TCM believes that spleen deficiency is the root cause of emotional abnormalities in chronic fatigue syndrome (CFS), and clinical treatment often involves the heart, liver and kidney. TCM therapy has a significant efficacy in CFS emotional abnormalities. It is mostly treated with oral administration of TCM, acupuncture, moxibustion and massage therapy. It may play a therapeutic role by improving oxidative stress and immune inflammation, regulating nerve-endocrine, controlling energy metabolism and other ways. It is suggested to establish the syndrome differentiation standard of CFS emotional abnormality in the future, so as to improve the accuracy of syndrome differentiation and treatment; form a perfect treatment guide or expert consensus to guide the standardized application of various internal and external treatment methods; explore objective indicators based on the pathogenesis, and focus on the morphological and functional changes of disease target brain regions with the help of neuroimaging techniques, so as to improve the diagnosis and prognosis evaluation of CFS; based on the guidance of TCM theory, improve the CFS emotional abnormal animal modeling method.

Objective:To explore the relationship between social exclusion, rumination, executive function and mobile phone addiction among college students.Methods:From November to December 2023, a total of 516 college students were investigated by social exclusion questionnaire for undergraduate, ruminative responses scale, the Geurten-questionnaire of executive functioning in Chinese college students and mobile phone addiction tendency scale. SPSS 26.0 statistical software was used for common method bias test, descriptive statistics, correlation analysis, and PROCESS 3.5 macro program was used to test the mediation effect.Results:Social exclusion (31.21±12.69), rumination (42.85±12.38), executive function (71.46±9.41), and college students' mobile phone addiction tendency (43.53±11.74) were all significantly and positively correlated with each other ( r=0.299-0.500, all P<0.01). The direct effect of social exclusion on mobile phone addiction was significant (effect size=0.138, 95% CI=0.048-0.228), accounting for 37.91%(0.138/0.364) of the total effect. Rumination had a mediating effect between social exclusion and mobile phone addiction (effect size=0.053, 95% CI=0.001-0.112), accounting for 14.56%(0.053/0.364) of the total effect. Executive function mediates the relationship between social exclusion and mobile phone addiction (effect size=0.137, 95% CI=0.091-0.188), accounting for 37.64%(0.137/0.364) of the total effect.Rumination and executive function has a chain mediating effect between social exclusion and mobile phone addiction (effect size=0.036, 95% CI=0.016-0.061), accounting for 9.89%(0.036/0.364) of the total effect. Conclusion:Social exclusion can directly affect mobile phone addiction in college students and can also influence mobile phone addiction in college students through the independent mediating effects of rumination and executive function, as well as the chain mediating effect of rumination and executive function.

Objective:To explore the mediating effect of experiential avoidance and emotional eating between intolerable uncertainty and life satisfaction of college students.Methods:From October to December 2021, a total of 890 college students in the Beijing-Tianjin-Hebei region were tested by the intolerable uncertainty scale (simplified version), the acceptance action scale second edition, the Dutch eating behavior questionnaire and the life satisfaction scale. All data processing and analysis were preformed by SPSS 22.0 software, and the mediating effect was tested by Pearson correlation analysis and Bootstrap analysis.Results:The intolerable uncertainty score was (26.43±7.64), the experiential avoidance score was (22.63±9.67), the emotional eating score was (26.43 ±11.83), and the life satisfaction score was (16.74±6.03). Intolerable uncertainty was significantly and negatively correlated with life satisfaction( r=-0.76, P<0.01), and was significantly and positively correlated with experience avoidance and emotional eating( r=0.66, 0.78, both P<0.01). Experience avoidance was significantly and positively correlated with emotional eating( r=0.70, P<0.01), and was significantly and negatively correlated with life satisfaction( r=-0.62, P<0.01). Emotional eating was significantly and negatively correlated with life satisfaction( r=-0.68, P<0.01). Intolerable uncertainty affects life satisfaction through four paths.The direct effect value of intolerable uncertainty on life satisfaction was -0.53, accounting for 70.23% of the total effect. The separate mediating effect value of experience avoidance was -0.11, accounting for 50.00% of the total indirect effect.The separate mediating effect value of emotional eating was -0.08, accounting for 36.36% of the total indirect effect, and the chain mediating effect value of experience avoidance and emotional eating was -0.03, accounting for 13.64% of the total indirect effect. Conclusion:Intolerable uncertainty can directly affect life satisfaction of college students and indirectly through experiencing avoidance and emotional eating.

