Objective To study the independent risk factors of relapse of smoking among current smokers of different ages who underwent percuta?neous coronary intervention(PCI). Methods Totally 197 current smokers who received PCI from January 2007 to December 2009 in the Fourth Affiliated Hospital of China Medical University were enrolled. Information about relapse of smoking was collected through the medical records and the telephone follow?up. Discrepancy of risk factors of smoking resumption was compared in different age groups. Results Totally 112 patients re?sumed smoking after PCI. There were 87 patients in the non?elderly group and 25 in the elderly group. According to the correlation analysis,more than one stents(P=0.025),severe nicotine dependence(P=0.001)and long time for daily passive smoking(P=0.000)were related with relapse in the non?elderly group,and there was a negative correlation between more than one stents and relapse. But in the elderly group,relapse was associ?ated with history of hypertension(P=0.034). According to the logistic regression analysis in different age groups,independent predictors of smoking relapse in the non?elderly group were severe nicotine dependence(OR:3.914,P=0.003)and long time for daily passive smoking(OR:1.352,P=0.000). And in the elderly group,independent risk factors of smoking relapse were male(OR:17.325,P=0.027),history of hypertension(OR:13.185,P=0.005),long time for daily passive smoking(OR:1.273,P=0.045)Conclusion Independent risk factors of smoking relapse were different in the elderly group and the non?elderly group. In the non?elderly group,these factors were severe nicotine dependence and long time for dai?ly passive smoking. And in elderly group,these factors were male,history of hypertension,long time for daily passive smoking.

Objective:To study the relationship between neutrophil to lymphocyte ratio (N/L) and traditional cardio‐vascular risk factors among community 35~64‐year‐old residents .Methods :A total of 1884 residents (548 males and 1336 females) from urban Shenyang city received baseline condition questionnaire on cardiovascular diseases and re‐lated diseases from Apr 2011 to Feb 2012. According to presence of cardiovascular risk factors or not ,subjects were divided into healthy control group (n=675) and risk factor group (n=1209);according to number of risk factors , risk factor group was further divided into one risk factor group (n=491) ,two risk factors group (n=263) and ≥3 risk factors group (n=455) .Morning blood sample and urine sample were retained to measure blood and urine rou‐tine ,blood glucose and blood lipid profile etc in all subjects .N/L was compared and analyzed among all groups .Re‐sults:Among patients with only one of following risk factors [hypertension ,diabetes mellitus (DM) ,dyslipidemia and obesity] ,N/L levels of patients with hypertension or DM were significantly higher than that of healthy control group [1.55(1.15 ,1.95) ,1.60(1.21 ,2.07) vs .1.45(1.09 ,1.91)] , P<0.05 both ,and there were no significant difference between any other one risk factor group and healthy control group , P>0.05 all .Among risk factor sub‐groups ,N/L level of ≥3 risk factors group was significantly higher than that of two risk factors group [1.57(1.16 , 2.04) vs .1.41(1.07 ,1.89) ,P<0.05] ,and there was no significant difference between any other two groups (P>0.05) .Conclusion:N/L significantly related to hypertension or DM ,and N/L level of ≥3 risk factors group was sig‐nificantly higher than that of two risk factors group ,N/L is helpful to assess risk of cardiovascular diseases .

Objective:To explore the value of multiphasic CT-based radiomics signature in predicting the invasive behavior of pancreatic solid pseudopapillary neoplasm (pSPN).Methods:The multiphasic CT images of patients with pSPN confirmed by postoperative pathology in the First Affiliated Hospital of Zhengzhou University from January 2012 to January 2021 were analyzed retrospectively. There were 23 cases of invasiveness and 59 cases of non-invasiveness. The region of interest(ROI) was artificially delineated layer by layer in the plain scan, arterial-phase and venous-phase images, respectively. The 1 316 image features were extracted from each ROI. The data set was divided into training and validation sets with a ratio of 7∶3 by stratified random sampling, and synthetic minority oversampling technique (SMOTE) algorithm was used for oversampling in the training set to generate invasive and non-invasive balanced data for building the training model. The constructed model was validated in the validation set. The receiver operating characteristic(ROC) analysis was used to evaluate model performance and the Delong′s test was applied to compare the area under the ROC curve (AUC) of different predict models. The improvement for classification efficiency of each independent model or their combinations were also assessed by net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices.Results:After feature extraction, 2, 6 and 3 features were retained to construct plain-scanned model, arterial-phase and venous-phase models, respectively. Seven independent-phase and combined-phase models were established. Except the plain-scanned model, the AUC values of other models were greater than 0.800. The arterial-phase model had the best efficiency for classification among all independent-phase models. The AUC values of arterial-phase model in the SMOTE training and validation sets were 0.913 and 0.873, respectively. By combining the radiomics signature of the arterial-phase and venous-phase models, the AUC values of training and validation sets increased to 0.934 and 0.913 respectively. There were no significant differences of the AUC values between the scan-arterial venous-phase model and arterial venous-phase model in both training and validation sets (both P>0.05). The NRI and IDI indexes showed that the combined form of plain-scan model and arterial-venous-phase model could not significantly improve the classification efficiency in the validation set (both NRI and IDI<0). Conclusions:The arterial-phase CT-based radiomics model has a good predictive performance in the invasive behavior of pSPN, and the combination with a venous-phase radiomics model can further improve the model performance.

