Immune inflammatory response runs through the whole pathological process of liver injury， but its specific regulatory mechanism remains unclear. Recent studies have shown that the Notch signaling pathway plays an important role in liver injury by regulating macrophage polarization， activating neutrophil recruitment， and modulating the differentiation of regulatory immune cells. This article systematically reviews the molecular mechanisms of the Notch signaling pathway in mediating immune inflammatory response in liver injury， in order to provide new perspectives for clarifying the molecular mechanism of immune inflammatory damage in liver diseases， as well as a new reference for future research directions.

Objective:To explore the feasibility of selecting appropriate respiratory motion management strategies for patients undergoing stereotactic radiotherapy for liver cancer using chi-square feature testing and machine learning techniques.Methods:A retrospective analysis was conducted on 95 liver cancer patients who underwent respiratory motion evaluation at Xiangya Hospital of Central South University between March 2022 and August 2024. Chi-square testing was used to screen features related to respiratory motion evaluation in liver cancer patients. Based on these features, predictive models were constructed using 4 machine learning classification algorithms: support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), and adaptive boosting (AdaBoost). The predictive performance of these models was evaluated using accuracy, sensitivity, specificity, F1 value, and area under the curve (AUC).Results:The accuracy values for the SVM, RF, GBDT and AdaBoost models were 0.75, 0.75, 0.70, and 0.82, respectively. The sensitivity values were 0.82, 0.82, 0.64, and 0.82, respectively. The specificity values were 0.63, 0.63, 0.63, and 0.75, respectively. The F1 scores were 0.78, 0.78, 0.67, and 0.82, respectively. The AUC values were 0.85, 0.80, 0.76, and 0.85, respectively.Conclusions:The predictive models constructed by combining chi-square feature testing and machine learning methods can effectively predict the selection of respiratory motion management strategies. Among the models, the AdaBoost model demonstrated the best predictive performance for selecting respiratory motion management strategies.

Objective:To explore the clinical application value of MRI ultra-short echo time sequence (MRI-UTE) in the diagnosis of pulmonary nodules.Methods:This study was a cross-sectional study. A total of 101 consecutive patients were recruited prospectively from January to August 2024 at Huazhong Fuwai Hospital of Zhengzhou University. All of the included patients were diagnosed with pulmonary nodules by chest CT examination and intended for treatment. All patients underwent low-dose CT examination and MRI-UTE examination. The number, classification, and lung imaging reporting and data system (lung-RADS) grading of the pulmonary nodules were analyzed. Nodules classification was determined as solid nodules or sub-solid nodules, and sub-solid nodules included part-solid nodules and pure ground-glass nodules. Taking the evaluation results of radiologists with 10 and 12 years of experience in chest imaging diagnosis as the reference standard, the Kappa test was used to analyze the agreement of CT and MRI-UTE in terms of the accurate diagnosis, classification, and lung-RADS grading of pulmonary nodules. Results:Among the 101 patients, a total of 216 pulmonary nodules were identified. MRI-UTE accurately diagnosed 180 pulmonary nodules, while 203 pulmonary nodules were detected by CT. The concordance was moderate ( Kappa=0.48, P<0.001). In terms of nodule classification, CT correctly classified 167 nodules as solid and 36 as sub-solid, whereas MRI-UTE correctly classified 153 as solid and 23 as sub-solid, with good agreement (weighted Kappa=0.73, P<0.001). For lung-RADS grading, CT correctly graded 186 nodules, with 85 graded as category 2, 46 as category 3, 33 as category 4A, 12 as category 4B, and 10 as category 4X; MRI-UTE correctly graded 155 nodules, with 74 graded as category 2, 30 as category 3, 30 as category 4A, 12 as category 4B, and 9 as category 4X. The agreement between the two modalities in determining lung-RADS grade was also good (weighted Kappa=0.74, P<0.001). Conclusion:MRI-UTE demonstrates good agreement with CT in the accurate diagnosis, classification, and lung-RADS grading of pulmonary nodules, indicating certain clinical application value.

