bluuebunny/crossref_metadata_2025_split huggingface dataset:
Narrative Assessment for Cantonese-Speaking Children
Authors: Kit-Sum To Carol , Stokes Stephanie F. , Cheung Hin-Tat , T’sou Benjamin 
Published: June 2010

Background
This study examined the narrative skills of Cantonese-speaking school-age children to fill a need for a normative language test for school-age children.

Purpose
To provide a benchmark of the narrative skills of Cantonese-speaking children; to identify which of the microstructure components was the best predictor of age; and to determine the diagnostic accuracy of the test components.

Method and Procedure
Data were collected from 1,120 Cantonese-speaking children between the ages of 4;10 (years;months) and 12;01, using a story-retell of a 24-frame picture series. Four narrative components (syntactic complexity, semantic score, referencing, and connective use) were measured.

Outcomes and Results
Each measure reflected significant age-related differences in narrative ability. Regression analyses revealed that vocabulary and syntactic complexity were the best predictors of grade. All measures showed high sensitivity (86%–94%) but relatively low specificity (60%–90%) and modest likelihood ratio (LR) values: LR+ (2.15–9.42) and LR− (0.07–0.34).

Conclusion and Implications
Narrative assessment can be standardized to be a reliable and valid instrument to assist in the identification of children with language impairment. Syntactic complexity is not only a strong predictor of grade but was also particularly vulnerable in Cantonese-speaking children with specific language impairment. Further diagnostic research using narrative analysis is warranted.
Electrophysiological Indices of Discrimination of Long-Duration, Phonetically Similar Vowels in Children With Typical and Atypical Language Development
Authors: Datta Hia , Shafer Valerie L. , Morr Mara L. , Kurtzberg Diane , Schwartz Richard G. 
Published: June 2010

Purpose
The authors investigated the neurophysiological bases of vowel perception in children with specific language impairment (SLI) compared with typical language development (TLD) controls using 250-ms phonetically similar vowels. In a previous study, children with SLI showed a poor neurophysiological response (the mismatch negativity [MMN]) to 50-ms versions of these vowels, regardless of whether attention was directed to (attend) or away (passive) from the auditory modality (V. Shafer, M. Morr, H. Datta, D. Kurtzberg, & R. Schwartz, 2005). They hypothesized that longer vowels would allow for improved speech perception.

Method
Brain responses were elicited to the vowel contrast in 2 conditions: (a) attend and (b) passive. Behavioral discrimination and identification responses were also examined.

Results
Both SLI and TLD groups showed evidence of discrimination (MMN) of the vowels in the attend and passive conditions. Only subtle differences in the scalp topography of a late negative (LN) brain component were observed between groups. The SLI compared with the TLD group showed significantly poorer identification of these long vowels, as found previously with the shorter vowels.

Conclusions
Increased vowel duration can improve discrimination in children with SLI. However, poor identification of these longer vowels by some children with SLI suggests a deficit in long-term phonological representations or accessing these representations.
Word Learning in Children With Primary Language Impairment: A Meta-Analysis
Authors: Kan Pui Fong , Windsor Jennifer 
Published: June 2010

Purpose
The present study is a meta-analysis that examines the difference in novel word learning performance between children with primary language impairment (LI) and typically developing children. Participant and task characteristics were examined as variables that potentially moderated children’s word learning.

Method
Eight hundred and forty-six published studies were retrieved from conventional databases (PsycINFO, MEDLINE, and Web of Science). Of these studies, 28 met the criteria for inclusion in the meta-analysis, yielding 244 effect sizes across experimental conditions.

Results
LI groups showed significantly lower word learning performance than typical age-matched groups and equivalent performance to typical language–matched groups. Moderator analyses showed that the magnitude of the group difference relative to age peers was significantly associated with participants' chronological age, receptive language and cognitive abilities, task and novel word type, and the extent of novel word exposure.

