Foodborne Transmission of Bovine Spongiform Encephalopathy to Non-Human Primates Results in Preclinical Rapid-Onset Obesity
Bibliographic record
Abstract
Obesity has become one of the largest public health challenges worldwide. Recently, certain bacterial and viral pathogens have been implicated in the pathogenesis of obesity. In the present study, we retrospectively analyzed clinical data, plasma samples and post-mortem tissue specimens derived from a risk assessment study in bovine spongiform encephalopathy (BSE)-infected female cynomolgus monkeys (Macaca fascicularis). The original study design aimed to determine minimal infectious doses after oral or intracerebral (i.c.) infection of macaques to assess the risk for humans. High-dose exposures resulted in 100% attack rates and a median incubation time of 4.7 years as described previously. Retrospective analyses of clinical data from high-dosed macaques revealed that foodborne BSE transmission caused rapid weight gain within 1.5 years post infection (β = 0.915; P<0.0001) which was not seen in age- and sex-matched control animals or i.c. infected animals. The rapid-onset obesity was not associated with impaired pancreatic islet function or glucose metabolism. In the early preclinical phase of oral transmission associated with body weight gain, prion accumulation was confined to the gastrointestinal tract. Intriguingly, immunohistochemical findings suggest that foodborne BSE transmission has a pathophysiological impact on gut endocrine cells which may explain rapid weight gain. To our knowledge, this is the first experimental model which clearly demonstrates that foodborne pathogens can induce obesity.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".