Predicting potential distribution of the jaguar (Panthera onca) in Mexico: identification of priority areas for conservation

Aim The jaguar, Panthera onca, is a species of global conservation concern. In Mexico, the northernmost part of its distribution range, its conservation status, is particularly critical, while its potential and actual distribution is poorly known. We propose an ensemble model (EM) of the potential distribution for the jaguar in Mexico and identify the priority areas for conservation.Location Mexico.Methods We generated our EM based on three presence-only methods (Ecological Niche Factor Analysis, Mahalanobis distance, Maxent) and considering environmental, biological and anthropogenic factors. We used this model to evaluate the efficacy of the existing Mexican protected areas (PAs), to evaluate the adequacy of the jaguar conservation units (JCUs) and to propose new areas that should be considered for conservation and management of the species in Mexico.Results Our results outline that 16% of Mexico (c. 312,000 km2) can be considered as suitable for the presence of the jaguar. Furthermore, 13% of the suitable areas are included in existing PAs and 14% are included in JCUs (Sanderson et al., 2002).Main conclusions Clearly much more should be carried out to establish a proactive conservation strategy. Based on our results, we propose here new jaguar conservation and management areas that are important for a nationwide conservation blueprint.

The impact of fasting on the interpretation of triglyceride levels for predicting myocardial infarction risk in HIV-positive individuals: the D:A:D study.

We assessed whether fasting modifies the prognostic value of these measurements for the risk of myocardial infarction (MI). Analyses used mixed effect models and Poisson regression. After confounders were controlled for, fasting triglyceride levels were, on average, 0.122 mmol/L lower than nonfasting levels. Each 2-fold increase in the latest triglyceride level was associated with a 38% increase in MI risk (relative rate, 1.38; 95% confidence interval, 1.26-1.51); fasting status did not modify this association. Our results suggest that it may not be necessary to restrict analyses to fasting measurements when considering MI risk.

Predicting the need for ditch network maintenance in drained peatland sites in Finland

Kunnostusojitustarpeen ennustaminen ojitusalueilla

Predicting future distributions of mountain plants under climate change: does dispersal capacity matter?

Many studies have investigated the impacts that climate change could potentially have on the distribution of plant species, but few have attempted to constrain projections through plant dispersal limitations. Instead, most studies published so far have been using the simplification of considering dispersal as either unlimited or null. However, depending on a species' dispersal capacity, landscape fragmentation, and the rate of climatic change, these assumptions can lead to serious over- or underestimation of a species' future distribution. To quantify the discrepancies between unlimited, realistic, and no dispersal scenarios, we carried out projections of future distribution over the 21st century for 287 mountain plant species in a study area of the Western Swiss Alps. For each species, simulations were run for four dispersal scenarios (unlimited dispersal, no dispersal, realistic dispersal and realistic dispersal with long-distance dispersal events) and under four climate change scenarios. Although simulations accounting for realistic dispersal limitations did significantly differ from those considering dispersal as unlimited or null in terms of projected future distribution, using the unlimited dispersal simplification nevertheless provided good approximations for species extinctions under more moderate climate change scenarios. Overall, simulations accounting for dispersal limitations produced, for our mountainous study area, results that were significantly closer to unlimited dispersal than to no dispersal. Finally, analyzing the temporal pattern of species extinctions over the entire 21st century showed that, due to the possibility of a large number of species shifting their distribution to higher elevation, important species extinctions for our study area might not occur before the 2080-2100 time periods.

Predicting the deleterious effects of mutation load in fragmented populations.

Human-induced habitat fragmentation constitutes a major threat to biodiversity. Both genetic and demographic factors combine to drive small and isolated populations into extinction vortices. Nevertheless, the deleterious effects of inbreeding and drift load may depend on population structure, migration patterns, and mating systems and are difficult to predict in the absence of crossing experiments. We performed stochastic individual-based simulations aimed at predicting the effects of deleterious mutations on population fitness (offspring viability and median time to extinction) under a variety of settings (landscape configurations, migration models, and mating systems) on the basis of easy-to-collect demographic and genetic information. Pooling all simulations, a large part (70%) of variance in offspring viability was explained by a combination of genetic structure (F(ST)) and within-deme heterozygosity (H(S)). A similar part of variance in median time to extinction was explained by a combination of local population size (N) and heterozygosity (H(S)). In both cases the predictive power increased above 80% when information on mating systems was available. These results provide robust predictive models to evaluate the viability prospects of fragmented populations.

KRAS mutation testing for predicting response to anti-EGFR therapy for colorectal carcinoma: proposal for an European quality assurance program.

