Objective To develop models for predicting response to chemotherapy combined with immunotherapy in patients with esophageal squamous carcinoma with various machine learning algorithms,and then select the optimal model.Methods A retrospective study was performed for 174 patients with esophageal squamous cell carcinoma undergoing chemotherapy combined with immunotherapy admitted in Department of Thoracic Surgery of the First Affiliated Hospital of Army Medical University from January 2022 to December 2023.The CT scans and clinical information were collected before treatment.They were randomly divided into a training set(n=122)and a testing set(n=52)in a ratio of 7∶3.CT radiomic features were extracted and selected,and then 5 machine-learning algorithms were employed to establish the prediction models,including radiomics model and clinical-radiomics model.Five-fold cross-validation was conducted on the training set,and the performance of the prediction models was evaluated on the testing set using receiver operating characteristic(ROC)curve and the F1 score.The best-performing model was further explained using local interpretable model-agnostic explanations(LIME)algorithm.Results Among the 174 patients,115(66.1%)achieved clinical remission.From the clinical information and CT images,1 clinical features and 10 radiomic features were identified.The area under of ROC curve(AUC)for the radiomics and clinical-radiomics models was 0.750(95%CI:0.616～0.883),and 0.766(95%CI:0.637～0.895),respectively.The F1 score of the optimal clinical-radiomics model was 0.829.LIME algorithm indicated that this best model demonstrated reliability in predicting individual samples.Conclusion The clinical-radiomics prediction model based on machine learning algorithm performs well,and can provide a reference for doctors'clinical decision-making by predicting the response to chemotherapy combined with immunotherapy in patients with esophageal squamous cell carcinoma.

There exist risks of ionizing radiation in radiodiagnosis examinations. Implementing shielding protection following the optimization and as low as reasonably achievable (ALARA) principles represents a measure to reduce radiation doses to patients. The implementation of shielding protection in clinical practices should meet high requirements due to variations in the modalities and items in radiodiagnosis examinations, the characteristics and irradiation method of X-ray beams, the method of automatic selection of image quality and radiation dose-related parameters by imaging equipment, the radiation sensitivity of human tissues and organs. This review introduced the shielding products, methods and effects in various radiodiagnosis examinations, as well as the current status and challenges in their applications, aiming to provide a reference for future related research and clinical practices.

Objective:To investigate the diagnostic value of different conventional ultrasound-based radiomics models and their combination with clinical ultrasound features in the pathological subtyping of renal cell carcinoma.Methods:Retrospective data from 286 patients diagnosed with renal cell carcinoma by pathology at the Tenth Affiliated Hospital of Southern Medical University between May 1，2017 and June 7，2024 were collected. Among the 286 patients，203 were clear cell carcinoma，44 were papillary renal cell carcinoma，and 39 were chromophobe renal cell carcinoma. The patients were randomly divided into a training group（201 cases）and a validation group（85 cases）in a ratio of 7 to 3. Regions of interest（ROI）were delineated on conventional ultrasound images，and the radiomics features were extracted. Feature selection was performed using Student's t-test，Pearson correlation，and the least absolute shrinkage and selection operator（LASSO）. Six different machine learning methods included category gradient boosting（CatBoost），light gradient boosting machine（LightGBM），Logistic regression（LR），random forest（RF），support vector machine（SVM）and extreme gradient boosting（XGBoost）were used to establish radiomics models. Weight balancing was applied to correct for sample imbalance，and an imaging genomics model was constructed after balancing the samples. Independent predictors of renal cell carcinoma subtyping were selected from clinical ultrasound features using univariate and multivariate logistic regression analyses，and a clinical imaging model was constructed. The best-performing radiomics model was combined with the clinical independent predictors to construct a combined model. Receiver operating characteristic curves and the obuchowski index were plotted to evaluate model performance. Results:Among the radiomics models，the model constructed using Random Forest（RS RF）after balancing the samples exhibited the best predictive performance，with area under the curve（AUCs）of 0.918（micro-average ROC）and 0.903（macro-average ROC），and the obuchowski index was 0.885 in the validation group. The long and short axes of ultrasound image tumor masses were used as imaging independent predictors to construct a clinical imaging model. In the validation group，the AUCs of the clinical model were 0.886（micro-average ROC）and 0.606（macro-average ROC），and the obuchowski index was 0.569. The combined model achieved AUCs of 0.888（micro-average ROC）and 0.967（macro-average ROC），with an obuchowski index of 0.933，outperforming any single model. Conclusions:The combination of conventional ultrasound-based radiomics models with clinical ultrasound features demonstrates high diagnostic value in differentiating clear cell carcinoma，papillary renal cell carcinoma，and chromophobe renal cell carcinoma. It may serve as an auxiliary tool for providing timely and effective clinical guidance.

