Objective:To quantitatively evaluate the level of the three medical linkage in China from 2009 to 2022,explore the influencing factors and driving paths of the three medical linkage in China,and provide a new perspective for promoting the development of the three medical linkage.Methods:An optimized coupling coordination degree model was used to calculate the coupling coordination degree between the trinity healthcare systems and different binary systems within the systems in 31 provinces of China(excluding Hong Kong,Macao and Taiwan),and the Fuzzy-set Qualitative Comparative Analysis method was used to explore the condition configurations of multi-factor-driven three medical linkage.Results:From 2009 to 2022,the coupling coordination degree between the trinity healthcare systems in each province of China generally showed an increasing trend year by year.Among the binary systems,the overall coordinated development situation between the medical and medical insurance systems was the best and the regional development was the most balanced.The coupling coordination degree gap between the trinity healthcare system and the internal binary systems among provinces gradually widened,and the multi-polarization trend intensified.The paths to promote high-level three medical linkage can be summarized into two types:internal and external balanced development type(H1)and government-led type(H2,H3),among which the H1 path with per capita GDP and health expenditure as core conditions was the most common.Conclusion:It is suggested to enhance institutional and technological innovation,and integrate resources through a cross-departmental collaboration mechanism and digital technology.Provinces should select high-level optimization paths by leveraging regional endowments to narrow the regional development gap.Meanwhile,under the impetus of high-level policies,the protection and supervision system continues to improve,thereby promoting the three medical linkage.

Sacroiliac complex injuries are commonly seen in high-energy pelvic fractures. The injuries make a big difference in treatment patterns due to the diverse injury types, posing considerable challenges in formulating optimal treatment strategies, and hence are persistent clinical difficulties in orthopedic trauma. The clinical management of sacroiliac complex injuries presents several key challenges such as a non-negligible rate of missed diagnoses in associated vascular and visceral injuries, absence of standardized protocols for surgical approaches and reduction-fixation strategies across different injury patterns, and ongoing controversies regarding surgical indications and optimal timing for patients combined with concomitant lumbosacral plexus injuries. Currently, no systematic clinical guidelines are available for the diagnosis and treatment of sacroiliac complex injuries both domestically and internationally. To this end, the Pelvic and Acetabular Surgery Group, Orthopedic Branch, China International Exchange and Promotive Association for Medical and Health Care and Orthopedic Physician Branch, Chinese Medical Doctor Association organized a panel of domestic experts in the field to develop the Clinical guideline for the diagnosis and treatment of sacroiliac complex injuries ( version 2025), based on evidence-based medicine and adhering to the principles of scientific rigor, clinical applicability, and innovation. These guidelines provided 11 recommendations covering diagnosis, therapeutic principles and techniques, management protocols for lumbosacral plexus injuries, outcome evaluation, and postoperative rehabilitation pathways, etc., aiming to standardize the clinical management of sacroiliac complex injuries.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Objective:To quantitatively evaluate the level of the three medical linkage in China from 2009 to 2022,explore the influencing factors and driving paths of the three medical linkage in China,and provide a new perspective for promoting the development of the three medical linkage.Methods:An optimized coupling coordination degree model was used to calculate the coupling coordination degree between the trinity healthcare systems and different binary systems within the systems in 31 provinces of China(excluding Hong Kong,Macao and Taiwan),and the Fuzzy-set Qualitative Comparative Analysis method was used to explore the condition configurations of multi-factor-driven three medical linkage.Results:From 2009 to 2022,the coupling coordination degree between the trinity healthcare systems in each province of China generally showed an increasing trend year by year.Among the binary systems,the overall coordinated development situation between the medical and medical insurance systems was the best and the regional development was the most balanced.The coupling coordination degree gap between the trinity healthcare system and the internal binary systems among provinces gradually widened,and the multi-polarization trend intensified.The paths to promote high-level three medical linkage can be summarized into two types:internal and external balanced development type(H1)and government-led type(H2,H3),among which the H1 path with per capita GDP and health expenditure as core conditions was the most common.Conclusion:It is suggested to enhance institutional and technological innovation,and integrate resources through a cross-departmental collaboration mechanism and digital technology.Provinces should select high-level optimization paths by leveraging regional endowments to narrow the regional development gap.Meanwhile,under the impetus of high-level policies,the protection and supervision system continues to improve,thereby promoting the three medical linkage.

