12 resultados para biological fluids

em Duke University


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UNLABELLED: PREMISE OF THE STUDY: The Frullania tamarisci complex includes eight Holarctic liverwort species. One of these, F. asagrayana, is distributed broadly throughout eastern North America from Canada to the Gulf Coast. Preliminary genetic data suggested that the species includes two groups of populations. This study was designed to test whether the two groups are reproductively isolated biological species. • METHODS: Eighty-eight samples from across the range of F. asagrayana, plus 73 samples from one population, were genotyped for 13 microsatellite loci. Sequences for two plastid loci and nrITS were obtained from 13 accessions. Genetic data were analyzed using coalescent models and Bayesian inference. • KEY RESULTS: Frullania asagrayana is sequence-invariant at the two plastid loci and ITS2, but two clear groups were resolved by microsatellites. The two groups are largely reproductively isolated, but there is a low level of gene flow from the southern to the northern group. No gene flow was detected in the other direction. A local population was heterogeneous but displayed strong genetic structure. • CONCLUSIONS: The genetic structure of F. asagrayana in eastern North America reflects morphologically cryptic differentiation between reproductively isolated groups of populations, near-panmixis within groups, and clonal propagation at local scales. Reproductive isolation between groups that are invariant at the level of nucleotide sequences shows that caution must be exercised in making taxonomic and evolutionary inferences from reciprocal monophyly (or lack thereof) between putative species.

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The ability of diffuse reflectance spectroscopy to extract quantitative biological composition of tissues has been used to discern tissue types in both pre-clinical and clinical cancer studies. Typically, diffuse reflectance spectroscopy systems are designed for single-point measurements. Clinically, an imaging system would provide valuable spatial information on tissue composition. While it is feasible to build a multiplexed fiber-optic probe based spectral imaging system, these systems suffer from drawbacks with respect to cost and size. To address these we developed a compact and low cost system using a broadband light source with an 8-slot filter wheel for illumination and silicon photodiodes for detection. The spectral imaging system was tested on a set of tissue mimicking liquid phantoms which yielded an optical property extraction accuracy of 6.40 +/- 7.78% for the absorption coefficient (micro(a)) and 11.37 +/- 19.62% for the wavelength-averaged reduced scattering coefficient (micro(s)').

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Complex diseases will have multiple functional sites, and it will be invaluable to understand the cross-locus interaction in terms of linkage disequilibrium (LD) between those sites (epistasis) in addition to the haplotype-LD effects. We investigated the statistical properties of a class of matrix-based statistics to assess this epistasis. These statistical methods include two LD contrast tests (Zaykin et al., 2006) and partial least squares regression (Wang et al., 2008). To estimate Type 1 error rates and power, we simulated multiple two-variant disease models using the SIMLA software package. SIMLA allows for the joint action of up to two disease genes in the simulated data with all possible multiplicative interaction effects between them. Our goal was to detect an interaction between multiple disease-causing variants by means of their linkage disequilibrium (LD) patterns with other markers. We measured the effects of marginal disease effect size, haplotype LD, disease prevalence and minor allele frequency have on cross-locus interaction (epistasis). In the setting of strong allele effects and strong interaction, the correlation between the two disease genes was weak (r=0.2). In a complex system with multiple correlations (both marginal and interaction), it was difficult to determine the source of a significant result. Despite these complications, the partial least squares and modified LD contrast methods maintained adequate power to detect the epistatic effects; however, for many of the analyses we often could not separate interaction from a strong marginal effect. While we did not exhaust the entire parameter space of possible models, we do provide guidance on the effects that population parameters have on cross-locus interaction.