Conclusion
The difference in novel word learning performance between children with LI and age-matched children is strongly affected by task and participant characteristics in the primary studies.
Neighborhood Density and Word Frequency Predict Vocabulary Size in Toddlers
Authors: Stokes Stephanie F. 
Published: June 2010

Purpose
To document the lexical characteristics of neighborhood density (ND) and word frequency (WF) in the lexicons of a large sample of English-speaking toddlers.

Method

Parents of 222 British-English–speaking children aged 27(±3) months completed a British adaptation of the MacArthur–Bates Communicative Development Inventory: Words and Sentences (MCDI; Klee & Harrison, 2001). Child words were coded for ND and WF, and the relationships among vocabulary, ND, and WF were examined. A cut-point of −1
SD
below the mean on the MCDI classified children into one of two groups: low or high vocabulary size. Group differences on ND and WF were examined using nonparametric statistics.

Results
In a hierarchical regression, ND and WF accounted for 47% and 14% of unique variance in MCDI scores, respectively. Low-vocabulary children scored significantly higher on ND and significantly lower on WF than did high-vocabulary children, but there was more variability in ND and WF for children at the lowest points of the vocabulary continuum.

Conclusion
Children at the lowest points of a continuum of vocabulary size may be extracting statistical properties of the input language in a manner quite different from their more able age peers.
Investigating Mechanisms of Suppression in Preschool Children With Specific Language Impairment
Authors: Spaulding Tammie J. 
Published: June 2010

Purpose
This study investigated 2 suppression mechanisms—(a) resistance to distracter interference and (b) inhibition of a prepotent response—in preschool children with specific language impairment (SLI) and their typically developing peers.

Method
Twenty-two preschool children with SLI and 22 typically developing controls participated in this study. The resistance to distracter interference task involved suppressing distracters (nonverbal auditory, linguistic, and visual) that were external and irrelevant to the task goal. Inhibition was assessed using a stop-signal paradigm to evaluate the ability to suppress a prepotent, conflicting response.

Results
The children with SLI exhibited decreased resistance to distracter interference regardless of distracter modality and poor inhibitory control relative to their typically developing peers.

Conclusion
These results identify suppression weaknesses in preschool-age children with SLI. Specifically, children with this disorder exhibited difficulty suppressing both irrelevant and contradictory information.
Improving the Quality and Applicability of the Dutch Scales of the Communication Profile for the Hearing Impaired Using Item Response Theory
Authors: Mokkink Lidwine B. , Knol Dirk L. , van Nispen Ruth M. A. , Kramer Sophia E. 
Published: June 2010

Purpose
The aim of this study was to improve the quality and applicability of the 6 Dutch scales of the Communication Profile for the Hearing Impaired (CPHI; Demorest & Erdman, 1986, 1987, 1988) using item response theory (IRT). IRT modeling can produce precise, valid, and relatively brief instruments, resulting in minimal response burden (Edelen & Reeve, 2006).

Method
We investigated (a) whether items fit to the graded response model (GRM; Samejima, 1969) using Stone and Zhang’s (2003) procedure to test goodness of fit and (b) whether items showed differential item functioning (DIF) with the IRT log-likelihood ratio approach for 5 group variables: gender, age, living arrangement, use of hearing aids, and degree of hearing impairment. We investigated the magnitude of DIF by calculating the maximum difference between expected item scores for subgroups of the group variables of items showing DIF.

Results
In a cross-sectional study, 408 consecutive individuals with hearing impairment completed the Dutch CPHI scales. Twelve items were deleted because of misfit to GRMs, 14 items showed uniform DIF, and 2 showed nonuniform DIF. Five items showing DIF were deleted due to large magnitude of DIF. The short form of the Dutch CPHI scales contains 35 items.

