Optimization of polymerase chain reaction for the detection of Borrelia burgdorferi in biologic specimens

This study describes the use of a newly constructed set of primers that amplifies an 85-base pair (bp) segment of Borrelia burgdorferi chromosomal DNA. This 85-bp product is not produced when other Borrelia species, Leptospira, or other bacteria are subjected to polymerase chain reaction (PCR). We also describe a rapid method of optimizing the amplification of B. burgdorferi DNA from canine ethylenediaminetetraacetic acid-treated blood and urine samples that circumvents some of the problems encountered due to low number of spirochetes in clinical specimens and that removes inhibiting substances, which improves the PCR diagnosis of canine Lyme borreliosis.     

Post-Placement Interconnect Entropy

We introduce the concept of post-placement interconnect entropy: the minimal number of bits required to describe a well-placed netlist, which has connection lengths distributed according to Rent's rule. The entropy is a function of the number N of cells in the netlist and the Rent exponent p. We derive an expression for the entropy per cell and show that it converges as N approaches infinity. The entropy provides an achievable lower bound on the number of configuration bits in a programmable logic device (PLD) [or field-programmable gate array (FPGA)] and a useful measure of its routing flexibility. Specific numerical values are computed for practical situations. For example, any scalable FPGA composed of 4-input lookup table cells would require 31 configuration bits per cell. We compare this to the actual number of configuration bits in a standard FPGA architecture. We generalize the bound to dimensions higher than two, and show that for any p there is an optimal dimension that minimizes the bound.     

Predicting key malaria transmission factors, biting and entomological inoculation rates, using modelled soil moisture in Kenya

While malaria transmission varies seasonally, large inter-annual heterogeneity of malaria incidence occurs. Variability in entomological parameters, biting rates and entomological inoculation rates (EIR) have been strongly associated with attack rates in children. The goal of this study was to assess the weather's impact on weekly biting and EIR in the endemic area of Kisian, Kenya. Entomological data collected by the U.S. Army from March 1986 through June 1988 at Kisian, Kenya was analysed with concurrent weather data from nearby Kisumu airport. A soil moisture model of surface-water availability was used to combine multiple weather parameters with landcover and soil features to improve disease prediction. Modelling soil moisture substantially improved prediction of biting rates compared to rainfall; soil moisture lagged two weeks explained up to 45% of An. gambiae biting variability, compared to 8% for raw precipitation. For An. funestus, soil moisture explained 32% variability, peaking after a 4-week lag. The interspecies difference in response to soil moisture was significant (P < 0.00001). A satellite normalized differential vegetation index (NDVI) of the study site yielded a similar correlation (r = 0.42 An. gambiae). Modelled soil moisture accounted for up to 56% variability of An. gambiae EIR, peaking at a lag of six weeks. The relationship between temperature and An. gambiae biting rates was less robust; maximum temperature r2 = -0.20, and minimum temperature r2 = 0.12 after lagging one week. Benefits of hydrological modelling are compared to raw weather parameters and to satellite NDVI. These findings can improve both current malaria risk assessments and those based on El Ni?o forecasts or global climate change model projections.     

Surface-based analysis methods for high-resolution functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) has become a popular technique for studies of human brain activity. Typically, fMRI is performed with >3-mm sampling, so that the imaging data can be regarded as two-dimensional samples that average through the 1.5-4-mm thickness of cerebral cortex. The increasing use of higher spatial resolutions, <1.5-mm sampling, complicates the analysis of fMRI, as one must now consider activity variations within the depth of the brain tissue. We present a set of surface-based methods to exploit the use of high-resolution fMRI for depth analysis. These methods utilize white-matter segmentations coupled with deformable-surface algorithms to create a smooth surface representation at the gray-white interface and pial membrane. These surfaces provide vertex positions and normals for depth calculations, enabling averaging schemes that can increase contrast-to-noise ratio, as well as permitting the direct analysis of depth profiles of functional activity in the human brain.     

Turbulence-induced resonance vibrations cause pollen release in wind-pollinated Plantago lanceolata L. (Plantaginaceae)

In wind pollination, the release of pollen from anthers into airflows determines the quantity and timing of pollen available for pollination. Despite the ecological and evolutionary importance of pollen release, wind–stamen interactions are poorly understood, as are the specific forces that deliver pollen grains into airflows. We present empirical evidence that atmospheric turbulence acts directly on stamens in the cosmopolitan, wind-pollinated weed, Plantago lanceolata, causing resonant vibrations that release episodic bursts of pollen grains. In laboratory experiments, we show that stamens have mechanical properties corresponding to theoretically predicted ranges for turbulence-driven resonant vibrations. The mechanical excitation of stamens at their characteristic resonance frequency caused them to resonate, shedding pollen vigorously. The characteristic natural frequency of the stamens increased over time with each shedding episode due to the reduction in anther mass, which increased the mechanical energy required to trigger subsequent episodes. Field observations of a natural population under turbulent wind conditions were consistent with these laboratory results and demonstrated that pollen is released from resonating stamens excited by small eddies whose turnover periods are similar to the characteristic resonance frequency measured in the laboratory. Turbulence-driven vibration of stamens at resonance may be a primary mechanism for pollen shedding in wind-pollinated angiosperms. The capacity to release pollen in wind can be viewed as a primary factor distinguishing animal- from wind-pollinated plants, and selection on traits such as the damping ratio and flexural rigidity may be of consequence in evolutionary transitions between pollination systems.     

The importance of advancing technology to America’s energy goals

A wide range of energy technologies appears to be needed for the United States to meet its energy goals. A method is developed that relates the uncertainty of technological progress in eleven technology areas to the achievement of CO₂ mitigation and reduced oil dependence. We conclude that to be confident of meeting both energy goals, each technology area must have a much better than 50/50 probability of success, that carbon capture and sequestration, biomass, battery electric or fuel cell vehicles, advanced fossil liquids, and energy efficiency technologies for buildings appear to be almost essential, and that the success of each one of the 11 technologies is important. These inferences are robust to moderate variations in assumptions.