OBJECTIVE To construct a predictive model for evaluating the efficacy of a triple antiemetic regimen （neurokinin- 1 receptor antagonist+5-hydroxytryptamine 3 receptor antagonist+dexamethasone） for preventing nausea and vomiting induced by highly emetogenic chemotherapy （HEC） based on interpretable deep learning algorithms. METHODS Clinical data of cancer patients who received HEC and were treated with the standard triple antiemetic regimen in the oncology department of Tianjin Medical University General Hospital from January 2018 to December 2022 were collected retrospectively. Demographic， clinical and metabolism-related variables were integrated. After data pre-processing， two deep learning algorithms （deep random forest and dense neural network） and four machine learning algorithms （support vector machine， categorical boosting， random forest and decision tree） were used to build predictive models. Subsequently， model performance evaluation and model interpretability analysis were conducted. RESULTS Among the six candidate models， the deep random forest model demonstrated the best predictive performance on the test set， with an area under the receiver operating characteristic curve of 0.850， an accuracy of 0.911， a precision of 0.805， a recall of 0.783， an F1 score of 0.793， and a Brier score of 0.075. Interpretability analysis revealed that creatinine clearance rate （Ccr） was the key predictive factor， and low Ccr levels， female gender， younger age， highly emetogenic drugs （particularly cisplatin-containing chemotherapy regimens）， and anticipatory nausea and vomiting were positively correlated with the risk of HEC-related nausea and vomiting. CONCLUSIONS The deep random forest model exhibits the best performance in predicting the efficacy of triple antiemetic regimen for preventing HEC-related nausea and vomiting. The key predictors in this model primarily include Ccr，anticipatory nausea and vomiting， gender， age， and highly emetogenic drugs.

This study aims to establish BHK-21 stable cell lines expressing APN from four species(human,pig,dog,and cat),the APN fragments were amplified from pEGFP-C1-APN plasmids of the four species stored in the laboratory to generate the recombinant plasmids pcDNA4.0-APN.Af-ter the recombinant plasmids were transfected into BHK-21 cells,the stable BHK-21 cell lines ex-pressing the APNs were selected by two rounds of limited dilution.The constructed BHK-21 cell lines were identified by indirect immunofluorescence assay(IFA),and their susceptibility to PD-CoV and TGEV was tested for these four cell lines.Virus infection experiments revealed that PD-CoV infected cells expressing human,pig,and dog APNs,while it did not infect cells expressing cat APN.Simultaneously,TGEV infected cells expressing pig,dog,and cat APNs,but did not infect cells expressing human APN.The results suggest that the risk of cross-species infection for different coronaviruses and the established cell line can be used effectively to evaluate the virus in-fection.The findings also revealed that PDCoV has the potential risk of cross-species infection of human and dog,and TGEV has the potential risk of cross-species infection of dog and cat.These results provide a basis for the prevention and control strategy of coronaviruses.

Objectives:To analyze the disease burden and trends of ischemic stroke attributable to major metabolic risk factors in China from 1990 to 2021,and provide a basis for disease prevention and management.Methods:Based on the Global Burden of Disease(GBD)2021 data,we compared the age-standardized mortality rate(ASMR)and age-standardized disability-adjusted life year rate(ASDR)of ischemic stroke attributable to major metabolic risk factors(including overweight/obesity,hypertension,elevated low-density lipoprotein cholesterol,low bone density,hyperglycemia,and impaired renal function)in China and globally,and estimated their time trends through estimated annual percentage change(EAPC).We also analyzed the number of deaths,mortality rate,disability adjusted life year(DALY),and DALY rate of ischemic stroke attributable to major metabolic risk factors in China from 1990 to 2021,and compared the epidemiological differences among different gender and age groups.Results:From 1990 to 2021,the disease burden of ischemic stroke attributable to major metabolic risk factors in China showed a slight upward trend(1990 to 2005)and then gradually decreased,with a relatively small overall decline.,while the global disease burden showed a decreasing trend.In 2021,the ASMR and ASDR of ischemic stroke attributable to major metabolic risk factors in China were 48.11/100 000 and 898.35/100 000(EAPC[95%CI]were-0.24%[-1.13%to 0.66%]and-0.25%[-1.00%to 0.51%]),respectively,both higher than the global average levels(33.96/100 000 and 651.46/100 000,EAPC[95%CI]were-1.75%[-2.03%to 1.47%]and-1.49%[-1.74%to-1.23%],respectively).Compared with 1990,the actual mortality rate and DALY rate of ischemic stroke attributable to major metabolic risk factors in China increased by 139.60%and 110.53%respectively in 2021.There are gender differences in the disease burden of ischemic stroke attributable to major metabolic risk factors in China,with significantly higher death numbers,mortality rates,DALY,and DALY rates in males compared to females.At the age level,DALY and DALY rates were both higher in individuals aged 15-49,DALY increased but DALY rates decreased in individuals aged 50-69.DALY surged in individuals aged 70 and above,male DALY rates showed increasing trend and female DALY rates showed slightly decreasing trend.Conclusions:The disease burden of ischemic stroke in China is significantly affected by metabolic risk factors.Although prevention and control have achieved certain positive results,the overall disease burden in China is higher than that of the world,and precise intervention strategies need to be developed for different genders and ages in China.

