Programmable Entropy-Driven Circuit-Cascaded Self-Feedback DNAzyme Network for Ultra-Sensitive Fluorescence and Photoelectrochemical Dual-Mode Biosensing.

Inspired by natural DNA networks, programmable artificial DNA networks have become an attractive tool for developing high-performance biosensors. However, there is still a lot of room for expansion in terms of sensitivity, atom economy, and result self-validation for current microRNA sensors. In this protocol, miRNA-122 as a target model, an ultrasensitive fluorescence (FL) and photoelectrochemical (PEC) dual-mode biosensing platform is developed using a programmable entropy-driven circuit (EDC) cascaded self-feedback DNAzyme network. The well-designed EDC realizes full utilization of the DNA strands and improves the atomic economy of the signal amplification system. The unique and rational design of the double-CdSe quantum-dot-released EDC substrate and the cascaded self-feedback DNAzyme amplification network significantly avoids high background signals and enhances sensitivity and specificity. Also, the enzyme-free, programmable EDC cascaded DNAzyme network effectively avoids the risk of signal leakage and enhances the accuracy of the sensor. Moreover, the introduction of superparamagnetic Fe3O4@SiO2-cDNA accelerates the rapid extraction of E2-CdSe QDs and E3-CdSe QDs, which greatly improves the timeliness of sensor signal reading. In addition to the strengths of linear range (6 orders of magnitude) and stability, the biosensor design with dual signal reading makes the test results self-confirming.

[Risk factors for hyperuricemia in active and retired employees underwent physical examination].

OBJECTIVE: To observe serum uric acid (UA) level distribution and explore risk factors of hyperuricemia (HUA) in a large cohort of active and retired employees underwent physical examination. METHODS: Physical examination was arranged for 21 700 active and retired employees from May 2010 to September 2011, 16 416 employees were examined and complete examination data were obtained in 14 044 subjects. The distribution characteristics of UA level and correlations of UA level and HUA prevalence rate with gender, age, body mass index (BMI), systolic pressure (SBP), diastolic pressure (DBP), fasting blood-glucose (FPG), serum total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) were analyzed. RESULTS: HUA prevalence rate was 11.2% in this cohort, which was significantly higher in males (15.8%) than in females (4.1%, P < 0.05). The UA level and the HUA prevalence rate presented a "J" curve relationship with aging and positively correlated with BMI, SBP, DBP, TG, LDL-C, TC and FPG while negatively correlated with HDL-C. Multiple linear regression analysis showed that SBP, BMI, FPG, TG, and LDL-C were independent risk factors while HDL-C and female gender were the protective factors of HUA(all P < 0.01). Aging and high DBP were independent risk factors of HUA for females (all P < 0.05) and LDL-C was risk factor of HUA for males (P < 0.05). CONCLUSIONS: Serum UA level presents a "J" wave relationship with aging. The risk factors of HUA are increased SBP, BMI, FPG, TG, LDL-C while the protective factors of HUA are female gender and high HDL-C.