Radiotherapy is a cornerstone in the treatment of malignant tumors. It induces DNA damage through high-energy radiation, preferentially eliminating rapidly proliferating tumor cells. However, its clinical efficacy is often limited by tumor radioresistance and collateral damage to normal tissues. Consequently, elucidating the cellular response mechanisms to radiation stress and identifying key targets that can both sensitize tumor cells and protect normal tissues have become critical strategies for improving radiotherapy outcomes. Radiation stress triggers structural remodeling of the nucleolus, leading to the dissociation of certain ribosomal proteins from the ribosome and enabling them to acquire extra-ribosomal functions. Among these, RPL11 can be released and specifically binds to MDM2, thus inhibiting its E3 ubiquitin ligase activity, stabilizing p53, and mediating cell cycle arrest and apoptosis. The RPL11-MDM2-p53 pathway, acting as a signaling hub that links nucleolar dysfunction to cell fate determination, plays a pivotal role in maintaining genomic stability and regulating cellular responses to radiation. This review first introduces the basic characteristics of RPL11 and elucidates the molecular basis of radiation-induced ribosomal stress. It then outlines the core regulatory mechanisms of the cell cycle. On this basis, it focuses on the mechanisms by which radiation-induced RPL11 regulates the cell cycle and analyzes the specific effects of RPL11 on cell cycle. Furthermore, it discusses the role of the RPL11-MDM2-p53 pathway in cell cycle regulation. Finally, it explores the role of this pathway in maintaining genomic stability and determining cell fate, and highlights its potential value as a target for radiosensitization, aiming to provide new perspectives for enhancing tumor radiosensitivity and reducing damage to normal tissues.

Radiotherapy is a cornerstone in the treatment of malignant tumors. It induces DNA damage through high-energy radiation, preferentially eliminating rapidly proliferating tumor cells. However, its clinical efficacy is often limited by tumor radioresistance and collateral damage to normal tissues. Consequently, elucidating the cellular response mechanisms to radiation stress and identifying key targets that can both sensitize tumor cells and protect normal tissues have become critical strategies for improving radiotherapy outcomes. Radiation stress triggers structural remodeling of the nucleolus, leading to the dissociation of certain ribosomal proteins from the ribosome and enabling them to acquire extra-ribosomal functions. Among these, RPL11 can be released and specifically binds to MDM2, thus inhibiting its E3 ubiquitin ligase activity, stabilizing p53, and mediating cell cycle arrest and apoptosis. The RPL11-MDM2-p53 pathway, acting as a signaling hub that links nucleolar dysfunction to cell fate determination, plays a pivotal role in maintaining genomic stability and regulating cellular responses to radiation. This review first introduces the basic characteristics of RPL11 and elucidates the molecular basis of radiation-induced ribosomal stress. It then outlines the core regulatory mechanisms of the cell cycle. On this basis, it focuses on the mechanisms by which radiation-induced RPL11 regulates the cell cycle and analyzes the specific effects of RPL11 on cell cycle. Furthermore, it discusses the role of the RPL11-MDM2-p53 pathway in cell cycle regulation. Finally, it explores the role of this pathway in maintaining genomic stability and determining cell fate, and highlights its potential value as a target for radiosensitization, aiming to provide new perspectives for enhancing tumor radiosensitivity and reducing damage to normal tissues.

Radiotherapy is a cornerstone in the treatment of malignant tumors. It induces DNA damage through high-energy radiation, preferentially eliminating rapidly proliferating tumor cells. However, its clinical efficacy is often limited by tumor radioresistance and collateral damage to normal tissues. Consequently, elucidating the cellular response mechanisms to radiation stress and identifying key targets that can both sensitize tumor cells and protect normal tissues have become critical strategies for improving radiotherapy outcomes. Radiation stress triggers structural remodeling of the nucleolus, leading to the dissociation of certain ribosomal proteins from the ribosome and enabling them to acquire extra-ribosomal functions. Among these, RPL11 can be released and specifically binds to MDM2, thus inhibiting its E3 ubiquitin ligase activity, stabilizing p53, and mediating cell cycle arrest and apoptosis. The RPL11-MDM2-p53 pathway, acting as a signaling hub that links nucleolar dysfunction to cell fate determination, plays a pivotal role in maintaining genomic stability and regulating cellular responses to radiation. This review first introduces the basic characteristics of RPL11 and elucidates the molecular basis of radiation-induced ribosomal stress. It then outlines the core regulatory mechanisms of the cell cycle. On this basis, it focuses on the mechanisms by which radiation-induced RPL11 regulates the cell cycle and analyzes the specific effects of RPL11 on cell cycle. Furthermore, it discusses the role of the RPL11-MDM2-p53 pathway in cell cycle regulation. Finally, it explores the role of this pathway in maintaining genomic stability and determining cell fate, and highlights its potential value as a target for radiosensitization, aiming to provide new perspectives for enhancing tumor radiosensitivity and reducing damage to normal tissues.

