Objective:To explore the diagnostic value and correlation of serum tumor markers combined detection of pancreatic cancer. Methods:Selected January 2013 to may 2016 in our hospital in patients with pancreatic cancer in 146 cases,128 cases of non pancreatic cancer with patients and 124 cases of healthy physical examination. Radiation immunity analyzer test groups of serum CA19-9,CA242,CA50,CA125,CEA and TSGF levels and compared between groups. To draw the working characteristic curve(ROC) to analyze the diagnostic value of tumor markers in patients with pancreatic cancer and the correlation of linear correlation analysis of tumor markers. Analysis of independent risk factors for pancreatic cancer using multiple logistic regression models. Results: The pancreatic cancer group of serum CA19-9,CA242,CA50,CA125,CEA and TSGF levels were significantly higher than the control group and non pancreatic cancer group,the differences were statistically significant(P<0. 05 or P<0. 01).Ⅳstage andⅢstage with patients of serum CA19-9,CA242,CA50,CA125 and TSGF levels were significantly higher than Ⅰstage and Ⅱstage with patients(P<0. 01).Ⅳ stage with patients of serum CA19-9, CA242, CA125 and CEA levels were significantly higher than Ⅲ stage with patients ( P<0. 01). The pancreatic cancer group of serum CA19-9,CA242,CA50,CA125,CEA and TSGF of positive rate were significantly higher than that of control group and non pancreatic cancer group(P<0. 01). ROC curves showed that the AUC of serum CA19-9 were higher than other single indexes,the best critical value,sensitivity and specificity were 114. 5 U/ml,81. 2% and 79. 3% respectively. The diagnostic efficacy of the six joint detection were better than the single detection,the sensitivity and specificity were 92. 4% and 76. 5%respectively. Correlation analysis showed that serum CA19-9 were positively correlated with CA242,CA50 and CA125(r=0. 703,P=0. 005;r=0. 572,P=0. 024;r=0. 439,P=0. 036). Multiple logistic regression analysis showed that smoking,incorrect diet,history of diabetes,gallbladder disease history and high levels of CA19-9,CA242,CEA into the regression model,the OR value and 95%CI were 1. 717(0. 736 to 2. 359),2. 865(2. 217 to 3. 685),2. 614(2. 186 to 3. 127),3. 527(2. 842 to 4. 377),4. 214(3. 570 to 4. 962), 2. 315(2. 114 to 2. 539),1. 876(1. 175 to 2. 852). Conclusion: Serum tumor markers combined detection can help to improve the accuracy of early diagnosis of pancreatic cancer and smoking,incorrect diet habits,history of diabetes,biliary disease history and high levels of CA19-9,CA242 and CEA are independent risk factors for pancreatic cancer.

Objective: To analyze the relationship between the serum levels of low density lipoprotein cholesterol (LDL-C) and achilles tendon thickness (ATT).
Methods: We studied 154 patients with high serum level of LDL-C (LDL-C≥3.37 mmol/L) from 2014-03 to 2015-03, the patients were at (18-75) years of age. According to《Guidelines on Prevention and Treatment of Blood Lipid Abnormality in Chinese Adults 2007》, the patients were divided into 2 groups:Borderline high LDL-C (3.3-4.12 mmol/L) group n=50 and High LDL-C (≥4.14 mmol/L) group, n=104;in addition, there was a Normal control group (LDL-C<3.37 mmol/L), n=51. ATT values were measured by standard digital radiography and the results were compared among 3 groups;the relationship between serum levels of LDL-C and ATT was studied.
Results: ATT levels in High LDL-C group (9.42 ± 3.63) mm was higher than Borderline high group (8.24±1.73) mm and Normal control group (6.05±0.28)mm, all P<0.05. The liner correlation coefifcient of serum level of LDL-C and the mean ATT was (r=0.346, P<0.001).
Conclusion: Our preliminary research showed that the higher serum level of LDL-C associated with thicker ATT, they had positive correlation. This phenomenon should be further conifrmed by large sample and multi-center investigation.

Objective To investigate the incidence of live births with Down syndrome(DS) in Sanya city as well as to discuss the related risk factors .Methods The object of investigation was the 25 032 infants who were born in Sanya city ,then the children with clinical suspected of DS were confirmed by peripheral blood chromosome analysis .Meanwhile ,the clinical data of children and their parents were collected ,calculating the incidence of DS in this region and analyzing the related risk factors .Results In this region , the total incidence of DS was 0 .959‰ ,the incidences in the Han nationality and Li nationality were 0 .834‰ ,1 .442‰ respectively . The mean age of DS children′s mother was 29 .8 years old ,and the incidence of DS increased as their mother grew older .Before pregnancy ,DS children′s mother who had an exposure history of toxicant and drugs accounted for 45 .8% .Conclusion The inci‐dence of DS in Sanya is quite high ,so it is extremely essential to strengthen the women′s pregnancy Down syndrome screening and improve the prenatal diagnosis in this region .

Early distinction of bipolar disorder (BD) from major depressive disorder (MDD) is difficult since no tools are available to estimate the risk of BD. In this study, we aimed to develop and validate a model of oxidative stress injury for predicting BD. Data were collected from 1252 BD and 1359 MDD patients, including 64 MDD patients identified as converting to BD from 2009 through 2018. 30 variables from a randomly-selected subsample of 1827 (70%) patients were used to develop the model, including age, sex, oxidative stress markers (uric acid, bilirubin, albumin, and prealbumin), sex hormones, cytokines, thyroid and liver function, and glycolipid metabolism. Univariate analyses and the Least Absolute Shrinkage and Selection Operator were applied for data dimension reduction and variable selection. Multivariable logistic regression was used to construct a model for predicting bipolar disorder by oxidative stress biomarkers (BIOS) on a nomogram. Internal validation was assessed in the remaining 784 patients (30%), and independent external validation was done with data from 3797 matched patients from five other hospitals in China. 10 predictors, mainly oxidative stress markers, were shown on the nomogram. The BIOS model showed good discrimination in the training sample, with an AUC of 75.1% (95% CI: 72.9%-77.3%), sensitivity of 0.66, and specificity of 0.73. The discrimination was good both in internal validation (AUC 72.1%, 68.6%-75.6%) and external validation (AUC 65.7%, 63.9%-67.5%). In this study, we developed a nomogram centered on oxidative stress injury, which could help in the individualized prediction of BD. For better real-world practice, a set of measurements, especially on oxidative stress markers, should be emphasized using big data in psychiatry.
Biomarkers/metabolism* ; Bipolar Disorder/metabolism* ; Depressive Disorder, Major/diagnosis* ; Early Diagnosis ; Humans ; Oxidative Stress