Quantitative Analysis of Porcine Reproductive and Respiratory Syndrome (PRRS) Viremia Profiles from Experimental Infection: A Statistical Modelling Approach
Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically significant viral diseases facing the global swine industry. Viremia profiles of PRRS virus challenged pigs reflect the severity and progression of infection within the host and provide crucial information for subse...
Gespeichert in:
| Veröffentlicht in: | PloS one 2013-12, Vol.8 (12), p.e83567-e83567 |
|---|---|
| Hauptverfasser: | , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | e83567 |
|---|---|
| container_issue | 12 |
| container_start_page | e83567 |
| container_title | PloS one |
| container_volume | 8 |
| creator | Islam, Zeenath U Bishop, Stephen C Savill, Nicholas J Rowland, Raymond R. R Lunney, Joan K Trible, Benjamin Doeschl-Wilson, Andrea B Meng, Xiang-Jin |
| description | Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically significant viral diseases facing the global swine industry. Viremia profiles of PRRS virus challenged pigs reflect the severity and progression of infection within the host and provide crucial information for subsequent control measures. In this study we analyse the largest longitudinal PRRS viremia dataset from an in-vivo experiment. The primary objective was to provide a suitable mathematical description of all viremia profiles with biologically meaningful parameters for quantitative analysis of profile characteristics. The Wood's function, a gamma-type function, and a biphasic extended Wood's function were fit to the individual profiles using Bayesian inference with a likelihood framework. Using maximum likelihood inference and numerous fit criteria, we established that the broad spectrum of viremia trends could be adequately represented by either uni- or biphasic Wood's functions. Three viremic categories emerged: cleared (uni-modal and below detection within 42 days post infection(dpi)), persistent (transient experimental persistence over 42 dpi) and rebound (biphasic within 42 dpi). The convenient biological interpretation of the model parameters estimates, allowed us not only to quantify inter-host variation, but also to establish common viremia curve characteristics and their predictability. Statistical analysis of the profile characteristics revealed that persistent profiles were distinguishable already within the first 21 dpi, whereas it is not possible to predict the onset of viremia rebound. Analysis of the neutralizing antibody(nAb) data indicated that there was a ubiquitous strong response to the homologous PRRSV challenge, but high variability in the range of cross-protection of the nAbs. Persistent pigs were found to have a significantly higher nAb cross-protectivity than pigs that either cleared viremia or experienced rebound within 42 dpi. Our study provides novel insights into the nature and degree of variation of hosts' responses to infection as well as new informative traits for subsequent genomic and modelling studies. |
| doi_str_mv | 10.1371/journal.pone.0083567 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_1468886348</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A478243056</galeid><doaj_id>oai_doaj_org_article_d51c5a6cd7e54c6abd168553eaadc3d9</doaj_id><sourcerecordid>A478243056</sourcerecordid><originalsourceid>FETCH-LOGICAL-c650t-fad52b6193336a10bc679c6aef5f56e76d215a5a7376a131d6afa7d104665ebb3</originalsourceid><addsrcrecordid>eNqNUsFuEzEQXSEQLYU_QGCJSzkk2Ou1d8MBKaoKRCoiJJSrNbG9qaONvdibivwLH8tsk5YG9YB9sOV582bm-WXZS0aHjJfs3Spsoodm2AZvh5RWXMjyUXbMRjwfyJzyx_fuR9mzlFaUCl5J-TQ7ygsuqnwkjrPf3zbgO9dB564tGSPhNrlEQk2mIWrnLZnZNgaz0TcA8AYfUusidCFuyXzrTQxrS06ns9n8Lfnhol07INMYatfYRGqMkvNfrY1ubX0HDZn42iJZ8O_JmMz7wqlzGgNfgrFN4_ySjFssCfrqefakhibZF_vzJLv8eP797PPg4uunydn4YqCloN2gBiPyhcRpOZfA6ELLcqQl2FrUQtpSmpwJEFDyEsOcGQk1lIbRQkphFwt-kr3e8bZNSGovbFKskFVVSV5UiJjsECbASrU4DMStCuDUzUOISwURx2isMoJpAVKb0ooCu1gYJishuAUwmpsRcn3YV9ss1tZolCVCc0B6GPHuSi3Dteo_LxccCU73BDH83NjUqbVLGrUDb8MmqZziYlT8B5QVI1qiF3iB0Df_QB8WYo9aAs7qfB2wRd2TqnFRVmgsKiSihg-gcBt0h0bD9uY4TCh2CTqGlKKt7-RgVPV2v21G9XZXe7tj2qv7Ut4l3fr778_WEBQso0vqcp5TJlGhnBZ5zv8AJhwIjw</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1468886348</pqid></control><display><type>article</type><title>Quantitative