Objective:To investigate the dynamic cerebral oxygen metabolism characteristics in drug-naive patients with primary insomnia (PI), and analyze the association between the cerebral oxygen metabolism and insomnia symptoms.Methods:A total of 31 drug-naive patients with PI and 36 healthy controls were recruited from July 2024 to February 2025. Insomnia symptoms were assessed by the Pittsburgh sleep quality index (PSQI). Functional near infrared spectroscopy (fNIRS) technique was employed to collect 180 s resting-state oxygenated hemoglobin concentration changes from dorsolateral prefrontal cortex (DLPFC), medial prefrontal cortex, temporal lobe (TL), parietal lobe (PL) and occipital lobe. Sliding time window analysis and K-means clustering algorithm were applied to cluster the oxygenation data into K temporal categories. Statistical analysis, including t-test, Wilcoxon rank-sum test, chi-square test, Pearson/Spearman correlation analysis, and multiple linear regression were performed using SPSS 26.0 software. Results:Clustering analysis revealed 4 characteristic temporal categories (K=4) during the 180 s resting-state. Compared to healthy controls, drug-naive PI patients exhibited higher oxygenation levels in bilateral TLs during the second temporal category(left TL(18.19±6.18)mmol/dL, (16.82±4.47)mmol/dL; right TL(18.20±8.97)mmol/dL, (16.17±5.64)mmol/dL), but lower levels during the third temporal category(left TL(16.54± 5.09)mmol/dL, (17.98±5.34)mmol/dL; right TL(15.82±7.29)mmol/dL, (17.84±5.94)mmol/dL), and exhibited lower oxygenation level in right PL during the second category((16.16±6.56)mmol/dL, (17.60±5.84)mmol/dL) (all P<0.05). Oxygenation levels in the right DLPFC during the first temporal category ( β=0.44, t=2.52, P=0.018), in the left DLPFC during the second temporal category( β=-0.47, t=-2.82, P=0.009), and in the right PL during the second temporal category( β=-0.46, t=-2.78, P=0.010) were influencing factors for the PSQI score. Conclusions:The bilateral TLs and right PL in drug-naive PI patients exhibit phase-specific abnormalities in oxygen metabolism, potentially attributable to the insomnia-induced dysregulation of endogenous neural oscillations. The oxygen concentration changes in bilateral DLPFCs and right TL are associated with insomnia symptoms.

