Objective To analyze the abnormal individual dose monitoring results in 206 medical institutions in a selected region in 2024, and to propose improvement measures. Methods Individuals with monitoring results exceeding the investigation level were subjected to high-dose investigation, and the results were statistically analyzed. Results In 2024, the individual dose monitoring of 206 medical institutions in a selected region showed 1.04% abnormal results. The proportions of abnormal results from primary, secondary, and tertiary medical institutions were 12.22%, 3.33%, and 84.45%, respectively. In analysis of the causes of abnormal results, 52.53% of the cases were due to personal dosimeters left in the radiation workplace, and 20.20% were due to the confusion in wearing personal dosimeters inside and outside the lead apron. In analysis of the occupational distribution of the radiation workers with abnormal monitoring results, interventional radiology and diagnostic radiology accounted for 73.34% and 24.44%, respectively. Statistical analysis of the dose range showed that doses in the ranges of 1.25-2.0 mSv and 2.0-5.0 mSv accounted for 42.22% and 33.33%, respectively. In the report of abnormal monitoring results, the proportions of reporting notional dose and reporting measured results accounted for 88.89% and 11.11%, respectively. Among institutions with consecutive abnormal results, primary, secondary, and tertiary medical institutions accounted for 15.39%, 7.69%, and 76.92%, respectively. Conclusion The level of the hospital, occupational type, the perceived importance of the hospital to the management of radiation protection, and the perceived importance and compliance of the radiation workers with the individual dose monitoring are potential causes of abnormal results. It is recommended that employers should enhance radiation protection training for their radiation workers to ensure proper wearing and storage of dosimeters, and progressively improve the standardization and effectiveness of individual dose monitoring practice.

Objective:To investigate the regulatory effects of transcutaneous auricular vagus nerve stimulation (taVNS) on functional connectivity (FC) of thalamic subregions in patients with premenstrual syndrome (PMS).Methods:This study was a cross-sectional investigation. Clinical, laboratory, and imaging data were retrospectively collected from 56 PMS patients (PMS group) and 66 healthy controls (control group) recruited from various universities and hospitals in Nanning between November 2021 and June 2024. Resting-state functional MRI (fMRI) data and fMRI data during taVNS immediate stimulation (2 Hz, 25 Hz) were acquired from subjects during their late luteal phase. Using thalamic subregions (anterior thalamic nucleus, lateral nucleus, ventral nucleus, medial nucleus, central nucleus, posterior nucleus) as seeds, two-sample t-tests or paired t-tests were employed to analyze alterations in thalamic subregion FC in PMS patients and the regulatory effects of taVNS on these changes. Independent samples t-test were used to compare the differences in clinical and laboratory indicators between the PMS group and the control group. The relationship between taVNS regulation of thalamic subregion FC in PMS patients and thalamic internal functional connectivity were analyzed using mediation effect analysis. Results:Compared to the control group, patients in the PMS group showed increased scores on the Daily Record of Severity of Problems, Pittsburgh Sleep Quality Index, Self-Rating Anxiety Scale, Self-Rating Depression Scale, Hamilton Anxiety Rating Scale 17, and Hamilton Depression Rating Scale 14 during the late luteal phase ( P<0.05). At baseline, PMS patients exhibited higher FC between the left thalamic lateral nucleus and the left insula, and lower FC between the left medial nucleus, posterior nucleus, and ventral nucleus of the thalamus and the right middle frontal gyrus (MFG) compared to the control group (GRF corrected, voxel-level P<0.001, cluster-level P<0.05). During 2 Hz taVNS immediate stimulation in PMS group, FC between the left thalamic medial nucleus, posterior nucleus, ventral nucleus and the right MFG, as well as the FC between the left thalamic ventral nucleu and the left MFG increased compared to baseline levels; meanwhile, FC between the left thalamic posterior nucleus, ventral nucleus and the left insula decreased compared to baseline levels (GRF corrected, voxel-level P<0.001, cluster-level P<0.05). During 25 Hz taVNS immediate stimulation, the FC between the left thalamic ventral nucleus and the right MFG decreased compared to the baseline level (GRF corrected, voxel-level P<0.001, cluster-level P<0.05). Mediation effect analysis showed that the FC between the left thalamic posterior nucleus and the left lateral nucleus mediated part of the association between the FC of the left lateral thalamic nucleus-left insula and the FC of the left ventral thalamic nucleus-left putamen/insula; there were significant direct effects between the FC of the left lateral thalamic nucleus-the left posterior nucleus and FC of the left lateral thalamic nucleus-the left insula, as well as between the FC of the left ventral thalamic nucleus-the left MFG and FC of the left ventral thalamic nucleus-the right MFG. Conclusions:taVNS can modulate abnormal FC of the left thalamic subregions in PMS patients, restoring it toward normalization. The regulatory effects of 2 Hz stimulation are more pronounced than those of 25 Hz stimulation. This modulation primarily operates through two pathways: the left thalamic lateral nucleus-left insula-left thalamic ventral nucleus pathway and the left MFG-left thalamic ventral nucleus-right MFG.

