Immune Status and the Development of Listeria monocytogenes Infection in Aged and Young Guinea Pigs
Bibliographic record
Abstract
PURPOSE: Consuming even low numbers of the foodborne pathogen, Listeria monocytogenes, places the elderly at risk for severe illness. The impact of immunomodulation on the development of listerial infection within a young and aged population after low dose challenge with L. monocytogenes was investigated. METHODS: Animals received daily supplementation of vitamin E for a period of 21 days to promote immunomodulation, and were then orally challenged with 100 CFU of L. monocytogenes. Levels of CD8+, CD4+ and CD3+ T cells were used as markers to determine the influence of daily supplementation with vitamin E on immune response; the spleen and liver were harvested for microbiological analysis. RESULTS: Higher numbers of animals became infected in control groups than in vitamin E-treated group. During the post-challenge period, vitamin E-treated aged animals showed faster CD8+ T cell proliferation than control aged animals. CONCLUSION: Daily supplementation with vitamin E was more beneficial in young compared with aged animals in mitigating listerial infection. Results suggest exposure to even low numbers of L. monocytogenes can result in infection in both healthy young and aged populations.
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".