Stressful life events are related to more negative interpretations, but not under acute stress

Studies have identified deleterious effects of stress on multiple cognitive processes such as memory and attention. Little is known about the impact of stress on interpretation. We investigated how an induced acute stress and more long-term stress related to life events were associated with interpretations of ambiguous stimuli. Fifty participants answered a questionnaire indexing the number of stressful life events. A median split was used to compare those reporting few or more events. Half of participants performed an arithmetic task that induced acute stress; they were compared to a control group performing a less stressful task. We measured the interpretation of ambiguous visual stimuli, which participants had to judge as “negative” or “positive”. We found a significant interaction between the number of stressful life events and the induced acute stress on the proportion of positive interpretations. In the control group, participants reporting more stressful events produced less positive interpretations than those reporting few events. In the induced stress condition, no significant difference was found. Life events tend to influence interpretation in the absence of an acute stressor, which seems to be more influent in the short term

PhyloCSF: a comparative genomics method to distinguish protein-coding and non-coding regions

As high-throughput transcriptome sequencing provides evidence for novel transcripts in many species, there is a renewed need for accurate methods to classify small genomic regions as protein-coding or non-coding. We present PhyloCSF, a novel comparative genomics method that analyzes a multi-species nucleotide sequence alignment to determine whether it is likely to represent a conserved protein-coding region, based on a formal statistical comparison of phylogenetic codon models. We show that PhyloCSF's classification performance in 12-species _Drosophila_ genome alignments exceeds all other methods we compared in a previous study, and we provide a software implementation for use by the community. We anticipate that this method will be widely applicable as the transcriptomes of many additional species, tissues, and subcellular compartments are sequenced, particularly in the context of ENCODE and modENCODE

Is anxiety associated with negative interpretations of ambiguity in children and adolescents? A systematic review and meta-analysis

Background The tendency to interpret ambiguity as threat (‘negative interpretation’) has been implicated in cognitive models of anxiety. A significant body of research has examined the association between anxiety and negative interpretation, and reviews suggest there is a robust positive association in adults. However, evidence with children and adolescents has been inconsistent. This study aimed to provide a systematic quantitative assessment of the association between anxiety and negative interpretation in children and adolescents. Methods Following systematic searches and screening for eligibility, 345 effects sizes from 77 studies were meta-analysed. Results Overall a medium positive association was found between anxiety and negative interpretation in children and adolescents (d ̂ = 0.62). Two variables significantly moderated this effect. Specifically, the association increased in strength with increasing age and when the content of ambiguous scenarios matched the anxiety subtype under investigation. Conclusions Results extend findings from adult literature by demonstrating an association in children and adolescents with evidence for content specificity in the association. Age effects imply a role for development. Results raise considerations for when and for whom clinical treatments for anxiety focusing on interpretation bias are appropriate. The vast majority of studies included in the review have used correlational designs and there are a limited number of studies with you ng children. The results should be considered with these limitations in mind

Disruption of working memory and contralateral delay activity by nociceptive stimuli is modulated by task demands

Top–down processes allow the selection and prioritization of information by limiting attentional capture by distractors, and these mechanisms depend on task demands such as working memory (WM) load. However, bottom–up processes give salient stimuli a stronger neuronal representation and provoke attentional capture. The aim of this study was to examine the effect of salient nociceptive stimuli on WM while manipulating task demands. Twenty-one healthy participants performed a change detection task during which they had to determine whether 2 successive visual arrays were different or the same. Task demands were modulated by manipulating the WM load (set size included 2 or 4 objects to recall) and by the correspondence between the 2 successive visual arrays (change vs no change). Innocuous stimuli (control) or nociceptive stimuli (distractors) were delivered during the delay period between the 2 visual arrays. Contralateral delay activity and laser-evoked potentials were recorded to examine neural markers of visual WM and nociceptive processes. Nociceptive stimuli decreased WM performance depending on task demands (all P < 0.05). Moreover, compared with control stimuli, nociceptive stimuli abolished the increase in contralateral delay activity amplitude for set size 4 vs set size 2 (P = 0.04). Consistent with these results, laser-evoked potential amplitude was not decreased when task demands were high (P = 0.5). These findings indicate that WM may shield cognition from nociceptive stimuli, but nociceptive stimuli disrupt WM and alter task performance when cognitive resources become insufficient to process all task-relevant information. Corresponding author. Address: Department of Anatomy, Université du Québec à Trois-Rivières, 3351 Blvd des Forges, C.P. 500, Trois-Rivières, QC, Canada G9A 5H7. Tel.: 819-376-5011, Ext.: 3998; fax: 819-376-5204. E-mail address: [email protected] (M. Piché). Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article. Received July 06, 2021 Received in revised form September 22, 2021 Accepted October 08, 2021 © 2022 International Association for the Study of Pai

A Unifying Model of Genome Evolution Under Parsimony

We present a data structure called a history graph that offers a practical basis for the analysis of genome evolution. It conceptually simplifies the study of parsimonious evolutionary histories by representing both substitutions and double cut and join (DCJ) rearrangements in the presence of duplications. The problem of constructing parsimonious history graphs thus subsumes related maximum parsimony problems in the fields of phylogenetic reconstruction and genome rearrangement. We show that tractable functions can be used to define upper and lower bounds on the minimum number of substitutions and DCJ rearrangements needed to explain any history graph. These bounds become tight for a special type of unambiguous history graph called an ancestral variation graph (AVG), which constrains in its combinatorial structure the number of operations required. We finally demonstrate that for a given history graph $G$, a finite set of AVGs describe all parsimonious interpretations of $G$, and this set can be explored with a few sampling moves.Comment: 52 pages, 24 figure

