Quantification of rat brain neurotransmitters and metabolites using liquid chromatography/electrospray tandem mass spectrometry and comparison with liquid chromatography/electrochemical detection

Analytical methodology based on solid-phase extraction, polar reversed-phase liquid chromatography, and electrospray tandem mass spectrometry (LC/MS/MS) with isotope dilution was developed and validated for quantifying the neurotransmitters, dopamine and serotonin, and their major metabolites in brain tissue. Limits of detection (0.1-20 pg/mg tissue) were sufficient for analysis of multiple neurotransmitters in rat brain regions, including parietal cortex, hypothalamus, pituitary, substantia nigra, and striatum. Method performance was compared with contemporaneous measurements using a well-established procedure based on ion-pairing reversed-phase liquid chromatography and amperometric detection. The principal advantages of the LC/MS/MS method include a more robust sample purification procedure, an optimized chromatographic separation, and the qualitative and quantitative assurance that comes from coeluting isotopically labeled internal standards; however, sensitivity did not consistently improve upon that provided by amperometric detection. This methodology may be particularly useful for applications in which simultaneous determinations are required for drugs and their affected neurotransmitters in specific brain regions.     

Electron transfer-induced fragmentation of thymine and uracil in atom-molecule collisions

Ion-pair formation has been studied in hyperthermal (30-100 eV) neutral potassium collisions with gas phase thymine (C(5)H(6)N(2)O(2)) and uracil (C(4)H(4)N(2)O(2)). Negative ions formed by electron transfer from the alkali atom to the target molecule were analysed by time-of-flight (TOF) mass spectrometry. The most abundant product anions are assigned to CNO(-) and (U-H)(-)/(T-H)(-) and the associated electron transfer mechanisms are discussed. Special emphasis is given to the enhancement of ring breaking pathways in the present experiments, notably CNO(-) formation, compared with free electron attachment measurements.     

Distinguishing phosphorylation and sulfation in carbohydrates and glycoproteins using ion-pairing and mass spectrometry

Phosphorylation and sulfation are important modifications affecting the biological properties of carbohydrates, proteins, and glycoproteins. Identification of these two functional groups facilitates the understanding of the structure/function relationship in various species. Mass spectrometry is one of the methods used to detect the presence of these two modifications in complex biological mixtures. However, phosphorylated and sulfated structures are isobaric; thus, differentiation between them in routinely used mass spectrometers is problematic. Herein, we demonstrate that these two groups can be discriminated by using ion-pairing in conjunction with MS/MS experiments. The characteristic product ions are used to successfully identify the phosphorylation and sulfation present in mono-, disaccharides, and the highly sulfated glycoprotein, ovine luteinizing hormone. This method is a robust approach to differentiate the two isobaric functional groups.     

Closing the gap in the purely elliptic generalized Davey–Stewartson system

In this note we improve the results presented previously on global existence and global nonexistence for the solutions of the purely elliptic generalized Davey–Stewartson system. These results left a gap in the parameter range where neither a global existence result nor a global nonexistence result could be established. Here we are able to show that when the coupling parameter is negative there is no gap. Moreover, in the case where the coupling parameter is positive we reduce the size of the gap.     

Bayesian decoding of neural spike trains

Perception, memory, learning, and decision making are processes carried out in the brain. The performance of such intelligent tasks is made possible by the communication of neurons through sequences of voltage pulses called spike trains. It is of great interest to have methods of extracting information from spike trains in order to learn about their relationship to behavior. In this article, we review a Bayesian approach to this problem based on state-space representations of point processes. We discuss some of the theory and we describe the way these methods are used in decoding motor cortical activity, in which the hand motion is reconstructed from neural spike trains.