Objective To investigate the application of machine learning to predict the hemodynamic parameters of combined stenotic left coronary artery(LCA)aneurysms.Methods Parameterized modeling and simulation based on the geometric parameter range of combined stenosis LCA aneurysms in clinical statistics were conducted.The obtained simulation data was used as the dataset,and two common machine learning models were constructed and trained for optimization to predict two key hemodynamic parameters:wall shear stress(WSS)and pressure.By comparing and analyzing the performances of these models on the training and testing sets,the accuracy of each model was evaluated,and the effectiveness of the data-driven prediction of hemodynamic parameters for LCA aneurysms with concomitant stenosis was verified.Results The effectiveness of machine learning method in inverting the hemodynamic parameters of aneurysms was determined.For WSS prediction,the trained deep learning model and random forest model achieved mean squared error(MSE),mean absolute error(MAE),and determination coefficient R2 of 0.052 8,0.032 2,0.988 3,and 0.078 2,0.046 3,and 0.976 6,respectively.For pressure prediction,the accuracies of the deep learning models and random forest models were comparable,with MSE,MAE,and R2 of 4.67×10-6,3×10-4,0.999 7,and 1.07×10-5,5×10-4,and 0.999 3,respectively.Conclusions Machine learning methods show high accuracy in predicting the hemodynamic parameters of combined stenotic coronary artery aneurysm models.The predictive accuracy of the model,computational efficiency,and needs of the application scenarios need to be considered in machine learning prediction so that the appropriate model can be selected according to the specific situation.This study has clinical significance,helping doctors to more accurately evaluate a patient's condition and provide new ideas and method for the diagnosis and treatment of cardiovascular diseases.

Objective:To summarize the clinical characteristics, prognostic factors and treatment outcomes of childhood aggressive mature B-cell lymphoma after liver transplantation.Methods:This retrospective study included 18 children with newly diagnosed aggressive mature B-cell lymphoma after liver transplantation and treated from June 2018 to June 2022 in the Department of Hematology and Oncology of Shanghai Children′s Medical Center, Shanghai Jiao Tong University School of Medicine. Clinical characteristics, treatment and outcomes of patients at last evaluation were analyzed. Overall survival (OS) and event free survival (EFS) rates were calculated by Kaplan-Meier method and Log-Rank analysis was performed to find factors of poor prognosis.Results:Among all 18 patients, there were 6 males and 12 females, and the age of onset was 40 (35, 54) months. The interval from transplant to tumor diagnosis was 21 (17, 35) months and 5 patients had early onset disease (<1 year since transplant). Seventeen patients had abdominal lesions. Diarrhea, vomiting and abdominal masses were the main clinical manifestations. All patients were Epstein-Barr virus (EBV) related posttransplant lymphoproliferative disorders (PTLD). One patient received individualized therapy due to critical sick at diagnosis, and the remaining 17 patients received CP (cyclophosphamide, methylprednisolone plus rituximab) and (or) modified EPOCH (prednisone, etoposide, doxorubicin, vincristine, cyclophosphamide plus rituximab) regimens. Of all 18 patients, 15 cases got complete response, 2 cases got partial response, 1 patient died of severe infection. The 2-year OS and EFS rates of 18 patients were (94±5)% and (83±8)%, respectively. None of age, gender or early onset disease had effect on OS and EFS rates in univariate analysis (all P>0.05). Conclusions:The symptoms of PTLD were atypical. Close surveillance of EBV-DNA for patients after liver transplantation was crucial to early stage PTLD diagnosis. CP or modified EPOCH regimen was efficient for pediatric patients with aggressive mature B cell lymphoma after liver transplantation.

