Purpose To evaluate the predictive value of multifunctional parameters of single photon emission computed tomography gated myocardial perfusion imaging(SPECT G-MPI)for major adverse cardiovascular events(MACE)in chronic kidney disease(CKD)with abnormal stress myocardial perfusion.Materials and Methods A total of 99 patients diagnosed with CKD from June 2017 to March 2024 who underwent stress and rest G-MPI indicating abnormal myocardial perfusion in Beijing Anzhen Hospital,Capital Medical University.The American Heart Association 17-segment 5-point method and PHASE software were used to obtain the left ventricular myocardial perfusion,functional and synchronization parameters.According to the occurrence of MACE,the patients were divided into MACE group and non-MACE group.Cox regression was used to analyze the predictors related to MACE.The receiver operator characteristic curve was used to analyze the performance of predictors,the survival curves were obtained by the Kaplan-Meier method,Log-rank test was used to compare the differences in different groups.Results Finally,we enrolled 99 CKD patients with abnormal stress myocardial perfusion.35 patients(35.35%)developed MACE during the follow-up period.Cox regression analysis showed that stress phase bandwidth(SPBW)(HR=1.015,95%CI 1.002-1.028)and sum difference score(SDS)(HR=1.105,95%CI 1.008-1.211)were independent risk factors for predicting MACE(both P<0.05).The optimal cut-off value of SPBW and SDS for predicting MACE were 69° and 6 points,the area under the curve was 0.801 and 0.778,respectively.The incidence of MACE in the SPBW≥69° group and SDS≥6 points group was higher than that in SPBW<69° group and SDS<6 points group(66.6%vs.13.2%,53.3%vs.20.4%,both P<0.05).Conclusion SPECT G-MPI multifunctional parameters can be used to predict the prognosis of CKD patients with abnormal stress myocardial perfusion.SPBW and SDS are independent risk factors for MACE in these patients.

Purpose To evaluate the predictive value of multifunctional parameters of single photon emission computed tomography gated myocardial perfusion imaging(SPECT G-MPI)for major adverse cardiovascular events(MACE)in chronic kidney disease(CKD)with abnormal stress myocardial perfusion.Materials and Methods A total of 99 patients diagnosed with CKD from June 2017 to March 2024 who underwent stress and rest G-MPI indicating abnormal myocardial perfusion in Beijing Anzhen Hospital,Capital Medical University.The American Heart Association 17-segment 5-point method and PHASE software were used to obtain the left ventricular myocardial perfusion,functional and synchronization parameters.According to the occurrence of MACE,the patients were divided into MACE group and non-MACE group.Cox regression was used to analyze the predictors related to MACE.The receiver operator characteristic curve was used to analyze the performance of predictors,the survival curves were obtained by the Kaplan-Meier method,Log-rank test was used to compare the differences in different groups.Results Finally,we enrolled 99 CKD patients with abnormal stress myocardial perfusion.35 patients(35.35%)developed MACE during the follow-up period.Cox regression analysis showed that stress phase bandwidth(SPBW)(HR=1.015,95%CI 1.002-1.028)and sum difference score(SDS)(HR=1.105,95%CI 1.008-1.211)were independent risk factors for predicting MACE(both P<0.05).The optimal cut-off value of SPBW and SDS for predicting MACE were 69° and 6 points,the area under the curve was 0.801 and 0.778,respectively.The incidence of MACE in the SPBW≥69° group and SDS≥6 points group was higher than that in SPBW<69° group and SDS<6 points group(66.6%vs.13.2%,53.3%vs.20.4%,both P<0.05).Conclusion SPECT G-MPI multifunctional parameters can be used to predict the prognosis of CKD patients with abnormal stress myocardial perfusion.SPBW and SDS are independent risk factors for MACE in these patients.

