ObjectiveTo construct an actor-network for integrating physical activity into rehabilitation services based on the World Health Organization Rehabilitation in Health Service System framework and actor-network theory (ANT). MethodsContent analysis was employed using the six building blocks of health service systems as the theoretical framework. Actors related to rehabilitation services were extracted and categorized into a rehabilitation actor pool, while a physical activity actor pool was formed based on four major physical activity scenarios. Actors from both pools were integrated, deduplicated and classified to form a final list of integrated actors. Using ANT, the construction process of the actor network integrating physical activity into rehabilitation was analyzed through the four stages of translation: problematization, interessment, enrollment and mobilization. ResultsA dynamic integration network was constructed, comprising human actors (patients, rehabilitation professionals, researchers, sports coaches, government departments, medical institutions, community organizations and industry media, etc.) and non-human actors (assistive devices, sports infrastructure, smart equipment, information systems, online exercise guidance systems, laws and regulations, strategic documents, and exercise prescriptions, etc.). The study identified maximizing rehabilitation outcomes as the mandatory passage point and elaborated on the critical role of government departments as focal actors in coordinating various stakeholders. ConclusionThe integration of physical activity into rehabilitation services is a dynamic network constructed by diverse actors through a process of translation. ANT provides an operational theoretical framework for cross-departmental governance of rehabilitation policies in China, promotes the spatial expansion of the rehabilitation field, and drives its transformation toward a networked and ecological system. The government needs to play a leading role in facilitating role reconstruction and synergy among heterogeneous actors in both the sports and rehabilitation sectors through mechanism design, to create a bidirectional empowerment mechanism that fosters mutual progress and ensures the sustainable development of integrated services.

Lung transplantation is a definitive treatment for end-stage lung disease and can significantly improve patient prognosis. However, postoperative complications such as infection, rejection, ischemia-reperfusion injury and chronic lung allograft dysfunction intertwine to form a complex pathological network, posing persistent challenges to long-term patient survival. In 2025, research teams worldwide have made systematic progress in the field of basic lung transplantation research. By integrating cutting-edge technologies including single-cell multi-omics, spatial transcriptomics and novel animal models, significant breakthroughs have been achieved in the evolutionary dynamics of drug-resistant infections, molecular mechanisms of immune regulation, programmed cell death, optimization of donor lung protection strategies and early warning of chronic lung allograft dysfunction. This article systematically reviews the representative advances in basic lung transplantation research worldwide in 2025, and deeply analyzes the implications of mechanistic breakthroughs for optimizing diagnosis and treatment strategies, aiming to anchor the direction for innovative breakthroughs and clinical translation in basic lung transplantation research.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

Objective:To construct a method for hepatitis B virus (HBV) DNA detection based on recombinase-mediated isothermal amplification (RAA)-clustered regularly interspaced short palindromic repeats and their associated protein 13a (CRISPR-Cas13a).Methods:Through the alignment and screening of HBV DNA sequences, a positive plasmid was constructed, and recombinase-aided amplification (RAA) primers and CRISPR RNA (crRNA) were designed. A method for detecting HBV DNA based on the RAA-CRISPR-Cas13a system was developed, and the specificity and sensitivity were evaluated. Utilizing the CRISPR-Cas13a system, 70 clinical samples from HBV DNA-positive patients with various viral loads collected at Beijing You′an Hospital from 2019 to 2021 were analyzed. The detection results were further compared with those results using real-time quantitative polymerase chain reaction (qPCR).Results:The optimal RAA amplification primers and crRNA were first screened using the RAA-CRISPR-Cas13a method, with the sensitivities for detecting HBV DNA standards and for clinical samples at 1 IU/ml and<10 IU/ml, respectively, demonstrating specificity for HBV DNA detection. Compared with qPCR (the gold standard), the detection consistency between the two methods was 100% (70/70).Conclusion:This study established a method for detecting HBV DNA by integrating recombinase-aided amplification (RAA) technology with CRISPR/Cas13a technology.

