Activity of anidulafungin in a murine model of Candida krusei infection: evaluation of mortality and disease burden by quantitative tissue cultures and measurement of serum (1,3)-beta-D-glucan levels.

Experience with anidulafungin against Candida krusei is limited. Immunosuppressed mice were injected with 1.3 x 10(7) to 1.5 x 10(7) CFU of C. krusei. Animals were treated with saline, 40 mg/kg fluconazole, 1 mg/kg amphotericin B, or 10 and 20 mg/kg anidulafungin for 5 days. Anidulafungin improved survival and significantly reduced the number of CFU/g in kidneys and serum beta-glucan levels.

Family models of independence/interdependence and their intergenerational similarity in Germany, Turkey, and India

Family change theory suggests three ideal-typical family models characterized by different combinations of emotional and material interdependencies in the family. Its major proposition is that in economically developing countries with a collectivistic background a family model of emotional interdependence emerges from a family model of complete interdependence. The current study aims to identify and compare patterns of family-related value orientations related to family change theory across three cultures and two generations. Overall, N = 919 dyads of mothers and their adolescent children from Germany, Turkey, and India participated in the study. Three clusters were identified representing the family models of independence, interdependence, and emotional interdependence, respectively. Especially the identification of an emotionally interdependent value pattern using a person-oriented approach is an important step in the empirical validation of family change theory. The preference for the three family models differed across as well as within cultures and generations according to theoretical predictions. Dyadic analyses pointed to substantial intergenerational similarities and also to differences in family models, reflecting both cultural continuity as well as change in family-related value orientations.

3.88 A structure of cytoplasmic polyhedrosis virus by cryo-electron microscopy.

Cytoplasmic polyhedrosis virus (CPV) is unique within the Reoviridae family in having a turreted single-layer capsid contained within polyhedrin inclusion bodies, yet being fully capable of cell entry and endogenous RNA transcription. Biochemical data have shown that the amino-terminal 79 residues of the CPV turret protein (TP) is sufficient to bring CPV or engineered proteins into the polyhedrin matrix for micro-encapsulation. Here we report the three-dimensional structure of CPV at 3.88 A resolution using single-particle cryo-electron microscopy. Our map clearly shows the turns and deep grooves of alpha-helices, the strand separation in beta-sheets, and densities for loops and many bulky side chains; thus permitting atomic model-building effort from cryo-electron microscopy maps. We observed a helix-to-beta-hairpin conformational change between the two conformational states of the capsid shell protein in the region directly interacting with genomic RNA. We have also discovered a messenger RNA release hole coupled with the mRNA capping machinery unique to CPV. Furthermore, we have identified the polyhedrin-binding domain, a structure that has potential in nanobiotechnology applications.

Values of children and family models of adolescents: An eleven-culture study

Starting from Kagitcibasi's (2007) conceptualization of family models, this study compared N = 2961 adolescents' values across eleven cultures and explored whether patterns of values were related to the three proposed family models through cluster analyses. Three clusters with value profiles corresponding to the family models of interdependence, emotional interdependence, and independence were identified on the cultural as well as on the individual level. Furthermore, individual-level clusters corresponded to culture-level clusters in terms of individual cluster membership. The results largely support Kagitcibasi's proposition of changing family models and demonstrate their representation as individual-level value profiles across cultures.

Improving the accuracy of radiation pneumonitis dose response models

The prognosis for lung cancer patients remains poor. Five year survival rates have been reported to be 15%. Studies have shown that dose escalation to the tumor can lead to better local control and subsequently better overall survival. However, dose to lung tumor is limited by normal tissue toxicity. The most prevalent thoracic toxicity is radiation pneumonitis. In order to determine a safe dose that can be delivered to the healthy lung, researchers have turned to mathematical models predicting the rate of radiation pneumonitis. However, these models rely on simple metrics based on the dose-volume histogram and are not yet accurate enough to be used for dose escalation trials. The purpose of this work was to improve the fit of predictive risk models for radiation pneumonitis and to show the dosimetric benefit of using the models to guide patient treatment planning. The study was divided into 3 specific aims. The first two specifics aims were focused on improving the fit of the predictive model. In Specific Aim 1 we incorporated information about the spatial location of the lung dose distribution into a predictive model. In Specific Aim 2 we incorporated ventilation-based functional information into a predictive pneumonitis model. In the third specific aim a proof of principle virtual simulation was performed where a model-determined limit was used to scale the prescription dose. The data showed that for our patient cohort, the fit of the model to the data was not improved by incorporating spatial information. Although we were not able to achieve a significant improvement in model fit using pre-treatment ventilation, we show some promising results indicating that ventilation imaging can provide useful information about lung function in lung cancer patients. The virtual simulation trial demonstrated that using a personalized lung dose limit derived from a predictive model will result in a different prescription than what was achieved with the clinically used plan; thus demonstrating the utility of a normal tissue toxicity model in personalizing the prescription dose.

