1,822 research outputs found

    Whitebark Pine Stand Condition, Tree Abundance, and Cone Production as Predictors of Visitation by Clark's Nutcracker

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    Accurately quantifying key interactions between species is important for developing effective recovery strategies for threatened and endangered species. Whitebark pine (Pinus albicaulis), a candidate species for listing under the Endangered Species Act, depends on Clark's nutcracker (Nucifraga columbiana) for seed dispersal. As whitebark pine succumbs to exotic disease and mountain pine beetles (Dendroctonus ponderosae), cone production declines, and nutcrackers visit stands less frequently, reducing the probability of seed dispersal.We quantified whitebark pine forest structure, health metrics, and the frequency of nutcracker occurrence in national parks within the Northern and Central Rocky Mountains in 2008 and 2009. Forest health characteristics varied between the two regions, with the northern region in overall poorer health. Using these data, we show that a previously published model consistently under-predicts the proportion of survey hours resulting in nutcracker observations at all cone density levels. We present a new statistical model of the relationship between whitebark pine cone production and the probability of Clark's nutcracker occurrence based on combining data from this study and the previous study.Our model clarified earlier findings and suggested a lower cone production threshold value for predicting likely visitation by nutcrackers: Although nutcrackers do visit whitebark pine stands with few cones, the probability of visitation increases with increased cone production. We use information theoretics to show that beta regression is a more appropriate statistical framework for modeling the relationship between cone density and proportion of survey time resulting in nutcracker observations. We illustrate how resource managers may apply this model in the process of prioritizing areas for whitebark pine restoration

    Use of a Physiologically Based Pharmacokinetic Model for Rats to Study the Influence of Body Fat Mass and Induction of CYP1A2 on the Pharmacokinetics of TCDD

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    2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a highly lipophilic chemical that distributes into adipose tissue, especially at low doses. However, at high doses TCDD sequesters in liver because it induces cytochrome P450 1A2 (CYP1A2) that binds TCDD. A physiologically based pharmacokinetic (PBPK) model was developed that included an inducible elimination rate of TCDD in the Sprague-Dawley rat. Objectives of this work were to characterize the influence of induction of CYP1A2 and adipose tissue mass fraction on the terminal elimination half-life (t(1/2)) of TCDD using this PBPK model. When the model assumes a fixed elimination of TCDD, t(1/2) increases with dose, due to hepatic sequestration. Because experimental data indicate that the t(1/2) of TCDD decreases with dose, the model was modified to include an inducible elimination rate. The PBPK model was then used to compare the t(1/2) after an increase of adipose tissue mass fraction from 6.9 to 70%. The model suggests that at low exposures, increasing adipose tissue mass increases the terminal t(1/2). However, at higher exposures, as CYP1A2 is induced, the relationship between adipose tissue mass and t(1/2) reaches a plateau. This demonstrates that an inducible elimination rate is needed in a PBPK model in order to describe the pharmacokinetics of TCDD. At low exposures these models are more sensitive to parameters related to partitioning into adipose tissue

    Filariasis of the Axilla in a Patient Returning from Travel Abroad: A Case Report

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    Background: The term filariasis comprises a group of parasitic infections caused by helminths belonging to different genera in the superfamily Filaroidea. The human parasites occur mainly in tropical and subtropical regions, but filariae are also found in temperate climates, where they can infect wild and domestic animals. Humans are rarely infected by these zoonotic parasites. Patients and Methods: A 55-year-old patient presented with a new-onset, subcutaneous, non-tender palpable mass in the right axilla. Ultrasonography showed a 1.3-cm, solid, singular encapsulated node. Sonography of the breast on both sides, axilla and lymphatic drainage on the left side, lymphatic drainage on the right side, and mammography on both sides were without pathological findings. The node was excised under local anesthesia as the patient refused minimal invasive biopsy. Results: On histopathological examination, the tail of a parasite of the group of filariae was found. The patient revealed that she had stayed in Africa and Malaysia for professional reasons. 6 months before the time of diagnosis, she had also suffered from a fever and poor general condition after a trip abroad. The patient was referred for further treatment to the Institute for Tropical Medicine at the University of Dusseldorf, where a treatment with ivermectin was conducted on the basis of positive staining with antibodies against filariae. Conclusion: Our case demonstrates the importance of interdisciplinary collaboration between breast center, pathology, and other specialties such as microbiology and tropical medicine

    Stochastic steps in secondary active sugar transport.