Objective:To investigate the dynamic cerebral oxygen metabolism characteristics in drug-naive patients with primary insomnia (PI), and analyze the association between the cerebral oxygen metabolism and insomnia symptoms.Methods:A total of 31 drug-naive patients with PI and 36 healthy controls were recruited from July 2024 to February 2025. Insomnia symptoms were assessed by the Pittsburgh sleep quality index (PSQI). Functional near infrared spectroscopy (fNIRS) technique was employed to collect 180 s resting-state oxygenated hemoglobin concentration changes from dorsolateral prefrontal cortex (DLPFC), medial prefrontal cortex, temporal lobe (TL), parietal lobe (PL) and occipital lobe. Sliding time window analysis and K-means clustering algorithm were applied to cluster the oxygenation data into K temporal categories. Statistical analysis, including t-test, Wilcoxon rank-sum test, chi-square test, Pearson/Spearman correlation analysis, and multiple linear regression were performed using SPSS 26.0 software. Results:Clustering analysis revealed 4 characteristic temporal categories (K=4) during the 180 s resting-state. Compared to healthy controls, drug-naive PI patients exhibited higher oxygenation levels in bilateral TLs during the second temporal category(left TL(18.19±6.18)mmol/dL, (16.82±4.47)mmol/dL; right TL(18.20±8.97)mmol/dL, (16.17±5.64)mmol/dL), but lower levels during the third temporal category(left TL(16.54± 5.09)mmol/dL, (17.98±5.34)mmol/dL; right TL(15.82±7.29)mmol/dL, (17.84±5.94)mmol/dL), and exhibited lower oxygenation level in right PL during the second category((16.16±6.56)mmol/dL, (17.60±5.84)mmol/dL) (all P<0.05). Oxygenation levels in the right DLPFC during the first temporal category ( β=0.44, t=2.52, P=0.018), in the left DLPFC during the second temporal category( β=-0.47, t=-2.82, P=0.009), and in the right PL during the second temporal category( β=-0.46, t=-2.78, P=0.010) were influencing factors for the PSQI score. Conclusions:The bilateral TLs and right PL in drug-naive PI patients exhibit phase-specific abnormalities in oxygen metabolism, potentially attributable to the insomnia-induced dysregulation of endogenous neural oscillations. The oxygen concentration changes in bilateral DLPFCs and right TL are associated with insomnia symptoms.

There exist risks of ionizing radiation in radiodiagnosis examinations. Implementing shielding protection following the optimization and as low as reasonably achievable (ALARA) principles represents a measure to reduce radiation doses to patients. The implementation of shielding protection in clinical practices should meet high requirements due to variations in the modalities and items in radiodiagnosis examinations, the characteristics and irradiation method of X-ray beams, the method of automatic selection of image quality and radiation dose-related parameters by imaging equipment, the radiation sensitivity of human tissues and organs. This review introduced the shielding products, methods and effects in various radiodiagnosis examinations, as well as the current status and challenges in their applications, aiming to provide a reference for future related research and clinical practices.

Objective:To investigate the diagnostic value of different conventional ultrasound-based radiomics models and their combination with clinical ultrasound features in the pathological subtyping of renal cell carcinoma.Methods:Retrospective data from 286 patients diagnosed with renal cell carcinoma by pathology at the Tenth Affiliated Hospital of Southern Medical University between May 1，2017 and June 7，2024 were collected. Among the 286 patients，203 were clear cell carcinoma，44 were papillary renal cell carcinoma，and 39 were chromophobe renal cell carcinoma. The patients were randomly divided into a training group（201 cases）and a validation group（85 cases）in a ratio of 7 to 3. Regions of interest（ROI）were delineated on conventional ultrasound images，and the radiomics features were extracted. Feature selection was performed using Student's t-test，Pearson correlation，and the least absolute shrinkage and selection operator（LASSO）. Six different machine learning methods included category gradient boosting（CatBoost），light gradient boosting machine（LightGBM），Logistic regression（LR），random forest（RF），support vector machine（SVM）and extreme gradient boosting（XGBoost）were used to establish radiomics models. Weight balancing was applied to correct for sample imbalance，and an imaging genomics model was constructed after balancing the samples. Independent predictors of renal cell carcinoma subtyping were selected from clinical ultrasound features using univariate and multivariate logistic regression analyses，and a clinical imaging model was constructed. The best-performing radiomics model was combined with the clinical independent predictors to construct a combined model. Receiver operating characteristic curves and the obuchowski index were plotted to evaluate model performance. Results:Among the radiomics models，the model constructed using Random Forest（RS RF）after balancing the samples exhibited the best predictive performance，with area under the curve（AUCs）of 0.918（micro-average ROC）and 0.903（macro-average ROC），and the obuchowski index was 0.885 in the validation group. The long and short axes of ultrasound image tumor masses were used as imaging independent predictors to construct a clinical imaging model. In the validation group，the AUCs of the clinical model were 0.886（micro-average ROC）and 0.606（macro-average ROC），and the obuchowski index was 0.569. The combined model achieved AUCs of 0.888（micro-average ROC）and 0.967（macro-average ROC），with an obuchowski index of 0.933，outperforming any single model. Conclusions:The combination of conventional ultrasound-based radiomics models with clinical ultrasound features demonstrates high diagnostic value in differentiating clear cell carcinoma，papillary renal cell carcinoma，and chromophobe renal cell carcinoma. It may serve as an auxiliary tool for providing timely and effective clinical guidance.