To analyze potential adverse drug events(ADEs) associated with ustekinumab and upadacitinib in the treatment of inflammatory bowel disease(IBD) based on an international authoritative database, thereby providing evidence for clinical medication safety.

This study aims to establish BHK-21 stable cell lines expressing APN from four species(human,pig,dog,and cat),the APN fragments were amplified from pEGFP-C1-APN plasmids of the four species stored in the laboratory to generate the recombinant plasmids pcDNA4.0-APN.Af-ter the recombinant plasmids were transfected into BHK-21 cells,the stable BHK-21 cell lines ex-pressing the APNs were selected by two rounds of limited dilution.The constructed BHK-21 cell lines were identified by indirect immunofluorescence assay(IFA),and their susceptibility to PD-CoV and TGEV was tested for these four cell lines.Virus infection experiments revealed that PD-CoV infected cells expressing human,pig,and dog APNs,while it did not infect cells expressing cat APN.Simultaneously,TGEV infected cells expressing pig,dog,and cat APNs,but did not infect cells expressing human APN.The results suggest that the risk of cross-species infection for different coronaviruses and the established cell line can be used effectively to evaluate the virus in-fection.The findings also revealed that PDCoV has the potential risk of cross-species infection of human and dog,and TGEV has the potential risk of cross-species infection of dog and cat.These results provide a basis for the prevention and control strategy of coronaviruses.

Objectives:To analyze the disease burden and trends of ischemic stroke attributable to major metabolic risk factors in China from 1990 to 2021,and provide a basis for disease prevention and management.Methods:Based on the Global Burden of Disease(GBD)2021 data,we compared the age-standardized mortality rate(ASMR)and age-standardized disability-adjusted life year rate(ASDR)of ischemic stroke attributable to major metabolic risk factors(including overweight/obesity,hypertension,elevated low-density lipoprotein cholesterol,low bone density,hyperglycemia,and impaired renal function)in China and globally,and estimated their time trends through estimated annual percentage change(EAPC).We also analyzed the number of deaths,mortality rate,disability adjusted life year(DALY),and DALY rate of ischemic stroke attributable to major metabolic risk factors in China from 1990 to 2021,and compared the epidemiological differences among different gender and age groups.Results:From 1990 to 2021,the disease burden of ischemic stroke attributable to major metabolic risk factors in China showed a slight upward trend(1990 to 2005)and then gradually decreased,with a relatively small overall decline.,while the global disease burden showed a decreasing trend.In 2021,the ASMR and ASDR of ischemic stroke attributable to major metabolic risk factors in China were 48.11/100 000 and 898.35/100 000(EAPC[95%CI]were-0.24%[-1.13%to 0.66%]and-0.25%[-1.00%to 0.51%]),respectively,both higher than the global average levels(33.96/100 000 and 651.46/100 000,EAPC[95%CI]were-1.75%[-2.03%to 1.47%]and-1.49%[-1.74%to-1.23%],respectively).Compared with 1990,the actual mortality rate and DALY rate of ischemic stroke attributable to major metabolic risk factors in China increased by 139.60%and 110.53%respectively in 2021.There are gender differences in the disease burden of ischemic stroke attributable to major metabolic risk factors in China,with significantly higher death numbers,mortality rates,DALY,and DALY rates in males compared to females.At the age level,DALY and DALY rates were both higher in individuals aged 15-49,DALY increased but DALY rates decreased in individuals aged 50-69.DALY surged in individuals aged 70 and above,male DALY rates showed increasing trend and female DALY rates showed slightly decreasing trend.Conclusions:The disease burden of ischemic stroke in China is significantly affected by metabolic risk factors.Although prevention and control have achieved certain positive results,the overall disease burden in China is higher than that of the world,and precise intervention strategies need to be developed for different genders and ages in China.

