Cancer-related depression (CRD) is a common pathological depression in the diagnosis and treatment of malignant tumors and an important factor affecting the progression and treatment of tumor diseases. Abdominal vibration therapy was developed from Professor Zang's loose vibration method. It is a set of techniques that mainly operates by vibrating the Shenque point; dredging meridians; and rubbing, pushing, and holding the abdomen. This therapy has unique advantages in the treatment of emotional diseases likely because it can stimulate the abdomen; tonify the spleen and stomach; and regulate the gut organs, the qi mechanism, and vitality. On the basis of the structure of the brain-gut axis, it regulates the inflammatory response then realizes the purpose of intervening in CRD.

Objective To perform on-site calibration of high-pressure ionization chambers and NaI(Tl) γ spectrometers in state-controlled atmospheric radiation environment automatic continuous monitoring stations and verify the reliability of the online radiation environment monitoring system. Methods ¹³⁷Cs, ⁶⁰Co, and ²⁴¹Am were used as γ reference radiation sources to measure the metrological performance of high-pressure ionization chambers in nine state-controlled atmospheric radiation environment automatic monitoring stations in Hubei Province, China. The performance metrics included background radiation, response, and repeatability. Additionally, the correlation between dose rate and humidity was analyzed, and the energy resolution and activity response of NaI(Tl) γ spectrometers were measured. Results Among the nine state-controlled atmospheric radiation environment automatic monitoring stations, the background radiation of high-pressure ionization chambers ranged from 58.2 nGy/h to 82.6 nGy/h. The response of the high-pressure ionization chambers ranged from 0.94 to 1.08, fulfilling the requirement of 1.0 ± 0.2. The repeatability of high-pressure ionization chambers ranged from 0.43% to 3.80%, satisfying the requirement of not exceeding 10%. A significant correlation was observed between dose rate and humidity, with a correlation coefficient of 0.4476. For NaI(Tl) γ spectrometers, the energy resolution ranged from 6.8% to 7.9%, fulfilling the requirement of not exceeding 9% for the 661.7 keV energy peak of ¹³⁷Cs. The NaI(Tl) γ spectrometers showed 1.4% to 1.8% s⁻¹·Bq⁻¹ activity response to ²⁴¹Am and 6.6‰ to 8.4‰ s⁻¹·Bq⁻¹ activity response to ⁶⁰Co. Conclusion The online monitoring systems in the nine state-controlled atmospheric radiation environment automatic monitoring stations are stable and reliable, providing accurate radiation environment monitoring data for public awareness.

