Objective We investigated the clinical features and the potential risk factors of malnutrition in patients with chronic heart failure(CHF),and constructed the risk prediction model of malnutrition.Methods A total of459 CHF patients admitted between January 2023 and July 2024 were classified into a normal nutrition group and a malnutrition group based on the geriatric Nutrition Risk Index(GNRI)score upon admission.The patient-related data were gathered,and single-variable and multi-variable logistic analyses were first carried out to identify the risk factors associated with the malnutrition risk.Subsequently,the stepwise regression approach was employed to define the inclusion criteria and construct a malnutrition nomogram model for CHF patients.The diagnostic efficacy and calibration of this model were appraised using the ROC curve and calibration curve,and its clinical utility was assessed via the clinical decision curve.A P value less than 0.05 signified statistically significant differences.Results Anxiety(OR=1.1902,95%CI:1.0217～1.3865),urea nitrogen(OR=1.4842,95%CI:1.1187～1.9691),low body weight(OR=0.8463,95%CI:0.7852～0.9121),and low albumin(OR=0.0467,95%CI:0.0172～0.1268)were risk factors for malnutrition.The optimal model inclusion factors were selected by stepwise regression,including:Body weight,7 items of Generalized Anxiety Disorder Scale(GAD-7),urea nitrogen,uric acid,albumin,total cholesterol,high density lipoprotein cholesterol(HDL-L),low density lipoprotein cholesterol(LDL-L),D-dimer.The area under the ROC curve(AUC)of the column chart model based on the above factors is 0.996(95%CI:0.971～0.978),with a sensitivity of 97.8%and a specificity of 97.1%.The C-index validated internally in the calibration curve was 0.824.The calibration chart and validation results demonstrate good consis-tency and applicability.Conclusion The column chart prediction model created in this study based on nine factors including body weight,GAD-7,urea nitrogen,uric acid,albumin,total cholesterol,HDL-L,LDL-L,and D-dimer had good calibration and prediction performance,and had good clinical practicality,which was helpful for clinicians to make diagnosis and treatment decisions for malnutrition in CHF patients.

Objective:To identify tumor-infiltrating immune cells that affect the prognosis of endometrial cancer(EC)with no specific molecular profile(NSMP)subtypeand to establish an integrated prognostic model based on immune cells.Methods:Gene expression data,whole exome sequencing data,and corresponding clinical infor-mation for EC patients were obtained from the The Cancer Genome Atlas(TCGA)database.The CIBERSORTx algorithm was used to evaluate the infiltration levels of 22 types of immune cells in the tumor microenvironment.Kaplan-Meier survival analysis,along with univariate and multivariate Cox regression analyses were used to identi-fy immune cells with prognostic values.A prognostic nomogram was subsequently developed based on significant immune cells and clinicopathological parameters.Results:A total of 169 EC patients classified as NSMP subtype-swere included in this study.Among them 123 patients(72.8％)were aged＜70 years,and 152 patients(89.9％)had type Ⅰ tumors.Kaplan-Meier curves showed that the proportion of plasma cells(P＜0.001),M1 macrophages(P=0.038)and activated NK cells(P=0.01)were significantly associated with overall survival.Multivariate Cox regression analysis revealed that the proportion of activated NK cells(proportion ≥0.027:HR 0.23,95％CI 0.08-0.66,P=0.006),age(≥70 years:HR4.59,95％CI 1.80-11.70,P=0.001)and tumor stage(stage Ⅱ:HR3.87,95％CI 1.18-12.70,P=0.026;stage Ⅲ:HR 6.08,95％CI 1.69-21.87,P=0.006;Ⅳ stage:HR 10.81,95％CI 3.07-38.08,P＜0.001)are independent prognostic indicators for NSMP tumors.A nomogram model was estab-lished by combining activation of NK cells,tumor stage and patient age.Internal cross-validation showed that the integrated prognostic model exhibited good predictive ability for the overall survival rates of patients(P＜0.001).Conclusions:Elevated tumor-infiltrating activated NK cells serve as an independent prognostic indicator for NSMP-subtype EC patients.When integrated with tumor stage and age,they form a robust multivariable prognos-tic model with superior predictive power.

