Micro Imaging Technology, Inc. announced today the volume availability in early 2012 of the MIT 1000A. The System, manufactured exclusively for MIT by Hawthorne, CA-based OSI Optoelectronics, Inc., is a stand-alone optically-based microbial identification system that uses proven principles of physics in conjunction with proprietary PC-based software and is totally USB compliant. The thoroughly green system can currently identify over twenty different species of bacteria without the use of chemicals, reagents, dyes or DNA processing. The only additive is clean water and a sample of the unknown bacteria. In addition to bacteria other microbes can be easily added to the System's identifying capabilities, including; protozoa, fungi, yeast and mold. The MIT 1000A can complete an identifying test in less than five (5) minutes and with a material cost of pennies -- adding further credence to MIT's claims of being able to annually save thousands of lives and tens of millions of dollars in health care costs.
As further explained by MIT's Chief Scientist, David Haavig, PhD, "The MIT 1000A is a natural evolution from our earlier MIT 1000 System, without changing the basic science -- but with specific added capabilities. The USB connectivity enables the instrument to attach directly to the user's PC and allows the software operating system and microbial identifiers to be provided separately by MIT."
As previously mentioned, over ninety percent of all infectious food contaminations are caused by E.coli, Salmonella or Listeria - which annually causes hundreds of deaths and thousands of hospitalizations. Also the recall of millions of pounds of processed meats, dairy, fish and poultry products and numerous crops of lettuce, spinach, peppers, peanuts, melons and tomatoes.
The Company's objective is the continual expansion of MIT's proprietary Microbe Library -- the repository of the identifiers for bacteria and other microbes. The process for entering a microbe identifier is to evaluate the specie in MIT's Laboratory with hundreds of thousands of measurements and statistically prove the uniqueness of the identifier. That identifier is then compared with other datum and then added to the Microbe Library.