Objective:To evaluate the morphological characteristics of the fetal heart and the contractile function of the left and right ventricles in fetuses with pulmonary stenosis (PS) and pulmonary atresia (PA) using fetal heart quantitative analysis technology (fetal HQ), and to assess the impact of different degrees of right ventricular outflow tract obstruction (RVOTO) on the contractile function of the fetal left and right ventricles. To accumulate early data and explore parameters for constructing a predictive model and clinical decision-making tool for the progression of fetal PS and PA.Methods:A retrospective analysis was conducted on 42 cases of mild to moderate PS and 23 cases of severe PS or PA detected through fetal echocardiography in the Department of Ultrasound, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, from July 2020 to December 2021. A control group of 195 normal fetal cases matching gestational weeks was selected. The fetal HQ technique was employed to measure the global sphericity index (GSI), left ventricular ejection fraction (EF), left/right ventricular area change percentage (LVFAC, RVFAC), and left/right ventricular longitudinal strain (LVGLS, RVGLS). Additionally, 24-segment sphericity index (SI) and fractional shortening (FS) for both left and right ventricles were measured. Comparative analyses were performed between the case and control groups, as well as within the case group.Results:In comparison with the control group, the case group exhibited significantly decreased GSI, LVGLS, LVEF, LVFAC, RVGLS, and RVFAC.The differences were statistically significant in the mild to moderate PS group (all P<0.05) and highly significant in the severe PS/PA group (all P<0.01). In the mild to moderate PS group, the left ventricle′s 2nd segment, right ventricle′s 24th segment SI, and the left ventricle′s 1st-13th segments, right ventricle′s 1st-16th and 20th-24th segments FS showed statistically significant differences compared to the control group (all P<0.05). In the severe PS/PA group, the right ventricle′s 1st-22nd segment SI, and the left ventricle′s 6th-13th, 21st-24th segments, and the right ventricle′s 1st-14th segments FS were reduced, showing statistically significant differences compared to the control group (all P<0.05). The severe PS/PA group showed lower RVGLS, RVFAC, and SI for the right ventricle′s 1st to 17th segments when compared to the mild to moderate PS group, with statistically significant differences (all P<0.05). Conclusions:Quantitative indices derived by fetal HQ is capable of evaluating the cardiac morphology and function of fetuses with PS/PA, which may provide for reference information for comprehensive understanding of cardiac morphological and functional changes in such fetuses.

Objective:To explore the potential application of two-dimensional speckle tracking echocardiography (2D-STE) in terms of quantification and evaluating left atrial function in normal fetuses and fetuses with left ventricular outflow tract obstruction (LVOTO).Methods:A total of 32 fetuses diagnosed with LVOTO, who underwent fetal echocardiography at Sir Run Run Shaw Hospital, Zhejiang University College of Medicine between May 2020 to June 2022, were selected as the case group, and 100 pregnant women with normal singleton fetuses between January 2019 to October 2022 were chosen as the control group. The standard basal or apical four-chamber view clips were obtained and were quantitatively analyzed using TomTec-Arena off-line cardiac analysis software to obtain the left atrial strain parameters of the two groups of fetuses including left atrial reservoir phase longitudinal strain(LASr), left atrial ductal phase longitudinal strain(LAScd), left atrial systolic phase longitudinal strain (LASct), as well as the routine obstetric ultrasound measurements and fetal echocardiographic parameters of the two groups: biparietal diameter (BPD), femur length (FL), aortic annulus end-systolic inner diameter (AO), pulmonary annulus end-systolic inner diameter (PA), left atrial end-systolic long length (LAESL), left atrial end-systolic transverse diameter (LAESD), right atrial end-systolic long length (RAESL), right atrial end-systolic transverse diameter (RAESD), left ventricular end-diastolic transverse diameter (LVEDD) and right ventricular diastole end-diastolic transverse diameter (RVEDD). The ratio of right ventricular end-diastolic transverse diameter to left ventricular end-diastolic transverse diameter (RVd/LVd) and the ratio of pulmonary annulus diameter to aortic annulus diameter (PA/AO) were calculated. The differences of strain parameters between the two groups were compared, and the correlation between strain parameters and gestational age, RVd/LVd and other conventional measurement parameters were analyzed. ROC curve was used to compare the specificity and sensitivity of LASr and RVd/LVd in evaluating fetal cardiac dysfunction with LVOTO.Results:There were significant differences in LASr, LAScd, LASct, MAPSE, AO, LAESL, LVEDD, RVd/LVd and PA/AO between the two groups (all P<0.05), there were no significant differences in other parameters (all P>0.05). Correlation analysis showed that LASr was negatively correlated with RVd/LVd in LVOTO group ( rs=-0.394, P=0.025), and LASct was negatively correlated with RVd/LVd ( rs=-0.626, P=0.004). In the control group, LASr was negatively correlated with gestational age, AO and PA ( r/ rs=-0.570, -0.440, -0.493; all P<0.001), and LASct was negatively correlated with gestational age, AO and PA ( r/ rs=-0.601, -0.532, -0.568; all P<0.001). LAScd was positively correlated with gestational age, AO and PA ( r/ rs=0.310, 0.370, 0.314; all P<0.05). There were no significant correlations between the other parameters (all P>0.05). ROC curve analysis showed that the area under the curve(AUC) in LASr evaluation of fetal cardiac dysfunction with LVOTO was 0.890 (0.826, 0.953) and the AUC in RVd/LVd evaluation of fetal cardiac dysfunction with LVOTO was 0.742 (0.637, 0.846), there were significant differences between them( P<0.05). Conclusions:2D-STE is highly feasible and reproducible in assessing fetal left atrial function. Evaluation of fetal left atrial function by 2D-STE provides a new reference index for quantitative analysis of fetal cardiac dysfunction.