Objective:To explore the mediating roles of rumination and avoidance coping between information anxiety and suicidal ideation.Methods:In March 2022, a total of 896 college students were surveyed by the information anxiety scale(IAS), ruminative responses scale(RRS), coping style questionnaire(CSQ)and self-rating idea of suicidal ideation scale(SIOSS). The ANOVA analysis, Pearson correlation analysis and mediating effect analysis were performed by the SPSS 22.0 software.Results:The detection rate of suicidal ideation among college students was 9.15%(82/896). The information anxiety score was(73.84±17.29), the rumination score was(47.73±12.16), the avoidance coping score was(3.76±2.52), and the suicidal ideation score was(5.41±4.09). Information anxiety was significantly positively correlated with rumination, avoidance coping and suicidal ideation( r=0.49, 0.36, 0.37, all P<0.05). Rumination was significantly positively correlated with avoidance coping and suicidal ideation( r=0.42, 0.59, both P<0.05). There was a significantly positive correlation between avoidance coping and suicidal ideation( r=0.45, P<0.05). Information anxiety affected suicidal ideation of college students through four paths.The direct effect value of information anxiety on suicidal ideation was 0.06, accounting for 16.67% of the total effect. The effect values of the separate mediating effect of rumination and avoid coping were 0.22 and 0.04, and accounting for 61.11% and 11.11% of the total effect respectively. The chain mediating effect value of rumination and avoid coping was 0.04, accounting for 11.11% of the total effect. Conclusion:Information anxiety can directly affect suicidal ideation of college students and indirectly affect suicidal ideation through rumination and avoidance coping.

At present, China has entered a deeply aging society, and preparing for elderly care actively can respond to the aging population. This article reviews the theoretical basis, research status, evaluation tools, and influencing factors of elderly care preparation, aiming to provide reference for deepening the elderly care preparation work and achieving healthy aging.

Abstract In recent years, the overall incidence of scoliosis in children and adolescents in China is on the rise, and it has become the third largest "killer" affecting the health of children and adolescents in China after obesity and myopia. The dysfunction caused by spinal deformity has no obvious pathological manifestations or clinical symptoms in children and adolescents (except for severe scoliosis). It is easy to be ignored in the early stage, but if it is not intervened in time, this will cause serious damage to the long term prognosis and quality of life of the patients. Therefore, through early scoliosis screening, we can effectively monitor the spinal health status of children and adolescents in China, ensure timely diagnosis of the disease, timely intervention (brace and other conservative treatment), and play the role of early prevention. Avoid further deterioration of scoliosis and surgical intervention. This article will focus on the research progress of screening and conservative treatment of scoliosis.

Objective:To explore the short-term outcomes of a 3D printed trabecular block cage to assist posterior internal fixation for the treatment of patients with basilar invagination and atlantoaxial dislocation.Methods:Between June 2017 and February 2019, 12 patients with basilar invagination and atlantoaxial dislocation underwent atlantoaxial distraction and posterior internal fixation at Department of Orthopedics, The First Affiliated Hospital to Zhengzhou University. They were 5 males and 7 females, aged from 34 to 62 years (average, 45.6 years). 3D printed cages were inserted intraoperatively between the joints of the atlantoaxial lateral mass. The atlanto-dental interval interval (ADI), cervico-medullary angle (CMA) and distance from tip of the odontoid process to Chamberlain's line (DOCL) and the Japanese Orthopedic Association (JOA) scale were compared between preoperation and 12 months postoperation to observe the fusion of the joints of the atlantoaxial lateral mass.Results:Operation went on uneventfully in all the 12 patients. Operation time averaged 116.5 min (from 85 to 190 min), fluoroscopy frequency 9.4 times (from 6 to 21 times), and intraoperative bleeding 82.3 mL (from 50 to 210 mL). No such postoperative complications occurred as cerebrospinal leak, cerebral infarction, or breakage, displacement or loosening of implants. All patients were followed up for 18 to 42 months (mean, 26.3 months). Their preoperative JOA, ADI, CMA and DOCL [8.33±0.98, (8.66±1.64) mm, 119.63°±4.15° and (9.66±2.15) mm] were significantly improved to 14.17±1.03, (2.63±0.59) mm, 153.76°±7.88° and (2.07±0.69) mm ( P<0.05) at 12 months postoperation. Bony fusion was achieved in all the operative segments. Conclusion:In the treatment of patients with basilar invagination and atlantoaxial dislocation, a 3D-printed trabecular block cage can be used to assist posterior internal fixation to achieve satisfactory reduction and maintain the height of joint space, leading to satisfactory short-term outcomes.

