Environmental variables, habitat discontinuity and life history shaping the genetic structure of Pomatoschistus marmoratus

Coastal lagoons are semi-isolated ecosystems exposed to wide fluctuations of environmental conditions and showing habitat fragmentation. These features may play an important role in separating species into different populations, even at small spatial scales. In this study, we evaluate the concordance between mitochondrial (previous published data) and nuclear data analyzing the genetic variability of Pomatoschistus marmoratus in five localities, inside and outside the Mar Menor coastal lagoon (SE Spain) using eight microsatellites. High genetic diversity and similar levels of allele richness were observed across all loci and localities, although significant genic and genotypic differentiation was found between populations inside and outside the lagoon. In contrast to the FST values obtained from previous mitochondrial DNA analyses (control region), the microsatellite data exhibited significant differentiation among samples inside the Mar Menor and between lagoonal and marine samples. This pattern was corroborated using Cavalli-Sforza genetic distances. The habitat fragmentation inside the coastal lagoon and among lagoon and marine localities could be acting as a barrier to gene flow and contributing to the observed genetic structure. Our results from generalized additive models point a significant link between extreme lagoonal environmental conditions (mainly maximum salinity) and P. marmoratus genetic composition. Thereby, these environmental features could be also acting on genetic structure of coastal lagoon populations of P. marmoratus favoring their genetic divergence. The mating strategy of P. marmoratus could be also influencing our results obtained from mitochondrial and nuclear DNA. Therefore, a special consideration must be done in the selection of the DNA markers depending on the reproductive strategy of the species

Analysis of Male Pheromones That Accelerate Female Reproductive Organ Development

Male odors can influence a female's reproductive physiology. In the mouse, the odor of male urine results in an early onset of female puberty. Several volatile and protein pheromones have previously been reported to each account for this bioactivity. Here we bioassay inbred BALB/cJ females to study pheromone-accelerated uterine growth, a developmental hallmark of puberty. We evaluate the response of wild-type and mutant mice lacking a specialized sensory transduction channel, TrpC2, and find TrpC2 function to be necessary for pheromone-mediated uterine growth. We analyze the relative effectiveness of pheromones previously identified to accelerate puberty through direct bioassay and find none to significantly accelerate uterine growth in BALB/cJ females. Complementary to this analysis, we have devised a strategy of partial purification of the uterine growth bioactivity from male urine and applied it to purify bioactivity from three different laboratory strains. The biochemical characteristics of the active fraction of all three strains are inconsistent with that of previously known pheromones. When directly analyzed, we are unable to detect previously known pheromones in urine fractions that generate uterine growth. Our analysis indicates that pheromones emitted by males to advance female puberty remain to be identified

Quantifying uncertainty, variability and likelihood for ordinary differential equation models

<p>Abstract</p> <p>Background</p> <p>In many applications, ordinary differential equation (ODE) models are subject to uncertainty or variability in initial conditions and parameters. Both, uncertainty and variability can be quantified in terms of a probability density function on the state and parameter space.</p> <p>Results</p> <p>The partial differential equation that describes the evolution of this probability density function has a form that is particularly amenable to application of the well-known method of characteristics. The value of the density at some point in time is directly accessible by the solution of the original ODE extended by a single extra dimension (for the value of the density). This leads to simple methods for studying uncertainty, variability and likelihood, with significant advantages over more traditional Monte Carlo and related approaches especially when studying regions with low probability.</p> <p>Conclusions</p> <p>While such approaches based on the method of characteristics are common practice in other disciplines, their advantages for the study of biological systems have so far remained unrecognized. Several examples illustrate performance and accuracy of the approach and its limitations.</p

Massive mortality of invasive bivalves as a potential resource subsidy for the adjacent terrestrial food web

Large-scale mortality of invasive bivalves was observed in the River Danube basin in the autumn of 2011 due to a particularly low water discharge. The aim of this study was to quantify and compare the biomass of invasive and native bivalve die-offs amongst eight different sites and to assess the potential role of invasive bivalve die-offs as a resource subsidy for the adjacent terrestrial food web. Invasive bivalve die-offs dominated half of the study sites and their highest density and biomass were recorded at the warm water effluent. The density and biomass values recorded in this study are amongst the highest values recorded for aquatic ecosystems and show that a habitat affected by heated water can sustain an extremely high biomass of invasive bivalves. These mortalities highlight invasive bivalves as a major resource subsidy, possibly contributing remarkable amounts of nutrients and energy to the adjacent terrestrial ecosystem. Given the widespread occurrence of these invasive bivalves and the predicted increase in the frequency and intensity of extreme climatic events, the ecological impacts generated by their massive mortalities should be taken into account in other geographical areas as well.The authors are grateful to David Strayer for valuable comments on a previous version of the manuscript. Special thanks to the Danube-Ipoly National Park for the help in field work. Ronaldo Sousa was supported by the project "ECOIAS" funded by the Portuguese Foundation for the Science and the Technology and COMPETE funds (contract: PTDC/AAC-AMB/116685/2010)

