Objective:To identify the risk factors influencing the prognosis of patients with advanced breast cancer through LASSO-Logistic regression analysis and construct a nomogram model to evaluate their prognostic risk.Methods:A total of 178 patients with advanced breast cancer who visited the Department of Thyroid and Breast Surgery of Chengyang District People’s Hospital of Qingdao City from Jan. 2015 to Jan. 2023 were selected as the research subjects. According to the follow-up results, the patients were divided into a good-prognosis group and a poor-prognosis group. Clinical data of the patients were collected. LASSO-Logistic regression analysis was used to identify the risk factors affecting the prognosis of patients with advanced breast cancer. A nomogram model was constructed based on the analysis results. The predictive efficacy of the model for the prognostic risk of patients with advanced breast cancer was evaluated using the receiver operating characteristic (ROC) curve and Hosmer-Lemeshow (H-L) test.Results:During the follow-up, 5 patients were lost to follow-up. Among the final 173 patients included, 60 had poor prognoses (accounting for 34.68%), and 113 had good prognoses (accounting for 65.32%). There were significant differences between the poor prognosis group and the good prognosis group in terms of the number of lymph node metastases ( χ 2=18.12), the number of organ metastases ( χ 2=14.28), the difference in ADC before and after treatment ( t=17.35), the difference in SER before and after treatment ( t=9.57), the enhancement of the echo behind the breast after treatment ( χ 2=13.00), and the proportion of increased calcification ( χ 2=8.06) (both P < 0.05). The clinical data with significant differences in the univariate analysis were included in the LASSO regression analysis. Six factors were finally selected: number of lymph node metastases > 5, number of organ metastases > 1, difference in ADC values before and after treatment, difference in SER values before and after treatment, enhanced echo behind the breast, and increased calcification. These six factors selected by LASSO regression were included in the Logistic regression analysis. The results showed that number of organ metastases > 1 ( OR=2.208, 95% CI: 1.153-3.263), small difference in ADC values before and after treatment ( OR=0.448, 95% CI: 0.287-0.608), enhanced echo behind the breast ( OR=2.474, 95% CI: 1.063-3.886), and increased calcification ( OR=3.762, 95% CI: 1.831-5.693) were independent risk factors for poor prognosis in patients with advanced breast cancer (both P<0.05). A nomogram model was constructed based on the analysis results. The ROC curve showed that the area under the curve (AUC) of the model was 0.778. The H-L test results showed that the calibration curve fit well with the ideal curve, with χ 2 = 0.69 and P = 0.273. Conclusion:The nomogram model constructed based on LASSO-Logistic regression analysis has good predictive efficacy for the prognosis of patients with advanced breast cancer.

Objective:To observe the effect of Liuzijue on post-stroke fatigue patients with the type of Qi deficiency and blood stasis and the effect of pulmonary function.Method:From March 2022 to March 2023,a total of 68 post-stroke fatigue patients with Qi deficiency and blood stasis who were hospitalized in the Affiliated Rehabilitation Hospital of Fujian University of Traditional Chinese Medicine and met the criteria were selected,the patients were divided into therapy group(n=34)and control group(n=34)according to random number table.The control group was treated with conventional reha-bilitation combined with conventional respiratory therapy,the therapy group was treated with conventional reha-bilitation combined with Liuzijue,30 minutes/time,5 times/week,a total of 12 weeks.The fatigue severity scale score(FSS),Qi Deficiency Syndrome and Blood Stasis factor diagnostic scale score,vital capacity(VC),forced vital capacity(FVC),peak expiratory flow(PEF),and maximal voluntary ventilation(MVV)were assessed in both groups before and after treatment.Result:After 12 weeks of treatment,the FSS scores and the Qi deficiency syndrome and blood stasis factor di-agnostic scale score exhibited significant differences in the therapy group compared with those before treatment(P＜0.05),and significant improvement compared with those in the control group(P＜0.05).The significant differ-ences were found in the VC、FVC、PEF and MVV of both two groups between before and after treatment(P＜0.05),and the degree of improvement was more pronounced in the therapy group.Conclusion:The Liuzijue applied to post-stroke fatigue patients with Qi deficiency and blood stasis can better improve the fatigue score and Qi deficiency syndrome and blood stasis score,as well as improve the level of pulmonary function of patients,which is worthy of clinical application.

