.58， 95% CI （1.42， 4.72）］， weak pulse ［OR = 3.97， 95% CI （2.06， 7.67）］， teeth-marked tongue ［OR = 4.38， 95% CI （2.32， 8.27）］， blood stasis constitution ［OR = 2.17， 95% CI （1.06， 4.44）］， phlegm-stasis mutual syndrome ［OR = 3.64， 95% CI （1.87， 7.09）］， and elevated non-high-density lipoprotein cholesterol ［OR = 1.30， 95% CI （1.01， 1.69）］ as influencing factors of readmission. These factors were used as predictors to construct a nomogram-based risk prediction model for readmission in patients with stable angina. The model demonstrated moderate predictive capability， with an area under the receiver operating characteristic curve （AUC） of 0.818 ［95% CI （0.781， 0.852）］ in the training set and 0.816 ［95% CI （0.779， 0.850）］ in the validation set. The Hosmer-Lemeshow test showed good calibration （χ² = 4.55， P = 0.80）， and the model's predictive ability was stable. When the threshold probability exceeded 5%， the clinical net benefit of using the model to predict readmission risk was significantly higher than intervening in all patients. ConclusionHistory of heart failure， teeth-marked tongue， weak pulse， wiry pulse， phlegm-stasis mutual syndrome， blood stasis constitution， and non-high-density lipoprotein cholesterol are influencing factors for readmission in patients with stable angina of CHD. A clinical prediction model was developed based on these factors， which showed good discrimination， calibration， and clinical utility， providing a scientific basis for predicting readmission events in patients with stable angina.

Objective To investigate and analyze the occupational stress levels and influencing factors among radiation workers in China, and provide a reference for alleviating occupational stress and promoting mental health. Methods Using the general situation questionnaire, Effort-Reward Imbalance questionnaire, and radiation protection knowledge questionnaire, a convenience sampling method was adopted to investigate the occupational stress of 243 radiation workers in Liaoning, Fujian, Guangdong, and Xinjiang provinces. The independent samples t-test, one-way analysis of variance, chi-square test, and binary logistic regression were used to analyze the influencing factors. Results The average score of Effort-Reward Imbalance was 0.97 ± 0.22, and 100 (41.15%) radiation workers had occupational stress. There were significant differences in the detection rate of occupational stress among radiation workers of different ages, working years in radiation positions, monthly incomes, daily sleep durations, and daily working hours (P < 0.05). Logistic regression analysis identified daily working hours as a factor contributing to occupational stress. Conclusion The occupational stress among radiation workers in China is relatively severe. It is recommended to pay attention to the associated risks and implement targeted intervention measures to reduce the impact of occupational stress.

Background Air pollution exposure has a significant impact on maternal and child health. However, the research on the association between ambient ozone (O₃) exposure during pregnancy and the risk of premature birth in newborns is limited, and the conclusions are inconsistent. Objective To investigate the association of ambient O₃ exposure during pregnancy with the risk of preterm birth in Guangdong Province. Methods Data of pregnant women in Guangzhou from 2013 to 2019 and Foshan from 2018 to 2023 were collected, and O₃ concentrations during different trimesters were assessed according to maternal residential addresses. Bilinear interpolation was used to evaluate the concentrations of air pollution. A cohort study design was adopted in our study. Restricted cubic spline curves were used to evaluate the exposure-response relationship between O₃ exposure and preterm birth risk and explore potential exposure threshold of O₃. Logistic regression models were used to evaluate the association of O₃ exposure with preterm birth. Results A total of 702 924 pregnant women were included in this study, of whom 43 051 (6.12%) were preterm. The average O₃ exposure concentrations of pregnant women during the first, second, third, and whole trimesters were 95.51, 97.51, 100.60, and 97.87 μg·m⁻³, respectively. We observed J-shaped associations between O₃ exposure and preterm birth risk during the second, third, and whole trimesters of pregnancy using restricted cubic spline curves. This study found that there were threshold concentrations between O₃ exposure and preterm birth risk during different gestational periods, and the threshold concentrations in the first, second, third, and whole trimesters were 112.32, 99.83, 111.74, and 112.46 μg·m⁻³, respectively. During the second, third, and whole trimesters of pregnancy, after adjusting for maternal age, baby sex, pre-pregnancy body mass index, mode of delivery, baby birth weight, gestational diabetes, and gestational hypertension, the odds ratios (OR) of preterm birth were 1.02 (95%CI: 1.01, 1.04), 1.02 (95%CI: 1.00, 1.03), and 1.17 (95%CI: 1.13, 1.21) for each 10 μg·m⁻³ increase in O₃ concentration above the O₃ threshold. No significant association was found between O₃ exposure and the risk of preterm birth during the first trimester. Conclusion There is a nonlinear association between the risk of preterm birth and O₃ exposure during pregnancy, and higher concentrations of O₃ exposure during pregnancy are associated with the risk of preterm birth. Above the O₃ threshold concentration during pregnancy, especially during the second, third, and whole trimesters, the risk of preterm birth elevates with the increase of O₃ exposure concentrations.

