A Comparison of Service Delivery Models: Effects on Curricular Vocabulary Skills in the School Setting

The present study evaluated the effectiveness of three service delivery models in the elementary school setting. Differences were investigated between (a) a collaborative approach, (b) a classroom-based intervention model with the speech-language pathologist (SLP) and classroom teachers working independently, and (c) a traditional pull-out model for children in kindergarten through third grade who qualified for speech or language services. The same curricular vocabulary targets and materials were used in all conditions. This study also examined the vocabulary skills of regular education children who participated in the collaborative approach, the independent classroom-based model, or received instruction from only classroom teachers, without the SLP’s involvement. Results indicated the collaborative model was more effective for teaching curricular vocabulary to students who qualified for speech or language services than a classroom-based model (teacher-SLP independent) or a traditional pull-out model. The findings for students who were not enrolled in speech or language services indicated the collaborative and classroom-based models increased vocabulary skills to a significantly greater degree than receiving only regular instruction from the classroom teacher. The results are congruent with the theoretical advantages of the collaborative model reported in the literature and support the use of integrated service delivery models for intervention in the school setting

Predictive validity of the UK clinical aptitude test in the final years of medical school:a prospective cohort study

Peer reviewedPublisher PD

Neural Representations of Airflow in Drosophila Mushroom Body

The Drosophila mushroom body (MB) is a higher olfactory center where olfactory and other sensory information are thought to be associated. However, how MB neurons of Drosophila respond to sensory stimuli other than odor is not known. Here, we characterized the responses of MB neurons to a change in airflow, a stimulus associated with odor perception. In vivo calcium imaging from MB neurons revealed surprisingly strong and dynamic responses to an airflow stimulus. This response was dependent on the movement of the 3rd antennal segment, suggesting that Johnston's organ may be detecting the airflow. The calyx, the input region of the MB, responded homogeneously to airflow on. However, in the output lobes of the MB, different types of MB neurons responded with different patterns of activity to airflow on and off. Furthermore, detailed spatial analysis of the responses revealed that even within a lobe that is composed of a single type of MB neuron, there are subdivisions that respond differently to airflow on and off. These subdivisions within a single lobe were organized in a stereotypic manner across flies. For the first time, we show that changes in airflow affect MB neurons significantly and these effects are spatially organized into divisions smaller than previously defined MB neuron types

Novel App knock-in mouse model shows key features of amyloid pathology and reveals profound metabolic dysregulation of microglia.

BACKGROUND: Genetic mutations underlying familial Alzheimer\u27s disease (AD) were identified decades ago, but the field is still in search of transformative therapies for patients. While mouse models based on overexpression of mutated transgenes have yielded key insights in mechanisms of disease, those models are subject to artifacts, including random genetic integration of the transgene, ectopic expression and non-physiological protein levels. The genetic engineering of novel mouse models using knock-in approaches addresses some of those limitations. With mounting evidence of the role played by microglia in AD, high-dimensional approaches to phenotype microglia in those models are critical to refine our understanding of the immune response in the brain. METHODS: We engineered a novel App knock-in mouse model (App RESULTS: Leveraging multi-omics approaches, we discovered profound alteration of diverse lipids and metabolites as well as an exacerbated disease-associated transcriptomic response in microglia with high intracellular Aβ content. The App DISCUSSION: Our findings demonstrate that fibrillar Aβ in microglia is associated with lipid dyshomeostasis consistent with lysosomal dysfunction and foam cell phenotypes as well as profound immuno-metabolic perturbations, opening new avenues to further investigate metabolic pathways at play in microglia responding to AD-relevant pathogenesis. The in-depth characterization of pathological hallmarks of AD in this novel and open-access mouse model should serve as a resource for the scientific community to investigate disease-relevant biology

New Horizons in the use of routine data for ageing research

The past three decades have seen a steady increase in the availability of routinely collected health and social care data and the processing power to analyse it. These developments represent a major opportunity for ageing research, especially with the integration of different datasets across traditional boundaries of health and social care, for prognostic research and novel evaluations of interventions with representative populations of older people. However, there are considerable challenges in using routine data at the level of coding, data analysis and in the application of findings to everyday care. New Horizons in applying routine data to investigate novel questions in ageing research require a collaborative approach between clinicians, data scientists, biostatisticians, epidemiologists and trial methodologists. This requires building capacity for the next generation of research leaders in this important area. There is a need to develop consensus code lists and standardised, validated algorithms for common conditions and outcomes that are relevant for older people to maximise the potential of routine data research in this group. Lastly, we must help drive the application of routine data to improve the care of older people, through the development of novel methods for evaluation of interventions using routine data infrastructure. We believe that harnessing routine data can help address knowledge gaps for older people living with multiple conditions and frailty, and design interventions and pathways of care to address the complex health issues we face in caring for older people