Corticosterone mediates the condition-dependent component of melanin-based coloration

The handicap principle of sexual selection theory states that colourful phenotypic traits signal aspects of individual quality because only individuals in prime condition can afford to produce and bear conspicuous traits. Melanin-based pigments participate in the elaboration of many secondary sexual characters and, given their role in sexual selection, melanin-based coloration may therefore honestly reject individual quality. Although the expression of melanism is usually under genetic control, in some species it is condition dependent. However, the underlying physiological mechanism is yet unknown. Based on the negative feedback link between corticosterone and melanogenesis ( melanocortins, tyrosinase) in response to stressful environmental factors, we hypothesize that corticosterone mediates the condition-dependent component of melanism. This hypothesis predicts that stressful factors induce a rise in circulating corticosterone which inhibits the secretion of melanocortins and tyrosinase and in turn melanin production. We tested this prediction by manipulating the level of corticosterone at the time of melanin production in nestling barn owls, Tyto alba, a species showing heritable variation in the degree of phaeomelanism from reddish-brown to white. The finding that corticosterone-implanted nestlings produced feathers with less phaeomelanic coloration than placebo-implanted nestlings is consistent with the hypothesis that the environment-mediated reduction in the degree of melanism is, at least in part, caused by a rise in corticosterone. In species in which the expression of melanin-based coloration is condition dependent, we now need a test showing that individuals with less corticosterone and more melanin-based signals are individuals in better condition.

Prediction of 18-month survival in patients with primary myelodysplastic syndrome. A regression model and scoring system based on the combination of chromosome findings and the Bournemouth score.

The predictive potential of six selected factors was assessed in 72 patients with primary myelodysplastic syndrome using univariate and multivariate logistic regression analysis of survival at 18 months. Factors were age (above median of 69 years), dysplastic features in the three myeloid bone marrow cell lineages, presence of chromosome defects, all metaphases abnormal, double or complex chromosome defects (C23), and a Bournemouth score of 2, 3, or 4 (B234). In the multivariate approach, B234 and C23 proved to be significantly associated with a reduction in the survival probability. The similarity of the regression coefficients associated with these two factors means that they have about the same weight. Consequently, the model was simplified by counting the number of factors (0, 1, or 2) present in each patient, thus generating a scoring system called the Lausanne-Bournemouth score (LB score). The LB score combines the well-recognized and easy-to-use Bournemouth score (B score) with the chromosome defect complexity, C23 constituting an additional indicator of patient outcome. The predicted risk of death within 18 months calculated from the model is as follows: 7.1% (confidence interval: 1.7-24.8) for patients with an LB score of 0, 60.1% (44.7-73.8) for an LB score of 1, and 96.8% (84.5-99.4) for an LB score of 2. The scoring system presented here has several interesting features. The LB score may improve the predictive value of the B score, as it is able to recognize two prognostic groups in the intermediate risk category of patients with B scores of 2 or 3. It has also the ability to identify two distinct prognostic subclasses among RAEB and possibly CMML patients. In addition to its above-described usefulness in the prognostic evaluation, the LB score may bring new insights into the understanding of evolution patterns in MDS. We used the combination of the B score and chromosome complexity to define four classes which may be considered four possible states of myelodysplasia and which describe two distinct evolutional pathways.

Uncertainty Quantification with Support Vector Regression Prediction Models

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. The paper considers a data driven approach in modelling uncertainty in spatial predictions. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic features and describe stochastic variability and non-uniqueness of spatial properties. It is able to capture and preserve key spatial dependencies such as connectivity, which is often difficult to achieve with two-point geostatistical models. Semi-supervised SVR is designed to integrate various kinds of conditioning data and learn dependences from them. A stochastic semi-supervised SVR model is integrated into a Bayesian framework to quantify uncertainty with multiple models fitted to dynamic observations. The developed approach is illustrated with a reservoir case study. The resulting probabilistic production forecasts are described by uncertainty envelopes.

Link between genotype and antimicrobial resistance in bovine mastitis-related Staphylococcus aureus strains, determined by comparing Swiss and French isolates from the Rhône Valley.

