KCNQ/M currents in sensory neurons: Significance for pain therapy

Neuronal hyperexcitability is a feature of epilepsy and both inflammatory and neuropathic pain. M currents [I-K(M)] play a key role in regulating neuronal excitability, and mutations in neuronal KCNQ2/3 subunits, the molecular correlates of I-K(M), have previously been linked to benign familial neonatal epilepsy. Here, we demonstrate that KCNQ/M channels are also present in nociceptive sensory systems. I-K(M) was identified, on the basis of biophysical and pharmacological properties, in cultured neurons isolated from dorsal root ganglia (DRGs) from 17-d-old rats. Currents were inhibited by the M-channel blockers linopirdine (IC50, 2.1 muM) and XE991 (IC50, 0.26 muM) and enhanced by retigabine (10 muM). The expression of neuronal KCNQ subunits in DRG neurons was confirmed using reverse transcription-PCR and single-cell PCR analysis and by immunofluorescence. Retigabine, applied to the dorsal spinal cord, inhibited C and Adelta fiber-mediated responses of dorsal horn neurons evoked by natural or electrical afferent stimulation and the progressive "windup" discharge with repetitive stimulation in normal rats and in rats subjected to spinal nerve ligation. Retigabine also inhibited responses to intrapaw application of carrageenan in a rat model of chronic pain; this was reversed by XE991. It is suggested that I-K(M) plays a key role in controlling the excitability of nociceptors and may represent a novel analgesic target

Phase I and pharmacokinetic study of XR11576, an oral topoisomerase I and II inhibitor, administered on days 1–5 of a 3-weekly cycle in patients with advanced solid tumours

XR11576 is an oral topoisomerase I and II inhibitor. The objectives of this phase I study were to assess the dose-limiting toxicities (DLTs), to determine the maximum tolerated dose (MTD) and to describe the pharmacokinetics (PKs) of XR11576 when administered orally on days 1-5 every 3 weeks to patients with advanced solid tumours. Patients were treated with escalating doses of XR11576 at doses ranging from 30

Effect of guar gum on the physicochemical, thermal, rheological and textural properties of green edam cheese

In attempts to produce a low-fat cheese with a rheology and texture similar to that of a full-fat cheese, guar gum (within 0.0025–0.01%; w/v, final concentration) was added to low-fat milk. The obtained cheeses were characterised regarding their physicochemical, thermal, rheological and textural properties. Control cheeses were also produced with low and full-fat milk. The physicochemical properties of the guar gum modified cheeses were similar to those of the low-fat control. No significant differences were detected in the thermal properties (concerning the enthalpy and profile of water desorption) among all types of cheeses. The rheological behaviour of the 0.0025% modified cheese was very similar to the full-fat control. Overall, no trend was observed in the texture profile (hardness, cohesiveness, gumminess and elasticity) of the modified cheeses versus guar gum concentration, as well as in comparison with the control groups, suggesting that none of the studied polysaccharide concentrations simulated the textural functions of fat in Edam cheese

Integration of multiple data sources to prioritize candidate genes using discounted rating system

Background: Identifying disease gene from a list of candidate genes is an important task in bioinformatics. The main strategy is to prioritize candidate genes based on their similarity to known disease genes. Most of existing gene prioritization methods access only one genomic data source, which is noisy and incomplete. Thus, there is a need for the integration of multiple data sources containing different information. Results: In this paper, we proposed a combination strategy, called discounted rating system (DRS). We performed leave one out cross validation to compare it with N-dimensional order statistics (NDOS) used in Endeavour. Results showed that the AUC (Area Under the Curve) values achieved by DRS were comparable with NDOS on most of the disease families. But DRS worked much faster than NDOS, especially when the number of data sources increases. When there are 100 candidate genes and 20 data sources, DRS works more than 180 times faster than NDOS. In the framework of DRS, we give different weights for different data sources. The weighted DRS achieved significantly higher AUC values than NDOS. Conclusion: The proposed DRS algorithm is a powerful and effective framework for candidate gene prioritization. If weights of different data sources are proper given, the DRS algorithm will perform better

Prostate cancer risk related to foods, food groups, macronutrients and micronutrients derived from the UK Dietary Cohort Consortium food diaries.