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My goal was to describe how biological and ecological factors give shape to fishing practices that can contribute to the successful self-governance of a small-scale fishing system in the Gulf of California, Mexico. The analysis was based on a comparison of the main ecological and biological indicators that fishers claim to use to govern their day-to-day decision making about fishing and data collected in situ. I found that certain indicators allow fishers to learn about differences and characteristics of the resource system and its units. Fishers use such information to guide their day-to-day fishing decisions. More importantly, these decisions appear unable to shape the reproductive viability of the fishery because no indicators were correlated to the reproductive cycle of the target species. As a result, the fishing practices constitute a number of mechanisms that might provide short-term buffering capacity against perturbations or stress factors that otherwise would threaten the overall sustainability and self-governance of the system. The particular biological circumstances that shape the harvesting practices might also act as a precursor of self-governance because they provide fishers with enough incentives to meet the costs of organizing the necessary rule structure that underlies a successful self-governance system.

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The advent of digital microfluidic lab-on-a-chip (LoC) technology offers a platform for developing diagnostic applications with the advantages of portability, reduction of the volumes of the sample and reagents, faster analysis times, increased automation, low power consumption, compatibility with mass manufacturing, and high throughput. Moreover, digital microfluidics is being applied in other areas such as airborne chemical detection, DNA sequencing by synthesis, and tissue engineering. In most diagnostic and chemical-detection applications, a key challenge is the preparation of the analyte for presentation to the on-chip detection system. Thus, in diagnostics, raw physiological samples must be introduced onto the chip and then further processed by lysing blood cells and extracting DNA. For massively parallel DNA sequencing, sample preparation can be performed off chip, but the synthesis steps must be performed in a sequential on-chip format by automated control of buffers and nucleotides to extend the read lengths of DNA fragments. In airborne particulate-sampling applications, the sample collection from an air stream must be integrated into the LoC analytical component, which requires a collection droplet to scan an exposed impacted surface after its introduction into a closed analytical section. Finally, in tissue-engineering applications, the challenge for LoC technology is to build high-resolution (less than 10 microns) 3D tissue constructs with embedded cells and growth factors by manipulating and maintaining live cells in the chip platform. This article discusses these applications and their implementation in digital-microfluidic LoC platforms. © 2007 IEEE.

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Regions of the hamster alpha 1-adrenergic receptor (alpha 1 AR) that are important in GTP-binding protein (G protein)-mediated activation of phospholipase C were determined by studying the biological functions of mutant receptors constructed by recombinant DNA techniques. A chimeric receptor consisting of the beta 2-adrenergic receptor (beta 2AR) into which the putative third cytoplasmic loop of the alpha 1AR had been placed activated phosphatidylinositol metabolism as effectively as the native alpha 1AR, as did a truncated alpha 1AR lacking the last 47 residues in its cytoplasmic tail. Substitutions of beta 2AR amino acid sequence in the intermediate portions of the third cytoplasmic loop of the alpha 1AR or at the N-terminal portion of the cytoplasmic tail caused marked decreases in receptor coupling to phospholipase C. Conservative substitutions of two residues in the C terminus of the third cytoplasmic loop (Ala293----Leu, Lys290----His) increased the potency of agonists for stimulating phosphatidylinositol metabolism by up to 2 orders of magnitude. These data indicate (i) that the regions of the alpha 1AR that determine coupling to phosphatidylinositol metabolism are similar to those previously shown to be involved in coupling of beta 2AR to adenylate cyclase stimulation and (ii) that point mutations of a G-protein-coupled receptor can cause remarkable increases in sensitivity of biological response.

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Wastewaters generated during hydraulic fracturing of the Marcellus Shale typically contain high concentrations of salts, naturally occurring radioactive material (NORM), and metals, such as barium, that pose environmental and public health risks upon inadequate treatment and disposal. In addition, fresh water scarcity in dry regions or during periods of drought could limit shale gas development. This paper explores the possibility of using alternative water sources and their impact on NORM levels through blending acid mine drainage (AMD) effluent with recycled hydraulic fracturing flowback fluids (HFFFs). We conducted a series of laboratory experiments in which the chemistry and NORM of different mix proportions of AMD and HFFF were examined after reacting for 48 h. The experimental data combined with geochemical modeling and X-ray diffraction analysis suggest that several ions, including sulfate, iron, barium, strontium, and a large portion of radium (60-100%), precipitated into newly formed solids composed mainly of Sr barite within the first ∼ 10 h of mixing. The results imply that blending AMD and HFFF could be an effective management practice for both remediation of the high NORM in the Marcellus HFFF wastewater and beneficial utilization of AMD that is currently contaminating waterways in northeastern U.S.A.