On the evolution of the oceanic component of the IPSL climate models from CMIP3 to CMIP5: A mean state comparison

This study analyses the impact on the oceanic mean state of the evolution of the oceanic component (NEMO) of the climate model developed at Institut Pierre Simon Laplace (IPSL-CM), from the version IPSL-CM4, used for third phase of the Coupled Model Intercomparison Project (CMIP3), to IPSL-CM5A, used for CMIP5. Several modifications have been implemented between these two versions, in particular an interactive coupling with a biogeochemical module, a 3-band model for the penetration of the solar radiation, partial steps at the bottom of the ocean and a set of physical parameterisations to improve the representation of the impact of turbulent and tidal mixing. A set of forced and coupled experiments is used to single out the effect of each of these modifications and more generally the evolution of the oceanic component on the IPSL coupled models family. Major improvements are located in the Southern Ocean, where physical parameterisations such as partial steps and tidal mixing reinforce the barotropic transport of water mass, in particular in the Antarctic Circumpolar Current) and ensure a better representation of Antarctic bottom water masses. However, our analysis highlights that modifications, which substantially improve ocean dynamics in forced configuration, can yield or amplify biases in coupled configuration. In particular, the activation of radiative biophysical coupling between biogeochemical cycle and ocean dynamics results in a cooling of the ocean mean state. This illustrates the difficulty to improve and tune coupled climate models, given the large number of degrees of freedom and the potential compensating effects masking some biases.

Models of DNA sequence evolution

Models of DNA sequence evolution and methods for estimating evolutionary distances are needed for studying the rate and pattern of molecular evolution and for inferring the evolutionary relationships of organisms or genes. In this dissertation, several new models and methods are developed.^ The rate variation among nucleotide sites: To obtain unbiased estimates of evolutionary distances, the rate heterogeneity among nucleotide sites of a gene should be considered. Commonly, it is assumed that the substitution rate varies among sites according to a gamma distribution (gamma model) or, more generally, an invariant+gamma model which includes some invariable sites. A maximum likelihood (ML) approach was developed for estimating the shape parameter of the gamma distribution $(\alpha)$ and/or the proportion of invariable sites $(\theta).$ Computer simulation showed that (1) under the gamma model, $\alpha$ can be well estimated from 3 or 4 sequences if the sequence length is long; and (2) the distance estimate is unbiased and robust against violations of the assumptions of the invariant+gamma model.^ However, this ML method requires a huge amount of computational time and is useful only for less than 6 sequences. Therefore, I developed a fast method for estimating $\alpha,$ which is easy to implement and requires no knowledge of tree. A computer program was developed for estimating $\alpha$ and evolutionary distances, which can handle the number of sequences as large as 30.^ Evolutionary distances under the stationary, time-reversible (SR) model: The SR model is a general model of nucleotide substitution, which assumes (i) stationary nucleotide frequencies and (ii) time-reversibility. It can be extended to SRV model which allows rate variation among sites. I developed a method for estimating the distance under the SR or SRV model, as well as the variance-covariance matrix of distances. Computer simulation showed that the SR method is better than a simpler method when the sequence length $L>1,000$ bp and is robust against deviations from time-reversibility. As expected, when the rate varies among sites, the SRV method is much better than the SR method.^ The evolutionary distances under nonstationary nucleotide frequencies: The statistical properties of the paralinear and LogDet distances under nonstationary nucleotide frequencies were studied. First, I developed formulas for correcting the estimation biases of the paralinear and LogDet distances. The performances of these formulas and the formulas for sampling variances were examined by computer simulation. Second, I developed a method for estimating the variance-covariance matrix of the paralinear distance, so that statistical tests of phylogenies can be conducted when the nucleotide frequencies are nonstationary. Third, a new method for testing the molecular clock hypothesis was developed in the nonstationary case. ^