Objective:To study the association between histopathological features and HER2 overexpression/amplification in breast cancers using deep learning algorithms.Methods:A total of 345 HE-stained slides of breast cancer from 2012 to 2018 were collected at the China-Japan Friendship Hospital, Beijing, China. All samples had accurate diagnosis results of HER2 which were classified into one of the 4 HER2 expression levels (0, 1+, 2+, 3+). After digitalization, 204 slides were used for weakly supervised model training, and 141 used for model testing. In the training process, the regions of interest were extracted through cancer detected model and then input to the weakly supervised classification model to tune the model parameters. In the testing phase, we compared performance of the single- and double-threshold strategies to assess the role of the double-threshold strategy in clinical practice.Results:Under the single-threshold strategy, the deep learning model had a sensitivity of 81.6% and a specificity of 42.1%, with the AUC of 0.67 [95% confidence intervals (0.560,0.778)]. Using the double-threshold strategy, the model achieved a sensitivity of 96.3% and a specificity of 89.5%.Conclusions:Using HE-stained histopathological slides alone, the deep learning technology could predict the HER2 status using breast cancer slides, with a satisfactory accuracy. Based on the double-threshold strategy, a large number of samples could be screened with high sensitivity and specificity.

Objective:Peripheral nerve invasion (PNI) is associated with local recurrence and poor prognosis in patients with advanced gastric cancer. A risk-assessment model based on preoperative indicators for predicting PNI of gastric cancer may help to formulate a more reasonable and accurate individualized diagnosis and treatment plan.Methods:Inclusion criteria: (1) electronic gastroscopy and enhanced CT examination of the upper abdomen were performed before surgery; (2) radical gastric cancer surgery (D2 lymph node dissection, R0 resection) was performed; (3) no distant metastasis was confirmed before and during operation; (4) postoperative pathology showed an advanced gastric cancer (T2-4aN0-3M0), and the clinical data was complete. Those who had other malignant tumors at the same time or in the past, and received neoadjuvant radiochemotherapy or immunotherapy before surgery were excluded. In this retrospective case-control study, 550 patients with advanced gastric cancer who underwent curative gastrectomy between September 2017 and June 2019 were selected from the Affiliated Hospital of Qingdao University for modeling and internal verification, including 262 (47.6%) PNI positive and 288 (52.4%) PNI negative patients. According to the same standard, clinical data of 50 patients with advanced gastric cancer who underwent radical surgery from July to November 2019 in Qingdao Municipal Hospital were selected for external verification of the model. There were no statistically significant differences between the clinical data of internal verification and external verification (all P>0.05). Univariate analysis and multivariate logistic regression analysis were used to determine the independent risk factors for PNI in advanced gastric cancer, and the clinical indicators with statistically significant difference were used to establish a preoperative nomogram model through R software. The Bootstrap method was applied as internal verification to show the robustness of the model. The discrimination of the nomogram was determined by calculating the average consistency index (C-index). The calibration curve was used to evaluate the consistency of the predicted results with the actual results. The Hosmer-Lemeshow test was used to examine the goodness of fit of the discriminant model. During external verification, the corresponding C-index index was also calculated. The area under ROC curve (AUC) was used to evaluate the predictive ability of the nomogram in the internal verification and external verification groups. Results:A total of 550 patients were identified in this study, 262 (47.6%) of which had PNI. Multivariate logistic regression analysis revealed that carcinoembryonic antigen level ≥ 5 μg/L (OR=5.870, 95% CI: 3.281-10.502, P<0.001), tumor length ≥5 cm (OR=5.539,95% CI: 3.165-9.694, P<0.001), mixed Lauren classification (OR=2.611, 95%CI: 1.272-5.360, P=0.009), cT3 stage (OR=13.053, 95% CI: 5.612-30.361, P<0.001) and the presence of lymph node metastasis (OR=4.826, 95% CI: 2.729-8.533, P<0.001) were significant independent risk factors of PNI in advanced gastric cancer (all P<0.05). Based on these results, diffused Lauren classification and cT4 stage were included to establish a predictive nomogram model. CEA ≥ 5 μg/L was for 68 points, tumor length ≥ 5 cm was for 67 points, mixed Lauren classification was for 21 points, diffused Lauren classification was for 38 points, cT3 stage was for 75 points, cT4 stage was for 100 points, and lymph node metastasis was for 62 points. Adding the scores of all risk factors was total score, and the probability corresponding to the total score was the probability that the model predicted PNI in advanced gastric cancer before surgery. The internal verification result revealed that the AUC of nomogram was 0.935, which was superior than that of any single variable, such as CEA, Lauren classification, cT stage, tumor length and lymph node metastasis (AUC: 0.731, 0.595, 0.838, 0.757 and 0.802, respectively). The external verification result revealed the AUC of nomogram was 0.828. The C-ndex was 0.931 after internal verification. External verification showed a C-index of 0.828 from the model. The calibration curve showed that the predictive results were good in accordance with the actual results ( P=0.415). Conclusion:A nomogram model constructed by CEA, tumor length, Lauren classification (mixed, diffuse), cT stage, and lymph node metastasis can predict the PNI of advanced gastric cancer before surgery.