Objective:To construct of a computed tomography (CT) based radiomics model for predicting the prognosis of patients with gastric neuroendocrine neoplasm (GNEN) and inves-tigate its application value.Methods:The retrospective cohort study was conducted. The clinico-pathological data of 182 patients with GNEN who were admitted to 2 medical centers, including the First Affiliated Hospital of Zhengzhou University of 124 cases and the Affiliated Cancer Hospital of Zhengzhou University of 58 cases, from August 2011 to December 2020 were collected. There were 130 males and 52 females, aged 64(range, 56-70)years. Based on random number table, all 182 patients were divided into the training dataset of 128 cases and the validation dataset of 54 cases with a ratio of 7:3. All patients underwent enhanced CT examination. Observation indicators: (1) construction and validation of the radiomics prediction model; (2) analysis of prognostic factors for patients with GNEN in the training dataset; (3) construction and evaluation of the prediction model for prognosis of patients with GNEN. Measurement data with skewed distribution were represented as M(range), and comparison between groups was conducted using the Mann-Whitney U test. Count data were described as absolute numbers, and the chi-square test, corrected chi-square test or Fisher exact probability were used for comparison between groups. The Kaplan-Meier method was used to calculate survival rate and draw survival curve, and the Log-rank test was used for survival analysis. The COX regression model was used for univariate and multivariate analyses. The R software (version 4.0.3) glmnet software package was used for least absolute shrinkage and selection operator (LASSO)-COX regression analysis. The rms software (version 4.0.3) was used to generate nomogram and calibration curve. The Hmisc software (version 4.0.3) was used to calculate C-index values. The dca.R software (version 4.0.3) was used for decision curve analysis. Results:(1) Construction and valida-tion of the radiomics prediction model. One thousand seven hundred and eighty-one radiomics features were finally extracted from the 182 patients. Based on the feature selection using intra-group correlation coefficient >0.75, and the reduce dimensionality using LASSO-COX regression analysis, 14 non zero coefficient radiomics features were finally selected from the 1 781 radiomics features. The radiomics prediction model was constructed based on the radiomics score (R-score) of these non zero coefficient radiomics features. According to the best cutoff value of the R-score as -0.494, 128 patients in the training dataset were divided into 64 cases with high risk and 64 cases with low risk, 54 patients in the validation dataset were divided into 35 cases with high risk and 19 cases with low risk. The area under curve (AUC) of radiomics prediction model in predicting 18-, 24-, 30-month overall survival rate of patients in the training dataset was 0.83[95% confidence interval ( CI ) as 0.76-0.87, P<0.05], 0.84(95% CI as 0.73-0.91, P<0.05), 0.91(95% CI as 0.78-0.95, P<0.05), respectively. The AUC of radiomics prediction model in predicting 18-, 24-, 30-month overall survival rate of patients in the validation dataset was 0.84(95% CI as 0.75-0.92, P<0.05), 0.84 (95% CI as 0.73-0.91, P<0.05), 0.86(95% CI as 0.82-0.94, P<0.05), respectively. (2) Analysis of prognostic factors for patients with GNEN in the training dataset. Results of multivariate analysis showed gender, age, treatment method, tumor boundary, tumor T staging, tumor N staging, tumor M staging, Ki-67 index, CD56 expression were independent factors influencing prognosis of patients with GNEN in the training dataset ( P<0.05). (3) Construction and evaluation of the prediction model for prognosis of patients with GNEN. The clinical prediction model was constructed based on the independent factors influen-cing prognosis of patients with GNEN including gender, age, treatment method, tumor boundary, tumor T staging, tumor N staging, tumor M staging, Ki-67 index, CD56 expression. The C-index value of clinical prediction model in the training dataset and the validation dataset was 0.86 (95% CI as 0.82-0.90) and 0.80(95% CI as 0.72-0.87), respectively. The C-index value of radiomics prediction model in the training dataset and the validation dataset was 0.80 (95% CI as 0.74-0.86, P<0.05) and 0.75(95% CI as 0.66-0.84, P<0.05), respectively. The C-index value of clinical-radiomics combined prediction model in the training dataset and the validation dataset was 0.88(95% CI as 0.85-0.92) and 0.83 (95% CI as 0.77-0.89), respectively. Results of calibration curve show that clinical prediction model, radiomics prediction model and clinical-radiomics combined prediction model had good predictive ability. Results of decision curve show that the clinical-radiomics combined prediction model is superior to the clinical prediction model, radiomics prediction model in evaluating the prognosis of patients with GNEN. Conclusions:The predection model for predicting the prognosis of patients with GNEN is constructed based on 14 radiomics features after selecting. The prediction model can predict the prognosis of patients with GNEN well, and the clinical-radiomics combined prediction model has a better prediction efficiency.

