24 resultados para Developmental disorders prevention


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Male infertility affects one man in twenty and a genetic basis seems likely in at least 30% of those men. Genetic regulation of fertility involves the inter-related processes of testicular development, spermatogenesis (involving germ cell mitosis, meiosis and spermatid maturation), and their endocrine and paracrine regulation. In regard to spermatogenesis, particular attention has been given to the Yq11 region, where some spermatogenesis genes ('azoospermia factors') appear to be located. Several candidate genes have been identified but have not been shown to have a defined or essential role in spermatogenesis. Microdeletions of Yq11 are found in approximately 15% of azoospermic or severely oligospermic men. The complexity of the genetic control of male fertility is demonstrated by the evidence for genes involved in spermatogenesis and sexual differentiation on the X chromosome and autosomes. Better understanding of the genetic regulation of normal spermatogenesis will provide new probes for clinical studies; however, at present the majority of spermatogenic failure remains without an identified genetic linkage. The advent of intracytoplasmic sperm injection permits fertility in many previously sterile men and presents the possibility of their transmission of infertility; appropriate counselling is required.

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Several studies have reported imitative deficits in autism spectrum disorder (ASD). However, it is still debated if imitative deficits are specific to ASD or shared with clinical groups with similar mental impairment and motor difficulties. We investigated whether imitative tasks can be used to discriminate ASD children from typically developing children (TD) and children with general developmental delay (GDD). We applied discriminant function analyses to the performance of these groups on three imitation tasks and tests of dexterity, motor planning, verbal skills, theory of mind (ToM). Analyses revealed two significant dimensions. The first represented impairment of dexterity and verbal ability, and discriminated TD from GDD children. Once these differences were accounted for, differences in ToM and the three imitation tasks accounted for a significant proportion of the remaining intergroup variance and discriminated the ASD group from other groups. Further analyses revealed that inclusion of imitative tasks increased the specificity and sensitivity of ASD classification and that imitative tasks considered alone were able to reliably discriminate ASD, TD and GDD. The results suggest that imitation and theory of mind impairment in autism may stem from a common domain of origin separate from general cognitive and motor skill.

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The number of children identified as having intellectual or developmental disability is rising worldwide and their education has been found wanting. It has been said that “they simply need better teaching.” At the same time, there is an increasing evidence base that pedagogy that is based on the discipline of behaviour analysis offers the best prospect for individuals diagnosed with autism spectrum disorders. On the basis of this evidence, it is proposed that behaviour analysis should be applied more broadly to improve teaching for all children with intellectual or developmental disability.

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Autism is a neuro-developmental disorder defined by atypical social behaviour, of which atypical social attention behaviours are among the earliest clinical markers (Volkmar et al., 1997). Eye tracking studies using still images and movie clips have provided a method for the precise quantification of atypical social attention in ASD. This is generally characterised by diminished viewing of the most socially pertinent regions (eyes), and increased viewing of less socially informative regions (body, background, objects) (Klin et al., 2002; Riby & Hancock, 2008, 2009). Ecological validity within eye tracking studies has become an increasingly important issue. As of yet, however, little is known about the precise nature of the atypicalities of social attention in ASD in real-life. Objectives: To capture and quantify gaze patterns for children with an ASD within a real life setting, compared to two Typically Developing (TD) comparison groups. Methods: Nine children with an ASD were compared to two age matched TD groups – a verbal (N=9) and a non-verbal (N=9) comparison group. A real-life scenario was created involving an experimenter posing as a magician, and consisted of 3 segments: a conversation segment; a magic trick segment; and a puppet segment. The first segment explored children’s attentional preferences during a real-life conversation; the magic trick segment explored children’s use of the eyes as a communicative cue, and the puppet segment explored attention capture. Finally, part of the puppet section explored children’s use of facial information in response to an unexpected event. Results: The most striking difference between the groups was the diminished viewing of the eyes by the ASD group in comparison to both control groups. This was found particularly during the conversation segment, but also during the magic trick segment, and during the puppet segment. When in conversation, participants with ASD were found to spend a greater proportion time looking off-screen, in comparison to TD participants. There was also a tendency for the ASD group to spend a greater proportion of time looking to the mouth of the experimenter. During the magic trick segment, despite the fact that the eyes were not predictive of a correct location, both TD comparison groups continued to use the eyes as a communicative cue, whereas the ASD group did not. In the puppet segment, all three groups spent a similar amount of time looking between the puppet and regions of the experimenter’s face. However, in response to an unexpected event, the ASD group were significantly slower to fixate back on the experimenter’s face. Conclusions: The results demonstrate the reduced salience of socially pertinent information for children with ASD in real life, and they provide support for the findings from previous eye tracking studies involving scene viewing. However, the results also highlight a pattern looking off-screen for both the TD and ASD groups. This eye movement behaviour is likely to be associated specifically with real-life interaction, as it has functional relevance (Doherty-Sneddon et al., 2002). However, the fact that it is significantly increased in the ASD group has implications for their understanding of real life social interactions.

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Here we use two filtered speech tasks to investigate children’s processing of slow (<4 Hz) versus faster (∼33 Hz) temporal modulations in speech. We compare groups of children with either developmental dyslexia (Experiment 1) or speech and language impairments (SLIs, Experiment 2) to groups of typically-developing (TD) children age-matched to each disorder group. Ten nursery rhymes were filtered so that their modulation frequencies were either low-pass filtered (<4 Hz) or band-pass filtered (22 – 40 Hz). Recognition of the filtered nursery rhymes was tested in a picture recognition multiple choice paradigm. Children with dyslexia aged 10 years showed equivalent recognition overall to TD controls for both the low-pass and band-pass filtered stimuli, but showed significantly impaired acoustic learning during the experiment from low-pass filtered targets. Children with oral SLIs aged 9 years showed significantly poorer recognition of band pass filtered targets compared to their TD controls, and showed comparable acoustic learning effects to TD children during the experiment. The SLI samples were also divided into children with and without phonological difficulties. The children with both SLI and phonological difficulties were impaired in recognizing both kinds of filtered speech. These data are suggestive of impaired temporal sampling of the speech signal at different modulation rates by children with different kinds of developmental language disorder. Both SLI and dyslexic samples showed impaired discrimination of amplitude rise times. Implications of these findings for a temporal sampling framework for understanding developmental language disorders are discussed.