Objective To investigate the characteristics of body fluid metabolic profile in patients with kidney stones based on surface-enhanced Raman spectroscopy,and to explore its application value and provide a reference for the screening of patients with kidney stones.Methods A total of 25 patients with kidney stones and 25 healthy controls were involved.Urine and blood samples were collected,whose spectra were measured with surface-enhanced Raman spectroscopy.The mean and difference spectra were plotted with origin software.The normalized data were processed with principal component analysis combined with linear discriminant analysis(PCA-LDA).Finally,the performance of the PCA-LDA method was evaluated with the receiver operating characteristic(ROC)curve.Results The levels of phosphatidylinositol,phenylalanine,palmitic acid/fatty acids,etc.in the urine of patients with kidney stones are higher than those in healthy controls,while the levels of components such as uracil and glycogen are lower.The content of methyl bands in the plasma of patients with kidney stones is higher than that of healthy controls,while the contents of glycogen,phosphatidylinositol,protein-tyrosine,phenylalanine,palmitic acid/fatty acid,hydroxyproline/tyrosine,and lipids are lower than those of healthy controls.Conclusion Surface-enhanced Raman spectroscopy can identify the changes in various metabolites in patients with kidney stones,and the combination of PCA-LDA and ROC analysis is helpful for the screening of patients.

Objective To determine the predictive parameters of impacted ureteral stones and evaluate the predictive value of ureteral wall thickness for impacted ureteral stones.Methods A total of 93 patients with proximal ureteral stones from January 2017 to December 2017 were included in the study [71 males and 22 females,aged 30-80 years,and body mass index (23.7 ± 2.7) kg/m2].Both clinical and computed tomography urography (CTU) data were compared between patients with or without impacted ureteral stone,including sex,age,body mass index,renal pelvic diameter,longitudinal size of stone,transverse size of stone,stone surface area,stone volume,hounsfield units of stone,diameter of the ureter proximal to the stone,and ureteral wall thickness at the impacted ureteral stone site.The receiver operating characteristic curve (ROC) was used to analyze the performance of each of the above-mentioned parameters for predicting the impacted ureteral stones.Multivariate logistic regression analysis was used to select the independent risk factors of impacted ureteral stones.Results Among 93 patients,38 (40.8％) patients were with impacted stones and 55 (59.1％) without impacted stones.Univariate analysis showed significant difference in ureteral wall thickness (t =6.344,P ＜ 0.001),diameter of the ureter proximal to the stone (U =607.5,P =0.001),longitudinal size of stone(U =580.5,P ＜0.001),transverse size of stone(t =4.172,P ＜0.001),stone surface area(U =508.5,P ＜ 0.001),stone volume (U =508.5,P ＜ 0.001) and hounsfield units of stone (t =6.344,P =0.006) between patients with or without impacted stones.Ureteral wall thickness(UWT)showed the largest area under curve (AUC) among those parameters (AUC =0.825,P ＜ 0.001),followed by stone surface area and stone volume.The optimal cut-off value of ureteral wall thickness was 3.16 mm,with sensitivity of 71.1％ and specificity of 85.5％.Multivariate analysis showed that ureteral wall thickness (Wald =18.709,P ＜ 0.001) and stone volume (Wald =8.391,P =0.004) were independent predictors of impacted stones.Conclusion Ureteral wall thickness was related to the presence of impacted ureteral stones and could be used for predicting impacted ureteral stones.

Objective: To classify the morphology of mandible posterior region and provide reference for the planning of dental implantation. Methods: Cone beam CT data of 208 patients were collected. The CT data were imported into CS 3D imaging V3 software and then the morphology of mandible posterior region were analyzed. The types of premolar and molar mandible cross-section morphology were recorded, classified and analyzed. Results: The results showed that type A (vertical type) (79%-96%) was the most common in the premolars, whereas type B (inclined type) (36%-37%) and type C (lingual inverted concave) (30%-54%) were the most common types in the molars, followed type D (absorption severe type) (2%-5%). There was a statistically significant differences in tooth positions (P<0.001), tooth deficiency aspect (P<0.001) and different side (P=0.013), different age (P<0.001), and different gender (P=0.007). Conclusions Using cone beam CT to determine the morphology of mandible may be a reference for the planning of dental implantation.

【Objective】 To explore the expression and clinical significance of prostate cancer tissue-specific lncRNAs. 【Methods】 The gene differences of 492 prostate cancer tissues and 152 adjacent tissues in TCGA and GEO genomic databases were analyzed with bioinformatics methods. A total of 5 lncRNAs were screened out, and their specificity in prostate tissues and impact on the prognosis of patients were analyzed. 【Results】 The 5 lncRNAs included PCAT14, PCA3, CTBP1-AS, DRAIC, and GPC5-AS1. PCAT14 and PCA3 were specifically expressed in prostate cancer tissues, and elevated expression was related to the prognosis. Moreover, they were well correlated with prostate cancer-specific antigens such as KLK3, AMACR, SLC45A3, and so on. GO function enrichment analysis and KEGG pathway enrichment analysis showed that the differential expression of PCA3 was closely related to phagocytosis, cell recognition, defense response to bacteria, immunoglobulin complex, Golgi apparatus, antigen binding, chemokine receptor binding, white matter digestion and absorption, renin-angiotensin system and other signaling pathways, while the differential expression of PCAT14 was closely related to the activity of Golgi apparatus and ion channels, renin secretion, cAMP signaling pathway, and gonadotropin secretion-related signaling pathway. 【Conclusion】 PCA3 and PCAT14 are specifically expressed in prostate cancer tissues, not in normal tissues, which can be used as potential indicators for the diagnosis of prostate cancer.