Staphylococcus aureus is a major bovine mastitis pathogen. Although the reported antimicrobial resistance was generally low, the emergence of new genetic clusters in bovine mastitis requires examination of the link between antimicrobial resistance and genotypes. Here, amplified fragment length polymorphism (AFLP) profiles and standard antimicrobial resistance profiles were determined in order to characterize a total of 343 S. aureus cow mastitis isolates from two geographically close regions of Switzerland and France. AFLP profiles revealed similar population compositions in the two regions, with 4 major clusters (C8, C20, C97, and C151), but the proportions of isolates in each cluster significantly diverged between the two countries (P = 9.2 × 10⁻⁹). Antimicrobial resistance was overall low (< 5% resistance to all therapeutically relevant molecules), with the exception of penicillin resistance, which was detected in 26% of the isolates. Penicillin resistance proportions differed between clusters, with only 1 to 2% of resistance associated with C20 and C151 and up to 70% associated with bovine C97. The prevalence of C20 and C8 was unexpectedly high and requires further investigation into the mechanism of adaptation to the bovine host. The strong association of penicillin resistance with few clusters highlights the fact that the knowledge of local epidemiology is essential for rational choices of antimicrobial treatment in the absence of susceptibility testing. Taken together, these observations argue in favor of more routine scrutiny of antimicrobial resistance and antibiotic-resistant clones in cattle and the farm environment.

The prediction of speed and incline in outdoor running in humans using accelerometry.

PURPOSE: To explore whether triaxial accelerometric measurements can be utilized to accurately assess speed and incline of running in free-living conditions. METHODS: Body accelerations during running were recorded at the lower back and at the heel by a portable data logger in 20 human subjects, 10 men, and 10 women. After parameterizing body accelerations, two neural networks were designed to recognize each running pattern and calculate speed and incline. Each subject ran 18 times on outdoor roads at various speeds and inclines; 12 runs were used to calibrate the neural networks whereas the 6 other runs were used to validate the model. RESULTS: A small difference between the estimated and the actual values was observed: the square root of the mean square error (RMSE) was 0.12 m x s(-1) for speed and 0.014 radiant (rad) (or 1.4% in absolute value) for incline. Multiple regression analysis allowed accurate prediction of speed (RMSE = 0.14 m x s(-1)) but not of incline (RMSE = 0.026 rad or 2.6% slope). CONCLUSION: Triaxial accelerometric measurements allows an accurate estimation of speed of running and incline of terrain (the latter with more uncertainty). This will permit the validation of the energetic results generated on the treadmill as applied to more physiological unconstrained running conditions.

Validated prediction of clinical outcome in sarcomas and multiple types of cancer on the basis of a gene expression signature related to genome complexity.

Sarcomas are heterogeneous and aggressive mesenchymal tumors. Histological grading has so far been the best predictor for metastasis-free survival, but it has several limitations, such as moderate reproducibility and poor prognostic value for some histological types. To improve patient grading, we performed genomic and expression profiling in a training set of 183 sarcomas and established a prognostic gene expression signature, complexity index in sarcomas (CINSARC), composed of 67 genes related to mitosis and chromosome management. In a multivariate analysis, CINSARC predicts metastasis outcome in the training set and in an independent 127 sarcomas validation set. It is superior to the Fédération Francaise des Centres de Lutte Contre le Cancer grading system in determining metastatic outcome for sarcoma patients. Furthermore, it also predicts outcome for gastrointestinal stromal tumors (GISTs), breast carcinomas and lymphomas. Application of the signature will permit more selective use of adjuvant therapies for people with sarcomas, leading to decreased iatrogenic morbidity and improved outcomes for such individuals.

Novel methods improve prediction of species' distributions from occurrence data

Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.

A link between eumelanism and calcium physiology in the barn owl.

In many animals, melanin-based coloration is strongly heritable and is largely insensitive to the environment and body condition. According to the handicap principle, such a trait may not reveal individual quality because the production of different melanin-based colorations often entails similar costs. However, a recent study showed that the production of eumelanin pigments requires relatively large amounts of calcium, potentially implying that melanin-based coloration is associated with physiological processes requiring calcium. If this is the case, eumelanism may be traded-off against other metabolic processes that require the same elements. We used a correlative approach to examine, for the first time, this proposition in the barn owl, a species in which individuals vary in the amount, size, and blackness of eumelanic spots. For this purpose, we measured calcium concentration in the left humerus of 85 dead owls. Results showed that the humeri of heavily spotted individuals had a higher concentration of calcium. This suggests either that plumage spottiness signals the ability to absorb calcium from the diet for both eumelanin production and storage in bones, or that lightly spotted individuals use more calcium for metabolic processes at the expense of calcium storage in bones. Our study supports the idea that eumelanin-based coloration is associated with a number of physiological processes requiring calcium.

