The neonatal mammalian heart has a remarkable regenerative capacity, while the adult heart has difficulty to regenerate. A metabolic reprogramming from glycolysis to fatty acid oxidation occurs along with the loss of cardiomyocyte proliferative capacity shortly after birth. In this study, we sought to determine if and how metabolic reprogramming regulates cardiomyocyte proliferation. Reversing metabolic reprogramming by carnitine palmitoyltransferase 1 (CPT1) inhibition, using cardiac-specific Cpt1a and Cpt1b knockout mice promoted cardiomyocyte proliferation and improved cardiac function post-myocardial infarction. The inhibition of CPT1 is of pharmacological significance because those protective effects were replicated by etomoxir, a CPT1 inhibitor. CPT1 inhibition, by decreasing poly(ADP-ribose) polymerase 1 expression, reduced ADP-ribosylation of dual-specificity phosphatase 1 in cardiomyocytes, leading to decreased p38 MAPK phosphorylation, and stimulation of cardiomyocyte proliferation. Our present study indicates that reversing metabolic reprogramming is an effective strategy to stimulate adult cardiomyocyte proliferation. CPT1 is a potential therapeutic target for promoting heart regeneration and myocardial infarction treatment.

Objective To explore the recognition capabilities of electronic nose combined with machine learning in identifying the breath odor map of benign and malignant pulmonary nodules and Traditional Chinese Medicine (TCM) syndrome elements. Methods The study design was a single-center observational study. General data and four diagnostic information were collected from 108 patients with pulmonary nodules admitted to the Department of Cardiothoracic Surgery of Hospital of Chengdu University of TCM from April 2023 to March 2024. The patients' TCM disease location and nature distribution characteristics were analyzed using the syndrome differentiation method. The Cyranose 320 electronic nose was used to collect the odor profiles of oral exhalation, and five machine learning algorithms including random forest (RF), K-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and eXtreme gradient boosting (XGBoost) were employed to identify the exhaled breath profiles of benign and malignant pulmonary nodules and different TCM syndromes. Results (1) The common disease locations in pulmonary nodules were ranked in descending order as liver, lung, and kidney; the common disease natures were ranked in descending order as Yin deficiency, phlegm, dampness, Qi stagnation, and blood deficiency. (2) The electronic nose combined with the RF algorithm had the best efficacy in identifying the exhaled breath profiles of benign and malignant pulmonary nodules, with an AUC of 0.91, accuracy of 86.36%, specificity of 75.00%, and sensitivity of 92.85%. (3) The electronic nose combined with RF, LR, or XGBoost algorithms could effectively identify the different TCM disease locations and natures of pulmonary nodules, with classification accuracy, specificity, and sensitivity generally exceeding 80.00%.Conclusion Electronic nose combined with machine learning not only has the potential capabilities to differentiate the benign and malignant pulmonary nodules, but also provides new technologies and methods for the objective diagnosis of TCM syndromes in pulmonary nodules.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective To analyze the radiomic and clinical features extracted from 2D ultrasound images of thyroid tumors in patients with Hashimoto's thyroiditis(HT)combined with papillary thyroid carcinoma(PTC)using machine learning(ML)models,and to explore the diagnostic performance of the method in making preoperative noninvasive identification of cervical lymph node metastasis(LNM).Methods A total of 528 patients with HT combined with PTC were enrolled and divided into two groups based on their pathological results of the presence or absence of LNM.The groups were subsequently designated the With LNM Group and the Without LNM Group.Three ultrasound doctors independently delineated the regions of interest and extracted radiomic features.Two modes,radiomic features and radiomics-clinical features,were used to construct random forest(RF),support vector machine(SVM),LightGBM,K-nearest neighbor(KNN),and XGBoost models.The performance of these five ML models in the two modes was evaluated by the receiver operating characteristic(ROC)curves on the test dataset,and SHapley Additive exPlanations(SHAP)was used for model visualization.Results All five ML models showed good performance,with area under the ROC curve(AUC)ranging from 0.798 to 0.921.LightGBM and XGBoost demonstrated the best performance,outperforming the other models(P＜0.05).The ML models constructed with radiomics-clinical features performed better than those constructed using only radiomic features(P＜0.05).The SHAP visualization of the best-performing models indicated that the anteroposterior diameter,superoinferior diameter,original_shape_VoxelVolume,age,wavelet-LHL_firstorder_10Percentile,and left-to-right diameter had the most significant effect on the LightGBM model.On the other hand,the superoinferior diameter,anteroposterior diameter,left-to-right diameter,original_shape_VoxelVolume,original_firstorder_InterquartileRange,and age had the most significant effect on the XGBoost model.Conclusion ML models based on radiomics and clinical features can accurately evaluate the cervical lymph node status in patients with HT combined with PTC.Among the 5 ML models,LightGBM and XGBoost demonstrate the best evaluation performance.

Objective:To seek a correlation between short-chain fatty acids (SCFAs) and skill in the activities of daily living (ADL) after an ischemic stroke.Methods:Ninety ischemic stroke survivors were assessed using the Barthel Index (BI). Fecal samples were collected and analyzed for the concentration of acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid, and isovaleric acid using gas chromatography. Spearman correlation analysis was conducted to identify SCFAs that correlated with the total BI score. Linear regressions were evaluated to explore the correlation between the total BI score and SCFAs.Results:The concentrations of propionic and butyric acids in the feces were found to correlate significantly with the total BI scores. Data including propionic acid and butyric acid levels, age, gender, body mass index, disease duration, any history of hypertension or diabetes, and other SCFAs were included in the regression models. Propionic and butyric acid levels were found to be potentially useful predictors of total BI scores.Conclusions:The concentration of propionic and butyric acids in the feces after an ischemic stroke can predict the survivor′s total BI score. Those concentrations could therefore be useful for predicting ADL ability.

