An evaluation of an adaptive learning system based on multimodal affect recognition for learners with intellectual disabilities

Artificial intelligence tools for education (AIEd) have been used to automate the provision of learning support to mainstream learners. One of the most innovative approaches in this field is the use of data and machine learning for the detection of a student's affective state, to move them out of negative states that inhibit learning, into positive states such as engagement. In spite of their obvious potential to provide the personalisation that would give extra support for learners with intellectual disabilities, little work on AIEd systems that utilise affect recognition currently addresses this group. Our system used multimodal sensor data and machine learning to first identify three affective states linked to learning (engagement, frustration, boredom) and second determine the presentation of learning content so that the learner is maintained in an optimal affective state and rate of learning is maximised. To evaluate this adaptive learning system, 67 participants aged between 6 and 18 years acting as their own control took part in a series of sessions using the system. Sessions alternated between using the system with both affect detection and learning achievement to drive the selection of learning content (intervention) and using learning achievement alone (control) to drive the selection of learning content. Lack of boredom was the state with the strongest link to achievement, with both frustration and engagement positively related to achievement. There was significantly more engagement and less boredom in intervention than control sessions, but no significant difference in achievement. These results suggest that engagement does increase when activities are tailored to the personal needs and emotional state of the learner and that the system was promoting affective states that in turn promote learning. However, longer exposure is necessary to determine the effect on learning

Toward homochiral protocells in noncatalytic peptide systems

The activation-polymerization-epimerization-depolymerization (APED) model of Plasson et al. has recently been proposed as a mechanism for the evolution of homochirality on prebiotic Earth. The dynamics of the APED model in two-dimensional spatially-extended systems is investigated for various realistic reaction parameters. It is found that the APED system allows for the formation of isolated homochiral proto-domains surrounded by a racemate. A diffusive slowdown of the APED network such as induced through tidal motion or evaporating pools and lagoons leads to the stabilization of homochiral bounded structures as expected in the first self-assembled protocells.Comment: 10 pages, 5 figure

Habitable Zones in the Universe

Habitability varies dramatically with location and time in the universe. This was recognized centuries ago, but it was only in the last few decades that astronomers began to systematize the study of habitability. The introduction of the concept of the habitable zone was key to progress in this area. The habitable zone concept was first applied to the space around a star, now called the Circumstellar Habitable Zone. Recently, other, vastly broader, habitable zones have been proposed. We review the historical development of the concept of habitable zones and the present state of the research. We also suggest ways to make progress on each of the habitable zones and to unify them into a single concept encompassing the entire universe.Comment: 71 pages, 3 figures, 1 table; to be published in Origins of Life and Evolution of Biospheres; table slightly revise

Structure and evolution of the mouse pregnancy-specific glycoprotein (Psg) gene locus

BACKGROUND: The pregnancy-specific glycoprotein (Psg) genes encode proteins of unknown function, and are members of the carcinoembryonic antigen (Cea) gene family, which is a member of the immunoglobulin gene (Ig) superfamily. In rodents and primates, but not in artiodactyls (even-toed ungulates / hoofed mammals), there have been independent expansions of the Psg gene family, with all members expressed exclusively in placental trophoblast cells. For the mouse Psg genes, we sought to determine the genomic organisation of the locus, the expression profiles of the various family members, and the evolution of exon structure, to attempt to reconstruct the evolutionary history of this locus, and to determine whether expansion of the gene family has been driven by selection for increased gene dosage, or diversification of function. RESULTS: We collated the mouse Psg gene sequences currently in the public genome and expressed-sequence tag (EST) databases and used systematic BLAST searches to generate complete sequences for all known mouse Psg genes. We identified a novel family member, Psg31, which is similar to Psg30 but, uniquely amongst mouse Psg genes, has a duplicated N1 domain. We also identified a novel splice variant of Psg16 (bCEA). We show that Psg24 and Psg30 / Psg31 have independently undergone expansion of N-domain number. By mapping BAC, YAC and cosmid clones we described two clusters of Psg genes, which we linked and oriented using fluorescent in situ hybridisation (FISH). Comparison of our Psg locus map with the public mouse genome database indicates good agreement in overall structure and further elucidates gene order. Expression levels of Psg genes in placentas of different developmental stages revealed dramatic differences in the developmental expression profile of individual family members. CONCLUSION: We have combined existing information, and provide new information concerning the evolution of mouse Psg exon organization, the mouse Psg genomic locus structure, and the expression patterns of individual Psg genes. This information will facilitate functional studies of this complex gene family

Hexose-6-phosphate Dehydrogenase Modulates 11β-Hydroxysteroid Dehydrogenase Type 1-Dependent Metabolism of 7-keto- and 7β-hydroxy-neurosteroids

