Intra-subject variability in attention-deficit hyperactivity disorder

BACKGROUND: This study is based on a comprehensive survey of the neuropsychological attention-deficit hyperactivity disorder (ADHD) literature and presents the first psychometric analyses of different parameters of intra-subject variability (ISV) in patients with ADHD compared to healthy controls, using the Continuous Performance Test, a Go-NoGo task, a Stop Signal Task, as well as N-back tasks. METHODS: Data of 57 patients with ADHD and 53 age- and gender-matched controls were available for statistical analysis. Different parameters were used to describe central tendency (arithmetic mean, median), dispersion (standard deviation, coefficient of variation, consecutive variance), and shape (skewness, excess) of reaction time distributions, as well as errors (commissions and omissions). RESULTS: Group comparisons revealed by far the strongest effect sizes for measures of dispersion, followed by measures of central tendency, and by commission errors. Statistical control of ISV reduced group differences in the other measures substantially. One (patients) or two (controls) principal components explained up to 67% of the inter-individual differences in intra-individual variability. CONCLUSIONS: Results suggest that, across a variety of neuropsychological tests, measures of ISV contribute best to group discrimination, with limited incremental validity of measures of central tendency and errors. Furthermore, increased ISV might be a unitary construct in ADHD.

A pain assessment scale for population-based studies: Development and validation of the Pain Module of the Standard Evaluation Questionnaire

The objectives of this study were to develop and validate a tool for assessing pain in population-based observational studies and to develop three subscales for back/neck, upper extremity and lower extremity pain. Based on a literature review, items were extracted from validated questionnaires and reviewed by an expert panel. The initial questionnaire consisted of a pain manikin and 34 items relating to (i) intensity of pain in different body regions (7 items), (ii) pain during activities of daily living (18 items) and (iii) various pain modalities (9 items). Psychometric validation of the initial questionnaire was performed in a random sample of the German-speaking Swiss population. Analyses included tests for reliability, correlation analysis, principal components factor analysis, tests for internal consistency and validity. Overall, 16,634 of 23,763 eligible individuals participated (70%). Test-retest reliability coefficients ranged from 0.32 to 0.97, but only three coefficients were below 0.60. Subscales were constructed combining four items for each of the subscales. Item-total coefficients ranged from 0.76 to 0.86 and Cronbach's alpha were 0.75 or higher for all subscales. Correlation coefficients between subscales and three validated instruments (WOMAC, SPADI and Oswestry) ranged from 0.62 to 0.79. The final Pain Standard Evaluation Questionnaire (SEQ Pain) included 28 items and the pain manikin and accounted for the multidimensionality of pain by assessing pain location and intensity, pain during activity, triggers and time of onset of pain and frequency of pain medication. It was found to be reliable and valid for the assessment of pain in population-based observational studies.

Automatic Reduction of Artifacts in EEG-Signals

Electroencephalograms (EEG) are often contaminated with high amplitude artifacts limiting the usability of data. Methods that reduce these artifacts are often restricted to certain types of artifacts, require manual interaction or large training data sets. Within this paper we introduce a novel method, which is able to eliminate many different types of artifacts without manual intervention. The algorithm first decomposes the signal into different sub-band signals in order to isolate different types of artifacts into specific frequency bands. After signal decomposition with principal component analysis (PCA) an adaptive threshold is applied to eliminate components with high variance corresponding to the dominant artifact activity. Our results show that the algorithm is able to significantly reduce artifacts while preserving the EEG activity. Parameters for the algorithm do not have to be identified for every patient individually making the method a good candidate for preprocessing in automatic seizure detection and prediction algorithms.

Transcriptional analysis of left-sided colitis, pancolitis, and ulcerative colitis-associated dysplasia.

BACKGROUND It is unknown why patients with extensive ulcerative colitis (UC) have a higher risk of colorectal cancer compared with patients with left-sided UC. This study characterizes the inflammatory processes in left-sided UC, pancolitis, and UC-associated dysplasia at the transcriptional level to identify potential biomarkers and transcripts of importance for the carcinogenic behavior of chronic inflammation. METHODS The Affymetrix GeneChip Human Genome U133 Plus 2.0 was applied on colonic biopsies from UC patients with left-sided UC, pancolitis, dysplasia, and controls. Reverse transcription polymerase chain reaction and immunohistochemistry were performed for validating selected transcripts in the initial cohort and in 2 independent cohorts of patients with UC. Microarray data were analyzed by principal component analysis, and reverse transcription polymerase chain reaction and immunohistochemistry data by the Wilcoxon's rank-sum test. RESULTS The principal component analysis results revealed separate clusters for left-sided UC, pancolitis, dysplasia, and controls. Close clustering of dysplastic and pancolitic samples indicated similarities in gene expression. Indeed, 101 and 656 parallel upregulated and downregulated transcripts, respectively, were identified in specimens from dysplasia and pancolitis. Validation of selected transcripts hereof identified insulin receptor alpha (INSRA) and MAP kinase interacting serine/threonine kinase 2 (MKNK2) with an enhanced expression in dysplasia compared with left-sided UC and controls, whereas laminin γ2 (LAMC2) was found with a lower expression in dysplasia compared with the remaining 3 groups. CONCLUSIONS This study demonstrates pancolitis and left-sided UC as distinct inflammatory processes at the transcriptional level, and identifies INSRA, MKNK2, and LAMC2 as potential critical transcripts in the inflammation-driven preneoplastic process of UC.

