3,805 research outputs found

    Ontogenetic and temporal variability in the fat content and fatty acid composition of Atlantic herring (Clupea harengus) from the Bay of Fundy, Canada

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    Atlantic herring (Clupea harengus) is an ecologically and economically valuable species in many food webs, yet surprisingly little is known about the variation in the nutritional quality of these fish. Atlantic herring collected from 2005 through 2008 from the Bay of Fundy, Canada, were examined for variability in their nutritional quality by using total lipid content (n=889) and fatty acid composition (n=551) as proxies for nutritional value. A significant positive relationship was found between fish length and total lipid content. Atlantic herring also had significantly different fatty acid signatures by age. Fish from 2005 had significantly lower total lipid content than fish from 2006 through 2008, and all years had significantly different fatty acid signatures. Summer fish were significantly fatter than winter fish and had significantly different fatty acid signatures. For all comparisons (ontogenetic, annual, and seasonal) percent concentrations of omega-3, -6, and long-chain monounsaturated fatty acids were the most important for distinguishing between the fatty acid signatures of fish. This study underscores the importance of quantifying variation in prey quality synoptically with prey quantity in food webs over ontogenetic and temporal scales when evaluating the effect of prey nutritional quality on predators and on modeling trophic dynamics

    Statistical Algorithms for Models in State Space Using SsfPack 2.2

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    Statistical Algorithms for Models in State Space Using SsfPack 2.2

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    This paper discusses and documents the algorithms of SsfPack 2.2. SsfPack is a suite of C routines for carrying out computations involving the statistical analysis of univariate and multivariate models in state space form. The emphasis is on documenting the link we have made to the Ox computing environment. SsfPack allows for a full range of different state space forms: from a simple time-invariant model to a complicated time-varying model. Functions can be used which put standard models such as ARIMA and cubic spline models in state space form. Basic functions are available for filtering, moment smoothing and simulation smoothing. Ready-to-use functions are provided for standard tasks such as likelihood evaluation, forecasting and signal extraction. We show that SsfPack can be easily used for implementing, fitting and analysing Gaussian models relevant to many areas of econometrics and statistics. Some Gaussian illustrations are given.Kalman filtering and smoothing;Markov chain Monte Carlo;Ox;simulation smoother;state space

    A Balint curriculum's effect on family medicine resident empathy and psychological skills

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    Balint groups are comprised of physicians who regularly gather to present and reflect on clinical cases with the goal of improving the physician-patient relationship by enhancing the physician's interpersonal and communication skills, patient care, and professionalism. The goal of this study was to assess the effect on empathy and psychological skills of a voluntary Balint curriculum in the University of Missouri Family Medicine Residency program since initiation in 2010

    Predictors of quality of life: A quantitative investigation of the stress-coping model in children with asthma

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    <p>Abstract</p> <p>Background</p> <p>Aim of this study is to further explore predictors of health related quality of life in children with asthma using factors derived from to the extended stress-coping model. While the stress-coping model has often been used as a frame of reference in studying health related quality of life in chronic illness, few have actually tested the model in children with asthma.</p> <p>Method</p> <p>In this survey study data were obtained by means of self-report questionnaires from seventy-eight children with asthma and their parents. Based on data derived from these questionnaires the constructs of the extended stress-coping model were assessed, using regression analysis and path analysis.</p> <p>Results</p> <p>The results of both regression analysis and path analysis reveal tentative support for the proposed relationships between predictors and health related quality of life in the stress-coping model. Moreover, as indicated in the stress-coping model, HRQoL is only directly predicted by coping. Both coping strategies 'emotional reaction' (significantly) and 'avoidance' are directly related to HRQoL.</p> <p>Conclusion</p> <p>In children with asthma, the extended stress-coping model appears to be a useful theoretical framework for understanding the impact of the illness on their quality of life. Consequently, the factors suggested by this model should be taken into account when designing optimal psychosocial-care interventions.</p

