Assessing Milk from CWD-Lactating Deer for Infectious Prions
Bibliographic record
Abstract
Transmissible spongiform encephalopathies (TSEs), or prions, cause a fatal neurodegenerative disease affecting mammals including bovine spongiform encephalopathy (BSE) in cattle, scrapie in sheep, variant Creutzfeldt-Jakob disease in humans and chronic wasting disease (CWD) in deer, elk and moose. CWD, the only prion disease to infect a native free-ranging population, has now been detected in 22 American states, 2 Canadian provinces and South Korea. While horizontal transmission is credited for much of the spread of CWD, few studies have monitored the potential for vertical/maternal transmission with an emphasis on lactation. Using a small, polyestrous cervid— the Reeves’ muntjac deer— we are addressing this issue by supplementing naive Reeve’s muntjac fawns (n=5) with milk collected from CWD-inoculated, pre-clinical and clinical muntjac doe. Blood, saliva, feces, urine and lymphoid biopsies will be collected from milk-exposed fawns at 10d, 21d, 40d, 3mo, 6mo, 12 and 18 mo pi to aid in CWD diagnosis. Similar samples, with the addition of mammary biopsy, will be collected from each mother doe at 3 months intervals to monitor CWD status. CWD fawn and mother doe CWD status will be monitored by immunohistochemistry, real time quaking induced conversion assay (RT-QuIC), protein misfolding cyclic amplification (PMCA) and clinical disease progression The results of this study will establish: 1) if there are sufficient infectious prions in the milk of lactating doe to transmit disease to offspring and 2) if mother to offspring transmission plays a role in the high efficiency with which CWD is transmitted in nature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".