1,306 research outputs found

    Progressive slip after removal of screw fixation in slipped capital femoral epiphysis: two case reports

    Get PDF
    <p>Abstract</p> <p>Introduction</p> <p>In slipped capital femoral epiphysis the femoral neck displaces relative to the head due to weakening of the epiphysis. Early recognition and adequate surgical fixation is essential for a good functional outcome. The fixation should be secured until the closure of the epiphysis to prevent further slippage. A slipped capital femoral epiphysis should not be confused with a femoral neck fracture.</p> <p>Case presentation</p> <p>Case 1 concerns a 15-year-old boy with an adequate initial screw fixation of his slipped capital femoral epiphysis. Unfortunately, it was thought that the epiphysis had healed and the screw was removed after 11 weeks. This caused new instability with a progressive slip of the femoral epiphysis and subsequently re-fixation and a subtrochanteric correction osteotomy was obligatory. Case 2 concerns a 13-year-old girl with persistent hip pain after screw fixation for slipped capital femoral epiphysis. The screw was removed as lysis was seen around the screw on the hip X-ray. This operation created a new unstable situation and the slip progressed resulting in poor hip function. A correction osteotomy with re-screw fixation was performed with a good functional result.</p> <p>Conclusion</p> <p>A slipped epiphysis of the hip is not considered ‘healed’ after a few months. Given the risk of progression of the slip the fixation material cannot be removed before closure of the growth plate.</p

    A Forward Chemical Screen in Zebrafish Identifies a Retinoic Acid Derivative with Receptor Specificity

    Get PDF
    Background: Retinoids regulate key developmental pathways throughout life, and have potential uses for differentiation therapy. It should be possible to identify novel retinoids by coupling new chemical reactions with screens using the zebrafish embryonic model. Principal Findings: We synthesized novel retinoid analogues and derivatives by amide coupling, obtaining 80–92% yields. A small library of these compounds was screened for bioactivity in living zebrafish embryos. We found that several structurally related compounds significantly affect development. Distinct phenotypes are generated depending on time of exposure, and we characterize one compound (BT10) that produces specific cardiovascular defects when added 1 day post fertilization. When compared to retinoic acid (ATRA), BT10 shows similar but not identical changes in the expression pattern of embryonic genes that are known targets of the retinoid pathway. Reporter assays determined that BT10 interacts with all three RAR receptor sub-types, but has no activity for RXR receptors, at all concentrations tested. Conclusions: Our screen has identified a novel retinoid with specificity for retinoid receptors. This lead compound may be useful for manipulating components of retinoid signaling networks, and may be further derivatized for enhanced activity

    Skillful long-range prediction of European and North American winters

    Get PDF
    This is the final version. Available from AGU via the DOI in this recordUntil recently, long-range forecast systems showed only modest levels of skill in predicting surface winter climate around the Atlantic Basin and associated fluctuations in the North Atlantic Oscillation at seasonal lead times. Here we use a new forecast system to assess seasonal predictability of winter North Atlantic climate. We demonstrate that key aspects of European and North American winter climate and the surface North Atlantic Oscillation are highly predictable months ahead. We demonstrate high levels of prediction skill in retrospective forecasts of the surface North Atlantic Oscillation, winter storminess, near-surface temperature, and wind speed, all of which have high value for planning and adaptation to extreme winter conditions. Analysis of forecast ensembles suggests that while useful levels of seasonal forecast skill have now been achieved, key sources of predictability are still only partially represented and there is further untapped predictability. Key Points The winter NAO can be skilfully predicted months ahead The signal-to-noise ratio of the predictable signal is anomalously low Predictions of the risk of regional winter extremes are possibleThis work was supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101), the UK Public Weather Service research program, and the European Union Framework 7 SPECS project. Leon Hermanson was funded as part of his Research Fellowship by Willis as part of Willis Research Network (WRN)

    Automated Reporter Quantification In Vivo: High-Throughput Screening Method for Reporter-Based Assays in Zebrafish

