Holland A. Fredrick

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Holland
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A. Fredrick
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  • Article
    The coastal environment and human health : microbial indicators, pathogens, sentinels and reservoirs
    (BioMed Central, 2008-11-07) Stewart, Jill R. ; Gast, Rebecca J. ; Fujioka, Roger S. ; Solo-Gabriele, Helena M. ; Meschke, J. Scott ; Amaral-Zettler, Linda A. ; del Castillo, Erika ; Polz, Martin F. ; Collier, Tracy K. ; Strom, Mark S. ; Sinigalliano, Christopher D. ; Moeller, Peter D. R. ; Holland, A. Fredrick
    Innovative research relating oceans and human health is advancing our understanding of disease-causing organisms in coastal ecosystems. Novel techniques are elucidating the loading, transport and fate of pathogens in coastal ecosystems, and identifying sources of contamination. This research is facilitating improved risk assessments for seafood consumers and those who use the oceans for recreation. A number of challenges still remain and define future directions of research and public policy. Sample processing and molecular detection techniques need to be advanced to allow rapid and specific identification of microbes of public health concern from complex environmental samples. Water quality standards need to be updated to more accurately reflect health risks and to provide managers with improved tools for decision-making. Greater discrimination of virulent versus harmless microbes is needed to identify environmental reservoirs of pathogens and factors leading to human infections. Investigations must include examination of microbial community dynamics that may be important from a human health perspective. Further research is needed to evaluate the ecology of non-enteric water-transmitted diseases. Sentinels should also be established and monitored, providing early warning of dangers to ecosystem health. Taken together, this effort will provide more reliable information about public health risks associated with beaches and seafood consumption, and how human activities can affect their exposure to disease-causing organisms from the oceans.
  • Article
    Environmental controls, oceanography and population dynamics of pathogens and harmful algal blooms: connecting sources to human exposure
    (BioMed Central, 2008-11-07) Dyble, Julianne ; Bienfang, Paul ; Dusek, Eva ; Hitchcock, Gary ; Holland, A. Fredrick ; Laws, Edward A. ; Lerczak, James A. ; McGillicuddy, Dennis J. ; Minnett, Peter ; Moore, Stephanie K. ; O'Kelly, Charles ; Solo-Gabriele, Helena M. ; Wang, John D.
    Coupled physical-biological models are capable of linking the complex interactions between environmental factors and physical hydrodynamics to simulate the growth, toxicity and transport of infectious pathogens and harmful algal blooms (HABs). Such simulations can be used to assess and predict the impact of pathogens and HABs on human health. Given the widespread and increasing reliance of coastal communities on aquatic systems for drinking water, seafood and recreation, such predictions are critical for making informed resource management decisions. Here we identify three challenges to making this connection between pathogens/HABs and human health: predicting concentrations and toxicity; identifying the spatial and temporal scales of population and ecosystem interactions; and applying the understanding of population dynamics of pathogens/HABs to management strategies. We elaborate on the need to meet each of these challenges, describe how modeling approaches can be used and discuss strategies for moving forward in addressing these challenges.
  • Preprint
    Modelling interactions of acid–base balance and respiratory status in the toxicity of metal mixtures in the American oyster Crassostrea virginica
    ( 2009-11-12) Macey, Brett M. ; Jenny, Matthew J. ; Williams, Heidi R. ; Thibodeaux, Lindy K. ; Beal, Marion ; Almeida, Jonas S. ; Cunningham, Charles ; Mancia, Annalaura ; Warr, Gregory W. ; Burge, Erin J. ; Holland, A. Fredrick ; Gross, Paul S. ; Hikima, Sonomi ; Burnett, Karen G. ; Burnett, Louis ; Chapman, Robert W.
    Heavy metals, such as copper, zinc and cadmium, represent some of the most common and serious pollutants in coastal estuaries. In the present study, we used a combination of linear and artificial neural network (ANN) modelling to detect and explore interactions among low-dose mixtures of these heavy metals and their impacts on fundamental physiological processes in tissues of the Eastern oyster, Crassostrea virginica. Animals were exposed to Cd (0.001 – 0.400 μM), Zn (0.001 – 3.059 μM) or Cu (0.002 – 0.787 μM), either alone or in combination for 1 to 27 days. We measured indicators of acid-base balance (hemolymph pH and total CO2), gas exchange (Po2), immunocompetence (total hemocyte counts, numbers of invasive bacteria), antioxidant status (glutathione, GSH), oxidative damage (lipid peroxidation; LPx), and metal accumulation in the gill and the hepatopancreas. Linear analysis showed that oxidative membrane damage from tissue accumulation of environmental metals was correlated with impaired acid-base balance in oysters. ANN analysis revealed interactions of metals with hemolymph acid-base chemistry in predicting oxidative damage that were not evident from linear analyses. These results highlight the usefulness of machine learning approaches, such as ANNs, for improving our ability to recognize and understand the effects of sub-acute exposure to contaminant mixtures.