Objective: To explore intraoral scanning strategies for elastic impressions during the fabrication process of duplicate complete dentures and to investigate the accuracy of 3D scanning strategies on the surface of complete dentures. The goal is to utilize digital technology to improve the traditional fabrication methods of duplicate complete dentures. Methods: Eight sets of replicated denture model for edentulous patients were selected. Conventional complete dentures were created based on these models. The condition of the patient’s alveolar bone atrophy was simulated on these models, and elastic impressions were built using complete dentures as individual trays with polyether silicone rubber materials. TRIOS 3 intraoral scanners were used to scan the elastic impressions according to four scanning strategies (A: tissue surface - artificial teeth - polished surface of denture; B: artificial teeth - polished surface of denture - tissue surface; C: tissue surface - artificial teeth - polished surface of denture in powder spraying state; D: artificial teeth - polished surface - tissue surface in powder spraying state). The 3D data obtained by the desktop scanner were used as the reference. The maximum deviation, average deviation, and standard deviation of the 3D data models obtained by different scanning strategies were compared using the Geomagic Control X software. For the complete denture, the maximum deviation was 0.3 mm. The obtained results were analyzed by PASW Statistics 18 software. Results: The maximum deviation value of the maxillary scans in the 3D data compared with the desktop scanning data was (0.188 ± 0.109) mm, and that of the mandibular scans was (0.200 ± 0.099) mm. There was no statistically significant difference between them (t = 0.139, P = 0.624). However, the maximum deviation values of both the maxillary and mandibular scans were lower than the required maximum error (0.3 mm) for complete dentures in clinical practice, and the difference was statistically significant (P<0.001). The average deviations of the maxillary and mandibular models were (0.024 ± 0.212) mm and (0.014 ± 0.014) mm, respectively, and the differences were statistically significant (t = 4.228, P = 0.021). The standard deviations of the maxillary and mandibular models were (0.074 ± 0.032) mm and (0.074 ± 0.034) mm, respectively. There was no statistically significant difference between them (t = 0.813, P = 0.371). There were no statistically significant differences in the average deviations and standard deviations of each scanning strategy between the maxillary and mandibular impressions within and between groups. Comparing the deviation between the tissue surface and the polished surface of the 3D data of the upper and lower jaws on the oral scanner and the desktop scanner shows that the areas with larger deviations in the maxillary impressions were mainly concentrated in the maxillary tuberosity and palatal vault regions, and those in the mandibular impressions were mainly concentrated in the molar posterior pad region. Conclusion The digital impressions formed by intraoral scanning the maxillary and mandibular elastic impressions can meet the requirements for clinical fabrication of complete dentures. However, in clinical practice, special attention should be paid to checking and adjusting the fit of the maxillary tuberosity and palatal vault and the mandibular molar posterior pad areas of the complete dentures.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Tumorigenesis， invasion， and metastasis occur in the context of a persistent inflammatory microenvironment， and a variety of inflammatory factors can lead to the development of various tumors. Guided by the thought of "preventive treatment of disease" in TCM and the concept of tertiary prevention in modern medicine， it is of great significance to effectively intervene in the inflammatory stage of the disease， interrupt disease progression， prevent the occurrence of malignant tumors， and reverse the process of "inflammation-to-cancer transformation". Sinisan， a commonly used prescription in the Treatise on Febrile Diseases， has been widely applied in the treatment of precancerous lesions of the digestive system， demonstrating considerable advantages. This article reviewed literature from the past 20 years， summarizing the application of Sinisan in precancerous lesions of the digestive system from three aspects： the exploration of its prescription-syndrome relationship， clinical application， and mechanistic study. It is found that basic syndrome indications of Sinisan include harmonizing the Earth element to promote spleen-stomach transportation and transformation， soothing the liver and nourishing the Wood element to restore the smooth flow of Qi， and regulating Yin and Yang to relieve stagnation within the system. In clinical application， Sinisan has shown significant efficacy in atrophic gastritis and precancerous conditions such as intestinal metaplasia， gastric ulcer， ulcerative colitis， esophagitis， and pancreatitis. Mechanistic studies have revealed that Sinisan can inhibit inflammatory factors and improve the inflammatory microenvironment， inhibit cell proliferation and regulate apoptosis， exhibit anti-angiogenic and antitumorigenic effects， modulate immune function， and exert antioxidant effects. These mechanisms can be achieved by regulating pathways such as nuclear factor erythroid 2-related factor 2/heme oxygenase-1 （Nrf2/HO-1）， farnesoid X receptor （FXR）/Nrf2， phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt）， Takeda G protein-coupled receptor 5/cyclic adenosine monophosphate/protein kinase A （TGR5/cAMP/PKA）， interleukin-4/signal transducer and activator of transcription 6 （IL-4/STAT6）， Janus kinase/signal transducer and activator of transcription （JAK/STAT）， RhoA/Rho-associated protein kinase （RhoA/ROCK）， and transforming growth factor-β/Smad proteins （TGF-β/Smads）， confirming Sinisan's role in reversing the inflammation-to-cancer transformation. The current research status of Sinisan in precancerous lesions of the digestive system was thoroughly examined through the above three aspects， along with the identification of limitations and areas for improvement in current research. The aim is to provide a basis and support for future in-depth research on Sinisan， promote the development of new integrated treatment models combining TCM and Western medicine for precancerous lesions， and aid in the research and development of drugs related to precancerous lesions.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.