Neonatal hypoxic ischemic encephalopathy (HIE) is a devastating disease that primarily causes neuronal and white matter injury and is among the leading cause of death among infants. Currently there are no well-established treatments; thus, it is important to understand the pathophysiology of the disease and elucidate complications that are creating a gap between basic science and clinical translation. In the development of neuroprotective strategies and translation of experimental results in HIE, there are many limitations and challenges to master based on an appropriate study design, drug delivery properties, dosage, and use in neonates. We will identify understudied targets after HIE, as well as neuroprotective molecules that bring hope to future treatments such as melatonin, topiramate, xenon, interferon-beta, stem cell transplantation. This review will also discuss some of the most recent trials being conducted in the clinical setting and evaluate what directions are needed in the future.

The results demonstrate that hypoxia induces epigenetic repression of the PKCε gene through a NADPH oxidase-independent ROS-mediated pathway in the foetal heart, leading to heightened heart vulnerability to ischaemic injury in offspring.

Neurological diseases, which consist of acute injuries and chronic neurodegeneration, are the leading causes of human death and disability. However, the pathophysiology of these diseases have not been fully elucidated, and effective treatments are still lacking. Astaxanthin, a member of the xanthophyll group, is a red-orange carotenoid with unique cell membrane actions and diverse biological activities. More importantly, there is evidence demonstrating that astaxanthin confers neuroprotective effects in experimental models of acute injuries, chronic neurodegenerative disorders, and neurological diseases. The beneficial effects of astaxanthin are linked to its oxidative, anti-inflammatory, and anti-apoptotic characteristics. In this review, we will focus on the neuroprotective properties of astaxanthin and explore the underlying mechanisms in the setting of neurological diseases.

BackgroundThe endoplasmic reticulum (ER) is responsible for the control of correct protein folding and protein function which is crucial for cell survival. However, under pathological conditions, such as hypoxia–ischemia (HI), there is an accumulation of unfolded proteins thereby triggering the unfolded protein response (UPR) and causing ER stress which is associated with activation of several stress sensor signaling pathways, one of them being the inositol requiring enzyme-1 alpha (IRE1α) signaling pathway. The UPR is regarded as a potential contributor to neuronal cell death and inflammation after HI. In the present study, we sought to investigate whether microRNA-17 (miR-17), a potential IRE1α ribonuclease (RNase) substrate, arbitrates downregulation of thioredoxin-interacting protein (TXNIP) and consequent NLRP3 inflammasome activation in the immature brain after HI injury and whether inhibition of IRE1α may attenuate inflammation via miR-17/TXNIP regulation.MethodsPostnatal day 10 rat pups (n = 287) were subjected to unilateral carotid artery ligation followed by 2.5 h of hypoxia (8% O2). STF-083010, an IRE1α RNase inhibitor, was intranasally delivered at 1 h post-HI or followed by an additional one administration per day for 2 days. MiR-17-5p mimic or anti-miR-17-5p inhibitor was injected intracerebroventricularly at 48 h before HI. Infarct volume and body weight were used to evaluate the short-term effects while brain weight, gross and microscopic brain tissue morphologies, and neurobehavioral tests were conducted for the long-term evaluation. Western blots, immunofluorescence staining, reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR), and co-immunoprecipitation (Co-IP) were used for mechanism studies.ResultsEndogenous phosphorylated IRE1α expression was significantly increased after HI. Intranasal administration of STF-083010 alleviated brain injury and improved neurological behavior. MiR-17-5p expression was reduced after HI, and this decrease was attenuated by STF-083010 treatment. MiR-17-5p mimic administration ameliorated TXNIP expression, NLRP3 inflammasome activation, caspase-1 cleavage, and IL-1β production, as well as brain infarct volume. Conversely, anti-miR-17-5p inhibitor reversed IRE1α inhibition-induced decrease in TXNIP expression and inflammasome activation, as well as exacerbated brain injury after HI.ConclusionsIRE1a-induced UPR pathway may contribute to inflammatory activation and brain injury following neonatal HI. IRE1a activation, through decay of miR-17-5p, elevated TXNIP expression to activate NLRP3 inflammasome and aggravated brain damage.Electronic supplementary materialThe online version of this article (10.1186/s12974-018-1077-9) contains supplementary material, which is available to authorized users.

Koml os has devised a way to use a linear number of binary comparisons to test whether a given spanning tree of a graph with edge costs is a minimum spanning tree. The total computational work required by his method is much larger than linear, however. We describe a linear-time algorithm for verifying a minimum spanning tree. Our algorithm combines the result of Koml os with a preprocessing and table look-up method for small subproblems and with a previously known almost-linear-time algorithm. Additionally, we present an optimal deterministic algorithm and a linear-time randomized algorithm for sensitivity analysis of minimum spanning trees. 1. Introduction. Suppose we wish to solve some problem for which we know in advance the size of the input data, using an algorithm from some well-dened class of algorithms. For example, consider sorting n numbers, when n is xed in advance, using a binary comparison tree. Given a sucient amount of preprocessing time and storage space, we can in a preprocessing step compute a minimum-depth comparison tree, store it explicitly, and then solve any instance of the sorting problem by using the precomputed comparison tree. This technique is of course generally useless because it is prohibitively expensive in preprocessing time and storage space, both being at least exponential in n. There are situations in which this idea can be used to advantage, however. This is the case in problems susceptible to very ecient divideand-conquer. The idea is to split the problem to be solved into subproblems, which are categorized into classes. If the subproblems are small enough, they can be solved eciently as follows: An optimal algorithm for each class is precomputed and stored in a look-up table, and each instance of a subproblem is solved by looking up and running the algorithm for its class. For this technique to pay o, solving all the subproblems must reduce the original problem suciently that it can be solved quickly with respect to the size of the original problem by using a non-optimal algorithm. This paper presents an applicationof this general techniqueto two problems concerningminimum spanning trees. This approach was rst proposed explicitly by Larmore [15], who used it to solve a convex matrix searching problem. Related techniques were used by Gabow and Tarjan [8] to solve a disjoint set union problem, by Harel and Tarjan [12] to nd nearest common ancestors in a tree, and by Fredman [5] to solve the all pairs shortest path problem. We present an algorithm that veries a minimum spanning tree in an n-vertex, m-edge graph in O(m) time. We also give algorithms performing sensitivity analysis of minimum spanning trees in worst-case time minimum to within a constant factor and in linear expected time. Our model of computation allows edge costs to be compared, added, or subtracted at unit cost, and side computations to be performed on a unit-cost random-access machine with word size (logn) bits. The verication algorithm uses the comparison bound of Koml os [14] for the subproblems and Tarjan'...