Objective:To construct and analyze the visual nomogram predictive model for the prognosis of elderly advanced lung adenocarcinoma patients after surgery based on the Surveillance, Epidemiology, and End Results (SEER) database.Methods:SEER*Stat8.4.0.1 software was used to screen out the data from 17 register in SEER database between 2000 and 2019, and finally 4 453 lung adenocarcinoma patients aged ≥ 65 years who underwent surgical treatment and were diagnosed as stage Ⅲ and Ⅳ according to the 7th edition of the American Joint Committee on Cancer (AJCC) staging criteria were enrolled. The data were randomly divided into the training set (3 117 cases) and the validation set (1 336 cases) in a 7:3 ratio; the epidemilogical data and clinicopathological characteristics of the two groups were compared. LASSO regression was used for data dimensionality reduction to select the best predictors from the prognostic factors of patients. Cox proportional risk model was used to perform univariate and multivariate analyses of the screened variables, and based on R software rms package and the prognostic independent risk factors, the nomogram was constructed to predict the 1-, 3-, and 5-year cancer-specific survival (CSS) rates of the patients. The validation set was validated by using Bootstrap method with 1 000 equal repeated samples with playback, and the accuracy of the nomogram model was verified by using the C-index, receiving operating characteristic (ROC) curves and calibration curves.Results:There were no statistically significant differences in age, gender, race, tumor location, Grade grading, surgery methods, the number of lymph node dissection, radiotherapy, tumor diameter, tumor metastasis, marriage, living condition, TNM staging, radiochemotherapy of training set and validation set (all P > 0.05). In training set, 18 variables were included into LASSO regression analysis and were performed with dimensionality reduction; ultimately, 11 optimal predictive variables were selected, including age ≥ 85 years ( HR = 2.34, 95% CI: 1.803-3.037, P < 0.01), male ( HR = 1.326, 95% CI: 1.228-1.432, P < 0.01), Grade grading Ⅲ-Ⅳ ( HR = 1.333, 95% CI: 0.844-2.105, P < 0.01), undissected lymph nodes ( HR = 2.261, 95% CI: 2.023-2.527, P < 0.01), tumor diameter ≥3.7 cm ( HR = 1.445, 95% CI: 1.333-1.566, P < 0.01), bone metastasis ( HR = 1.535, 95% CI: 1.294-1.819, P < 0.01), brain metastasis ( HR = 1.308, 95% CI: 1.117-1.532, P < 0.01), lung metastasis ( HR = 1.229, 95% CI: 1.056-1.431, P = 0.01), living in rural areas ( HR = 1.215, 95% CI: 1.084-1.363, P < 0.01), TNM staging Ⅳ ( HR = 1.155, 95% CI: 1.044-1.278, P = 0.01), postoperative radiotherapy ( HR = 1.148, 95% CI: 1.054-1.250, P < 0.01); lung adenocarcinoma patients with the above 11 factors had worse prognosis. Based on the variables, the nomogram predictive model was constructed to predict 1-, 3-, and 5-year CSS rates of elderly advanced lung adenocarcinoma patients. Bootstrap method was used for repeated sampling for 1 000 times to verify the modeling effect of nomogram. In the model group, C-index was 0.654 (95% CI: 0.641-0.668), 0.666 (95% CI: 0.646-0.685), respectively in the training set and the validation set. The nomogram was drawn to predict ROC curves of 1-, 3-, and 5-year CSS rates for elderly advanced lung adenocarcinoma patients after operation in the training set and validation set; the area under the curve (AUC) of 1-year, 3-year, and 5-year CSS rates was 0.730 (95% CI: 0.708-0.754) and 0.689 (95% CI: 0.672-0.710), 0.687 (95% CI: 0.668-0.711) and 0.731 (95% CI: 0.697-0.765), 0.712 (95% CI:0.684-0.740) and 0.714 (95% CI: 0.683-0.745), respectively in the training and validation sets. The calibration curve showed a high consistency between the predicted probability of the model and the actual probability. Conclusions:The nomogram model constructed by optimal predictive variables for predicting the prognosis of elderly advanced lung adenocarcinoma patients after surgery may be a convenient tool for survival prediction of these patients.

Objective To propose a novel algorithm model based on YOLOv7 for detecting small lesions in ultrasound images of hepatic cystic echinococcosis.Methods The original feature extraction backbone was replaced with a lightweight feature extraction backbone network GhostNet for reducing the quantity of model parameters.To address the problem of low detection accuracy when the evaluation index CIoU of YOLOv7 was used as a loss function,ECIoU was substituting for CIoU,which further improved the model detection accuracy.Results The model was trained on a self-built dataset of small lesion ultrasound images of hepatic cystic echinococcosis.The results showed that the improved model had a size of 59.4 G and a detection accuracy of 88.1%for mAP@0.5,outperforming the original model and surpassing other mainstream detection methods.Conclusion The proposed model can detect and classify the location and category of lesions in ultrasound images of hepatic cystic echinococcosis more efficiently.

Objective:To analyze the dynamic development of physical, psychological, and cognitive degenerative multimorbidity among middle-aged and older Chinese adults (≥45 years old) while estimating the longitudinal association between socioeconomic status (SES) and the progression of multimorbidity.Methods:Based on data from the China Health and Retirement Longitudinal Study (2011-2020), the Sankey diagram was used to show the dynamic development of physical, psychological, and cognitive degenerative multimorbidity from 2011 to 2020. SES was constructed based on the level of education and total household wealth. Logistic regression was used to estimate OR and 95% CI to evaluate the association between SES and the progression of multimorbidity. Results:Of the 5 393 participants included, 4 484 (83.14%) of them developed new diseases, and the prevalence of physical, psychological, and cognitive degenerative multimorbidity increased from 38.04% to 74.23%. Compared to those with no reported disorders at baseline, participants with psychological disorder (for newly developed physical-cognitive multimorbidity: OR=4.59,95% CI: 2.89-7.29), cognitive disorder (for newly developed physical-psychological multimorbidity: OR=2.24,95% CI: 1.40-3.60), or their multimorbidity at baseline were more likely to progress to physical, psychological, and cognitive degenerative multimorbidity. After adjusting covariates, individuals with low SES were more likely to develop physical diseases ( OR=1.45, 95% CI: 1.11-1.89), cognitive disorder ( OR=1.84, 95% CI: 1.16-2.91), physical-psychological multimorbidity ( OR=1.87, 95% CI: 1.37-2.56), physical-cognitive multimorbidity ( OR=3.58, 95% CI: 2.54-5.06), psychological-cognitive multimorbidity ( OR=5.66, 95% CI: 3.04-10.55), and physical-psychological-cognitive multimorbidity ( OR=3.21, 95% CI: 2.06-5.01) in comparison to those with high SES. There is a dose-response relationship between SES and the multimorbidity progression (all trend P<0.001). Conclusions:The prevalence of physical, psychological, and cognitive degenerative multimorbidity increased significantly among middle-aged and older Chinese adults. Lower SES was associated with multiple patterns of physical, psychological, and cognitive disorders progression.

