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61.
Identification of a binding site of the human immunodeficiency virus envelope protein gp120 to neuronal‐specific tubulin 下载免费PDF全文
62.
Analytica is an easy-to-learn, easy-to-use modeling tool that allows modelers to represent what they know through influence diagrams. These diagrams show which model quantities are derived from which others and indicate by shape and color the roles that different nodes play in the model, e.g., decision variables, chance variables, outcome variables, deterministic functions, or abstractions of sub-models. A wide variety of built-in probability distributions allow uncertainties about input values to be painlessly specified and propagated through the model via a fast, professional Monte-Carlo simulation engine. Resulting uncertainties and sensitivities about any quantity in the model can be viewed with admirable ease and flexibility by selecting among probability density, cumulative distribution, confidence band, sensitivity analysis, and other displays. Analytica features clever hierarchical model management and navigation features that serious model-builders will appreciate and that novice modelers will learn from as they are led to develop well-structured, well-documented models. Simple continuous (compartmental-flow) and Markov chain dynamic simulation models can be built by paying some detailed attention to arrays and indices, although Analytica does not support true discrete-event simulation. Within its chosen domain—uncertainty propagation through influence diagram models—Analytica is by far the easiest and best tool that we have seen. 相似文献
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Metacommunity ecology has rapidly become a dominant framework through which ecologists understand the natural world. Unfortunately, persistent misunderstandings regarding metacommunity theory and the methods for evaluating hypotheses based on the theory are common in the ecological literature. Since its beginnings, four major paradigms—species sorting, mass effects, neutrality, and patch dynamics—have been associated with metacommunity ecology. The Big 4 have been misconstrued to represent the complete set of metacommunity dynamics. As a result, many investigators attempt to evaluate community assembly processes as strictly belonging to one of the Big 4 types, rather than embracing the full scope of metacommunity theory. The Big 4 were never intended to represent the entire spectrum of metacommunity dynamics and were rather examples of historical paradigms that fit within the new framework. We argue that perpetuation of the Big 4 typology hurts community ecology and we encourage researchers to embrace the full inference space of metacommunity theory. A related, but distinct issue is that the technique of variation partitioning is often used to evaluate the dynamics of metacommunities. This methodology has produced its own set of misunderstandings, some of which are directly a product of the Big 4 typology and others which are simply the product of poor study design or statistical artefacts. However, variation partitioning is a potentially powerful technique when used appropriately and we identify several strategies for successful utilization of variation partitioning. 相似文献
65.
Paige B. Miller Eamon B. O’Dea Pejman Rohani John M. Drake 《Theoretical biology & medical modelling》2017,14(1):17
Background
Despite high vaccination coverage, many childhood infections pose a growing threat to human populations. Accurate disease forecasting would be of tremendous value to public health. Forecasting disease emergence using early warning signals (EWS) is possible in non-seasonal models of infectious diseases. Here, we assessed whether EWS also anticipate disease emergence in seasonal models.Methods
We simulated the dynamics of an immunizing infectious pathogen approaching the tipping point to disease endemicity. To explore the effect of seasonality on the reliability of early warning statistics, we varied the amplitude of fluctuations around the average transmission. We proposed and analyzed two new early warning signals based on the wavelet spectrum. We measured the reliability of the early warning signals depending on the strength of their trend preceding the tipping point and then calculated the Area Under the Curve (AUC) statistic.Results
Early warning signals were reliable when disease transmission was subject to seasonal forcing. Wavelet-based early warning signals were as reliable as other conventional early warning signals. We found that removing seasonal trends, prior to analysis, did not improve early warning statistics uniformly.Conclusions
Early warning signals anticipate the onset of critical transitions for infectious diseases which are subject to seasonal forcing. Wavelet-based early warning statistics can also be used to forecast infectious disease.66.
Linda J.S. Allen Curtis L. Wesley Robert D. Owen Douglas G. Goodin David Koch Colleen B. Jonsson Yong-Kyu Chu J.M. Shawn Hutchinson Robert L. Paige 《Journal of theoretical biology》2009,260(4):510-522
New habitat-based models for spread of hantavirus are developed which account for interspecies interaction. Existing habitat-based models do not consider interspecies pathogen transmission, a primary route for emergence of new infectious diseases and reservoirs in wildlife and man. The modeling of interspecies transmission has the potential to provide more accurate predictions of disease persistence and emergence dynamics. The new models are motivated by our recent work on hantavirus in rodent communities in Paraguay. Our Paraguayan data illustrate the spatial and temporal overlaps among rodent species, one of which is the reservoir species for Jabora virus and others which are spillover species. Disease transmission occurs when their habitats overlap. Two mathematical models, a system of ordinary differential equations (ODE) and a continuous-time Markov chain (CTMC) model, are developed for spread of hantavirus between a reservoir and a spillover species. Analysis of a special case of the ODE model provides an explicit expression for the basic reproduction number, , such that if , then the pathogen does not persist in either population but if , pathogen outbreaks or persistence may occur. Numerical simulations of the CTMC model display sporadic disease incidence, a new behavior of our habitat-based model, not present in other models, but which is a prominent feature of the seroprevalence data from Paraguay. Environmental changes that result in greater habitat overlap result in more encounters among various species that may lead to pathogen outbreaks and pathogen establishment in a new host. 相似文献
67.