Objective:To investigate the prevalence and influencing factors of frailty among older adults diagnosed with non-ST-segment elevation acute coronary syndrome(NSTE-ACS).Methods:We conducted a cross-sectional study involving patients aged 65 years and older with NSTE-ACS, who were admitted to the Cardiology Center and the Department of Geriatrics at Beijing Friendship Hospital, Capital Medical University, between January 2020 and November 2021.Patients were categorized into non-frail, pre-frail, and frail groups based on the FRAIL scale.We collected clinical data, including general health conditions, comorbidities, laboratory results, treatments, and comprehensive geriatric assessments.Logistic regression analysis was employed to identify the influencing factors associated with frailty and pre-frailty in older adults with NSTE-ACS.Results:A total of 528 patients with NSTE-ACS were included in the study, comprising 308 males(58.3%)and 220 females(41.7%). The age range of participants was from 65 to 90 years, with a median age of 72(68, 76)years.The prevalence of frailty among older adults with NSTE-ACS was 11.4%(60/528), while pre-frailty was observed in 51.9%(274/528), and non-frailty in 36.7%(194/528). Compared to the non-frail and pre-frail groups, patients in the frail group were older, had a higher proportion of females, exhibited a greater prevalence of chronic diseases, and presented with elevated inflammatory markers.Additionally, frail patients demonstrated poorer nutritional status and reduced functional ability(all P<0.005). Risk factors for frailty in older adults with NSTE-ACS included older age( OR=1.110, 95% CI: 1.032-1.194, P=0.005), diabetes( OR=2.489, 95% CI: 1.091-5.679, P=0.030), cerebrovascular disease ( OR=4.151, 95% CI: 1.660-10.384, P=0.002), chronic kidney disease ( OR=42.874, 95% CI: 3.957-464.513, P=0.002), and elevated white blood cell levels( OR=1.424, 95% CI: 1.125-1.802, P=0.003). Conversely, being male( OR=0.252, 95% CI: 0.105-0.604, P=0.002)was identified as a protective factor against frailty in this patient population.For pre-frail older adults with NSTE-ACS, identified risk factors included diabetes( OR=1.882, 95% CI: 1.199-2.955, P=0.006), cerebrovascular disease( OR=1.938, 95% CI: 1.176-3.195, P=0.009), and chronic kidney disease ( OR=12.137, 95% CI: 1.536-95.934, P=0.018). Similarly, being male( OR=0.601, 95% CI: 0.376-0.961, P=0.033)was also a protective factor for pre-frailty in older adults with NSTE-ACS. Conclusions:The prevalence of frailty and pre-frailty among older adults with NSTE-ACS is notably high.Common risk factors for frailty and pre-frailty in this population include female gender, diabetes, cerebrovascular disease, and chronic kidney disease.

Purpose To investigate the diagnostic value of quantitative 123I-Metaiodobenzylguanidine(MIBG)xSPECT/CT imaging in bone metastases of neuroblastoma in children.Materials and Methods We retrospectively assessed 123I-MIBG xSPECT/CT images of 61 children with neuroblastoma confirmed by pathology analyzed the influencing factors of bone metastatic lesions and normal bone quantitative parameters from March 2022 to March 2023 in Beijing Friendship Hospital,Capital Medical University,and compared the differences in standard uptake value(SUV).We used receiver operating characteristics curves to determine the optimum maximum standard uptake value(SUVmax),average standard uptake value(SUVavg),minimum standard uptake value(SUVmin)and peak standard uptake value(SUVpeak)cut-off value to diagnose bone metastatic lesions.Results There was no statistically significant difference in normal bone SUV values among different physical parameters(r=-0.204-0.071,all P>0.05).SUVmax,SUVavg,SUVmin and SUVpeak of bone metastatic lesions were significantly higher than those of normal bone(Z=-10.118--9.703,all P<0.000 1),and there was no significant statistical difference in SUV measurements of bone metastatic lesions among different Curie score intervals(H=0.226,0.107,0.149,0.342,all P>0.05).The area under the curve of SUVmax,SUVavg,SUVmin and SUVpeak were 0.929(95%CI 0.884-0.974),0.948(95%CI 0.906-0.989),0.935(95%CI 0.890-0.981),0.942(95%CI 0.899-0.985);sensitivity was 90.9%,90.2%,93.7%,92.3%,and specificity was 86.9%,93.4%,85.2%,88.5%,respectively,with statistically significant differences(P<0.000 1).The optimal diagnostic thresholds for SUVmax,SUVavg,SUVmin and SUVpeak were 0.39 g/ml,0.33 g/ml,0.20 g/ml and 0.33 g/ml,respectively.Conclusion We demonstrate that SUVavg above 0.33 g/ml in neuroblastoma patients have best diagnostic efficacy in the diagnosis of bone metastasis of neuroblastoma.Quantitative indexes of xSPECT/CT increase the specificity of diagnosing bone metastases of neuroblastoma,demonstrating the high diagnostic efficiency of 123I-MIBG xSPECT/CT imaging quantitative analysis and its potential usefulness as a diagnostic aid for visual evaluation.

