Objective To conduct item analysis on Work Attitude Scale(Wa) and to develop a short-versioned scale.Methods Wa and Symptom Checklist 90(SCL-90) were administered to 3767 recruits,item analysis of Wa was conducted and short version of Wa was developed based on the results of item analysis,Cronbach' s αcoefficient of the original scale and the short-versioned scale was calculated,criterion validity of the original scale and the short-versioned scale was analyzed using SCL-90 as the validity criterion.For other samples,16 Personality Factor Questionnaire (16PF),Eysenck Personality Questionnaire ( EPQ),and Self-Rating Anxiety Scale (SAS) were tested while the short-versioned scale was tested at the same time,criterion validity of the short-versioned Wa was analyzed using 16PF,EPQ,and SAS as the validity criterion.Results Difficulty of the original scale was from 0.03 to 0.87,27 items' difficulty was less than 0.20 or greater than.Discrimination index was from 0.04 to 0.56,22 items' discrimination index was less than 0.30.Correlation coefficient of the item score and the total score is from 0.02 to 0.52,18 items' correlation coefficient was less than 0.30.The short-versioned scale was made up of the 18 items with better quality.Cronbach' s α coefficient of the original scale and the short-versioned scale was 0.778 and 0.789,respectively.Both the total score of the original scale and the short-versioned scale were significantly correlated with the scores of SCL-90,and all the correlation coefficient were above 0.40.The correlation coefficient between the score of the short-versioned scale and that of the original scale was 0.934.The correlation coefficient between the score of the short-versioned scale and 16PF,EPQ,SAS was significant.Conclusion The short-versioned scale has a higher reliability and good validity.

BACKGROUND:Traumatic spinal cord injury primarily relies on scale assessment and imaging examinations in clinical practice.However,there are limitations in predicting the prognosis of the injury.Therefore,the use of metabolomics technology for biomarker screening is significant for estimating the extent of damage,injury and recovery,as well as developing new therapies. OBJECTIVE:To characterize the metabolic features of patients with traumatic spinal cord injury using metabolomics technology and explore potential biomarkers and disrupted metabolic pathways. METHODS:Serum and urine samples were collected from 20 patients with traumatic spinal cord injury(observation group)and 10 healthy subjects(control group).Metabolites were analyzed and multivariate statistical analysis was then performed for data processing to screen differential metabolites.Metabolic pathway enrichment was performed using MetaboAnalyst software.Logistic regression was applied to construct a biomarker combination model,and its relationship with the American Spinal Injury Association grading was analyzed. RESULTS AND CONCLUSION:Significant differences in 160 and 73 metabolites were detected in the serum and urine samples of the two groups,respectively.Pathway enrichment analysis showed evident disturbances in lipid metabolism after traumatic spinal cord injury,including sphingolipid,arachidonic acid,α-linolenic acid,and arachidonic acid metabolism,as well as glycerophospholipid and inositol phosphate biosynthesis.The combination of two identified biomarkers,telmisartan and quercetin glycoside,showed a correlation with the American Spinal Injury Association grading in both serum and urine levels.Thus,metabolomics technology provides assistance in further understanding the pathological mechanisms of traumatic spinal cord injury and screening therapeutic targets.The identified metabolic biomarker combination may serve as a reference for assessing the severity of traumatic spinal cord injury.

Objective: To compare the clinicopathological characteristics of second primary lung cancer following breast cancer and lung metastases from breast cancer, and then to analyze the risk factors in breast cancer patients with second primary lung tumor. Methods: Clinical data of 55 breast cancer patients with second primary lung tumor and 205 breast cancer patients with solitary pulmonary metastasis in Shandong Cancer Hospital from January 2006 to January 2017 were retrospectively analyzed. The risk factors of primary lung cancer following breast cancer were analyzed using logistic regression model. Results: Second primary lung cancer in patients with first breast cancer accounted for approximately 21.2%(55/260) of pulmonary malignant solitary nodules, and 0.84%(55/6 580) of all breast cancer patients. The median intervals between the diagnosis of second primary lung cancer or lung metastasis and first breast cancer were 52 months and 42 months, respectively. These two groups showed significant difference between age, time interval between diagnoses, breast tumor size, axillary lymph node metastasis, estrogen receptor, molecular subtype (luminal B and triple-negative) and history of radiotherapy (P<0.05 for all). A multivariate logistic regression model confirmed that age (OR=1.088, P<0.001), breast tumor size(OR=0.480, P<0.001), and radiotherapy history (OR=3.460, P=0.004) were all independent factors for second primary lung cancer. Conclusions For isolated pulmonary nodules in patients with breast cancer, especially for those with elder age, larger tumor size and radiotherapy history, we should distinguish the second primary lung cancer from pulmonary metastasis. The treatment regimen for lung metastasis and primary lung cancer in patients with breast cancer are entirely distinct. The timely histopathology examinations for pulmonary nodes in patients with breast cancer are recommended.