Objective:To evaluate the clinical predictive value of SPECT myocardial perfusion imaging (MPI) in the occurrence of cardiac death in patients with chronic kidney disease (CKD).Methods:A retrospective follow-up was performed for 160 patients (109 males, 51 females; age: 68.5(61.0, 74.0) years) who underwent MPI in Beijing Anzhen Hospital, Capital Medical University between June 2017 and March 2024. The 17-segment 5-point method was used for image analysis to obtain the left ventricular myocardial perfusion and functional parameters. The patients were followed up for cardiac death, and divided into death group and survival group. Clinical data of those 2 groups were compare by χ2 test, the independent-sample t test or Mann-Whitney U test. Cox proportional hazards regression analysis was used to analyze the predictors related to cardiac death. The ROC curve was used to analyze the performance of predictors. Survival curves were obtained by the Kaplan-Meier method, and log-rank test was performed to compare the difference between 2 groups. Results:The follow-up time of 160 patients with CKD was 26.0(10.0, 46.5) months. Of 160 patients, 17 died and 143 survived. There were statistically significant differences in body mass index (BMI), previous myocardial infarction, previous revascularization, hypersensitive C-reactive protein (hs-CRP), positive MPI, left ventricular end-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), summed stress score (SSS), summed rest score (SRS) and summed difference score (SDS) between the death group and the survival group ( χ2 values: 4.58-16.13, t values: -2.34, -3.97, Z values: from -2.81 to 5.02, all P<0.05). Multivariate Cox regression analysis showed that SSS (hazard ratio ( HR)=1.153, 95% CI: 1.062-1.252, P=0.001) and hs-CRP ( HR=1.031, 95% CI: 1.004-1.058, P=0.023) were independent risk factors for cardiac death in patients with CKD. The optimal cut-off value of SSS for predicting cardiac death in those patients was determined to be 8 with the AUC of 0.815, and the incidence of cardiac death in the SSS ≥8 group was significantly higher than that in the SSS<8 group (33.3%(12/36) vs 4.0%(5/124); χ2 = 25.44, P<0.001). Conclusion:MPI is an important imaging method for the evaluation of cardiac death in patients with CKD, SSS and hs-CRP are important risk factors in predicting cardiac death in those patients.

Objective To explore the influencing factors of acute kidney injury in severe burn patients,and to construct a visual risk nomogram model.Methods A total of 390 patients with severe burn admitted to the Institute of Burn Frostbite and Tissue Function Reconstruction of Chinese People's Armed Police Force Specialty Medical Center from January 2018 to January 2022 were collected as an internal training data set,and 50 patients with severe burn admitted from February to December 2022 were collected as an external validation data set.The 390 patients of the internal training data set were divided into the acute kidney injury group and the non-acute kidney injury group according to the occurrence of acute kidney injury,and the baseline data of patients in the two groups were compared.Univariate and multivariate Logistic regression were used to analyze the risk factors of acute kidney injury in severe burn patients of the internal training data set,and a nomogram model was drawn.Subsequently,the model was verified both internally and externally.Kaplan-Meier analysis and Log-rank test were used to compare the 90-day survival rate of patients between the acute kidney injury group and the non-acute kidney injury group.Results The burn area(OR=1.18,95%CI:1.06 to 2.36,P=0.004),sequential organ failure assessment(SOFA)score(OR=1.81,95%CI:1.21 to 5.92,P<0.001),inhalation injury(OR=3.21,95%CI:1.23 to 6.35,P<0.001),neutrophil to lymphocyte ratio(NLR)(OR=1.22,95%CI:1.05 to 3.65,P<0.001)and albumin(ALB)(OR=0.78,95%CI:0.57 to 0.92,P=0.011)were the independent risk factors for the development of acute kidney injury in severe burn patients.The nomogram model was established by the above factors.The area under the receiver operating characteristic curve(AUC)of the internal training data set was 0.833(95%CI:0.752 to 0.935),the sensitivity was 81.2%,and the specificity was 83.2%.The AUC of the external validation data set was 0.842(95%CI:0.762 to 0.912),the sensitivity 87.2%,and the specificity was 78.7%.The 90-day survival rate of patients in the acute kidney injury group after burns was significantly lower than that in the non-acute kidney injury group(P<0.001).Conclusion Larger burn area,higher SOFA score,combined inhalation injury,increased NLR,and decreased ALB level are the risk factors for the occurrence of acute kidney injury in severe burn patients,which are related to the 90-day survival rate of patients after burns.The nomogram model based on the risk factors can provide certain reference for clinical individualized prevention and treatment of acute kidney injury in severe burn patients.