[Objective]To explore the effects of astragalin(AST)on autophagy and apoptosis of astrocytes in the L4-5 dorsal horn of the spinal cord in mice with inflammatory pain induced by complete Freund's adjuvant(CFA).[Methods]Twenty-four male C57BL/6 mice,aged six months,were randomly assigned to four groups:control group,saline group,CFA model group,and CFA+AST group,six mice in each group.The inflammatory pain model was established by injection of 10 μL CFA into the right lateral malleolus fossa.The saline group were injected with an equal amount of normal saline at the same site.The inflammatory pain mice in CFA+AST group were further treated with AST(60 mg/kg)intraperitoneally once a day for 21 consecutive days.Multiplex immunofluorescence staining was used to detect the coexpression of autophagy-related factors including ATG 12 and Beclin-1,apoptosis-related factors including Cleaved-Caspase3 and Caspase9,and the astrocyte marker such as GFAP in the L4-5 spinal dorsal horn of the mice in each group.Western blot was used to examine the protein expression levels of autophagy-related proteins(ATG12,Beclin-1)and apoptosis-related proteins(Caspase 3,Caspase 9)in the L4-5 spinal dorsal horn of mice.[Results]Immunofluorescent staining showed that in the L4-5 dorsal horn of the spinal cord,the fluorescence intensity of ATG12(P<0.000 1)and Beclin-1(P<0.000 1)was significantly increased,while that of Cleaved-Caspase 3(P<0.001)and Caspase 9(P<0.000 1)was decreased in the CFA+AST group when compared to the CFA model group.Furthermore,AST could inhibit the activation of astrocytes.Western blot further confirmed that AST significantly upregulated the expression of ATG12(P<0.000 1)and Beclin-1(P<0.000 1)in the L4-5 spinal cord of CFA mice,and downregulated the expression of Caspase 3(P<0.01)and Caspase 9(P<0.001).[Conclusions]AST promotes autophagy of astrocytes and inhibits their apoptosis in the L4-5 spinal dorsal horn of CFA mice.

Objective:To identify the risk factors influencing the prognosis of patients with advanced breast cancer through LASSO-Logistic regression analysis and construct a nomogram model to evaluate their prognostic risk.Methods:A total of 178 patients with advanced breast cancer who visited the Department of Thyroid and Breast Surgery of Chengyang District People’s Hospital of Qingdao City from Jan. 2015 to Jan. 2023 were selected as the research subjects. According to the follow-up results, the patients were divided into a good-prognosis group and a poor-prognosis group. Clinical data of the patients were collected. LASSO-Logistic regression analysis was used to identify the risk factors affecting the prognosis of patients with advanced breast cancer. A nomogram model was constructed based on the analysis results. The predictive efficacy of the model for the prognostic risk of patients with advanced breast cancer was evaluated using the receiver operating characteristic (ROC) curve and Hosmer-Lemeshow (H-L) test.Results:During the follow-up, 5 patients were lost to follow-up. Among the final 173 patients included, 60 had poor prognoses (accounting for 34.68%), and 113 had good prognoses (accounting for 65.32%). There were significant differences between the poor prognosis group and the good prognosis group in terms of the number of lymph node metastases ( χ 2=18.12), the number of organ metastases ( χ 2=14.28), the difference in ADC before and after treatment ( t=17.35), the difference in SER before and after treatment ( t=9.57), the enhancement of the echo behind the breast after treatment ( χ 2=13.00), and the proportion of increased calcification ( χ 2=8.06) (both P < 0.05). The clinical data with significant differences in the univariate analysis were included in the LASSO regression analysis. Six factors were finally selected: number of lymph node metastases > 5, number of organ metastases > 1, difference in ADC values before and after treatment, difference in SER values before and after treatment, enhanced echo behind the breast, and increased calcification. These six factors selected by LASSO regression were included in the Logistic regression analysis. The results showed that number of organ metastases > 1 ( OR=2.208, 95% CI: 1.153-3.263), small difference in ADC values before and after treatment ( OR=0.448, 95% CI: 0.287-0.608), enhanced echo behind the breast ( OR=2.474, 95% CI: 1.063-3.886), and increased calcification ( OR=3.762, 95% CI: 1.831-5.693) were independent risk factors for poor prognosis in patients with advanced breast cancer (both P<0.05). A nomogram model was constructed based on the analysis results. The ROC curve showed that the area under the curve (AUC) of the model was 0.778. The H-L test results showed that the calibration curve fit well with the ideal curve, with χ 2 = 0.69 and P = 0.273. Conclusion:The nomogram model constructed based on LASSO-Logistic regression analysis has good predictive efficacy for the prognosis of patients with advanced breast cancer.

