Visualizing and Calculating Tip-Substrate Distance in Nanoscale Scanning Electrochemical Microscopy Using 3-Dimensional Super-Resolution Optical Imaging.

We report a strategy for the optical determination of tip-substrate distance in nanoscale scanning electrochemical microscopy (SECM) using three-dimensional super-resolution fluorescence imaging. A phase mask is placed in the emission path of our dual SECM/optical microscope, generating a double helix point spread function at the image plane, which allows us to measure the height of emitting objects relative to the focus of the microscope. By exciting both a fluorogenic reaction at the nanoscale electrode tip as well as fluorescent nanoparticles at the substrate, we are able to calculate the tip-substrate distance as the tip approaches the surface with precision better than 25 nm. Attachment of a fluorescent particle to the insulating sheath of the SECM tip extends this technique to nonfluorogenic electrochemical reactions. Correlated electrochemical and optical determination of tip-substrate distance yielded excellent agreement between the two techniques. Not only does super-resolution imaging offer a secondary feedback mechanism for measuring the tip-sample gap during SECM experiments, it also enables facile tip alignment and a strategy for accounting for electrode tilt relative to the substrate.

Clinical chemistry measurements with commercially available test slides on a smartphone platform: Colorimetric determination of glucose and urea.

BACKGKROUND: Rapidly increasing healthcare costs in economically advantaged countries are currently unsustainable, while in many developing nations, even 50-year-old technologies are too expensive to implement. New and unconventional technologies are being explored as solutions to this problem. In this study, we examined the use of a smartphone as the detection platform for 2 well-developed, relatively inexpensive, commercially available clinical chemistry assays as a model for rapid and inexpensive clinical diagnostic testing. METHODS: An Apple iPhone 4 camera phone equipped with a color analysis application (ColorAssist) was combined with Vitros® glucose and urea colorimetric assays. Color images of assay slides at various concentrations of glucose or urea were collected with the iPhone 4 and quantitated in three different spectral ranges (red/green/blue or RGB) using the ColorAssist app. When the diffuse reflectance data was converted into absorbance, it was possible to quantitate glucose or blood urea nitrogen (BUN) over their clinically important concentration ranges (30-515mg/dl for glucose or 2-190mg/dl for BUN), with good linearity (R(2)=0.9994 or 0.9996, respectively [n=5]). RESULTS: Data collected using the iPhone 4 and canine serum samples were in agreement with results from the instrumental "gold standard" (Beckman Coulter AU480 Chemistry System) (R(2)=0.9966 and slope=1.0001 for glucose; R(2)=0.9958 and slope=0.9454 for BUN). Glucose determinations of serum samples made using this smartphone method were as accurate as or more accurate than a commercial colorimetric dry slide analyzer (Heska® Element DC Chemistry Analyzer, Loveland, CO) and 2 glucometers: ReliOn® Ultima (Abbott Diabetes Care Inc) and Presto® (AgaMatrix Inc.H). BUN determinations made using the smartphone approach were comparable in accuracy to the Heska instrument. CONCLUSION: This demonstration shows that smartphones have the potential to be used as simple, effective colorimetric detectors for quantitative diagnostic tests, and may be applicable for both point-of-care applications in the developed world and field deployment in developing nations.