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Biomedical subjects

Andrew Curtis

Publications and source records attributed to Andrew Curtis.

5 recordsLinked to original sources
PubMed2006

Triatoma dimidiata (Latreille, 1811): a review of its diversity across its geographic range and the relationship among populations.

Due to its vast diversity the Chagas vector, Triatoma dimidiata, has been merged and split into species and subspecies since its first description in 1811. Across its geographic range from Southern Mexico to Northern Peru populations differ in their biology and ethology in many ways including those that directly affect vector capacity and competence. Recent phenetic and genetic data suggest that T. dimidiata can be divided into at least three clades and in fact may be a polytypic species or species complex. To effectively target this vector, it will be necessary to clearly understand how "T. dimidiata" is genetically partitioned both at the taxonomic and population level.

Animals↗
PubMed2006

Preliminary observation of elevated levels of nanocrystalline iron oxide in the basal ganglia of neuroferritinopathy patients.

Magnetometry analysis of brain tissue sub-samples from two neuroferritinopathy patients provides a preliminary indication that the amount of magnetic iron compounds associated with this rare disease is significantly larger than in age/sex-matched controls. The primary iron compounds contributing to the remnant magnetization of the tissue above 50 K and at body temperature are both blocked and superparamagnetic (SPM) biogenic magnetite (Fe3O4) and/or maghemite (gamma-Fe2O3). The concentration of SPM magnetite is significant and appears to be proportional to the concentration of ferritin, which varies with progression of the disease. The mutated ferritin protein appears to be responsible for the presence of iron oxide nano-particules, which in turn could be responsible for extensive damage in the brain.

Aged↗
PubMed2006

Spatial and temporal structure of typhoid outbreaks in Washington, D.C., 1906-1909: evaluating local clustering with the Gi* statistic.

BACKGROUND: To better understand the distribution of typhoid outbreaks in Washington, D.C., the U.S. Public Health Service (PHS) conducted four investigations of typhoid fever. These studies included maps of cases reported between 1 May - 31 October 1906 - 1909. These data were entered into a GIS database and analyzed using Ripley's K-function followed by the Gi* statistic in yearly intervals to evaluate spatial clustering, the scale of clustering, and the temporal stability of these clusters. RESULTS: The Ripley's K-function indicated no global spatial autocorrelation. The Gi* statistic indicated clustering of typhoid at multiple scales across the four year time period, refuting the conclusions drawn in all four PHS reports concerning the distribution of cases. While the PHS reports suggested an even distribution of the disease, this study quantified both areas of localized disease clustering, as well as mobile larger regions of clustering. Thus, indicating both highly localized and periodic generalized sources of infection within the city. CONCLUSION: The methodology applied in this study was useful for evaluating the spatial distribution and annual-level temporal patterns of typhoid outbreaks in Washington, D.C. from 1906 to 1909. While advanced spatial analyses of historical data sets must be interpreted with caution, this study does suggest that there is utility in these types of analyses and that they provide new insights into the urban patterns of typhoid outbreaks during the early part of the twentieth century.

Disease Outbreaks↗
PubMed2005

Modeling of wave propagation in inhomogeneous media.

We present a methodology providing a new perspective on modeling and inversion of wave propagation satisfying time-reversal invariance and reciprocity in generally inhomogeneous media. The approach relies on a representation theorem of the wave equation to express the Green function between points in the interior as an integral over the response in those points due to sources on a surface surrounding the medium. Following a predictable initial computational effort, Green's functions between arbitrary points in the medium can be computed as needed using a simple cross-correlation algorithm.

Journal Article↗