Biochemistry/history* ; China ; Exercise/physiology* ; History, 20th Century ; History, 21st Century ; Humans ; Sports Medicine/history*

Patient experience is an important window for modern hospital management and medical service quality, and also an important point for humanistic hospital construction. Improving patient experience is of great significance for constructing harmonious doctor-patient relationship and improving patients’ satisfaction and sense of gain. Based on the perspective of patient experience improvement, this paper analyzed the core value of "patient demand first" of Mayo Clinic and the operational experience of Cleveland Medical Center Patient Experience Office, and applied them to the cultivation of humanistic hospital culture in the First Affiliated Hospital of Xi’an Jiaotong University. Based on the concept of "strengthening patient demand orientation", with the goal of "building a high-quality patient service system and significantly improving patient satisfaction", through building education platforms for medical ethics and medical humanism, exploring the medical humanism dissemination mode for medical staff, and carrying out the humanism literacy cultivation practice in the training camp for improving hospital service efficiency, the humanistic cultural atmosphere of the hospital has been further enhanced, and the patient satisfaction has been steadily improved. It provides reference for the cultivation of humanistic literacy and the construction of new culture in public hospitals in the context of high-quality development.

Objective To analyze the correlation between intestinal flora changes and neonatal necrotizing enterocolitis (NEC)through 16S rRNA metagenomic sequencing and bacterial culture. Methods From September 2018 to March 2019, 10 NEC cases and 6 controls were randomly selected in the neonatal ICU ward of Nanjing maternal and child health care hospital to analyze the 16S rRNA metagenomic diversity of the for intestinal flora. The fecal samples and corresponding environmental samples were corrected from 51 cases of NEC children and their case controls to isolate and culture Clostridium. Results The dispersion of samples within the case group was smaller than that of the control group, and the sample diversity was higher than that of the control group. In the isolation and culture of Clostridium, the overall detection rate of Clostridium in the case group was 43.14% (22/51), and the detection rate of Clostridium butyricum was the highest (19.61%, 10/51). There was a statistical difference between the two groups (χ²=5.85, P=0.015 58). All Clostridium strains did not carry the A, B and E type neurotoxin genes. Conclusion: Increased intestinal flora diversity, intestinal flora abundance and changes in the abundance of Clostridium may be closely related to the intestinal environment of children with NEC; Clostridium, especially Clostridium butyricum, may be related to the occurrence of NEC.

To develop a clinical diagnosis technique for bluetongue virus infection, we established serotype-specific methods to detect serotype 4 of bluetongue virus (BTV-4). Two monoclonal antibodies (mAbs) against VP2 protein of BTV-4, named 4A-1G7 and 4B-1B6, were used as competitive antibodies in the competitive enzyme-linked immunosorbent assays (C-ELISA). We detected 50 negative serum samples from sheep, goats and cattle by C-ELISA. The cut-off values of 4A-1G7 and 4B-1B6 mAbs were 49% and 40%, respectively. The results of the sensitivity, specificity and repeatability by detecting standard positive serum, were consistent with the general standard of Office International Des Epizooties. Furthermore, serum samples of BTV-4, BTV-18 and BTV-20 infection could be screened out through the combined C-ELISAs by 4A-1G7 and 4B-1B6 mAbs. Thus, this technique may diagnose BTV-4, BTV-18 and BTV-20 infections.

To confirm the B cell epitope recognized by monoclonal antibody (MAb) 3G11 of bluetongue virus type 8 (BTV-8) VP2 protein prepared in our laboratory, antigen epitopes recognized by 3G11 were screened and identified by phage display technology. KLLAT sequence was found by sequencing of blue spot after four rounds panning and 283LL284 of common short peptide sequence was obtained after comparison to amino acid sequence of BTV-8 VP2 protein. The peptide sequences KLLAA, KALAT, KLAAT and KLLAT were synthesized and identified by indirect ELISA. KLLAA and KLLAT bound strongly with supernatant and as cites of 3G11 cells and reacted specifically with BTV-8 positive standard sera. Further sequence analysis showed that amino acid sequence 283LL284 was conserved among different serotypes of BTV-8 strains, and283LL284 was the key amino acids of antigen epitopes recognized by 3G11. This study laid the foundation to establish type 8 BTV specific immunological detection methods.