Analysis of Porcine Reproductive and Respiratory Syndrome (PRRS) Viremia Profiles from Experimental Infection: A Statistical Modelling Approach</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><source>Public Library of Science (PLoS)</source><creator>Islam, Zeenath U ; Bishop, Stephen C ; Savill, Nicholas J ; Rowland, Raymond R. R ; Lunney, Joan K ; Trible, Benjamin ; Doeschl-Wilson, Andrea B ; Meng, Xiang-Jin</creator><creatorcontrib>Islam, Zeenath U ; Bishop, Stephen C ; Savill, Nicholas J ; Rowland, Raymond R. R ; Lunney, Joan K ; Trible, Benjamin ; Doeschl-Wilson, Andrea B ; Meng, Xiang-Jin</creatorcontrib><description>Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically significant viral diseases facing the global swine industry. Viremia profiles of PRRS virus challenged pigs reflect the severity and progression of infection within the host and provide crucial information for subsequent control measures. In this study we analyse the largest longitudinal PRRS viremia dataset from an in-vivo experiment. The primary objective was to provide a suitable mathematical description of all viremia profiles with biologically meaningful parameters for quantitative analysis of profile characteristics. The Wood's function, a gamma-type function, and a biphasic extended Wood's function were fit to the individual profiles using Bayesian inference with a likelihood framework. Using maximum likelihood inference and numerous fit criteria, we established that the broad spectrum of viremia trends could be adequately represented by either uni- or biphasic Wood's functions. Three viremic categories emerged: cleared (uni-modal and below detection within 42 days post infection(dpi)), persistent (transient experimental persistence over 42 dpi) and rebound (biphasic within 42 dpi). The convenient biological interpretation of the model parameters estimates, allowed us not only to quantify inter-host variation, but also to establish common viremia curve characteristics and their predictability. Statistical analysis of the profile characteristics revealed that persistent profiles were distinguishable already within the first 21 dpi, whereas it is not possible to predict the onset of viremia rebound. Analysis of the neutralizing antibody(nAb) data indicated that there was a ubiquitous strong response to the homologous PRRSV challenge, but high variability in the range of cross-protection of the nAbs. Persistent pigs were found to have a significantly higher nAb cross-protectivity than pigs that either cleared viremia or experienced rebound within 42 dpi. Our study provides novel insights into the nature and degree of variation of hosts' responses to infection as well as new informative traits for subsequent genomic and modelling studies.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0083567</identifier><identifier>PMID: 24358295</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Animal lactation ; Animals ; Antibodies, Viral - metabolism ; Antibody Formation ; Bayes Theorem ; Bayesian analysis ; Bayesian theory ; Biological models (mathematics) ; Biology ; Blood ; control methods ; cross immunity ; Cross-protection ; data collection ; Disease control ; Disease Progression ; Experimental infection ; Functions (mathematics) ; Growth models ; Hogs ; Homology ; hosts ; Immunology ; Infection ; Infections ; Livestock ; Mathematical models ; Medical research ; Models, Animal ; Models, Statistical ; Mutation ; neutralizing antibodies ; Parameter estimation ; Porcine reproductive and respiratory syndrome ; Porcine Reproductive and Respiratory Syndrome - blood ; Porcine Reproductive and Respiratory Syndrome - immunology ; Porcine Reproductive and Respiratory Syndrome - virology ; Porcine reproductive and respiratory syndrome virus ; Porcine respiratory and reproductive syndrome virus - physiology ; Pork industry ; PRRS ; PRRS virus ; Quantitative analysis ; Statistical analysis ; Statistical inference ; Statistical modelling ; Statistical models ; Swine ; Swine Diseases - immunology ; Swine Diseases - virology ; Vaccines ; Veterinary colleges ; Veterinary medicine ; Viral diseases ; Viremia ; Viremia - immunology ; Viremia - pathology ; Virology ; Virus Replication ; Viruses</subject><ispartof>PloS one, 2013-12, Vol.8 (12), p.e83567-e83567</ispartof><rights>COPYRIGHT 2013 Public Library of Science</rights><rights>2013 Islam et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2013 Islam et al 2013 Islam et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c650t-fad52b6193336a10bc679c6aef5f56e76d215a5a7376a131d6afa7d104665ebb3</citedby><cites>FETCH-LOGICAL-c650t-fad52b6193336a10bc679c6aef5f56e76d215a5a7376a131d6afa7d104665ebb3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3866253/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3866253/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24358295$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Islam, Zeenath U</creatorcontrib><creatorcontrib>Bishop, Stephen C</creatorcontrib><creatorcontrib>Savill, Nicholas J</creatorcontrib><creatorcontrib>Rowland, Raymond R. R</creatorcontrib><creatorcontrib>Lunney, Joan K</creatorcontrib><creatorcontrib>Trible, Benjamin</creatorcontrib><creatorcontrib>Doeschl-Wilson, Andrea B</creatorcontrib><creatorcontrib>Meng, Xiang-Jin</creatorcontrib><title>Quantitative Analysis of Porcine Reproductive and Respiratory Syndrome (PRRS) Viremia Profiles from Experimental Infection: A Statistical Modelling Approach</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically significant viral diseases facing the global swine industry. Viremia profiles of PRRS virus challenged pigs reflect the severity and progression of infection within the host and provide crucial information for subsequent control measures. In this study we analyse the largest longitudinal PRRS viremia dataset from an in-vivo experiment. The primary objective was to provide a suitable mathematical description of all viremia profiles with biologically meaningful parameters for quantitative analysis of profile characteristics. The Wood's function, a gamma-type function, and a biphasic extended Wood's function were fit to the individual profiles using Bayesian inference with a likelihood framework. Using maximum likelihood inference and numerous fit criteria, we established that the broad spectrum of viremia trends could be adequately represented by either uni- or biphasic Wood's functions. Three viremic categories emerged: cleared (uni-modal and below detection within 42 days post infection(dpi)), persistent (transient experimental persistence over 42 dpi) and rebound (biphasic within 42 dpi). The convenient biological interpretation of the model parameters estimates, allowed us not only to quantify inter-host variation, but also to establish common viremia curve characteristics and their predictability. Statistical analysis of the profile characteristics revealed that persistent profiles were distinguishable already within the first 21 dpi, whereas it is not possible to predict the onset of viremia rebound. Analysis of the neutralizing antibody(nAb) data indicated that there was a ubiquitous strong response to the homologous PRRSV challenge, but high variability in the range of cross-protection of the nAbs. Persistent pigs were found to have a significantly higher nAb cross-protectivity than pigs that either cleared viremia or experienced rebound within 42 dpi. Our study provides novel insights into the nature and degree of variation of hosts' responses to infection as well as new informative traits for subsequent genomic and modelling studies.</description><subject>Analysis</subject><subject>Animal lactation</subject><subject>Animals</subject><subject>Antibodies, Viral - metabolism</subject><subject>Antibody Formation</subject><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Bayesian theory</subject><subject>Biological models (mathematics)</subject><subject>Biology</subject><subject>Blood</subject><subject>control methods</subject><subject>cross immunity</subject><subject>Cross-protection</subject><subject>data collection</subject><subject>Disease control</subject><subject>Disease Progression</subject><subject>Experimental infection</subject><subject>Functions (mathematics)</subject><subject>Growth models</subject><subject>Hogs</subject><subject>Homology</subject><subject>hosts</subject><subject>Immunology</subject><subject>Infection</subject><subject>Infections</subject><subject>Livestock</subject><subject>Mathematical models</subject><subject>Medical research</subject><subject>Models, Animal</subject><subject>Models, Statistical</subject><subject>Mutation</subject><subject>neutralizing antibodies</subject><subject>Parameter estimation</subject><subject>Porcine reproductive and respiratory syndrome</subject><subject>Porcine Reproductive and Respiratory Syndrome - blood</subject><subject>Porcine Reproductive and Respiratory Syndrome - immunology</subject><subject>Porcine Reproductive and Respiratory Syndrome - virology</subject><subject>Porcine reproductive and respiratory syndrome virus</subject><subject>Porcine respiratory and reproductive syndrome virus - physiology</subject><subject>Pork industry</subject><subject>PRRS</subject><subject>PRRS virus</subject><subject>Quantitative analysis</subject><subject>Statistical analysis</subject><subject>Statistical inference</subject><subject>Statistical modelling</subject><subject>Statistical models</subject><subject>Swine</subject><subject>Swine Diseases - immunology</subject><subject>Swine Diseases - virology</subject><subject>Vaccines</subject><subject>Veterinary colleges</subject><subject>Veterinary medicine</subject><subject>Viral diseases</subject><subject>Viremia</subject><subject>Viremia - immunology</subject><subject>Viremia - pathology</subject><subject>Virology</subject><subject>Virus Replication</subject><subject>Viruses</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqNUsFuEzEQXSEQLYU_QGCJSzkk2Ou1d8MBKaoKRCoiJJSrNbG9qaONvdibivwLH8tsk5YG9YB9sOV582bm-WXZS0aHjJfs3Spsoodm2AZvh5RWXMjyUXbMRjwfyJzyx_fuR9mzlFaUCl5J-TQ7ygsuqnwkjrPf3zbgO9dB564tGSPhNrlEQk2mIWrnLZnZNgaz0TcA8AYfUusidCFuyXzrTQxrS06ns9n8Lfnhol07INMYatfYRGqMkvNfrY1ubX0HDZn42iJZ8O_JmMz7wqlzGgNfgrFN4_ySjFssCfrqefakhibZF_vzJLv8eP797PPg4uunydn4YqCloN2gBiPyhcRpOZfA6ELLcqQl2FrUQtpSmpwJEFDyEsOcGQk1lIbRQkphFwt-kr3e8bZNSGovbFKskFVVSV5UiJjsECbASrU4DMStCuDUzUOISwURx2isMoJpAVKb0ooCu1gYJishuAUwmpsRcn3YV9ss1tZolCVCc0B6GPHuSi3Dteo_LxccCU73BDH83NjUqbVLGrUDb8MmqZziYlT8B5QVI1qiF3iB0Df_QB8WYo9aAs7qfB2wRd2TqnFRVmgsKiSihg-gcBt0h0bD9uY4TCh2CTqGlKKt7-RgVPV2v21G9XZXe7tj2qv7Ut4l3fr778_WEBQso0vqcp5TJlGhnBZ5zv8AJhwIjw</recordid><startdate>20131217</startdate><enddate>20131217</enddate><creator>Islam, Zeenath U</creator><creator>Bishop, Stephen C</creator><creator>Savill, Nicholas J</creator><creator>Rowland, Raymond R. R</creator><creator>Lunney, Joan K</creator><creator>Trible, Benjamin</creator><creator>Doeschl-Wilson, Andrea B</creator><creator>Meng, Xiang-Jin</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>FBQ</scope><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>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20131217</creationdate><title>Quantitative Analysis of Porcine Reproductive and Respiratory Syndrome (PRRS) Viremia Profiles from Experimental Infection: A Statistical Modelling Approach</title><author>Islam, Zeenath U ; Bishop, Stephen C ; Savill, Nicholas J ; Rowland, Raymond R. R ; Lunney, Joan K ; Trible, Benjamin ; Doeschl-Wilson, Andrea B ; Meng, Xiang-Jin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c650t-fad52b6193336a10bc679c6aef5f56e76d215a5a7376a131d6afa7d104665ebb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Analysis</topic><topic>Animal lactation</topic><topic>Animals</topic><topic>Antibodies, Viral - metabolism</topic><topic>Antibody Formation</topic><topic>Bayes Theorem</topic><topic>Bayesian analysis</topic><topic>Bayesian theory</topic><topic>Biological models (mathematics)</topic><topic>Biology</topic><topic>Blood</topic><topic>control methods</topic><topic>cross immunity</topic><topic>Cross-protection</topic><topic>data collection</topic><topic>Disease control</topic><topic>Disease Progression</topic><topic>Experimental infection</topic><topic>Functions (mathematics)</topic><topic>Growth models</topic><topic>Hogs</topic><topic>Homology</topic><topic>hosts</topic><topic>Immunology</topic><topic>Infection</topic><topic>Infections</topic><topic>Livestock</topic><topic>Mathematical models</topic><topic>Medical research</topic><topic>Models, Animal</topic><topic>Models, Statistical</topic><topic>Mutation</topic><topic>neutralizing antibodies</topic><topic>Parameter estimation</topic><topic>Porcine reproductive and respiratory syndrome</topic><topic>Porcine Reproductive and Respiratory Syndrome - blood</topic><topic>Porcine Reproductive and Respiratory Syndrome - immunology</topic><topic>Porcine Reproductive and Respiratory Syndrome - virology</topic><topic>Porcine reproductive and respiratory syndrome virus</topic><topic>Porcine respiratory and reproductive syndrome virus - physiology</topic><topic>Pork industry</topic><topic>PRRS</topic><topic>PRRS virus</topic><topic>Quantitative analysis</topic><topic>Statistical analysis</topic><topic>Statistical inference</topic><topic>Statistical modelling</topic><topic>Statistical models</topic><topic>Swine</topic><topic>Swine Diseases - immunology</topic><topic>Swine Diseases - virology</topic><topic>Vaccines</topic><topic>Veterinary colleges</topic><topic>Veterinary medicine</topic><topic>Viral diseases</topic><topic>Viremia</topic><topic>Viremia - immunology</topic><topic>Viremia - pathology</topic><topic>Virology</topic><topic>Virus Replication</topic><topic>Viruses</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Islam, Zeenath U</creatorcontrib><creatorcontrib>Bishop, Stephen C</creatorcontrib><creatorcontrib>Savill, Nicholas J</creatorcontrib><creatorcontrib>Rowland, Raymond R. R</creatorcontrib><creatorcontrib>Lunney, Joan K</creatorcontrib><creatorcontrib>Trible, Benjamin</creatorcontrib><creatorcontrib>Doeschl-Wilson, Andrea B</creatorcontrib><creatorcontrib>Meng, Xiang-Jin</creatorcontrib><collection>AGRIS</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Islam, Zeenath U</au><au>Bishop, Stephen C</au><au>Savill, Nicholas J</au><au>Rowland, Raymond R. R</au><au>Lunney, Joan K</au><au>Trible, Benjamin</au><au>Doeschl-Wilson, Andrea B</au><au>Meng, Xiang-Jin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantitative Analysis of Porcine Reproductive and Respiratory Syndrome (PRRS) Viremia Profiles from Experimental Infection: A Statistical Modelling Approach</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2013-12-17</date><risdate>2013</risdate><volume>8</volume><issue>12</issue><spage>e83567</spage><epage>e83567</epage><pages>e83567-e83567</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically significant viral diseases facing the global swine industry. Viremia profiles of PRRS virus challenged pigs reflect the severity and progression of infection within the host and provide crucial information for subsequent control measures. In this study we analyse the largest longitudinal PRRS viremia dataset from an in-vivo experiment. The primary objective was to provide a suitable mathematical description of all viremia profiles with biologically meaningful parameters for quantitative analysis of profile characteristics. The Wood's function, a