The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

Progressive pulmonary fibrosis (PPF) is a progressive and lethal condition with few effective treatment options. Improvements in quality of life for patients with PPF remain limited even while receiving treatment with approved antifibrotic drugs. Traditional Chinese medicine (TCM) has the potential to improve cough, dyspnea and fatigue symptoms of patients with PPF. TCM treatments are typically diverse and individualized, requiring urgent development of efficient and precise design strategies to identify effective treatment options. We designed an innovative Bayesian adaptive two-stage trial, hoping to provide new ideas for the rapid evaluation of the effectiveness of TCM in PPF. An open-label, two-stage, adaptive Bayesian randomized controlled trial will be conducted in China. Based on Bayesian methods, the trial will employ response-adaptive randomization to allocate patients to study groups based on data collected over the course of the trial. The adaptive Bayesian trial design will employ a Bayesian hierarchical model with "stopping" and "continuation" criteria once a predetermined posterior probability of superiority or futility and a decision threshold are reached. The trial can be implemented more efficiently by sharing the master protocol and organizational management mechanisms of the sub-trial we have implemented. The primary patient-reported outcome is a change in the Leicester Cough Questionnaire score, reflecting an improvement in cough-specific quality of life. The adaptive Bayesian trial design may be a promising method to facilitate the rapid clinical evaluation of TCM effectiveness for PPF, and will provide an example for how to evaluate TCM effectiveness in rare and refractory diseases. However, due to the complexity of the trial implementation, sufficient simulation analysis by professional statistical analysts is required to construct a Bayesian response-adaptive randomization procedure for timely response. Moreover, detailed standard operating procedures need to be developed to ensure the feasibility of the trial implementation. Please cite this article as: Zhang C, Nie YS, Zhang CT, Yang HJ, Zhang HR, Xiao W, Cui GF, Li J, Li SJ, Huang QS, Yan SY. An adaptive Bayesian randomized controlled trial of traditional Chinese medicine in progressive pulmonary fibrosis: Rationale and study design. J Integr Med. 2025; 23(2): 138-145.
Female ; Humans ; Male ; Bayes Theorem ; Disease Progression ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional/methods* ; Pulmonary Fibrosis/therapy* ; Quality of Life ; Randomized Controlled Trials as Topic ; Research Design ; Adaptive Clinical Trials as Topic

PURPOSE: To investigate the protective effect of sub-hypothermic mechanical perfusion combined with membrane lung oxygenation on ischemic hypoxic injury of yorkshire brain tissue caused by traumatic blood loss. METHODS: This article performed a random controlled trial. Brain tissue of 7 yorkshire was selected and divided into the sub-low temperature anterograde machine perfusion group (n = 4) and the blank control group (n = 3) using the random number table method. A yorkshire model of brain tissue injury induced by traumatic blood loss was established. Firstly, the perfusion temperature and blood oxygen saturation were monitored in real-time during the perfusion process. The number of red blood cells, hemoglobin content, NA⁺, K⁺, and Ca²⁺ ions concentrations and pH of the perfusate were detected. Following perfusion, we specifically examined the parietal lobe to assess its water content. The prefrontal cortex and hippocampus were then dissected for histological evaluation, allowing us to investigate potential regional differences in tissue injury. The blank control group was sampled directly before perfusion. All statistical analyses and graphs were performed using GraphPad Prism 8.0 Student t-test. All tests were two-sided, and p value of less than 0.05 was considered to indicate statistical significance. RESULTS: The contents of red blood cells and hemoglobin during perfusion were maintained at normal levels but more red blood cells were destroyed 3 h after the perfusion. The blood oxygen saturation of the perfusion group was maintained at 95% - 98%. NA⁺ and K⁺ concentrations were normal most of the time during perfusion but increased significantly at about 4 h. The Ca²⁺ concentration remained within the normal range at each period. Glucose levels were slightly higher than the baseline level. The pH of the perfusion solution was slightly lower at the beginning of perfusion, and then gradually increased to the normal level. The water content of brain tissue in the sub-low and docile perfusion group was 78.95% ± 0.39%, which was significantly higher than that in the control group (75.27% ± 0.55%, t = 10.49, p < 0.001), and the difference was statistically significant. Compared with the blank control group, the structure and morphology of pyramidal neurons in the prefrontal cortex and CA1 region of the hippocampal gyrus were similar, and their integrity was better. The structural integrity of granulosa neurons was destroyed and cell edema increased in the perfusion group compared with the blank control group. Immunofluorescence staining for glail fibrillary acidic protein and Iba1, markers of glial cells, revealed well-preserved cell structures in the perfusion group. While there were indications of abnormal cellular activity, the analysis showed no significant difference in axon thickness or integrity compared to the 1-h blank control group. CONCLUSIONS Mild hypothermic machine perfusion can improve ischemia and hypoxia injury of yorkshire brain tissue caused by traumatic blood loss and delay the necrosis and apoptosis of yorkshire brain tissue by continuous oxygen supply, maintaining ion homeostasis and reducing tissue metabolism level.
Animals ; Perfusion/methods* ; Disease Models, Animal ; Brain Injuries/etiology* ; Swine ; Male ; Hypothermia, Induced/methods*