Improving the prediction of plant species distribution and community composition by adding edaphic to topo-climatic variables

Questions Soil properties have been widely shown to influence plant growth and distribution. However, the degree to which edaphic variables can improve models based on topo-climatic variables is still unclear. In this study, we tested the roles of seven edaphic variables, namely (1) pH; (2) the content of nitrogen and of (3) phosphorus; (4) silt; (5) sand; (6) clay and (7) carbon-to-nitrogen ratio, as predictors of species distribution models in an edaphically heterogeneous landscape. We also tested how the respective influence of these variables in the models is linked to different ecological and functional species characteristics. Location The Western Alps, Switzerland. Methods With four different modelling techniques, we built models for 115 plant species using topo-climatic variables alone and then topo-climatic variables plus each of the seven edaphic variables, one at a time. We evaluated the contribution of each edaphic variable by assessing the change in predictive power of the model. In a second step, we evaluated the importance of the two edaphic variables that yielded the largest increase in predictive power in one final set of models for each species. Third, we explored the change in predictive power and the importance of variables across plant functional groups. Finally, we assessed the influence of the edaphic predictors on the prediction of community composition by stacking the models for all species and comparing the predicted communities with the observed community. Results Among the set of edaphic variables studied, pH and nitrogen content showed the highest contributions to improvement of the predictive power of the models, as well as the predictions of community composition. When considering all topo-climatic and edaphic variables together, pH was the second most important variable after degree-days. The changes in model results caused by edaphic predictors were dependent on species characteristics. The predictions for the species that have a low specific leaf area, and acidophilic preferences, tolerating low soil pH and high humus content, showed the largest improvement by the addition of pH and nitrogen in the model. Conclusions pH was an important predictor variable for explaining species distribution and community composition of the mountain plants considered in our study. pH allowed more precise predictions for acidophilic species. This variable should not be neglected in the construction of species distribution models in areas with contrasting edaphic conditions.

Prediction of difficult intubation with advanced face recognition techniques: a preliminary study

Introduction: Difficult tracheal intubation remains a constant and significant source of morbidity and mortality in anaesthetic practice. Insufficient airway assessment in the preoperative period continues to be a major cause of unanticipated difficult intubation. Although many risk factors have already been identified, preoperative airway evaluation is not always regarded as a standard procedure and the respective weight of each risk factor remains unclear. Moreover the predictive scores available are not sensitive, moderately specific and often operator-dependant. In order to improve the preoperative detection of patients at risk for difficult intubation, we developed a system for automated and objective evaluation of morphologic criteria of the face and neck using video recordings and advanced techniques borrowed from face recognition. Method and results: Frontal video sequences were recorded in 5 healthy volunteers. During the video recording, subjects were requested to perform maximal flexion-extension of the neck and to open wide the mouth with tongue pulled out. A robust and real-time face tracking system was then applied, allowing to automatically identify and map a grid of 55 control points on the face, which were tracked during head motion. These points located important features of the face, such as the eyebrows, the nose, the contours of the eyes and mouth, and the external contours, including the chin. Moreover, based on this face tracking, the orientation of the head could also be estimated at each frame of the video sequence. Thus, we could infer for each frame the pitch angle of the head pose (related to the vertical rotation of the head) and obtain the degree of head extension. Morphological criteria used in the most frequent cited predictive scores were also extracted, such as mouth opening, degree of visibility of the uvula or thyreo-mental distance. Discussion and conclusion: Preliminary results suggest the high feasibility of the technique. The next step will be the application of the same automated and objective evaluation to patients who will undergo tracheal intubation. The difficulties related to intubation will be then correlated to the biometric characteristics of the patients. The objective in mind is to analyze the biometrics data with artificial intelligence algorithms to build a highly sensitive and specific predictive test.

Alcohol-attributable injuries in admissions to a swiss emergency room--an analysis of the link between volume of drinking, drinking patterns, and preattendance drinking.

