84 research outputs found

    RNA-seq based transcriptomic map reveals new insights into mouse salivary gland development and maturation

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    Heatmap depicting the hierarchical clustering of the 45 genes that are conserved between the mouse adult salivary gland gene signature and the RNA-seq data obtained from the Human Protein Atlas. The values reported represent Z-scores of the conserved genes in their respective datasets. (PDF 737 kb

    A global analysis of the complex landscape of isoforms and regulatory networks of p63 in human cells and tissues

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    Expression database. Column A contains the names of the 1099 TFs in humans. Columns B–BC provide the expression of the TFs in FPKM (fragments per kilobase of transcript per million), as calculated by Analysis Pipeline 1, across the 40 cell-types (52 experiments). (CSV 553 kb

    Computational Models of Timing Mechanisms in the Cerebellar Granular Layer

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    A long-standing question in neuroscience is how the brain controls movement that requires precisely timed muscle activations. Studies using Pavlovian delay eyeblink conditioning provide good insight into this question. In delay eyeblink conditioning, which is believed to involve the cerebellum, a subject learns an interstimulus interval (ISI) between the onsets of a conditioned stimulus (CS) such as a tone and an unconditioned stimulus such as an airpuff to the eye. After a conditioning phase, the subject’s eyes automatically close or blink when the ISI time has passed after CS onset. This timing information is thought to be represented in some way in the cerebellum. Several computational models of the cerebellum have been proposed to explain the mechanisms of time representation, and they commonly point to the granular layer network. This article will review these computational models and discuss the possible computational power of the cerebellum

    A Computational Mechanism for Unified Gain and Timing Control in the Cerebellum

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    Precise gain and timing control is the goal of cerebellar motor learning. Because the basic neural circuitry of the cerebellum is homogeneous throughout the cerebellar cortex, a single computational mechanism may be used for simultaneous gain and timing control. Although many computational models of the cerebellum have been proposed for either gain or timing control, few models have aimed to unify them. In this paper, we hypothesize that gain and timing control can be unified by learning of the complete waveform of the desired movement profile instructed by climbing fiber signals. To justify our hypothesis, we adopted a large-scale spiking network model of the cerebellum, which was originally developed for cerebellar timing mechanisms to explain the experimental data of Pavlovian delay eyeblink conditioning, to the gain adaptation of optokinetic response (OKR) eye movements. By conducting large-scale computer simulations, we could reproduce some features of OKR adaptation, such as the learning-related change of simple spike firing of model Purkinje cells and vestibular nuclear neurons, simulated gain increase, and frequency-dependent gain increase. These results suggest that the cerebellum may use a single computational mechanism to control gain and timing simultaneously

    MORFEO enters final design phase

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    MORFEO (Multi-conjugate adaptive Optics Relay For ELT Observations, formerly MAORY), the MCAO system for the ELT, will provide diffraction-limited optical quality to the large field camera MICADO. MORFEO has officially passed the Preliminary Design Review and it is entering the final design phase. We present the current status of the project, with a focus on the adaptive optics system aspects and expected milestones during the next project phase

    Increasing frailty is associated with higher prevalence and reduced recognition of delirium in older hospitalised inpatients: results of a multi-centre study

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    Purpose: Delirium is a neuropsychiatric disorder delineated by an acute change in cognition, attention, and consciousness. It is common, particularly in older adults, but poorly recognised. Frailty is the accumulation of deficits conferring an increased risk of adverse outcomes. We set out to determine how severity of frailty, as measured using the CFS, affected delirium rates, and recognition in hospitalised older people in the United Kingdom. Methods: Adults over 65 years were included in an observational multi-centre audit across UK hospitals, two prospective rounds, and one retrospective note review. Clinical Frailty Scale (CFS), delirium status, and 30-day outcomes were recorded. Results: The overall prevalence of delirium was 16.3% (483). Patients with delirium were more frail than patients without delirium (median CFS 6 vs 4). The risk of delirium was greater with increasing frailty [OR 2.9 (1.8–4.6) in CFS 4 vs 1–3; OR 12.4 (6.2–24.5) in CFS 8 vs 1–3]. Higher CFS was associated with reduced recognition of delirium (OR of 0.7 (0.3–1.9) in CFS 4 compared to 0.2 (0.1–0.7) in CFS 8). These risks were both independent of age and dementia. Conclusion: We have demonstrated an incremental increase in risk of delirium with increasing frailty. This has important clinical implications, suggesting that frailty may provide a more nuanced measure of vulnerability to delirium and poor outcomes. However, the most frail patients are least likely to have their delirium diagnosed and there is a significant lack of research into the underlying pathophysiology of both of these common geriatric syndromes

    Individual Nomad Clinical Assistant: Supporting Nurses at the Point of Care

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    Accessing patients' data at the point of care has the potential to ease the workflow of nurses and to improve the documentation. We have launched an initiative to develop a mobile assistant focused on managing nurses' daily intervention. The design has required the involvement of many stakeholder and has followed a user centered design process. The evaluation is planned in two stages with an increasing level of ecology. The solution is a client server application displaying a contextualized view on nurses' interventions. It allows to validate and comment each intervention presented as an item in a list. Deploying mobile client applications in healthcare is a challenging task not only from a technical point of view but also regarding organizational factors and human factors
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