Conclusions
DIF analyses showed that the short form was relatively free of DIF with respect to the 5 group variables. Hence, there is no need to make adjustments for the calculation of subgroup scores.
Theoretical Form Factor, Attenuation, and Scattering Tabulation for Z=1–92 from E=1–10 eV to E=0.4–1.0 MeV
Authors: Chantler C. T. 
Published: June 2010

Tables for form factors and anomalous dispersion are widely used in the UV, x-ray, and y-ray communities, and have existed for a considerable period of time. Much of the recent theoretical basis for these was contributed by Cromer, Mann, and Liberman while much of the experimental data were synthesized by Henke et al. More recent developments in both areas have led to new and revised tables. These works have employed numerous simplifications compared to detailed relativistic S-matrix calculations; the latter do not lend themselves to convenient tabular application for the range of Z and energy of general interest. Conversely, the former tables appear to have large regions of limited validity throughout the range of Z and energies, and in particular have important limitations with regard to extrapolation to energies outside tabulated ranges. In the present study, the primary interactions of x-rays with isolated atoms from Z=1 (hydrogen) to Z=92 (uranium) are described and computed within a self-consistent Dirac–Hartree–Fock framework. This has general application across the range of energy from 1–10 eV to 400–1000 keV, with limitations (described below) as the low- and high-energy extremes are approached.
Tabulations are provided for the f1 and f2 components of the form factors, together with the photoelectric attenuation coefficient for the atom, μ, and the value for the K-shell, μK, as functions of energy and wavelength. Also provided are estimated correction factors as described in the text, conversion factors, and a simple estimate for the sum of the scattering contributions (from an isolated atom). The method used herein is primarily theoretical and considers intermediate assumptions which limit the precision and applicability of previous theoretical tabulations. Particular concern involves the application of the dispersion relation to derive Re(f) from photoelectric absorption cross-sections. The revised formulation presented here explicitly avoids most of the limitations of previous works. Revised formulae can lead to significant qualitative and quantitative improvement, particularly above 30–60 keV energies, near absorption edges, and at 0.03 keV to 3 keV energies. Recent experimental syntheses are often complementary to this approach. Examples are given where the revised theoretical tables are in better agreement with experiment than are those based on experimental syntheses.
Use of allostery to identify inhibitors of calmodulin-induced activation of
Bacillus anthracis
edema factor
Authors: Laine Elodie , Goncalves Christophe , Karst Johanna C. , Lesnard Aurélien , Rault Sylvain , Tang Wei-Jen , Malliavin Thérèse E. , Ladant Daniel , Blondel Arnaud 
Published: June 2010

Allostery plays a key role in the regulation of the activity and function of many biomolecules. And although many ligands act through allostery, no systematic use is made of it in drug design strategies. Here we describe a procedure for identifying the regions of a protein that can be used to control its activity through allostery. This procedure is based on the construction of a plausible conformational path, which describes protein transition between known active and inactive conformations. The path is calculated by using a framework approach that steers and markedly improves the conjugate peak refinement method. The evolution of conformations along this path was used to identify a putative allosteric site that could regulate activation of
Bacillus anthracis
adenylyl cyclase toxin (EF) by calmodulin. Conformations of the allosteric site at different steps along the path from the inactive (free) to the active (bound to calmodulin) forms of EF were used to perform virtual screenings and propose candidate EF inhibitors. Several candidates then proved to inhibit calmodulin-induced activation in an in vitro assay. The most potent compound fully inhibited EF at a concentration of 10 μM. The compounds also inhibited the related adenylyl cyclase toxin from
Bordetella pertussis
(CyaA). The specific homology between the putative allosteric sites in both toxins supports that these pockets are the actual binding sites of the selected inhibitors.
Motivating the emergence of new markers of sentential negation
Authors: Willis David 
Published: June 2010

