Eumelanin-based coloration and fitness parameters in birds: a meta-analysis

Although melanin is the most common pigment in animal integuments, the adaptive function of variation in melanin-based coloration remains poorly understood. The individual fitness returns associated with melanin pigments can be variable across species as these pigments can have physical and biological protective properties and genes involved in melanogenesis may vary in the intensity of pleiotropic effects. Moreover, dark and pale coloration can also enhance camouflage in alternative habitats and melanin-based coloration can be involved in social interactions. We investigated whether darker or paler individuals achieve a higher fitness in birds, a taxon wherein associations between melanin-based coloration and fitness parameters have been studied in a large number of species. A meta-analysis showed that the degree of melanin-based coloration was not significantly associated with laying date, clutch size, brood size, and survival across 26 species. Similar results were found when restricting the analyses to non-sexually dimorphic birds, colour polymorphic and monomorphic species, in passerines and non-passerines and in species for which inter-individual variation in melanism is due to colour intensity. However, eumelanic coloration was positively associated with clutch and brood size in sexually dimorphic species and those that vary in the size of black patches, respectively. Given that greater extent of melanin-based coloration was positively associated with reproductive parameters and survival in some species but negatively in other species, we conclude that in birds the sign and magnitude of selection exerted on melanin-based coloration is species- or trait-specific.

A cohort study of routinely used sepsis biomarkers and 28-day mortality.

The evaluation of sepsis severity is complicated by the highly variable and nonspecific nature of clinical signs and symptoms. We studied routinely used biomarkers together with clinical parameters to compare their prognostic value for severe sepsis and evaluate their usefulness.

The automatic selection of ventilation parameters during the initial phase of mechanical ventilation.

OBJECTIVE: To test a method that allows automatic set-up of the ventilator controls at the onset of ventilation. DESIGN: Prospective randomized crossover study. SETTING: ICUs in one adult and one children's hospital in Switzerland. PATIENTS: Thirty intubated stable, critically ill patients (20 adults and 10 children). INTERVENTIONS: The patients were ventilated during two 20-min periods using a modified Hamilton AMADEUS ventilator. During the control period the ventilator settings were chosen immediately prior to the study. During the other period individual settings were automatically determined by the ventilatior (AutoInit). MEASUREMENTS AND RESULTS: Pressure, flow, and instantaneous CO2 concentration were measured at the airway opening. From these measurements, series dead space (V(DS)), expiratory time constant (RC), tidal volume (VT, total respiratory frequency (f(tot), minute ventilation (MV), and maximal and mean airway pressure (Paw, max and Paw, mean) were calculated. Arterial blood gases were analyzed at the end of each period. Paw, max was significantly less with the AutoInit ventilator settings while f(tot) was significantly greater (P < 0.05). The other values were not statistically significant. CONCLUSIONS: The AutoInit ventilator settings, which were automatically derived, were acceptable for all patients for a period of 20 min and were not found to be inferior to the control ventilator settings. This makes the AutoInit method potentially useful as an automatic start-up procedure for mechanical ventilation.

Life-Cycle Effects on Household Expenditures: A Latent-Variable Approach

Using data from the Spanish household budget survey, we investigate life- cycle effects on several product expenditures. A latent-variable model approach is adopted to evaluate the impact of income on expenditures, controlling for the number of members in the family. Two latent factors underlying repeated measures of monetary and non-monetary income are used as explanatory variables in the expenditure regression equations, thus avoiding possible bias associated to the measurement error in income. The proposed methodology also takes care of the case in which product expenditures exhibit a pattern of infrequent purchases. Multiple-group analysis is used to assess the variation of key parameters of the model across various household life-cycle typologies. The analysis discloses significant life-cycle effects on the mean levels of expenditures; it also detects significant life-cycle effects on the way expenditures are affected by income and family size. Asymptotic robust methods are used to account for possible non-normality of the data.