Higher emotional distress in female partners of cancer patients: prevalence and patient-partner interdependencies in a 3-year cohort

OBJECTIVE: Assessment and treatment of psychological distress in cancer patients was recognized as a major challenge. The role of spouses, caregivers, and significant others became of salient importance not only because of their supportive functions but also in respect to their own burden. The purpose of this study was to assess the amount of distress in a mixed sample of cancer patients and their partners and to explore the dyadic interdependence. METHODS: An initial sample of 154 dyads was recruited, and distress questionnaires (Hospital Anxiety and Depression Scale, Symptom Checklist 9-Item Short Version and 12-Item Short Form Health Survey) were assessed over four time points. Linear mixed models and actor-partner interdependence models were applied. RESULTS: A significant proportion of patients and their partners (up to 40%) reported high levels of anxiety, depression, psychological distress, and low quality of life over the course of the investigation. Mixed model analyses revealed that higher risks for clinical relevant anxiety and depression in couples exist for female patients and especially for female partners. Although psychological strain decreased over time, the risk for elevated distress in female partners remained. Modeling patient-partner interdependence over time stratified by patients' gender revealed specific effects: a moderate correlation between distress in patients and partners, and a transmission of distress from male patients to their female partners. CONCLUSIONS: Our findings provide empirical support for gender-specific transmission of distress in dyads coping with cancer. This should be considered as an important starting point for planning systemic psycho-oncological interventions and conceptualizing further research.

Apoptosis of hippocampal neurons in organotypic slice culture models: direct effect of bacteria revisited

Neurons of the hippocampal dentate gyrus selectively undergo programmed cell death in patients suffering from bacterial meningitis and in experimental models of pneumococcal meningitis in infant rats. In the present study, a membrane-based organotypic slice culture system of rat hippocampus was used to test whether this selective vulnerability of neurons of the dentate gyrus could be reproduced in vitro. Apoptosis was assessed by nuclear morphology (condensed and fragmented nuclei), by immunochemistry for active caspase-3 and deltaC-APP, and by proteolytic caspase-3 activity. Co-incubation of the cultures with live pneumococci did not induce neuronal apoptosis unless cultures were kept in partially nutrient-deprived medium. Complete nutrient deprivation alone and staurosporine independently induced significant apoptosis, the latter in a dose-response way. In all experimental settings, apoptosis occurred preferentially in the dentate gyrus. Our data demonstrate that factors released by pneumococci per se failed to induce significant apoptosis in vitro. Thus, these factors appear to contribute to a multifactorial pathway, which ultimately leads to neuronal apoptosis in bacterial meningitis.

The Value of Adding Optics to Ecosystem Models: A Case Study

Many ecosystem models have been developed to study the ocean's biogeochemical properties, but most of these models use simple formulations to describe light penetration and spectral quality. Here, an optical model is coupled with a previously published ecosystem model that explicitly represents two phytoplankton (picoplankton and diatoms) and two zooplankton functional groups, as well as multiple nutrients and detritus. Surface ocean color fields and subsurface light fields are calculated by coupling the ecosystem model with an optical model that relates biogeochemical standing stocks with inherent optical properties (absorption, scattering); this provides input to a commercially available radiative transfer model (Ecolight). We apply this bio-optical model to the equatorial Pacific upwelling region, and find the model to be capable of reproducing many measured optical properties and key biogeochemical processes in this region. Our model results suggest that non-algal particles largely contribute to the total scattering or attenuation (> 50% at 660 nm) but have a much smaller contribution to particulate absorption (< 20% at 440 nm), while picoplankton dominate the total phytoplankton absorption (> 95% at 440 nm). These results are consistent with the field observations. In order to achieve such good agreement between data and model results, however, key model parameters, for which no field data are available, have to be constrained. Sensitivity analysis of the model results to optical parameters reveals a significant role played by colored dissolved organic matter through its influence on the quantity and quality of the ambient light. Coupling explicit optics to an ecosystem model provides advantages in generating: (1) a more accurate subsurface light-field, which is important for light sensitive biogeochemical processes such as photosynthesis and photo-oxidation, (2) additional constraints on model parameters that help to reduce uncertainties in ecosystem model simulations, and (3) model output which is comparable to basic remotely-sensed properties. In addition, the coupling of biogeochemical models and optics paves the road for future assimilation of ocean color and in-situ measured optical properties into the models.