    Get PDF
    Reporter-based assays underlie many high-throughput screening (HTS) platforms, but most are limited to in vitro applications. Here, we report a simple whole-organism HTS method for quantifying changes in reporter intensity in individual zebrafish over time termed, Automated Reporter Quantification in vivo (ARQiv). ARQiv differs from current “high-content” (e.g., confocal imaging-based) whole-organism screening technologies by providing a purely quantitative data acquisition approach that affords marked improvements in throughput. ARQiv uses a fluorescence microplate reader with specific detection functionalities necessary for robust quantification of reporter signals in vivo. This approach is: 1) Rapid; achieving true HTS capacities (i.e., >50,000 units per day), 2) Reproducible; attaining HTS-compatible assay quality (i.e., Z'-factors of ≥0.5), and 3) Flexible; amenable to nearly any reporter-based assay in zebrafish embryos, larvae, or juveniles. ARQiv is used here to quantify changes in: 1) Cell number; loss and regeneration of two different fluorescently tagged cell types (pancreatic beta cells and rod photoreceptors), 2) Cell signaling; relative activity of a transgenic Notch-signaling reporter, and 3) Cell metabolism; accumulation of reactive oxygen species. In summary, ARQiv is a versatile and readily accessible approach facilitating evaluation of genetic and/or chemical manipulations in living zebrafish that complements current “high-content” whole-organism screening methods by providing a first-tier in vivo HTS drug discovery platform

    The Role of Hospitalists in the Acute Care of Stroke Patients

    Get PDF
    Stroke care has become progressively more complicated with advances in therapies necessitating timely intervention. There are multiple potential providers of stroke care, which traditionally has been the province of general neurologists and primary care physicians. These new players, be they vascular neurologists, neurohospitalists, internal medicine hospitalists, or neurocritical care physicians, at the bedside or at a distance, are poised to make a significant impact on our care of stroke patients. The collaborative model of care may be or become the most prevalent as physicians apply their distinct skill sets to the complex care of inpatients with cerebrovascular disease

    A Discrete Time Model for the Analysis of Medium-Throughput C. elegans Growth Data

    Get PDF
    BACKGROUND: As part of a program to predict the toxicity of environmental agents on human health using alternative methods, several in vivo high- and medium-throughput assays are being developed that use C. elegans as a model organism. C. elegans-based toxicological assays utilize the COPAS Biosort flow sorting system that can rapidly measure size, extinction (EXT) and time-of-flight (TOF), of individual nematodes. The use of this technology requires the development of mathematical and statistical tools to properly analyze the large volumes of biological data. METHODOLOGY/PRINCIPAL FINDINGS: Findings A Markov model was developed that predicts the growth of populations of C. elegans. The model was developed using observations from a 60 h growth study in which five cohorts of 300 nematodes each were aspirated and measured every 12 h. Frequency distributions of log(EXT) measurements that were made when loading C. elegans L1 larvae into 96 well plates (t = 0 h) were used by the model to predict the frequency distributions of the same set of nematodes when measured at 12 h intervals. The model prediction coincided well with the biological observations confirming the validity of the model. The model was also applied to log(TOF) measurements following an adaptation. The adaptation accounted for variability in TOF measurements associated with potential curling or shortening of the nematodes as they passed through the flow cell of the Biosort. By providing accurate estimates of frequencies of EXT or TOF measurements following varying growth periods, the model was able to estimate growth rates. Best model fits showed that C. elegans did not grow at a constant exponential rate. Growth was best described with three different rates. Microscopic observations indicated that the points where the growth rates changed corresponded to specific developmental events: the L1/L2 molt and the start of oogenesis in young adult C. elegans. CONCLUSIONS: Quantitative analysis of COPAS Biosort measurements of C. elegans growth has been hampered by the lack of a mathematical model. In addition, extraneous matter and the inability to assign specific measurements to specific nematodes made it difficult to estimate growth rates. The present model addresses these problems through a population-based Markov model

    Collaborative denoising autoencoder for high glycated haemoglobin prediction.

    Get PDF
    A pioneering study is presented demonstrating that the presence of high glycated haemoglobin (HbA1c) levels in a patient’s blood can be reliably predicted from routinely collected clinical data. This paves the way for performing early detection of Type-2 Diabetes Mellitus (T2DM). This will save healthcare providers a major cost associated with the administration and assessment of clinical tests for HbA1c. A novel collaborative denoising autoencoder framework is used to address this challenge. The framework builds an independent denoising autoencoder model for the high and low HbA1c level, which extracts feature representations in the latent space. A baseline model using just three features: patient age together with triglycerides and glucose level achieves 76% F1-score with an SVM classifier. The collaborative denoising autoencoder uses 78 features and can predict HbA1c level with 81% F1-score
    corecore