Chapter 3 Xenotropic Murine Leukemia Virus-Related Virus as a Case Study: Using a Precautionary Risk Management Approach for Emerging Blood-Borne Pathogens in Canada
Bibliographic record
Abstract
In October 2009 it was reported that 68 of 101 patients with chronic fatigue syndrome (CFS) in the United States, when tested, were infected with a novel gamma retrovirus, xenotropic murine leukemia virus-related virus (XMRV) (Lombardi et al., 2009). XMRV is a recently discovered human gammaretrovirus first described in prostate cancers that shares significant homology with murine leukemia virus (MLV) (Ursiman et al., 2006). It is known that XMRV can cause leukemias and sarcomas in several rodent, feline, and primate species but has not been shown to cause disease in humans. XMRV was detectable in the peripheral blood mononuclear cells (PBMCs) and plasma of individuals diagnosed with CFS (Lombardi et al., 2009). After this report was published there was a great deal of uncertainty surrounding this emergent virus and its involvement in the etiology of CFS. The uncertainty was, in part, due to CFS being a complex, poorly understood multi-system disorder with different disease criteria used for its diagnosis. CFS, also known as Myalgic Encephalomyelitis (ME), is a debilitating disease of unknown origin that is estimated to affect 17 million people worldwide. The initial report connecting XMRV to prostate cancers and CFS garnered significant media and scientific interest since it provided a potential Susie ElSaadany2**, Tamer Oraby1 * Daniel Krewski1, 4 and Peter R. Ganz5 1McLaughlin Centre for Population Health Risk Assessment, Institute of Population Health, University of Ottawa, Ontario, Canada 2Blood Safety Surveillance and Health Care Acquired Infections Division, Centre for Communicable Diseases and Infection Control, Public Health Agency of Canada, Ottawa, Ontario, Canada 3Aspinall and Associates, Cleveland House, High Street, and Earth Sciences, Bristol University, Bristol, United Kingdom 4Department of Epidemiology and Community Medicine, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada 5Health Canada, Director’s Office, Ottawa, Ontario, Canada ** Corresponding Author , Marian Laderoute2 , Jun Wu2 , Willy Aspinall3 , www.intechopen.com 32 The Continuum of Health Risk Assessments explanation for the disease but also an avenue for possible therapeutic treatments since XMRV is known to be susceptible to some anti-retroviral drugs (Cohen, 2011).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".