Objective To analyze the practical value of spiral CT three-dimensional reconstruction techniquein evaluating triplane fractures of the distal tibia.Methods A retrospective analysis was conducted on183 patients with triplane fractures of the distal tibia admitted to Sichuan Orthopedic Hospital from January 2021 to March 2023.All patients underwent both X-ray and spiral CT examinations.Taking surgical reduction results as the gold standard for diagnosis,the diagnostic accuracies of X-ray examination and spiral CT three-dimensional reconstruction technique for triplane fractures of the distal tibia were analyzed.Results Fracture classification according to the number of fracture fragments showed that among the 183 patients with triplane fractures of the distal tibial,there were 44 cases of four-part fractures,62 cases of three-part fractures,and 77 cases of two-part fractures.The classification by the location of epiphyseal injury in the distal tibia showed 175 cases of lateral type and 8 cases of medial type.According to whether the fracture line involved the articular surface,they were categorized into 94 cases of type I,60 cases of type II,and 29 cases of type III.For the classification of the number of fracture fragments,X-ray misdiagnosed 9 cases of four-part fractures as three-part or two-part fractures,and 21 cases of three-part fractures as two-part fractures,resulting in a diagnostic accuracy of 83.60%.For theclassification of fracture line and articular surface position,X-ray led to misdiagnosis or inaccurate diagnosis in 39 cases,with a diagnostic accuracy of 78.69%.When spiral CT three-dimensional reconstruction technique was used to classify the number of fracture fragments,only 1 case of four-part fracture was misdiagnosed as three-part fracture,and 2 cases of three-part fractures were misdiagnosed as four-part fractures or two-part fractures,yielding a diagnostic accuracy of 98.36%.For the diagnosis of the positional relationship of the fracture line to the articular surface,spiral CT three-dimensional reconstruction technique had 8 misdiagnoses,with a corresponding diagnostic accuracy of 95.63%.Conclusion Spiral CT three-dimensional reconstruction technique can stereoscopically display the spatial information of the triplane fractures of the distal tibia,such as the location,shape,type,and articular surface,exhibiting high accuracy for classification diagnosis and significant application value in the reduction and treatment of triplane fractures of the distal tibia.

Existing emotion recognition research is typically limited to static laboratory settings and has not fully handle the changes in emotional states in dynamic scenarios. To address this problem, this paper proposes a method for dynamic continuous emotion recognition based on electroencephalography (EEG) and eye movement signals. Firstly, an experimental paradigm was designed to cover six dynamic emotion transition scenarios including happy to calm, calm to happy, sad to calm, calm to sad, nervous to calm, and calm to nervous. EEG and eye movement data were collected simultaneously from 20 subjects to fill the gap in current multimodal dynamic continuous emotion datasets. In the valence-arousal two-dimensional space, emotion ratings for stimulus videos were performed every five seconds on a scale of 1 to 9, and dynamic continuous emotion labels were normalized. Subsequently, frequency band features were extracted from the preprocessed EEG and eye movement data. A cascade feature fusion approach was used to effectively combine EEG and eye movement features, generating an information-rich multimodal feature vector. This feature vector was input into four regression models including support vector regression with radial basis function kernel, decision tree, random forest, and K-nearest neighbors, to develop the dynamic continuous emotion recognition model. The results showed that the proposed method achieved the lowest mean square error for valence and arousal across the six dynamic continuous emotions. This approach can accurately recognize various emotion transitions in dynamic situations, offering higher accuracy and robustness compared to using either EEG or eye movement signals alone, making it well-suited for practical applications.
Humans ; Electroencephalography/methods* ; Emotions/physiology* ; Eye Movements/physiology* ; Signal Processing, Computer-Assisted ; Support Vector Machine ; Algorithms

