A comprehensive multilevel model meta-analysis of self-concept interventions

The efficacy of self-concept interventions has previously been examined through traditional meta-analytic methods, and a host of moderators of intervention outcomes have been identified (O’Mara, Marsh, & Craven, 2004; Haney & Durlak, 1998; Hattie, 1992). However, traditional meta-analytic models have increasingly been criticized because they fail to account for the nested structure of effect sizes within studies, thereby violating statistical assumptions of independence. The multilevel model approach to meta-analysis takes into account the hierarchical structure of meta-analytic data, thus providing findings that are more statistically sound. Consequently, the present study applies the multilevel model technique to the analysis of the self-concept intervention literature. The overall mean effect size of .47 suggests a moderate impact of interventions on self-concept at post-test, and analyses show that intervention effects are maintained at follow-up. Other moderators examined include the construct validity approach to the multidimensionality of self-concept; the focus of the intervention on self-concept; the use of random assignment to treatment and control groups; the control group type; treatment type; and the treatment administrator. Intraclass correlations and the variance explained by each moderator model are presented to emphasise the importance of using a multilevel model approach to meta-analytic research. It is concluded that multilevel models provide a more accurate understanding of the self-concept intervention literature than traditional meta-analytic models. Suggestions for future self-concept intervention design and evaluation are provided

Unmasking the true effects of self-concept interventions and suggested guidelines for rectification

Over recent decades, traditional literature reviews have intimated that self-concept interventions have produced inconsistent or disappointing results (e.g., Marsh & Craven, 1997). It is put forth here that existing research practices, ranging from insufficient theoretical grounding to the use of inappropriate evaluation measures, have generally undermined the effectiveness of self-concept interventions to date. A brief rationale for the necessity of self-concept interventions for children and adolescents will be provided, followed by a review of self-concept enhancement research. This review will focus on the theoretical and methodological weaknesses that have typically resulted in an underestimation of the true effects of such interventions, as revealed by sophisticated meta-analytic techniques. A particular emphasis will be placed on the need for multidimensional approaches to intervention design and evaluation. Following from this, suggestions for improving self-concept intervention research will be posited, with the aim of increasing the consistency and effectiveness of such interventions, and thus unmasking the true effects of such interventions

Identification of a novel type of spacer element required for imprinting in fission yeast

Asymmetrical segregation of differentiated sister chromatids is thought to be important for cellular differentiation in higher eukaryotes. Similarly, in fission yeast, cellular differentiation involves the asymmetrical segregation of a chromosomal imprint. This imprint has been shown to consist of two ribonucleotides that are incorporated into the DNA during laggingstrand synthesis in response to a replication pause, but the underlying mechanism remains unknown. Here we present key novel discoveries important for unravelling this process. Our data show that cis-acting sequences within the mat1 cassette mediate pausing of replication forks at the proximity of the imprinting site, and the results suggest that this pause dictates specific priming at the position of imprinting in a sequence-independent manner. Also, we identify a novel type of cis-acting spacer region important for the imprinting process that affects where subsequent primers are put down after the replication fork is released from the pause. Thus, our data suggest that the imprint is formed by ligation of a not-fullyprocessed Okazaki fragment to the subsequent fragment. The presented work addresses how differentiated sister chromatids are established during DNA replication through the involvement of replication barriers

A specialized learner for inferring structured cis-regulatory modules

BACKGROUND: The process of transcription is controlled by systems of transcription factors, which bind to specific patterns of binding sites in the transcriptional control regions of genes, called cis-regulatory modules (CRMs). We present an expressive and easily comprehensible CRM representation which is capable of capturing several aspects of a CRM's structure and distinguishing between DNA sequences which do or do not contain it. We also present a learning algorithm tailored for this domain, and a novel method to avoid overfitting by controlling the expressivity of the model. RESULTS: We are able to find statistically significant CRMs more often then a current state-of-the-art approach on the same data sets. We also show experimentally that each aspect of our expressive CRM model space makes a positive contribution to the learned models on yeast and fly data. CONCLUSION: Structural aspects are an important part of CRMs, both in terms of interpreting them biologically and learning them accurately. Source code for our algorithm is available at

International Veterinary Epilepsy Task Force recommendations for a veterinary epilepsy-specific MRI protocol

Epilepsy is one of the most common chronic neurological diseases in veterinary practice. Magnetic resonance imaging (MRI) is regarded as an important diagnostic test to reach the diagnosis of idiopathic epilepsy. However, given that the diagnosis requires the exclusion of other differentials for seizures, the parameters for MRI examination should allow the detection of subtle lesions which may not be obvious with existing techniques. In addition, there are several differentials for idiopathic epilepsy in humans, for example some focal cortical dysplasias, which may only apparent with special sequences, imaging planes and/or particular techniques used in performing the MRI scan. As a result, there is a need to standardize MRI examination in veterinary patients with techniques that reliably diagnose subtle lesions, identify post-seizure changes, and which will allow for future identification of underlying causes of seizures not yet apparent in the veterinary literature. There is a need for a standardized veterinary epilepsy-specific MRI protocol which will facilitate more detailed examination of areas susceptible to generating and perpetuating seizures, is cost efficient, simple to perform and can be adapted for both low and high field scanners. Standardisation of imaging will improve clinical communication and uniformity of case definition between research studies. A 6–7 sequence epilepsy-specific MRI protocol for veterinary patients is proposed and further advanced MR and functional imaging is reviewed

