Plos One
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Falls in the elderly are a major public health concern because of their high incidence, the involvement of many risk factors, the considerable post-fall morbidity and mortality, and the health-related and social costs. Given that many falls are preventable, the early identification of older adults at risk of falling is crucial in order to develop tailored interventions to prevent such falls. To date, however, the fall-risk assessment tools currently used in the elderly have not shown sufficiently high predictive validity to distinguish between subjects at high and low fall risk. Consequently, predicting the risk of falling remains an unsolved issue in geriatric medicine. This one-year prospective study aims to develop and validate, by means of a cross-validation method, a multifactorial fall-risk model based on clinical and robotic parameters in older adults. ⋯ A multifactorial fall-risk assessment that includes clinical and hunova robotic variables significantly improves the accuracy of predicting the risk of falling in community-dwelling older people. Our data suggest that combining clinical and robotic assessments can more accurately identify older people at high risk of falls, thereby enabling personalized fall-prevention interventions to be undertaken.
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Spontaneous electroencephalogram (EEG) and auditory evoked potentials (AEP) have been suggested to monitor the level of consciousness during anesthesia. As both signals reflect different neuronal pathways, a combination of parameters from both signals may provide broader information about the brain status during anesthesia. Appropriate parameter selection and combination to a single index is crucial to take advantage of this potential. ⋯ The present analysis considers several classification algorithms, among those support vector machines, artificial neural networks and Bayesian learning algorithms. On the basis of data from the transition between consciousness and unconsciousness, a combination of EEG and AEP signal parameters developed with automated methods provides a maximum prediction probability of 0.935, which is higher than 0.916 (for EEG parameters) and 0.880 (for AEP parameters) using a cross-validation approach. This suggests that machine learning techniques can successfully be applied to develop an improved combined EEG and AEP parameter to separate consciousness from unconsciousness.
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The acute respiratory distress syndrome (ARDS) is characterized by pulmonary epithelial and endothelial barrier dysfunction and injury. In severe forms of ARDS, extracorporeal membrane oxygenation (ECMO) is often the last option for life support. Endothelial progenitor (EPC) and mesenchymal stem cells (MSC) can regenerate damaged endothelium and thereby improve pulmonary endothelial dysfunction. However, we still lack sufficient knowledge about how ECMO might affect EPC- and MSC-mediated regenerative pathways in ARDS. Therefore, we investigated if ECMO impacts EPC and MSC numbers in ARDS patients. ⋯ ECMO support in ARDS is specifically associated with an increased number of circulating MSC, most likely due to enhanced mobilization, but not with a higher numbers of EPC or serum concentrations of VEGF and Ang2.
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The Upper Palaeolithic is characterised by the appearance of iconographic expressions most often depicting animals, including anthropomorphic forms, and geometric signs. The Late Upper Palaeolithic Magdalenian saw a flourishing of such depictions, encompassing cave art, engraving of stone, bone and antler blanks and decoration of tools and weapons. Though Magdalenian settlement exists as far northwest as Britain, there is a limited range of art known from this region, possibly associated with only fleeting occupation of Britain during this period. ⋯ Between 2015 and 2018, ten fragments of stone plaquettes extensively engraved with abstract designs were uncovered at the Magdalenian site of Les Varines, Jersey, Channel Islands. In this paper, we report detailed analyses of these finds, which provide new evidence for technologies of abstract mark-making, and their significance within the lives of people on the edge of the Magdalenian world. These engraved stone fragments represent important, rare evidence of artistic expression in what is the far northern and western range of the Magdalenian and add new insight to the wider significance of dynamic practices of artistic expression during the Upper Palaeolithic.
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A lack of N95 Filtering Facepiece Respirators (FFRs) during the COVID-19 crisis has placed healthcare workers at risk. It is important for any N95 reuse strategy to determine the effects that proposed protocols would have on the physical functioning of the mask, as well as the practical aspects of implementation. Here we propose and implement a method of heating N95 respirators with moisture (85°C, 60-85% humidity). ⋯ After five cycles of the heating procedure, all three respirators pass both quantitative fit testing (score of >100) and show no degradation of mask filtration efficiency. We also test the Chen Heng V9501 KN95 and HKYQ N95 finding no degradation of mask filtration efficiency, however even for unheated masks these scored <50 for every fit test. The heating method presented here is scalable from individual masks to over a thousand a day with a single industrial convection oven, making this method practical for local application inside health-care facilities.