OBJECTIVE To standardize the main processes and related technical links of the clinical comprehensive evaluation of drugs， and provide guidance and reference for improving the quality of comprehensive evaluation evidence and its transformation and application value. METHODS The construction of Guideline for the Workflow of Clinical Comprehensive Evaluation of Drugs was based on the standard guideline formulation method of the World Health Organization （WHO）， strictly followed the latest definition of guidelines by the Institute of Medicine of the National Academy of Sciences of the United States， and conformed to the six major areas of the Guideline Research and Evaluation Tool Ⅱ. Delphi method was adopted to construct the research questions； research evidence was established by applying the research methods of evidence-based medicine. The evidence quality classification system of the Chinese Evidence-Based Medicine Center was adopted for evidence classification and evaluation. The recommendation strength was determined by the recommendation strength classification standard formulated by the Oxford University Evidence-Based Medicine Center， and the recommendation opinions were formed through the expert consensus method. RESULTS & CONCLUSIONS The Guideline for the Workflow of Clinical Comprehensive Evaluation of Drugs covers 4 major categories of research questions， including topic selection， evaluation implementation， evidence evaluation， and application and transformation of results. The formulation of this guideline has standardized the technical links of the entire process of clinical comprehensive evaluation of drugs， which can effectively guide the high-quality and high-efficient development of this work， enhance the standardized output and transformation application value of evaluation evidence， and provide high-quality evidence support for the scientific decision-making of health and the rationalization of clinical medication.

Objective:To observe the effect of Liuzijue on post-stroke fatigue patients with the type of Qi deficiency and blood stasis and the effect of pulmonary function.Method:From March 2022 to March 2023,a total of 68 post-stroke fatigue patients with Qi deficiency and blood stasis who were hospitalized in the Affiliated Rehabilitation Hospital of Fujian University of Traditional Chinese Medicine and met the criteria were selected,the patients were divided into therapy group(n=34)and control group(n=34)according to random number table.The control group was treated with conventional reha-bilitation combined with conventional respiratory therapy,the therapy group was treated with conventional reha-bilitation combined with Liuzijue,30 minutes/time,5 times/week,a total of 12 weeks.The fatigue severity scale score(FSS),Qi Deficiency Syndrome and Blood Stasis factor diagnostic scale score,vital capacity(VC),forced vital capacity(FVC),peak expiratory flow(PEF),and maximal voluntary ventilation(MVV)were assessed in both groups before and after treatment.Result:After 12 weeks of treatment,the FSS scores and the Qi deficiency syndrome and blood stasis factor di-agnostic scale score exhibited significant differences in the therapy group compared with those before treatment(P＜0.05),and significant improvement compared with those in the control group(P＜0.05).The significant differ-ences were found in the VC、FVC、PEF and MVV of both two groups between before and after treatment(P＜0.05),and the degree of improvement was more pronounced in the therapy group.Conclusion:The Liuzijue applied to post-stroke fatigue patients with Qi deficiency and blood stasis can better improve the fatigue score and Qi deficiency syndrome and blood stasis score,as well as improve the level of pulmonary function of patients,which is worthy of clinical application.