Objective:To investigate the association between estimated cumulative low-density lipoprotein cholesterol (LDL-C) exposure and the severity of coronary artery disease and long-term adverse cardiovascular and cerebrovascular events (MACCE) in patients with acute coronary syndrome (ACS).Methods:The subjects were from the PROMISE study. This study was a prospective cohort study led by Fuwai Hospital, Chinese Academy of Medical Sciences, with participation from eight regional tertiary hospitals as sub-centers, and enrolled 18 701 patients with confirmed coronary heart disease between January 2015 and May 2019. Among them, 8 429 patients with ACS were included in this study. The estimated cumulative LDL-C exposure was calculated by multiplying LDL-C by age. Participants were then divided into four groups based on quartiles. Baseline data and coronary angiography data were collected, and participants were followed for 2 years. The primary endpoint was MACCE, which was composed of all-cause death, cardiac death, myocardial infarction, revascularization, and stroke. Spearman correlation analysis was used to estimate the correlation between cumulative LDL-C exposure and the severity of coronary artery disease. The differences in MACCE among the four groups were compared, and multivariate Cox regression was used to divide the estimated cumulative exposure LDL-C into two groups, three groups, and four groups to analyze its relationship with MACCE.Results:The 8 429 ACS patients included in the study had an age of (60.9±11.4) years, with 1 951(23.1%) females. Spearman correlation analysis revealed that estimated cumulative LDL-C exposure was positively associated with the preoperative SYNTAX score, three-vessel lesions disease, left main disease, and the number of target lesions (correlation coefficients r=0.14, 0.10, 0.04 and 0.03, respectively, with all P<0.05). The 2-year follow-up results indicated that the incidence rates of MACCE, all-cause death, cardiac death, myocardial infarction, and stroke in ACS patients grouped by different levels of estimated cumulative LDL-C exposure were statistically significant (all P<0.05). The results of the Cox multivariate regression analysis showed that when the estimated cumulative LDL-C exposure was treated as a continuous variable and analyzed in two, three, and four groups, with the lowest group as the reference, the risk of MACCE occurrence in the high-value group increased by 21% (95% CI 1.08-1.37, P=0.002), 24% (95% CI 1.07-1.43, P=0.004), and 21% (95% CI 1.02-1.43, P=0.025) respectively. Conclusions:A positive correlation was found between estimated cumulative LDL-C exposure and severity of coronary artery disease. High estimated cumulative LDL-C exposure level is a risk factor for MACCE in ACS patients within 2 years.

