Translation into Arabic and validation of the ASES index in assessment of shoulder disabilities

AbstractObjectiveTo translate into Arabic and validate the “American Shoulder and Elbow Surgeons Evaluation Form” (ASES) for use in a Tunisian population presenting with periarticular pathologies of the shoulder.BackgroundNo functional index assessing the functional capacities of the shoulder is presently available in Arabic.Patients and methodsThe translation was achieved by means of forward/backward translation. Adaptations were carried out subsequent to a preliminary test involving 15 persons. Patients with periarticular shoulder disabilities were included. Clinical measurements evaluated pain and functional disability by means of the visual analogue scale (VAS). Interrater concordance (repeatability) was assessed using the intraclass correlation coefficient (ICC) and the Bland and Altman method. Construct validity (convergent and discriminant validity) was investigated using the Spearman rank correlation coefficient and a factorial analysis followed by orthogonal rotation. The internal consistency of each factor was graded in terms of the Cronbach alpha coefficient.ResultsEighty (80) patients were included in the study. Interrater concordance was excellent (ICC=0.96). The Bland and Altman method showed a low-variability mean difference. Correlations of the index score with the pain VAS (r=−0.49) and functional disability (r=−0.58) suggested satisfactory convergent validity, and our index likewise showed good discriminant validity. Factorial analysis led to the extraction of two factors with a cumulative variance rate of 92.6% that could not be explained.ConclusionTranslated into Arabic, the ASES index was found to possess high metrological qualities. While the index has been satisfactorily validated with regard to a Tunisian population, additional studies are needed to verify its applicability to other Arab populations

Towards the Formal Reliability Analysis of Oil and Gas Pipelines

It is customary to assess the reliability of underground oil and gas pipelines in the presence of excessive loading and corrosion effects to ensure a leak-free transport of hazardous materials. The main idea behind this reliability analysis is to model the given pipeline system as a Reliability Block Diagram (RBD) of segments such that the reliability of an individual pipeline segment can be represented by a random variable. Traditionally, computer simulation is used to perform this reliability analysis but it provides approximate results and requires an enormous amount of CPU time for attaining reasonable estimates. Due to its approximate nature, simulation is not very suitable for analyzing safety-critical systems like oil and gas pipelines, where even minor analysis flaws may result in catastrophic consequences. As an accurate alternative, we propose to use a higher-order-logic theorem prover (HOL) for the reliability analysis of pipelines. As a first step towards this idea, this paper provides a higher-order-logic formalization of reliability and the series RBD using the HOL theorem prover. For illustration, we present the formal analysis of a simple pipeline that can be modeled as a series RBD of segments with exponentially distributed failure times.Comment: 15 page

Alternative Splicing of Spg7, a Gene Involved in Hereditary Spastic Paraplegia, Encodes a Variant of Paraplegin Targeted to the Endoplasmic Reticulum

BACKGROUND: Hereditary spastic paraplegia defines a group of genetically heterogeneous diseases characterized by weakness and spasticity of the lower limbs owing to retrograde degeneration of corticospinal axons. One autosomal recessive form of the disease is caused by mutation in the SPG7 gene. Paraplegin, the product of SPG7, is a component of the m-AAA protease, a high molecular weight complex that resides in the mitochondrial inner membrane, and performs crucial quality control and biogenesis functions in mitochondria. PRINCIPAL FINDINGS: Here we show the existence in the mouse of a novel isoform of paraplegin, which we name paraplegin-2, encoded by alternative splicing of Spg7 through usage of an alternative first exon. Paraplegin-2 lacks the mitochondrial targeting sequence, and is identical to the mature mitochondrial protein. Remarkably, paraplegin-2 is targeted to the endoplasmic reticulum. We find that paraplegin-2 exposes the catalytic domains to the lumen of the endoplasmic reticulum. Moreover, endogenous paraplegin-2 accumulates in microsomal fractions prepared from mouse brain and retina. Finally, we show that the previously generated mouse model of Spg7-linked hereditary spastic paraplegia is an isoform-specific knock-out, in which mitochondrial paraplegin is specifically ablated, while expression of paraplegin-2 is retained. CONCLUSIONS/SIGNIFICANCE: These data suggest a possible additional role of AAA proteases outside mitochondria and open the question of their implication in neurodegeneration

Bioactive Secondary Metabolites from a New Terrestrial Streptomyces sp. TN262

During our search for Streptomyces spp. as new producers of bioactive secondary metabolites, the ethyl acetate extract of the new terrestrial Streptomyces isolate TN262 delivered eight antimicrobially active compounds. They were identified as 1-acetyl-β-carboline (1), tryptophol (2), cineromycin B (3), 2,3-dihydrocineromycin B (4), cyclo-(tyrosylprolyl) (5), 3-(hydroxyacetyl)-indole (6), brevianamide F (7), and cis-cyclo-(l-prolyl-l-leucyl) (8). Three further metabolites were detected in the unpolar fractions using GC–MS and tentatively assigned as benzophenone (9), N-butyl-benzenesulfonamide (10), and hexanedioic acid-bis-(2-ethylhexyl) ester (11). This last compound is known as plasticizer derivatives, but it has never been described from natural sources. In this article, we describe the identification of the new Streptomyces sp. isolate TN262 using its cultural characteristics, the nucleotide sequence of the corresponding 16S rRNA gene and the phylogenetic analysis, followed by optimization, large-scale fermentation, isolation of the bioactive constituents, and determination of their structures. The biological activity of compounds (2), (3), (4), and those of the unpolar fractions was addressed as well

Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging

Hyperspectral imaging enables researchers and plant breeders to analyze various traits of interest like nutritional value in high throughput. In order to achieve this, the optimal design of a reliable calibration model, linking the measured spectra with the investigated traits, is necessary. In the present study we investigated the impact of different regression models, calibration set sizes and calibration set compositions on prediction performance. For this purpose, we analyzed concentrations of six globally relevant grain nutrients of the wild barley population HEB-YIELD as case study. The data comprised 1,593 plots, grown in 2015 and 2016 at the locations Dundee and Halle, which have been entirely analyzed through traditional laboratory methods and hyperspectral imaging. The results indicated that a linear regression model based on partial least squares outperformed neural networks in this particular data modelling task. There existed a positive relationship between the number of samples in a calibration model and prediction performance, with a local optimum at a calibration set size of ~40% of the total data. The inclusion of samples from several years and locations could clearly improve the predictions of the investigated nutrient traits at small calibration set sizes. It should be stated that the expansion of calibration models with additional samples is only useful as long as they are able to increase trait variability. Models obtained in a certain environment were only to a limited extent transferable to other environments. They should therefore be successively upgraded with new calibration data to enable a reliable prediction of the desired traits. The presented results will assist the design and conceptualization of future hyperspectral imaging projects in order to achieve reliable predictions. It will in general help to establish practical applications of hyperspectral imaging systems, for instance in plant breeding concepts