Fatty acid amides are a diverse family of underappreciated, biologically occurring lipids. Herein, the methods for the chemical synthesis and subsequent characterization of specific members of the fatty acid amide family are described. The synthetically prepared fatty acid amides and those obtained commercially are used as standards for the characterization and quantification of the fatty acid amides produced by biological systems, a fatty acid amidome. The fatty acid amidomes from mouse N18TG2 cells, sheep choroid plexus cells, Drosophila melanogaster, Bombyx mori, Apis mellifera, and Tribolium castaneum are presented.

The fatty acid amides are a family of lipids composed of two chemical moieties, a fatty acid and a biogenic amine linked together in an amide bond. This lipid family is structurally related to the endocannabinoid anandamide (N-arachidonoylethanolamine) and, thus, is frequently referred to as a family of endocannabinoid-related lipids. The fatty acid amide family is divided into different classes based on the conjugate amine; anandamide being a member of the N-acylethanolamine class (NAE). Another class within the fatty acid amide family is the N-acyl amino acids (NA-AAs). The focus of this review is a sub-class of the NA-AAs, the N-acyl aromatic amino acids (NA-ArAAs). The NA-ArAAs are not broadly recognized, even by those interested in the endocannabinoids and endocannabinoid-related lipids. Herein, the NA-ArAAs that have been identified from a biological source will be highlighted and pathways for their biosynthesis, degradation, enzymatic modification, and transport will be presented. Also, information about the cellular functions of the NA-ArAAs will be placed in context with the data regarding the identification and metabolism of these N-acylated amino acids. A review of the current state-of-knowledge about the NA-ArAAs is to stimulate future research about this underappreciated sub-class of the fatty acid amide family.

Matrix-Assisted Laser Desorption/Ionization Mass Spectrometric Imaging (MALDI-MSI) has developed as a useful tool in generating comprehensive metabolite profiles along with spatial information in model organisms. The ability of MALDI-MSI to generate in situ profiles in whole organisms or specific tissue sections serves as an efficient alternative to solvent extraction protocols, especially for the identification of biomolecules that are unstable under extraction conditions. Herein, we have utilized MALDI-MSI to spatially profile various classes of lipids in two model organisms, Drosophila melanogaster (fruit fly), and Tribolium castaneum (red flour beetle). Five different classes of phospholipids were imaged in positive ionization mode in both insect species. Confirmation of the m/z assignment for selected lipids was performed using on-tissue MS/MS fragmentation.

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Abstract. Digital Elevation Models are one of the important datasets of any Geographic Information System (GIS) and so are the parameters derived from them. One such parameter is slope, whose accuracy can have a significant effect on many engineering and construction works. This paper addresses the eight-slope calculation methods that are currently available to calculate slope value from a DEM and compares how these methods works on different slope range and values. These methods were applied to calculate slope from DEM of 30 m. To determine the method that calculates the most accurate slope value for a particular slope range by comparing them with actual slope value is the main objective of this paper. The methods 2FD, 3FD, 3FDWRD, Average Neighborhood, Constrained Quadratic Surface and FFD has given similar results across all slope range while the algorithms that appears to yield the most varying results are Maximum Max and Simple D. In addition, it is observed that the choice of algorithms is more important when grade slope is less than 10 percent. However, for terrains with above 10 percent slope, the choice of algorithms seems less important with only a difference of approximately 0.5 gradient.