Objective:To explore the feasibility of the new auxiliary analysis software in chromosomal aberration analysis of radiation workers during occupational health examinations.Methods:Health examination data of 2 469 radiation workers in Henan province were collected. Manual analysis of chromosomal aberrations in peripheral blood lymphocytes was conducted using the new auxiliary software and the Ikaros software. Then, the chromosomal aberrations detected using both software tools were compared.Results:The new auxiliary software yielded a lower chromosomal aberration rate among radiation workers compared with the Ikaros software [(0.314 ± 0.014)% vs. (0.391 ± 0.022)%, χ2 = 9.24, P = 0.002]. Notably, the new auxiliary software yielded a significantly lower rate of acentric fragments (ace) [(0.136 ± 0.009)% vs. (0.209 ± 0.020)%, χ2= 17.76, P < 0.001]. However, no statistically significant differences were observed between the result of the two software tools in the rates of dicentrics plus rings (dic + r) and translocations ( P > 0.05). According to the GBZ/T 248-2014 standard, the differences in abnormality rates of chromosomal aberrations between the two groups had no statistically significance ( P > 0.05), with both groups showing an abnormality rate of 0 for ace. Furthermore, the new auxiliary software could double the detection efficiency. Among pre-service radiation workers of various occupations, the differences in the chromosomal aberrations detected using the two software tools exhibited statistical significance ( χ2 = 10.26, P = 0.001). In contrast, the differences in the chromosomal aberrations among in-service and post-service radiation workers had no statistically different significance ( P>0.05). The Poisson regression analysis result demonstrated that the rate of chromosomal aberrations excluding ace was affected by age ( z = 2.73, P = 0.006), while gender, analysis method, service status, and occupation had no impact. Conclusions:The two software tools yielded largely consistent result in detecting chromosomal aberrations induced by exposure to ionizing radiation. Notably, the new auxiliary software can significantly improve detection efficiency, indicating the feasibility of applying it to chromosomal aberration analysis among radiation workers.

Objective:To explore the feasibility of the new auxiliary analysis software in chromosomal aberration analysis of radiation workers during occupational health examinations.Methods:Health examination data of 2 469 radiation workers in Henan province were collected. Manual analysis of chromosomal aberrations in peripheral blood lymphocytes was conducted using the new auxiliary software and the Ikaros software. Then, the chromosomal aberrations detected using both software tools were compared.Results:The new auxiliary software yielded a lower chromosomal aberration rate among radiation workers compared with the Ikaros software [(0.314 ± 0.014)% vs. (0.391 ± 0.022)%, χ2 = 9.24, P = 0.002]. Notably, the new auxiliary software yielded a significantly lower rate of acentric fragments (ace) [(0.136 ± 0.009)% vs. (0.209 ± 0.020)%, χ2= 17.76, P < 0.001]. However, no statistically significant differences were observed between the result of the two software tools in the rates of dicentrics plus rings (dic + r) and translocations ( P > 0.05). According to the GBZ/T 248-2014 standard, the differences in abnormality rates of chromosomal aberrations between the two groups had no statistically significance ( P > 0.05), with both groups showing an abnormality rate of 0 for ace. Furthermore, the new auxiliary software could double the detection efficiency. Among pre-service radiation workers of various occupations, the differences in the chromosomal aberrations detected using the two software tools exhibited statistical significance ( χ2 = 10.26, P = 0.001). In contrast, the differences in the chromosomal aberrations among in-service and post-service radiation workers had no statistically different significance ( P>0.05). The Poisson regression analysis result demonstrated that the rate of chromosomal aberrations excluding ace was affected by age ( z = 2.73, P = 0.006), while gender, analysis method, service status, and occupation had no impact. Conclusions:The two software tools yielded largely consistent result in detecting chromosomal aberrations induced by exposure to ionizing radiation. Notably, the new auxiliary software can significantly improve detection efficiency, indicating the feasibility of applying it to chromosomal aberration analysis among radiation workers.

