Radionuclide drug conjugates(RDC)represent the culmination of interdisciplinary integra-tion.By virtue of their precise targeting capability,high diagnostic sensitivity,and remarkable therapeutic effi-cacy in tumor diagnosis and treatment,RDC has emerged as promising theranostic agents with immense applica-tion potential.This article systematically reviews the progress in RDC development in China from 2009 to 2024,encompassing an overview of RDC,its structure and classification,trends in clinical research,advances in clinical trials,and national policy support.The aim is to provide valuable insights for researchers in related fields,thereby facilitating further development and application of RDC-based therapeutics.

Objective:To construct a tripartite game model involving the government,the public,and the pharmaceutical industry alliance during public health emergencies,revealing the dynamic mechanisms of health-related information quality regulation and exploring effective strategies to optimize the informa-tion dissemination environment through reward-punishment mechanisms.Methods:Based on evolutionary game theory,a tripartite evolutionary game model was established,integrating strategy spaces,payoff functions,and parameter definitions for each stakeholder.The pharmaceutical industry alliance's strate-gies included publishing high-or low-quality information(α),the public's strategies encompassed ration-al analysis or passive response(β),and the government's strategies involved regulatory enforcement or inaction(γ).Key parameters,such as economic benefits(Iyy),regulatory costs(Czf),penalties(Fyy),and incentives(Pyy),were quantified to reflect real-world scenarios.Replicator dynamic equa-tions and Jacobian matrices were derived to analyze the stability of equilibrium points,while MATLAB 2016a simulations were conducted to validate the model under varying initial conditions(e.g.,Iyy=100,150,200;Pyy=0,20,35;Fyy=0,10,20).Sensitivity analyses examined the impact of critical pa-rameters on system evolution,by 50 iterative simulations to observe convergence patterns.Results:The study revealed three key findings:(1)Public rational discernment(β)significantly influenced the phar-maceutical industry's strategy.Simulations demonstrated that increasing Iqz(benefits of information acqui-sition)reduced Cqz(cognitive costs),elevating β from 0.4 to 0.8 and driving α(high-quality information probability)to stabilize at 1.(2)Government regulatory intensity(γ)correlated positively with the so-cial hazards of low-quality information.When Fyy+Pyy＞Iyy,speculative behaviors decreased,achieving equilibrium at α=1.(3)Dual stable equilibria emerged:a high-quality equilibrium(α=1,β=1,γ=0)with lower regulatory costs and a low-quality equilibrium(α=0,β=0,γ=1)associated with higher social risks.Phase diagrams illustrated path dependency,where initial α＜0.5 led to the low-quality equilibrium unless dynamic penalties(Fyy＞20)and incentives(Pyy＞30)were enforced.Conclusion:A"carrot-stick"collaborative governance framework is proposed,emphasizing categorized regulation,AI-enabled auditing,and dynamic penalty systems.Future research should integrate emotional utility func-tions to address irrational decision-making impacts,thereby enhancing the adaptability of health informa-tion regulatory systems.

Radionuclide drug conjugates(RDC)represent the culmination of interdisciplinary integra-tion.By virtue of their precise targeting capability,high diagnostic sensitivity,and remarkable therapeutic effi-cacy in tumor diagnosis and treatment,RDC has emerged as promising theranostic agents with immense applica-tion potential.This article systematically reviews the progress in RDC development in China from 2009 to 2024,encompassing an overview of RDC,its structure and classification,trends in clinical research,advances in clinical trials,and national policy support.The aim is to provide valuable insights for researchers in related fields,thereby facilitating further development and application of RDC-based therapeutics.

