Quantitative Analysis of Porcine Reproductive and Respiratory Syndrome (PRRS) Viremia Profiles from Experimental Infection
Bibliographic record
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 unior 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. Citation: Islam ZU, Bishop SC, Savill NJ, Rowland RRR, Lunney JK, et al. (2013) Quantitative Analysis of Porcine Reproductive and Respiratory Syndrome (PRRS) Viremia Profiles from Experimental Infection: A Statistical Modelling Approach. PLoS ONE 8(12): e83567. doi:10.1371/journal.pone.0083567 Editor: Xiang-Jin Meng, Virginia Polytechnic Institute and State University, United States of America Received September 17, 2013; Accepted November 13, 2013; Published December 17, 2013 Copyright: 2013 Islam et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: The development of the model fitting code was supported by a Wellcome Trust Project grant to NJS (Grant No. 091078/Z/09/Z, http://www.wellcome. ac.uk/). The characterization of neutralizing antibody responses to PRRSV and association with host factors was supported by the NPB (Grant No. 12–120, http:// www.pork.org/filelibrary/ResearchGrants/Funded2012.pdf). Funding for the project also came from Canada: Application of Genomics to Improve Swine Health and Welfare (http://www.swineimprovement.com/) and CSHB: Development of genetic selection tools to enhance sow health using a novel acclimation challenge model in Canadian commercial herds (http://www.swinehealth.ca/program-research-proj-11.php). This work was supported by the Roslin Institute Strategic Grant funding from the BBSRC (ISPG 1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors received funding from a commercial source, Genome Canada, and are not related to the organisation in the form of: employment, consultancy, patents, products in development, or marketed products. This source of funding does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials. * E-mail: zeenath.islam@roslin.ed.ac.uk
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".