ObjectiveTo investigate the association of SH2B1 rs7359397 （C>T） polymorphism with the progression to hepatic fibrosis in the elderly patients with metabolic dysfunction-associated steatotic liver disease （MASLD） in Beijing， China， and to provide an important genetic basis for the precise subtyping， prognostic evaluation， and individualized treatment of elderly MASLD patients in China. MethodsA total of 505 elderly patients （aged ≥65 years） who participated in regular physical examination in Mentougou Kuangshan Hospital of Beijing Jingmei Group General Hospital from November 2020 to September 2021 and were diagnosed with MASLD by abdominal ultrasound were enrolled as MASLD group， and 381 elderly population who underwent physical examination in the same community hospital during the same period of time and were not found to have MASLD by abdominal ultrasound were enrolled as control group. FibroScan was used to measure liver fat content and determine fibrosis stage. The 96-well microfluidic chip technique was used to identify SH2B1 rs7359397 polymorphism. The independent-samples t test was used for comparison of normally distributed continuous data between the two groups， and the chi-square test or the adjusted chi-square test was used for comparison of categorical data between the two groups. Univariate and multivariate Logistic regression analyses were used to identify the independent predictive factors for MASLD and its comorbidities. ResultsCompared with the control group， the MASLD group had a significantly younger age and significantly higher levels of waist circumference， hip circumference， waist-hip ratio， body mass index （BMI）， alanine aminotransferase， aspartate aminotransferase， triglyceride， platelet count， and fibrosis-4 （FIB-4） index， as well as a significantly lower level of high-density lipoprotein cholesterol （all P<0.05）. Among the 381 patients in the control group， 264 （69.29%） had genotype CC and 117 （30.71%） had genotype CT+TT， while among the 505 patients in the MASLD group， 317 （62.77%） had genotype CC and 188 （37.23%） had genotype CT+TT， suggesting that the MASLD group had a significantly higher proportion of patients with genotype CT+TT compared with the control group （χ²=4.09， P=0.043）. In the MASLD group， compared with the genotype CC group， the genotype CT+TT group had a significantly lower proportion of patients with FIB-4 ≥2 or atherosclerotic cardiovascular diseases （P<0.05）. The multivariate Logistic regression analysis showed that after adjustment for age， sex， and BMI， carrying T allele was a protective factor against progressive hepatic fibrosis （odds ratio ［OR］=0.481， 95% confidence interval ［CI］： 0.249 — 0.929， P=0.029）. In the subgroups of comorbidities with hypertension， metabolic syndrome， and obesity， genotype CT+TT was associated with a significant reduction in the risk of progressive hepatic fibrosis （hypertension： OR=0.27， 95%CI：0.09 — 0.77， P=0.014； metabolic syndrome： OR=0.30， 95%CI： 0.11 — 0.79， P=0.015； obesity： OR=0.11， 95%CI： 0.03 — 0.48， P=0.003）. After adjustment for age， sex， and BMI， in the patients with MASLD， the patients with genotype CT+TT had a significant reduction in the prevalence rate of atherosclerotic cardiovascular diseases compared with those with genotype CC （OR=0.506， 95%CI：0.336 — 0.761， P=0.001）. ConclusionSH2B1 rs7359397 （C>T） polymorphism is associated with the reduction in the risk of hepatic fibrosis and atherosclerotic cardiovascular diseases in MASLD patients.

Objective:To study the risk and pattern of deaths caused by various diseases in the population and in the case of long-term occupational X-ray exposure.Methods:Using a combination of retrospective and prospective cohort research methods, an exposure group of medical X-ray diagnostic workers who worked in the radiology department of Jiangsu Provincial Hospital between 1950 and 1980 and a control group of medical workers from other departments who did not work with radiolog during the same period in the same hospital were selected to form a study cohort. The cumulative number of person years of observation in the cohort during 1950-2011 was calculated, and the Cox regression model was used to calculate the risk of deaths of medical X-ray diagnostic workers for various diseases through adjusting sex, attained age, birth age, and starting working age.Results:A total of 6 953 follow-up visits was completed to the cohort, including 3 649 in the radiation group and 3 304 in the control group, with a total of 347 362 person years of observation. There were 2 099 deaths in the cohort as of December 31, 2021. Cox regression results showed that diseases with a significantly higher risk of death in the radiation group compared with the control group were: all-cancer ( RR=1.20, 95% CI: 1.04-1.39, Z=2.56, P<0.05, including lung cancer RR=1.52, 95% CI: 1.17-1.98, Z=3.10, P<0.01, and pancreatic cancer RR=1.96, 95% CI: 1.11-3.46, Z=2.31, P<0.05); diseases of the circulatory system ( RR=1.29, 95% CI: 1.06-1.57, Z=2.58, P<0.01); endocrine, nutritional and metabolic diseases ( RR=1.90, 95% CI: 1.06-3.42, Z=2.14, P<0.05). Stratified analyses showed that, of male workers, the radiation group had an increased risk of death caused by all-cancer and lung cancer ( Z=3.50, 2.92, P<0.01); of the age group at starting ages 26 to 30, the radiation group had an increased risk of death distributed to circulatory diseases ( Z=2.06, P<0.05); and in the age group at attained ages elder than 61 years, the radiation group had an increased risk of death distributed to all cancers, lung cancer, and circulatory diseases ( Z=2.90-4.31, P<0.01). Conclusions:As has been shown, threre is an increasing risk of death distributed to lung cancer, pancreatic cancer, and circulatory diseases in medical X-ray diagnostic workers in Jiangsu province. Further in-depth research in related areas may be conducted in the future.