Objective:To construct a tripartite game model involving the government,the public,and the pharmaceutical industry alliance during public health emergencies,revealing the dynamic mechanisms of health-related information quality regulation and exploring effective strategies to optimize the informa-tion dissemination environment through reward-punishment mechanisms.Methods:Based on evolutionary game theory,a tripartite evolutionary game model was established,integrating strategy spaces,payoff functions,and parameter definitions for each stakeholder.The pharmaceutical industry alliance's strate-gies included publishing high-or low-quality information(α),the public's strategies encompassed ration-al analysis or passive response(β),and the government's strategies involved regulatory enforcement or inaction(γ).Key parameters,such as economic benefits(Iyy),regulatory costs(Czf),penalties(Fyy),and incentives(Pyy),were quantified to reflect real-world scenarios.Replicator dynamic equa-tions and Jacobian matrices were derived to analyze the stability of equilibrium points,while MATLAB 2016a simulations were conducted to validate the model under varying initial conditions(e.g.,Iyy=100,150,200;Pyy=0,20,35;Fyy=0,10,20).Sensitivity analyses examined the impact of critical pa-rameters on system evolution,by 50 iterative simulations to observe convergence patterns.Results:The study revealed three key findings:(1)Public rational discernment(β)significantly influenced the phar-maceutical industry's strategy.Simulations demonstrated that increasing Iqz(benefits of information acqui-sition)reduced Cqz(cognitive costs),elevating β from 0.4 to 0.8 and driving α(high-quality information probability)to stabilize at 1.(2)Government regulatory intensity(γ)correlated positively with the so-cial hazards of low-quality information.When Fyy+Pyy＞Iyy,speculative behaviors decreased,achieving equilibrium at α=1.(3)Dual stable equilibria emerged:a high-quality equilibrium(α=1,β=1,γ=0)with lower regulatory costs and a low-quality equilibrium(α=0,β=0,γ=1)associated with higher social risks.Phase diagrams illustrated path dependency,where initial α＜0.5 led to the low-quality equilibrium unless dynamic penalties(Fyy＞20)and incentives(Pyy＞30)were enforced.Conclusion:A"carrot-stick"collaborative governance framework is proposed,emphasizing categorized regulation,AI-enabled auditing,and dynamic penalty systems.Future research should integrate emotional utility func-tions to address irrational decision-making impacts,thereby enhancing the adaptability of health informa-tion regulatory systems.

Objective To investigate the application of organoid technology in colorectal cancer research and analyze the factors influencing the success rate of organoid cultivation. Methods A total of 24 samples of colorectal cancer patients treated at Tianjin Fifth Central Hospital and cultured organoids using specific culture media and Matrigel. The samples were collected within 30 minutes post-excision and stored at 4℃ to minimize contamination and protein degradation. During the cultivation process,the authors recorded instances of bacterial or fungal contamination and the organoid growth,and test for their histological structure and expression of tumor markers. Additionally,by analyzing clinical information from the patients who provided the samples,explore potential factors that may affect the success rate of culturing colorectal cancer organoids. Results A success rate of 70.8％ (17/24) was achieved in the cultivation of organoid. The success rate of organoid culture was significantly different from that of tumor stage (all P<0.05),with significantly higher successful organoid cultivation rate for stage Ⅱ and stage Ⅲ tumor tissues than those for stageⅠand Ⅳ[83.3％ (5/6),90.9％ (10/11) vs. 33.4％ (1/3),25.0％ (1/4)]. Additionally,samples with a Ki-67 positive area proportion of 55％-70％ exhibited the highest success rate (100％). Phenotypic experiments on the organoids indicated that their pathological histological structure and the expression of tumor markers were consistent with those of the primary tissues,suggesting that the organoids retained the histological characteristics of the primary lesions. Conclusions This study successfully established a colorectal cancer organoid model revealing the impact of tumor staging and the proportion of Ki-67 positive areas on the success rate of culture. The organoid model effectively retains the histological characteristics of the primary lesion,providing a powerful in vitro tool for the research and treatment of colorectal cancer.

Objective To investigate the influencing factors of low cardiac output syndrome(LCOS)after coronary artery bypass grafting(CABG)and construct a nomogram model to predict the risk of LCOS occurrence.Methods A total of 231 patients with coronary atherosclerotic heart disease who underwent CABG surgery in the Heart Center of Henan Provincial People's Hospital from October 2019 to May 2022 were selected for the study.The patients were randomly divided into a training set(n=162)and a validation set(n=69)at a ratio of 7∶3.The comparability between the parameters of the patients in the training and validation sets was assessed.Based on the occurrence of LCOS after CABG,patients in the training set were divided into LCOS group(n=33)and non-LCOS group(n=129).Univariate and multivariate logistic regression analysis were conducted on the sample parameters in the training set to identify independent risk factors for LCOS after CABG.A nomogram prediction model for the risk of LCOS after CABG was constructed,and its discrimination,calibration,and clinical applicability were evaluated by using the receiver operating characteristic curve,calibration curve,and decision curve analysis.Results The incidence of LCOS in patients of the training and validation sets was 20.37％(33/162)and 18.84％(13/69),respectively.There were no statistically significant differences in various parameters between the training and validation sets(P＞0.05).In the training set,there were statistically significant differences in the following parameters between the non-LCOS group and the LCOS group patients,including age,heart rate,blood urea nitrogen,serum creatinine,estimated glomerular filtration rate(eGFR),serum N-terminal pro B-type natriuretic peptide(NT-proBNP),serum troponin T,left ventricular ejection fraction(LVEF),mitral regurgitation area,history of myocardial infarction,proportion of NYHA class Ⅲ-Ⅳ,proportion of patients requiring cardiopulmonary bypass,surgical duration,intraoperative bleeding volume,and postoperative hemodynamic indicators such as central venous pressure,pulmonary arterial diastolic pressure and pulmonary artery pulse index(PAPI)(P＜0.05).Multivariate logistic regression analysis showed that preoperative LVEF decrease[odds ratio(OR)=0.891,95％confidence interval(CI):0.832-0.954,P=0.001)],preoperative eGFR decrease(OR=0.963,95％CI:0.934-0.994,P=0.018),preoperative NT-proBNP increase(OR=1.001,95％CI:1.000-1.001,P=0.006),increased operation time(OR=1.013,95％CI:1.003-1.022,P=0.008),and postoperative PAPI reduction(OR=0.094,95％CI:0.028-0.319,P=0.000)were independent risk factors for LCOS after CABG.A nomogram prediction model was built based on these indicators.In the training set,the nomogram prediction model had an area under the curve(AUC)of 0.931(95％CI:0.890-0.972)for predicting the LCOS occurrence,with a sensitivity of 82.20％and a specificity of 90.90％.In the validation set,the AUC for predicting the LCOS occurrence was 0.907(95％CI:0.813-1.000),with a sensitivity of 96.40％and a specificity of 84.60％.This indicated that the model had high discrimination.The calibration curve showed good consistency between the predicted probability and the actual probability of LCOS occurrence in both the training and validation sets(average absolute error:0.038 and 0.026,respectively).The Hosmer-Lemeshow goodness-of-fit test demonstrated that the model's prediction deviation for the LCOS occurrence was not statistically significant compared to the actual occurrence(x2=6.381,6.907,P＞0.05),indicating good calibration of the model.Conclusion Decreased LVEF and eGFR and elevated NT-proBNP preoperatively,prolonged surgical duration,and decreased PAPI postoperatively are independent risk factors for LCOS after CABG.The nomogram prediction model established based on these factors has high discrimination,calibration,and clinical applicability,and can effectively predict the occurrence of LCOS after CABG.

