Detect Anything With a Personal Glucose Meter

Here’s an extremely innovative idea from Yi Lu and Yu Xiang at the University of Illinois Urbana-Champaign, just published in Nature Chemistry.

Medical demand for home blood glucose monitoring equipment has led to the development of inexpensive, accurate, and widely available electronic instruments that can measure glucose levels in blood. Some modern personal glucose meters, or PGMs, cost as little as $10.

Li and Xiang reasoned that, if they could find a way to chemically couple a compound with glucose, i.e. a reaction that would produce one molecule of glucose for each molecule of the target compound, then a PGM could be used just as well to measure the target compound. Then they went and found a way to do that for, well, just about any compound a person might want to measure.

The process requires some fancy chemistry to raise a DNA fragment that will bind specifically to the target molecule, but once that’s done, the reagent can be produced and sold in bulk inexpensively. You would buy a reagent custom-designed for your analyte of interest, mix it with your sample, add a pinch of sugar (literally), and the sugar would be converted to glucose in direct proportion to the concentration of your target. Then stick a grocery store PGM in the vial and take a reading. [via Science Daily]

5 Responses to Detect Anything With a Personal Glucose Meter

Bryan on July 29th, 2011 at 3:28 pm said:

That would only really be useful for verifying that you mixed everything correctly. You already know how much of the compound in question you wanted to mix with the reagent. This would let you verify that you mixed it properly. The next question is, what good does that do you? You now have a batch of compound mixed with the reagent and sugar at a known concentration. What can you use it for other than re-measuring it? Also, the typical home glucose reader has a 40 mg/dL “Normal Control Solution Range.” For example, when using control solution (basically sugar water with a known amount of sugar in it) the test strips in my current canister are considered good if the meter reading taken from a drop of the control solution is between 107 and 147 mg/dL. That’s a pretty large margin of error. I kinda doubt that’s sufficiently accurate to be useful in any scientific scenario. It’s really only useful for tracking trends over time.

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- anomdebus on July 29th, 2011 at 4:55 pm said:
  
  Current glucose readers are only as accurate as they need to be. If there is a separate market for greater accuracy, then the technology will be developed. As a side benefit diabetics will end up with more reliable meters.
  I see this as being much more useful for field measurements. (ie: water quality, inebriation detection and quality control.)
  
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- Sean Michael Ragan on August 2nd, 2011 at 3:11 am said:
  
  Why would you “already know how much of the compound in question you wanted to mix with the reagent?”
  
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- Sean Michael Ragan on August 2nd, 2011 at 3:11 am said:
  
  Why would you “already know how much of the compound in question you wanted to mix with the reagent?”
  
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Bryan on July 29th, 2011 at 3:28 pm said:

That would only really be useful for verifying that you mixed everything correctly. You already know how much of the compound in question you wanted to mix with the reagent. This would let you verify that you mixed it properly. The next question is, what good does that do you? You now have a batch of compound mixed with the reagent and sugar at a known concentration. What can you use it for other than re-measuring it? Also, the typical home glucose reader has a 40 mg/dL “Normal Control Solution Range.” For example, when using control solution (basically sugar water with a known amount of sugar in it) the test strips in my current canister are considered good if the meter reading taken from a drop of the control solution is between 107 and 147 mg/dL. That’s a pretty large margin of error. I kinda doubt that’s sufficiently accurate to be useful in any scientific scenario. It’s really only useful for tracking trends over time.

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