Lyfe-cycle effects on household expenditures: A latent-variable approach

Using data from the Spanish household budget survey, we investigate life-cycle effects on several product expenditures. A latent-variable model approach is adopted to evaluate the impact of income on expenditures, controlling for the number of members in the family. Two latent factors underlying repeated measures of monetary and non-monetary income are used as explanatory variables in the expenditure regression equations, thus avoiding possible bias associated to the measurement error in income. The proposed methodology also takes care of the case in which product expenditures exhibit a pattern of infrequent purchases. Multiple-group analysis is used to assess the variation of key parameters of the model across various household life-cycle typologies. The analysis discloses significant life-cycle effects on the mean levels of expenditures; it also detects significant life-cycle effects on the way expenditures are affected by income and family size. Asymptotic robust methods are used to account for possible non-normality of the data.

On the performance of small-area estimators: Fixed vs. random area parameters

Most methods for small-area estimation are based on composite estimators derived from design- or model-based methods. A composite estimator is a linear combination of a direct and an indirect estimator with weights that usually depend on unknown parameters which need to be estimated. Although model-based small-area estimators are usually based on random-effects models, the assumption of fixed effects is at face value more appropriate.Model-based estimators are justified by the assumption of random (interchangeable) area effects; in practice, however, areas are not interchangeable. In the present paper we empirically assess the quality of several small-area estimators in the setting in which the area effects are treated as fixed. We consider two settings: one that draws samples from a theoretical population, and another that draws samples from an empirical population of a labor force register maintained by the National Institute of Social Security (NISS) of Catalonia. We distinguish two types of composite estimators: a) those that use weights that involve area specific estimates of bias and variance; and, b) those that use weights that involve a common variance and a common squared bias estimate for all the areas. We assess their precision and discuss alternatives to optimizing composite estimation in applications.

Expanding molecular modeling and design tools to non-natural sidechains.

Protein-protein interactions encode the wiring diagram of cellular signaling pathways and their deregulations underlie a variety of diseases, such as cancer. Inhibiting protein-protein interactions with peptide derivatives is a promising way to develop new biological and therapeutic tools. Here, we develop a general framework to computationally handle hundreds of non-natural amino acid sidechains and predict the effect of inserting them into peptides or proteins. We first generate all structural files (pdb and mol2), as well as parameters and topologies for standard molecular mechanics software (CHARMM and Gromacs). Accurate predictions of rotamer probabilities are provided using a novel combined knowledge and physics based strategy. Non-natural sidechains are useful to increase peptide ligand binding affinity. Our results obtained on non-natural mutants of a BCL9 peptide targeting beta-catenin show very good correlation between predicted and experimental binding free-energies, indicating that such predictions can be used to design new inhibitors. Data generated in this work, as well as PyMOL and UCSF Chimera plug-ins for user-friendly visualization of non-natural sidechains, are all available at http://www.swisssidechain.ch. Our results enable researchers to rapidly and efficiently work with hundreds of non-natural sidechains.

iLOGP: A Simple, Robust, and Efficient Description of n-Octanol/Water Partition Coefficient for Drug Design Using the GB/SA Approach.

The n-octanol/water partition coefficient (log Po/w) is a key physicochemical parameter for drug discovery, design, and development. Here, we present a physics-based approach that shows a strong linear correlation between the computed solvation free energy in implicit solvents and the experimental log Po/w on a cleansed data set of more than 17,500 molecules. After internal validation by five-fold cross-validation and data randomization, the predictive power of the most interesting multiple linear model, based on two GB/SA parameters solely, was tested on two different external sets of molecules. On the Martel druglike test set, the predictive power of the best model (N = 706, r = 0.64, MAE = 1.18, and RMSE = 1.40) is similar to six well-established empirical methods. On the 17-drug test set, our model outperformed all compared empirical methodologies (N = 17, r = 0.94, MAE = 0.38, and RMSE = 0.52). The physical basis of our original GB/SA approach together with its predictive capacity, computational efficiency (1 to 2 s per molecule), and tridimensional molecular graphics capability lay the foundations for a promising predictor, the implicit log P method (iLOGP), to complement the portfolio of drug design tools developed and provided by the SIB Swiss Institute of Bioinformatics.

