69 research outputs found
Planetary Dynamics and Habitable Planet Formation In Binary Star Systems
Whether binaries can harbor potentially habitable planets depends on several
factors including the physical properties and the orbital characteristics of
the binary system. While the former determines the location of the habitable
zone (HZ), the latter affects the dynamics of the material from which
terrestrial planets are formed (i.e., planetesimals and planetary embryos), and
drives the final architecture of the planets assembly. In order for a habitable
planet to form in a binary star system, these two factors have to work in
harmony. That is, the orbital dynamics of the two stars and their interactions
with the planet-forming material have to allow terrestrial planet formation in
the habitable zone, and ensure that the orbit of a potentially habitable planet
will be stable for long times. We have organized this chapter with the same
order in mind. We begin by presenting a general discussion on the motion of
planets in binary stars and their stability. We then discuss the stability of
terrestrial planets, and the formation of potentially habitable planets in a
binary-planetary system.Comment: 56 pages, 29 figures, chapter to appear in the book: Planets in
Binary Star Systems (Ed. N. Haghighipour, Springer publishing company
A bovine lymphosarcoma cell line infected with theileria annulata exhibits an irreversible reconfiguration of host cell gene expression
Theileria annulata, an intracellular parasite of bovine lymphoid cells, induces substantial phenotypic alterations to its host cell including continuous proliferation, cytoskeletal changes and resistance to apoptosis. While parasite induced modulation of host cell signal transduction pathways and NFκB activation are established, there remains considerable speculation on the complexities of the parasite directed control mechanisms that govern these radical changes to the host cell. Our objectives in this study were to provide a comprehensive analysis of the global changes to host cell gene expression with emphasis on those that result from direct intervention by the parasite. By using comparative microarray analysis of an uninfected bovine cell line and its Theileria infected counterpart, in conjunction with use of the specific parasitacidal agent, buparvaquone, we have identified a large number of host cell gene expression changes that result from parasite infection. Our results indicate that the viable parasite can irreversibly modify the transformed phenotype of a bovine cell line. Fifty percent of genes with altered expression failed to show a reversible response to parasite death, a possible contributing factor to initiation of host cell apoptosis. The genes that did show an early predicted response to loss of parasite viability highlighted a sub-group of genes that are likely to be under direct control by parasite infection. Network and pathway analysis demonstrated that this sub-group is significantly enriched for genes involved in regulation of chromatin modification and gene expression. The results provide evidence that the Theileria parasite has the regulatory capacity to generate widespread change to host cell gene expression in a complex and largely irreversible manner
The choice of seed tracking method influenced fate of beech seeds dispersed by rodents
Larval Transport Modeling of Deep-Sea Invertebrates Can Aid the Search for Undiscovered Populations
Background: Many deep-sea benthic animals occur in patchy distributions separated by thousands of kilometres, yet because deep-sea habitats are remote, little is known about their larval dispersal. Our novel method simulates dispersal by combining data from the Argo array of autonomous oceanographic probes, deep-sea ecological surveys, and comparative invertebrate physiology. The predicted particle tracks allow quantitative, testable predictions about the dispersal of benthic invertebrate larvae in the south-west Pacific. Principal Findings: In a test case presented here, using non-feeding, non-swimming (lecithotrophic trochophore) larvae of polyplacophoran molluscs (chitons), we show that the likely dispersal pathways in a single generation are significantly shorter than the distances between the three known population centres in our study region. The large-scale density of chiton populations throughout our study region is potentially much greater than present survey data suggest, with intermediate 'stepping stone' populations yet to be discovered. Conclusions/Significance: We present a new method that is broadly applicable to studies of the dispersal of deep-sea organisms. This test case demonstrates the power and potential applications of our new method, in generating quantitative, testable hypotheses at multiple levels to solve the mismatch between observed and expected distributions: probabilistic predictions of locations of intermediate populations, potential alternative dispersal mechanisms, and expected population genetic structure. The global Argo data have never previously been used to address benthic biology, and our method can be applied to any non-swimming larvae of the deep-sea, giving information upon dispersal corridors and population densities in habitats that remain intrinsically difficult to assess.Irish Research Council for Science, Engineering and TechnologyScience Foundation Irelan
Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications
Damien Caillaud is with UT Austin and Max Planck Institute for Evolutionary Anthropology; Margaret C. Crofoot is with the Smithsonian Tropical Research Institute, Max Planck Institute for Ornithology, and Princeton University; Samuel V. Scarpino is with UT Austin; Patrick A. Jansen is with the Smithsonian Tropical Research Institute, Wageningen University, and University of Groningen; Carol X. Garzon-Lopez is with University of Groningen; Annemarie J. S. Winkelhagen is with Wageningen University; Stephanie A. Bohlman is with Princeton University; Peter D. Walsh is with VaccinApe.Background -- The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings -- Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance -- We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI.The National Center For Ecological Analysis is supported by NSF Grant DEB-0553768, the University of California Santa Barbara and the State of California. The Forest Dynamics Plots were funded by NSF Grants to Stephen Hubbell DEB-0640386, DEB-0425651, DEB-0346488, DEB-0129874, DEB-00753102, DEB-9909347, DEB-9615226, DEB-9615226, DEB-9405933, DEB-9221033, DEB-9100058, DEB-8906869, DEB-8605042, DEB-8206992, DEB-7922197, and by the Center for Tropical Forest Science, the Smithsonian Tropical Forest Research Institute, The John D. and Catherine T. MacArthur Foundation, the Mellon Foundation and the Celera Foundation. DC is supported by NSF grant DEB-0749097 to L.A. Meyers. SS is supported by an NSF Graduate Research Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Biological Sciences, School o
Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set
Molecular Mechanisms Associated with Nicotine Pharmacology and Dependence.
Tobacco dependence is a leading cause of preventable disease and death worldwide. Nicotine, the main psychoactive component in tobacco cigarettes, has also been garnering increased popularity in its vaporized form, as derived from e-cigarette devices. Thus, an understanding of the molecular mechanisms underlying nicotine pharmacology and dependence is required to ascertain novel approaches to treat drug dependence. In this chapter, we review the field's current understanding of nicotine's actions in the brain, the neurocircuitry underlying drug dependence, factors that modulate the function of nicotinic acetylcholine receptors, and the role of specific genes in mitigating the vulnerability to develop nicotine dependence. In addition to nicotine's direct actions in the brain, other constituents in nicotine and tobacco products have also been found to alter drug use, and thus, evidence is provided to highlight this issue. Finally, currently available pharmacotherapeutic strategies are discussed, along with an outlook for future therapeutic directions to achieve to the goal of long-term nicotine cessation
Nicotinic Receptors Underlying Nicotine Dependence: Evidence from Transgenic Mouse Models.
Nicotine underlies the reinforcing properties of tobacco cigarettes and e-cigarettes. After inhalation and absorption, nicotine binds to various nicotinic acetylcholine receptor (nAChR) subtypes localized on the pre- and postsynaptic membranes of cells, which subsequently leads to the modulation of cellular function and neurotransmitter signaling. In this chapter, we begin by briefly reviewing the current understanding of nicotine's actions on nAChRs and highlight considerations regarding nAChR subtype localization and pharmacodynamics. Thereafter, we discuss the seminal discoveries derived from genetically modified mouse models, which have greatly contributed to our understanding of nicotine's effects on the reward-related mesolimbic pathway and the aversion-related habenulo-interpeduncular pathway. Thereafter, emerging areas of research focusing on modulation of nAChR expression and/or function are considered. Taken together, these discoveries have provided a foundational understanding of various genetic, neurobiological, and behavioral factors underlying the motivation to use nicotine and related dependence processes, which are thereby advancing drug discovery efforts to promote long-term abstinence
Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.
BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700
Cancer Biomarker Discovery: The Entropic Hallmark
Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases
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