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 analyze the results of national external quality assessment (EQA) for transfusion compatibility test from 2018 to 2023, with the aim of providing references for improving laboratory testing quality and ensuring the safety of clinical blood transfusion. Methods: Three EQA programs were conducted annually, each distributing 22 quality assessment samples. Participating transfusion laboratories were required to complete testing within specified deadlines and to submit results along with documentation of testing methodologies, reagents, and equipment used. National Center for Clinical Laboratories (NCCL) conducted statistical analysis of laboratory results, evaluated testing outcomes and related circumstances, and provided feedback to participating laboratories. EQA data from transfusion laboratories across China from 2018 to 2023 were collected and systematically analyzed. Results: From 2018 to 2023, the qualification rates for all five items (ABO forward typing, ABO reverse typing, Rh blood group typing, antibody screening, and cross-matching) were 67.59%, 77.11%, 77.38%, 72.78%, 79.96%, and 85.16%, respectively. The mean qualification rates for ABO forward typing, ABO reverse typing, RhD blood group typing, antibody screening, and cross-matching over the past six years were 96.25%±0.59%, 90.45%±4.52%, 96.05%±0.71%, 90.88%±2.86%, and 88.34%±3.48%, respectively. The qualification rates in 2019, 2020, 2022, and 2023 all showed a stable trend of "blood stations>tertiary hospitals>secondary hospitals". The mean qualification rate of laboratories in secondary hospitals from 2018 to 2023 was significantly lower than those of laboratories in tertiary hospitals and blood stations (P<0.05), while no significant difference was observed between laboratories in tertiary hospitals and blood stations (P>0.05). The micro column agglutination method was the most widely used in all five tests. In the four test items, namely ABO forward typing, ABO reverse typing, antibody screening, and cross-matching, there was a statistically significant difference in the qualification rate of micro column agglutination method compared to other methods (P<0.05). There was a statistical difference in the qualification rate between manual and automated detection using micro column agglutination method in the cross-matching tests (P<0.05), whereas no significant difference was noted for the other test items (P>0.05). Conclusion: From 2018 to 2023, the number of laboratories participating in EQA activities has been increasing year by year, and the qualification rate has shown an overall upward trend. The type of laboratory is a key factor affecting the qualification rate, and the testing capabilities of some laboratories still need to be improved. The micro column agglutination method is widely used in transfusion compatibility tests. The established EQA program effectively monitors quality issues in laboratories, drives continuous improvement, and ensures sustained enhancement of testing standards to safeguard clinical blood safety.

Objective:To analyze the results of national external quality assessment (EQA) for transfusion compatibility test in 2023, and provide reference for quality management of clinical transfusion compatibility testing.Methods:The EQA of clinical transfusion compatibility testing by NCCL was performed 3 times in 2023 among included laboratories. The panel consisting of 22 samples was distributed to 4 186 laboratories across 31 provinces (Including 2 961 tertiary hospital laboratories, 1 085 secondary hospital laboratories, 23 primary hospital laboratories, 106 blood station laboratories and 11 independent clinical laboratories). Each panel contains 11 red blood cell and 11 plasma samples per 1.5 ml/tube. Each participant laboratory of the EQA program was required to carry out the detection and return results in expected time. Statistical analysis and evaluation on the reported results were conducted by NCCL from the aspects of regional distribution, laboratory grading, testing methodology, reagent and testing system usage.Results:The qualification rates of EQA for five items including ABO positive typing, ABO reverse typing, RhD blood type, antibody screening, and cross matching were 96.68%, 95.10%, 96.46%, 95.32%, and 91.04%, respectively. The EQA qualification rate of tertiary hospital laboratories was 87.77% (2 599/2 961), which was significantly higher than the 77.79% (844/1 085) of secondary hospital laboratories. There were significant differences in the qualification rate of participating laboratories among different regions. The utilization rates of micro column agglutination method in ABO positive typing, ABO reverse typing, RhD blood type, antibody screening, and cross matching were 80.81% (10 080/12 474), 75.06% (9 337/12 440), 81.38% (10 118/12 433), 89.59% (11 104/12 394) and 76.25% (9 495/12 453), respectively. The qualification rate of micro column agglutination method was significantly higher than that of saline slide method in ABO positive typing detection ( P<0.05). The qualification rate of micro column agglutination method was significantly higher than that of the polyamine method and anti-human globulin test tube method in antibody screening ( P<0.05). There were statistically significant differences in qualification rate of 7 reagents in ABO reverse typing, antibody screening and cross matching ( P<0.05). There was no statistically significant difference in the qualification rate between the two detection systems for other reagents, except for the ABO reverse typing where the qualification rate of reagent 1 in a single system was higher than that in a mixed system ( P<0.05). Conclusion:The testing capabilities of clinical laboratories in different regions and different type varied significantly in China. Micro column agglutination method was the most popular selection in transfusion compatibility testing. The regents used in these laboratories showed good performance. However, the detection efficiency of some reagents still need to be improved. EQA could be used to evaluate, monitor, and improve the quality of testing.