    Evaluation of a surrogate contact model of TKA

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    INTRODUCTION: Simultaneous prediction of body-level dynamics and detailed joint mechanics in the frame of musculoskeletal (MS) modeling represents still a highly computationally demanding task. Marra et al. (2014) recently presented and validated a MS model capable of concurrent prediction of muscle forces, knee ligament forces, tibiofemoral (TF) and patellofemoral (PF) contact forces in a MS model of Total Knee Arthroplasty (TKA) [1]. Simulation time for one complete gait cycle was in the order of 3 hours, and the iterative process that solved the equilibrium in the knee joint was thought to be the main source of overhead. Surrogate modeling techniques were suggested [2]. In this study, we develop a surrogate contact model of TKA to decrease the simulation time in the MS simulation. We hypothesize that the algorithm that allows the muscle fibers to wrap around the bones constitutes another source of overhead in the MS model. Therefore, we will also evaluate the performances of the surrogate model with and without muscle wrapping. METHODS: The original tibial component from our TKA model [1] was split in a medial and lateral hemi-part and fixed to the ground, whereas the femoral part was left with 6 degrees of freedom (DOF). The contacting pairs exchanged three forces and three moments, which were assumed functions of the relative pose only. Translations (X, Y, Z) were defined relative to the tibial component frame and rotations of the femoral component (RotX, RotY, RotZ) were described with Cardan angles, using the z-y-x rotation sequence. Similarly to Lin et al (2010) [3] we identified two sensitive directions, Y and RotX and, therefore, we defined a sample point as composed by four pose parameters and the two loads in the sensitive directions: X, Fy, Z, Tx, RotY, RotZ. Reference load-pose data were obtained from four simulations of gait, squat, chair-rise, and right-turn trials using the original contact model. The design space was populated using the Hammersley quasi-random sequence and adopting a multi-domain approach, as proposed by Eskinazi and Fregly (2015) [2]. One domain consisted of 20 data points per each frame of the four dynamic simulations, spanning the boundaries of ± 1 standard deviation from the time-varying reference envelopes. A second domain of 2500 points was generated in the principal component space of the reference load-pose data of each dynamic simulation, with boundaries enlarged by 50%. A third domain of 1000 data points represented one-side-contact situations, in which Tx was bounded to ± 4 Nm. In total, 36000 data points were sampled in the three different domains. Data points were evaluated using the original contact model (Fig. 1) by repeated Force-Dependent Kinematics (FDK) analyses. Data points which did not lead to equilibrium were discarded. The remaining 27620 points were randomly subdivided into a training (70%) and testing (30%) group. Three separate Feed-Forward Artificial Neural Networks (FFANN), consisting of four inner layers of 20 hyperbolic tangent sigmoid neurons each, were configured within the Neural Network Toolbox in MATLAB 8.1 (The MathWorks Inc., Natick, MA, 2013). The first network was trained to learn the relationships between the four –two medial and two lateral– sensitive loads (output) and the six pose parameters (input). Two other networks –one medial and one lateral– were trained separately to learn the relationships between the remaining loads of each side (output) and all the pose parameters plus the two sensitive loads from each side (input). We used the popular Levenberg-Marquardt training algorithm in conjunction with Bayesian regularization to avoid over-fitting. Stopping criterion was a training time of two hours for each network. The trained networks were translated to custom C++ DLL functions for successive inclusion in our MS model. The surrogate contact model replaced the original contact model and one gait trial was simulated with 4 different combination of the following model settings: original versus surrogate contact model, wrapping enabled versus disabled. RESULTS: The contact sampling model required 238 hours to evaluate the 36000 data points. Predicted tibiofemoral compressive forces under all simulated cases are shown in Fig. 2. A comparison with experimental measurements (eTibia line) is also shown. Surrogate model predictions showed a very good agreement with the original model counterparts. Fig. 3 summarizes the computation times: simulations took the longest when muscle wrapping was enabled and the benefits of using the surrogate model became evident only when the wrapping algorithm was switched off, leading to a 6x speed-up. Simulation time with the original contact model decreased by a factor of 8 by switching off the wrapping algorithm. DISCUSSION: The use of FFANN-based surrogate contact model, in place of the original rigid contact model, could substantially reduce the simulation time of a full gait cycle down to 3 minutes, when the wrapping algorithm was turned off. Such improvement could not be achieved when using the wrapping algorithm. This enlightens another important source of overhead in MS modeling –the muscle wrapping algorithm– which unexpectedly was found to dominate the simulation time. At each FDK iteration, the wrapping algorithm needs to be solved as well, introducing overhead. If the wrapping algorithm is slower than the contact algorithm, then the computation time of each step will be dominated by the former, leaving only a small fraction to be gained from the latter. SIGNIFICANCE: We showed that surrogate contact model could reduce the simulation time in a MS model of TKA down to a level which allows parametric studies and/or optimization to be feasible. We also discovered that the muscle wrapping algorithm constituted an unexpectedly large source of overhead during dynamic simulations. These represent new and important findings for the MS modeling community. REFERENCES: [1] M. A. Marra, V. Vanheule, R. Fluit, B. H. F. J. M. Koopman, J. Rasmussen, N. J. J. Verdonschot, and M. S. Andersen, “A Subject-Specific Musculoskeletal Modeling Framework to Predict in Vivo Mechanics of Total Knee Arthroplasty.,” J. Biomech. Eng., Nov. 2014. [2] I. Eskinazi and B. J. Fregly, “Surrogate modeling of deformable joint contact using artificial neural networks.,” Med. Eng. Phys., Jul. 2015. [3] Y.-C. Lin, R. T. Haftka, N. V Queipo, and B. J. Fregly, “Surrogate articular contact models for computationally efficient multibody dynamic simulations.,” Med. Eng. Phys., vol. 32, no. 6, pp. 584–94, Jul. 2010. ACKNOWLEDGEMENTS: This study was conducted within the ERC ‘BioMechTools’ project, funded by the European Research Council

    Normal Levels of Sox9 Expression in the Developing Mouse Testis Depend on the TES/TESCO Enhancer, but This Does Not Act Alone