Lung transplantation is currently the only recognized effective treatment for end-stage lung disease and has improved the quality of life for patients. However, lung transplantation still faces many challenges, including rejection, infection, post-transplant acute kidney injury, post-transplant diabetes mellitus, ischemia-reperfusion injury and donor shortage, etc. Chinese lung transplantation scholars made a series of important progress in the field of clinical research in 2024, focusing on the study and solution of the above problems, and providing new ideas for lung transplantation surgery. This article systematically reviews the clinical research and technological innovation in the field of lung transplantation in 2024, summarizes the achievements of clinical research in the field of lung transplantation in China in 2024, and aims to providing new directions and strategies for future research.

Lung transplantation is the optimal treatment for end-stage lung diseases and can significantly improve prognosis of the patients. However, postoperative complications such as infection, rejection, ischemia-reperfusion injury, and other challenges (like shortage of donor lungs) , limit the practical application of lung transplantation in clinical practice. Chinese research teams have been making continuous efforts and have achieved breakthroughs in basic research on lung transplantation by integrating emerging technologies and cutting-edge achievements from interdisciplinary fields, which has strongly propelled the development of this field. This article will comprehensively review the academic progress made by Chinese research teams in the field of lung transplantation in 2024, with a focus on the achievements of Chinese teams in basic research on lung transplantation. It aims to provide innovative ideas and strategies for key issues in the basic field of lung transplantation and to help China's lung transplantation cause reach a higher level.

Objective To examine the association between lymphocyte subsets and renal clinicopathological characteristics as well as prognosis in patients with IgA nephropathy(IgAN).Methods The retrospective analysis included general clinical data and pathological examination results of IgAN patients diagnosed by renal biopsy at the Fourth Hospital of Hebei Medical University from January 2018 to January 2022.Correlation tests were conducted to examine the relationship between lymphocyte subsets and other significant clinicopathological parameters.The optimal cut-off value of CD4+T determined using the Youden index,and patients were grouped accordingly.Kaplan-Meier survival curves and Cox regression analyses were employed to compare the low and high CD4+T lymphocyte groups among IgAN patients,identifying factors influencing renal function progression.The endpoint event was defined as a decrease in estimated glomerular filtration rate(eGFR)of≥30%from baseline,progression to end-stage renal disease(ESRD)[eGFR<15 mL/(min·1.73 m2)or initiation of renal replacement therapy],or all-cause mortality.Results Low CD4+T lymphocytes were significantly positively correlated with blood IgA levels and the proportion of glomerular crescents in IgAN patients(all P<0.05).This study included a total of 53 IgAN patients,divided into two groups based on CD4+T lymphocyte counts:20 patients in the low CD4+T lymphocyte group and 33 patients in the high CD4+T lymphocyte group.In the low CD4+T lymphocyte group,there was a higher proportion of males and a lower proportion of glomerular crescents(P<0.05).Kaplan-Meier survival analysis revealed that patients with low CD4+lymphocytes had a significantly lower cumulative renal survival rate(Log-Rank test χ2=4.188,P=0.041).Cox regression analysis indicated that low CD4+lymphocytes were an independent risk factor for the progression of renal function decline in IgAN patients(HR=2.614,95%CI:1.006～6.788,P=0.048).Conclusions Patients with higher levels of CD4+T lymphocytes exhibit a lower risk of adverse renal outcomes.In contrast,patients with IgA nephropathy and low CD4+T lymphocyte counts tend to have poorer renal survival rates.

Objective:To construct a method for hepatitis B virus (HBV) DNA detection based on recombinase-mediated isothermal amplification (RAA)-clustered regularly interspaced short palindromic repeats and their associated protein 13a (CRISPR-Cas13a).Methods:Through the alignment and screening of HBV DNA sequences, a positive plasmid was constructed, and recombinase-aided amplification (RAA) primers and CRISPR RNA (crRNA) were designed. A method for detecting HBV DNA based on the RAA-CRISPR-Cas13a system was developed, and the specificity and sensitivity were evaluated. Utilizing the CRISPR-Cas13a system, 70 clinical samples from HBV DNA-positive patients with various viral loads collected at Beijing You′an Hospital from 2019 to 2021 were analyzed. The detection results were further compared with those results using real-time quantitative polymerase chain reaction (qPCR).Results:The optimal RAA amplification primers and crRNA were first screened using the RAA-CRISPR-Cas13a method, with the sensitivities for detecting HBV DNA standards and for clinical samples at 1 IU/ml and<10 IU/ml, respectively, demonstrating specificity for HBV DNA detection. Compared with qPCR (the gold standard), the detection consistency between the two methods was 100% (70/70).Conclusion:This study established a method for detecting HBV DNA by integrating recombinase-aided amplification (RAA) technology with CRISPR/Cas13a technology.