A double-quadrature radiofrequency coil design for proton-decoupled carbon-13 magnetic resonance spectroscopy in humans at 7T

Purpose Carbon-13 magnetic resonance spectroscopy (13C-MRS) is challenging because of the inherent low sensitivity of 13C detection and the need for radiofrequency transmission at the 1H frequency while receiving the 13C signal, the latter requiring electrical decoupling of the 13C and 1H radiofrequency channels. In this study, we added traps to the 13C coil to construct a quadrature-13C/quadrature-1H surface coil, with sufficient isolation between channels to allow simultaneous operation at both frequencies without compromise in coil performance. Methods Isolation between channels was evaluated on the bench by measuring all coupling parameters. The quadrature mode of the quadrature-13C coil was assessed using in vitro 23Na gradient echo images. The signal-to-noise ratio (SNR) was measured on the glycogen and glucose resonances by 13C-MRS in vitro, compared with that obtained with a linear-13C/quadrature-1H coil, and validated by 13C-MRS in vivo in the human calf at 7T. Results Isolation between channels was better than â^'30 dB. The 23Na gradient echo images indicate a region where the field is strongly circularly polarized. The quadrature coil provided an SNR enhancement over a linear coil of 1.4, in vitro and in vivo. Conclusion It is feasible to construct a double-quadrature 13C-1H surface coil for proton decoupled sensitivity enhanced 13C-NMR spectroscopy in humans at 7T. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

Diagnostic value of vestibulo-ocular reflex parameters in the detection and characterization of labyrinthine lesions.

OBJECTIVE: To evaluate the power of various parameters of the vestibulo-ocular reflex (VOR) in detecting unilateral peripheral vestibular dysfunction and in characterizing certain inner ear pathologies. STUDY DESIGN: Prospective study of consecutive ambulatory patients presenting with acute onset of peripheral vertigo and spontaneous nystagmus. SETTING: Tertiary referral center. PATIENTS: Seventy-four patients (40 females, 34 males) and 22 normal subjects (11 females, 11 males) were included in the study. Patients were classified in three main diagnoses: vestibular neuritis: 40; viral labyrinthitis: 22; Meniere's disease: 12. METHODS: The VOR function was evaluated by standard caloric and impulse rotary tests (velocity step). A mathematical model of vestibular function was used to characterize the VOR response to rotational stimulation. The diagnostic value of the different VOR parameters was assessed by uni- and multivariable logistic regression. RESULTS: In univariable analysis, caloric asymmetry emerged as the most powerful VOR parameter in identifying unilateral vestibular deficit, with a boundary limit set at 20%. In multivariable analysis, the combination of caloric asymmetry and rotational time constant asymmetry significantly improved the discriminatory power over caloric alone (p&lt;0.0001) and produced a detection score with a correct classification of 92.4%. In discriminating labyrinthine diseases, different combinations of the VOR parameters were obtained for each diagnosis (p&lt;0.003) supporting that the VOR characteristics differ between the three inner ear disorders. However, the clinical usefulness of these characteristics in separating the pathologies was limited. CONCLUSION: We propose a powerful logistic model combining the indices of caloric and time constant asymmetries to detect a peripheral vestibular loss, with an accuracy of 92.4%. Based on vestibular data only, the discrimination between the different inner ear diseases is statistically possible, which supports different pathophysiologic changes in labyrinthine pathologies.

A type stars - physical parameters from UVBY and H-beta photometry

uvby H-beta photometry has been obtained for a sample of 93 selected main sequence A stars. The purpose was to determine accurate effective temperatures, surface gravities, and absolute magnitudes for an individual determination of ages and parallaxes, which have to be included in a more extensive work analyzing the kinematic properties of A V stars. Several calibrations and methods to determine the above mentioned parameters have been reviewed, allowing the design of a new algorithm for their determination. The results obtained using this procedure were tested in a previous paper using uvby H-beta data from the Hauck and Mermilliod catalogue, and comparing the rusulting temperatures, surface gravities and absolute magnitudes with empirical determinations of these parameters.

Pretherapeutic gamma-glutamyltransferase is an independent prognostic factor for patients with renal cell carcinoma.