Optimizing Models of the North Atlantic Spring Bloom Using Physical, Chemical and Bio-Optical Observations from a Lagrangian Float

The North Atlantic spring bloom is one of the main events that lead to carbon export to the deep ocean and drive oceanic uptake of CO(2) from the atmosphere. Here we use a suite of physical, bio-optical and chemical measurements made during the 2008 spring bloom to optimize and compare three different models of biological carbon export. The observations are from a Lagrangian float that operated south of Iceland from early April to late June, and were calibrated with ship-based measurements. The simplest model is representative of typical NPZD models used for the North Atlantic, while the most complex model explicitly includes diatoms and the formation of fast sinking diatom aggregates and cysts under silicate limitation. We carried out a variational optimization and error analysis for the biological parameters of all three models, and compared their ability to replicate the observations. The observations were sufficient to constrain most phytoplankton-related model parameters to accuracies of better than 15 %. However, the lack of zooplankton observations leads to large uncertainties in model parameters for grazing. The simulated vertical carbon flux at 100 m depth is similar between models and agrees well with available observations, but at 600 m the simulated flux is larger by a factor of 2.5 to 4.5 for the model with diatom aggregation. While none of the models can be formally rejected based on their misfit with the available observations, the model that includes export by diatom aggregation has a statistically significant better fit to the observations and more accurately represents the mechanisms and timing of carbon export based on observations not included in the optimization. Thus models that accurately simulate the upper 100 m do not necessarily accurately simulate export to deeper depths.

An Early-Warning System for Hypo-/Hyperglycemic Events Based on Fusion of Adaptive Prediction Models

Introduction: Early warning of future hypoglycemic and hyperglycemic events can improve the safety of type 1 diabetes mellitus (T1DM) patients. The aim of this study is to design and evaluate a hypoglycemia / hyperglycemia early warning system (EWS) for T1DM patients under sensor-augmented pump (SAP) therapy. Methods: The EWS is based on the combination of data-driven online adaptive prediction models and a warning algorithm. Three modeling approaches have been investigated: (i) autoregressive (ARX) models, (ii) auto-regressive with an output correction module (cARX) models, and (iii) recurrent neural network (RNN) models. The warning algorithm performs postprocessing of the models′ outputs and issues alerts if upcoming hypoglycemic/hyperglycemic events are detected. Fusion of the cARX and RNN models, due to their complementary prediction performances, resulted in the hybrid autoregressive with an output correction module/recurrent neural network (cARN)-based EWS. Results: The EWS was evaluated on 23 T1DM patients under SAP therapy. The ARX-based system achieved hypoglycemic (hyperglycemic) event prediction with median values of accuracy of 100.0% (100.0%), detection time of 10.0 (8.0) min, and daily false alarms of 0.7 (0.5). The respective values for the cARX-based system were 100.0% (100.0%), 17.5 (14.8) min, and 1.5 (1.3) and, for the RNN-based system, were 100.0% (92.0%), 8.4 (7.0) min, and 0.1 (0.2). The hybrid cARN-based EWS presented outperforming results with 100.0% (100.0%) prediction accuracy, detection 16.7 (14.7) min in advance, and 0.8 (0.8) daily false alarms. Conclusion: Combined use of cARX and RNN models for the development of an EWS outperformed the single use of each model, achieving accurate and prompt event prediction with few false alarms, thus providing increased safety and comfort.