Objective:To investigate the prevalence and influencing factors of frailty among older adults diagnosed with non-ST-segment elevation acute coronary syndrome(NSTE-ACS).Methods:We conducted a cross-sectional study involving patients aged 65 years and older with NSTE-ACS, who were admitted to the Cardiology Center and the Department of Geriatrics at Beijing Friendship Hospital, Capital Medical University, between January 2020 and November 2021.Patients were categorized into non-frail, pre-frail, and frail groups based on the FRAIL scale.We collected clinical data, including general health conditions, comorbidities, laboratory results, treatments, and comprehensive geriatric assessments.Logistic regression analysis was employed to identify the influencing factors associated with frailty and pre-frailty in older adults with NSTE-ACS.Results:A total of 528 patients with NSTE-ACS were included in the study, comprising 308 males(58.3%)and 220 females(41.7%). The age range of participants was from 65 to 90 years, with a median age of 72(68, 76)years.The prevalence of frailty among older adults with NSTE-ACS was 11.4%(60/528), while pre-frailty was observed in 51.9%(274/528), and non-frailty in 36.7%(194/528). Compared to the non-frail and pre-frail groups, patients in the frail group were older, had a higher proportion of females, exhibited a greater prevalence of chronic diseases, and presented with elevated inflammatory markers.Additionally, frail patients demonstrated poorer nutritional status and reduced functional ability(all P<0.005). Risk factors for frailty in older adults with NSTE-ACS included older age( OR=1.110, 95% CI: 1.032-1.194, P=0.005), diabetes( OR=2.489, 95% CI: 1.091-5.679, P=0.030), cerebrovascular disease ( OR=4.151, 95% CI: 1.660-10.384, P=0.002), chronic kidney disease ( OR=42.874, 95% CI: 3.957-464.513, P=0.002), and elevated white blood cell levels( OR=1.424, 95% CI: 1.125-1.802, P=0.003). Conversely, being male( OR=0.252, 95% CI: 0.105-0.604, P=0.002)was identified as a protective factor against frailty in this patient population.For pre-frail older adults with NSTE-ACS, identified risk factors included diabetes( OR=1.882, 95% CI: 1.199-2.955, P=0.006), cerebrovascular disease( OR=1.938, 95% CI: 1.176-3.195, P=0.009), and chronic kidney disease ( OR=12.137, 95% CI: 1.536-95.934, P=0.018). Similarly, being male( OR=0.601, 95% CI: 0.376-0.961, P=0.033)was also a protective factor for pre-frailty in older adults with NSTE-ACS. Conclusions:The prevalence of frailty and pre-frailty among older adults with NSTE-ACS is notably high.Common risk factors for frailty and pre-frailty in this population include female gender, diabetes, cerebrovascular disease, and chronic kidney disease.

Purpose To investigate the diagnostic value of quantitative 123I-Metaiodobenzylguanidine(MIBG)xSPECT/CT imaging in bone metastases of neuroblastoma in children.Materials and Methods We retrospectively assessed 123I-MIBG xSPECT/CT images of 61 children with neuroblastoma confirmed by pathology analyzed the influencing factors of bone metastatic lesions and normal bone quantitative parameters from March 2022 to March 2023 in Beijing Friendship Hospital,Capital Medical University,and compared the differences in standard uptake value(SUV).We used receiver operating characteristics curves to determine the optimum maximum standard uptake value(SUVmax),average standard uptake value(SUVavg),minimum standard uptake value(SUVmin)and peak standard uptake value(SUVpeak)cut-off value to diagnose bone metastatic lesions.Results There was no statistically significant difference in normal bone SUV values among different physical parameters(r=-0.204-0.071,all P>0.05).SUVmax,SUVavg,SUVmin and SUVpeak of bone metastatic lesions were significantly higher than those of normal bone(Z=-10.118--9.703,all P<0.000 1),and there was no significant statistical difference in SUV measurements of bone metastatic lesions among different Curie score intervals(H=0.226,0.107,0.149,0.342,all P>0.05).The area under the curve of SUVmax,SUVavg,SUVmin and SUVpeak were 0.929(95%CI 0.884-0.974),0.948(95%CI 0.906-0.989),0.935(95%CI 0.890-0.981),0.942(95%CI 0.899-0.985);sensitivity was 90.9%,90.2%,93.7%,92.3%,and specificity was 86.9%,93.4%,85.2%,88.5%,respectively,with statistically significant differences(P<0.000 1).The optimal diagnostic thresholds for SUVmax,SUVavg,SUVmin and SUVpeak were 0.39 g/ml,0.33 g/ml,0.20 g/ml and 0.33 g/ml,respectively.Conclusion We demonstrate that SUVavg above 0.33 g/ml in neuroblastoma patients have best diagnostic efficacy in the diagnosis of bone metastasis of neuroblastoma.Quantitative indexes of xSPECT/CT increase the specificity of diagnosing bone metastases of neuroblastoma,demonstrating the high diagnostic efficiency of 123I-MIBG xSPECT/CT imaging quantitative analysis and its potential usefulness as a diagnostic aid for visual evaluation.