Objective:To evaluate the clinical predictive value of SPECT myocardial perfusion imaging (MPI) in the occurrence of cardiac death in patients with chronic kidney disease (CKD).Methods:A retrospective follow-up was performed for 160 patients (109 males, 51 females; age: 68.5(61.0, 74.0) years) who underwent MPI in Beijing Anzhen Hospital, Capital Medical University between June 2017 and March 2024. The 17-segment 5-point method was used for image analysis to obtain the left ventricular myocardial perfusion and functional parameters. The patients were followed up for cardiac death, and divided into death group and survival group. Clinical data of those 2 groups were compare by χ2 test, the independent-sample t test or Mann-Whitney U test. Cox proportional hazards regression analysis was used to analyze the predictors related to cardiac death. The ROC curve was used to analyze the performance of predictors. Survival curves were obtained by the Kaplan-Meier method, and log-rank test was performed to compare the difference between 2 groups. Results:The follow-up time of 160 patients with CKD was 26.0(10.0, 46.5) months. Of 160 patients, 17 died and 143 survived. There were statistically significant differences in body mass index (BMI), previous myocardial infarction, previous revascularization, hypersensitive C-reactive protein (hs-CRP), positive MPI, left ventricular end-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), summed stress score (SSS), summed rest score (SRS) and summed difference score (SDS) between the death group and the survival group ( χ2 values: 4.58-16.13, t values: -2.34, -3.97, Z values: from -2.81 to 5.02, all P<0.05). Multivariate Cox regression analysis showed that SSS (hazard ratio ( HR)=1.153, 95% CI: 1.062-1.252, P=0.001) and hs-CRP ( HR=1.031, 95% CI: 1.004-1.058, P=0.023) were independent risk factors for cardiac death in patients with CKD. The optimal cut-off value of SSS for predicting cardiac death in those patients was determined to be 8 with the AUC of 0.815, and the incidence of cardiac death in the SSS ≥8 group was significantly higher than that in the SSS<8 group (33.3%(12/36) vs 4.0%(5/124); χ2 = 25.44, P<0.001). Conclusion:MPI is an important imaging method for the evaluation of cardiac death in patients with CKD, SSS and hs-CRP are important risk factors in predicting cardiac death in those patients.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

ObjectiveTo explore the correlation between the occurrence of cardiovascular events in rheumatoid arthritis（RA） and traditional Chinese medicine（TCM） syndrome. MethodsThe cross-sectional study selected 6713 RA patients from 122 centres nationwide， in which general information such as name， gender， age， height， body weight， and course of disease were collected by completing a questionnaire； patients were classified into eight types of syndrome according to the information of their four examinations，i.e. wind-dampness obstruction syndrome， cold-dampness obstruction syndrome， dampness-heat obstruction syndrome， phlegm-stasis obstruction syndrome， stasis-blood obstructing collateral syndrome， qi-blood deficiency syndrome， liver-kidney insufficiency syndrome， and qi-yin deficiency syndrome. According to the occurrence of cardiovascular events， they were divided into the occurrence group and the non-occurrence group， and the condition assessment data and laboratory examination indexes were recorded. The test of difference between groups was used to analyse the possible risk factors for the occurrence of RA cardiovascular events， and binary logistic regression was used to analyse the correlation between TCM syndromes and RA cardiovascular events. ResultsA total of 6713 RA patients were included， including 256 cases in occurrence group and 6457 in non-occurrence group. There was no statistically significant difference between groups in terms of height， gender， insomnia， appetite， white blood cell（WBC）， hemoglobin（HGB）， platelets（PLT）， rheumatoid factor（RF）， anti-cyclic peptide containing citrulline（CCP）， alanine aminotransferase（ALT）， aspartate aminotransferase（AST）， γ-glutamyl transpeptidase（GGT）， urea creatinine（CREA）， and glucose（GLU）（P＞0.05）. The TCM syndromes between groups showed significant statistic differences（P＜0.05）. Patients in occurrence group had longer disease duration， heavier body weight， and older age； more severe conditions such as