gamma-type function, and a biphasic extended Wood's function were fit to the individual profiles using Bayesian inference with a likelihood framework. Using maximum likelihood inference and numerous fit criteria, we established that the broad spectrum of viremia trends could be adequately represented by either uni- or biphasic Wood's functions. Three viremic categories emerged: cleared (uni-modal and below detection within 42 days post infection(dpi)), persistent (transient experimental persistence over 42 dpi) and rebound (biphasic within 42 dpi). The convenient biological interpretation of the model parameters estimates, allowed us not only to quantify inter-host variation, but also to establish common viremia curve characteristics and their predictability. Statistical analysis of the profile characteristics revealed that persistent profiles were distinguishable already within the first 21 dpi, whereas it is not possible to predict the onset of viremia rebound. Analysis of the neutralizing antibody(nAb) data indicated that there was a ubiquitous strong response to the homologous PRRSV challenge, but high variability in the range of cross-protection of the nAbs. Persistent pigs were found to have a significantly higher nAb cross-protectivity than pigs that either cleared viremia or experienced rebound within 42 dpi. Our study provides novel insights into the nature and degree of variation of hosts' responses to infection as well as new informative traits for subsequent genomic and modelling studies.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24358295</pmid><doi>10.1371/journal.pone.0083567</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2013-12, Vol.8 (12), p.e83567-e83567 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1468886348 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Analysis Animal lactation Animals Antibodies, Viral - metabolism Antibody Formation Bayes Theorem Bayesian analysis Bayesian theory Biological models (mathematics) Biology Blood control methods cross immunity Cross-protection data collection Disease control Disease Progression Experimental infection Functions (mathematics) Growth models Hogs Homology hosts Immunology Infection Infections Livestock Mathematical models Medical research Models, Animal Models, Statistical Mutation neutralizing antibodies Parameter estimation Porcine reproductive and respiratory syndrome Porcine Reproductive and Respiratory Syndrome - blood Porcine Reproductive and Respiratory Syndrome - immunology Porcine Reproductive and Respiratory Syndrome - virology Porcine reproductive and respiratory syndrome virus Porcine respiratory and reproductive syndrome virus - physiology Pork industry PRRS PRRS virus Quantitative analysis Statistical analysis Statistical inference Statistical modelling Statistical models Swine Swine Diseases - immunology Swine Diseases - virology Vaccines Veterinary colleges Veterinary medicine Viral diseases Viremia Viremia - immunology Viremia - pathology Virology Virus Replication Viruses |
| title | Quantitative Analysis of Porcine Reproductive and Respiratory Syndrome (PRRS) Viremia Profiles from Experimental Infection: A Statistical Modelling Approach |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-05T05%3A44%3A42IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Quantitative%20Analysis%20of%20Porcine%20Reproductive%20and%20Respiratory%20Syndrome%20(PRRS)%20Viremia%20Profiles%20from%20Experimental%20Infection:%20A%20Statistical%20Modelling%20Approach&rft.jtitle=PloS%20one&rft.au=Islam,%20Zeenath%20U&rft.date=2013-12-17&rft.volume=8&rft.issue=12&rft.spage=e83567&rft.epage=e83567&rft.pages=e83567-e83567&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0083567&rft_dat=%3Cgale_plos_%3EA478243056%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1468886348&rft_id=info:pmid/24358295&rft_galeid=A478243056&rft_doaj_id=oai_doaj_org_article_d51c5a6cd7e54c6abd168553eaadc3d9&rfr_iscdi=true |