Objective To explore the effect of resilience in the relationship between workplace bullying （WPB） and professional identity among nursing interns. Methods A total of 292 nursing interns from six grade A hospitals were selected as the research subjects using convenience sampling method. The WPB，professional identity，resilience，perceived stress and coping styles were investigated by the Negative Acts Questionnaire Revised， the Professional Identity Questionnaire for nurse students，the Chinese version of 10-item Connor-Davidson Resilience Scale，the Chinese Perceived Stress Scale and the Simplified Coping Style Questionnaire. Results The scores of WPB and perceived stress were negatively correlated with those of professional identity，resilience，and positive coping styles（PCS）［Spearman correlation coefficients（rS ）were −0.354，−0.316，−0.388，−0.488，−0.636 and −0.478，all P<0.01］. There was a negative correlation between negative coping styles（NCS）and professional identity（rS =−0.117，P=0.046）. The scores of resilience and professional identity were positively correlated with that of PCS（rS were 0.539 and 0.482，both P<0.01）. There was a positive correlation between resilience and professional identity （rS =0.567，P<0.01）. The scores of WPB and perceived stress were positively correlated with that of NCS（rS were 0.350 and 0.281，both P<0.01）. There was a positive correlation between WPB and perceived stress（rS =0.419，P<0.01）. The scores of resilience and PCS were not correlated with that of NCS（both P>0.05）. Resilience played a mediating role between WPB and professional identity. The interaction between WPB and NCS could predict the professional identity and resilience of nursing interns（standardized regression coefficient were 0.31 and 0.17，both P<0.01）. Conclusion WPB can directly or indirectly affect nursing interns’professional identity through resilience，and NCS plays a moderating role on the direct effect of WPB and professional identity，and the relationship between WPB and resilience.

Objective To analyze molecular evolution of carbapenemase KPC-12 and its binding free energies with β-lactams.Methods Class A beta-lactamases were divided into 2 clusters:those with carbapenemase activities and those without.Minimum Evolution method in MEGA4.1 software was used to analyze molecular evolution of class A beta-lactamases with carbapenemase activity,including KPC-2 to KPC-13,SFC-1,SME-1,IMI-1,NMC-A,and class A beta-lactamases without carbapenemase activity,including TEM-1,SHV-1.Then,tertiary structure of KPC-12 was predicted by homology modeling as reported in SWISS-MODEL database depending on tertiary structure of KPC-2.Moreover,DOCK module in ArgusLab 4.1 software was used to perform molecular docking of KPC-12 to 10 kinds of beta-lactams substrates,and the binding free energies (△ G) were calculated.Results Molecular evolution between KPC-12 and KPC-2 was the closest.The top three decline in binding free energies of β-lactams were penicillin G sodium salt (△G =-8.45149 kcal/mol),ertapenem (△G =-8.36383 kcal/mol) and ampicillin (△G =-8.19326 kcal/mol),while the last two decline in binding free energies of β-lactams were aztreonam (△G =-6.50614 kca]/mol) and clavulanic acid (△G =-6.88533 kcal/mol).Conclusion Carbapenemase KPC-12 has high catalytic activities to penicillin G sodium salt,ertapenem and ampicillin,while has low catalytic activities to aztreonam and clavulanic acid.

Objective To investigate the correlation between spread through air space (STAS) of sub-centimeter non-small cell lung cancer and clinical characteristics and radiological features, constructing a nomogram risk prediction model for STAS to provide a reference for the preoperative planning of sub-centimeter non-small cell lung cancer patients. Methods The data of patients with sub-centimeter non-small cell lung cancer who underwent surgical treatment in Nanjing Drum Tower Hospital from January 2022 to October 2023 were retrospectively collected. According to the pathological diagnosis of whether the tumor was accompanied with STAS, they were divided into a STAS positive group and a STAS negative group. The clinical and radiological data of the two groups were collected for univariate logistic regression analysis, and the variables with statistical differences were included in the multivariate analysis. Finally, independent risk factors for STAS were screened out and a nomogram model was constructed. The sensitivity and specificity were calculated based on the Youden index, and area under the curve (AUC), calibration plots and decision curve analysis (DCA) were used to evaluate the performance of the model. Results A total of 112 patients were collected, which included 17 patients in the STAS positive group, consisting of 11 males and 6 females, with a mean age of (59.0±10.3) years. The STAS negative group included 95 patients, with 30 males and 65 females, and a mean age of (56.8±10.3) years. Univariate logistic regression analysis showed that male, anti-GAGE7 antibody positive, mean CT value and spiculation were associated with the occurrence of STAS (P＜0.05). Multivariate regression analysis showed that associations between STAS and male (OR=5.974, 95%CI 1.495 to 23.872), anti-GAGE7 antibody positive (OR=11.760, 95%CI 1.619 to 85.408) and mean CT value (OR=1.008, 95%CI 1.004 to 1.013) were still significant (P＜0.05), while the association between STAS and spiculation was not significant anymore (P=0.438). Based on the above three independent predictors, a nomogram model of STAS in sub-centimeter non-small cell lung cancer was constructed. The AUC value of the model was 0.890, the sensitivity was 76.5%, and the specificity was 91.6%. The calibration curve was well fitted, suggesting that the model had a good prediction efficiency for STAS. The DCA plot showed that the model had a good clinically utility. Conclusion Male, anti-GAGE7 antibody positive and mean CT value are independent predictors of STAS positivity of sub-centimeter non-small cell lung cancer, and the nomogram model established in this study has a good predictive value and provides reference for preoperative planning of patients.