An Introduction to Ecology of Infectious Diseases - Oysters and Estuaries

Infectious diseases are recognized as an important factor regulating marine ecosystems (Harvell et al., 1999, 2002, 2004; Porter et al., 2001; McCallum et al., 2004; Ward and Lafferty, 2004; Stewart et al., 2008; Bienfang et al., 2011). Many of the organisms affected by marine diseases have important ecological roles in estuarine and coastal environments and some are also commercially important. Outbreaks of infectious diseases in these environments, referred to as epizootics, can produce significant population declines and extinctions, both of which threaten biodiversity, food web interactions, and ecosystem productivity (Harvell et al., 2002, 2004)

Treatment of Inconclusive Results in Firearms Error Rate Studies

★ Defining error rates for firearms evidence ★ Impact of inconclusive decisions on error rates ★ Predictive probabilities and error

Modeling the MSX Parasite in Eastern Oyster (Crassostrea virginica) Populations. I. Model Development, Implementation, and Verification

A mathematical model simulating the host-parasite-environmental interactions of eastern oysters (Crassostrea virginica) and the pathogen, Haplosporidium nelsoni, which causes MSX disease, has been developed. The model has 2 components. One replicates the infection process within the oyster and the other simulates transmission. The infection-development component relies on basic physiological processes of both host and parasite, modified by the environment, to reproduce the observed annual prevalence cycle of H. nelsoni. Equations describing these rates were constructed using data from long-term field observations, and field and laboratory experiments. In the model, salinity and temperature have direct effects upon in vivo parasite survival and proliferation as well as on transmission rates. Cold winters depress transmission rates for 1 or 2 years after the event, even if temperatures return to normal. Warm winters have no effect on transmission in subsequent years. Hemocyte activity, parasite density, and the overall environmental quality provided to the parasite by the host also influence the modeled infection process. Hemocytes scavenge and eliminate parasites that die over the winter or that degenerate as a result of failed sporulation. Replication rates of H. nelsoni are slowed at high parasite densities. The environmental quality provided by the host, which is a function of oyster food availability and the oyster\u27s potential growth efficiency, affects doubling times and also determines whether the parasite completes its life cycle by forming spores. Sport production is related to a threshold environmental quality, which occurs only in small oysters because of their high growth efficiency. Simulations that use environmental conditions characteristic of Delaware Bay reproduce the observed seasonal H. nelsoni cycle, consequent oyster mortality, and spore production in juvenile oysters. The oyster-H. nelsoni model provides a quantitative framework for guiding future laboratory and field studies as well as management efforts

Reply to Response by FBI Laboratory Filed in Illinois v. Winfield and Affidavit by Biederman et al. (2022) Filed in US v. Kaevon Sutton (2018 CF1 009709)

1 Preliminaries 1.1 Scope The aim of this document is to respond to issues raised in Federal Bureau of Investigation1 and Alex Biedermann, Bruce Budowle & Christophe Champod.2 1.2 Conflict of Interest We are statisticians employed at public institutions of higher education (Iowa State University and University of Nebraska, Lincoln) and have not been paid for our time or expertise when preparing either this response or the original affidavit.3 We provide this information as a public service and as scientists and researchers in this area. 1.3 Organization The rest of the document precedes as follows: we begin by outlining our main points of agreement with the Federal Bureau of Investigation4 (hereafter, FBI) and Biedermann, Budowle, and Champod5 (hereafter, BBC) in Section 2. As a threshold issue, we consider the concept of a general discipline-wide error rate in Section 3 in order to correct statistical misconceptions in Biedermann, Budowle, and Champod.6 We then describe the statistical concepts underlying our assessment of the discipline of firearms and toolmark examiners in Section 4. Finally, we address specific issues with participant and material sampling (Section 5), study design (Section 6), and the use of inconclusives (Section 7). 1 FBI Laboratory Response to the Declaration Regarding Firearms and Toolmark Error Rates Filed in Illinois v. Winfield (Aff. filed in US v Kaevon Sutton dated May 3, 2022). 2 Forensic feature-comparison as applied to firearms examinations: evidential value of findings and expert performance characteristics (Aff. filed in US v Kaevon Sutton dated April 28, 2022). 3 Susan Vanderplas et al., Firearms and Toolmark Error Rates (Aff. filed in Illinois v Winfield, January 2022). 4 Supra note 1. 5 Supra note 2. 6 Supra note 2

Biologically meaningful expression profiling across species using heterologous hybridization to a cDNA microarray

BACKGROUND: Unravelling the path from genotype to phenotype, as it is influenced by an organism's environment, is one of the central goals in biology. Gene expression profiling by means of microarrays has become very prominent in this endeavour, although resources exist only for relatively few model systems. As genomics has matured into a comparative research program, expression profiling now also provides a powerful tool for non-traditional model systems to elucidate the molecular basis of complex traits. RESULTS: Here we present a microarray constructed with ~4500 features, derived from a brain-specific cDNA library for the African cichlid fish Astatotilapia burtoni (Perciformes). Heterologous hybridization, targeting RNA to an array constructed for a different species, is used for eight different fish species. We quantified the concordance in gene expression profiles across these species (number of genes and fold-changes). Although most robust when target RNA is derived from closely related species (<10 MA divergence time), our results showed consistent profiles for other closely related taxa (~65 MA divergence time) and, to a lesser extent, even very distantly related species (>200 MA divergence time). CONCLUSION: This strategy overcomes some of the restrictions imposed on model systems that are of importance for evolutionary and ecological studies, but for which only limited sequence information is available. Our work validates the use of expression profiling for functional genomics within a comparative framework and provides a foundation for the molecular and cellular analysis of complex traits in a wide range of organisms

Impulsivity, Impulsive and Reflective Processes and the Development of Alcohol Use and Misuse in Adolescents and Young Adults

This paper contrasts dual-process and personality approaches in the prediction of addictive behaviors and related risk behaviors. In dual-process models, behavior is described as the joint outcome of qualitatively different “impulsive” (or associative) and “reflective” processes. There are important individual differences regarding both types of processes, and the relative strength of both in a specific situation is influenced by prior behavior and state variables (e.g., fatigue, alcohol use). From this perspective, a specific behavior (e.g., alcohol misuse) can be predicted by the combined indices of the behavior-related impulsive processes (e.g., associations with alcohol), and reflective processes, including the ability to refrain from a motivationally salient action. Personality approaches have reported that general traits such as impulsivity predict addictive behaviors. Here we contrast these two approaches, with supplementary analyses on four datasets. We hypothesized that trait impulsivity can predict specific risky behaviors, but that its predictive power disappears once specific behavior-related associations, indicators of executive functioning, and their interaction are entered into the equation. In all four studies the observed interaction between specific associations and executive control (EC) was robust: trait impulsivity did not diminish the prediction of alcohol use by the interaction. Trait impulsivity was not always related to alcohol use, and when it was, the predictive power disappeared after entering the interaction between behavior-specific associations and EC in one study, but not in the other. These findings are interpreted in relation to the validity of the measurements used, which leads to a more refined hypothesis

Modeling the MSX Parasite in Eastern Oyster (Crassostrea virginica) Populations. III. Regional Application and the Problem of Transmission

A model of transmission for Haplosporidium nelsoni, the disease agent for MSX disease, is developed and applied to sites in Delaware Bay and Chesapeake Bay. The environmental factors that force the oyster population- H. nelsoni model are salinity, temperature, food, and total suspended solids. The simulated development of MSX disease was verified using 3 time series of disease prevalence and intensity: 1960 to 1970 and 1980 to 1990 for Delaware Bay, and 1980 to 1994 for Chesapeake Bay, and for a series of sites covering the salinity gradient in each bay. Additional simulations consider the implications of assumptions made in development of the model for constraining the mode of transmission of H. nelsoni disease in oyster populations. Transmission of H. nelsoni includes non-local factors that exert a paramount influence on the transmission process. Key environmental forcing factors of season, salinity, and winter temperature exert a direct control on the transmission process, either by controlling the availability of infective particles in the water column or by controlling the population dynamics of an alternate host. Salinity\u27s role is a dual one. Salinity acts on the local host population by varying the infectivity of infective particles as they impinge the oyster gill during the filtration process. In addition, salinity exerts a regional influence on the transmission process by controlling, in part and on a bay-wide scale, the concentration of infective particles in the water column (or perhaps the abundance of an alternate host). In addition to the effect of salinity, infective particle concentration also decreases for 1 to 2 years after a cold winter and returns to high levels faster after a warm winter. It is the presence in the H. nelsoni transmission model of these bay-wide influences of environmental change that make this model different: from most other transmission models. Simulations suggest that epizootic cycles are principally the product of enhanced transmission rather than enhanced intensification. These influences of transmission on the course of infection, in many cases, have multiyear implications for prevalence and infection intensity, and the root of much of this multiyear behavior is in the processes that control the concentration of infective particles in the water column

Modeling The MSX Parasite in Eastern Oyster (Crassostrea virginica) Populations. II. Salinity Effects

An oyster population model coupled with a model for Haplosporidium nelsoni, the causative agent of the oyster disease MSX, was used with salinity time-series constructed from Delaware River flow measurements to study environmentally-induced variations in the annual cycle of this disease in Delaware Bay oyster populations. Model simulations for the lower Bay (high salinity) sire reproduced the annual cycle observed in lower Delaware Bay. Simulations at both upper Bay (low salinity) and lower Bay sites produced prevalences and intensities that were consistent with field observations. At all sites, low freshwater discharge resulted in increased disease levels, whereas high freshwater discharge produced decreased levels. At upper Bay sites, simulated changes in runoff produced high variability in disease prevalence; in the lower Bay, they produced a much lesser effect. Changes in salinity within the 10-20 ppt range produced the greatest changes in disease levels and patterns. Simulated shifts in timing of the spring runoff from March to either February or May affected the mid-Bay (13-19 ppt) only. A February runoff reduced the spring prevalence peak and caused a complete loss of systemic infections. In contrast, a May discharge occurred too late to affect parasite proliferation in the spring so that the spring peak was higher than average. Almost 100% of the infections were systemic by June, which resulted in high oyster mortality during July at this site. Model results indicate that parasite infection intensity under changing salinity is more complex than a simple function of salinity as it affects parasite proliferation and death rates within the oyster, and that the rate of infection is most likely reduced at low salinity. The simulated results demonstrate the ability of the model to reproduce field measurements and its usefulness in elucidating the association between the magnitude and timing of Delaware River discharge, its associated salinity variations, and the H. nelsoni annual cycle

Outcomes of Asymmetric Selection Pressure and Larval Dispersal on Evolution of Disease Resistance: A Metapopulation Modeling Study With Oysters

Marine diseases are a strong selective force that can have important economic and ecological consequences. Larval dispersal patterns, selective mortality and individual growth rates can modulate metapopulation responses to disease pressure. Here, we use a modeling framework that includes distinct populations, connected via larval transport, with varying disease selection pressure and connectivity to examine how these dynamics enhance or inhibit the evolution of disease resistance in metapopulations. Our system, oysters and MSX disease, is one in which disease resistance is highly and demonstrably heritable. Simulations show that under conditions of population isolation (i.e. local retention of larvae) and strong disease selection, populations rapidly evolve genetic disease resistance. Varying the patterns of larval dispersal alone doubles the time for evolution of disease resistance. Spatially varying disease in the absence of larval dispersal leaves some populations unable to respond to the disease, whereas adding larval dispersal slows the response of populations under strong selection and speeds the response in populations under low selection when fitness is based on relatively limited genetic structure (‘juvenile fitness’ in our simulations). Under spatially variable disease pressure, larval dispersal generates a fourfold greater variance in fitness outcomes across the dispersal patterns tested. In a metapopulation, populations experiencing lower selection pressure will tend to slow the development of other, more heavily selected populations. This suggests that conservation efforts aimed at improving overall metapopulation resistance in the face of marine diseases should target those populations under modest or high disease pressure, rather than protecting those experiencing low selective pressure