Local and systemic metabolic alterations in brain, plasma, and liver of rats in response to aging and ischemic stroke, as detected by nuclear magnetic resonance (NMR) spectroscopy

Metabolic dysfunction impacts stroke incidence and outcome. However, the intricate association between altered metabolic program due to aging, and focal ischemia in brain, circulation, and peripheral organs is not completely elucidated. Here we identified locally and systemically altered metabolites in brain, liver, and plasma as a result of normal aging, ischemic-stroke, and extended time of reperfusion injury. Comprehensive quantitative metabolic profiling was carried out using nuclear magnetic resonance spectroscopy. Aging, but healthy rats showed significant metabolic alterations in the brain, but only a few metabolic changes in the liver and plasma as compared to younger rats. But, ischemic stroke altered metabolites significantly in liver and plasma of older rats during early acute phase. Major metabolic changes were also seen in the brains of younger rats following ischemic stroke during early acute phase of injury. We further report that metabolic changes occur sequentially in a tissue specific manner during extended reperfusion time of late repair phase. First metabolic alterations occurred in brain due to local injury. Next, changes in circulating metabolites in plasma occurred during acute-repair phase transition time. Lastly, the delayed systemic effect was seen in the peripheral organ, liver that exhibited significant and persistent changes in selected metabolites during later reperfusion time. The metabolic pathways involved in energy/glucose, and amino acid metabolism, inflammation, and oxidative stress were mainly altered as a result of aging and ischemia/reperfusion. Biomarker analysis revealed citrate, lysine, and tyrosine as potential age-independent blood metabolic biomarkers of ischemia/reperfusion. Overall, our study elucidates the complex network of metabolic events as a function of normal aging and acute stroke. We further provide evidence for a clear transition from local to systemic metabolic dysfunction due to ischemic injury in a time dependent manner, which may altogether greatly impact the post-stroke outcome

Prevalence of Listeria species in camel sausages from retail markets in Aydin province in Turkey and RAPD analysis of Listeria monocytogenes isolates

Samples were taken from 100 camel sausages from the different retail markets in Aydin province in the south-west of Turkey and they were tested for the presence of Listeria spp by biochemical methods. Samples were enriched using Listeria Enrichment Broth and they were inoculated onto Listeria Selective Agar. Listeria monocytogenes was isolated from nine samples (9%), Listeria innocua from 14 samples (14%) and Listeria welshimeri from two samples(2%). A 701 bp fragment of listeriolysin O sequence for L. monocytogenes was amplified using specific primers by polymerase chain reaction (PCR) for confirmation of the identification. A random primer (OPA-11) was used in a random amplified polymorphic DNA (RAPD) assay. This detected five different band profiles amongst the L. monocytogenes isolates, indicating a relatively large amount of genetic heterogeneity amongst the nine isolates. The study has highlighted the need for improved strategies for food safety, in particular appropriate hygienic precautions to avoid contamination of sausage during the manufacturing process and appropriate preservation techniques during storage and transport, to prevent transmission of Listeria spp to consumers at home and abroad

Ensemble-Based Computational Approach Discriminates Functional Activity of p53 Cancer and Rescue Mutants

The tumor suppressor protein p53 can lose its function upon single-point missense mutations in the core DNA-binding domain (“cancer mutants”). Activity can be restored by second-site suppressor mutations (“rescue mutants”). This paper relates the functional activity of p53 cancer and rescue mutants to their overall molecular dynamics (MD), without focusing on local structural details. A novel global measure of protein flexibility for the p53 core DNA-binding domain, the number of clusters at a certain RMSD cutoff, was computed by clustering over 0.7 µs of explicitly solvated all-atom MD simulations. For wild-type p53 and a sample of p53 cancer or rescue mutants, the number of clusters was a good predictor of in vivo p53 functional activity in cell-based assays. This number-of-clusters (NOC) metric was strongly correlated (r2 = 0.77) with reported values of experimentally measured ΔΔG protein thermodynamic stability. Interpreting the number of clusters as a measure of protein flexibility: (i) p53 cancer mutants were more flexible than wild-type protein, (ii) second-site rescue mutations decreased the flexibility of cancer mutants, and (iii) negative controls of non-rescue second-site mutants did not. This new method reflects the overall stability of the p53 core domain and can discriminate which second-site mutations restore activity to p53 cancer mutants

Predicting Positive p53 Cancer Rescue Regions Using Most Informative Positive (MIP) Active Learning