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Antiaging therapies show promise in model organism research. Translation to humans is needed to address the challenges of an aging global population. Interventions to slow human aging will need to be applied to still-young individuals. However, most human aging research examines older adults, many with chronic disease. As a result, little is known about aging in young humans. We studied aging in 954 young humans, the Dunedin Study birth cohort, tracking multiple biomarkers across three time points spanning their third and fourth decades of life. We developed and validated two methods by which aging can be measured in young adults, one cross-sectional and one longitudinal. Our longitudinal measure allows quantification of the pace of coordinated physiological deterioration across multiple organ systems (e.g., pulmonary, periodontal, cardiovascular, renal, hepatic, and immune function). We applied these methods to assess biological aging in young humans who had not yet developed age-related diseases. Young individuals of the same chronological age varied in their "biological aging" (declining integrity of multiple organ systems). Already, before midlife, individuals who were aging more rapidly were less physically able, showed cognitive decline and brain aging, self-reported worse health, and looked older. Measured biological aging in young adults can be used to identify causes of aging and evaluate rejuvenation therapies.

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The Moorea Coral Reef Long Term Ecological Research project funded by the US National Science Foundation includes multidisciplinary studies of physical processes driving ecological dynamics across the fringing reef, back reef, and fore reef habitats of Moorea, French Polynesia. A network of oceanographic moorings and a variety of other approaches have been used to investigate the biological and biogeochemical aspects of water transport and retention processes in this system. There is evidence to support the hypothesis that a low-frequency counterclockwise flow around the island is superimposed on the relatively strong alongshore currents on each side of the island. Despite the rapid flow and flushing of the back reef, waters over the reef display chemical and biological characteristics distinct from those offshore. The patterns include higher nutrient and lower dissolved organic carbon concentrations, distinct microbial community compositions among habitats, and reef assemblages of zooplankton that exhibit migration behavior, suggesting multigenerational residence on the reef. Zooplankton consumption by planktivorous fish on the reef reflects both retention of reef-associated taxa and capture by the reef community of resources originating offshore. Coral recruitment and population genetics of reef fishes point to retention of larvae within the system and high recruitment levels from local adult populations. The combined results suggest that a broad suite of physical and biological processes contribute to high retention of externally derived and locally produced organic materials within this island coral reef system. © 2013 by The Oceanography Society. All rights reserved.

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MOTIVATION: Although many network inference algorithms have been presented in the bioinformatics literature, no suitable approach has been formulated for evaluating their effectiveness at recovering models of complex biological systems from limited data. To overcome this limitation, we propose an approach to evaluate network inference algorithms according to their ability to recover a complex functional network from biologically reasonable simulated data. RESULTS: We designed a simulator to generate data representing a complex biological system at multiple levels of organization: behaviour, neural anatomy, brain electrophysiology, and gene expression of songbirds. About 90% of the simulated variables are unregulated by other variables in the system and are included simply as distracters. We sampled the simulated data at intervals as one would sample from a biological system in practice, and then used the sampled data to evaluate the effectiveness of an algorithm we developed for functional network inference. We found that our algorithm is highly effective at recovering the functional network structure of the simulated system-including the irrelevance of unregulated variables-from sampled data alone. To assess the reproducibility of these results, we tested our inference algorithm on 50 separately simulated sets of data and it consistently recovered almost perfectly the complex functional network structure underlying the simulated data. To our knowledge, this is the first approach for evaluating the effectiveness of functional network inference algorithms at recovering models from limited data. Our simulation approach also enables researchers a priori to design experiments and data-collection protocols that are amenable to functional network inference.