Objective:Peripheral nerve invasion (PNI) is associated with local recurrence and poor prognosis in patients with advanced gastric cancer. A risk-assessment model based on preoperative indicators for predicting PNI of gastric cancer may help to formulate a more reasonable and accurate individualized diagnosis and treatment plan.Methods:Inclusion criteria: (1) electronic gastroscopy and enhanced CT examination of the upper abdomen were performed before surgery; (2) radical gastric cancer surgery (D2 lymph node dissection, R0 resection) was performed; (3) no distant metastasis was confirmed before and during operation; (4) postoperative pathology showed an advanced gastric cancer (T2-4aN0-3M0), and the clinical data was complete. Those who had other malignant tumors at the same time or in the past, and received neoadjuvant radiochemotherapy or immunotherapy before surgery were excluded. In this retrospective case-control study, 550 patients with advanced gastric cancer who underwent curative gastrectomy between September 2017 and June 2019 were selected from the Affiliated Hospital of Qingdao University for modeling and internal verification, including 262 (47.6%) PNI positive and 288 (52.4%) PNI negative patients. According to the same standard, clinical data of 50 patients with advanced gastric cancer who underwent radical surgery from July to November 2019 in Qingdao Municipal Hospital were selected for external verification of the model. There were no statistically significant differences between the clinical data of internal verification and external verification (all P>0.05). Univariate analysis and multivariate logistic regression analysis were used to determine the independent risk factors for PNI in advanced gastric cancer, and the clinical indicators with statistically significant difference were used to establish a preoperative nomogram model through R software. The Bootstrap method was applied as internal verification to show the robustness of the model. The discrimination of the nomogram was determined by calculating the average consistency index (C-index). The calibration curve was used to evaluate the consistency of the predicted results with the actual results. The Hosmer-Lemeshow test was used to examine the goodness of fit of the discriminant model. During external verification, the corresponding C-index index was also calculated. The area under ROC curve (AUC) was used to evaluate the predictive ability of the nomogram in the internal verification and external verification groups. Results:A total of 550 patients were identified in this study, 262 (47.6%) of which had PNI. Multivariate logistic regression analysis revealed that carcinoembryonic antigen level ≥ 5 μg/L (OR=5.870, 95% CI: 3.281-10.502, P<0.001), tumor length ≥5 cm (OR=5.539,95% CI: 3.165-9.694, P<0.001), mixed Lauren classification (OR=2.611, 95%CI: 1.272-5.360, P=0.009), cT3 stage (OR=13.053, 95% CI: 5.612-30.361, P<0.001) and the presence of lymph node metastasis (OR=4.826, 95% CI: 2.729-8.533, P<0.001) were significant independent risk factors of PNI in advanced gastric cancer (all P<0.05). Based on these results, diffused Lauren classification and cT4 stage were included to establish a predictive nomogram model. CEA ≥ 5 μg/L was for 68 points, tumor length ≥ 5 cm was for 67 points, mixed Lauren classification was for 21 points, diffused Lauren classification was for 38 points, cT3 stage was for 75 points, cT4 stage was for 100 points, and lymph node metastasis was for 62 points. Adding the scores of all risk factors was total score, and the probability corresponding to the total score was the probability that the model predicted PNI in advanced gastric cancer before surgery. The internal verification result revealed that the AUC of nomogram was 0.935, which was superior than that of any single variable, such as CEA, Lauren classification, cT stage, tumor length and lymph node metastasis (AUC: 0.731, 0.595, 0.838, 0.757 and 0.802, respectively). The external verification result revealed the AUC of nomogram was 0.828. The C-ndex was 0.931 after internal verification. External verification showed a C-index of 0.828 from the model. The calibration curve showed that the predictive results were good in accordance with the actual results ( P=0.415). Conclusion:A nomogram model constructed by CEA, tumor length, Lauren classification (mixed, diffuse), cT stage, and lymph node metastasis can predict the PNI of advanced gastric cancer before surgery.