Sacroiliac complex injuries are commonly seen in high-energy pelvic fractures. The injuries make a big difference in treatment patterns due to the diverse injury types, posing considerable challenges in formulating optimal treatment strategies, and hence are persistent clinical difficulties in orthopedic trauma. The clinical management of sacroiliac complex injuries presents several key challenges such as a non-negligible rate of missed diagnoses in associated vascular and visceral injuries, absence of standardized protocols for surgical approaches and reduction-fixation strategies across different injury patterns, and ongoing controversies regarding surgical indications and optimal timing for patients combined with concomitant lumbosacral plexus injuries. Currently, no systematic clinical guidelines are available for the diagnosis and treatment of sacroiliac complex injuries both domestically and internationally. To this end, the Pelvic and Acetabular Surgery Group, Orthopedic Branch, China International Exchange and Promotive Association for Medical and Health Care and Orthopedic Physician Branch, Chinese Medical Doctor Association organized a panel of domestic experts in the field to develop the Clinical guideline for the diagnosis and treatment of sacroiliac complex injuries ( version 2025), based on evidence-based medicine and adhering to the principles of scientific rigor, clinical applicability, and innovation. These guidelines provided 11 recommendations covering diagnosis, therapeutic principles and techniques, management protocols for lumbosacral plexus injuries, outcome evaluation, and postoperative rehabilitation pathways, etc., aiming to standardize the clinical management of sacroiliac complex injuries.

Objective:To analyze the safety and efficacy of ultrasound-guided percutaneous thermal ablation treatment for multiple T1N0M0 papillary thyroid carcinoma(PTC)with over 5 years follow-up.Methods:From January 2014 to January 2019,a retrospective analysis was conducted on patients with multiple T1N0M0 PTC who underwent ultrasound-guided thermal ablation.Patients with bilateral or unilateral lobes with isthmus PTC were enrolled in this study and were followed up at 1,3,6,12,24,36,48,and 60 months after ablation.The clinical data,ultrasound characteristics and ablation parameters of recurrent and non-recurrent patients were compared,and the efficacy and influencing factors of thermal ablation for multiple T1N0M0 PTC were analyzed.Results:After over 5 years follow-up,a total of 11 patients(16.18％)relapsed,57 patients(83.82％)did not re-lapse.No lymph node and distant metastasis were found.No significant correlation was detected between the recurrence and clinical features,ultrasound findings and ablation parameters(P＞0.05).Among the patients with recurrence,1 patient underwent observation,2 patients underwent total thyroidectomy,and the other 8 patients successfully underwent secondary ablation,all of which had no obvious adverse reactions.Conclusion:The ablation of multiple PTC in T1N0M0 stage is safe and effective,with a recurrence rate of 16.18％over 5 years follow-up,and ablation has no effect on second treatment for recurrent patients.

China prospective multicenter birth cohort (Prospective Omics Health Atlas birth cohort, POHA birth cohort) study was officially launched in 2022. This study, in collaboration with 12 participating units, aims to establish a high-quality, multidimensional cohort comprising 20 000 naturally conceived families and assisted reproductive families. The study involves long-term follow-up of parents and offspring, with corresponding biological samples collected at key time points. Through multi-omics testing and analysis, the study aims to conduct multi-omics big data research across the entire maternal and infant life cycle. The goal is to identify new biomarkers for maternal and infant diseases and provide scientific evidence for risk prediction related to maternal diseases and neonatal health.