OBJECTIVE To explore the color and odor changes of Salvia miltiorrhiza Bge.slices from different origins,and com-bine modern machine learning technology to achieve rapid differentiation of origins.METHODS Intelligent sensory technology was used to quantify the color and represent the odor of Salvia miltiorrhiza Bge.slices from different geographical origins.Various data a-nalysis methods including principal component analysis(PCA),discriminant analysis,discriminant factor analysis(DFA),component heat maps,correlation analysis,machine learning and so on,were employed to establish a discrimination function for distinguishing the origin of Salvia miltiorrhiza Bge.slices based on color data.RESULTS Classification and screening of odor information led to the i-dentification of 10 differential markers:ethanol,carbon disulfide,cyclopentane,3-methylfuran,propylene glycol,nonane,phenol,1,5-octadienone,1,8-cineole,and sotolon.It was also found that there was a significant correlation between the color and odor of the slices.Furthermore,based on the concept of data fusion,the study established classification models such as subspace clustering,and compared to single-color discriminant analysis,the classification accuracy was improved to 94.4%.CONCLUSION The feasibility and superiority of intelligent sensory technology in classifying the geographical origin of TCM is confirmed,providing new methods and insights for quality control of Salvia miltiorrhiza Bge.slices.

OBJECTIVE To explore the color and odor changes of Salvia miltiorrhiza Bge.slices from different origins,and com-bine modern machine learning technology to achieve rapid differentiation of origins.METHODS Intelligent sensory technology was used to quantify the color and represent the odor of Salvia miltiorrhiza Bge.slices from different geographical origins.Various data a-nalysis methods including principal component analysis(PCA),discriminant analysis,discriminant factor analysis(DFA),component heat maps,correlation analysis,machine learning and so on,were employed to establish a discrimination function for distinguishing the origin of Salvia miltiorrhiza Bge.slices based on color data.RESULTS Classification and screening of odor information led to the i-dentification of 10 differential markers:ethanol,carbon disulfide,cyclopentane,3-methylfuran,propylene glycol,nonane,phenol,1,5-octadienone,1,8-cineole,and sotolon.It was also found that there was a significant correlation between the color and odor of the slices.Furthermore,based on the concept of data fusion,the study established classification models such as subspace clustering,and compared to single-color discriminant analysis,the classification accuracy was improved to 94.4%.CONCLUSION The feasibility and superiority of intelligent sensory technology in classifying the geographical origin of TCM is confirmed,providing new methods and insights for quality control of Salvia miltiorrhiza Bge.slices.

Malignant tumors are diseases that seriously threaten human health and social development. Traditional tumor therapies such as surgery, radiotherapy, chemotherapy and targeted therapy cannot fully meet the needs of clinical treatment, and emerging immunotherapy has become a research hotspot in the field of tumor treatment. Immune checkpoint inhibitors (ICIs) have been approved as a tumor immunotherapy method for the treatment of various tumors, such as lung cancer, liver cancer, stomach cancer and colorectal cancer, etc. However, during the clinical use of ICIs, only a small number of patients experienced durable responses, which also led to drug resistance and adverse reactions. Therefore, the identification and development of predictive biomarkers is crucial to improve the therapeutic efficacy of ICIs. The predictive biomarkers of tumor ICIs mainly include tumor biomarkers, tumor microenvironment biomarkers, circulation-related biomarkers, host environmental biomarkers and combinatorial biomarkers. They are of great significance for screening, individualized treatment and prognosis evaluation of tumor patients. This article reviews the advances of predictive markers for tumor ICIs therapy.
Humans ; Immune Checkpoint Inhibitors/therapeutic use* ; Lung Neoplasms ; Biomarkers ; Immunotherapy/methods* ; Biomarkers, Tumor/genetics* ; Prognosis ; Tumor Microenvironment