Objective:To investigate the correlation between occupational ionizing radiation exposure and abnormal metabolic indicators, providing a basis for assessing the health risks of occupational ionizing radiation workers and establishing a risk prediction model for chronic metabolic diseases.Methods:In January 2023, 7708 individuals were randomly selected from the occupational health examination data in Zhejiang Province. After excluding 16 individuals due to record errors, 2698 on-the-job workers exposed to ionizing radiation from 2020 to 2021 were selected as the exposure group, 2027 pre-employment workers exposed to ionizing radiation from 2016 to 2022 were selected as the pre-employment control group, and 2967 non-ionizing radiation workers from 2016 to 2022 were selected as the control group. Demographic data, blood routine, urine routine, biochemical indicators, and peripheral blood lymphocyte micronucleus rate of each group were collected. One-way ANOVA and rank sum test were used for comparison of indicators. The exposure group was divided into different groups based on age, exposure duration, and body mass index (BMI), and the correlation between indicators and occupational ionizing radiation was analyzed. Lasso variable selection was conducted by constructing a penalty coefficient (λ), and a complete regression model was established.Results:There were statistically significant differences in indicators such as blood pressure, heart rate, and average hemoglobin concentration between the exposure group and the control group, as well as the pre-employment control group ( P<0.05). Through Lasso variable selection, 19 indicators including exposure length, systolic blood pressure (SBP), diastolic blood pressure (DBP), body weight, body mass index (BMI), urine pH value, red blood cell count, microscopic white blood cells, casts, absolute value of monocytes, mean corpuscular volume of red blood cells, mean hemoglobin concentration, alkaline phosphatase, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, and low-density lipoprotein cholesterol (LDL-C). There were statistically significant differences in exposure length, SBP, DBP, body weight, BMI, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, and mean corpuscular volume of red blood cells among workers of different ages in the exposure group ( P<0.05) ; there were statistically significant differences in SBP, DBP, body weight, BMI, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, and mean corpuscular volume of red blood cells among workers with different exposure durations ( P<0.05) ; there were statistically significant differences in exposure length, SBP, DBP, body weight, BMI, red blood cells, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, absolute value of monocytes, mean corpuscular volume of red blood cells, and mean hemoglobin concentration among workers with different BMIs ( P<0.05) . Conclusion:Occupational ionizing radiation is associated with abnormal metabolic indicators such as blood pressure, heart rate, total bile acid, α-L-fucosidase, urea, and creatinine in the human body. More attention should be paid to the risk of chronic metabolic diseases among workers exposed to ionizing radiation.

Intracranial solitary fibrous tumor（ISFT）is a rare spindle cell central nervous system tumor originating from mesenchymal tissue. There are few reports of ISFT ultrasound findings in China. In this case，the patient，a 59-year-old man，was admitted to the hospital because of "skull tumor found on the top of the head for more than 2 years". The patient found tumor protrusion on the skull at the top of the head 2 years ago，without pain and other feelings. It was as small as a mung bean at first，and gradually increased during the course of the disease. After admission，ultrasound examination was performed，which suggested solid space occupying lesions in the skull. Considering the possibility of eosinophilic granuloma，malignant tumors were to be excluded.CT scan，three-dimensional imaging of skull and MRI scan and enhancement examination of skull were performed，which suggested that the right frontoparietal skull and skull mass shadow occupied the right side，and meningioma may occur. The brain tumor was resected under neuronavigation，and the solitary fibrous tumor was confirmed by postoperative pathology. The author analyzed the pathophysiology，imaging findings，ultrasound characteristics，differential diagnosis of ISFT in detail，in order to improve the understanding of ISFT in clinical work.

Objective:To explore the application effect of 3D technology-assisted teaching based on "four-in-one" flipped classroom in clinical teaching of neurosurgery, and provide a basis for optimizing the medical education mode.Methods:A total of 50 students from the Second Clinical College were selected between June 2020 and June 2024, including eight-year program medical students and postgraduate neurosurgery students. The control group ( n=25) received the conventional teaching mode. The experimental group ( n=25) was taught using the "four-in-one" flipped classroom combined with 3D technology, including characteristic textbooks with 3D model drawings, Internet platforms (video libraries and virtual simulation modules), mobile interactive terminals (real-time question and answer), and virtual simulation technology. Effectiveness was evaluated through theoretical assessment (e.g., neuroanatomy and clinical application ability, with a total score of 100 points), operational assessment (e.g., surgical design and aseptic concept, with a total score of 100 points), and a teaching quality questionnaire. Independent samples t-test was conducted using SPSS 22.0. Results:The total score of theoretical assessment was higher in the experimental group than that in the control group [(86.52±5.21) vs. (73.56±6.32), P<0.001], with the largest difference observed in case analysis questions [(26.03±3.65) vs. (22.22±3.50), P=0.001]. In the operational assessment, the experimental group performed better in "surgical process design" [(26.30±4.14) vs. (21.44±3.45), P<0.001] and "aseptic concept" [(8.18±0.98) vs. (6.64±0.79), P<0.001]. The teaching quality questionnaire showed that the experimental group scored higher in "clinical practice skill enhancement" [(23.13±1.39) vs. (21.45±1.86), P=0.001] and "self-directed learning motivation" [(21.84±1.60) vs. (19.75±1.45), P<0.001]. Conclusions:The combination of "four-in-one" flipped classroom and 3D technology can significantly improve the teaching effectiveness of neurosurgery, especially in the cultivation of clinical thinking and practical abilities. This approach is worth promoting.

