An NMR Metabolomics Study of Elk Inoculated with Chronic Wasting Disease
Bibliographic record
Abstract
Chronic wasting disease (CWD) is a fatal neurodegenerative disease affecting both farmed and wild cervids, specifically deer and elk, and is a member of the larger family of prion diseases. Prion disease transmission is believed to occur through exposure to infectious prion material-a misfolded and infectious form of the prion protein that is normally present in the host. Chronic wasting disease is endemic to regions of central North America and infectious material can persist for long periods in the environment, posing challenges for remediation and monitoring. The current methods of detection are relatively invasive, require the host animal to be in intermediate to late stages of disease incubation, and are not without risk to those collecting samples. The potential for a blood test that could identify key biomarkers of disease incubation is of great interest. Serum from elk (Cervus elaphus) (n = 4) was collected on a monthly schedule before, and following, oral inoculation of CWD-positive homogenate, and collection continued until clinical signs were apparent. Blood was collected on the same schedule for a group of control animals (n = 2) housed under identical conditions. Targeted profiling, using (1)H-nuclear magnetic resonance (NMR) spectroscopy, of serum metabolites was used to yield metabolite identification as well as quantitation. Hierarchical multivariate statistical orthogonal partial least-squares (O-PLS) models were generated to identify predictive components in the data. Due to the duration of the study (25 mo) a significant aging component was taken into account during analysis. Several metabolites were correlated with aging in elk inoculated with CWD, but not in the control group.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".