Objective To develop and verify a method for determination of cyanide residues in polysaccharide-protein conjugate vaccines based on flow injection analysis(FIA)with amperometric detector.Methods After removing macromolecular substances in the samples by ultrafiltration,the cyanide residues were determined by a 3700 automatic chemical analyzer with the injection time of 35 s,injection volume of 200 μL,pump speed of 40%,sample cycle time of 140 s,ultraviolet wavelength of 312 nm and an Ampere detector.The developed method was verified for the specificity,matrix effect,linear range,limit of detection(LOD),limit of quantitation(LOQ),accuracy,presicion and stability.The cyanide residues in the polysaccharide derivative bulk(13 batches)and conjugate bulk(21 batches)of Haemophilus influenzae type b conjugate vaccine and group A and C meningococcal conjugate vaccine produced by 5 manufacturers were determined by the developed method.Results Blank samples showed no interference to detection;The recoveries of the matrix effector solution of Haemophilus influenzae type b conjugate vaccine polysaccharide derivative and conjugate bulk,group A and C meningococcal conjugate vaccine polysaccharide derivative and conjugate bulk were 97.4%,102.4%,96.8% and 99.8% respectively,with all CV values less than 15%;In the range of 0.312 5 ～ 80 ng/mL,cyanogroup concentration showed a good linear relationship with peak height with a regression equation of y = 133.13 x + 57.556,R2= 0.999 1;The LOD was 0.2 ng/mL,and the LOQ was 0.6 ng/mL.The average recoveries of the control solution were 108.9%,106.5%,103.5% respectively with RSD value of 6.4% in the groups added with 5,10 and 20 ng/mL of cyanogroup and the CV values of precision verification were all less than 15%;The average concentrations of the control solution injected 20 times continuously were 76,38,18and 5 ng/mL with all CV values less than 15%,when cyanogroup concentration was 80,40,20 and 5 ng/mL,respectively.Cyanide residues were detected in 13 batches of derivative bulk samples,while not in 2 batches of 21 batches of polysaccharide conjugate bulk samples,and were detected in the others.Conclusion The developed method had good accuracy,precision and stability,which might be applied to the quantitative determination of cyanide residues in polysaccharideprotein conjugate vaccines.

Objective:To investigate the association between cancer fatalism and optimistic attitudes among colorectal cancer patients, and how the above linkage is moderated by the involvement of patients′ opinions, the family members′ opinions and the physicians′ opinions in treatment decision-making.Methods:A cross-sectional survey was conducted on 64 patients diagnosed with colorectal cancer and awaiting radical colorectal cancer surgery in the Department of General Surgery of Beijing Friendship Hospital Affiliated to Capital Medical University, from January 2021 to December 2021. There were 38 males and 26 females, aged (61.2±13.0) years from 30 to 84 years. Cancer fatalism, optimism attitudes, and the involvement of patients′ opinions, the family members′ opinions and the physicians′ opinions in treatment decision-making were assessed. The patients′ cancer fatalism beliefs were measured by the " Chance" subscale of the Form C of the Multidimensional Health Locus of Control (MHLC-C), optimism attitudes were assessed by the Chinese version of the revised Life Orientation Test (CLOT-R), and the influence of patients′, family members′, and physicians′ opinions in the medical decision-making process was measured by a self-designed single factor scale. Measurement data of normal distribution were expressed as mean±standard deviation ( ± s). Measurement data of skewed distribution were expressed as M( Q1, Q3). Spearman correlation analysis and Chi-square test was used to examine the association between the main outcome variable (patients′ optimistic attitudes) and demographic and clinical characteristics. Interaction was examined by hierarchical linear regression analysis combined with simple slope tests. Results:Cancer fatalism was negatively associated with patients′ optimistic attitudes ( r=-0.35, P<0.01). Optimistic attitude of patients was significantly and negatively correlated with the influence of family members′ opinions on medical decision-making ( r=-0.25, P<0.05). There were significant positive correlations between the influence of patients′ and family members′ opinions ( r=0.50, P<0.01), family members′ and physicians′ opinions ( r=0.67, P<0.01), and physicians′ and patients′ opinions ( r=0.38, P<0.01) in medical decision making. Hierarchical linear regression analysis showed a negative association between cancer fatalism and optimism ( β=-0.32, P=0.01). This association was further moderated by the involvement of family members′ opinions ( β=-0.56, P<0.01) and the involvement of physicians′ opinions ( β=-0.36, P=0.04) in medical decision-making. Simple slope tests revealed that the negative impact of fatalistic attitudes on patients′ optimism attitudes may be potentiated when family members′ opinions have high influence on medical decision-making, while the negative impact may be buffered to some extent when physicians′ opinions have high influence on medical decision-making. Conclusions:Cancer fatalism had a negative effect on patients′ optimism. The high influence of physicians in treatment decision-making buffered the negative effect of cancer fatalism on optimism; the high influence of family members in treatment decision-making potentiated the negative effect of cancer fatalism on optimism. In the process of doctor-patient communication and shared decision-making, for patients with strong fatalistic attitudes, consideration should be given to appropriately increasing direct informational communication between physicians and patients and reducing excessive family intervention in medical decision-making, so as to enhance patients′ autonomy for treatment, promote optimism, and reduce the negative effects of cancer fatalism.

