OBJECTIVES: The aim of this study is to develop a colorimetric sensor to detect Hg2+ in water sources using HRP inhibitive assay. The system can be incorporated with a mobile app to make it practical for a prompt in-situ analysis.
METHODS: HRP enzyme was pre-incubated with different concentration of Hg2+ at 37°C for 1 hour prior to the addition of chromogen. The mix of PBS buffer, 4-AAP and phenol which act as a chromogen was then added to the HRP enzyme and was incubated for 20 minutes. Alcohol was added to stop the enzymatic reaction, and the change of colour were observed and analyse using UV-Vis spectrophotometer at 520 nm wavelength. The results were then analysed using GraphPad PRISM 4 for a non-linear regression analysis, and using Mathematica (Wolfram) 10.0 software for a hierarchical cluster analysis. The samples from spectroscopy measurement were directly used for dynamic light scattering (DLS) evaluation to evaluate the changes in HRP size due to Hg2+ malfunctionation. Finally, molecular dynamic simulations comparing normal and malfunctioned HRP were carried out to investigate structural changes of the HRP using YASARA software.
RESULTS: Naked eye detection and data from UV-Vis spectroscopy showed good selectivity of Hg2+ over other metal ions as a distinctive color of Hg2+ is observed at 0.5 ppm with the IC50 of 0.290 ppm. The mechanism of Hg2+ inhibition towards HRP was further validated using a dynamic light scattering (DLS) and molecular dynamics (MD) simulation to ensure that there is a conformational change in HRP size due to the presence of Hg2+ ions. The naked eye detection can be quantitatively determined using a smartphone app namely ColorAssist, suggesting that the detection signal does not require expensive instruments to be quantified.
CONCLUSION: A naked-eye colorimetric sensor for mercury ions detection was developed. The colour change due to the presence of Hg2+ can be easily distinguished using an app via a smartphone. Thus, without resorting to any expensive instruments that are mostly laboratory bound, Hg2+ can be easily detected at IC50 value of 0.29 ppm. This is a promising alternative and practical method to detect Hg2+ in the environment.
MATERIALS/METHODS: Multivariable models developed to predict atomised and generalised urinary symptoms, both acute and late, were considered for validation using a dataset representing 754 participants from the TROG 03.04-RADAR trial. Endpoints and features were harmonised to match the predictive models. The overall performance, calibration and discrimination were assessed.
RESULTS: 14 models from four publications were validated. The discrimination of the predictive models in an independent external validation cohort, measured using the area under the receiver operating characteristic (ROC) curve, ranged from 0.473 to 0.695, generally lower than in internal validation. 4 models had ROC >0.6. Shrinkage was required for all predictive models' coefficients ranging from -0.309 (prediction probability was inverse to observed proportion) to 0.823. Predictive models which include baseline symptoms as a feature produced the highest discrimination. Two models produced a predicted probability of 0 and 1 for all patients.
CONCLUSIONS: Predictive models vary in performance and transferability illustrating the need for improvements in model development and reporting. Several models showed reasonable potential but efforts should be increased to improve performance. Baseline symptoms should always be considered as potential features for predictive models.
RESULTS: The calibration curve showed a linear range between 0.01 fM to 0.01 nM with a limit of detection 0.05 fM. The results showed that the optimum concentration for DNA probe was 5 µM. The good performance of the proposed biosensor was achieved through hybridization of DNA probe-modified SPCE with extracted DNA from clinical samples.
CONCLUSIONS: According to the investigated results, this biosensor can be introduced as a proprietary, accurate, sensitive, and rapid diagnostic method of HPV 18 in the polymerase chain reaction (PCR) of real samples.