Objective To investigate the risk factors for pediatric acute perforation appendicitis,and to construct a nomogram predictive model and conduct the verification.Methods A total of 426 children patients with appendectomy in this hospital from June 30,2020 to June 30,2022 were selected as the study subjects 340 children with acute appendicitis admitted to the hospital from 30 June 2020 to 28 February 2022 were the training set and 86 children patients with appendicitis hospitalized in this hospital from March 1,2022 to June 30,2022 conducted the external validation(verification set).The univariate and multivariate logistic regression models were employed to analyze the independent risk factors of pediatric acute perforation appendicitis.The nomograms predictive model was constructed.The receiver operating characteristic(ROC)curve and calibra-tion curve were used to evaluate the predictive efficiency of the model.The decision curve analysis(DCA)was used to evaluate the application value of the model.Results Of the 426 children,198 were perforated and 228 were not perforated.The univariate and multivariate logistic regression analyses revealed that elevated C-reac-tive protein(CRP),presence of stercorolith in appendiceal cavity,time of onset to visiting hospital ≥2 d and body temperature ≥37.3 ℃ were the independent risk factors for pediatric acute perforation appendicitis(P＜0.05).The Hosmer-Lemeshow test demonstrated that the nomogram predictive model had good fitting(P=0.869),and the area under the curve(AUC)for the training and validation sets were 0.808 and 0.860 respectively,showing the good predictive ability of the model.The calibration curve closely approach the ideal diagonal.The model showed good discrimination,consistency and accuracy.The DC A revealed that the curve was far away from oblique and horizontal lines,and the model had good clinical practicability.Conclusion The constructed nomogram model of pediatric acute perforation appendicitis has good predictive ability and may help clinic to identify as early as possible.

Objective To apply the improved DeepLabV3+based image semantic segmentation algorithm to the ultrasound image processing for hepatic cystic echinococcosis,thereby achieving automatic segmentation and detection of hepatic echinococcosis lesions,and improving clinical diagnostic efficiency.Methods DeepLabV3+based image semantic segmentation network was employed as the basic method,and the following improvements were made.To address the issues of high computational complexity,high memory consumption,difficulty in deploying on embedded platforms with limited computing power,and difficulty in fully utilizing multi-scale information when extracting image feature information,the original backbone network Xception of the model was replaced with MobileNetV2 for obtaining a lightweight model framework.Additionally,efficient channel attention was applied to underlying features for reducing computational complexity and improving the clarity of target boundaries;and finally,Dice Loss was introduced into the model to alleviate the problem of the model focusing more on the background area and ignoring the foreground area containing the target.Results Validation was conducted on 5 lesion types in the self-built VOC2007 dataset of hepatic cystic echinococcosis.Experimental results showed that the improved model achieved a mean intersection over union of 73.8 and a mean pixel accuracy of 83.5,indicating that the model can predict more precise semantic segmentation results and effectively optimize model complexity and segmentation accuracy.

