Enhanced Lipidome Coverage in Shotgun Analyses by using Gas-Phase Fractionation

A high resolving power shotgun lipidomics strategy using gas-phase fractionation and data-dependent acquisition (DDA) was applied toward comprehensive characterization of lipids in a hen ovarian tissue in an untargeted fashion. Using this approach, a total of 822 unique lipids across a diverse range of lipid categories and classes were identified based on their MS/MS fragmentation patterns. Classes of glycerophospholipids and glycerolipids, such as glycerophosphocholines (PC), glycerophosphoethanolamines (PE), and triglycerides (TG), are often the most abundant peaks observed in shotgun lipidomics analyses. These ions suppress the signal from low abundance ions and hinder the chances of characterizing low abundant lipids when DDA is used. These issues were circumvented by utilizing gas-phase fractionation, where DDA was performed on narrow m/z ranges instead of a broad m/z range. Employing gas-phase fractionation resulted in an increase in sensitivity by more than an order of magnitude in both positive- and negative-ion modes. Furthermore, the enhanced sensitivity increased the number of lipids identified by a factor of ≈4, and facilitated identification of low abundant lipids from classes such as cardiolipins that are often difficult to observe in untargeted shotgun analyses and require sample-specific preparation steps prior to analysis. This method serves as a resource for comprehensive profiling of lipids from many different categories and classes in an untargeted manner, as well as for targeted and quantitative analyses of individual lipids. Furthermore, this comprehensive analysis of the lipidome can serve as a species- and tissue-specific database for confident identification of other MS-based datasets, such as mass spectrometry imaging.

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A robust model for a leader–follower competitive facility location problem in a discrete space

This paper aims at determining the optimal locations for the leader’s new facilities under the condition that the number of the follower’s new facilities is unknown for the leader. The leader and the follower have some facilities in advance. The first competitor, the leader, opens p new facilities in order to increase her own market share. On the other hand, she knows that her competitor, the follower, will react to her action and locate his new facilities as well. The number of the follower’s new facilities is unknown for the leader but it is assumed that the leader knows the probability of opening different numbers of the follower’s new facilities. The leader aims at maximizing her own market share after the follower’s new facilities entry. The follower’s objective is also to maximize his own market share. Since the number of the follower’s new facilities is unknown for leader, “Robust Optimization” is used for maximizing the leader’s market share and making the obtained results “robust” in various scenarios in terms of different numbers of the follower’s new facilities. The optimal locations for new facilities of both the leader and the follower are chosen among pre-determined potential locations. It is assumed that the demand is inelastic. The customers probabilistically meet their demands from all different facilities and the demand level which is met by each facility is computed by Huff rule. The computational experiments have been applied to evaluate the efficiency of the proposed model.     

Synthesis of 4′-[3-methyl-5-thioxo-1H-1,2,4-triazol-4(5H)-yl]-2′,5′-diphenyl-2′,4′-dihydro spiro[indolin-3,3′[1,2,4]triazol]-2-one derivatives

In this paper 1,3-dipolar cycloaddition reaction has been studied. An efficient synthesis of 4′-[3-methyl-5-thioxo-1H-1,2,4-triazol-4(5H)-yl]-2′,5′-diphenyl-2′,4′-dihydro spiro(indolin-3,3′[1,2,4]triazol)-2-one derivatives using triethylamine in MeCN at room temperature is reported. The structures of the obtained compounds were confirmed by means of elemental analysis, MS and spectral (IR, ¹H, and ¹³C NMR) methods.     

Stability and Rheological Properties of Model Low-Fat Salad Dressing Stabilized by Salep

A model low-fat salad dressing including salep as thickening agent was prepared. In order to obtain an stable salad dressing, different variables each one at three levels like salep content (0.5, 2.0, and 3.5% w/w), oil volume fraction (7.50, 16.25, and 25.00% w/w), pH (3, 5, and 7), salt concentration (0.3, 0.9, and 1.5% w/w), and egg yolk content (2, 4, and 6% w/w) were chosen and their effect on the creaming index of salad dressing was studied. It was observed that samples with highest salep content at pH 3 were the most stable during storage time (15 days). The microstructure of some samples was considered. Rheological measurements were performed for stable samples. Oil fraction and salt content increased zero shear viscosity and G′ modulus of samples.