Objective:To conduct a visual analysis of the papers published in the Chinese Journal of Industrial Hygiene and Occupational Diseases since its inception, and to understand the current situation and development trends in the field of occupational health and occupational diseases.Methods:A total of 9894 papers published in the Chinese Journal of Industrial Hygiene and Occupational Diseases from January 1, 1983 to December 31, 2023 were retrieved from China National Knowledge Infrastructure (CNKI) in February 2024. Non-academic literature was screened and excluded. Excel 2010 and SPSS 24.0 were used to analyze the annual publication situation. Visualization software CiteSpace V6.2.R7 was used to conduct co-occurrence analysis, cluster analysis and emergence analysis for keywords and to make knowledge graph.Results:A total of 9381 literatures were included. From 1983 to 2023, the annual publication volume in Chinese Journal of Industrial Hygiene and Occupational Diseases showed an M-shaped fluctuation, with the largest number of literatures published in 2010 (351 literatures). The co-occurrence analysis of keywords showed that the occurrence frequency of keywords such as poisoning, pneumoconiosis, occupational exposure and silicosis was high. By cluster analysis, the literature keywords were summarized into 10 clusters of pneumoconiosis, noise, stress, microwave, paraquat, poisoning, chromatography, polymorphism, silicosis, and yellow phosphorus. The emergence analysis showed that occupational stress, influencing factors, occupational health, occupational diseases and pneumoconiosis were the top 5 keywords of emergence intensity, while noise and hearing loss were the keywords of greater emergence intensity after 2020.Conclusion:The contents of the studies on pneumoconiosis and poisoning published in the Chinese Journal of Industrial Hygiene and Occupational Diseases are relatively stable, while occupational stress and noise have become research hot spots in recent years. It is suggested to strengthen the cross and integration of multi-disciplines in order to promote the development of occupational health and occupational disease fields.

With the popularization of computer software technology and the development of hospital informatization,virtu-alization technology-as a key technology supporting IT infrastructure-has seen continuously expanding market demand and ap-plication scenarios.In recent years,domestic virtualization manufacturers have increased investment in independent innovation,achieving breakthroughs in virtualization software and related technologies,along with iterative product updates.This has enabled them to catch up with and surpass foreign virtualization technologies,providing more personalized virtualization products for Chi-nese enterprises.Hospitals operate multiple systems such as HIS databases,Electronic Medical Record Systems(EMRS),Pic-ture Archiving and Communication Systems(PACS),and Laboratory Information Systems(LIS).Migrating these systems from a purely physical machine environment to a virtualization platform,and using CNware virtualization products to manage existing physical resources in the data center,enables the sharing and integration of computing resources such as server resources,storage resources,and memory resources.This improves hardware utilization and software operation efficiency,achieves significant appli-cation results,and continuously enhances the quality of medical informatization services.

Objective This study aims to apply the moving average method of time series analysis to forecast outpatient and emergency department visits at our hospital for 2024.Additionally,we will validate the trend prediction model against actual visit data from January to April 2024,assessing the accuracy of the time series fitting.The insights generated will serve as a sci-entific foundation for the hospital to allocate resources effectively,formulate work plans,and meet annual objectives.Methods We collected data on outpatient and emergency visits from 2020 to 2023(n=16 periods)and employed the four moving average method for time series decomposition.We calculated the adjusted seasonal index values and developed a linear trend prediction model(Y=7 3847+568.08t)that incorporates seasonal factors.We then computed the predicted monthly outpatient emergency visits for 2024 and compared these forecasts with actual values from the first four months of 2024 to test the model's reliability.Results The predicted visits for the first four months of 2024 were 84 396,80 633,88 244,and 84 158 respectively.The rela-tive errors compared to actual figures ranged from 1.13％to 8.81％,with an average relative error of 4.22％.The seasonal indi-ces revealed that the third quarter represents the peak period(104.26％),while the second quarter is the low point(95.91％).Conclusion The moving average seasonal index method effectively captures the seasonal variations in outpatient and emergency department visits,offering high prediction accuracy.This methodology can assist hospitals in dynamically adjusting their schedu-ling and optimizing resource allocation.