Objective:To evaluate the effectiveness and safety of transepithelial photorefractive keratectomy (TransPRK) assisted by smart pluse technology (SPT) for the correction of high myopia.Methods:An observational case series study was conducted.Sixty high myopic patients (107 eyes) with spherical equivalent (SE)≥-6.0 D who received TransPRK assisted by SPT from January to December 2016 in Eye Hospital of Wenzhou Medical University were enrolled.Uncorrected visual acuity (UCVA) and best corrected visual acuity (BCVA) of the patients were examined and recorded in logarithm of the minimum angle of resolution (LogMAR) units, and refraction was examined with a subjective refractometer.The healing of corneal epithelium and corneal haze was observed with a slit lamp.Intraocular pressure (IOP) was measured with the non-contact tonometer.Safety index (SI) and efficacy index (EI) were analyzed.The follow-up time was 12 months.This study protocol adhered to the Declaration of Helsinki and was approved by an Ethics Committee of Eye Hospital of Wenzhou Medical University (No.2019-197-k-177). Written informed consent was obtained from each patient prior to any medical examination.Results:The mean epithelial healing time was (3.77±1.02) days.There were statistically significant differences in UCVA and BCVA between before and after surgery ( Z=380.812, 267.313; both at P<0.001). And the 7-day, 6-month, and 12-month postoperative BCVA were better than preoperative BCVA, showing statistically significant differences (all at P<0.05). Mean SI was 1.10±0.12, and mean EI was 1.05±0.17 at 12 months after surgery.There was no significant difference between the attempted SE before surgery (-8.02±1.36)D and the achieved SE at 12 months after surgery (-8.04±1.51)D ( P=0.523). SE in the predictive range within ±0.50 D accounted for 79% (85/107) and that within ±1.0 D accounted for 92% (98/107). The IOP was slightly increased in 3 eyes at 7 days and 7 eyes at 1 month after surgery, respectively, which returned to normal after the use of ophthalmic solution for lowing IOP.The incidence of haze severer than grade 1 was less than 1% (1 eye), and haze gradually disappeared after application of drugs. Conclusions:TransPRK assisted by SPT for high myopia shows good safety, effectiveness and predictability.It is an ideal corneal surface surgery to correct high myopia.

Objective:To explore the value of a deep learning model based on MRI in predicting the methylation status of MGMT in WHO Ⅱ, Ⅲ gliomas.Methods:The clinical and imaging data of 121 patients with WHO grade Ⅱ, Ⅲ glioma confirmed by surgical pathology and molecular pathology in the Second Hospital of Lanzhou University from June 2016 to June 2020 were retrospectively analyzed. Among them, the MGMT promoter was methylated. A total of 78 cases were metabolized and 43 cases were unmethylated. T 2WI and T 1WI enhanced sequence images of 121 cases of WHO Ⅱ, Ⅲ gliomas were collected, and all the images of each patient including the lesion level were selected manually, and were randomly divided into training set and validation set according to 7∶3. The EfficientNet-B3 convolutional neural network was used to build independent prediction models (T 2-net, T 1C-net, TS-net) based on T 2WI, T 1WI enhancement, T 2WI combined with T 1WI enhancement, and the prediction performance of each model was evaluated separately through the ROC curve. Results:The T 2-net model in the validation set presented an accuracy of 72.3%, a sensitivity of 64.7%, a specificity of 73.3%, and an area under the curve (AUC) of 0.72 for predicting the methylation status of the MGMT promoter in WHO Ⅱ, Ⅲ gliomas. The T 1C-net model showed an accuracy of 66.8%, a sensitivity of 68.3%, a specificity of 66.9%, and an AUC of 0.72. The TS-net model showed an accuracy of 81.8%, a sensitivity of 63.1%, a specificity of 85.0%, and AUC of 0.78. Conclusions:The EfficientNet-B3 convolutional neural network based on MRI can predict the methylation status of the MGMT promoter of WHO Ⅱ, Ⅲ gliomas; the TS-net model has the best prediction performance.