PubMed · 4779902
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L L Alber, M W Overton, D E Smith. 1973. Minicomputer-automatic analysis system for pharmaceuticals.. https://pubmed.ncbi.nlm.nih.gov/4779902/
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Protein identification through peptide mass mapping by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has become a standard technique, used in many laboratories around the world. The traditional methodology often includes long incubations (6-24 h) and extensive manual steps. In an effort to address this, an integrated microanalytical platform has been developed for automated identification of proteins. The silicon micromachined analytical tools, i.e., the microchip immobilized enzyme reactor (mu-chip IMER), the piezoelectric microdispenser, and the high-density nanovial target plates, are the cornerstones in the system. The mu-chip IMER provides on-line enzymatic digestion of protein samples (1 microL) within 1-3 min, and the microdispenser enables subsequent on-line picoliter sample preparation in a high-density format. Interfaced to automated MALDI-TOF MS, these tools compose a highly efficient platform that can analyze 100 protein samples in 3.5 h. Kinetic studies on the microreactors are reported as well as the operation of this microanalytical platform for protein identification, wherein lysozyme, myoglobin, ribonuclease A, and cytochrome c have been identified with a high sequence coverage (50-100%).
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A viable approach for the determination of sources of essential oils based on automatic injection solid-phase microextraction-chiral-gas chromatography-mass selective detection is demonstrated. With no sample preparation, it is shown that the source of essential oils such as peppermint, spearmint, and rosemary can be easily distinguished. Short fiber exposure times of approximately 6 s to the headspace above submicroliter quantities of the selected oils are all that is required to obtain both the required sensitivity and resolution to afford analyses with excellent reproducibilities (relative standard deviation values consistently less than 5.0%).