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    Secondary active transporters, such as those that adopt the leucine-transporter fold, are found in all domains of life, and they have the unique capability of harnessing the energy stored in ion gradients to accumulate small molecules essential for life as well as expel toxic and harmful compounds. How these proteins couple ion binding and transport to the concomitant flow of substrates is a fundamental structural and biophysical question that is beginning to be answered at the atomistic level with the advent of high-resolution structures of transporters in different structural states. Nonetheless, the dynamic character of the transporters, such as ion/substrate binding order and how binding triggers conformational change, is not revealed from static structures, yet it is critical to understanding their function. Here, we report a series of molecular simulations carried out on the sugar transporter vSGLT that lend insight into how substrate and ions are released from the inward-facing state of the transporter. Our simulations reveal that the order of release is stochastic. Functional experiments were designed to test this prediction on the human homolog, hSGLT1, and we also found that cytoplasmic release is not ordered, but we confirmed that substrate and ion binding from the extracellular space is ordered. Our findings unify conflicting published results concerning cytoplasmic release of ions and substrate and hint at the possibility that other transporters in the superfamily may lack coordination between ions and substrate in the inward-facing state

    Effectiveness and cost-effectiveness of an educational intervention for practice teams to deliver problem focused therapy for insomnia: rationale and design of a pilot cluster randomised trial

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    Background: Sleep problems are common, affecting over a third of adults in the United Kingdom and leading to reduced productivity and impaired health-related quality of life. Many of those whose lives are affected seek medical help from primary care. Drug treatment is ineffective long term. Psychological methods for managing sleep problems, including cognitive behavioural therapy for insomnia (CBTi) have been shown to be effective and cost effective but have not been widely implemented or evaluated in a general practice setting where they are most likely to be needed and most appropriately delivered. This paper outlines the protocol for a pilot study designed to evaluate the effectiveness and cost-effectiveness of an educational intervention for general practitioners, primary care nurses and other members of the primary care team to deliver problem focused therapy to adult patients presenting with sleep problems due to lifestyle causes, pain or mild to moderate depression or anxiety. Methods and design: This will be a pilot cluster randomised controlled trial of a complex intervention. General practices will be randomised to an educational intervention for problem focused therapy which includes a consultation approach comprising careful assessment (using assessment of secondary causes, sleep diaries and severity) and use of modified CBTi for insomnia in the consultation compared with usual care (general advice on sleep hygiene and pharmacotherapy with hypnotic drugs). Clinicians randomised to the intervention will receive an educational intervention (2 × 2 hours) to implement a complex intervention of problem focused therapy. Clinicians randomised to the control group will receive reinforcement of usual care with sleep hygiene advice. Outcomes will be assessed via self-completion questionnaires and telephone interviews of patients and staff as well as clinical records for interventions and prescribing. Discussion: Previous studies in adults have shown that psychological treatments for insomnia administered by specialist nurses to groups of patients can be effective within a primary care setting. This will be a pilot study to determine whether an educational intervention aimed at primary care teams to deliver problem focused therapy for insomnia can improve sleep management and outcomes for individual adult patients presenting to general practice. The study will also test procedures and collect information in preparation for a larger definitive cluster-randomised trial. The study is funded by The Health Foundation

    A Bayesian method for evaluating and discovering disease loci associations

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    Background: A genome-wide association study (GWAS) typically involves examining representative SNPs in individuals from some population. A GWAS data set can concern a million SNPs and may soon concern billions. Researchers investigate the association of each SNP individually with a disease, and it is becoming increasingly commonplace to also analyze multi-SNP associations. Techniques for handling so many hypotheses include the Bonferroni correction and recently developed Bayesian methods. These methods can encounter problems. Most importantly, they are not applicable to a complex multi-locus hypothesis which has several competing hypotheses rather than only a null hypothesis. A method that computes the posterior probability of complex hypotheses is a pressing need. Methodology/Findings: We introduce the Bayesian network posterior probability (BNPP) method which addresses the difficulties. The method represents the relationship between a disease and SNPs using a directed acyclic graph (DAG) model, and computes the likelihood of such models using a Bayesian network scoring criterion. The posterior probability of a hypothesis is computed based on the likelihoods of all competing hypotheses. The BNPP can not only be used to evaluate a hypothesis that has previously been discovered or suspected, but also to discover new disease loci associations. The results of experiments using simulated and real data sets are presented. Our results concerning simulated data sets indicate that the BNPP exhibits both better evaluation and discovery performance than does a p-value based method. For the real data sets, previous findings in the literature are confirmed and additional findings are found. Conclusions/Significance: We conclude that the BNPP resolves a pressing problem by providing a way to compute the posterior probability of complex multi-locus hypotheses. A researcher can use the BNPP to determine the expected utility of investigating a hypothesis further. Furthermore, we conclude that the BNPP is a promising method for discovering disease loci associations. © 2011 Jiang et al