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Depleting Components of the THO Complex Causes Increased Telomere Length by Reducing the Expression of the Telomere-Associated Protein Rif1p

Telomere length is regulated mostly by proteins directly associated with telomeres. However, genome-wide analysis of Saccharomyces cerevisiae mutants has revealed that deletion of Hpr1p, a component of the THO complex, also affects telomere length. The THO complex comprises four protein subunits, namely, Tho2p, Hpr1p, Mft1p, and Thp2p. These subunits interplay between transcription elongation and co-transcriptional assembly of export-competent mRNPs. Here we found that the deletion of tho2 or hpr1 caused telomere lengthening by ∼50–100 bps, whereas that of mft1 or thp2 did not affect telomere length. Since the THO complex functions in transcription elongation, we analyzed the expression of telomere-associated proteins in mutants depleted of complex components. We found that both the mRNA and protein levels of RIF1 were decreased in tho2 and hpr1 cells. RIF1 encodes a 1917-amino acid polypeptide that is involved in regulating telomere length and the formation of telomeric heterochromatin. Hpr1p and Tho2p appeared to affect telomeres through Rif1p, as increased Rif1p levels suppressed the telomere lengthening in tho2 and hpr1 cells. Moreover, yeast cells carrying rif1 tho2 or rif1 hpr1 double mutations showed telomere lengths and telomere silencing effects similar to those observed in the rif1 mutant. Thus, we conclude that mutations of components of the THO complex affect telomere functions by reducing the expression of a telomere-associated protein, Rif1p

Predicting protein linkages in bacteria: Which method is best depends on task

<p>Abstract</p> <p>Background</p> <p>Applications of computational methods for predicting protein functional linkages are increasing. In recent years, several bacteria-specific methods for predicting linkages have been developed. The four major genomic context methods are: Gene cluster, Gene neighbor, Rosetta Stone, and Phylogenetic profiles. These methods have been shown to be powerful tools and this paper provides guidelines for when each method is appropriate by exploring different features of each method and potential improvements offered by their combination. We also review many previous treatments of these prediction methods, use the latest available annotations, and offer a number of new observations.</p> <p>Results</p> <p>Using <it>Escherichia coli </it>K12 and <it>Bacillus subtilis</it>, linkage predictions made by each of these methods were evaluated against three benchmarks: functional categories defined by COG and KEGG, known pathways listed in EcoCyc, and known operons listed in RegulonDB. Each evaluated method had strengths and weaknesses, with no one method dominating all aspects of predictive ability studied. For functional categories, as previous studies have shown, the Rosetta Stone method was individually best at detecting linkages and predicting functions among proteins with shared KEGG categories while the Phylogenetic profile method was best for linkage detection and function prediction among proteins with common COG functions. Differences in performance under COG versus KEGG may be attributable to the presence of paralogs. Better function prediction was observed when using a weighted combination of linkages based on reliability versus using a simple unweighted union of the linkage sets. For pathway reconstruction, 99 complete metabolic pathways in <it>E. coli </it>K12 (out of the 209 known, non-trivial pathways) and 193 pathways with 50% of their proteins were covered by linkages from at least one method. Gene neighbor was most effective individually on pathway reconstruction, with 48 complete pathways reconstructed. For operon prediction, Gene cluster predicted completely 59% of the known operons in <it>E. coli </it>K12 and 88% (333/418)in <it>B. subtilis</it>. Comparing two versions of the <it>E. coli </it>K12 operon database, many of the unannotated predictions in the earlier version were updated to true predictions in the later version. Using only linkages found by both Gene Cluster and Gene Neighbor improved the precision of operon predictions. Additionally, as previous studies have shown, combining features based on intergenic region and protein function improved the specificity of operon prediction.</p> <p>Conclusion</p> <p>A common problem for computational methods is the generation of a large number of false positives that might be caused by an incomplete source of validation. By comparing two versions of a database, we demonstrated the dramatic differences on reported results. We used several benchmarks on which we have shown the comparative effectiveness of each prediction method, as well as provided guidelines as to which method is most appropriate for a given prediction task.</p

Biology of human hair: Know your hair to control it

Hair can be engineered at different levels—its structure and surface—through modification of its constituent molecules, in particular proteins, but also the hair follicle (HF) can be genetically altered, in particular with the advent of siRNA-based applications. General aspects of hair biology are reviewed, as well as the most recent contributions to understanding hair pigmentation and the regulation of hair development. Focus will also be placed on the techniques developed specifically for delivering compounds of varying chemical nature to the HF, indicating methods for genetic/biochemical modulation of HF components for the treatment of hair diseases. Finally, hair fiber structure and chemical characteristics will be discussed as targets for keratin surface functionalization