Many protein engineering problems involve finding mutations that produce proteins with a particular function. Computational active learning is an attractive approach to discover desired biological activities. Traditional active learning techniques have been optimized to iteratively improve classifier accuracy, not to quickly discover biologically significant results. We report here a novel active learning technique, Most Informative Positive (MIP), which is tailored to biological problems because it seeks novel and informative positive results. MIP active learning differs from traditional active learning methods in two ways: (1) it preferentially seeks Positive (functionally active) examples; and (2) it may be effectively extended to select gene regions suitable for high throughput combinatorial mutagenesis. We applied MIP to discover mutations in the tumor suppressor protein p53 that reactivate mutated p53 found in human cancers. This is an important biomedical goal because p53 mutants have been implicated in half of all human cancers, and restoring active p53 in tumors leads to tumor regression. MIP found Positive (cancer rescue) p53 mutants in silico using 33% fewer experiments than traditional non-MIP active learning, with only a minor decrease in classifier accuracy. Applying MIP to in vivo experimentation yielded immediate Positive results. Ten different p53 mutations found in human cancers were paired in silico with all possible single amino acid rescue mutations, from which MIP was used to select a Positive Region predicted to be enriched for p53 cancer rescue mutants. In vivo assays showed that the predicted Positive Region: (1) had significantly more (p<0.01) new strong cancer rescue mutants than control regions (Negative, and non-MIP active learning); (2) had slightly more new strong cancer rescue mutants than an Expert region selected for purely biological considerations; and (3) rescued for the first time the previously unrescuable p53 cancer mutant P152L

Salivary Gland NK Cells Are Phenotypically and Functionally Unique

Natural killer (NK) cells and CD8+ T cells play vital roles in containing and eliminating systemic cytomegalovirus (CMV). However, CMV has a tropism for the salivary gland acinar epithelial cells and persists in this organ for several weeks after primary infection. Here we characterize a distinct NK cell population that resides in the salivary gland, uncommon to any described to date, expressing both mature and immature NK cell markers. Using RORγt reporter mice and nude mice, we also show that the salivary gland NK cells are not lymphoid tissue inducer NK-like cells and are not thymic derived. During the course of murine cytomegalovirus (MCMV) infection, we found that salivary gland NK cells detect the infection and acquire activation markers, but have limited capacity to produce IFN-γ and degranulate. Salivary gland NK cell effector functions are not regulated by iNKT or Treg cells, which are mostly absent in the salivary gland. Additionally, we demonstrate that peripheral NK cells are not recruited to this organ even after the systemic infection has been controlled. Altogether, these results indicate that viral persistence and latency in the salivary glands may be due in part to the presence of unfit NK cells and the lack of recruitment of peripheral NK cells

Evaluating early administration of the hydroxymethylglutaryl-CoA reductase inhibitor simvastatin in the prevention and treatment of delirium in critically ill ventilated patients (MoDUS trial): Study protocol for a randomized controlled trial

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Abstract Background The incidence of delirium in ventilated patients is estimated at up to 82%, and it is associated with longer intensive care and hospital stays, and long-term cognitive impairment and mortality. The pathophysiology of delirium has been linked with inflammation and neuronal apoptosis. Simvastatin has pleiotropic properties; it penetrates the brain and, as well as reducing cholesterol, reduces inflammation when used at clinically relevant doses over the short term. This is a single centre randomised, controlled trial which aims to test the hypothesis that treatment with simvastatin will modify delirium incidence and outcomes. Methods/Design The ongoing study will include 142 adults admitted to the Watford General Hospital Intensive Care Unit who require mechanical ventilation in the first 72 hours of admission. The primary outcome is the number of delirium- and coma-free days in the first 14 days. Secondary outcomes include incidence of delirium, delirium- and coma-free days in the first 28 days, days in delirium and in coma at 14 and 28 days, number of ventilator-free days at 28 days, length of critical care and hospital stay, mortality, cognitive decline and healthcare resource use. Informed consent will be taken from patient’s consultee before randomisation to receive either simvastatin (80 mg) or placebo once daily. Daily data will be recorded until day 28 after randomisation or until discharge from the ICU if sooner. Surviving patients will be followed up on at six months from discharge. Plasma and urine samples will be taken to investigate the biological effect of simvastatin on systemic markers of inflammation, as related to the number of delirium- and coma-free days, and the potential of cholinesterase activity and beta-amyloid as predictors of the risk of delirium and long-term cognitive impairment. Discussion This trial will test the efficacy of simvastatin on reducing delirium in the critically ill. If patients receiving the statin show a reduced number of days in delirium compared with the placebo group, the inflammatory theory implicated in the pathogenesis of delirium will be strengthened. Trial registration The trial was registered with the International Standard Randomised Controlled Trial Registry (ISRCTN89079989) on 26 March 2013.Peer reviewe

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost