, Melissa Yssel, MB ChB, FC Path(SA) Chem 139, and Wendy M. Zakowicz, BS 79 Purpose: To achieve clinical validation of cutoff values for newborn screening by tandem mass spectrometry through a worldwide collaborative effort. Methods: Cumulative percentiles of amino acids and acylcarnitines in dried blood spots of approximately 25-30 million normal newborns and 10,742 deidentified true positive cases are compared to assign clinical significance, which is achieved when the median of a disorder range is, and usually markedly outside, either the 99th or the 1st percentile of the normal population. The cutoff target ranges of analytes and ratios are then defined as the interval between selected percentiles of the two populations. When overlaps occur, adjustments are made to maximize sensitivity and specificity taking all available factors into consideration.
In rodent populations, males are more likely to be infected with hantaviruses and to engage in aggression than are females. To assess the relationship between aggression and Seoul virus infection, Norway rats were trapped in Baltimore, Maryland and wounding, infection status, and steroid hormone concentrations were examined. Older males and males with high-grade wounds were more likely to have IgG antibody to Seoul, to shed virus in saliva, urine, and feces, and to have viral RNA in organs than either juveniles or adult males with less severe wounds. In contrast, neither age nor wounding predicted virus shedding among females. Although viral antigen was not identified in the brain, viral protein was detected in the gonads and adrenal glands of adult males. Males with more severe wounds had higher testosterone concentrations than males with no or low-grade wounds. Because wounding, testosterone, and virus shedding are associated among males, aggression may be the primary mode of Seoul virus transmission among male, but not female, Norway rats.
Background Newborn screening (NBS) occupies a unique space at the intersection of translational science and public health. As the only truly population-based public health program in the United States, NBS offers the promise of making the successes of translational medicine available to every infant with a rare disorder that is difficult to diagnose clinically, but for which strong evidence indicates that presymptomatic treatment will substantially improve outcomes. Realistic NBS policy requires data, but rare disorders face a special challenge: Screening cannot be done without supportive data, but adequate data cannot be collected in the absence of large-scale screening. The magnitude and scale of research to provide this expanse of data require working with public health programs, but most do not have the resources or mandate to conduct research. Methods To address this gap, we have established Early Check, a research program in partnership with a state NBS program. Early Check provides the infrastructure needed to identify conditions for which there have been significant advances in treatment potential, but require a large-scale, population-based study to test benefits and risks, demonstrate feasibility, and inform NBS policy. Discussion Our goal is to prove the benefits of a program that can, when compared with current models, accelerate understanding of diseases and treatments, reduce the time needed to consider inclusion of appropriate conditions in the standard NBS panel, and accelerate future research on new NBS conditions, including clinical trials for investigational interventions. Trial registration Clinicaltrials.gov registration # NCT03655223 . Registered on August 31, 2018.
It has long been recognized that arthropod populations fluctuate with changes in environmental conditions and these changes occur at various spatial and temporal scales. Empirical studies that have explored associations between vector abundance and the environment often considered meterological events as leading indicators with their effects traditionally restricted to single points in time, such as precipitation 12 days prior to trapping. Field experience, however, suggests that the duration of these environmental effects on vectors often extends over a range or interval of time. Such a scenario is not directly interpretable from cross correlation plots routinely employed to visualize and identify time lag associations. Cross correlation maps are introduced as a way to generalize cross correlation plots and to visualize the effects of environmental conditions over intervals of time. This graphical method is flexible and can include different characterizations of environmental effects, as well as interactions among environmental variables. A time series of daily trapped female Ochlerotatus sollicitans mosquitos and leading meterologic conditions were used for demonstration. Associations shown in cross correlation maps were consistent with the arthropod biology and trapping efficacy and were also stronger than those identified at single time points using cross correlation plots. Poisson regression models for vector abundance built using meterological variables with both single and interval based leading time lags were compared. The approach based on the leading meterological events allowed to extend over time intervals reproduced the Oc. sollicitans daily population dynamics better than the traditional approach.
Numerous studies have investigated the role of weather on insect species. For mosquitoes, these studies have yielded mixed results. Although it is clear that weather impacts mosquito population dynamics, these investigations have failed to accurately characterize their fluctuations. We use a novel graphical method to examine large numbers of meteorological aggregations of varying lengths and lags simultaneously to establish relationships between these summary variables and mosquito counts, to gain a better understanding of the weather effects. Poisson regression models were developed to characterize the population dynamics of Aedes sollicitans (Walker) by using meteorological data and a 34-yr set of daily mosquito count data. The models accurately characterize mosquito dynamics over time and space. The aggregated meteorological variables included in the model were lowest minimum tides between days 27 and 14 before trapping, total precipitation between days 22 and 9, total precipitation on day 1 and the day of trapping, cooling degree-days on day 0, average minimum relative humidity between days 28 and 9, lowest stream flow from day 11 to day 0, and lowest minimum temperature between days 28 and 13.
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