Objective:To explore the clinical application value of MRI ultra-short echo time sequence (MRI-UTE) in the diagnosis of pulmonary nodules.Methods:This study was a cross-sectional study. A total of 101 consecutive patients were recruited prospectively from January to August 2024 at Huazhong Fuwai Hospital of Zhengzhou University. All of the included patients were diagnosed with pulmonary nodules by chest CT examination and intended for treatment. All patients underwent low-dose CT examination and MRI-UTE examination. The number, classification, and lung imaging reporting and data system (lung-RADS) grading of the pulmonary nodules were analyzed. Nodules classification was determined as solid nodules or sub-solid nodules, and sub-solid nodules included part-solid nodules and pure ground-glass nodules. Taking the evaluation results of radiologists with 10 and 12 years of experience in chest imaging diagnosis as the reference standard, the Kappa test was used to analyze the agreement of CT and MRI-UTE in terms of the accurate diagnosis, classification, and lung-RADS grading of pulmonary nodules. Results:Among the 101 patients, a total of 216 pulmonary nodules were identified. MRI-UTE accurately diagnosed 180 pulmonary nodules, while 203 pulmonary nodules were detected by CT. The concordance was moderate ( Kappa=0.48, P<0.001). In terms of nodule classification, CT correctly classified 167 nodules as solid and 36 as sub-solid, whereas MRI-UTE correctly classified 153 as solid and 23 as sub-solid, with good agreement (weighted Kappa=0.73, P<0.001). For lung-RADS grading, CT correctly graded 186 nodules, with 85 graded as category 2, 46 as category 3, 33 as category 4A, 12 as category 4B, and 10 as category 4X; MRI-UTE correctly graded 155 nodules, with 74 graded as category 2, 30 as category 3, 30 as category 4A, 12 as category 4B, and 9 as category 4X. The agreement between the two modalities in determining lung-RADS grade was also good (weighted Kappa=0.74, P<0.001). Conclusion:MRI-UTE demonstrates good agreement with CT in the accurate diagnosis, classification, and lung-RADS grading of pulmonary nodules, indicating certain clinical application value.

Objective:To explore the feasibility of selecting appropriate respiratory motion management strategies for patients undergoing stereotactic radiotherapy for liver cancer using chi-square feature testing and machine learning techniques.Methods:A retrospective analysis was conducted on 95 liver cancer patients who underwent respiratory motion evaluation at Xiangya Hospital of Central South University between March 2022 and August 2024. Chi-square testing was used to screen features related to respiratory motion evaluation in liver cancer patients. Based on these features, predictive models were constructed using 4 machine learning classification algorithms: support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), and adaptive boosting (AdaBoost). The predictive performance of these models was evaluated using accuracy, sensitivity, specificity, F1 value, and area under the curve (AUC).Results:The accuracy values for the SVM, RF, GBDT and AdaBoost models were 0.75, 0.75, 0.70, and 0.82, respectively. The sensitivity values were 0.82, 0.82, 0.64, and 0.82, respectively. The specificity values were 0.63, 0.63, 0.63, and 0.75, respectively. The F1 scores were 0.78, 0.78, 0.67, and 0.82, respectively. The AUC values were 0.85, 0.80, 0.76, and 0.85, respectively.Conclusions:The predictive models constructed by combining chi-square feature testing and machine learning methods can effectively predict the selection of respiratory motion management strategies. Among the models, the AdaBoost model demonstrated the best predictive performance for selecting respiratory motion management strategies.

During the treatment of non-small cell lung cancer ( NSCLC) , many patients have developed drug resistance due to the use of targeted EGFR inhibitors. The main reasons for drug resistance are EGFR site mutations and bypass activation. Activation of ALK pathway is one of the major types of bypass activation. A recent authoritative study indicates that ALK is closely related to immunotherapy. This article reviews the treatment of ALK in tumors from three aspects: the structure and physiological function of ALK, the small molecule inhibitor of ALK, the biological function of ALK and its related treatment methods for NSCLC, and prospects future directions for better application of ALK in the treatment of NSCLC.