Matching Items (14)

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Accelerated Diversification of Nonhuman Primate Malarias in Southeast Asia: Adaptive Radiation or Geographic Speciation?

Description

Although parasitic organisms are found worldwide, the relative importance of host specificity and geographic isolation for parasite speciation has been explored in only a few systems. Here, we study Plasmodium

Although parasitic organisms are found worldwide, the relative importance of host specificity and geographic isolation for parasite speciation has been explored in only a few systems. Here, we study Plasmodium parasites known to infect Asian nonhuman primates, a monophyletic group that includes the lineage leading to the human parasite Plasmodium vivax and several species used as laboratory models in malaria research. We analyze the available data together with new samples from three sympatric primate species from Borneo: The Bornean orangutan and the long-tailed and the pig-tailed macaques. We find several species of malaria parasites, including three putatively new species in this biodiversity hotspot. Among those newly discovered lineages, we report two sympatric parasites in orangutans. We find no differences in the sets of malaria species infecting each macaque species indicating that these species show no host specificity. Finally, phylogenetic analysis of these data suggests that the malaria parasites infecting Southeast Asian macaques and their relatives are speciating three to four times more rapidly than those with other mammalian hosts such as lemurs and African apes. We estimate that these events took place in approximately a 3–4-Ma period. Based on the genetic and phenotypic diversity of the macaque malarias, we hypothesize that the diversification of this group of parasites has been facilitated by the diversity, geographic distributions, and demographic histories of their primate hosts.

Contributors

Agent

Created

Date Created
  • 2014-11-10

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Bayesian Biogeographical Analyses with Beast: Assessment Using Simulated Data

Description

Biogeography is the study of the spatial distribution of the earth's biota, both in the present and the past. Traditionally, biogeographical studies have relied on a combination of surveys of

Biogeography is the study of the spatial distribution of the earth's biota, both in the present and the past. Traditionally, biogeographical studies have relied on a combination of surveys of existing populations, fossil evidence, and the geological record of the earth. However, with the advent of relatively inexpensive methods of DNA sequencing, it is now possible to use information concerning the genetic relatedness of individuals in populations to address questions about how those populations came to be where they are today. For example, biogeographical studies of HIV-I provide strong support for the hypothesis that this virus arose in Africa through a host switch from chimpanzees to humans and only began to spread to human populations located on other continents some 60 to 70 years ago (Sharp & Hahn, 2010).

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Agent

Created

Date Created
  • 2015-05

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The Role of Multiple Expression Sites and Mosaic Gene Conversion in Antigenic Variation in African Trypanosomes

Description

Although extracellular throughout their lifecycle, trypanosomes are able to persist despite strong host immune responses through a process known as antigenic variation involving a large, highly diverse family of surface

Although extracellular throughout their lifecycle, trypanosomes are able to persist despite strong host immune responses through a process known as antigenic variation involving a large, highly diverse family of surface glycopro- tein (VSG) genes, only one of which is expressed at a time. Previous studies have used mathematical models to investigate the relationship between VSG switching and the dynamics of trypanosome infections, but none have explored the role of multiple VSG expression sites or the contribution of mosaic gene conversion events involving VSG pseudogenes.

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Agent

Created

Date Created
  • 2020-05

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Analysis of Specificity of Associations Between Myrmecophilous Mites and their Host Species

Description

Ants are widespread species of eusocial insects, and myrmecophily describes the species which are associated with ants. Many mites are myrmecophilous species and interact with hosts in many ways such

Ants are widespread species of eusocial insects, and myrmecophily describes the species which are associated with ants. Many mites are myrmecophilous species and interact with hosts in many ways such as phoresis or parasitism. The relationship between ants and mites are interesting as parasitic species could be used to control the spread of invasive ant species. For this project, I reviewed the existing literature on myrmecophilous mites around the world and compiled a database of ant-mite associations, which I then used to characterize factors such as host specificity, attachment sites, and biogeographical patterns. This work demonstrates that existing research on myrmecophilous mites has been both geographically and taxonomically biased and highlights the need for much more comprehensive surveys of mites living in association with ants.