Emotion classification and recognition is a crucial area in emotional computing. Physiological signals, such as electroencephalogram (EEG), provide an accurate reflection of emotions and are difficult to disguise. However, emotion recognition still faces challenges in single-modal signal feature extraction and multi-modal signal integration. This study collected EEG, electromyogram (EMG), and electrodermal activity (EDA) signals from participants under three emotional states: happiness, sadness, and fear. A feature-weighted fusion method was applied for integrating the signals, and both support vector machine (SVM) and extreme learning machine (ELM) were used for classification. The results showed that the classification accuracy was highest when the fusion weights were set to EEG 0.7, EMG 0.15, and EDA 0.15, achieving accuracy rates of 80.19% and 82.48% for SVM and ELM, respectively. These rates represented an improvement of 5.81% and 2.95% compared to using EEG alone. This study offers methodological support for emotion classification and recognition using multi-modal physiological signals.
Humans ; Emotions/physiology* ; Electroencephalography ; Support Vector Machine ; Electromyography ; Signal Processing, Computer-Assisted ; Galvanic Skin Response/physiology* ; Machine Learning ; Male

Objective:To study the risk and pattern of deaths caused by various diseases in the population and in the case of long-term occupational X-ray exposure.Methods:Using a combination of retrospective and prospective cohort research methods, an exposure group of medical X-ray diagnostic workers who worked in the radiology department of Jiangsu Provincial Hospital between 1950 and 1980 and a control group of medical workers from other departments who did not work with radiolog during the same period in the same hospital were selected to form a study cohort. The cumulative number of person years of observation in the cohort during 1950-2011 was calculated, and the Cox regression model was used to calculate the risk of deaths of medical X-ray diagnostic workers for various diseases through adjusting sex, attained age, birth age, and starting working age.Results:A total of 6 953 follow-up visits was completed to the cohort, including 3 649 in the radiation group and 3 304 in the control group, with a total of 347 362 person years of observation. There were 2 099 deaths in the cohort as of December 31, 2021. Cox regression results showed that diseases with a significantly higher risk of death in the radiation group compared with the control group were: all-cancer ( RR=1.20, 95% CI: 1.04-1.39, Z=2.56, P<0.05, including lung cancer RR=1.52, 95% CI: 1.17-1.98, Z=3.10, P<0.01, and pancreatic cancer RR=1.96, 95% CI: 1.11-3.46, Z=2.31, P<0.05); diseases of the circulatory system ( RR=1.29, 95% CI: 1.06-1.57, Z=2.58, P<0.01); endocrine, nutritional and metabolic diseases ( RR=1.90, 95% CI: 1.06-3.42, Z=2.14, P<0.05). Stratified analyses showed that, of male workers, the radiation group had an increased risk of death caused by all-cancer and lung cancer ( Z=3.50, 2.92, P<0.01); of the age group at starting ages 26 to 30, the radiation group had an increased risk of death distributed to circulatory diseases ( Z=2.06, P<0.05); and in the age group at attained ages elder than 61 years, the radiation group had an increased risk of death distributed to all cancers, lung cancer, and circulatory diseases ( Z=2.90-4.31, P<0.01). Conclusions:As has been shown, threre is an increasing risk of death distributed to lung cancer, pancreatic cancer, and circulatory diseases in medical X-ray diagnostic workers in Jiangsu province. Further in-depth research in related areas may be conducted in the future.

