Pilot scale application of ozonated water wash - effect on microbiological and sensory quality parameters of processed iceberg lettuce during self-life

The aim of the study was to assess the effect of ozonated water wash on the microbiological and sensory quality parameters of minimally processed iceberg lettuce in pilot scale in comparison to aqueous chlorine wash. Alternative solutions for chlorine are needed, since its use is prohibited in organic food processing. Iceberg lettuce samples were washed with three different ozone solutions and the water wash and the 100 ppm chlorine wash were used as control. Ozone generator based on corona discharge was used to produce ozone at level 7 ppm. The samples (150 g) packed in oriented polypropylene pouches were stored for 10 days at +5C and the microbiological and sensory quality was analysed on days 1, 6 and 10. There was no significant difference between chlorine wash samples and the samples washed 1 min in a machine with ozonated water concerning the microbiological quality. Compared with the chlorine with lower concentrations of ozone it is possible to control the microbial load. Concerning the sensory quality all samples endured all of the treatments well except the treatment with 7 ppm ozone for 5 min. As a conclusion the bubbling gaseous ozone in water can be as effective disinfection method as chlorine wash when the following processing parameters are taken into account: concentration of ozone during the whole process, exposure time, water temperature and the amount and type of the organic material

Genotype-phenotype correlation in seven motor neuron disease families with novel ALS2 mutations

Autosomal-recessive mutations in the Alsin Rho guanine nucleotide exchange factor (ALS2) gene may cause specific subtypes of childhood-onset progressive neurodegenerative motor neuron diseases (MND). These diseases can manifest with a clinical continuum from infantile ascending hereditary spastic paraplegia (IAHSP) to juvenile-onset forms with or without lower motor neuron involvement, the juvenile primary lateral sclerosis (JPLS) and the juvenile amyotrophic lateral sclerosis (JALS). We report 11 patients from seven unrelated Turkish and Yemeni families with clinical signs of IAHSP or JPLS. We performed haplotype analysis or next-generation panel sequencing followed by Sanger Sequencing to unravel the genetic disease cause. We described their clinical phenotype and analyzed the pathogenicity of the detected variants with bioinformatics tools. We further reviewed all previously reported cases with ALS2-related MND. We identified five novel homozygous pathogenic variants in ALS2 at various positions: c.275_276delAT (p.Tyr92CysfsTer11), c.1044C>G (p.Tyr348Ter), c.1718C>A (p.Ala573Glu), c.3161T>C (p.Leu1054Pro), and c.1471+1G>A (NM_020919.3, NP_065970.2). In our cohort, disease onset was in infancy or early childhood with rapid onset of motor neuron signs. Muscle weakness, spasticity, severe dysarthria, dysphagia, and facial weakness were common features in the first decade of life. Frameshift and nonsense mutations clustered in the N-terminal Alsin domains are most prevalent. We enriched the mutational spectrum of ALS2-related disorders with five novel pathogenic variants. Our study indicates a high detection rate of ALS2 mutations in patients with a clinically well-characterized early onset MND. Intrafamilial and even interfamilial diversity in patients with identical pathogenic variants suggest yet unknown modifiers for phenotypic expression

Black hole mass and angular momentum in topologically massive gravity

We extend the Abbott-Deser-Tekin approach to the computation of the Killing charge for a solution of topologically massive gravity (TMG) linearized around an arbitrary background. This is then applied to evaluate the mass and angular momentum of black hole solutions of TMG with non-constant curvature asymptotics. The resulting values, together with the appropriate black hole entropy, fit nicely into the first law of black hole thermodynamics.Comment: 20 pages, references added, version to appear in Classical and Quantum Gravit

Holography in Three-dimensional Kerr-de Sitter Space with a Gravitational Chern-Simons Term

The holographic description of the three-dimensional Kerr-de Sitter space with a gravitational Chern-Simons term is studied, in the context of dS/CFT correspondence. The space has only one (cosmological) event horizon and its mass and angular momentum are identified from the holographic energy-momentum tensor at the asymptotic infinity. The thermodynamic entropy of the cosmological horizon is computed directly from the first law of thermodynamics, with the usual Hawking temperature, and it is found that the usual Gibbons-Hawking entropy is modified. It is remarked that, due to the gravitational Chern-Simons term, (a) the results go beyond analytic continuation from AdS, (b) the maximum-mass/N-bound conjecture may be violated, and (c) the three-dimensional cosmology is chiral. A statistical mechanical computation of the entropy, from a Cardy-like formula for a dual CFT at the asymptotic boundary, is discussed. Some technical difference in the Chern-Simons energy-momentum tensor, from literatures is remarked also.Comment: Typos corrected; Accepted in CQ

Placing limits on the stochastic gravitational-wave background using European Pulsar Timing Array data

