Lipidomics Provides New Insight into Pathogenesis and Therapeutic Targets of the Ischemia-Reperfusion Injury

Lipids play an essential role in both tissue protection and damage. Tissue ischemia creates anaerobic conditions in which enzyme inactivation occurs, and reperfusion can initiate oxidative stress that leads to harmful changes in membrane lipids, the formation of aldehydes, and chain damage until cell death. The critical event in such a series of harmful events in the cell is the unwanted accumulation of fatty acids that leads to lipotoxicity. Lipid analysis provides additional insight into the pathogenesis of ischemia/reperfusion (I/R) disorders and reveals new targets for drug action. The profile of changes in the composition of fatty acids in the cell, as well as the time course of these changes, indicate both the mechanism of damage and new therapeutic possibilities. A therapeutic approach to reperfusion lipotoxicity involves attenuation of fatty acids overload, i.e., their transport to adipose tissue and/or inhibition of the adverse effects of fatty acids on cell damage and death. The latter option involves using PPAR agonists and drugs that modulate the transport of fatty acids via carnitine into the interior of the mitochondria or the redirection of long-chain fatty acids to peroxisomes

Genetic Algorithm to Evolve Ensembles of Rules for On-Line Scheduling on Single Machine with Variable Capacity

International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC (8th . 2019. Almería, Spain

Selective inhibition of divergent seryl-tRNA synthetases by serine analogues.

Seryl-tRNA synthetases (SerRSs) fall into two distinct evolutionary groups of enzymes, bacterial and methanogenic. These two types of SerRSs display only minimal sequence similarity, primarily within the class II conserved motifs, and possess distinct modes of tRNA(Ser) recognition. In order to determine whether the two types of SerRSs also differ in their recognition of the serine substrate, we compared the sensitivity of the representative methanogenic and bacterial-type SerRSs to serine hydroxamate and two previously unidentified inhibitors, serinamide and serine methyl ester. Our kinetic data showed selective inhibition of the methanogenic SerRS by serinamide, suggesting a lack of mechanistic uniformity in serine recognition between the evolutionarily distinct SerRSs

New links between protein biosynthesis and nonribosomal peptide synthesis

Hybrid glass–carbon 2D braided composites with varying carbon contents are impacted using a gas gun by impactors of masses 12.5 and 44.5 g, at impact energies up to 50 J. The damage area detected by ultrasound C-scan is found to increase roughly linearly with impact energy, and is larger for the lighter impactor at the same impact energy. The area of whitening of the glass tows on the distal side corresponds with the measured C-scan damage area. X-ray imaging shows more intense damage, at the same impact energy, for a higher-mass impactor. Braids with more glass content have a modest increase in density, decrease in modulus, and reduction in the C-scan area and dent depth at the impact site, particularly at the higher impact energies. Impact damage is found to reduce significantly the compressive strength, giving up to a 26% reduction at the maximum impact energ

Transfer RNA-dependent cognate amino acid recognition by an aminoacyl-tRNA synthetase.

An investigation of the role of tRNA in the catalysis of aminoacylation of Escherichia coli glutaminyl-tRNA synthetase (GlnRS) has revealed that the accuracy of specific interactions between GlnRS and tRNAGln determines amino acid affinity. Mutations in GlnRS at D235, which makes contacts with nucleotides in the acceptor stem of tRNAGln, and at R260 in the enzyme's active site were found to be independent during tRNA binding but interactive for aminoacylation. Characterization of mutants of GlnRS at position 235, showed amino acid recognition to be tRNA mediated. Aminoacylation of tRNA(CUA)Tyr [tyrT (UAG)] by GlnRS-D235H resulted in a 4-fold increase in the Km for the Gln, which was reduced to a 2-fold increase when A73 was replaced with G73. These and previous results suggest that specific interactions between GlnRS and tRNAGln ensure the accurate positioning of the 3' terminus. Disruption of these interactions can change the Km for Gln over a 30-fold range, indicating that the accuracy of aminoacylation is regulated by tRNA at the level of both substrate recognition and catalysis. The observed role of RNA as a cofactor in optimizing amino acid activation suggests that the tRNAGln-GlnRS complex may be partly analogous to ribonucleoprotein enzymes where protein-RNA interactions facilitate catalysis

Guided Subtree Selection for Genetic Operators in Genetic Programming for Dynamic Flexible Job Shop Scheduling

© 2020, Springer Nature Switzerland AG. Dynamic flexible job shop scheduling (DFJSS) has been widely studied in both academia and industry. Both machine assignment and operation sequencing decisions need to be made simultaneously as an operation can be processed by a set of machines in DFJSS. Using scheduling heuristics to solve the DFJSS problems becomes an effective way due to its efficiency and simplicity. Genetic programming (GP) has been successfully applied to evolve scheduling heuristics for job shop scheduling automatically. However, the subtrees of the selected parents are randomly chosen in traditional GP for crossover and mutation, which may not be sufficiently effective, especially in a huge search space. This paper proposes new strategies to guide the subtree selection rather than picking them randomly. To be specific, the occurrences of features are used to measure the importance of each subtree of the selected parents. The probability to select a subtree is based on its importance and the type of genetic operators. This paper examines the proposed algorithm on six DFJSS scenarios. The results show that the proposed GP algorithm with the guided subtree selection for crossover can converge faster and achieve significantly better performance than its counterpart in half of the scenarios while no worse in all other scenarios without increasing the computational time

Genetic Programming with Adaptive Search Based on the Frequency of Features for Dynamic Flexible Job Shop Scheduling

© 2020, Springer Nature Switzerland AG. Dynamic flexible job shop scheduling (DFJSS) is a very valuable practical application problem that can be applied in many fields such as cloud computing and manufacturing. In DFJSS, machine assignment and operation sequencing decisions need to be made simultaneously in dynamic environments with unpredicted events such as new job arrivals. Scheduling heuristic is an ideal candidate for solving the DFJSS problem due to its efficiency and simplicity. Genetic programming (GP) has been successfully applied to evolve scheduling heuristics for job shop scheduling automatically. However, GP has a huge search space, and the traditional search algorithms do not utilise effectively the information obtained from the evolutionary process. This paper proposes a new method to make better use of the information during the evolutionary process of GP to further enhance the ability of GP. To be specific, this paper proposes two adaptive search strategies based on the frequency of features in promising individuals to guide GP to evolve effective rules. This paper examines the proposed algorithm on six different DFJSS scenarios. The results show that the proposed GP with adaptive search can converge faster and achieve significantly better performance than the GP without adaptive search in most scenarios while no worse in all other scenarios without increasing the computational cost