Spectrum-Resolved Electrochemiluminescence to Multiplex the Immunoassay and DNA Probe Assay

The investigation on electrochemiluminescence (ECL) multiplexing bioassays mainly focuses on simultaneously detecting either proteins or nucleic acids. To overcome the limitation of a short waveband for spectrum-resolved ECL multiplexing bioassays, herein, a highly monochromatic (FWHM <40 nm) and bandgap-engineered ECL luminophore, that is, mercaptopropionic acid-capped and Zn2+-mediated aggregation-induced emission (AIE) assembly of Au nanocrystals (NCs) (Zn2+-AIE-AuNCs), of strong emission and the maximum emission wavelength at 485 nm is developed. The highly monochromatic and bandgap-engineered ECL (485 nm) of Zn2+-AIE-AuNCs can multiplex with the single-waveband and surface-defect-involved ECL (775 nm) of dual-stabilizer-capped CuInS2@ZnS NCs (CIS@ZnS-NCs), enabling a spectrum-resolved ECL multiplexing strategy with different NCs luminophores of a similar particle size as tags. This ECL multiplexing strategy can be utilized to simultaneously detect antigen and DNA probe together without any additional signal amplification procedure and obvious spectroscopic cross-talk, in which the highly monochromatic ECL from Zn2+-AIE-AuNCs is utilized to dynamically determine human carcinoembryonic antigen from 1 pg/mL to 50 ng/mL with a limit of detection (LOD) of 0.3 pg/mL, while the single-waveband ECL from CIS@ZnS-NCs is employed to linearly detect wild-type p53 from 1 pM to 50 nM with a LOD of 0.5 pM. The ECL immunoassay of the proposed strategy is free from the interference of the synchronously conducted DNA probe assay and vice versa, which would open an avenue to couple the immunoassay and DNA probe assay together for clinical colon and breast cancer identification

Cumulative incidence (%) of diabetes among men (A) and women (B) by educational level.

<p>Cumulative incidence (%) of diabetes among men (A) and women (B) by educational level.</p

Association between educational level and incidence of diabetes among men and women at each BMI category.

<p>Model 1: unadjusted. Model 2: adjusted for baseline age, family history of diabetes, marriage status and occupation. Model 3: adjustments in model 2 plus baseline cigarette smoking, alcohol consumption, physical exercise, work strength, dietary intake and salt taste preference. Model 4: adjustments in model 3 plus baseline WC, RHR, BP, TC, TG, UA and FPG. Model 5: adjustments for risk factors in model 4 as time dependent variables.</p

Hazard ratios for incidence of diabetes among men and women.

<p>Model 1: unadjusted. Model 2: adjusted for family history of diabetes, baseline age, marriage status, occupation, cigarette smoking, alcohol consumption, physical exercise, work strength, dietary intake and salt taste preference. Model 3: adjustments in model 2 plus baseline WC, RHR, BP, TC, TG, UA and FPG. Model 4: adjustments for risk factors in model 3 as time dependent variables.</p>*<p>Added BMI category in model 3 when accessing the association of educational level with incidence of diabetes.</p>†<p>Added educational level in model 2 when accessing the association of overweight and obesity with incidence of diabetes.</p

Definition of study participants.

<p>Definition of study participants.</p

Characteristics of the study groups at baseline in 2000, means ± SD, or N (%).

<p>Educational level differences were compared using chi-square test for categorical variables and ANOVA analysis for continuous variables.</p><p>Age, occupation, cigarette smoking, alcohol consumption, physical exercise, BMI, WC, RHR, BP, TC, TG, UA, and FPG were collected annually from 2000 to 2011.</p><p>Family history of diabetes, marriage status, and work strength were collected annually from 2000 to 2003.</p><p>Dietary intake and salt taste preference were collected in 2000 and 2003.</p