This article investigates the historical emergence of postverbal negation in Welsh. Welsh undergoes a shift from preverbal negation (Middle Welsh ny(t)) to postverbal negation (Present-day Welsh ddim “not” < Middle Welsh dim “at all” < dim “thing, anything”) (Jespersen’s Cycle). In Middle Welsh, ddim occupies a late clausal position, but it later undergoes a syntactic reanalysis which moves	it to an earlier immediately post-subject position. It also shifts in status from a weak negative polarity item, appearing in interrogative, conditional and negative clauses, to a purely negative particle. The article argues that, when ddim begins to occupy an earlier clausal position around 1600, it becomes phonologically less salient, and subsequently loses its emphatic sense in the seventeenth and eighteenth centuries. Finally, the article considers the loss of the preverbal negative marker ni(d) in spoken Welsh, and whether this can best be understood as a push chain (ddim makes ni(d) unnecessary) or as a pull chain (ni(d) is phonologically weak and needs reinforcing by ddim). It concludes that push-chain explanations are most probable for the earlier part of the development up to 1750, with pull-chain explanations being more convincing thereafter.
Using semantic web rules to reason on an ontology of pseudogenes
Authors: Holford Matthew E. , Khurana Ekta , Cheung Kei-Hoi , Gerstein Mark 
Published: June 2010

Abstract
Motivation: Recent years have seen the development of a wide range of biomedical ontologies. Notable among these is Sequence Ontology (SO) which offers a rich hierarchy of terms and relationships that can be used to annotate genomic data. Well-designed formal ontologies allow data to be reasoned upon in a consistent and logically sound way and can lead to the discovery of new relationships. The Semantic Web Rules Language (SWRL) augments the capabilities of a reasoner by allowing the creation of conditional rules. To date, however, formal reasoning, especially the use of SWRL rules, has not been widely used in biomedicine.
Results: We have built a knowledge base of human pseudogenes, extending the existing SO framework to incorporate additional attributes. In particular, we have defined the relationships between pseudogenes and segmental duplications. We then created a series of logical rules using SWRL to answer research questions and to annotate our pseudogenes appropriately. Finally, we were left with a knowledge base which could be queried to discover information about human pseudogene evolution.
Availability: The fully populated knowledge base described in this document is available for download from http://ontology.pseudogene.org. A SPARQL endpoint from which to query the dataset is also available at this location.
Contact: matthew.holford@yale.edu; mark.gerstein@yale.edu
A dynamic Bayesian network for identifying protein-binding footprints from single molecule-based sequencing data
Authors: Chen Xiaoyu , Hoffman Michael M. , Bilmes Jeff A. , Hesselberth Jay R. , Noble William S. 
Published: June 2010

Abstract
Motivation: A global map of transcription factor binding sites (TFBSs) is critical to understanding gene regulation and genome function. DNaseI digestion of chromatin coupled with massively parallel sequencing (digital genomic footprinting) enables the identification of protein-binding footprints with high resolution on a genome-wide scale. However, accurately inferring the locations of these footprints remains a challenging computational problem.
Results: We present a dynamic Bayesian network-based approach for the identification and assignment of statistical confidence estimates to protein-binding footprints from digital genomic footprinting data. The method, DBFP, allows footprints to be identified in a probabilistic framework and outperforms our previously described algorithm in terms of precision at a fixed recall. Applied to a digital footprinting data set from Saccharomyces cerevisiae, DBFP identifies 4679 statistically significant footprints within intergenic regions. These footprints are mainly located near transcription start sites and are strongly enriched for known TFBSs. Footprints containing no known motif are preferentially located proximal to other footprints, consistent with cooperative binding of these footprints. DBFP also identifies a set of statistically significant footprints in the yeast coding regions. Many of these footprints coincide with the boundaries of antisense transcripts, and the most significant footprints are enriched for binding sites of the chromatin-associated factors Abf1 and Rap1.
Contact: jay.hesselberth@ucdenver.edu; william-noble@u.washington.edu
Supplementary information: Supplementary material is available at Bioinformatics online.
Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework
Authors: Yamanishi Yoshihiro , Kotera Masaaki , Kanehisa Minoru , Goto Susumu 
Published: June 2010