Objective:To construct a biosafety evaluation index system for major emergency public health events in medical institutions.Methods:Based on previous laboratory biosafety evaluation work, relevant regulations and standards on biosafety in China were collected through literature research and expert consultations. Candidate indicators for constructing the biosafety evaluation system for major emergency public health events in medical institutions were selected, and a framework was established. Two rounds of expert questionnaires were conducted to determine the content of the index system based on experts′ evaluation, and each indicator′s relevance and importance were scored. Finally, two rounds of Delphi consultations were carried out, and the Analytic Hierarchy Process (AHP) was applied to calculate the weights of indicators.Results:The response rates for the total four rounds of questionnaire surveys were all 100%. The first two rounds focused on determining the framework, while the latter two focused on determining the weights for each indicator. The authority coefficients of the expert consultations for the two rounds of weights were 0.65 and 0.70, respectively, indicating the reliability of the research results. In the final round of survey, the Kendall′s coefficients of concordance at each level were all greater than 0.1. Through statistical testing, the P-values were all less than 0.05, indicating good coordination of expert opinions. Ultimately, we established an operational biosafety evaluation system for major emergency public health events in medical institutions, consisting of 4 primary indicators, 26 secondary indicators, and 119 tertiary indicators, with additional deduction items, bonus items, unacceptable items, and monitoring indicators.Conclusions:Based on scientific theory, a biosafety evaluation system for major emergency public health events in medical institutions was constructed, achieving the integration of routine and emergency measures. This system can be used for self-assessment of laboratory biosafety during emergency public health events, addressing the lack of unified standards in biosafety evaluation. Through regular self-assessment, it can enhance the level of biosafety management in medical institution laboratories, to realize the value of application and dissemination.

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.

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 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 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 chemical constituents of Heihuang Chizhu Granules and the blood composition of rats af-ter administration by UPLC-Q-TOF-MS/MS.METHODS A Waters ACQUITY UPLC HSS T3 column(3 mm×100 mm,1.8 μm)was eluted with acetonitrile-0.1%formic acid as mobile phase,and the data were collected in electrospray ion source positive and neg-ative ion mode and then identified with the reference retention time,precise molecular weight,secondary fragment ions,and references to relevant literature.RESULTS A total of 104 chemical components were identified from Heihuang Chizhu Granules,including 26 flavonoids,24 organic acids,14 triterpenoids,8 terpenoids,7 phenylpropanoids,11 monoglycosides,and 14 other components(phe-nols,alkaloids,etc.).On this basis,39 blood-entering components were identified in the plasma of rats administered via gavage,in-cluding 28 prototypes and 11 metabolites.CONCLUSION The chemical constituents of Heihuang Chizhu Granules and the compo-nents entering the blood of rats are analyzed and identified for the first time in this study,and the results provide a scientific basis for the basic research of Heihuang Chizhu Granules and the establishment of process quality control standards.

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.