Novel therapeutic agents targeting the epidermal growth factor receptor (EGFR) have improved outcomes for patients with colorectal carcinoma. However, these therapies are effective only in a subset of patients. Activating mutations in the KRAS gene are found in 30-40% of colorectal tumors and are associated with poor response to anti-EGFR therapies. Thus, KRAS mutation status can predict which patient may or may not benefit from anti-EGFR therapy. Although many diagnostic tools have been developed for KRAS mutation analysis, validated methods and standardized testing procedures are lacking. This poses a challenge for the optimal use of anti-EGFR therapies in the management of colorectal carcinoma. Here we review the molecular basis of EGFR-targeted therapies and the resistance to treatment conferred by KRAS mutations. We also present guideline recommendations and a proposal for a European quality assurance program to help ensure accuracy and proficiency in KRAS mutation testing across the European Union.

Predicting present and future intra-specific genetic structure through niche hindcasting across 24 millennia.

Paleoclimatic reconstructions coupled with species distribution models and identification of extant spatial genetic structure have the potential to provide insights into the demographic events that shape the distribution of intra-specific genetic variation across time. Using the globeflower Trollius europaeus as a case-study, we combined (1) Amplified Fragment Length Polymorphisms, (2) suites of 1000-years stepwise hindcasted species distributions and (3) a model of diffusion through time over the last 24,000 years, to trace the spatial dynamics that most likely fits the species' current genetic structure. We show that the globeflower comprises four gene pools in Europe which, from the dry period preceding the Last Glacial Maximum, dispersed while tracking the conditions fitting its climatic niche. Among these four gene pools, two are predicted to experience drastic range retraction in the near future. Our interdisciplinary approach, applicable to virtually any taxon, is an advance in inferring how climate change impacts species' genetic structures.

Predicting the mating system from phenotypic correlations between life-history and sperm quality traits in the Alpine whitefish Coregonus zugensis

The mating behavior and reproductive strategies of Alpine whitefish like Coregonus zugensis (Nusslin) are poorly understood, probably because they spawn in deep water where direct observations are difficult. In this study, we interpret life-history and sperm quality traits of fish that we caught from their spawning place. We found that males invest heavily into gonadal tissue (up to 5.6% of their body weight), which is, in comparison to other fish, consistent with external fertilization, distinct pairing and moderate to high communal spawning, or no pairing and low to moderate communal spawning. Sperm competition theory and recent experimental studies on other salmonids predict that males optimize ejaculate characteristics in relation to the costs of sperm and the level of competition they have to expect: dominant males are predicted to invest less into ejaculate quality and to have slower spermatozoa than subdominant males. We found that spermatozoa of older males are slower than those of younger males. Moreover, older males have larger breeding tubercles, a secondary sexual trait that has, in some previous studies, been found to be linked to good condition and to good genetic quality. Our results suggest that C. zugensis has age-linked reproductive strategies, that multimale spawning is common, i.e., that sperm competition plays a significant role, and that older males are on average dominant over younger males at the spawning place.

Salting kinetics and salt diffusivities in farmed Pantanal caiman muscle

The legal Pantanal caiman (Caiman crocodilus yacare) farming, in Brazil, has been stimulated and among meat preservation techniques the salting process is a relatively simple and low-cost method. The objective of this work was to study the sodium chloride diffusion kinetics in farmed caiman muscle during salting. Limited volumes of brine were employed, with salting essays carried at 3, 4 and 5 brine/muscle ratios, at 15%, 20% and 25% w/w brine concentrations, and brine temperatures of 10, 15 and 20ºC. The analytical solution of second Fick's law considering one-dimensional diffusion through an infinite slab in contact with a well-stirred solution of limited volume was used to calculate effective salt diffusion coefficients and to predict the sodium chloride content in the fillets. A good agreement was obtained between the considered analytical model and experimental data. Salt diffusivities in fillets were found to be in the range of 0.47x10-10 to 9.62x10-10 m²/s.

Predicting current and future spatial community patterns of plant functional traits

Community-level patterns of functional traits relate to community assembly and ecosystem functioning. By modelling the changes of different indices describing such patterns - trait means, extremes and diversity in communities - as a function of abiotic gradients, we could understand their drivers and build projections of the impact of global change on the functional components of biodiversity. We used five plant functional traits (vegetative height, specific leaf area, leaf dry matter content, leaf nitrogen content and seed mass) and non-woody vegetation plots to model several indices depicting community-level patterns of functional traits from a set of abiotic environmental variables (topographic, climatic and edaphic) over contrasting environmental conditions in a mountainous landscape. We performed a variation partitioning analysis to assess the relative importance of these variables for predicting patterns of functional traits in communities, and projected the best models under several climate change scenarios to examine future potential changes in vegetation functional properties. Not all indices of trait patterns within communities could be modelled with the same level of accuracy: the models for mean and extreme values of functional traits provided substantially better predictive accuracy than the models calibrated for diversity indices. Topographic and climatic factors were more important predictors of functional trait patterns within communities than edaphic predictors. Overall, model projections forecast an increase in mean vegetation height and in mean specific leaf area following climate warming. This trend was important at mid elevation particularly between 1000 and 2000 m asl. With this study we showed that topographic, climatic and edaphic variables can successfully model descriptors of community-level patterns of plant functional traits such as mean and extreme trait values. However, which factors determine the diversity of functional traits in plant communities remains unclear and requires more investigations.