Objective To evaluate the acute exacerbation of chronic obstructive pulmonary disease(COPD)(AECOPD)status via combining clinical data,lung function parameters with CT radiomic features based on machine learning method.Methods A total of 343 COPD patients,including 158 AECOPD patients and 185 non-AECOPD patients were retrospectively selected and randomly divided into training and testing sets at a ratio of 7∶3.The radiomics features were calculated after automatically delineating the whole lung volume of interest(VOI).Five machine learning methods were used to construct the AECOPD diagnostic model,then the corresponding Radiomics score(Rad-score)was calculated in the training set and was validated in the testing set.The logistic-combined model was established after integrating age,Global Initiative for Chronic Obstructive Lung Disease(GOLD)classification,vital capacity(VC),forced vital capacity(FVC),forced expiratory volume in one second(FEV1),FEV1％pred,FEV1/FVC％,peak expiratory flow(PEF),maximum ventilatory volume(MVV),and Rad-score value.The area under the curve(AUC)of receiver operating characteristic(ROC)curve was calculated to evaluate the evaluated performance of all models.Results The logistic regression model had the best diagnostic performance,with AUC of 0.724 and 0.758 in the training and testing sets,respectively.The performance of the logistic-combined model to diagnose AECOPD was superior to that of the single logistic regression model,with the AUC of 0.777 and 0.760 in the training and testing sets,respectively.Conclusion A combination strategy including clinical data,lung function parameters,and CT radiomics may be helpful to diagnose AECOPD status,with moderate diagnostic performance.

Objective To analyze the risk factors for severe illness caused by coronavirus disease 2019 in Fuzhou city.Methods The data of 4081 confirmed cases with current address in Fuzhou was collected from China Information System for Disease Control and Prevention from January 1 to June 30,2023.The epidemiological data of those cases was investigated such as the demographic characteristics,clinical manifestations and past medical history,etc.The risk factors of severe cases were analyzed by using the logistic regression.Results 4081 confirmed cases had been reported including 671 severe cases and 3410 non-severe cases.The demographic characteristics of severe cases,such as the proportion of male,age and current address in community were higher than that of non-severe cases,vaccination rate was lower than non-severe cases(59.02%vs.80.12%),the differences are statistically significant(P＜0.001).The clinical manifestations such as interval time between onset and visit(P=0.001),fever(P=0.002),difficulty in breathing/shortness of breath(P=0.001)were the factors related to severe illness.The past medical histories such as history of chronic lung disease,history of heart cerebrovascular disease of severe cases,were higher than that of non-severe cases(P＜0.001).Multivariate logistic regression showed that the male,the higher age,current address in community,no vaccination,the longer interval time between onset and visit,fever,difficulty in breathing/shortness of breath,the history of chronic lung disease,the history of heart cerebrovascular disease raised the risk of becoming severe cases.The healing time for severe cases was longer than that for non-severe cases(P＜0.001).Conclusion Sex,age,current address,vaccination,interval time between onset and visit,fever,difficulty in breathing/shortness of breath,history of chronic lung disease,and history of heart cerebrovascular disease are the influencing factors for severe illness.

Objective To establish antemortem and postmortem injury models in nude mice,observe the morphological changes of the wounds and the changes of the microbial communities in the wounds at different time points after the injury,and analyze the differences between antemortem and postmor-tem wounds.Methods Abdominal injury models were established in 48 BALB/c nude mice,which were classified into antemortem injury,4 h and 72 h postmortem injury groups,and the gross manifesta-tions and histopathological changes were observed on days 1,3,5,8,11 and 15 after injury.The mi-crobial communities in the wounds were analyzed by 16S rRNA sequencing technology.QIIME 2 soft-ware was used to calculate Shannon and Observed species indices.The Kruskal-Wallis test was used to determine statistical differences in α-diversity between groups.Jaccard similarity coefficients were calculated by using R v4.3.0 software and applied to the principal co-ordinates analysis to demonstrate inter-sample differences.Permutational multivariate analysis of variance(PERMANOVA)was used to analyze the differences between groups in the composition of bacterial colonies,and R2 values were calculated.Results On days 8,11 and 15 after injury,the antemortem and postmortem injuries could not be differentiated by morphological examination;the Shannon index and Observed species index were statistically different between the antemortem injury group and the 72 h postmortem injury group;the Jaccard similarity coefficient of the microbial community was statistically different between the an-temortem injury group and the 72 h postmortem injury group.The PERMANOVA R2 value gradually increased with the extension of time(0.22-0.61).Conclusion Through the analysis of the wound mi-crobial community,the microbial composition of wounds at different time points can be identified and compared,which provides a new perspective and method for the differentiation of antemortem injuries from postmortem injuries,with good application prospects.