Objective To examine the association between lymphocyte subsets and renal clinicopathological characteristics as well as prognosis in patients with IgA nephropathy(IgAN).Methods The retrospective analysis included general clinical data and pathological examination results of IgAN patients diagnosed by renal biopsy at the Fourth Hospital of Hebei Medical University from January 2018 to January 2022.Correlation tests were conducted to examine the relationship between lymphocyte subsets and other significant clinicopathological parameters.The optimal cut-off value of CD4+T determined using the Youden index,and patients were grouped accordingly.Kaplan-Meier survival curves and Cox regression analyses were employed to compare the low and high CD4+T lymphocyte groups among IgAN patients,identifying factors influencing renal function progression.The endpoint event was defined as a decrease in estimated glomerular filtration rate(eGFR)of≥30%from baseline,progression to end-stage renal disease(ESRD)[eGFR<15 mL/(min·1.73 m2)or initiation of renal replacement therapy],or all-cause mortality.Results Low CD4+T lymphocytes were significantly positively correlated with blood IgA levels and the proportion of glomerular crescents in IgAN patients(all P<0.05).This study included a total of 53 IgAN patients,divided into two groups based on CD4+T lymphocyte counts:20 patients in the low CD4+T lymphocyte group and 33 patients in the high CD4+T lymphocyte group.In the low CD4+T lymphocyte group,there was a higher proportion of males and a lower proportion of glomerular crescents(P<0.05).Kaplan-Meier survival analysis revealed that patients with low CD4+lymphocytes had a significantly lower cumulative renal survival rate(Log-Rank test χ2=4.188,P=0.041).Cox regression analysis indicated that low CD4+lymphocytes were an independent risk factor for the progression of renal function decline in IgAN patients(HR=2.614,95%CI:1.006～6.788,P=0.048).Conclusions Patients with higher levels of CD4+T lymphocytes exhibit a lower risk of adverse renal outcomes.In contrast,patients with IgA nephropathy and low CD4+T lymphocyte counts tend to have poorer renal survival rates.

Objective:To investigate the application effect of problem-based learning (PBL) combined with scenario simulation in nursing teaching of needlestick injuries.Methods:A total of 123 undergraduates majoring in nursing were selected as research subjects from the classes of 2020 and 2021 in a medical university. The 60 undergraduates in the class of 2020 were established as control group and were given PBL teaching, and the 63 undergraduates in the class of 2021 were established as experimental group and were given PBL combined with scenario simulation. The two groups were compared in terms of theoretical score, skill examination score, and knowledge-attitude-practice (KAP) score of needlestick injury knowledge. SPSS 25.0 was used to perform the t-test, the chi-square test, and the rank sum test. Results:Compared with the control group, the experimental group had significantly higher scores of theoretical examination [(84.43±5.03) vs. (80.30±4.81), P<0.001] and skill examination [(88.40±4.26) vs. (83.55±5.84), P<0.001], as well as significantly higher scores of knowledge [(14.46±1.03) vs. (13.18±1.23), P<0.001], attitude [(52.59±3.09) vs. (48.05±3.06), P<0.001], and practice [(67.37±4.28) vs. (62.17±3.92), P<0.001] in KAP questionnaire. Conclusions:PBL combined with scenario simulation teaching can effectively improve the knowledge of protection against needlestick injuries and related skills in nursing students, enhance their awareness of needlestick injuries, and promote the protective behavior against needlestick injuries.