BACKGROUND: An association between alcohol consumption and injury is clearly established from volume of drinking, heavy episodic drinking (HED), and consumption before injury. Little is known, however, about how their interaction raises risk of injury and what combination of factors carries the highest risk. This study explores which of 11 specified groups of drinkers (a) are at high risk and (b) contribute most to alcohol-attributable injuries. METHODS: In all, 8,736 patients, of whom 5,077 were injured, admitted to the surgical ward of the emergency department of Lausanne University Hospital between January 1, 2003, and June 30, 2004, were screened for alcohol use. Eleven groups were constructed on the basis of usual patterns of intake and preattendance drinking. Odds ratios (ORs) comparing injured and noninjured were derived, and alcohol-attributable fractions of injuries were calculated from ORs and prevalence of exposure groups. RESULTS: Risk of injury increased with volume of drinking, HED, and preattendance drinking. For both sexes, the highest risk was associated with low intake, HED, and 4 (women), 5 (men), or more drinks before injury. At the same level of preattendance drinking, high-volume drinkers were at lower risk than low-volume drinkers. In women, the group of low-risk non-HED drinkers taking fewer than 4 drinks suffered 47.5% of the alcohol-attributable injuries in contrast to only 20.4% for men. Low-volume male drinkers with HED had more alcohol-attributable injuries than that of low-volume female drinkers with HED (46.9% vs 23.2%). CONCLUSIONS: Although all groups of drinkers are at increased risk of alcohol-related injury, those who usually drink little but on occasion heavily are at particular risk. The lower risk of chronic heavy drinkers may be due to higher tolerance of alcohol. Prevention should thus target heavy-drinking occasions. Low-volume drinking women without HED and with only little preattendance drinking experienced a high proportion of injuries; such women would be well advised to drink very little or to take other special precautions in risky circumstances.

Development and validation of a clinical prediction rule for chest wall syndrome in primary care

Le "Chest wall syndrome" (CWS) est défini comme étant une source bénigne de douleurs thoraciques, localisées sur la paroi thoracique antérieure et provoquées par une affection musculosquelettique. Le CWS représente la cause la plus fréquente de douleurs thoraciques en médecine de premier recours. Le but de cette étude est de développer et valider un score de prédiction clinique pour le CWS. Une revue de la littérature a d'abord été effectuée, d'une part pour savoir si un tel score existait déjà, et d'autre part pour retrouver les variables décrites comme étant prédictives d'un CWS. Le travail d'analyse statistique a été effectué avec les données issues d'une cohorte clinique multicentrique de patients qui avaient consulté en médecine de premier recours en Suisse romande avec une douleur thoracique (59 cabinets, 672 patients). Un diagnostic définitif avait été posé à 12 mois de suivi. Les variables pertinentes ont été sélectionnées par analyses bivariées, et le score de prédiction clinique a été développé par régression logistique multivariée. Une validation externe de ce score a été faite en utilisant les données d'une cohorte allemande (n= 1212). Les analyses bivariées ont permis d'identifier 6 variables caractérisant le CWS : douleur thoracique (ni rétrosternale ni oppressive), douleur en lancées, douleur bien localisée, absence d'antécédent de maladie coronarienne, absence d'inquiétude du médecin et douleur reproductible à la palpation. Cette dernière variable compte pour 2 points dans le score, les autres comptent pour 1 point chacune; le score total s'étend donc de 0 à 7 points. Dans la cohorte de dérivation, l'aire sous la courbe sensibilité/spécificité (courbe ROC) est de 0.80 (95% de l'intervalle de confiance : 0.76-0.83). Avec un seuil diagnostic de > 6 points, le score présente 89% de spécificité et 45% de sensibilité. Parmi tous les patients qui présentaient un CWS (n = 284), 71% (n = 201) avaient une douleur reproductible à la palpation et 45% (n= 127) sont correctement diagnostiqués par le score. Pour une partie (n = 43) de ces patients souffrant de CWS et correctement classifiés, 65 investigations complémentaires (30 électrocardiogrammes, 16 radiographies du thorax, 10 analyses de laboratoire, 8 consultations spécialisées, et une tomodensitométrie thoracique) avaient été réalisées pour parvenir au diagnostic. Parmi les faux positifs (n = 41), on compte trois angors stables (1.8% de tous les positifs). Les résultats de la validation externe sont les suivants : une aire sous la courbe ROC de 0.76 (95% de l'intervalle de confiance : 0.73-0.79) avec une sensibilité de 22% et une spécificité de 93%. Ce score de prédiction clinique pour le CWS constitue un complément utile à son diagnostic, habituellement obtenu par exclusion. En effet, pour les 127 patients présentant un CWS et correctement classifiés par notre score, 65 investigations complémentaires auraient pu être évitées. Par ailleurs, la présence d'une douleur thoracique reproductible à la palpation, bien qu'étant sa plus importante caractéristique, n'est pas pathognomonique du CWS.