Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Background::In vitro fertilization (IVF) has emerged as a transformative solution for infertility. However, achieving favorable live-birth outcomes remains challenging. Current clinical IVF practices in IVF involve the collection of heterogeneous embryo data through diverse methods, including static images and temporal videos. However, traditional embryo selection methods, primarily reliant on visual inspection of morphology, exhibit variability and are contingent on the experience of practitioners. Therefore, an automated system that can evaluate heterogeneous embryo data to predict the final outcomes of live births is highly desirable. Methods::We employed artificial intelligence (AI) for embryo morphological grading, blastocyst embryo selection, aneuploidy prediction, and final live-birth outcome prediction. We developed and validated the AI models using multitask learning for embryo morphological assessment, including pronucleus type on day 1 and the number of blastomeres, asymmetry, and fragmentation of blastomeres on day 3, using 19,201 embryo photographs from 8271 patients. A neural network was trained on embryo and clinical metadata to identify good-quality embryos for implantation on day 3 or day 5, and predict live-birth outcomes. Additionally, a 3D convolutional neural network was trained on 418 time-lapse videos of preimplantation genetic testing (PGT)-based ploidy outcomes for the prediction of aneuploidy and consequent live-birth outcomes.Results::These two approaches enabled us to automatically assess the implantation potential. By combining embryo and maternal metrics in an ensemble AI model, we evaluated live-birth outcomes in a prospective cohort that achieved higher accuracy than experienced embryologists (46.1% vs. 30.7% on day 3, 55.0% vs. 40.7% on day 5). Our results demonstrate the potential for AI-based selection of embryos based on characteristics beyond the observational abilities of human clinicians (area under the curve: 0.769, 95% confidence interval: 0.709–0.820). These findings could potentially provide a noninvasive, high-throughput, and low-cost screening tool to facilitate embryo selection and achieve better outcomes. Conclusions::Our study underscores the AI model’s ability to provide interpretable evidence for clinicians in assisted reproduction, highlighting its potential as a noninvasive, efficient, and cost-effective tool for improved embryo selection and enhanced IVF outcomes. The convergence of cutting-edge technology and reproductive medicine has opened new avenues for addressing infertility challenges and optimizing IVF success rates.

Objective:Primary biliary cholangitis (PBC) and Primary Sj?gren′s syndrome (pSS) are autoimmune epithelial inflammatory diseases that share many common clinical symptoms. The aim of this study was to investigate the differences and diagnostic value of Autotaxin (ATX) in PBC and SS.Methods:The clinical data of 237 cases diagnosed with PBC, PBC secondary to SS, pSS and healthy individuals(HC) between September 2020 and September 2021 were retrospectively analyzed. The levels of ATX in each group were measured by enzyme-linked immunosorbent assay (ELISA), and the corresponding sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the curve ( AUC), etc were analyzed. Normally distributed data were expressed as mean ±SD and non-normally distributed as median (IQR). The differences and correlations between ATX and the biochemical tests in each group were assessed by applying the Mann-Whitney U test, Spearman correlation analysis, etc. P<0.05 was considered statistically significant difference. Results:The results showed that ATX was positive in 33.9%, 33.3% and 53.3% for PBC, PBC secondary SS, and pSS, respectively, with the specificities of 93.1%, 100% and 93.2%, respectively. The highest accuracy was achieved in pSS and the sensitivity and specificity were 86.5% and 93.2%, which were higher than those in PBC group(56.8%, 93.1%), respectively. Compared with HC [32.6(21.8, 60.5)ng/ml], ATX levels in PBC[59.3(48.6, 86.3)ng/ml, U=1 750.50, P<0.001], PBC-SS [73.6 (53.3,102.4)ng/ml; U=199.00, P<0.001], and pSS [152.6 (97.4,192.1)ng/ml, U=264.00, P<0.001] were elevated with significant difference ( P<0.05). ATX levels showed a decreasing trend from the pSS group to the HC group. ATX in PBC group[AUC(95% CI)= 0.73(0.651,0.812), P<0.001], PBC secondary SS group [AUC(95% CI)=0.82(0.730, 0.912), P<0.001], and pSS group [AUC(95% CI)=0.94(0.898, 0.984), P<0.001] had prediction accuracy. ATX was associated with total protein ( r=-0.31, P=0.041) level and glutaminase (r=-0.26, P=0.024) level. Conclusion:ATX has diagnostic value in both PBC and SS, and with higher sensitivity and specificity for the latter.