Aim To investigate the effect of interdialytic serum potassium levels on thrombosis of autologous ar-teriovenous fistula(AVF)in patients with chronic kidney disease(CKD)on maintenance haemodialysis(MHD).Methods 159 CKD patients who underwent MHD in our hospital from October 2021 to October 2022 were retrospectively analyzed.They were divided into hyperkalemia group(n=53),normal serum potassium group(n=61)and hypokalemia group(n=45)according to the mean serum potassium level of patients with different dialysis intervals,and all patients were followed up for 1 year or followed up until AVF thrombosis.General datas were collected and the following indicators were detected at the time of patient enrolment,including biochemical indicators,inflammatory factors,ultrasound indicators of AVF and oxidative stress factors levels.Multifactorial Logistic regression equations were used to analyze the effects of clinical indicators on AVF thrombosis in MHD patients,receiver operating characteristic(ROC)curve was used to assess the predictive efficacy of clinical indicators on AVF thrombosis;And interval likelihood ratio was used to stratify interdialyt-ic serum potassium levels,and further observe whether the relationship was stability between AVF thrombosis and interdia-lytic serum potassium levels in MHD patients.Results Compared with the normal serum potassium group,the levels of C-reactive protein(CRP),intact parathyroid hormone(iPTH),procalcitonin(PCT),triglyceride(TG),malondial-dehyde(MDA),myeloperoxidase(MPO),brachial artery resistance index(RI),brachial artery pulsatility index(PI)and radial artery PI were significantly elevated in hyperkalemia group and hypokalemia group,while the levels of albumin(Alb),total cholesterol(TC),superoxide dismutase(SOD)and fistula blood flow were significantly reduced(P＜0.05).Systolic blood pressure,diastolic blood pressure,fistula blood flow,Alb and SOD levels were significantly lower in patients with AVF thrombosis than those in patients with AVF unthrombosis(P＜0.05);Interdialytic mean serum potassium level,CRP,iPTH,PCT,brachial artery RI,brachial artery PI,radial artery PI,radial artery RI,MDA and MPO levels were significantly higher in patients with AVF thrombosis(P＜0.05).The ROC curve was used to analyse the model estab-lished by the multifactorial Logistic regression equation,and it was found that model 1 and model 2 had good predictive effi-cacy,and model 2 had the best predictive efficacy.The results of the interval likelihood ratio showed that:when the patient's interdialytic serum potassium level was 3.5～4.5 mmol/L,the possibility of the patient's AVF thrombosis was the lowest,and when the patient's interdialytic serum potassium level was＞5.5 mmol/L or＜3.5 mmol/L,the possibility of the patient's AVF thrombosis was higher,and when the patient's serum potassium level was＞5.5 mmol/L,the probability of AVF thrombosis was the highest in patients,which was 3.925 times higher than that of patients without AVF thrombosis.Conclusion Abnormal interdialytic serum potassium levels may induce AVF thrombosis in CKD patients.Serum potassium levels can be monitored during MHD treatment to enable timely intervention and improve clinical treatment outcomes for patients.

Prostate cancer is the most prevalent malignant tumor among men, ranking first in incidence and second in mortality globally. Novel hormone therapies (NHT) targeting the androgen receptor (AR) pathway have become the standard of care for metastatic prostate cancer. This review offers a comprehensive overview of NHT, including abiraterone, enzalutamide, apalutamide, darolutamide, and rezvilutamide, which have demonstrated efficacy in delaying disease progression and improving patient survival and quality of life. Nevertheless, resistance to NHT remains a critical challenge. The mechanisms underlying resistance are complex, involving AR gene amplification, mutations, splice variants, increased intratumoral androgens, and AR-independent pathways such as the glucocorticoid receptor, neuroendocrine differentiation, DNA repair defects, autophagy, immune evasion, and activation of alternative signaling pathways. This review discusses these resistance mechanisms and examines strategies to counteract them, including sequential treatment with novel AR-targeted drugs, chemotherapy, poly ADP-ribose polymerase inhibitors, radionuclide therapy, bipolar androgen therapy, and approaches targeting specific resistance pathways. Future research should prioritize elucidating the molecular basis of NHT resistance, optimizing existing therapeutic strategies, and developing more effective combination regimens. Additionally, advanced sequencing technologies and resistance research models should be leveraged to identify novel therapeutic targets and improve drug delivery efficiencies. These advancements hold the potential to overcome NHT resistance and significantly enhance the management and prognosis of patients with advanced prostate cancer.

