Objective:To analyze the correlation between simple thyroid nodule and blood lipid and glucose metabolism and iodine nutrition level.Methods:A cross-sectional study was conducted by collecting data of the population undergoing epidemiological investigation in Jinshan District, Shanghai from July to December 2015, to calculate the prevalence of thyroid nodules and analyze relevant functional indicators.Results:Simple thyroid nodules were detected in 603 subjects, with a prevalence of 22.6% (603/2 669). There were 358 female patients with simple thyroid nodules, with a prevalence rate of 26.9%, and 245 male patients with simple thyroid nodules, with a prevalence rate of 18.3%. The prevalence of simple thyroid nodule in female was higher than that in male, and the difference was statistically significant (χ 2=27.686, P<0.001). In addition, the prevalence of simple thyroid nodules increased with age (13.1% (92/704) and 20.2% (104/514) and 25.1% (145/578) and 24.4% (107/439) and 36.3% (98/270) and 34.8% (57/164), χ 2=83.872,P<0.001). In the ≤30 years group (8.0% (30/704) vs. 18.8% (62/331), χ 2=35.716, P<0.001), >30 to ≤40 years old group (14.1% (37/263) vs. 26.7% (67/251), χ 2=12.683, P<0.001), >60 to ≤70 years old group (26.2% (33/126) vs. 45.1% (65/144), χ 2=10.435, P<0.001), and the 70-year-old group (24.4% (21/86) vs. 46.2% (36/78), χ 2=8.521, P<0.001). The prevalence of simple thyroid nodules in males was lower than that in females. In the simple positive thyroid nodule group, Fasting blood glucose (5.12 (4.80, 5.69) and 5.02 (4.72, 5.48)), total cholesterol (1.24 (0.85, 1.86) and 1.13 (0.77, 1.76)), triglyceride (4.77 (4.09, 5.48) and 4.49 (3.92, 5.16)), low density lipoprotein((2.79 (2.26, 3.36) and 2.63 (2.19, 3.16)), and high density lipoprotein cholesterol (1.41 (1.18, 1.66) and 1.35 (1.13, 1.61)) were higher than those in the negative group ( U values were 554 818, 578 468, 535 622, 556 067 and 567 960, respectively, all P<0.01). The BMI index grade distribution of thyroid nodule positive group was higher than that of negative group, and the difference was statistically significant (3.7% (77/2 066), 50.1% (1 034/2 066), 32.4% (669/2 066), 13.8% (286/2 066), 3.2% (19/603), 43.6% (263/603), 38.1% (230/603), 15.1% (91/603), χ2=9.5201, P=0.023). The prevalence of simple thyroid nodules was significantly lower in the iodized salt group than in the non-iodized salt group (20.7% (436/2 102) vs. 29.5% (167/567), χ 2=19.376, P<0.001). The urinary iodine level in the positive thyroid nodule group was significantly lower than that in the negative group (148.4(100.2, 213.7) vs. 169.5(115.4, 241.75), U=545 129.5, P<0.001). After Logistic regression screening, age ( OR=1.57, 95% CI: 1.292-1.908, P<0.001), gender ( OR=1.278, 95% CI: 1.193-1.368, P<0.001), BMI grade ( OR=1.166, 95% CI: 1.022-1.330, P=0.022), total cholesterol ( OR=1.105, 95% CI: 1.005-1.214, P=0.040), iodized salt ( OR=0.689, 95% CI: 0.556-0.854, P=0.001) were independent influencing factors of thyroid nodule. Conclusion:The prevalence of simple thyroid nodules in Shanghai is relatively low. Age, sex, BMI level, total cholesterol and iodized salt are independent factors causing thyroid nodules. In addition, blood glucose level may also be related to the prevalence of thyroid nodules.

Objective Metabolomics was used to analyze the changes of metabolites in the plasma of Fenpropathrin-contaminated rats to find potential biomarkers for forensic identification of Fenpropathrin poisoning.Methods SD rats in the two experimental groups were given 20.5 mg/kg and 41 mg/kg doses of fenpropathrin respectively by gavage.The rats in the control group were given equivalent volume of normal saline.The angular vein blood of rats was collected 24 hours after gavage,and endogenous small molecule metabolites in plasma were investigated by ultra-performance liquid chromatography-time-of-flight mass spectrometry(UPLC-TOF-MS).The data was processed by SIMCA14.1.The differential metabolites in plasma of fenpropathrin-infected rats were screened out according to the Variable Importance in Projection(VIP)and p<0.05 in the OPLS-DA model.Finally,the pathways were analyzed.Results There were significant differences in plasma metabolite levels between the control group and the experimental group,and 17 biomarkers were selected to identify whether the rats had received fenpropathrin,which mainly affected purine metabolism,Alanine,aspartate and glutamate metabolism,arginine biosynthesis,biosynthesis of unsaturated fatty acids and pyrimidine metabolism.Conclusion Fenpropathrin can change the composition of metabolites in rats,and the differential markers screened can provide supportive forensic evidence for cases related to deltamethrin poisoning.