The Effect of Pre-Injury Anti-Platelet Therapy on the Development of Complications in Isolated Blunt Chest Wall Trauma: A Retrospective Study

INTRODUCTION: The difficulties in the management of the blunt chest wall trauma patient in the Emergency Department due to the development of late complications are well recognised in the literature. Pre-injury anti-platelet therapy has been previously investigated as a risk factor for poor outcomes following traumatic head injury, but not in the blunt chest wall trauma patient cohort. The aim of this study was to investigate pre-injury anti-platelet therapy as a risk factor for the development of complications in the recovery phase following blunt chest wall trauma. METHODS: A retrospective study was completed in which the medical notes were analysed of all blunt chest wall trauma patients presenting to a large trauma centre in Wales in 2012 and 2013. Using univariate and multivariable logistic regression analysis, pre-injury platelet therapy was investigated as a risk factor for the development of complications following blunt chest wall trauma. Previously identified risk factors were included in the analysis to address the influence of confounding. RESULTS: A total of 1303 isolated blunt chest wall trauma patients presented to the ED in Morriston Hospital in 2012 and 2013 with complications recorded in 144 patients (11%). On multi-variable analysis, pre-injury anti-platelet therapy was found to be a significant risk factor for the development of complications following isolated blunt chest wall trauma (odds ratio: 16.9; 95% confidence intervals: 8.2-35.2). As in previous studies patient age, number of rib fractures, chronic lung disease and pre-injury anti-coagulant use were also found to be significant risk factors. CONCLUSIONS: Pre-injury anti-platelet therapy is being increasingly used as a first line treatment for a number of conditions and there is a concurrent increase in trauma in the elderly population. Pre-injury anti-platelet therapy should be considered as a risk factor for the development of complications by clinicians managing blunt chest wall trauma

Track A Basic Science

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138319/1/jia218438.pd

Ferrotoroidic ground state in a heterometallic {Cr^IIIDy^III<inf>6</inf>} complex displaying slow magnetic relaxation

© 2017 The Author(s). Toroidal quantum states are most promising for building quantum computing and information storage devices, as they are insensitive to homogeneous magnetic fields, but interact with charge and spin currents, allowing this moment to be manipulated purely by electrical means. Coupling molecular toroids into larger toroidal moments via ferrotoroidic interactions can be pivotal not only to enhance ground state toroidicity, but also to develop materials displaying ferrotoroidic ordered phases, which sustain linear magneto-electric coupling and multiferroic behavior. However, engineering ferrotoroidic coupling is known to be a challenging task. Here we have isolated a {CrIIIDyIII6} complex that exhibits the much sought-after ferrotoroidic ground state with an enhanced toroidal moment, solely arising from intramolecular dipolar interactions. Moreover, a theoretical analysis of the observed sub-Kelvin zero-field hysteretic spin dynamics of {CrIIIDyIII6} reveals the pivotal role played by ferrotoroidic states in slowing down the magnetic relaxation, in spite of large calculated single-ion quantum tunneling rates

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

The Core Value Compass: visually evaluating the goodness of brands that do good

yesBrands that do good for the society as well as for themselves are motivated by the core values they espouse, which necessitates a better understanding of what qualities a true core value must possess. The inherent tension within brands that do good, between commercial interests to increase competitiveness, and societal interests that are closely linked to the brand’s authenticity, has largely been overlooked. Hence, we develop and demonstrate a relatively easy-to-apply visual tool for evaluating core values based on a set of ‘goodness’ criteria derived from extant theory. The Core Value Compass adopts a paradox-based, evolutionary perspective by incorporating the inherent tensions within true core values, and classifying them according to their temporal orientation. Thus, we contribute towards a better understanding of underlying tensions of core values and provide a practical tool that paves the way for improved, and indeed ethical, corporate branding strategies. Furthermore, we demonstrate the Compass’ application using the case of a public sector brand, which is a quintessential brand that does good. Therefore, we also contribute to the nascent theoretical discourse on public sector branding. This paper therefore adds to the notable attempts to bridge the gap between theory and practice in core values-based corporate branding

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

The Helicobacter pylori Genome Project : insights into H. pylori population structure from analysis of a worldwide collection of complete genomes

Helicobacter pylori, a dominant member of the gastric microbiota, shares co-evolutionary history with humans. This has led to the development of genetically distinct H. pylori subpopulations associated with the geographic origin of the host and with differential gastric disease risk. Here, we provide insights into H. pylori population structure as a part of the Helicobacter pylori Genome Project (HpGP), a multi-disciplinary initiative aimed at elucidating H. pylori pathogenesis and identifying new therapeutic targets. We collected 1011 well-characterized clinical strains from 50 countries and generated high-quality genome sequences. We analysed core genome diversity and population structure of the HpGP dataset and 255 worldwide reference genomes to outline the ancestral contribution to Eurasian, African, and American populations. We found evidence of substantial contribution of population hpNorthAsia and subpopulation hspUral in Northern European H. pylori. The genomes of H. pylori isolated from northern and southern Indigenous Americans differed in that bacteria isolated in northern Indigenous communities were more similar to North Asian H. pylori while the southern had higher relatedness to hpEastAsia. Notably, we also found a highly clonal yet geographically dispersed North American subpopulation, which is negative for the cag pathogenicity island, and present in 7% of sequenced US genomes. We expect the HpGP dataset and the corresponding strains to become a major asset for H. pylori genomics