BACKGROUND: The role of 11beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1) in the regulation of energy metabolism and immune system by locally reactivating glucocorticoids has been extensively studied. Experiments determining initial rates of enzyme activity revealed that 11beta-HSD1 can catalyze both the reductase and the dehydrogenase reaction in cell lysates, whereas it predominantly catalyzes the reduction of cortisone to cortisol in intact cells that also express hexose-6-phosphate dehydrogenase (H6PDH), which provides cofactor NADPH. Besides its role in glucocorticoid metabolism, there is evidence that 11beta-HSD1 is involved in the metabolism of 7-keto- and 7-hydroxy-steroids; however the impact of H6PDH on this alternative function of 11beta-HSD1 has not been assessed. METHODOLOGY: We investigated the 11beta-HSD1-dependent metabolism of the neurosteroids 7-keto-, 7alpha-hydroxy- and 7beta-hydroxy-dehydroepiandrosterone (DHEA) and 7-keto- and 7beta-hydroxy-pregnenolone, respectively, in the absence or presence of H6PDH in intact cells. 3D-structural modeling was applied to study the binding of ligands in 11beta-HSD1. PRINCIPAL FINDINGS: We demonstrated that 11beta-HSD1 functions in a reversible way and efficiently catalyzed the interconversion of these 7-keto- and 7-hydroxy-neurosteroids in intact cells. In the presence of H6PDH, 11beta-HSD1 predominantly converted 7-keto-DHEA and 7-ketopregnenolone into their corresponding 7beta-hydroxy metabolites, indicating a role for H6PDH and 11beta-HSD1 in the local generation of 7beta-hydroxy-neurosteroids. 3D-structural modeling offered an explanation for the preferred formation of 7beta-hydroxy-neurosteroids. CONCLUSIONS: Our results from experiments determining the steady state concentrations of glucocorticoids or 7-oxygenated neurosteroids suggested that the equilibrium between cortisone and cortisol and between 7-keto- and 7-hydroxy-neurosteroids is regulated by 11beta-HSD1 and greatly depends on the coexpression with H6PDH. Thus, the impact of H6PDH on 11beta-HSD1 activity has to be considered for understanding both glucocorticoid and neurosteroid action in different tissues

The phase diagram of NiSi under the conditions of small planetary interiors

The phase diagram of NiSi has been determined using in situ synchrotron X-ray powder diffraction multi-anvil experiments to 19 GPa, with further preliminary results in the laser-heated diamond cell reported to 60 GPa. The low-pressure MnP-structured phase transforms to two different high-pressure phases depending on the temperature: the ε-FeSi structure is stable at temperatures above ∼1100 K and a previously reported distorted-CuTi structure (with Pmmn symmetry) is stable at lower temperature. The invariant point is located at 12.8 ± 0.2 GPa and 1100 ± 20 K. At higher pressures, ε -FeSi-structured NiSi transforms to the CsCl structure with CsCl-NiSi as the liquidus phase above 30 GPa. The Clapeyron slope of this transition is -67 MPa/K. The phase boundary between the ε -FeSi and Pmmn structured phases is nearly pressure independent implying there will be a second sub-solidus invariant point between CsCl, ε -FeSi and Pmmn structures at higher pressure than attained in this study. In addition to these stable phases, the MnP structure was observed to spontaneously transform at room temperature to a new orthorhombic structure (also with Pnma symmetry) which had been detailed in previous ab initio simulations. This new phase of NiSi is shown here to be metastable

A Computational Study of Elongation Factor G (EFG) Duplicated Genes: Diverged Nature Underlying the Innovation on the Same Structural Template

BACKGROUND: Elongation factor G (EFG) is a core translational protein that catalyzes the elongation and recycling phases of translation. A more complex picture of EFG's evolution and function than previously accepted is emerging from analyzes of heterogeneous EFG family members. Whereas the gene duplication is postulated to be a prominent factor creating functional novelty, the striking divergence between EFG paralogs can be interpreted in terms of innovation in gene function. METHODOLOGY/PRINCIPAL FINDINGS: We present a computational study of the EFG protein family to cover the role of gene duplication in the evolution of protein function. Using phylogenetic methods, genome context conservation and insertion/deletion (indel) analysis we demonstrate that the EFG gene copies form four subfamilies: EFG I, spdEFG1, spdEFG2, and EFG II. These ancient gene families differ by their indispensability, degree of divergence and number of indels. We show the distribution of EFG subfamilies and describe evidences for lateral gene transfer and recent duplications. Extended studies of the EFG II subfamily concern its diverged nature. Remarkably, EFG II appears to be a widely distributed and a much-diversified subfamily whose subdivisions correlate with phylum or class borders. The EFG II subfamily specific characteristics are low conservation of the GTPase domain, domains II and III; absence of the trGTPase specific G2 consensus motif "RGITI"; and twelve conserved positions common to the whole subfamily. The EFG II specific functional changes could be related to changes in the properties of nucleotide binding and hydrolysis and strengthened ionic interactions between EFG II and the ribosome, particularly between parts of the decoding site and loop I of domain IV. CONCLUSIONS/SIGNIFICANCE: Our work, for the first time, comprehensively identifies and describes EFG subfamilies and improves our understanding of the function and evolution of EFG duplicated genes