Objective:To investigate the correlation between occupational ionizing radiation exposure and abnormal metabolic indicators, providing a basis for assessing the health risks of occupational ionizing radiation workers and establishing a risk prediction model for chronic metabolic diseases.Methods:In January 2023, 7708 individuals were randomly selected from the occupational health examination data in Zhejiang Province. After excluding 16 individuals due to record errors, 2698 on-the-job workers exposed to ionizing radiation from 2020 to 2021 were selected as the exposure group, 2027 pre-employment workers exposed to ionizing radiation from 2016 to 2022 were selected as the pre-employment control group, and 2967 non-ionizing radiation workers from 2016 to 2022 were selected as the control group. Demographic data, blood routine, urine routine, biochemical indicators, and peripheral blood lymphocyte micronucleus rate of each group were collected. One-way ANOVA and rank sum test were used for comparison of indicators. The exposure group was divided into different groups based on age, exposure duration, and body mass index (BMI), and the correlation between indicators and occupational ionizing radiation was analyzed. Lasso variable selection was conducted by constructing a penalty coefficient (λ), and a complete regression model was established.Results:There were statistically significant differences in indicators such as blood pressure, heart rate, and average hemoglobin concentration between the exposure group and the control group, as well as the pre-employment control group ( P<0.05). Through Lasso variable selection, 19 indicators including exposure length, systolic blood pressure (SBP), diastolic blood pressure (DBP), body weight, body mass index (BMI), urine pH value, red blood cell count, microscopic white blood cells, casts, absolute value of monocytes, mean corpuscular volume of red blood cells, mean hemoglobin concentration, alkaline phosphatase, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, and low-density lipoprotein cholesterol (LDL-C). There were statistically significant differences in exposure length, SBP, DBP, body weight, BMI, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, and mean corpuscular volume of red blood cells among workers of different ages in the exposure group ( P<0.05) ; there were statistically significant differences in SBP, DBP, body weight, BMI, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, and mean corpuscular volume of red blood cells among workers with different exposure durations ( P<0.05) ; there were statistically significant differences in exposure length, SBP, DBP, body weight, BMI, red blood cells, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, absolute value of monocytes, mean corpuscular volume of red blood cells, and mean hemoglobin concentration among workers with different BMIs ( P<0.05) . Conclusion:Occupational ionizing radiation is associated with abnormal metabolic indicators such as blood pressure, heart rate, total bile acid, α-L-fucosidase, urea, and creatinine in the human body. More attention should be paid to the risk of chronic metabolic diseases among workers exposed to ionizing radiation.

Objective:To identify tumor-infiltrating immune cells that affect the prognosis of endometrial cancer(EC)with no specific molecular profile(NSMP)subtypeand to establish an integrated prognostic model based on immune cells.Methods:Gene expression data,whole exome sequencing data,and corresponding clinical infor-mation for EC patients were obtained from the The Cancer Genome Atlas(TCGA)database.The CIBERSORTx algorithm was used to evaluate the infiltration levels of 22 types of immune cells in the tumor microenvironment.Kaplan-Meier survival analysis,along with univariate and multivariate Cox regression analyses were used to identi-fy immune cells with prognostic values.A prognostic nomogram was subsequently developed based on significant immune cells and clinicopathological parameters.Results:A total of 169 EC patients classified as NSMP subtype-swere included in this study.Among them 123 patients(72.8％)were aged＜70 years,and 152 patients(89.9％)had type Ⅰ tumors.Kaplan-Meier curves showed that the proportion of plasma cells(P＜0.001),M1 macrophages(P=0.038)and activated NK cells(P=0.01)were significantly associated with overall survival.Multivariate Cox regression analysis revealed that the proportion of activated NK cells(proportion ≥0.027:HR 0.23,95％CI 0.08-0.66,P=0.006),age(≥70 years:HR4.59,95％CI 1.80-11.70,P=0.001)and tumor stage(stage Ⅱ:HR3.87,95％CI 1.18-12.70,P=0.026;stage Ⅲ:HR 6.08,95％CI 1.69-21.87,P=0.006;Ⅳ stage:HR 10.81,95％CI 3.07-38.08,P＜0.001)are independent prognostic indicators for NSMP tumors.A nomogram model was estab-lished by combining activation of NK cells,tumor stage and patient age.Internal cross-validation showed that the integrated prognostic model exhibited good predictive ability for the overall survival rates of patients(P＜0.001).Conclusions:Elevated tumor-infiltrating activated NK cells serve as an independent prognostic indicator for NSMP-subtype EC patients.When integrated with tumor stage and age,they form a robust multivariable prognos-tic model with superior predictive power.