Direct detection of low-frequency gravitational waves ($10^{-9} - 10^{-8}$ Hz) is the main goal of pulsar timing array (PTA) projects. One of the main targets for the PTAs is to measure the stochastic background of gravitational waves (GWB) whose characteristic strain is expected to approximately follow a power-law of the form $h_c(f)=A (f/\hbox{yr}^{-1})^{\alpha}$, where $f$ is the gravitational-wave frequency. In this paper we use the current data from the European PTA to determine an upper limit on the GWB amplitude $A$ as a function of the unknown spectral slope $\alpha$ with a Bayesian algorithm, by modelling the GWB as a random Gaussian process. For the case $\alpha=-2/3$, which is expected if the GWB is produced by supermassive black-hole binaries, we obtain a 95% confidence upper limit on $A$ of $6\times 10^{-15}$, which is 1.8 times lower than the 95% confidence GWB limit obtained by the Parkes PTA in 2006. Our approach to the data analysis incorporates the multi-telescope nature of the European PTA and thus can serve as a useful template for future intercontinental PTA collaborations.Comment: 14 pages, 8 figures, 3 tables, mnras accepte

Essential oils as antibacterial agents against food-borne pathogens: are they really as useful as they are claimed to be ?

Original articleMost studies evaluating the use of essential oils (EO) as antibacterial agents focus mainly on minimal inhibitory concentrations (MIC) rather than minimal bactericidal concentrations (MBC). In this work, we compared MICs and MBCs of EO from condiment plants commonly used in Mediterranean Europe, namely Origanum vulgare, Salvia lavandulaefolia, Salvia officinalis, Salvia sclarea and Rosmarinus officinalis, aiming to evaluate their application as disinfecting agents in minimally processed produce. Outbreaks-related pathogens such as Listeria monocytogenes, Pseudomonas aeruginosa and Yarrowia lipolytica were used. Results showed that all EO were able to reduce bacterial growth in all bacterial strains tested, particularly O. vulgare. However, fewer EO exhibited bactericidal activities, and were only effective against one or two bacterial strains, hence eliminating the possibility to use them as broad range disinfectants. Furthermore, the necessary concentrations were too high for food application. Hence, our work suggests the need to evaluate MBC rather than MIC and questions EO usefulness in controlling undesired microorganisms. Overall, and despite the large volume of data published on EO, results obtained were not very encouraging for a realistic application on produce and question the viability of EOs as disinfecting agents in foodinfo:eu-repo/semantics/publishedVersio

Novel SPG11 mutations in Asian kindreds and disruption of spatacsin function in the zebrafish

Autosomal recessive hereditary spastic paraplegia with thin corpus callosum (HSP-TCC) maps to the SPG11 locus in the majority of cases. Mutations in the KIAA1840 gene, encoding spatacsin, have been shown to underlie SPG11-linked HSP-TCC. The aim of this study was to perform candidate gene analysis in HSP-TCC subjects from Asian families and to characterize disruption of spatacsin function during zebrafish development. Homozygosity mapping and direct sequencing were used to assess the ACCPN, SPG11, and SPG21 loci in four inbred kindreds originating from the Indian subcontinent. Four novel homozygous SPG11 mutations (c.442+1G>A, c.2146C>T, c.3602_3603delAT, and c.4846C>T) were identified, predicting a loss of spatacsin function in each case. To investigate the role of spatacsin during development, we additionally ascertained the complete zebrafish spg11 ortholog by reverse transcriptase PCR and 5′ RACE. Analysis of transcript expression through whole-mount in situ hybridization demonstrated ubiquitous distribution, with highest levels detected in the brain. Morpholino antisense oligonucleotide injection was used to knock down spatacsin function in zebrafish embryos. Examination of spg11 morphant embryos revealed a range of developmental defects and CNS abnormalities, and analysis of axon pathway formation demonstrated an overall perturbation of neuronal differentiation. These data confirm loss of spatacsin as the cause of SPG11-linked HSP-TCC in Asian kindreds, expanding the mutation spectrum recognized in this disorder. This study represents the first investigation in zebrafish addressing the function of a causative gene in autosomal recessive HSP and identifies a critical role for spatacsin during early neural development in vivo

Crowdsourced mapping of unexplored target space of kinase inhibitors

Despite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound-kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome. The IDG-DREAM Challenge carried out crowdsourced benchmarking of predictive algorithms for kinase inhibitor activities on unpublished data. This study provides a resource to compare emerging algorithms and prioritize new kinase activities to accelerate drug discovery and repurposing efforts

Intelligent Identification of Childhood Musical Murmurs

Heart murmurs are often the first signs of heart valvular disorders. However, most heart murmurs detected in children are innocent musical murmurs (also called Still's murmurs), which should be distinguished from other murmur types that are mostly pathological, such as regurgitant, obstructive, and flow murmurs. In order to reduce both unnecessary healthcare expenditures and parental anxiety, this study aims to develop algorithms for intelligently identifying musical murmurs in children. Discrete wavelet transform was applied to phonocardiographic signals to extract features. Singular value decomposition was applied on the matrix derived from continuous wavelet transform to extract extra features. The sequential forward feature selection algorithm was then utilized to select significant features. Musical murmurs were subsequently differentiated via a classification procedure consisting of three classification techniques: discriminant analysis, support vector machine, and artificial neural network. The results of 89.02% sensitivity, 84.76% specificity and 87.36% classification accuracy were achieved