Altering the trajectory of early postnatal cortical development can lead to structural and behavioural features of autism

<p>Abstract</p> <p>Background</p> <p>Autism is a behaviourally defined neurodevelopmental disorder with unknown etiology. Recent studies in autistic children consistently point to neuropathological and functional abnormalities in the temporal association cortex (TeA) and its associated structures. It has been proposed that the trajectory of postnatal development in these regions may undergo accelerated maturational alterations that predominantly affect sensory recognition and social interaction. Indeed, the temporal association regions that are important for sensory recognition and social interaction are one of the last regions to mature suggesting a potential vulnerability to early maturation. However, direct evaluation of the emerging hypothesis that an altered time course of early postnatal development can lead to an ASD phenotype remains lacking.</p> <p>Results</p> <p>We used electrophysiological, histological, and behavioural techniques to investigate if the known neuronal maturational promoter valproate, similar to that in culture systems, can influence the normal developmental trajectory of TeA <it>in vivo</it>. Brain sections obtained from postnatal rat pups treated with VPA <it>in vivo </it>revealed that almost 40% of cortical cells in TeA prematurely exhibited adult-like intrinsic electrophysiological properties and that this was often associated with gross cortical hypertrophy and a reduced predisposition for social play behaviour.</p> <p>Conclusions</p> <p>The co-manifestation of these functional, structural and behavioural features suggests that alteration of the developmental time course in certain high-order cortical networks may play an important role in the neurophysiological basis of autism.</p

Mapping HIV-1 Vaccine Induced T-Cell Responses: Bias towards Less-Conserved Regions and Potential Impact on Vaccine Efficacy in the Step Study

T cell directed HIV vaccines are based upon the induction of CD8+ T cell memory responses that would be effective in inhibiting infection and subsequent replication of an infecting HIV-1 strain, a process that requires a match or near-match between the epitope induced by vaccination and the infecting viral strain. We compared the frequency and specificity of the CTL epitope responses elicited by the replication-defective Ad5 gag/pol/nef vaccine used in the Step trial with the likelihood of encountering those epitopes among recently sequenced Clade B isolates of HIV-1. Among vaccinees with detectable 15-mer peptide pool ELISpot responses, there was a median of four (one Gag, one Nef and two Pol) CD8 epitopes per vaccinee detected by 9-mer peptide ELISpot assay. Importantly, frequency analysis of the mapped epitopes indicated that there was a significant skewing of the T cell response; variable epitopes were detected more frequently than would be expected from an unbiased sampling of the vaccine sequences. Correspondingly, the most highly conserved epitopes in Gag, Pol, and Nef (defined by presence in >80% of sequences currently in the Los Alamos database www.hiv.lanl.gov) were detected at a lower frequency than unbiased sampling, similar to the frequency reported for responses to natural infection, suggesting potential epitope masking of these responses. This may be a generic mechanism used by the virus in both contexts to escape effective T cell immune surveillance. The disappointing results of the Step trial raise the bar for future HIV vaccine candidates. This report highlights the bias towards less-conserved epitopes present in the same vaccine used in the Step trial. Development of vaccine strategies that can elicit a greater breadth of responses, and towards conserved regions of the genome in particular, are critical requirements for effective T-cell based vaccines against HIV-1

GO4genome: A Prokaryotic Phylogeny Based on Genome Organization

Determining the phylogeny of closely related prokaryotes may fail in an analysis of rRNA or a small set of sequences. Whole-genome phylogeny utilizes the maximally available sample space. For a precise determination of genome similarity, two aspects have to be considered when developing an algorithm of whole-genome phylogeny: (1) gene order conservation is a more precise signal than gene content; and (2) when using sequence similarity, failures in identifying orthologues or the in situ replacement of genes via horizontal gene transfer may give misleading results. GO4genome is a new paradigm, which is based on a detailed analysis of gene function and the location of the respective genes. For characterization of genes, the algorithm uses gene ontology enabling a comparison of function independent of evolutionary relationship. After the identification of locally optimal series of gene functions, their length distribution is utilized to compute a phylogenetic distance. The outcome is a classification of genomes based on metabolic capabilities and their organization. Thus, the impact of effects on genome organization that are not covered by methods of molecular phylogeny can be studied. Genomes of strains belonging to Escherichia coli, Shigella, Streptococcus, Methanosarcina, and Yersinia were analyzed. Differences from the findings of classical methods are discussed