[Objective]To investigate the value of radiomics based on contrast-enhanced computed tomography(CT)image in predicting the traditional Chinese medicine(TCM)differentiation typing of primary non-small cell lung cancer(NSCLC).[Methods]A total of 130 patients diagnosed as NSCLC by pathology from July 2018 to October 2023 in Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University were retrospectively analyzed.According to the diagnostic criteria of TCM,all the enrolled patients were divided into deficiency syndrome group(67 cases)and excess syndrome group(63 cases),and then assigned to training cohort(91 cases)and validation cohort(39 cases)in a ratio of 7:3.The largest diameter slice of lesion on cross-sectional images was selected and the regions of interest were contoured at unenhanced,arterial and venous phases respectively,and then the radiomics features were extracted.The linear correlation among features and L1 regularization were used for feature selection,and then logistic regression was used to construct the radiomics model based on radiomics features of each phase.The receiver operating characteristic(ROC)curve was used to evaluate the effectiveness of the model in predicting deficiency and excess syndromes of NSCLC.The Delong test was used for comparison of area under curve(AUC)between the two models.[Results]In the training cohort,a total of 7 radiomics models were constructed,including three single-phase radiomics models,three two-phase combination radiomics models and one three-phase combination radiomics model.The AUC of combination radiomics model was higher than that of the single-phase radiomics model.The AUC of three-phase combination radiomics model was the largest,which was 0.876[95%confidence interval(CI)(0.807～0.945)]and 0.755[95%CI(0.603～0.908)]in the training cohort and validation cohort respectively.[Conclusion]The radiomics model based on contrast-enhanced CT image has high efficacy in predicting the TCM differentiation typing of NSCLC,and the three-phase combination radiomics model demonstrates the best diagnostic efficacy.

Objective:To analyze the association between daily physical activity patterns and dyslipidemia among people receiving physical examination aged 40-65 years.Methods:This cross-sectional study consecutively enrolled 864 participants aged 40-65 years and met the inclusion and exclusion criteria who underwent health check-ups at the Physical Examination Center of Fuquan First People′s Hospital from March to November in 2022. The data of general characteristics, physical activity, physical examination findings, and lipid profiles were collected. The daily physical activity patterns were identified using K-means clustering analysis. The unconditional binary logistic regression was employed to explore the associations between these activity patterns and dyslipidemia, followed by subgroup analyses.Results:The physical activity of the 864 study participants (517 males and 347 females) included in the analysis was divided into 4 patterns (G1: low physical activity; G2: active commuting; G3: housework; G4: leisure exercise). Using G1 as a reference, after adjusting for confounders, G4 was negatively associated with low high density lipoprotein cholesterol (HDL-C) ( OR=0.37, 95% CI: 0.14-1.00) ( P=0.05). In the male, G3 was negatively associated with dyslipidemia ( OR=0.44, 95% CI: 0.21-0.93) and low HDL-C ( OR=0.25, 95% CI: 0.10-0.68) (both P<0.05). In the subjects aged 50 years and above, G2 was negatively associated with dyslipidemia ( OR=0.52, 95% CI: 0.30-0.90), hypertriglyceridemia ( OR=0.50, 95% CI: 0.28-0.90) and low HDL-C ( OR=0.47, 95% CI: 0.24-0.91) (all P<0.05). In those who never or occasionally stayed up late, G2 was negatively associated with hypertriglyceridemia ( OR=0.31, 95% CI: 0.13-0.75) ( P<0.05); in those who stayed up late often, G4 was negatively associated with dyslipidemia ( OR=0.33, 95% CI: 0.13-0.85) and low HDL-C ( OR=0.19, 95% CI: 0.04-0.84) (both P<0.05). In the centrally obese population, G2 was negatively associated with dyslipidemia ( OR=0.55, 95% CI: 0.35-0.88) and hypertriglyceridemia ( OR=0.54, 95% CI: 0.33-0.86) (both P<0.05). Conclusions:Association between different physical activity patterns and dyslipidemia varied among adults aged 40-65 years undergoing health check-ups. Leisure-time exercise is associated with a reduced risk of dyslipidemia, while household activities also emerges as a beneficial factor linked to lower dyslipidemia risk particularly in the male population.