Objective We investigated the clinical features and the potential risk factors of malnutrition in patients with chronic heart failure(CHF),and constructed the risk prediction model of malnutrition.Methods A total of459 CHF patients admitted between January 2023 and July 2024 were classified into a normal nutrition group and a malnutrition group based on the geriatric Nutrition Risk Index(GNRI)score upon admission.The patient-related data were gathered,and single-variable and multi-variable logistic analyses were first carried out to identify the risk factors associated with the malnutrition risk.Subsequently,the stepwise regression approach was employed to define the inclusion criteria and construct a malnutrition nomogram model for CHF patients.The diagnostic efficacy and calibration of this model were appraised using the ROC curve and calibration curve,and its clinical utility was assessed via the clinical decision curve.A P value less than 0.05 signified statistically significant differences.Results Anxiety(OR=1.1902,95%CI:1.0217～1.3865),urea nitrogen(OR=1.4842,95%CI:1.1187～1.9691),low body weight(OR=0.8463,95%CI:0.7852～0.9121),and low albumin(OR=0.0467,95%CI:0.0172～0.1268)were risk factors for malnutrition.The optimal model inclusion factors were selected by stepwise regression,including:Body weight,7 items of Generalized Anxiety Disorder Scale(GAD-7),urea nitrogen,uric acid,albumin,total cholesterol,high density lipoprotein cholesterol(HDL-L),low density lipoprotein cholesterol(LDL-L),D-dimer.The area under the ROC curve(AUC)of the column chart model based on the above factors is 0.996(95%CI:0.971～0.978),with a sensitivity of 97.8%and a specificity of 97.1%.The C-index validated internally in the calibration curve was 0.824.The calibration chart and validation results demonstrate good consis-tency and applicability.Conclusion The column chart prediction model created in this study based on nine factors including body weight,GAD-7,urea nitrogen,uric acid,albumin,total cholesterol,HDL-L,LDL-L,and D-dimer had good calibration and prediction performance,and had good clinical practicality,which was helpful for clinicians to make diagnosis and treatment decisions for malnutrition in CHF patients.

Objective:To explore the application effect of 3D technology-assisted teaching based on "four-in-one" flipped classroom in clinical teaching of neurosurgery, and provide a basis for optimizing the medical education mode.Methods:A total of 50 students from the Second Clinical College were selected between June 2020 and June 2024, including eight-year program medical students and postgraduate neurosurgery students. The control group ( n=25) received the conventional teaching mode. The experimental group ( n=25) was taught using the "four-in-one" flipped classroom combined with 3D technology, including characteristic textbooks with 3D model drawings, Internet platforms (video libraries and virtual simulation modules), mobile interactive terminals (real-time question and answer), and virtual simulation technology. Effectiveness was evaluated through theoretical assessment (e.g., neuroanatomy and clinical application ability, with a total score of 100 points), operational assessment (e.g., surgical design and aseptic concept, with a total score of 100 points), and a teaching quality questionnaire. Independent samples t-test was conducted using SPSS 22.0. Results:The total score of theoretical assessment was higher in the experimental group than that in the control group [(86.52±5.21) vs. (73.56±6.32), P<0.001], with the largest difference observed in case analysis questions [(26.03±3.65) vs. (22.22±3.50), P=0.001]. In the operational assessment, the experimental group performed better in "surgical process design" [(26.30±4.14) vs. (21.44±3.45), P<0.001] and "aseptic concept" [(8.18±0.98) vs. (6.64±0.79), P<0.001]. The teaching quality questionnaire showed that the experimental group scored higher in "clinical practice skill enhancement" [(23.13±1.39) vs. (21.45±1.86), P=0.001] and "self-directed learning motivation" [(21.84±1.60) vs. (19.75±1.45), P<0.001]. Conclusions:The combination of "four-in-one" flipped classroom and 3D technology can significantly improve the teaching effectiveness of neurosurgery, especially in the cultivation of clinical thinking and practical abilities. This approach is worth promoting.