Objective To establish a method for rapid detection of tramadol in urine by liquid-liquid extraction（LLE）-surface-enhanced Raman spectroscopy （SERS）. Methods Tramadol was extracted from urine with chloroform∶isopropyl alcohol （9∶1） extractant and detected in urine samples by enhanced Raman spectroscopy （wavelength 785 nm）. Results The quantitative curve of tramadol was Y=204.35 X−465.62, r=0.9952, and the linear range was 1-100 μg/ml. The detection limit of tramadol by this method （S/N=3） was 0.53 μg/ml. The sensitivity of SERS was higher than that of conventional methods, and it had reasonable reproducibility. Conclusion This method is simple, efficient and economical, and can be used for qualitative and quantitative analysis of tramadol personalized medicine.

Objective:To establish three machine learning prediction models based on CT imaging characteristics of papillary thyroid carcinoma (PTC) , and use SHAP (shapley additive explanations) analysis to investigate the contribution of each CT image features in the best model.Methods:CT imaging features in 426 cases of 440 PTCs confirmed pathologically from Jan. 2016 to Jan. 2021 at the affiliated Hangzhou First People’s Hospital of Westlake University Medical School were retrospectively analyzed. compared with 467 cases of 528 nodular goiter (NG) , evaluating the distribution of four CT characteristics: cookie bite sign, enhanced range of narrowing/blur (ERNB) , microcalcifications, and irregular shape. We split the data into 8∶2 ratio for training and testing sets, then constructed three machine learning models using XGBoost, RF, and SVM. Based on AUC, accuracy, F1 score, and other metrics, we selected the best model. Lastly, we used SHAP values to assess each CT feature’s contribution and positive/negative effects on the model.Results:Among 440 PTC and 528 NG nodules, CT features like cookie bite sign, ERNB, microcalcifications, and irregular shape occurred in 326 and 30 ( χ 2=483.05, P<0.001) , 363 and 106 ( χ 2=374.45, P<0.001) , 158 and 53 ( χ 2=94.24, P<0.001) , and 354 and 52 ( χ 2=491.34, P<0.001) nodules, respectively. The machine learning models built using XGBoost, RF, and SVM had AUC, accuracy, and F1 scores ranging from 0.884~0.925, 0.867~0.873, and 0.844~0.854 respectively on the training set. On the test set, the scores ranged from 0.869~0.923, 0.845~0.871, and 0.803~0.845. Among them, the XGBoost model demonstrated the highest diagnostic performance on the test set. Among the four CT features, irregular shape had the highest absolute SHAP value, positively contributing to PTC diagnosis. Conclusion:XGBoost model showed the highest PTC diagnostic performance. Irregular shape had the greatest positive impact on PTC diagnosis.

Objective:To establish three machine learning prediction models based on CT imaging characteristics of papillary thyroid carcinoma (PTC) , and use SHAP (shapley additive explanations) analysis to investigate the contribution of each CT image features in the best model.Methods:CT imaging features in 426 cases of 440 PTCs confirmed pathologically from Jan. 2016 to Jan. 2021 at the affiliated Hangzhou First People’s Hospital of Westlake University Medical School were retrospectively analyzed. compared with 467 cases of 528 nodular goiter (NG) , evaluating the distribution of four CT characteristics: cookie bite sign, enhanced range of narrowing/blur (ERNB) , microcalcifications, and irregular shape. We split the data into 8∶2 ratio for training and testing sets, then constructed three machine learning models using XGBoost, RF, and SVM. Based on AUC, accuracy, F1 score, and other metrics, we selected the best model. Lastly, we used SHAP values to assess each CT feature’s contribution and positive/negative effects on the model.Results:Among 440 PTC and 528 NG nodules, CT features like cookie bite sign, ERNB, microcalcifications, and irregular shape occurred in 326 and 30 ( χ 2=483.05, P<0.001) , 363 and 106 ( χ 2=374.45, P<0.001) , 158 and 53 ( χ 2=94.24, P<0.001) , and 354 and 52 ( χ 2=491.34, P<0.001) nodules, respectively. The machine learning models built using XGBoost, RF, and SVM had AUC, accuracy, and F1 scores ranging from 0.884~0.925, 0.867~0.873, and 0.844~0.854 respectively on the training set. On the test set, the scores ranged from 0.869~0.923, 0.845~0.871, and 0.803~0.845. Among them, the XGBoost model demonstrated the highest diagnostic performance on the test set. Among the four CT features, irregular shape had the highest absolute SHAP value, positively contributing to PTC diagnosis. Conclusion:XGBoost model showed the highest PTC diagnostic performance. Irregular shape had the greatest positive impact on PTC diagnosis.

