Human chorionic gonadotropin (hCG), a glycoprotein hormone secreted from the placenta, is a key molecule that indicates pregnancy. Here, we have designed a cost-effective, label-free, in situ point-of-care (POC) immunosensor to estimate hCG using a cuneated 25 nm polysilicon nanogap electrode. A tiny chip with the dimensions of 20.5 × 12.5 mm was fabricated using conventional lithography and size expansion techniques. Furthermore, the sensing surface was functionalized by (3-aminopropyl)triethoxysilane and quantitatively measured the variations in hCG levels from clinically obtained human urine samples. The dielectric properties of the present sensor are shown with a capacitance above 40 nF for samples from pregnant women; it was lower with samples from non-pregnant women. Furthermore, it has been proven that our sensor has a wide linear range of detection, as a sensitivity of 835.88 μA mIU(-1) ml(-2) cm(-2) was attained, and the detection limit was 0.28 mIU/ml (27.78 pg/ml). The dissociation constant Kd of the specific antigen binding to the anti-hCG was calculated as 2.23 ± 0.66 mIU, and the maximum number of binding sites per antigen was Bmax = 22.54 ± 1.46 mIU. The sensing system shown here, with a narrow nanogap, is suitable for high-throughput POC diagnosis, and a single injection can obtain triplicate data or parallel analyses of different targets.
Most studies of metals exposure focus on the heavy metals. There are many other metals (the transition, alkali and alkaline earth metals in particular) in common use in electronics, defense industries, emitted via combustion and which are naturally present in the environment, that have received limited attention in terms of human exposure. We analysed samples of whole blood (172), urine (173) and drinking water (172) for antimony, beryllium, bismuth, cesium, gallium, rubidium, silver, strontium, thallium, thorium and vanadium using ICPMS. In general most metals concentrations were low and below the analytical limit of detection with some high concentrations observed. Few factors examined in regression models were shown to influence biological metals concentrations and explained little of the variation. Further study is required to establish the source of metals exposures at the high end of the ranges of concentrations measured and the potential for any adverse health impacts in children.