Abstract
Motivation: In silico prediction of drug–target interactions from heterogeneous biological data is critical in the search for drugs and therapeutic targets for known diseases such as cancers. There is therefore a strong incentive to develop new methods capable of detecting these potential drug–target interactions efficiently.
Results: In this article, we investigate the relationship between the chemical space, the pharmacological space and the topology of drug–target interaction networks, and show that drug–target interactions are more correlated with pharmacological effect similarity than with chemical structure similarity. We then develop a new method to predict unknown drug–target interactions from chemical, genomic and pharmacological data on a large scale. The proposed method consists of two steps: (i) prediction of pharmacological effects from chemical structures of given compounds and (ii) inference of unknown drug–target interactions based on the pharmacological effect similarity in the framework of supervised bipartite graph inference. The originality of the proposed method lies in the prediction of potential pharmacological similarity for any drug candidate compounds and in the integration of chemical, genomic and pharmacological data in a unified framework. In the results, we make predictions for four classes of important drug–target interactions involving enzymes, ion channels, GPCRs and nuclear receptors. Our comprehensively predicted drug–target interaction networks enable us to suggest many potential drug–target interactions and to increase research productivity toward genomic drug discovery.
Supplementary information: Datasets and all prediction results are available at http://cbio.ensmp.fr/~yyamanishi/pharmaco/.
Availability: Softwares are available upon request.
Contact: yoshihiro.yamanishi@ensmp.fr
A soft kinetic data structure for lesion border detection
Authors: Kockara Sinan , Mete Mutlu , Yip Vincent , Lee Brendan , Aydin Kemal 
Published: June 2010

Abstract
Motivation: The medical imaging and image processing techniques, ranging from microscopic to macroscopic, has become one of the main components of diagnostic procedures to assist dermatologists in their medical decision-making processes. Computer-aided segmentation and border detection on dermoscopic images is one of the core components of diagnostic procedures and therapeutic interventions for skin cancer. Automated assessment tools for dermoscopic images have become an important research field mainly because of inter- and intra-observer variations in human interpretations. In this study, a novel approach—graph spanner—for automatic border detection in dermoscopic images is proposed. In this approach, a proximity graph representation of dermoscopic images in order to detect regions and borders in skin lesion is presented.
Results: Graph spanner approach is examined on a set of 100 dermoscopic images whose manually drawn borders by a dermatologist are used as the ground truth. Error rates, false positives and false negatives along with true positives and true negatives are quantified by digitally comparing results with manually determined borders from a dermatologist. The results show that the highest precision and recall rates obtained to determine lesion boundaries are 100%. However, accuracy of assessment averages out at 97.72% and borders errors' mean is 2.28% for whole dataset.
Contact: skockara@uca.edu
Complex event extraction at PubMed scale
Authors: Björne Jari , Ginter Filip , Pyysalo Sampo , Tsujii Jun'ichi , Salakoski Tapio 
Published: June 2010

Abstract
Motivation: There has recently been a notable shift in biomedical information extraction (IE) from relation models toward the more expressive event model, facilitated by the maturation of basic tools for biomedical text analysis and the availability of manually annotated resources. The event model allows detailed representation of complex natural language statements and can support a number of advanced text mining applications ranging from semantic search to pathway extraction. A recent collaborative evaluation demonstrated the potential of event extraction systems, yet there have so far been no studies of the generalization ability of the systems nor the feasibility of large-scale extraction.
Results: This study considers event-based IE at PubMed scale. We introduce a system combining publicly available, state-of-the-art methods for domain parsing, named entity recognition and event extraction, and test the system on a representative 1% sample of all PubMed citations. We present the first evaluation of the generalization performance of event extraction systems to this scale and show that despite its computational complexity, event extraction from the entire PubMed is feasible. We further illustrate the value of the extraction approach through a number of analyses of the extracted information.
Availability: The event detection system and extracted data are open source licensed and available at http://bionlp.utu.fi/.
Contact: jari.bjorne@utu.fi