Visible near infra-red (VisNIR) spectroscopy for predicting soil organic carbon in Ethiopia

Over the past few decades, the advantages of the visible-near infra-red (VisNIR) diffuse reflectance spectrometer (DRS) method have enabled prediction of soil organic carbon (SOC). In this study, SOC was predicted using regression models for samples taken from three sites (Gununo, Maybar and Anjeni) in Ethiopia. SOC was characterized in laboratory using conventional wet chemistry and VisNIR-DRS methods. Principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLS) models were developed using Unscrambler X 10.2. PCA results show that the first two components accounted for a minimum of 96% variation which increased for individual sites and with data treatments. Correlation (r), coefficient of determination (R2) and residual prediction deviation (RPD) were used to rate four models built. PLS model (r, R2, RPD) values for Anjeni were 0.9, 0.9 and 3.6; for Gununo values 0.6, 0.3 and 1.2; for Maybar values 0.6, 0.3 and 0.9, and for the three sites values 0.7, 0.6 and 1.5, respectively. PCR model values (r, R2, RPD) for Anjeni were 0.9, 0.8 and 2.7; for Gununo values 0.5, 0.3 and 1; for Maybar values 0.5, 0.1 and 0.7, and for the three sites values 0.7, 0.5 and 1.2, respectively. Comparison and testing of models shows superior performance of PLS to PCR. Models were rated as very poor (Maybar), poor (Gununo and three sites) and excellent (Anjeni). A robust model, Anjeni, is recommended for prediction of SOC in Ethiopia.

Geographic variation in floral allometry suggests repeated transitions between selfing and outcrossing in a mixed mating plant

• Premise of the study: Isometric and allometric scaling of a conserved floral plan could provide a parsimonious mechanism for rapid and reversible transitions between breeding systems. This scaling may occur during transitions between predominant autogamy and xenogamy, contributing to the maintenance of a stable mixed mating system. • Methods: We compared nine disjunct populations of the polytypic, mixed mating species Oenothera flava (Onagraceae) to two parapatric relatives, the obligately xenogamous species O. acutissima and the mixed mating species O. triloba. We compared floral morphology of all taxa using principal component analysis (PCA) and developmental trajectories of floral organs using ANCOVA homogeneity of slopes. • Key results: The PCA revealed both isometric and allometric scaling of a conserved floral plan. Three principal components (PCs) explained 92.5% of the variation in the three species. PC1 predominantly loaded on measures of floral size and accounts for 36% of the variation. PC2 accounted for 35% of the variation, predominantly in traits that influence pollinator handling. PC3 accounted for 22% of the variation, primarily in anther–stigma distance (herkogamy). During O. flava subsp. taraxacoides development, style elongation was accelerated relative to anthers, resulting in positive herkogamy. During O. flava subsp. flava development, style elongation was decelerated, resulting in zero or negative herkogamy. Of the two populations with intermediate morphology, style elongation was accelerated in one population and decelerated in the other. • Conclusions: Isometric and allometric scaling of floral organs in North American Oenothera section Lavauxia drive variation in breeding system. Multiple developmental paths to intermediate phenotypes support the likelihood of multiple mating system transitions.

Grain yield variation and association of major traits in brown-seeded genotypes of tef [Eragrostis tef (Zucc.)Trotter]

Background Tef [Eragrostis tef (Zucc.) Trotter] is the major cereal crop of Ethiopia where it is annually cultivated on more than three million hectares of land by over six million small-scale farmers. It is broadly grouped into white and brown-seeded type depending on grain color, although some intermediate color grains also exist. Earlier breeding experiments focused on white-seeded tef, and a number of improved varieties were released to the farming community. Thirty-six brown-seeded tef genotypes were evaluated using a 6 × 6 simple lattice design at three locations in the central highlands of Ethiopia to assess the productivity, heritability, and association among major pheno-morphic traits. Results The mean square due to genotypes, locations, and genotype by locations were significant (P < 0.01) for all traits studied. Genotypic and phenotypic coefficients of variations ranged from 2.5 to 20.3 % and from 4.3 to 21.7 %, respectively. Grain yield showed significant (P < 0.01) genotypic correlation with shoot biomass and harvest index, while it had highly significant (P < 0.01) phenotypic correlation with all the traits evaluated. Besides, association of lodging index with biomass and grain yield was negative and significant at phenotypic level while it was not significant at genotypic level. Cluster analysis grouped the 36 test genotypes into seven distinct classes. Furthermore, the first three principal components with eigenvalues greater than unity extracted 78.3 % of the total variation. Conclusion The current study, generally, revealed the identification of genotypes with superior grain yield and other desirable traits for further evaluation and eventual release to the farming community.

Mapping Emotion Terms into Affective Space: Further Evidence for a Four-Dimensional Structure

Recent empirical work on the semantics of emotion terms across many different cultures and languages, using a theoretical componential approach, suggested that four dimensions are needed to parsimoniously describe the semantic space of the emotion domain as reflected in emotion terms (Fontaine, Scherer, Roesch, & Ellsworth, 2007; Fontaine, Scherer, & Soriano, 2013). In addition to valence, power, and arousal, a novelty dimension was discovered that mostly differentiated surprise from other emotions. Here, we further explore the existence and nature of the fourth dimension in semantic emotion space using a much larger and much more representative set of emotion terms. A group of 156 participants each rated 10 out of a set of 80 French emotion terms with respect to semantic meaning. The meaning of an emotion term was evaluated with respect to 68 emotion features representing the appraisal, action tendency, bodily reaction, expression, and feeling components of the emotion process. A principal component analysis confirmed the four-dimensional valence, power, arousal, and novelty structure. Moreover, this larger and much more representative set of emotion terms revealed that the novelty dimension not only differentiates surprise terms from other emotion terms, but also identifies substantial variation within the fear and joy emotion families.