BACKGROUND/OBJECTIVES: The influence of dietary factors remains controversial for screen-detected prostate cancer and inconclusive for clinically detected disease. We aimed to examine these associations using prospectively collected food diaries. SUBJECTS/METHODS: A total of 1,717 prostate cancer cases in middle-aged and older UK men were pooled from four prospective cohorts with clinically detected disease (n=663), with routine data follow-up (means 6.6-13.3 years) and a case-control study with screen-detected disease (n=1054), nested in a randomised trial of prostate cancer treatments (ISCTRN 20141297). Multiple-day food diaries (records) completed by men prior to diagnosis were used to estimate intakes of 37 selected nutrients, food groups and items, including carbohydrate, fat, protein, dairy products, fish, meat, fruit and vegetables, energy, fibre, alcohol, lycopene and selenium. Cases were matched on age and diary date to at least one control within study (n=3528). Prostate cancer risk was calculated, using conditional logistic regression (adjusted for baseline covariates) and expressed as odds ratios in each quintile of intake (±95% confidence intervals). Prostate cancer risk was also investigated by localised or advanced stage and by cancer detection method. RESULTS: There were no strong associations between prostate cancer risk and 37 dietary factors. CONCLUSIONS: Prostate cancer risk, including by disease stage, was not strongly associated with dietary factors measured by food diaries in middle-aged and older UK men.Medical Research Council (Grant ID: MC_UU_12019/1), Medical Research Council Population Health Sciences Research Network, British Heart Foundation, Cancer Research UK (Grant ID: C8221/A19170), Department of Health, Food Standards Agency, Stroke Association, WCRF, National Institute for Health Research Health Technology Assessment Programme (Project IDs: 96/20/06, 96/20/99), National Cancer Research Institute (formed by Cancer Research UK, Medical Research Council, Department of Health)This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/ejcn.2016.16

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Substrate cycling between de novo lipogenesis and lipid oxidation: a thermogenic mechanism against skeletal muscle lipotoxicity and glucolipotoxicity

Life is a combustion, but how the major fuel substrates that sustain human life compete and interact with each other for combustion has been at the epicenter of research into the pathogenesis of insulin resistance ever since Randle proposed a 'glucose-fatty acid cycle' in 1963. Since then, several features of a mutual interaction that is characterized by both reciprocality and dependency between glucose and lipid metabolism have been unravelled, namely: 1. the inhibitory effects of elevated concentrations of fatty acids on glucose oxidation (via inactivation of mitochondrial pyruvate dehydrogenase or via desensitization of insulin-mediated glucose transport), 2. the inhibitory effects of elevated concentrations of glucose on fatty acid oxidation (via malonyl-CoA regulation of fatty acid entry into the mitochondria), and more recently 3. the stimulatory effects of elevated concentrations of glucose on de novo lipogenesis, that is, synthesis of lipids from glucose (via SREBP1c regulation of glycolytic and lipogenic enzymes). This paper first revisits the physiological significance of these mutual interactions between glucose and lipids in skeletal muscle pertaining to both blood glucose and intramyocellular lipid homeostasis. It then concentrates upon emerging evidence, from calorimetric studies investigating the direct effect of leptin on thermogenesis in intact skeletal muscle, of yet another feature of the mutual interaction between glucose and lipid oxidation: that of substrate cycling between de novo lipogenesis and lipid oxidation. It is proposed that this energy-dissipating substrate cycling that links glucose and lipid metabolism to thermogenesis could function as a 'fine-tuning' mechanism that regulates intramyocellular lipid homeostasis, and hence contributes to the protection of skeletal muscle against lipotoxicity

Using genetic variation and environmental risk factor data to identify individuals at high risk for age-related macular degeneration

A major goal of personalized medicine is to pre-symptomatically identify individuals at high risk for disease using knowledge of each individual's particular genetic profile and constellation of environmental risk factors. With the identification of several well-replicated risk factors for age-related macular degeneration (AMD), the leading cause of legal blindness in older adults, this previously unreachable goal is beginning to seem less elusive. However, recently developed algorithms have either been much less accurate than expected, given the strong effects of the identified risk factors, or have not been applied to independent datasets, leaving unknown how well they would perform in the population at large. We sought to increase accuracy by using novel modeling strategies, including multifactor dimensionality reduction (MDR) and grammatical evolution of neural networks (GENN), in addition to the traditional logistic regression approach. Furthermore, we rigorously designed and tested our models in three distinct datasets: a Vanderbilt-Miami (VM) clinic-based case-control dataset, a VM family dataset, and the population-based Age-related Maculopathy Ancillary (ARMA) Study cohort. Using a consensus approach to combine the results from logistic regression and GENN models, our algorithm was successful in differentiating between high- and low-risk groups (sensitivity 77.0%, specificity 74.1%). In the ARMA cohort, the positive and negative predictive values were 63.3% and 70.7%, respectively. We expect that future efforts to refine this algorithm by increasing the sample size available for model building, including novel susceptibility factors as they are discovered, and by calibrating the model for diverse populations will improve accuracy