Objective To observe the value of non-contrast CT radiomics extreme gradient boosting(XGBoost)model based on SHAP method for predicting acute necrotic collection(ANC)around acute pancreatitis(AP).Methods A total of 307 patients with initially clinically diagnosed AP were retrospectively enrolled.The optimal radiomics features of peripheral pancreatic tissue volume of interest(VOI)were extracted and screened based on automatic segmentation on the first non-contrast CT,and the evaluation results of modified CT severity index(MCTSI)score of AP severity based on first enhanced CT were recorded.The patients were divided into peripancreatic ANC group(ANC group)and acute peripancreatic fluid collection(APFC)group according to follow-up abdominal CT.XGBoost method was used to construct radiomics model,MCTSI model and combined model for predicting AP ANC based on the optimal radiomics features,MCTSI and their combination,respectively.The diagnostic efficacy of each model was evaluated using 5-fold cross-validation method,and the contribution of each variable to combined model was analyzed with SHAP method.Results Among 307 cases,there were 134 cases in ANC group and 173 in APFC group.Totally 6 optimal radiomics features were screened based on the first non-contrast CT.The area under the receiver operating characteristic curve(AUC)of radiomics model,MCTSI model and combined model was 0.936,0.693 and 0.917,respectively.The AUC of MCTSI model was lower than that of radiomics model and combined model(Z=-3.485,-2.824,both P＜0.01),while no significant difference of AUC was found between radiomics model and combined model(Z=-0.817,P=0.415).The contribution of optimal radiomics features to combined model were all higher than that of MCTSI score.Conclusion Non-contrast CT radiomics XGBoost model could effectively predict AP ANC.

Objective To observe the value of non-contrast CT radiomics extreme gradient boosting(XGBoost)model based on SHAP method for predicting acute necrotic collection(ANC)around acute pancreatitis(AP).Methods A total of 307 patients with initially clinically diagnosed AP were retrospectively enrolled.The optimal radiomics features of peripheral pancreatic tissue volume of interest(VOI)were extracted and screened based on automatic segmentation on the first non-contrast CT,and the evaluation results of modified CT severity index(MCTSI)score of AP severity based on first enhanced CT were recorded.The patients were divided into peripancreatic ANC group(ANC group)and acute peripancreatic fluid collection(APFC)group according to follow-up abdominal CT.XGBoost method was used to construct radiomics model,MCTSI model and combined model for predicting AP ANC based on the optimal radiomics features,MCTSI and their combination,respectively.The diagnostic efficacy of each model was evaluated using 5-fold cross-validation method,and the contribution of each variable to combined model was analyzed with SHAP method.Results Among 307 cases,there were 134 cases in ANC group and 173 in APFC group.Totally 6 optimal radiomics features were screened based on the first non-contrast CT.The area under the receiver operating characteristic curve(AUC)of radiomics model,MCTSI model and combined model was 0.936,0.693 and 0.917,respectively.The AUC of MCTSI model was lower than that of radiomics model and combined model(Z=-3.485,-2.824,both P＜0.01),while no significant difference of AUC was found between radiomics model and combined model(Z=-0.817,P=0.415).The contribution of optimal radiomics features to combined model were all higher than that of MCTSI score.Conclusion Non-contrast CT radiomics XGBoost model could effectively predict AP ANC.

[Objective]To explore the distribution patterns and correlations of pet-related cat/dog dander allergens and mold allergens in patients with allergic diseases,providing evidence for individualized diagnosis,treatment,and prevention strategies.[Methods]A retrospective analysis was conducted on 798 patients diagnosed with allergic diseases at the Third Affiliated Hospital of Sun Yat-sen University between April 2021 and October 2023.All patients underwent UniCAP platform testing for specific immunoglobulin E(sIgE)levels against cat dander,dog dander,and mold mix(mx1/mx2),alongside total IgE(tIgE)quantification.Descriptive statistics,Mann-Whitney U tests,and chi-square analyses were employed to evaluate allergen distribution and interrelationships.[Results]Among the 798 patients(395 males,403 females,ratio 1:1.02),their ages ranged from 0.67 to 69 years(median 14 years,IQR 6-29).A total of 63.2％(504/798)had a single allergic disease,with allergic rhinitis(AR,49.2％)being the most common.The remaining 36.8％(294/798)had≥2 allergic diseases,with AR combined with atopic dermatitis(AD,10.7％)as the predominant comorbidity.The positivity rate for cat/dog dander sIgE was 24.1％(192/798),with a significantly higher prevalence in females(30.8％)than males(16.7％,P<0.05).Cat dander sensitization increased with age in patients under 18 years.Among positive cases,cat dander sIgE level 2 was most frequent(25.9％),while dog dander sIgE level 1 predominated(55％).Patients with cat dander sIgE levels 4-6 had significantly higher tIgE than those with levels 1-3(P<0.05).The positivity rate for mold mix(mx1/mx2)sIgE was 7.4％(59/798),with mx2 as the primary sensitizer and level 2 being the most common.In mx2-positive patients,the cat/dog dander sIgE positivity rate(44.8％)was significantly higher than that in mx2-negative patients(17.9％,P<0.05),and tIgE levels were also higher(P<0.05).[Conclusion]Cat dander sensitization increases with age in children.Cat/dog dander and mold allergens are closely linked to AR and AR combined with AD.Synergistic correlations exist between cat/dog dander sIgE and mold mx2 sIgE.Combined detection of these allergens is critical for precision diagnosis and management of pet-related allergic diseases.

Objective:To determine the causal relationship between educational attainment and the risk of allergic rhinitis and (or) eczema using Mendelian randomization (MR) analyses.Methods:This study was a secondary data analysis based on the summary data of genome-wide association studies (GWAS), which involved 293 723 participants (educational attainment) from the Social Science Genetics Association Consortium and 462 013 participants [allergic rhinitis and (or) eczema] from the UK Biobank. Genetic variants that were closely related to educational attainment were identified as instrumental variables. Two-sample MR analyses, including inverse-variance weighted (IVW), MR-Egger regression, weighted median method and weighted model-based estimation, were performed to investigate the causal relationship between educational attainment and the risk of allergic rhinitis and (or) eczema, in which the odds ratio ( OR) values were used as indicators. Results:A total of 70 single-nucleotide polymorphisms (SNPs) were chosen as instrumental variables. The MR-Egger regression results suggested that the genetic pleiotropy was unlikely to bias our results ( P=0.107). In the univariable MR analyses, IVW regression showed that the risk of allergic rhinitis and (or) eczema was OR=1.044 (95% CI: 1.020-1.069, P<0.001) and OR=1.170 (95% CI: 1.074-1.256, P<0.001), respectively, for the increase in the duration of education by one year or one standard deviation ( SD) (3.71 years). In the reverse MR analysis, IVW regression showed little evidence that allergic rhinitis and (or) eczema affected educational attainment ( OR=1.020, 95% CI: 0.927-1.023, P=0.683). The results of the weighted median method and weighted mode-based estimation were consistent with the results of IVW. Conclusion:This study suggests that there is a positive causal relationship between educational attainment and the risk of allergic rhinitis and (or) eczema, which means that educational attainment can increase the occurrence of allergic rhinitis and (or) eczema.

Objective:To determine the causal relationship between educational attainment and the risk of allergic rhinitis and (or) eczema using Mendelian randomization (MR) analyses.Methods:This study was a secondary data analysis based on the summary data of genome-wide association studies (GWAS), which involved 293 723 participants (educational attainment) from the Social Science Genetics Association Consortium and 462 013 participants [allergic rhinitis and (or) eczema] from the UK Biobank. Genetic variants that were closely related to educational attainment were identified as instrumental variables. Two-sample MR analyses, including inverse-variance weighted (IVW), MR-Egger regression, weighted median method and weighted model-based estimation, were performed to investigate the causal relationship between educational attainment and the risk of allergic rhinitis and (or) eczema, in which the odds ratio ( OR) values were used as indicators. Results:A total of 70 single-nucleotide polymorphisms (SNPs) were chosen as instrumental variables. The MR-Egger regression results suggested that the genetic pleiotropy was unlikely to bias our results ( P=0.107). In the univariable MR analyses, IVW regression showed that the risk of allergic rhinitis and (or) eczema was OR=1.044 (95% CI: 1.020-1.069, P<0.001) and OR=1.170 (95% CI: 1.074-1.256, P<0.001), respectively, for the increase in the duration of education by one year or one standard deviation ( SD) (3.71 years). In the reverse MR analysis, IVW regression showed little evidence that allergic rhinitis and (or) eczema affected educational attainment ( OR=1.020, 95% CI: 0.927-1.023, P=0.683). The results of the weighted median method and weighted mode-based estimation were consistent with the results of IVW. Conclusion:This study suggests that there is a positive causal relationship between educational attainment and the risk of allergic rhinitis and (or) eczema, which means that educational attainment can increase the occurrence of allergic rhinitis and (or) eczema.

ObjectiveTo explore the effect of Suanzaoren Tang combined with Ziwu Liuzhu acupuncture on the vertebral artery hemodynamics， inflammatory cytokines， and neurotrophic factors in the patients with cervical insomnia with syndrome of deficiency of both heart and spleen. MethodThe random number table method was employed to assign 164 patients with cervical insomnia with syndrome of deficiency of both heart and spleen treated in the First Clinical Medical School of Guangzhou University of Chinese Medicine from January 2018 to June 2021 into a control group and an observation group. The control group was orally administrated with 1-2 mg estazolam tablets before bed for 4 weeks， and the observation group with Suanzaoren Tang combined with Ziwu Liuzhu acupuncture for 4 weeks. The therapeutic efficacy and safety were observed. The Pittsburgh Sleep Quality Index （PSQI） score， polysomnography monitoring results， hemodynamics parameters of vertebral artery， and serum levels of inflammatory cytokines and neurotrophic factors were compared before and after treatment. ResultExcept 4 dropouts， the remaining 160 patients were included in this study， with 80 patients in each group. The observation group had higher total effective rate than the control group ［92.50% （74/80） vs. 80.00% （64/80）， χ²=5.270， P<0.05］. Compared with that before treatment， the therapies in both groups decreased the PSQI score， sleep latency time， awakening time， awakening times， serum levels of interleukin-1β （IL-1β）， C-reactive protein （CRP）， and tumor necrosis factor-α （TNF-α） （P<0.01）. Meanwhile， they increased the proportion of rapid-eye-movement （REM） sleep， the diastolic blood flow velocity （Vd）， systolic blood flow velocity （Vs）， and mean blood flow velocity （MFV） of vertebral artery， as well as the serum levels of brain-derived neurotrophic factor （BDNF） and glial cell-derived neurotrophic factor （GDNF） （P<0.05， P<0.01）. Moreover， the observation group had lower PSQI score， sleep latency time， awakening time， awakening times， and serum IL-1β， CRP， and TNF-α levels （P<0.01） and higher proportion of REM sleep， Vd， Vs， MFV of vertebral artery， and serum BDNF and GDNF levels （P<0.05， P<0.01） than the control group. ConclusionZiwu Liuzhu acupuncture combined with Suanzaoren Tang can improve blood circulation of vertebral artery， reduce the serum levels of inflammatory cytokine， and increase the serum levels of neurotrophic factors to improve the sleep quality of the patients with cervical insomnia with syndrome of deficiency of both heart and spleen.

Clinical final examination is an important link in the standardized training of residents in dermatology and quantification of evaluation indicators is one of the important parameters. In this study, the scores of clinical examinations of six candidates who participated in standardized training of residents in dermatology of Sun Yat-Sen University in June 2019 were taken as examples to explore the quantitative indicators of standardized and multi-station clinical final examinations. The indicators contained four stations and five links: skin pathological reading, skin biopsy, medical history collection and physical examination, medical record writing, and comprehensive questioning, which covered the main contents of the standardized training outline of residents in dermatology. Each evaluation indicator was refined and quantified. Finally, heuristic ideas were put forward, including a wider range of standardized and multi-station clinical examinations, introduction of new examination places, and utilization of information technology.