What does your neighbourhood say about you? A study of life expectancy in 1.3 million Swiss neighbourhoods

BACKGROUND Switzerland had the highest life expectancy at 82.8 years among the Organisation for Economic Co-operation and Development (OECD) countries in 2011. Geographical variation of life expectancy and its relation to the socioeconomic position of neighbourhoods are, however, not well understood. METHODS We analysed the Swiss National Cohort, which linked the 2000 census with mortality records 2000-2008 to estimate life expectancy across neighbourhoods. A neighbourhood index of socioeconomic position (SEP) based on the median rent, education and occupation of household heads and crowding was calculated for 1.3 million overlapping neighbourhoods of 50 households. We used skew-normal regression models, including the index and additionally marital status, education, nationality, religion and occupation to calculate crude and adjusted estimates of life expectancy at age 30 years. RESULTS Based on over 4.5 million individuals and over 400 000 deaths, estimates of life expectancy at age 30 in neighbourhoods ranged from 46.9 to 54.2 years in men and from 53.5 to 57.2 years in women. The correlation between life expectancy and neighbourhood SEP was strong (r=0.95 in men and r=0.94 women, both p values <0.0001). In a comparison of the lowest with the highest percentile of neighbourhood SEP, the crude difference in life expectancy from skew-normal regression was 4.5 years in men and 2.5 years in women. The corresponding adjusted differences were 2.8 and 1.9 years, respectively (all p values <0.0001). CONCLUSIONS Although life expectancy is high in Switzerland, there is substantial geographical variation and life expectancy is strongly associated with the social standing of neighbourhoods.

High Resolution Transmission Spectroscopy as a Diagnostic for Jovian Exoplanet Atmospheres: Constraints from Theoretical Models

We present high resolution transmission spectra of giant planet atmospheres from a coupled 3-D atmospheric dynamics and transmission spectrum model that includes Doppler shifts which arise from winds and planetary motion. We model jovian planets covering more than two orders of magnitude in incident flux, corresponding to planets with 0.9 to 55 day orbital periods around solar-type stars. The results of our 3-D dynamical models reveal certain aspects of high resolution transmission spectra that are not present in simple 1-D models. We find that the hottest planets experience strong substellar to anti-stellar (SSAS) winds, resulting in transmission spectra with net blue shifts of up to 3 km s−1, whereas less irradiated planets show almost no net Doppler shifts. Compared to 1-D models, peak line strengths are significantly reduced for the hottest atmospheres owing to Doppler broadening from a combination of rotation (which is faster for close-in planets under the assumption of tidal locking) and atmospheric winds. Finally, high resolution transmission spectra may be useful in studying the atmospheres of exoplanets with optically thick clouds since line cores for very strong transitions should remain optically thick to very high altitude. High resolution transmission spectra are an excellent observational test for the validity of 3-D atmospheric dynamics models, because they provide a direct probe of wind structures and heat circulation. Ground-based exoplanet spectroscopy is currently on the verge of being able to verify some of our modeling predictions, most notably the dependence of SSAS winds on insolation. We caution that interpretation of high resolution transmission spectra based on 1-D atmospheric models may be inadequate, as 3-D atmospheric motions can produce a noticeable effect on the absorption signatures.

Analytical Models of Exoplanetary Atmospheres. II. Radiative Transfer via the Two-Stream Approximation

We present a comprehensive analytical study of radiative transfer using the method of moments and include the effects of non-isotropic scattering in the coherent limit. Within this unified formalism, we derive the governing equations and solutions describing two-stream radiative transfer (which approximates the passage of radiation as a pair of outgoing and incoming fluxes), flux-limited diffusion (which describes radiative transfer in the deep interior) and solutions for the temperature-pressure profiles. Generally, the problem is mathematically under-determined unless a set of closures (Eddington coefficients) is specified. We demonstrate that the hemispheric (or hemi-isotropic) closure naturally derives from the radiative transfer equation if energy conservation is obeyed, while the Eddington closure produces spurious enhancements of both reflected light and thermal emission. We concoct recipes for implementing two-stream radiative transfer in stand-alone numerical calculations and general circulation models. We use our two-stream solutions to construct toy models of the runaway greenhouse effect. We present a new solution for temperature-pressure profiles with a non-constant optical opacity and elucidate the effects of non-isotropic scattering in the optical and infrared. We derive generalized expressions for the spherical and Bond albedos and the photon deposition depth. We demonstrate that the value of the optical depth corresponding to the photosphere is not always 2/3 (Milne's solution) and depends on a combination of stellar irradiation, internal heat and the properties of scattering both in optical and infrared. Finally, we derive generalized expressions for the total, net, outgoing and incoming fluxes in the convective regime.