Objective:To analyze clinical indicators and imaging data of hospitalized pneumonia patients and develop prediction models for length of hospital stay based on CT radiomics features and clinical indicators.Methods:Patients admitted to the First Clinical School of Hainan Medical University for pneumonia treatment between November 2020 and May 2024 were enrolled. Clinical data and CT imaging were collected, and radiomics features were extracted. Patients were divided into three groups based on the length of stay (<8 d, 8-28 d,>28 d, and poor prognosis). Three prediction models were constructed using logistic regression (LR): clinical features model, imaging features model and a combined clinical and imaging features model. The predictive performance of three models was evaluated using the area under the receiver operating characteristic (ROC) curve and DeLong test, followed by feature analysis. The Kappa test was used to compare the consistency of the overall classification.Results:A total of 343 subjects were included, with an average age of 61.46±20.98 years. The area under the curve (AUC) values of the combined model in different hospitalization duration classifications (<8 d, 8-28 d,>28 d, and poor prognosis) were 0.73, 0.65 and 0.78 in the training set, and 0.71, 0.65 and 0.76 in the validation set, respectively. The AUC values of the clinical feature model in different hospitalization duration classifications were 0.63, 0.64 and 0.73 in the training set, and 0.60, 0.52 and 0.63 in the validation set, respectively. The AUC values of the imaging feature model in different hospitalization duration classifications (<8 d, 8-28 d,>28 d, and poor prognosis) were 0.67, 0.66 and 0.73 in the training set, and 0.68, 0.54 and 0.66 in the validation set, respectively. The DeLong test results showed that the combined model outperformed other models in hospitalization duration classification (validation set AUC, all P<0.05, Bonferroni correction). Kappa test results showed that the combined model achieved the highest consistency between predicted classifications and actual hospitalization classifications ( K=0.615). Shape features, texture features and clinical features all contributed proportionally to the combined model. Conclusion:The combined model integrating radiomics features with clinical indicators can significantly enhance the predictive efficacy for the length of hospitalization in pneumonia patients.

Objective:To analyze clinical indicators and imaging data of hospitalized pneumonia patients and develop prediction models for length of hospital stay based on CT radiomics features and clinical indicators.Methods:Patients admitted to the First Clinical School of Hainan Medical University for pneumonia treatment between November 2020 and May 2024 were enrolled. Clinical data and CT imaging were collected, and radiomics features were extracted. Patients were divided into three groups based on the length of stay (<8 d, 8-28 d,>28 d, and poor prognosis). Three prediction models were constructed using logistic regression (LR): clinical features model, imaging features model and a combined clinical and imaging features model. The predictive performance of three models was evaluated using the area under the receiver operating characteristic (ROC) curve and DeLong test, followed by feature analysis. The Kappa test was used to compare the consistency of the overall classification.Results:A total of 343 subjects were included, with an average age of 61.46±20.98 years. The area under the curve (AUC) values of the combined model in different hospitalization duration classifications (<8 d, 8-28 d,>28 d, and poor prognosis) were 0.73, 0.65 and 0.78 in the training set, and 0.71, 0.65 and 0.76 in the validation set, respectively. The AUC values of the clinical feature model in different hospitalization duration classifications were 0.63, 0.64 and 0.73 in the training set, and 0.60, 0.52 and 0.63 in the validation set, respectively. The AUC values of the imaging feature model in different hospitalization duration classifications (<8 d, 8-28 d,>28 d, and poor prognosis) were 0.67, 0.66 and 0.73 in the training set, and 0.68, 0.54 and 0.66 in the validation set, respectively. The DeLong test results showed that the combined model outperformed other models in hospitalization duration classification (validation set AUC, all P<0.05, Bonferroni correction). Kappa test results showed that the combined model achieved the highest consistency between predicted classifications and actual hospitalization classifications ( K=0.615). Shape features, texture features and clinical features all contributed proportionally to the combined model. Conclusion:The combined model integrating radiomics features with clinical indicators can significantly enhance the predictive efficacy for the length of hospitalization in pneumonia patients.

To analyze the disease group structure and its trends in key departments of large public hospitals using diagnosis related group (DRG) data, explore the key points of intervention and optimization of disease groups in departments, and further promote the rational allocation of department resources.

Objective To investigate the basic situation and occupational health conditions of nuclear medicine radiation workers in Jiangsu Province based on the research protocol developed by the Institute of Radiation Medicine, Chinese Academy of Medical Sciences for the nationwide study on the health effects of nuclear medicine radiation in China, understand the impact of occupational radiation on the physical health of nuclear medicine radiation workers, and provide a basis for improving the occupational protection of nuclear medicine radiation workers and reducing the risk of occupational radiation-related health issues. Methods A census approach was used to collect general data and occupational health information of nuclear medicine radiation workers in Jiangsu Province. The analysis focused on the abnormalities in physical examination indicators among radiation workers of different genders, ages, and working years to evaluate the health effects of occupational radiation exposure. Results The occupational health examination data of 472 nuclear medicine radiation workers were collected from 76 medical institutions in Jiangsu Province. The results showed that the detection rate of abnormal hypothyroidism in female workers (8.90%) was higher than that in male workers (2.54%) (P=0.028). With increasing working years, the detection rates of cataract and continuous decrease in white blood cell count increased (P＜0.001). The multivariate logistic regression identified working years as a risk factor for cataract and continuous decrease in white blood cell count (OR=1.59, 95%CI=1.40-3.35, P=0.0003; OR=4.15, 95%CI=3.11-29.91, P=0.0001). In addition, working years was also a risk factor for hypertension, fatty liver, and tumor (OR=2.28, 95%CI=1.51-3.47, P=8.76 × 10⁻⁵; OR=1.69, 95%CI=1.10-2.58, P=0.0145; OR=2.04, 95%CI=1.00-4.16, P=0.0469). Conclusion The study found that working in nuclear medicine could increase the risk of various radiation-related diseases, and the risk is influenced by factors such as working years.

