Nitrite augments tolerance to ischemia/reperfusion injury via the modulation of mitochondrial electron transfer

Nitrite (NO2−) is an intrinsic signaling molecule that is reduced to NO during ischemia and limits apoptosis and cytotoxicity at reperfusion in the mammalian heart, liver, and brain. Although the mechanism of nitrite-mediated cytoprotection is unknown, NO is a mediator of the ischemic preconditioning cell-survival program. Analogous to the temporally distinct acute and delayed ischemic preconditioning cytoprotective phenotypes, we report that both acute and delayed (24 h before ischemia) exposure to physiological concentrations of nitrite, given both systemically or orally, potently limits cardiac and hepatic reperfusion injury. This cytoprotection is associated with increases in mitochondrial oxidative phosphorylation. Remarkably, isolated mitochondria subjected to 30 min of anoxia followed by reoxygenation were directly protected by nitrite administered both in vitro during anoxia or in vivo 24 h before mitochondrial isolation. Mechanistically, nitrite dose-dependently modifies and inhibits complex I by posttranslational S-nitrosation; this dampens electron transfer and effectively reduces reperfusion reactive oxygen species generation and ameliorates oxidative inactivation of complexes II–IV and aconitase, thus preventing mitochondrial permeability transition pore opening and cytochrome c release. These data suggest that nitrite dynamically modulates mitochondrial resilience to reperfusion injury and may represent an effector of the cell-survival program of ischemic preconditioning and the Mediterranean diet

An Efficient and Improved Coronavirus Herd Immunity Algorithm Using Knowledge-Driven Variable Neighborhood Search for Flexible Job-Shop Scheduling Problems

By addressing the flexible job shop scheduling problem (FJSP), this paper proposes a new type of algorithm for the FJSP. We named it the hybrid coronavirus population immunity optimization algorithm. Based on the characteristics of the problem, firstly, this paper redefined the discretized two-stage individual encoding and decoding scheme. Secondly, in order to realize the multi-scale search of the solution space, a multi-population update mechanism is designed, and a collaborative learning method is proposed to ensure the diversity of the population. Then, an adaptive mutation operation is introduced to enrich the diversity of the population, relying on the adaptive adjustment of the mutation operator to balance global search and local search capabilities. In order to realize a directional and efficient neighborhood search, this algorithm proposed a knowledge-driven variable neighborhood search strategy. Finally, the algorithm’s performance comparison experiment is carried out. The minimum makespans on the MK06 medium-scale case and MK10 large-scale case are 58 and 201, respectively. The experimental results verify the effectiveness of the hybrid algorithm

The Adaptive Optimal Output Feedback Tracking Control of Unknown Discrete-Time Linear Systems Using a Multistep Q-Learning Approach

This paper investigates the output feedback (OPFB) tracking control problem for discrete-time linear (DTL) systems with unknown dynamics. To solve this problem, we use an augmented system approach, which first transforms the tracking control problem into a regulation problem with a discounted performance function. The solution to this problem is derived using a Bellman equation, based on the Q-function. In order to overcome the challenges of unmeasurable system state variables, we employ a multistep Q-learning algorithm that surpasses the advantages of the policy iteration (PI) and value iteration (VI) techniques and state reconstruction methods for output feedback control. As such, the requirement for an initial stabilizing control policy for the PI method is removed and the convergence speed of the learning algorithm is improved. Finally, we demonstrate the effectiveness of the proposed scheme using a simulation example

Mutational Analysis To Define an Activating Region on the Redox-Sensitive Transcriptional Regulator OxyR

The OxyR transcription factor is a key regulator of the Escherichia coli response to oxidative stress. Previous studies showed that OxyR binding to a target promoter enhances RNA polymerase binding and vice versa, suggesting a direct interaction between OxyR and RNA polymerase. To identify the region of OxyR that might contact RNA polymerase, we carried out alanine scanning and random mutagenesis of oxyR. The combination of these approaches led to the identification of several mutants defective in the activation of an OxyR target gene. A subset of the mutations map to the DNA-binding domain, other mutations appear to affect dimerization of the regulatory domain, while another group is suggested to affect disulfide bond formation. The two mutations, D142A and R273H, giving the most dramatic phenotype are located in a patch on the surface of the oxidized OxyR protein and possibly define an activating region on OxyR

Measurement of nitric oxide levels in the red cell: validation of tri-iodide-based chemiluminescence with acid-sulfanilamide pretreatment

The tri-iodide-based chemiluminescence assay is the most widely used methodology for the detection of S-nitrosothiols (RSNOs) in biological samples. Because of the low RSNO levels detected in a number of biological compartments using this assay, criticism has been raised that this method underestimates the true values in biological samples. This claim is based on the beliefs that (i) acidified sulfanilamide pretreatment, required to remove nitrite, leads to RSNO degradation and (ii) that there is auto-capture of released NO by heme in the reaction vessel. Because our laboratories have used this assay extensively without ever encountering evidence that corroborated these claims, we sought to experimentally address these issues using several independent techniques. We find that RSNOs of glutathione, cysteine, albumin, and hemoglobin are stable in acidified sulfanilamide as determined by the tri-iodide method, copper/cysteine assay, Griess-Saville assay and spectrophotometric analysis. Quantitatively there was no difference in S-nitroso-hemoglobin (SNOHb) or S-nitroso-albumin (SNOAlb) using the tri-iodide method and a recently described modified assay using a ferricyanide-enhanced reaction mix at biologically relevant NO:heme ratios. Levels of SNOHb detected in human blood ranged from 20-100 nM with no arterial-venous gradient. We further find that 90% of the total NO-related signal in blood is caused by erythrocytic nitrite, which may partly be bound to hemoglobin. We conclude that all claims made thus far that the tri-iodide assay underestimates RSNO levels are unsubstantiated and that this assay remains the "gold standard" for sensitive and specific measurement of RSNOs in biological matrices

Characterization of Microbial Communities in a Dairy Farm Matrix in Ningxia, China, by 16S rDNA Analysis

A large amount of dairy manure is produced annually in the Ningxia Hui Autonomous Region of China due to the increase in food-producing animal agriculture in this region. The presence of bovine-originated zoonotic, especially human, pathogenic bacteria in untreated manure poses a significant threat to the environment and to public health. However, little is known about the composition, diversity, and abundance of bacterial communities in untreated dairy manure in the Ningxia region. In this study, the microbial community structure of the dairy farm matrix was characterized through 16S rDNA sequencing. The impact of manure treatment methods on bacterial communities was also analyzed. The results showed that the microbial community in dairy manure contained both beneficial bacteria and pathogens, with Firmicutes, Bacteroidetes, Proteobacteria, Spirochaetes, and Actinobacteria as dominant phyla. The results also showed the diversity and variety of abundance of zoonotic pathogens among different matrices. The number of pathogens was found to increase significantly in the accumulated but untreated manure, which appeared to be the main matrix of dairy farms that accumulated pathogens including zoonotic pathogens. Findings from this study suggested that farm management, particularly proper treatment of manure, is essential to achieve a shift in the bacterial community composition and a reduction in the environmental load of pathogens including zoonotic pathogens