Objective:To analyze the evaluation of the application effect and deficiency of nurses acting as standardized parents in the graduation examination of standardized residency training of pediatrics and further improve and promote the level of standardized parents.Methods:A questionnaire survey was used to collect the scores of nurse standardized parents by students and examiners who took part in the graduation examination of standardized residency training of pediatrics in 2021. And the self-evaluation scores of standardized parents were collected. Counting data were represented by the number of cases and composition ratio. A Chi-square test was used to compare the rates.Results:A total of 125 questionnaires from students and 37 questionnaires from nurse standardized parents were collected, and the overall satisfaction (very satisfied + satisfied) of standardized parents reached 121 (96.80%). In the three dimensions of simulation ability, compliance with question-and-answer rules, and simulated attitude, students believed that the consistency between standardized parents and actual parents in simulated altitude was lower than that in the simulation ability and compliance with question-and-answer rules ( P=0.007, P=0.001). The overall satisfaction of standardized parents (very satisfied + satisfied) reached 87.38% (388/444). There were 26 (70.27%) nurse standardized parents who had the lowest satisfaction with their own performance ability, followed by 28 (75.68%) cases of imitation ability and 30 (81.08%) cases of adaptability. Conclusions:It is feasible to adopt nurse standardized parents in the assessment of standardized residency training of pediatrics, and both students and examiners have higher satisfaction. The next step is to improve the training of nurses standardized parents in the attitude of simulation and, at the same time, enhance the training of imitation ability and adaptability, so as to further expand the construction of standardized parents.

Objective:To explore influencing factors of the self-reported brief life quality satisfaction score(Brief-QoL) in patients with acromegaly and understand the persistent low Brief-QoL scores in cases achieving biochemical remission.Methods:This study included 836 acromegaly patients who were hospitalized at Peking Union Medical College Hospital between January 2012 and December 2020. We retrospectively examined how clinical characteristics, biochemical parameters, comorbidities, and symptoms influenced Brief-QoL. Among patients who achieved biochemical remission, differences in clinical symptoms and comorbidities were analyzed between the high and low quality of life groups.Results:Patients with well-controlled biochemical indicators at the last follow-up had generally high Brief-QoL. However, patients with symptoms such as headaches (47.8% in the low-score group vs 14.9% in the high-score group, P<0.001) and joint pain (69.6% in the low-score group vs 19.0% in the high-score group, P<0.001) had low Brief-QoL despite biochemical remission. Receiving combined treatment(52.4% in the low-score group vs 27.5% in the high-score group, P=0.030) and having comorbid diabetes or hyperlipidemia were significant factors leading to decreased quality of life. Conclusion:Brief-QoL is suitable for follow-up of outpatient patients. Early identification of factors affecting quality of life and timely intervention can facilitate the realization of standardized management.

Humans ; Uric Acid ; Cross-Sectional Studies ; Spondylarthritis/diagnostic imaging* ; C-Reactive Protein ; Spondylitis, Ankylosing