Objective To provide a theoretical basis for radiation health supervision through an analysis of the situation of computed tomography (CT) equipment quality control and CT room radiological protection in Guangdong Province, China in recent years. Methods We collected the data of 392 times of CT quality control and radiological protection testing by a third-party radiological health technical service institution in Guangdong Province from 2019 to 2021. We analyzed the levels of CT-owning hospitals, CT manufacturers, CT quality control test results, and the pass rate of radiation protection tests. Results The examined CT scanners were from different levels of hospitals in Guangdong Province, and were manufactured by nine major CT equipment manufacturers at home and abroad. The pass rate of CT room radiological protection was 99.88%, and the ambient dose equivalent rates of five monitoring points exceeded the limit, with four at the control room door and one at the shield wall of the room. The overall pass rate of CT equipment quality control was 99.49%, and the non-conforming parameters were the accuracy of positioning light and the deviation of reconstructed slice thickness. Conclusion In recent years, CT equipment quality control and room radiation protection in Guangdong Province have been at a high level.

To explore the status and characteristics of clinical trials of therapeutic cancer vaccines, and provide the overall trend of clinical translational research of therapeutic cancer vaccines.

To explore the status and characteristics of clinical trials of therapeutic cancer vaccines, and provide the overall trend of clinical translational research of therapeutic cancer vaccines.

Objective To investigate the application of organoid technology in colorectal cancer research and analyze the factors influencing the success rate of organoid cultivation. Methods A total of 24 samples of colorectal cancer patients treated at Tianjin Fifth Central Hospital and cultured organoids using specific culture media and Matrigel. The samples were collected within 30 minutes post-excision and stored at 4℃ to minimize contamination and protein degradation. During the cultivation process,the authors recorded instances of bacterial or fungal contamination and the organoid growth,and test for their histological structure and expression of tumor markers. Additionally,by analyzing clinical information from the patients who provided the samples,explore potential factors that may affect the success rate of culturing colorectal cancer organoids. Results A success rate of 70.8％ (17/24) was achieved in the cultivation of organoid. The success rate of organoid culture was significantly different from that of tumor stage (all P<0.05),with significantly higher successful organoid cultivation rate for stage Ⅱ and stage Ⅲ tumor tissues than those for stageⅠand Ⅳ[83.3％ (5/6),90.9％ (10/11) vs. 33.4％ (1/3),25.0％ (1/4)]. Additionally,samples with a Ki-67 positive area proportion of 55％-70％ exhibited the highest success rate (100％). Phenotypic experiments on the organoids indicated that their pathological histological structure and the expression of tumor markers were consistent with those of the primary tissues,suggesting that the organoids retained the histological characteristics of the primary lesions. Conclusions This study successfully established a colorectal cancer organoid model revealing the impact of tumor staging and the proportion of Ki-67 positive areas on the success rate of culture. The organoid model effectively retains the histological characteristics of the primary lesion,providing a powerful in vitro tool for the research and treatment of colorectal cancer.