Modeling the Dose Response Relationship of Waterborne Acanthamoeba
This study developed dose response models for determining the probability of eye or central nervous system infections from previously conducted studies using different strains of Acanthamoeba spp. The data were a result of animal experiments using mice and rats exposed corneally and intranasally to...
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| Veröffentlicht in: | Risk analysis 2021-01, Vol.41 (1), p.79-91 |
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| creator | Dean, Kara Tamrakar, Sushil Huang, Yin Rose, Joan B. Mitchell, Jade |
| description | This study developed dose response models for determining the probability of eye or central nervous system infections from previously conducted studies using different strains of Acanthamoeba spp. The data were a result of animal experiments using mice and rats exposed corneally and intranasally to the pathogens. The corneal inoculations of Acanthamoeba isolate Ac 118 included varied amounts of Corynebacterium xerosis and were best fit by the exponential model. Virulence increased with higher levels of C. xerosis. The Acanthamoeba culbertsoni intranasal study with death as an endpoint of response was best fit by the beta‐Poisson model. The HN‐3 strain of A. castellanii was studied with an intranasal exposure and three different endpoints of response. For all three studies, the exponential model was the best fit. A model based on pooling data sets of the intranasal exposure and death endpoint resulted in an LD50 of 19,357 amebae. The dose response models developed in this study are an important step towards characterizing the risk associated with free‐living amoeba like Acanthamoeba in drinking water distribution systems. Understanding the human health risk posed by free‐living amoeba will allow for quantitative microbial risk assessments that support building design decisions to minimize opportunities for pathogen growth and survival. |
| doi_str_mv | 10.1111/risa.13603 |
| format | Article |
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The corneal inoculations of Acanthamoeba isolate Ac 118 included varied amounts of Corynebacterium xerosis and were best fit by the exponential model. Virulence increased with higher levels of C. xerosis. The Acanthamoeba culbertsoni intranasal study with death as an endpoint of response was best fit by the beta‐Poisson model. The HN‐3 strain of A. castellanii was studied with an intranasal exposure and three different endpoints of response. For all three studies, the exponential model was the best fit. A model based on pooling data sets of the intranasal exposure and death endpoint resulted in an LD50 of 19,357 amebae. The dose response models developed in this study are an important step towards characterizing the risk associated with free‐living amoeba like Acanthamoeba in drinking water distribution systems. Understanding the human health risk posed by free‐living amoeba will allow for quantitative microbial risk assessments that support building design decisions to minimize opportunities for pathogen growth and survival.</description><identifier>ISSN: 0272-4332</identifier><identifier>EISSN: 1539-6924</identifier><identifier>DOI: 10.1111/risa.13603</identifier><identifier>PMID: 33047815</identifier><language>eng</language><publisher>United States: Blackwell Publishing Ltd</publisher><subject>Acanthamoeba ; Acanthamoeba - pathogenicity ; Amoeba ; Animal research ; Animals ; beta‐Poisson model ; Building design ; Central nervous system ; Central Nervous System Infections - diagnosis ; Central Nervous System Infections - parasitology ; Cornea ; Corynebacterium ; Death & dying ; Disease Models, Animal ; dose response ; Drinking water ; exponential model ; Exposure ; Eye Infections, Parasitic - diagnosis ; Health risks ; Inoculation ; Likelihood Functions ; Mice ; microbial risk assessment ; Microorganisms ; Models, Statistical ; Nasal sprays ; Nervous system ; Pathogens ; Rats ; Risk assessment ; Risk Assessment - methods ; Virulence ; Water - parasitology ; Water distribution ; Water distribution systems ; Water engineering</subject><ispartof>Risk analysis, 2021-01, Vol.41 (1), p.79-91</ispartof><rights>2020 Society for Risk Analysis</rights><rights>2020 Society for Risk Analysis.</rights><rights>2021 Society for Risk Analysis</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2723-61dca741bdacb0fe28222ac777b722d0f07fd761eab70e4b1750a9017a4ed3293</citedby><cites>FETCH-LOGICAL-c2723-61dca741bdacb0fe28222ac777b722d0f07fd761eab70e4b1750a9017a4ed3293</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Frisa.13603$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Frisa.13603$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,778,782,1414,27913,27914,45563,45564</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33047815$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Dean, Kara</creatorcontrib><creatorcontrib>Tamrakar, Sushil</creatorcontrib><creatorcontrib>Huang, Yin</creatorcontrib><creatorcontrib>Rose, Joan B.