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    During mouse sex determination, transient expression of the Y-linked gene Sry up-regulates its direct target gene Sox9, via a 3.2 kb testis specific enhancer of Sox9 (TES), which includes a core 1.4 kb element, TESCO. SOX9 activity leads to differentiation of Sertoli cells, rather than granulosa cells from the bipotential supporting cell precursor lineage. Here, we present functional analysis of TES/TESCO, using CRISPR/Cas9 genome editing in mice. Deletion of TESCO or TES reduced Sox9 expression levels in XY fetal gonads to 60 or 45% respectively relative to wild type gonads, and reduced expression of the SOX9 target Amh. Although human patients heterozygous for null mutations in SOX9, which are assumed to have 50% of normal expression, often show XY female sex reversal, mice deleted for one copy of Sox9 do not. Consistent with this, we did not observe sex reversal in either TESCO-/- or TES-/- XY embryos or adult mice. However, embryos carrying both a conditional Sox9 null allele and the TES deletion developed ovotestes. Quantitative analysis of these revealed levels of 23% expression of Sox9 compared to wild type, and a significant increase in the expression of the granulosa cell marker Foxl2. This indicates that the threshold in mice where sex reversal begins to be seen is about half that of the ~50% levels predicted in humans. Our results demonstrate that TES/TESCO is a crucial enhancer regulating Sox9 expression in the gonad, but point to the existence of additional enhancers that act redundantly

    The dynamics of methicillin-resistant Staphylococcus aureus exposure in a hospital model and the potential for environmental intervention

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    Abstract Background Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of healthcare-associated infections. An important control strategy is hand hygiene; however, non-compliance has been a major problem in healthcare settings. Furthermore, modeling studies have suggested that the law of diminishing return applies to hand hygiene. Other additional control strategies such as environmental cleaning may be warranted, given that MRSA-positive individuals constantly shed contaminated desquamated skin particles to the environment. Methods We constructed and analyzed a deterministic environmental compartmental model of MRSA fate, transport, and exposure between two hypothetical hospital rooms: one with a colonized patient, shedding MRSA; another with an uncolonized patient, susceptible to exposure. Healthcare workers (HCWs), acting solely as vectors, spread MRSA from one patient room to the other. Results Although porous surfaces became highly contaminated, their low transfer efficiency limited the exposure dose to HCWs and the uncolonized patient. Conversely, the high transfer efficiency of nonporous surfaces allows greater MRSA transfer when touched. In the colonized patient’s room, HCW exposure occurred more predominantly through the indirect (patient to surfaces to HCW) mode compared to the direct (patient to HCW) mode. In contrast, in the uncolonized patient’s room, patient exposure was more predominant in the direct (HCW to patient) mode compared to the indirect (HCW to surfaces to patient) mode. Surface wiping decreased MRSA exposure to the uncolonized patient more than daily surface decontamination. This was because wiping allowed higher cleaning frequency and cleaned more total surface area per day. Conclusions Environmental cleaning should be considered as an integral component of MRSA infection control in hospitals. Given the previously under-appreciated role of surface contamination in MRSA transmission, this intervention mode can contribute to an effective multiple barrier approach in concert with hand hygiene.http://deepblue.lib.umich.edu/bitstream/2027.42/112924/1/12879_2013_Article_2936.pd

    The Effect of Ongoing Exposure Dynamics in Dose Response Relationships

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    Characterizing infectivity as a function of pathogen dose is integral to microbial risk assessment. Dose-response experiments usually administer doses to subjects at one time. Phenomenological models of the resulting data, such as the exponential and the Beta-Poisson models, ignore dose timing and assume independent risks from each pathogen. Real world exposure to pathogens, however, is a sequence of discrete events where concurrent or prior pathogen arrival affects the capacity of immune effectors to engage and kill newly arriving pathogens. We model immune effector and pathogen interactions during the period before infection becomes established in order to capture the dynamics generating dose timing effects. Model analysis reveals an inverse relationship between the time over which exposures accumulate and the risk of infection. Data from one time dose experiments will thus overestimate per pathogen infection risks of real world exposures. For instance, fitting our model to one time dosing data reveals a risk of 0.66 from 313 Cryptosporidium parvum pathogens. When the temporal exposure window is increased 100-fold using the same parameters fitted by our model to the one time dose data, the risk of infection is reduced to 0.09. Confirmation of this risk prediction requires data from experiments administering doses with different timings. Our model demonstrates that dose timing could markedly alter the risks generated by airborne versus fomite transmitted pathogens

    Consistency of the Shannon entropy in quantum experiments

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    The consistency of the Shannon entropy, when applied to outcomes of quantum experiments, is analysed. It is shown that the Shannon entropy is fully consistent and its properties are never violated in quantum settings, but attention must be paid to logical and experimental contexts. This last remark is shown to apply regardless of the quantum or classical nature of the experiments.Comment: 12 pages, LaTeX2e/REVTeX4. V5: slightly different than the published versio
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