Objective To investigate the basic situation and occupational health conditions of nuclear medicine radiation workers in Jiangsu Province based on the research protocol developed by the Institute of Radiation Medicine, Chinese Academy of Medical Sciences for the nationwide study on the health effects of nuclear medicine radiation in China, understand the impact of occupational radiation on the physical health of nuclear medicine radiation workers, and provide a basis for improving the occupational protection of nuclear medicine radiation workers and reducing the risk of occupational radiation-related health issues. Methods A census approach was used to collect general data and occupational health information of nuclear medicine radiation workers in Jiangsu Province. The analysis focused on the abnormalities in physical examination indicators among radiation workers of different genders, ages, and working years to evaluate the health effects of occupational radiation exposure. Results The occupational health examination data of 472 nuclear medicine radiation workers were collected from 76 medical institutions in Jiangsu Province. The results showed that the detection rate of abnormal hypothyroidism in female workers (8.90%) was higher than that in male workers (2.54%) (P=0.028). With increasing working years, the detection rates of cataract and continuous decrease in white blood cell count increased (P＜0.001). The multivariate logistic regression identified working years as a risk factor for cataract and continuous decrease in white blood cell count (OR=1.59, 95%CI=1.40-3.35, P=0.0003; OR=4.15, 95%CI=3.11-29.91, P=0.0001). In addition, working years was also a risk factor for hypertension, fatty liver, and tumor (OR=2.28, 95%CI=1.51-3.47, P=8.76 × 10⁻⁵; OR=1.69, 95%CI=1.10-2.58, P=0.0145; OR=2.04, 95%CI=1.00-4.16, P=0.0469). Conclusion The study found that working in nuclear medicine could increase the risk of various radiation-related diseases, and the risk is influenced by factors such as working years.

Objective:To investigate the effects of long-term X-ray radiation exposure on the tumor risk of medical X-ray workers in Jiangsu province, and to provide a scientific basis for the development of occupational protection policies and the improvement of workers′ health.Methods:By using a combination of retrospective and prospective cohort research method, the medical diagnostic X-ray workers who worked in the radiology department of all hospitals in Jiangsu province between 1950 and 1980 were selected as the radiology group.In the meantime medical personnel in internal medicine, otorhinolaryngology, pediatrics and other medical departments who had not been engaged in radiology during the same period of time at the same hospital were selected as the control group to form a survey cohort. The cumulative number of person-years of observation of the cohort during 1950-2011 was calculated, and the relative risk of various malignant tumors among medical X-ray workers was calculated by using Cox regression model after adjusting for sex, attained age, year of birth, and year of work initiation.Results:A total of 6 954 follow-ups was completed for the cohort, including 3 649 in the irradiation group and 3 305 in the control group, totally 340 483 person-years of observation. As of December 31, 2021, there were 1 328 patients with malignant tumors in this cohort. Cox regression result showed that compared with the control group, the irradiation group who had developed lung cancer ( RR=1.60, 95% CI 1.24-2.08), lymphoma ( RR =4.28, 95% CI 1.54-11.93), solid cancer ( RR =1.17, 95% CI 1.04-1.31), and total cancer ( RR =1.29, 95% CI 1.14-1.46) had significantly higher relative risks ( Z=3.56, 2.78, 2.71, 3.96, P<0.05). Stratified analyses showed that the risks of lung, lymphoma, solid and total cancers were higher in the radiation group than in the control group for males and for those who arrived at the age of 61 years or older ( χ2=6.70-33.86, P<0.05). The risks of lung, solid and total cancers were higher in the radiation group than in the control group for those who started to work in the age group of 21 to 25 years ( χ2=6.46, 6.16, 5.62, P<0.05). Conclusions:The relative risks of lung, lymphoma, solid and total cancers among medical X-ray workers in Jiangsu province are significantly higher, suggesting that attention should be paid to strengthening radiation protection for radiation workers in their radiological practices.