Objective:To establish a normal data model of fetal right ventricular size and function using echocardiography，and to explore the clinical value of quantitative assessment of right ventricular size and function in the diagnosis of congenital heart diseases.Methods:（1）A simple random sampling method was employed to collect 1 004 pregnant women with normal singleton pregnancies at 24 to 32 +6 weeks of gestation who underwent fetal cardiac ultrasound examinations at the First Affiliated Hospital of Air Force Medical University from January 2021 to December 2023. Two-dimensional and M-mode echocardiography were used to measure the right ventricular end-diastolic diameter（RVEDD），right ventricular end-diastolic area（RVEDA），tricuspid annular plane systolic excursion（TAPSE）during systole，and the right ventricular fractional area change（RVFAC）was calculated. The correlations between the above parameters and ultrasound gestational age（USGA）were analyzed. Moreover，percentile growth curves for each parameter were plotted. With the above parameters as dependent variables and the USGA as the independent variable，a Z-score model was established through regression analysis.（2）A stratified sampling method was adopted to select 30 fetuses diagnosed with hypoplastic right heart syndrome（HRHS）and 30 fetuses diagnosed with pulmonary stenosis（PS）during the same period as the case group. The model was verified，and the morphological and functional characteristics of the right ventricle were analyzed. Results:The data of RVEDD，RVEDA，TAPSE，and RVFAC in normal fetuses showed a skewed distribution. Each parameter showed good linear correlations with USGA（ r=0.836，0.834，0.846，0.242；all P<0.001）. The constructed percentile curves for each parameter indicated that RVEDD，RVEDA and TAPSE increased significantly with the growth of USGA，while RVFAC showed a slow downward trend. All parameters in the HRHS group and TAPSE and RVFAC in the PS group deviated significantly from the normal reference range（all P<0.001）. Conclusions:By analyzing RVEDD，RVEDA，TAPSE and RVFAC of normal fetuses，the percentile and Z-score normal reference value models of multiple parameters of fetal right ventricular size and function have been established，providing corresponding standards for quantitative analysis.

Objective This study aims to apply the moving average method of time series analysis to forecast outpatient and emergency department visits at our hospital for 2024.Additionally,we will validate the trend prediction model against actual visit data from January to April 2024,assessing the accuracy of the time series fitting.The insights generated will serve as a sci-entific foundation for the hospital to allocate resources effectively,formulate work plans,and meet annual objectives.Methods We collected data on outpatient and emergency visits from 2020 to 2023(n=16 periods)and employed the four moving average method for time series decomposition.We calculated the adjusted seasonal index values and developed a linear trend prediction model(Y=7 3847+568.08t)that incorporates seasonal factors.We then computed the predicted monthly outpatient emergency visits for 2024 and compared these forecasts with actual values from the first four months of 2024 to test the model's reliability.Results The predicted visits for the first four months of 2024 were 84 396,80 633,88 244,and 84 158 respectively.The rela-tive errors compared to actual figures ranged from 1.13％to 8.81％,with an average relative error of 4.22％.The seasonal indi-ces revealed that the third quarter represents the peak period(104.26％),while the second quarter is the low point(95.91％).Conclusion The moving average seasonal index method effectively captures the seasonal variations in outpatient and emergency department visits,offering high prediction accuracy.This methodology can assist hospitals in dynamically adjusting their schedu-ling and optimizing resource allocation.

With the popularization of computer software technology and the development of hospital informatization,virtu-alization technology-as a key technology supporting IT infrastructure-has seen continuously expanding market demand and ap-plication scenarios.In recent years,domestic virtualization manufacturers have increased investment in independent innovation,achieving breakthroughs in virtualization software and related technologies,along with iterative product updates.This has enabled them to catch up with and surpass foreign virtualization technologies,providing more personalized virtualization products for Chi-nese enterprises.Hospitals operate multiple systems such as HIS databases,Electronic Medical Record Systems(EMRS),Pic-ture Archiving and Communication Systems(PACS),and Laboratory Information Systems(LIS).Migrating these systems from a purely physical machine environment to a virtualization platform,and using CNware virtualization products to manage existing physical resources in the data center,enables the sharing and integration of computing resources such as server resources,storage resources,and memory resources.This improves hardware utilization and software operation efficiency,achieves significant appli-cation results,and continuously enhances the quality of medical informatization services.