Local and Global Effects of Climate on Dengue Transmission in Puerto Rico

The four dengue viruses, the agents of dengue fever and dengue hemorrhagic fever in humans, are transmitted predominantly by the mosquito Aedes aegypti. The abundance and the transmission potential of Ae. aegypti are influenced by temperature and precipitation. While there is strong biological evidence for these effects, empirical studies of the relationship between climate and dengue incidence in human populations are potentially confounded by seasonal covariation and spatial heterogeneity. Using 20 years of data and a statistical approach to control for seasonality, we show a positive and statistically significant association between monthly changes in temperature and precipitation and monthly changes in dengue transmission in Puerto Rico. We also found that the strength of this association varies spatially, that this variation is associated with differences in local climate, and that this relationship is consistent with laboratory studies of the impacts of these factors on vector survival and viral replication. These results suggest the importance of temperature and precipitation in the transmission of dengue viruses and suggest a reason for their spatial heterogeneity. Thus, while dengue transmission may have a general system, its manifestation on a local scale may differ from global expectations

Second Order Dimensionality Reduction Using Minimum and Maximum Mutual Information Models

Conventional methods used to characterize multidimensional neural feature selectivity, such as spike-triggered covariance (STC) or maximally informative dimensions (MID), are limited to Gaussian stimuli or are only able to identify a small number of features due to the curse of dimensionality. To overcome these issues, we propose two new dimensionality reduction methods that use minimum and maximum information models. These methods are information theoretic extensions of STC that can be used with non-Gaussian stimulus distributions to find relevant linear subspaces of arbitrary dimensionality. We compare these new methods to the conventional methods in two ways: with biologically-inspired simulated neurons responding to natural images and with recordings from macaque retinal and thalamic cells responding to naturalistic time-varying stimuli. With non-Gaussian stimuli, the minimum and maximum information methods significantly outperform STC in all cases, whereas MID performs best in the regime of low dimensional feature spaces

Pain coping skills training for African Americans with osteoarthritis (STAART): study protocol of a randomized controlled trial

Background: African Americans bear a disproportionate burden of osteoarthritis (OA), with higher prevalence rates, more severe pain, and more functional limitations. One key barrier to addressing these disparities has been limited engagement of African Americans in the development and evaluation of behavioral interventions for management of OA. Pain Coping Skills Training (CST) is a cognitive-behavioral intervention with shown efficacy to improve OA-related pain and other outcomes. Emerging data indicate pain CST may be a promising intervention for reducing racial disparities in OA symptom severity. However, there are important gaps in this research, including incorporation of stakeholder perspectives (e.g. cultural appropriateness, strategies for implementation into clinical practice) and testing pain CST specifically among African Americans with OA. This study will evaluate the effectiveness of a culturally enhanced pain CST program among African Americans with OA. Methods/Design: This is a randomized controlled trial among 248 participants with symptomatic hip or knee OA, with equal allocation to a pain CST group and a wait list (WL) control group. The pain CST program incorporated feedback from patients and other stakeholders and involves 11 weekly telephone-based sessions. Outcomes are assessed at baseline, 12 weeks (primary time point), and 36 weeks (to assess maintenance of treatment effects). The primary outcome is the Western Ontario and McMaster Universities Osteoarthritis Index, and secondary outcomes include self-efficacy, pain coping, pain interference, quality of life, depressive symptoms, and global assessment of change. Linear mixed models will be used to compare the pain CST group to the WL control group and explore whether participant characteristics are associated with differential improvement in the pain CST program. This research is in compliance with the Helsinki Declaration and was approved by the Institutional Review Boards of the University of North Carolina at Chapel Hill, Durham Veterans Affairs Medical Center, East Carolina University, and Duke University Health System. Discussion: This culturally enhanced pain CST program could have a substantial impact on outcomes for African Americans with OA and may be a key strategy in the reduction of racial health disparities.Funded by Patient-Centered Outcomes Research Institute (PCORI) Award (AD-1408-19519)

Gallbladder Cancer Predisposition: A Multigenic Approach to DNA-Repair, Apoptotic and Inflammatory Pathway Genes

Gallbladder cancer (GBC) is a multifactorial disease with complex interplay between multiple genetic variants. We performed Classification and Regression Tree Analysis (CART) and Grade of Membership (GoM) analysis to identify combinations of alleles among the DNA repair, inflammatory and apoptotic pathway genetic variants in modifying the risk for GBC. We analyzed 16 polymorphisms in 8 genes involved in DNA repair, apoptotic and inflammatory pathways to find out combinations of genetic variants contributing to GBC risk. The genes included in the study were XRCC1, OGG1, ERCC2, MSH2, CASP8, TLR2, TLR4 and PTGS2. Single locus analysis by logistic regression showed association of MSH2 IVS1+9G>C (rs2303426), ERCC2 Asp312Asn (rs1799793), OGG1 Ser326Cys (rs1052133), OGG1 IVS4-15C>G (rs2072668), CASP8 -652 6N ins/del (rs3834129), PTGS2 -1195G>A (rs689466), PTGS2 -765G>C (rs20417), TLR4 Ex4+936C>T (rs4986791) and TLR2 –196 to –174del polymorphisms with GBC risk. The CART analysis revealed OGG1 Ser326Cys, and OGG1 IVS4-15C>G polymorphisms as the best polymorphic signature for discriminating between cases and controls. In the GoM analysis, the data was categorized into six sets representing risk for GBC with respect to the investigated polymorphisms. Sets I, II and III described low intrinsic risk (controls) characterized by multiple protective alleles while sets IV, V and VI represented high intrinsic risk groups (GBC cases) characterized by the presence of multiple risk alleles. The CART and GoM analyses also showed the importance of PTGS2 -1195G>A polymorphism in susceptibility to GBC risk. In conclusion, the present multigenic approach can be used to define individual risk profiles for gallbladder cancer in North Indian population