OBJECTIVE To analyze and identify non-target proteins in human albumin and human immunoglobulin by ultra high performance liquid chromatography tandem linear ion trap orbitrap mass spectrometry. METHODS The extract was separated on a ACQUITY UPLC peptide BEH C18(300Å, 1.7 μm, 2.1 mm×100 mm) column and the gradient elution was performed with mobile phase consisting of 0.1% formic acid aqueous solution-0.1% formic acid acetonitrile. The analytes were detected in Full MS/dd-MS2(TopN). RESULTS A total of 52 non-target proteins were identified from human albumin and human immunoglobulin. Among them, 25 non-target proteins were identified in human albumin samples, and 27 non-target proteins were identified in human immunoglobulin samples. CONCLUSION The established qualitative method can rapidly, accurately and systematically identify various proteins in human albumin and human immunoglobulin. The results provide reference for the quality control of the preparation as well as its further clinical application.

Objective:To provide a basis for the selection of antiemetic regimen by establishing an artificial intelligence model for predicting chemotherapy-induced nausea and vomiting (CINV) in cancer patients receiving platinum-based chemotherapy with high emetic risk.Methods:The clinical information on cancer patients who received cisplatin or carboplatin with area under the blood concentration-time curve (AUC) ≥4 and registered in the Department of Oncology, Tianjin Medical University General Hospital from January 2018 to December 2022 was collected, including gender, age, history of alcohol consumption, history of vomiting in pregnancy, chemotherapy cycle, patient expects to have CINV, chemotherapeutic agents, antiemetic regimen, out-of-hospital antiemetic treatment, sleep of less than 7 hours on the night before chemotherapy, occurrence of CINV in the previous cycle, and creatinine clearance (Ccr). After pre-processing, the data were randomly divided into the training set and the test set. The training set was used to construct the prediction model, and the test set was used to evaluate the prediction efficiency of the model. Three algorithms, gradient boosting decision tree (GBDT), random forest (RF), and logistic regression (LR), were used to build a prediction model and evaluate the model performance, respectively. The evaluation metrics included accuracy, sensitivity, recall, F1 value (the reconciled mean of sensitivity and recall), and area under the receiver operating characteristic curve (AUROC). Finally, Shapley Additive exPlanation (SHAP) was applied to analyze the interpretability of the clinical features with predictive significance.Results:A total of 698 patients, 439 males (62.9%) with a median age of 64 (21, 84) years, were included in this study and received a total of 1 654 cycles of chemotherapy. The chemotherapy regimen contained cisplatin in 364 cases with 864 cycles of chemotherapy, and carboplatin with AUC ≥4 in 361 cases with 790 cycles of chemotherapy. The number of treatment cycles in which neurokinin-1 receptor antagonist (NK-1 RA), 5-hydroxytryptamine-3 receptor antagonist (5-HT3 RA), and dexamethasone were selected as the antiemetic regimen was 1 347, and in those with the selection of 5-HT3 RA and dexamethasone was 307. The Spearman′s correlation analysis showed no strong correlation between the feature variables in the patients, and all of them could be used for model building. GBDT optimal hyperparameters n_estimators=500, max_depth=9; RF optimal hyperparameters max_depth=5; LR optimal hyperparameters penalty=L2. Three prediction models, GBDT, RF and LR, were established based on the optimal hyperparameter training data, respectively. The accuracy of GBDT model was 0.903, sensitivity was 0.882, recall was 0.903, F1 value was 0.883, and AUROC was 0.778±0.036 (95% CI: 0.739-0.814); the accuracy of RF model was 0.885, sensitivity was 0.861, recall was 0.885, F1 value was 0.870, and AUROC was 0.679±0.041 (95% CI: 0.636-0.720); the LR model had an accuracy of 0.817, a sensitivity of 0.851, a recall of 0.817, an F1 value of 0.832, and an AUROC of 0.682±0.042 (95% CI: 0.639-0.723). Ccr, age, chemotherapy cycle, history of alcohol consumption, and patient expects to have CINV were the main features predicted by the model. The risk of CINV was negatively associated with Ccr, age, and chemotherapy cycle. And the risk of CINV was lower in patients with no history of drinking alcohol and patient expects to have CINV. Conclusion:The GBDT, RF, and LR models could all predict the risk of CINV in patients receiving platinum-based chemotherapy with high emetic risk, with the GBDT model having the best predictive effect.