Cranial defects may result from clinical brain tumor surgery or accidental trauma. The defect skulls require hand-designed skull implants to repair. The edge of the skull implant needs to be accurately matched to the boundary of the skull wound with various defects. For the manual design of cranial implants, it is time-consuming and technically demanding, and the accuracy is low. Therefore, an informer residual attention U-Net (IRA-Unet) for the automatic design of three-dimensional (3D) skull implants was proposed in this paper. Informer was applied from the field of natural language processing to the field of computer vision for attention extraction. Informer attention can extract attention and make the model focus more on the location of the skull defect. Informer attention can also reduce the computation and parameter count from N ² to log( N). Furthermore,the informer residual attention is constructed. The informer attention and the residual are combined and placed in the position of the model close to the output layer. Thus, the model can select and synthesize the global receptive field and local information to improve the model accuracy and speed up the model convergence. In this paper, the open data set of the AutoImplant 2020 was used for training and testing, and the effects of direct and indirect acquisition of skull implants on the results were compared and analyzed in the experimental part. The experimental results show that the performance of the model is robust on the test set of 110 cases fromAutoImplant 2020. The Dice coefficient and Hausdorff distance are 0.940 4 and 3.686 6, respectively. The proposed model reduces the resources required to run the model while maintaining the accuracy of the cranial implant shape, and effectively assists the surgeon in automating the design of efficient cranial repair, thereby improving the quality of the patient's postoperative recovery.
Humans ; Computer-Aided Design ; Skull/surgery* ; Prostheses and Implants ; Head

Objective:To establish silicone cartilage models of donor-sites for the microtia patients by using digital technology, and to explore the application of surgical simulation in auricular reconstruction.Methods:From June 2018 to October 2019, 19 congenital microtia patients underwent thoracic CT scans and following three-dimensional costal cartilage imaging with Mimics software at the Nanfang Hospital, Southern Medical University. Among these patients, 16 were males and 3 were females. The mean age of patients was 16 years (range 8 to 35 years). Silicon cartilage models were produced by 3D printing and used for surgical planning and preoperative simulation in ear framework fabrication. Cartilaginous framework was sculptured according to the simulation during operation. Patients were followed up for a minimum of six months to evaluate the size, outline, height and auriculocephalic angle of the reconstructed ear. The satisfactory outcomes of the patients were scored according to a 5-point Likert scale.Results:All the patients received the surgical simulation and sculpture training with silicone cartilage models before operation. Auricular reconstruction was completed successfully according to the simulation. The duration of sculpture was shortened to 1-1.5 hours. There were no serious complications, such as hematoma, inflammation, skin necrosis and framework exposure. The contour of reconstructed ear was natural and clear over a 6 months follow-up, and all the patients were satisfied with their surgical outcomes.Conclusions:With the application of digital technology and silicone cartilage models by 3D printing to the surgical planning and training in microtia patients, patient-specific framework is fabricated with precisely assembling, which not only shortens the operation time, but also provides the unexperienced surgeons with a safe and effective training of ear framework fabrication.

Objective:To investigate the application of three-dimensional digital technique in customized ear framework fabrication for auricular reconstruction.Methods:From July 2018 to October 2019, the patients with microtia who underwent ear reconstruction in the Department of Plastic and Aesthetic Surgery, Nanfang Hospital, Southern Medical University were enrolled. Each patient with unilateral microtia underwent auricular CT scan and preoperative analysis and ear framework design were carried out with Mimics software 18.0. The two-dimension(2D) ear films and three-dimension(3D) silicon models were produced by 1∶1 2D printing and 3D printing, respectively. Microtia reconstruction was performed according to the guide of the models, patients were followed up over a six-month period to evaluate the size, outline, height and auriculocephalic angle of the reconstructed ear. The satisfactory outcomes of the patients were scored according to a 5-point Likert scale.Results:A total of 15 patients were included in this study, including 11 males and 4 females, aged 8-27 years, with an average of 15.5 years old. All the 15 patients completed the surgical planning and ear reconstruction successfully, without major complications, such as hematomas, inflammation, skin necrosis and framework exposure. The costal cartilage frameworks were very similar to the printed 3D models in size and contour. Comparison between the two sides was made at six months postoperatively. The reconstructed ear was much the same as that of contralateral side, and all patients were satisfied with their reconstructed ear outcomes with average score of 4.4.Conclusions:With the application of digital technique for pre-surgical planning in microtia reconstruction patients, ear templates were produced from 2D to 3D, and the correction of microtia was changed from standard auricular reconstruction to personalized auricular reconstruction, with a great improvement of the precision in ear framework fabrication.