Evaluation of a multicomponent worksite health promotion program for cardiovascular risk factors-correcting for the regression towards the mean effect.

BACKGROUND: We assessed the impact of a multicomponent worksite health promotion program for0 reducing cardiovascular risk factors (CVRF) with short intervention, adjusting for regression towards the mean (RTM) affecting such nonexperimental study without control group. METHODS: A cohort of 4,198 workers (aged 42 +/- 10 years, range 16-76 years, 27% women) were analyzed at 3.7-year interval and stratified by each CVRF risk category (low/medium/high blood pressure [BP], total cholesterol [TC], body mass index [BMI], and smoking) with RTM and secular trend adjustments. Intervention consisted of 15 min CVRF screening and individualized counseling by health professionals to medium- and high-risk individuals, with eventual physician referral. RESULTS: High-risk groups participants improved diastolic BP (-3.4 mm Hg [95%CI: -5.1, -1.7]) in 190 hypertensive patients, TC (-0.58 mmol/l [-0.71, -0.44]) in 693 hypercholesterolemic patients, and smoking (-3.1 cig/day [-3.9, -2.3]) in 808 smokers, while systolic BP changes reflected RTM. Low-risk individuals without counseling deteriorated TC and BMI. Body weight increased uniformly in all risk groups (+0.35 kg/year). CONCLUSIONS: In real-world conditions, short intervention program participants in high-risk groups for diastolic BP, TC, and smoking improved their CVRF, whereas low-risk TC and BMI groups deteriorated. Future programs may include specific advises to low-risk groups to maintain a favorable CVRF profile.

An approach to predicting bowing control parameter contours in violin performance

We present a machine learning approach to modeling bowing control parametercontours in violin performance. Using accurate sensing techniqueswe obtain relevant timbre-related bowing control parameters such as bowtransversal velocity, bow pressing force, and bow-bridge distance of eachperformed note. Each performed note is represented by a curve parametervector and a number of note classes are defined. The principal componentsof the data represented by the set of curve parameter vectors are obtainedfor each class. Once curve parameter vectors are expressed in the new spacedefined by the principal components, we train a model based on inductivelogic programming, able to predict curve parameter vectors used for renderingbowing controls. We evaluate the prediction results and show the potentialof the model by predicting bowing control parameter contours from anannotated input score.

Clinical Prognostic Factors Predicting Outcomes Of Patients With Recurrent Gbm And Nomograms

BACKGROUND: Prognostic models and nomograms were recently developed to predict survival of patients with newly diagnosed glioblastoma multiforme (GBM).1 To improve predictions, models should be updated with the most recent patient and disease information. Nomograms predicting patient outcome at the time of disease progression are required. METHODS: Baseline information from 299 patients with recurrent GBM recruited in 8 phase I or II trials of the EORTC Brain Tumor Group was used to evaluate clinical parameters as prognosticators of patient outcome. Univariate (log rank) and multivariate (Cox models) analyses were made to assess the ability of patients' characteristics (age, sex, performance status [WHO PS], and MRC neurological deficit scale), disease history (prior treatments, time since last treatment or initial diagnosis, and administration of steroids or antiepileptics) and disease characteristics (tumor size and number of lesions) to predict progression free survival (PFS) and overall survival (OS). Bootstrap technique was used for models internal validation. Nomograms were computed to provide individual patients predictions. RESULTS: Poor PS and more than 1 lesion had a significant prognostic impact for both PFS and OS. Antiepileptic drug use was significantly associated with worse PFS. Larger tumors (split by the median of the largest tumor diameter >42.5 mm) and steroid use had shorter OS. Age, sex, neurologic deficit, prior therapies, and time since last therapy or initial diagnosis did not show independent prognostic value for PFS or OS. CONCLUSIONS: This analysis confirms that PS but not age is a major prognostic factor for PFS and OS. Multiple or large tumors and the need to administer steroids significantly increase the risk of progression and death. Nomograms at the recurrence could be used to obtain accurate predictions for the design of new targeted therapy trials or retrospective analyses. (1. T. Gorlia et al., Nomograms for predicting survival of patients with newly diagnosed glioblastoma. Lancet Oncol 9 (1): 29-38, 2008.)