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 investigate the distribution of solute carrier organic anion transporter family member 1B1(SLCO1B1) and apolipoprotein E(ApoE) gene polymorphisms in the patients of Han ethnic group with cardiovascular and cerebrovascular diseases from Anhui Province, in order to provide the basis for the individualized therapy of statins in clinical practice. Methods: 924 Han patients with cardiovascular and cerebrovascular diseases were selected. The SLCO1B1 and ApoE genotypes of the patients were detected by polymerase chain reaction-fluorescent probe method, and their distribution was compared among different genders and other regions in China. Results: Seven SLCO1B1 gene subtypes were detected in 924 patients, including *1a/*1b(33.01%),*1b/*1b(41.45%), *1b/*15(12.34%), *1a/*1a(7.03%), *1a/*15(5.52%), *15/*15(0.54%) and *5/*5(0.11%), without detection of the two gene subtypes of *1a/*5 and *5/*15; the normal metabolic genotype I of SLCO1B1(*1a/*1a, *1a/*1b, *1b/*1b) accounted for the highest proportion in this population(81.49%), the intermediate metabolic genotype II and the weak metabolic genotype III of SLCO1B1 accounted for 17.86% and 0.65% respectively; six ApoE gene subtypes were detected, including E3/E3(66.78%), E3/E4(19.37%), E2/E3(9.63%), E4/E4(1.84%), E2/E4(1.73%) and E2/E2(0.65%); the E3 mass genotype(E2/E4, E3/E3) accounted for the highest proportion in this population(68.51%); there was no significant difference in the distribution of SLCO1B1 and ApoE genes between different genders; there was no significant difference in the distribution of SLCO1B1 between the Han population from Anhui and the South China and Central China, but a significant difference was found between the Anhui Han population and the Southwest China(P<0.05); the distribution of ApoE in the Anhui Han population demonstrated no statistically significant variation from those in South China and Southwest China, whereas significant differences were observed in comparison with Central China(P<0.05). Conclusion In the Han population with cardiovascular and cerebrovascular diseases in Anhui, the distributions of SLCO1B1 and ApoE gene polymorphisms show no significant gender differences but exhibit regional variations. These populations are predominantly characterized by class I normal metabolic genotype(SLCO1B1) and E3 mass genotypes(ApoE), indicating a higher tolerance to statin dosages and normal therapeutic efficacy in this cohort.

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 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 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 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.

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.

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.