Objective:To investigate the clinical significance of constructing a nomogram based on a combined model of clinical-pathological-imaging data for predicting postoperative recurrence/metastasis of breast cancer.Meth-ods:A retrospective study was conducted on 194 breast cancer patients who were admitted to the department of breast and thyroid surgery from June 2019 to June 2022.unvariate and multivariate Logistic regression analyses were used to screen independent predictors of postoperative recurrence/metastasis of breast cancer,and a model was con-structed based on the independent predictors.Another 83 breast cancer patients from July 2022 to February 2023 were taken as the validation set to verify the model with the ratio of 7∶3(training set∶validation set).Results:The postopera-tive recurrence/metastasis rate of breast cancer was 29.90％.Ki-67 expression level ≥20％,tumor location in the inner upper quadrant and outer upper quadrant,lesion size ≥20 mm,multiple lesions,and BI-RADS grade of 5 were indepen-dent risk factors for postoperative recurrence/metastasis of breast cancer(P＜0.05).PR positive expression was an inde-pendent protective factor for postoperative recurrence/metastasis of breast cancer(P＜0.05).The diagnostic performance of the combined clinical-pathological-imaging model(AUC:0.900)was superior to that of the clinical-pathological pa-rameters(AUC:0.655)and the MRI parameter model(AUC:0.857).In its nomogram model constructed based on a com-bined clinical-pathological-imaging model to predict breast cancer recurrence/metastasis after surgery,the AUC in the training set was 0.900(95％CI:0.859～0.942)with good discrimination,the maximum Yoden value was 0.710,the sensi-tivity was 0.931,and the specificity was 0.779,and the AUC in the validation set was 0.820(95％C/:0.712～0.928),well differentiated,with a maximum Yoden value of 0.554,a sensitivity of 0.630,and a specificity of 0.914.The theoretical and actual values of the calibration curves of the two sets were in good agreement,and the decision curve indicated the net benefit of the breast cancer recurrence-metastasis prediction model after surgery,which showed good predictive ability.Conclusion:The nomogram constructed based on the combined model of clinical-pathological-imaging data has good predictive ability,accuracy,and clinical applicability,which is helpful for clinicians to evaluate the risk of postoperative re-currence/metastasis of breast cancer.

Objective:To investigate the clinical significance of constructing a nomogram based on a combined model of clinical-pathological-imaging data for predicting postoperative recurrence/metastasis of breast cancer.Meth-ods:A retrospective study was conducted on 194 breast cancer patients who were admitted to the department of breast and thyroid surgery from June 2019 to June 2022.unvariate and multivariate Logistic regression analyses were used to screen independent predictors of postoperative recurrence/metastasis of breast cancer,and a model was con-structed based on the independent predictors.Another 83 breast cancer patients from July 2022 to February 2023 were taken as the validation set to verify the model with the ratio of 7∶3(training set∶validation set).Results:The postopera-tive recurrence/metastasis rate of breast cancer was 29.90％.Ki-67 expression level ≥20％,tumor location in the inner upper quadrant and outer upper quadrant,lesion size ≥20 mm,multiple lesions,and BI-RADS grade of 5 were indepen-dent risk factors for postoperative recurrence/metastasis of breast cancer(P＜0.05).PR positive expression was an inde-pendent protective factor for postoperative recurrence/metastasis of breast cancer(P＜0.05).The diagnostic performance of the combined clinical-pathological-imaging model(AUC:0.900)was superior to that of the clinical-pathological pa-rameters(AUC:0.655)and the MRI parameter model(AUC:0.857).In its nomogram model constructed based on a com-bined clinical-pathological-imaging model to predict breast cancer recurrence/metastasis after surgery,the AUC in the training set was 0.900(95％CI:0.859～0.942)with good discrimination,the maximum Yoden value was 0.710,the sensi-tivity was 0.931,and the specificity was 0.779,and the AUC in the validation set was 0.820(95％C/:0.712～0.928),well differentiated,with a maximum Yoden value of 0.554,a sensitivity of 0.630,and a specificity of 0.914.The theoretical and actual values of the calibration curves of the two sets were in good agreement,and the decision curve indicated the net benefit of the breast cancer recurrence-metastasis prediction model after surgery,which showed good predictive ability.Conclusion:The nomogram constructed based on the combined model of clinical-pathological-imaging data has good predictive ability,accuracy,and clinical applicability,which is helpful for clinicians to evaluate the risk of postoperative re-currence/metastasis of breast cancer.