Objective To evaluate the process risk of the implementation of prevention and control measures for surgical site infection(SSI)after colorectal surgery,and explore the application effect of failure mode and effects analysis(FMEA)based on action priority.Methods FMEA based on action priority was adopted to evaluate the whole process of the implementation of prevention and control measures for SSI after colorectal surgery.Prioritiza-tion ranking was conducted according to whether optimized measures were taken.Standard-reaching rate of comp-liance to SSI prevention and control measures as well as SSI incidence before and after the implementation of FMEA were compared.Results After evaluation,there were 7 high-priority and 22 medium-priority prevention and control measures for SSI.The control of medium-priority measures was strengthened,with a focus on developing further preventive and detectable measures for high-priority measures.The re-evaluation results after improvement showed that 7 high-priority measures have been downgraded to medium priority,and 16 medium-priority measures have been downgraded to low priority.Standard-reaching rate of compliance to SSI prevention and control measures in-creased from 77.15％(2 566/3 326)to 92.47％(3 096/3 348),and SSI incidence decreased from 6.04％(58/960)to 2.54％(60/2 364).Conclusion Application of FMEA based on action priority can effectively evaluate the risk of prevention and control process of SSI after colorectal surgery,and adopting preventive risk control measures accord-ing to the current situation can reduce the incidence of SSI after colorectal surgery.

Objective:To investigate the safety and therapeutic effect of split liver transplantation (SLT) in clinical application.Methods:This is a retrospective case-series study. The clinical data of 203 consecutive SLT, 79 living donor liver transplantation (LDLT) and 1 298 whole liver transplantation (WLT) performed at the Third Affiliated Hospital of Sun Yat-sen University from July 2014 to July 2023 were retrospectively analyzed. Two hundred and three SLT liver grafts were obtained from 109 donors. One hundred and twenty-seven grafts were generated by in vitro splitting and 76 grafts were generated by in vivo splitting. There were 90 adult recipients and 113 pediatric recipients. According to time, SLT patients were divided into two groups: the early SLT group (40 cases, from July 2014 to December 2017) and the mature SLT technology group (163 cases, from January 2018 to July 2023). The survival of each group was analyzed and the main factors affecting the survival rate of SLT were analyzed. The Kaplan-Meier method and Log-rank test were used for survival analysis.Results:The cumulative survival rates at 1-, 3-, and 5-year were 74.58%, 71.47%, and 71.47% in the early SLT group, and 88.03%, 87.23%, and 87.23% in the mature SLT group, respectively. Survival rates in the mature SLT group were significantly higher than those in the early SLT group ( χ2=5.560, P=0.018). The cumulative survival rates at 1-, 3- and 5-year were 93.41%, 93.41%, 89.95% in the LDLT group and 87.38%, 81.98%, 77.04% in the WLT group, respectively. There was no significant difference among the mature SLT group, the LDLT group and the WLT group ( χ2=4.016, P=0.134). Abdominal hemorrhage, infection, primary liver graft nonfunction,and portal vein thrombosis were the main causes of early postoperative death. Conclusion:SLT can achieve results comparable to those of WLT and LDLT in mature technology liver transplant centers, but it needs to go through a certain time learning curve.

Objective:To investigate the safety and therapeutic effect of split liver transplantation (SLT) in clinical application.Methods:This is a retrospective case-series study. The clinical data of 203 consecutive SLT, 79 living donor liver transplantation (LDLT) and 1 298 whole liver transplantation (WLT) performed at the Third Affiliated Hospital of Sun Yat-sen University from July 2014 to July 2023 were retrospectively analyzed. Two hundred and three SLT liver grafts were obtained from 109 donors. One hundred and twenty-seven grafts were generated by in vitro splitting and 76 grafts were generated by in vivo splitting. There were 90 adult recipients and 113 pediatric recipients. According to time, SLT patients were divided into two groups: the early SLT group (40 cases, from July 2014 to December 2017) and the mature SLT technology group (163 cases, from January 2018 to July 2023). The survival of each group was analyzed and the main factors affecting the survival rate of SLT were analyzed. The Kaplan-Meier method and Log-rank test were used for survival analysis.Results:The cumulative survival rates at 1-, 3-, and 5-year were 74.58%, 71.47%, and 71.47% in the early SLT group, and 88.03%, 87.23%, and 87.23% in the mature SLT group, respectively. Survival rates in the mature SLT group were significantly higher than those in the early SLT group ( χ2=5.560, P=0.018). The cumulative survival rates at 1-, 3- and 5-year were 93.41%, 93.41%, 89.95% in the LDLT group and 87.38%, 81.98%, 77.04% in the WLT group, respectively. There was no significant difference among the mature SLT group, the LDLT group and the WLT group ( χ2=4.016, P=0.134). Abdominal hemorrhage, infection, primary liver graft nonfunction,and portal vein thrombosis were the main causes of early postoperative death. Conclusion:SLT can achieve results comparable to those of WLT and LDLT in mature technology liver transplant centers, but it needs to go through a certain time learning curve.