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Agent

Created

Date Created
  • 2021-05

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Modeling Health Indicators of Arizona State's Women's Soccer Team

Description

Winning records are critical to a team's morale, success, and future. As such, players need to perform their best when they are called into a game to ensure the best

Winning records are critical to a team's morale, success, and future. As such, players need to perform their best when they are called into a game to ensure the best possible chance of contributing to the team's success. During the 2013 fall season of Arizona State's NCAA soccer team, twenty-five females had quantities measured, such as heart rate workload, weight loss and playing time, that were analyzed using a least squares regression line and other mathematical relationships with mathematical software. Equations and box plots were produced for each player in the hopes that the coaches could tailor practices to the athletes' bodies needs to increase performance and results for the upcoming fall 2014 season. The playing time and heart rate workload model suggests that increased playing time increases heart rate workload in a linear fashion, though the increase varies by player. The model for the team proposes that the heart rate workload changes in response to playing time according to the equation y=2.67x+127.41 throughout the season. The weight loss and heart rate workload model suggest that establishing a relationship between the two variables is complex since the linear and power regression models did not fit the data. Future studies can focus on the Rate of Perceived Exertion scale, which can supplement the heart rate workload and provide valuable information on players' fatigue levels.

Contributors

Agent

Created

Date Created
  • 2014-05

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Longitudinal analysis of Plasmodium falciparum genetic variation in Turbo, Colombia: implications for malaria control and elimination

Description

Background
Malaria programmes estimate changes in prevalence to evaluate their efficacy. In this study, parasite genetic data was used to explore how the demography of the parasite population can inform

Background
Malaria programmes estimate changes in prevalence to evaluate their efficacy. In this study, parasite genetic data was used to explore how the demography of the parasite population can inform about the processes driving variation in prevalence. In particular, how changes in treatment and population movement have affected malaria prevalence in an area with seasonal malaria.
Methods
Samples of Plasmodium falciparum collected over 8 years from a population in Turbo, Colombia were genotyped at nine microsatellite loci and three drug-resistance loci. These data were analysed using several population genetic methods to detect changes in parasite genetic diversity and population structure. In addition, a coalescent-based method was used to estimate substitution rates at the microsatellite loci.
Results
The estimated mean microsatellite substitution rates varied between 5.35 × 10[superscript −3] and 3.77 × 10[superscript −2] substitutions/locus/month. Cluster analysis identified six distinct parasite clusters, five of which persisted for the full duration of the study. However, the frequencies of the clusters varied significantly between years, consistent with a small effective population size.
Conclusions
Malaria control programmes can detect re-introductions and changes in transmission using rapidly evolving microsatellite loci. In this population, the steadily decreasing diversity and the relatively constant effective population size suggest that an increase in malaria prevalence from 2004 to 2007 was primarily driven by local rather than imported cases.

Contributors

Agent

Created

Date Created
  • 2015-09-22

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Mathematical and statistical insights in evaluating state dependent effectiveness of HIV prevention interventions

Description

Pre-Exposure Prophylaxis (PrEP) is any medical or public health procedure used before exposure to the disease causing agent, its purpose is to prevent, rather than treat or cure a disease.

Pre-Exposure Prophylaxis (PrEP) is any medical or public health procedure used before exposure to the disease causing agent, its purpose is to prevent, rather than treat or cure a disease. Most commonly, PrEP refers to an experimental HIV-prevention strategy that would use antiretrovirals to protect HIV-negative people from HIV infection. A deterministic mathematical model of HIV transmission is developed to evaluate the public-health impact of oral PrEP interventions, and to compare PrEP effectiveness with respect to different evaluation methods. The effects of demographic, behavioral, and epidemic parameters on the PrEP impact are studied in a multivariate sensitivity analysis. Most of the published models on HIV intervention impact assume that the number of individuals joining the sexually active population per year is constant or proportional to the total population. In the second part of this study, three models are presented and analyzed to study the PrEP intervention, with constant, linear, and logistic recruitment rates. How different demographic assumptions can affect the evaluation of PrEP is studied. When provided with data, often least square fitting or similar approaches can be used to determine a single set of approximated parameter values that make the model fit the data best. However, least square fitting only provides point estimates and does not provide information on how strongly the data supports these particular estimates. Therefore, in the third part of this study, Bayesian parameter estimation is applied on fitting ODE model to the related HIV data. Starting with a set of prior distributions for the parameters as initial guess, Bayes' formula can be applied to obtain a set of posterior distributions for the parameters which makes the model fit the observed data best. Evaluating the posterior distribution often requires the integration of high-dimensional functions, which is usually difficult to calculate numerically. Therefore, the Markov chain Monte Carlo (MCMC) method is used to approximate the posterior distribution.