</creatorcontrib><creatorcontrib>Mitchell, Jade</creatorcontrib><title>Modeling the Dose Response Relationship of Waterborne Acanthamoeba</title><title>Risk analysis</title><addtitle>Risk Anal</addtitle><description>This study developed dose response models for determining the probability of eye or central nervous system infections from previously conducted studies using different strains of Acanthamoeba spp. The data were a result of animal experiments using mice and rats exposed corneally and intranasally to the pathogens. The corneal inoculations of Acanthamoeba isolate Ac 118 included varied amounts of Corynebacterium xerosis and were best fit by the exponential model. Virulence increased with higher levels of C. xerosis. The Acanthamoeba culbertsoni intranasal study with death as an endpoint of response was best fit by the beta‐Poisson model. The HN‐3 strain of A. castellanii was studied with an intranasal exposure and three different endpoints of response. For all three studies, the exponential model was the best fit. A model based on pooling data sets of the intranasal exposure and death endpoint resulted in an LD50 of 19,357 amebae. The dose response models developed in this study are an important step towards characterizing the risk associated with free‐living amoeba like Acanthamoeba in drinking water distribution systems. Understanding the human health risk posed by free‐living amoeba will allow for quantitative microbial risk assessments that support building design decisions to minimize opportunities for pathogen growth and survival.</description><subject>Acanthamoeba</subject><subject>Acanthamoeba - pathogenicity</subject><subject>Amoeba</subject><subject>Animal research</subject><subject>Animals</subject><subject>beta‐Poisson model</subject><subject>Building design</subject><subject>Central nervous system</subject><subject>Central Nervous System Infections - diagnosis</subject><subject>Central Nervous System Infections - parasitology</subject><subject>Cornea</subject><subject>Corynebacterium</subject><subject>Death & dying</subject><subject>Disease Models, Animal</subject><subject>dose response</subject><subject>Drinking water</subject><subject>exponential model</subject><subject>Exposure</subject><subject>Eye Infections, Parasitic - diagnosis</subject><subject>Health risks</subject><subject>Inoculation</subject><subject>Likelihood Functions</subject><subject>Mice</subject><subject>microbial risk assessment</subject><subject>Microorganisms</subject><subject>Models, Statistical</subject><subject>Nasal sprays</subject><subject>Nervous system</subject><subject>Pathogens</subject><subject>Rats</subject><subject>Risk assessment</subject><subject>Risk Assessment - methods</subject><subject>Virulence</subject><subject>Water - parasitology</subject><subject>Water distribution</subject><subject>Water distribution systems</subject><subject>Water engineering</subject><issn>0272-4332</issn><issn>1539-6924</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kEtLw0AUhQdRbK1u_AEScCNC6p1HMs2y1lehIlTFZZgkNzaSZOJMgvTfO22qCxfezT2Lj8PhI-SUwpi6uzKFVWPKQ-B7ZEgDHvlhxMQ-GQKTzBecswE5svYDgAIE8pAMOAchJzQYkutHnWFZ1O9eu0LvRlv0lmgbXW9DqdrCxVXReDr33lSLJtGmRm-aqrpdqUpjoo7JQa5Kiye7PyKvd7cvswd_8XQ_n00XfupmcD-kWaqkoEmm0gRyZBPGmEqllIlkLIMcZJ7JkKJKJKBIqAxARUClEphxFvERueh7G6M_O7RtXBU2xbJUNerOxkwEEAYgKTj0_A_6oTtTu3WOmkgmROQmjchlT6VGW2swjxtTVMqsYwrxxmy8MRtvzTr4bFfZJRVmv-iPSgfQHvgqSlz_UxUv58_TvvQbUmWB_g</recordid><startdate>202101</startdate><enddate>202101</enddate><creator>Dean, Kara</creator><creator>Tamrakar, Sushil</creator><creator>Huang, Yin</creator><creator>Rose, Joan B.</creator><creator>Mitchell, Jade</creator><general>Blackwell Publishing Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7U7</scope><scope>7U9</scope><scope>8BJ</scope><scope>8FD</scope><scope>C1K</scope><scope>FQK</scope><scope>FR3</scope><scope>H94</scope><scope>JBE</scope><scope>JQ2</scope><scope>KR7</scope><scope>M7N</scope><scope>SOI</scope><scope>7X8</scope></search><sort><creationdate>202101</creationdate><title>Modeling the Dose Response Relationship of Waterborne Acanthamoeba</title><author>Dean, Kara ; Tamrakar, Sushil ; Huang, Yin ; Rose, Joan B. ; Mitchell, Jade</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2723-61dca741bdacb0fe28222ac777b722d0f07fd761eab70e4b1750a9017a4ed3293</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Acanthamoeba</topic><topic>Acanthamoeba - pathogenicity</topic><topic>Amoeba</topic><topic>Animal research</topic><topic>Animals</topic><topic>beta‐Poisson model</topic><topic>Building design</topic><topic>Central nervous system</topic><topic>Central Nervous System Infections - diagnosis</topic><topic>Central Nervous System Infections - parasitology</topic><topic>Cornea</topic><topic>Corynebacterium</topic><topic>Death & dying</topic><topic>Disease Models, Animal</topic><topic>dose response</topic><topic>Drinking water</topic><topic>exponential model</topic><topic>Exposure</topic><topic>Eye Infections, Parasitic - diagnosis</topic><topic>Health risks</topic><topic>Inoculation</topic><topic>Likelihood Functions</topic><topic>Mice</topic><topic>microbial risk assessment</topic><topic>Microorganisms</topic><topic>Models, Statistical</topic><topic>Nasal sprays</topic><topic>Nervous system</topic><topic>Pathogens</topic><topic>Rats</topic><topic>Risk assessment</topic><topic>Risk Assessment - methods</topic><topic>Virulence</topic><topic>Water - parasitology</topic><topic>Water distribution</topic><topic>Water distribution systems</topic><topic>Water engineering</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dean, Kara</creatorcontrib><creatorcontrib>Tamrakar, Sushil</creatorcontrib><creatorcontrib>Huang, Yin</creatorcontrib><creatorcontrib>Rose, Joan B.</creatorcontrib><creatorcontrib>Mitchell, Jade</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>International Bibliography of the Social Sciences</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Environment Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Risk analysis</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dean, Kara</au><au>Tamrakar, Sushil</au><au>Huang, Yin</au><au>Rose, Joan B.</au><au>Mitchell, Jade</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modeling the Dose Response Relationship of Waterborne Acanthamoeba</atitle><jtitle>Risk analysis</jtitle><addtitle>Risk Anal</addtitle><date>2021-01</date><risdate>2021</risdate><volume>41</volume><issue>1</issue><spage>79</spage><epage>91</epage><pages>79-91</pages><issn>0272-4332</issn><eissn>1539-6924</eissn><abstract>This study developed dose response models for determining the probability of eye or central nervous system infections from previously conducted studies using different strains of Acanthamoeba spp. The data were a result of animal experiments using mice and rats exposed corneally and intranasally to the pathogens. The corneal inoculations of Acanthamoeba isolate Ac 118 included varied amounts of Corynebacterium xerosis and were best fit by the exponential model. Virulence increased with higher levels of C. xerosis. The Acanthamoeba culbertsoni intranasal study with death as an endpoint of response was best fit by the beta‐Poisson model. The HN‐3 strain of A. castellanii was studied with an intranasal exposure and three different endpoints of response. For all three studies, the exponential model was the best fit. A model based on pooling data sets of the intranasal exposure and death endpoint resulted in an LD50 of 19,357 amebae. The dose response models developed in this study are an important step towards characterizing the risk associated with free‐living amoeba like Acanthamoeba in drinking water distribution systems. Understanding the human health risk posed by free‐living amoeba will allow for quantitative microbial risk assessments that support building design decisions to minimize opportunities for pathogen growth and survival.</abstract><cop>United States</cop><pub>Blackwell Publishing Ltd</pub><pmid>33047815</pmid><doi>10.1111/risa.13603</doi><tpages>13</tpages></addata></record> |
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| source | MEDLINE; Wiley Online Library Journals Frontfile Complete; EBSCOhost Business Source Complete |
| subjects | Acanthamoeba Acanthamoeba - pathogenicity Amoeba Animal research Animals beta‐Poisson model Building design Central nervous system Central Nervous System Infections - diagnosis Central Nervous System Infections - parasitology Cornea Corynebacterium Death & dying Disease Models, Animal dose response Drinking water exponential model Exposure Eye Infections, Parasitic - diagnosis Health risks Inoculation Likelihood Functions Mice microbial risk assessment Microorganisms Models, Statistical Nasal sprays Nervous system Pathogens Rats Risk assessment Risk Assessment - methods Virulence Water - parasitology Water distribution Water distribution systems Water engineering |
| title | Modeling the Dose Response Relationship of Waterborne Acanthamoeba |
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