    A Generative Model of Cognitive State from Task and Eye Movements

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    The early eye tracking studies of Yarbus provided descriptive evidence that an observer’s task influences patterns of eye movements, leading to the tantalizing prospect that an observer’s intentions could be inferred from their saccade behavior. We investigate the predictive value of task and eye movement properties by creating a computational cognitive model of saccade selection based on instructed task and internal cognitive state using a Dynamic Bayesian Network (DBN). Understanding how humans generate saccades under different conditions and cognitive sets links recent work on salience models of low-level vision with higher level cognitive goals. This model provides a Bayesian, cognitive approach to top-down transitions in attentional set in pre-frontal areas along with vector-based saccade generation from the superior colliculus. Our approach is to begin with eye movement data that has previously been shown to differ across task. We first present an analysis of the extent to which individual saccadic features are diagnostic of an observer’s task. Second, we use those features to infer an underlying cognitive state that potentially differs from the instructed task. Finally, we demonstrate how changes of cognitive state over time can be incorporated into a generative model of eye movement vectors without resorting to an external decision homunculus. Internal cognitive state frees the model from the assumption that instructed task is the only factor influencing observers’ saccadic behavior. While the inclusion of hidden temporal state does not improve the classification accuracy of the model, it does allow accurate prediction of saccadic sequence results observed in search paradigms. Given the generative nature of this model, it is capable of saccadic simulation in real time. We demonstrated that the properties from its generated saccadic vectors closely match those of human observers given a particular task and cognitive state. Many current models of vision focus entirely on bottom-up salience to produce estimates of spatial “areas of interest” within a visual scene. While a few recent models do add top-down knowledge and task information, we believe our contribution is important in three key ways. First, we incorporate task as learned attentional sets that are capable of self-transition given only information available to the visual system. This matches influential theories of bias signals by (Miller and Cohen Annu Rev Neurosci 24:167–202, 2001) and implements selection of state without simply shifting the decision to an external homunculus. Second, our model is generative and capable of predicting sequence artifacts in saccade generation like those found in visual search. Third, our model generates relative saccadic vector information as opposed to absolute spatial coordinates. This matches more closely the internal saccadic representations as they are generated in the superior colliculus

    Blockade of insulin-like growth factors increases efficacy of paclitaxel in metastatic breast cancer.

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    Breast cancer remains the leading cause of cancer death in women owing to metastasis and the development of resistance to established therapies. Macrophages are the most abundant immune cells in the breast tumor microenvironment and can both inhibit and support cancer progression. Thus, gaining a better understanding of how macrophages support cancer could lead to the development of more effective therapies. In this study, we find that breast cancer-associated macrophages express high levels of insulin-like growth factors 1 and 2 (IGFs) and are the main source of IGFs within both primary and metastatic tumors. In total, 75% of breast cancer patients show activation of insulin/IGF-1 receptor signaling and this correlates with increased macrophage infiltration and advanced tumor stage. In patients with invasive breast cancer, activation of Insulin/IGF-1 receptors increased to 87%. Blocking IGF in combination with paclitaxel, a chemotherapeutic agent commonly used to treat breast cancer, showed a significant reduction in tumor cell proliferation and lung metastasis in pre-clinical breast cancer models compared to paclitaxel monotherapy. Our findings provide the rationale for further developing the combination of paclitaxel with IGF blockers for the treatment of invasive breast cancer, and Insulin/IGF1R activation and IGF+ stroma cells as potential biomarker candidates for further evaluation

    Multiferroicity in an organic charge-transfer salt: Electric-dipole-driven magnetism

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    Multiferroics, showing simultaneous ordering of electrical and magnetic degrees of freedom, are remarkable materials as seen from both the academic and technological points of view. A prominent mechanism of multiferroicity is the spin-driven ferroelectricity, often found in frustrated antiferromagnets with helical spin order. There, similar to conventional ferroelectrics, the electrical dipoles arise from an off-centre displacement of ions. However, recently a different mechanism, namely purely electronic ferroelectricity, where charge order breaks inversion symmetry, has attracted considerable interest. Here we provide evidence for this exotic type of ferroelectricity, accompanied by antiferromagnetic spin order, in a two-dimensional organic charge-transfer salt, thus representing a new class of multiferroics. Quite unexpectedly for electronic ferroelectrics, dipolar and spin order arise nearly simultaneously. This can be ascribed to the loss of spin frustration induced by the ferroelectric ordering. Hence, here the spin order is driven by the ferroelectricity, in marked contrast to the spin-driven ferroelectricity in helical magnets.Comment: 8 pages, 9 figures (including 4 pages and 6 figures in supplementary information). Version 2 with minor errors corrected (legend of Fig. 3c and definition of vectors e and Q
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