3 resultados para Specific language impairment

em WestminsterResearch - UK


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BACKGROUND: We report on a young female, who presents with a severe speech and language disorder and a balanced de novo complex chromosomal rearrangement, likely to have resulted from a chromosome 7 pericentromeric inversion, followed by a chromosome 7 and 11 translocation. RESULTS: Using molecular cytogenetics, we mapped the four breakpoints to 7p21.1-15.3 (chromosome position: 20,954,043-21,001,537, hg19), 7q31 (chromosome position: 114,528,369-114,556,605, hg19), 7q21.3 (chromosome position: 93,884,065-93,933,453, hg19) and 11p12 (chromosome position: 38,601,145-38,621,572, hg19). These regions contain only non-coding transcripts (ENSG00000232790 on 7p21.1 and TCONS_00013886, TCONS_00013887, TCONS_00014353, TCONS_00013888 on 7q21) indicating that no coding sequences are directly disrupted. The breakpoint on 7q31 mapped 200 kb downstream of FOXP2, a well-known language gene. No splice site or non-synonymous coding variants were found in the FOXP2 coding sequence. We were unable to detect any changes in the expression level of FOXP2 in fibroblast cells derived from the proband, although this may be the result of the low expression level of FOXP2 in these cells. CONCLUSIONS: We conclude that the phenotype observed in this patient either arises from a subtle change in FOXP2 regulation due to the disruption of a downstream element controlling its expression, or from the direct disruption of non-coding RNAs.

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The advantages a DSL and the benefits its use potentially brings imply that informed decisions on the design of a domain specific language are of paramount importance for its use. We believe that the foundations of such decisions should be informed by analysis of data empirically collected from systems to highlight salient features that should then form the basis of a DSL. To support this theory, we describe an empirical study of a large OSS called Barcode, written in C, and from which we collected two well-known 'slice' based metrics. We analyzed multiple versions of the system and sliced its functions in three separate ways (i.e., input, output and global variables). The purpose of the study was to try and identify sensitivities and traits in those metrics that might inform features of a potential slice-based DSL. Results indicated that cohesion was adversely affected through the use of global variables and that appreciation of the role of function inputs and outputs can be revealed through slicing. The study presented is motivated primarily by the problems with current tools and interfaces experienced directly by the authors in extracting slicing data and the need to promote the benefits that analysis of slice data and slicing in general can offer.

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Goldin-Meadow (2015) presents an exceptional synthesis of work from studies of children acquiring language under variable circumstances of input or processing abilities. Deaf children who acquire homesign without any well- formed model from which to learn language represent a powerful example. Goldin-Meadow argues that the resilient properties of language that nevertheless emerge include simple syntactic structures, hierarchical organisa- tion, markers modulating the meaning of sentences, and social-communicative functions. Among the fragile or input-dependent properties are the orders that the language follows, the parts into which words are decomposed, and the features that distinguish nominals from predicates. Separation of these two types of properties poses questions concerning the innate constraints on language acquisition (perhaps these equate to the resilient properties) and con‐ cerning the specificity of processes to language (e.g., whether properties such as hierarchical organisation are specific to language or originate in the structure of thought). The study of the resilient properties of human language in the face of adversity and the relation of these properties to the information that is encoded in the human genome represent a research strategy that draws inferences about species universals (properties that all humans share) from data about individual differences (IDs; factors that make humans different from one another). In the following, we suggest three reasons to be cautious about this approach.