Mahaney PE Webb MB Ye F Sabatucci JP Steffan RJ Chadwick CC Harnish DC Trybulski EJ 《Bioorganic & medicinal chemistry》2006,14(10):3455-3466
The anti-inflammatory activity of non-selective estrogens has been attributed to their ability to antagonize the activity of nuclear factor kappaB (NF-kappaB), a known mediator of inflammatory responses. Here we report the identification of a potent new class of pathway-selective ER ligands that selectively antagonize NF-kappaB functional activity, while exhibiting a lack of classical estrogenic effect. 相似文献
68.
Stormy Dawn Lindblom Sirine C. Fakra Jessica Landon Paige Schulz Ben Tracy Elizabeth A. H. Pilon‐Smits 《Physiologia plantarum》2014,150(1):107-118
Little is known about how fungi affect elemental accumulation in hyperaccumulators (HAs). Here, two rhizosphere fungi from selenium (Se) HA Stanleya pinnata, Alternaria seleniiphila (A1) and Aspergillus leporis (AS117), were used to inoculate S. pinnata and related non‐HA Stanleya elata. Growth and Se and sulfur (S) accumulation were analyzed. Furthermore, X‐ray microprobe analysis was used to investigate elemental distribution and speciation. Growth of S. pinnata was not affected by inoculation or by Se. Stanleya elata growth was negatively affected by AS117 and by Se, but combination of both did not reduce growth. Selenium translocation was reduced in inoculated S. pinnata, and inoculation reduced S translocation in both species. Root Se distribution and speciation were not affected by inoculation in either species; both species accumulated mainly (90%) organic Se. Sulfur, in contrast, was present equally in organic and inorganic forms in S. pinnata roots. Thus, these rhizosphere fungi can affect growth and Se and/or S accumulation, depending on host species. They generally enhanced root accumulation and reduced translocation. These effects cannot be attributed to altered plant Se speciation but may involve altered rhizosphere speciation, as these fungi are known to produce elemental Se. Reduced Se translocation may be useful in applications where toxicity to herbivores and movement of Se into the food chain is a concern. The finding that fungal inoculation can enhance root Se accumulation may be useful in Se biofortification or phytoremediation using root crop species. 相似文献
69.
Xiaohui Gao Xiao Dong Sundharraman Subramanian Paige M. Matthews Caleb A. Cooper Daniel B. Kearns Charles E. Dann III 《Applied and environmental microbiology》2014,80(19):6167-6174
Microbial processes, including biofilm formation, motility, and virulence, are often regulated by changes in the available concentration of cyclic dimeric guanosine monophosphate (c-di-GMP). Generally, high c-di-GMP concentrations are correlated with decreased motility and increased biofilm formation and low c-di-GMP concentrations are correlated with an increase in motility and activation of virulence pathways. The study of c-di-GMP is complicated, however, by the fact that organisms often encode dozens of redundant enzymes that synthesize and hydrolyze c-di-GMP, diguanylate cyclases (DGCs), and c-di-GMP phosphodiesterases (PDEs); thus, determining the contribution of any one particular enzyme is challenging. In an effort to develop a facile system to study c-di-GMP metabolic enzymes, we have engineered a suite of Bacillus subtilis strains to assess the effect of individual heterologously expressed proteins on c-di-GMP levels. As a proof of principle, we characterized all 37 known genes encoding predicted DGCs and PDEs in Clostridium difficile using parallel readouts of swarming motility and fluorescence from green fluorescent protein (GFP) expressed under the control of a c-di-GMP-controlled riboswitch. We found that 27 of the 37 putative C. difficile 630 c-di-GMP metabolic enzymes had either active cyclase or phosphodiesterase activity, with agreement between our motility phenotypes and fluorescence-based c-di-GMP reporter. Finally, we show that there appears to be a threshold level of c-di-GMP needed to inhibit motility in Bacillus subtilis. 相似文献
70.