A fast algorithm for the multiple genome rearrangement problem with weighted reversals and transpositions

<p>Abstract</p> <p>Background</p> <p>Due to recent progress in genome sequencing, more and more data for phylogenetic reconstruction based on rearrangement distances between genomes become available. However, this phylogenetic reconstruction is a very challenging task. For the most simple distance measures (the breakpoint distance and the reversal distance), the problem is NP-hard even if one considers only three genomes.</p> <p>Results</p> <p>In this paper, we present a new heuristic algorithm that directly constructs a phylogenetic tree w.r.t. the weighted reversal and transposition distance. Experimental results on previously published datasets show that constructing phylogenetic trees in this way results in better trees than constructing the trees w.r.t. the reversal distance, and recalculating the weight of the trees with the weighted reversal and transposition distance. An implementation of the algorithm can be obtained from the authors.</p> <p>Conclusion</p> <p>The possibility of creating phylogenetic trees directly w.r.t. the weighted reversal and transposition distance results in biologically more realistic scenarios. Our algorithm can solve today's most challenging biological datasets in a reasonable amount of time.</p

The atmospheric parameters and spectral interpolator for the stars of MILES

Context. Empirical libraries of stellar spectra are used for stellar classification and synthesis of stellar populations. MILES is a medium spectral-resolution library in the optical domain covering a wide range of temperatures, surface gravities and metallicities. Aims. We re-determine the atmospheric parameters of these stars in order to improve the homogeneity and accuracy. We build an interpolating function that returns a spectrum as a function of the three atmospheric parameters, and finally, we characterize the precision of the wavelength calibration and stability of the spectral resolution. Methods. We use the ULySS program with the ELODIE library as a reference and compare the results with literature compilations. Results. We obtain precisions of 60 K, 0.13 and 0.05 dex respectively for Teff, log g and [Fe/H] for the FGK stars. For the M stars, the mean errors are 38 K, 0.26 and 0.12 dex, and for the OBA 3.5%, 0.17 and 0.13 dex. We construct an interpolator that we test against the MILES stars themselves. We test it also by measuring the atmospheric parameters of the CFLIB stars with MILES as reference and find it to be more reliable than the ELODIE interpolator for the evolved hot stars, like in particular those of the blue horizontal branch.Comment: A&A accepted, 29 pages, 6 figure

CSMET: Comparative Genomic Motif Detection via Multi-Resolution Phylogenetic Shadowing

Functional turnover of transcription factor binding sites (TFBSs), such as whole-motif loss or gain, are common events during genome evolution. Conventional probabilistic phylogenetic shadowing methods model the evolution of genomes only at nucleotide level, and lack the ability to capture the evolutionary dynamics of functional turnover of aligned sequence entities. As a result, comparative genomic search of non-conserved motifs across evolutionarily related taxa remains a difficult challenge, especially in higher eukaryotes, where the cis-regulatory regions containing motifs can be long and divergent; existing methods rely heavily on specialized pattern-driven heuristic search or sampling algorithms, which can be difficult to generalize and hard to interpret based on phylogenetic principles. We propose a new method: Conditional Shadowing via Multi-resolution Evolutionary Trees, or CSMET, which uses a context-dependent probabilistic graphical model that allows aligned sites from different taxa in a multiple alignment to be modeled by either a background or an appropriate motif phylogeny conditioning on the functional specifications of each taxon. The functional specifications themselves are the output of a phylogeny which models the evolution not of individual nucleotides, but of the overall functionality (e.g., functional retention or loss) of the aligned sequence segments over lineages. Combining this method with a hidden Markov model that autocorrelates evolutionary rates on successive sites in the genome, CSMET offers a principled way to take into consideration lineage-specific evolution of TFBSs during motif detection, and a readily computable analytical form of the posterior distribution of motifs under TFBS turnover. On both simulated and real Drosophila cis-regulatory modules, CSMET outperforms other state-of-the-art comparative genomic motif finders

Prediction of tissue-specific cis-regulatory modules using Bayesian networks and regression trees

<p>Abstract</p> <p>Background</p> <p>In vertebrates, a large part of gene transcriptional regulation is operated by cis-regulatory modules. These modules are believed to be regulating much of the tissue-specificity of gene expression.</p> <p>Results</p> <p>We develop a Bayesian network approach for identifying cis-regulatory modules likely to regulate tissue-specific expression. The network integrates predicted transcription factor binding site information, transcription factor expression data, and target gene expression data. At its core is a regression tree modeling the effect of combinations of transcription factors bound to a module. A new unsupervised EM-like algorithm is developed to learn the parameters of the network, including the regression tree structure.</p> <p>Conclusion</p> <p>Our approach is shown to accurately identify known human liver and erythroid-specific modules. When applied to the prediction of tissue-specific modules in 10 different tissues, the network predicts a number of important transcription factor combinations whose concerted binding is associated to specific expression.</p