BACKGROUND: Gamma-glutamyltransferase (GGT) regulates apoptotic balance and promotes cancer progression and invasion. Higher pretherapeutic GGT serum levels have been associated with worse outcomes in various malignancies, but there are no data for renal cell carcinoma (RCC). METHODS: Pretherapeutic GGT serum levels and clinicopathological parameters were retrospectively evaluated in 921 consecutive RCC patients treated with nephrectomy at a single institution between 1998 and 2013. Gamma-glutamyltransferase was analysed as continuous and categorical variable. Associations with RCC-specific survival were assessed with Cox proportional hazards models. Discrimination was measured with the C-index. Decision-curve analysis was used to evaluate the clinical net benefit. The median postoperative follow-up was 45 months. RESULTS: Median pretherapeutic serum GGT level was 25 U l(-1). Gamma-glutamyltransferase levels increased with advancing T (P<0.001), N (P=0.006) and M stages (P<0.001), higher grades (P<0.001), and presence of tumour necrosis (P<0.001). An increase of GGT by 10 U l(-1) was associated with an increase in the risk of death from RCC by 4% (HR 1.04, P<0.001). Based on recursive partitioning-based survival tree analysis, we defined four prognostic categories of GGT: normal low (<17.5 U l(-1)), normal high (17.5 to <34.5 U l(-1)), elevated (34.5 to <181.5 U l(-1)), and highly elevated (⩾181.5 U l(-1)). In multivariable analyses that adjusted for the effect of standard features, both continuously and categorically coded GGT were independent prognostic factors. Adding GGT to a model that included standard features increased the discrimination by 0.9% to 1.8% and improved the clinical net benefit. CONCLUSIONS: Pretherapeutic serum GGT is a novel and independent prognostic factor for patients with RCC. Stratifying patients into prognostic subgroups according to GGT may be used for patient counselling, tailoring surveillance, individualised treatment planning, and clinical trial design.

Design of electron band pass filters for electrically biased finite superlattices

We design optimal band pass filters for electrons in semiconductor heterostructures, under a uniform applied electric field. The inner cells are chosen to provide a desired transmission window. The outer cells are then designed to transform purely incoming or outgoing waves into Bloch states of the inner cells. The transfer matrix is interpreted as a conformal mapping in the complex plane, which allows us to write constraints on the outer cell parameters, from which physically useful values can be obtained.

Kinetic parameters of silicon uptake by rice cultivars

Silicon is considered an important chemical element for rice, because it can improve tolerance to biotic and abiotic stress. However, in many situations no positive effect of silicon was observed, probably due to genetic factors. The objective of this research was to monitor Si uptake kinetics and identify responses of rice cultivars in terms of Si uptake capacity and use. The experiment was carried out in a greenhouse of the São Paulo State University (UNESP), Brazil. The experiment was arranged in a completely randomized, factorial design with three replications. that consisted of two rice cultivars and two Si levels. Kinetic parameters (Vmax, Km, and Cmin), root morphology variables, dry matter yield, Si accumulation and levels in shoots and roots, uptake efficiency, utilization efficiency, and root/shoot ratio were evaluated. Higher Si concentrations in the nutrient solution did not increase rice dry matter. The development of the low-affinity silicon uptake system of the rice cultivar 'Caiapó' was better than of 'Maravilha'.

Cost-effective experimental design to support modeling of concentration-response functions

Modeling concentration-response function became extremely popular in ecotoxicology during the last decade. Indeed, modeling allows determining the total response pattern of a given substance. However, reliable modeling is consuming in term of data, which is in contradiction with the current trend in ecotoxicology, which aims to reduce, for cost and ethical reasons, the number of data produced during an experiment. It is therefore crucial to determine experimental design in a cost-effective manner. In this paper, we propose to use the theory of locally D-optimal designs to determine the set of concentrations to be tested so that the parameters of the concentration-response function can be estimated with high precision. We illustrated this approach by determining the locally D-optimal designs to estimate the toxicity of the herbicide dinoseb on daphnids and algae. The results show that the number of concentrations to be tested is often equal to the number of parameters and often related to the their meaning, i.e. they are located close to the parameters. Furthermore, the results show that the locally D-optimal design often has the minimal number of support points and is not much sensitive to small changes in nominal values of the parameters. In order to reduce the experimental cost and the use of test organisms, especially in case of long-term studies, reliable nominal values may therefore be fixed based on prior knowledge and literature research instead of on preliminary experiments