Freeze-drying technique,also known as lyophilization,is a process of removing moisture from a solution or suspension through freezing and vacuum dehydration to maintain the stability of the samples and prolong their shelf life.Freeze-drying technology has been widely used in food,pharmaceutical,clinical testing,chemical and other fields but its application in the field of forensic medicine has just started.Polymerase chain reaction(PCR)and its derivative detection technologies are widely used in forensic DNA detection,but PCR reagents need to be stored and transported at low temperature.In recent years,forensic scientists have begun applying freeze-drying technology to PCR amplification reagents to solve the transportation and storage problems of PCR reagents.In order to promote the application of PCR freeze-drying technology in forensic genetics,this paper mainly expounds the research course,system and process of PCR freeze-drying technology,compares the advantages and disadvantages of PCR reagents with traditional PCR reagents,and introduces the advantages and challenges of PCR freeze-drying reagents in forensic medicine.

Objective To explore the correlation between serum hypoxia-inducible factor-1α(HIF-1α)levels and cerebral microbleeds(CMBs)and cognitive impairment and to assess the predictive value of HIF-1α for CSVD-related cognitive impairment.Methods A total of 104 patients with CSVD who attended the Department of Neurology,First Affiliated Hospital of Xinxiang Medical University from June 2022 to November 2023 were enrolled.All enrolled patients were subjected to basic statistics,cranial nuclear magnetic resonance examination,cognitive function assessment,and serum HIF-1α test,and the number and location of CMBs were counted.Based on the above data the enrolled patients were grouped.The correlation between HIF-1α and cognitive function and CMBs was studied the influencing factors of CMBs and cognitive impairment were analyzed,and the predictive value of HIF-1α on the occurrence of cognitive impairment was evaluated.Results There were statistically significant differences in HIF-1α levels and cognitive function among different CMBs groups.Serum HIF-1α levels were significantly negatively correlated with overall cognitive function,visuospatial and executive function,attention,and delayed recall,and serum HIF-1α was positively correlated with the number of CMBs.HIF-1α may be a risk factor for CMBs and cognitive impairment associated with CSVD,and serum HIF-1α has potential in predict the cognitive impairment caused by CSVD.Conclusion Serum levels of HIF-1α were associated with the number of CMB and CSVD-related cognitive impairment,and serum levels of HIF-1α may have a predictive value for CSVD-related cognitive impairment.

Objective To explore the correlation between serum hypoxia-inducible factor-1α(HIF-1α)levels and cerebral microbleeds(CMBs)and cognitive impairment and to assess the predictive value of HIF-1α for CSVD-related cognitive impairment.Methods A total of 104 patients with CSVD who attended the Department of Neurology,First Affiliated Hospital of Xinxiang Medical University from June 2022 to November 2023 were enrolled.All enrolled patients were subjected to basic statistics,cranial nuclear magnetic resonance examination,cognitive function assessment,and serum HIF-1α test,and the number and location of CMBs were counted.Based on the above data the enrolled patients were grouped.The correlation between HIF-1α and cognitive function and CMBs was studied the influencing factors of CMBs and cognitive impairment were analyzed,and the predictive value of HIF-1α on the occurrence of cognitive impairment was evaluated.Results There were statistically significant differences in HIF-1α levels and cognitive function among different CMBs groups.Serum HIF-1α levels were significantly negatively correlated with overall cognitive function,visuospatial and executive function,attention,and delayed recall,and serum HIF-1α was positively correlated with the number of CMBs.HIF-1α may be a risk factor for CMBs and cognitive impairment associated with CSVD,and serum HIF-1α has potential in predict the cognitive impairment caused by CSVD.Conclusion Serum levels of HIF-1α were associated with the number of CMB and CSVD-related cognitive impairment,and serum levels of HIF-1α may have a predictive value for CSVD-related cognitive impairment.