Contributors

Agent

Created

Date Created
  • 2014

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Time-dependent models of signal transduction networks

Description

Signaling cascades transduce signals received on the cell membrane to the nucleus. While noise filtering, ultra-sensitive switches, and signal amplification have all been shown to be features of such signaling

Signaling cascades transduce signals received on the cell membrane to the nucleus. While noise filtering, ultra-sensitive switches, and signal amplification have all been shown to be features of such signaling cascades, it is not understood why cascades typically show three or four layers. Using singular perturbation theory, Michaelis-Menten type equations are derived for open enzymatic systems. When these equations are organized into a cascade, it is demonstrated that the output signal as a function of time becomes sigmoidal with the addition of more layers. Furthermore, it is shown that the activation time will speed up to a point, after which more layers become superfluous. It is shown that three layers create a reliable sigmoidal response progress curve from a wide variety of time-dependent signaling inputs arriving at the cell membrane, suggesting that natural selection may have favored signaling cascades as a parsimonious solution to the problem of generating switch-like behavior in a noisy environment.

Contributors

Agent

Created

Date Created
  • 2013

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A: kinetic approach to anomalous diffusion in biological trapping regions

Description

Advances in experimental techniques have allowed for investigation of molecular dynamics at ever smaller temporal and spatial scales. There is currently a varied and growing body of literature which demonstrates

Advances in experimental techniques have allowed for investigation of molecular dynamics at ever smaller temporal and spatial scales. There is currently a varied and growing body of literature which demonstrates the phenomenon of \emph{anomalous diffusion} in physics, engineering, and biology. In particular many diffusive type processes in the cell have been observed to follow a power law $\left \propto t^\alpha$ scaling of the mean square displacement of a particle. This contrasts with the expected linear behavior of particles undergoing normal diffusion. \emph{Anomalous sub-diffusion} ($\alpha<1$) has been attributed to factors such as cytoplasmic crowding of macromolecules, and trap-like structures in the subcellular environment non-linearly slowing the diffusion of molecules. Compared to normal diffusion, signaling molecules in these constrained spaces can be more concentrated at the source, and more diffuse at longer distances, potentially effecting the signalling dynamics. As diffusion at the cellular scale is a fundamental mechanism of cellular signaling and additionally is an implicit underlying mathematical assumption of many canonical models, a closer look at models of anomalous diffusion is warranted. Approaches in the literature include derivations of fractional differential diffusion equations (FDE) and continuous time random walks (CTRW). However these approaches are typically based on \emph{ad-hoc} assumptions on time- and space- jump distributions. We apply recent developments in asymptotic techniques on collisional kinetic equations to develop a FDE model of sub-diffusion due to trapping regions and investigate the nature of the space/time probability distributions assosiated with trapping regions. This approach both contrasts and compliments the stochastic CTRW approach by positing more physically realistic underlying assumptions on the motion of particles and their interactions with trapping regions, and additionally allowing varying assumptions to be applied individually to the traps and particle kinetics.

Contributors

Agent

Created

Date Created
  • 2014

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Methods for Detecting Mutations in Non-model Organisms

Description

Next-generation sequencing is a powerful tool for detecting genetic variation. How-ever, it is also error-prone, with error rates that are much larger than mutation rates.
This can make mutation detection

Next-generation sequencing is a powerful tool for detecting genetic variation. How-ever, it is also error-prone, with error rates that are much larger than mutation rates.
This can make mutation detection difficult; and while increasing sequencing depth
can often help, sequence-specific errors and other non-random biases cannot be de-
tected by increased depth. The problem of accurate genotyping is exacerbated when
there is not a reference genome or other auxiliary information available.
I explore several methods for sensitively detecting mutations in non-model or-
ganisms using an example Eucalyptus melliodora individual. I use the structure of
the tree to find bounds on its somatic mutation rate and evaluate several algorithms
for variant calling. I find that conventional methods are suitable if the genome of a
close relative can be adapted to the study organism. However, with structured data,
a likelihood framework that is aware of this structure is more accurate. I use the
techniques developed here to evaluate a reference-free variant calling algorithm.
I also use this data to evaluate a k-mer based base quality score recalibrator
(KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing
data. Base quality scores can help detect errors in sequencing reads, but are often
inaccurate. The most popular method for correcting this issue requires a known
set of variant sites, which is unavailable in most cases. I simulate data and show
that errors in this set of variant sites can cause calibration errors. I then show that
KBBQ accurately recalibrates base quality scores while requiring no reference or other
information and performs as well as other methods.
Finally, I use the Eucalyptus data to investigate the impact of quality score calibra-
tion on the quality of output variant calls and show that improved base quality score
calibration increases the sensitivity and reduces the false positive rate of a variant
calling algorithm.

Contributors

Agent

Created

Date Created
  • 2020