disease activity（DAS-28）， number of painful joints（TJC）， number of swollen joints（SJC）， health questionnaire scores（HAQ）， visual analog scores（VAS）， restlessness， and fatigue； higher blood sedimentation rate（ESR）， low-density lipoprotein（LDL-C）， triglyceride（TG）， total cholesterol（TC）， D-Dimer， and lower high-density lipoprotein（HDL-C）（P＜0.05）. The distribution of syndrome types showed that dampness-heat obstruction syndrome accounted for the largest proportion of patients in both groups and was higher in RA cardiovascular events. Logistic regression analysis showed that the occurrence of RA cardiovascular events was strongly associated with dampness-heat obstruction syndrome［OR=5.937， 95%CI （4.434， 7.949）， P＜0.001］. ConclusionThe occurrence of RA cardiovascular events were associated with TCM syndromes， and the probability of cardiovascular events in the RA patients with dampness-heat obstruction syndrome was 5.937 times higher than patients with other TCM syndromes.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Since the promulgation of the first Drug Administration Law of the People's Republic of China 40 years ago in 1984, China has undergone four main stages in the traditional Chinese medicine(TCM) regulation: the initial establishment of TCM regulation rules(1984-1997), the formation of a modern TCM regulatory system(1998-2014), the reform of the review and approval system for new TCM drugs(2015-2018), and the construction of a scientific regulation system for TCM(2019-2024). Over the past five years, a series of milestone achievements of TCM regulation in China have been achieved in the six aspects, including its strategic objectives and the establishment of a science-based regulatory system, the reform of the review and approval system for new TCM drugs, the optimization and improvement of the TCM standard system and its formation mechanism, comprehensive enhancement of regulatory capabilities for TCM safety, international harmonization of TCM regulation and its role in promoting innovation. Looking ahead, centered on advancing TCMRS to establish a sound regulatory framework tailored to the unique characteristics of TCM, TCM regulation will evolve into new reform patterns, advancing and extending across eight critical fronts, including the legal framework and policy architecture, the review and approval system for new TCM drugs, the quality standard and management system of TCM, the comprehensive quality & safety regulation and traceability system, the research and transformation system for TCMRS, AI-driven innovations in TCM regulation, the coordination between high-quality industrial development and high-level regulation, and the leadership in international cooperation and regulatory harmonization. In this way, a unique path for the development of modern TCM regulation with Chinese characteristics will be pioneered.
Humans ; China ; Drugs, Chinese Herbal/standards* ; History, 20th Century ; History, 21st Century ; Medicine, Chinese Traditional/trends*

Detection of poor-water-soluble substances typically requires an organic solvent containing solution,and therefore,the biosensors that can operate in such conditions are highly promising for practical applications.However,most existing biosensors have been developed in aqueous solution and it is hard to work effectively in organic solvent systems.In this work,we uncovered that the G-quadruplex(G4)/hemin DNAzyme(G4HD)could be strongly reactivated by NH4 in organic solvents at concentration up to 30％,and the activity was significantly higher than that in aqueous solutions containing K+.Based on this discovery,a biosensing system was developed for small molecule in 40％methanol by coupling G4HD with our previously identified RNA-cleaving DNAzyme(E3).This system comprised an ATP-activated aptazyme that was made of E3 and a G4HD that was activated by the cleavage product of the aptazyme.By using a manmade pipette tip filter to separate the reaction products,the subsequent colorimetric reaction of the G4HD could be triggered.This biosensing system enabled the visualization of target molecules in organic cosolvents without any other instruments.The activable DNAzyme-cascade sensing system had potential in point-of-care detection of poor-water-soluble pollutants,thereby enhancing the practical values of functional nucleic acid-based biosensors in real-world detection conditions.