The influence of commensal bacteria on anti-viral immunity (39.26)
Bibliographic record
Abstract
Abstract Alterations in the composition of intestinal commensal bacteria in humans are associated with enhanced susceptibility to multiple inflammatory diseases suggesting that signals derived from commensal bacteria may influence the development and/or function of the immune system. Supporting this, germ-free or gnotobiotic mice exhibit reduced numbers of lymphocytes in the intestinal intraepithelial compartment. However, whether alterations in the acquisition or composition of commensal bacteria influence immunity to infection remains poorly defined. To test this, mice housed under conventional or gnotobiotic conditions were infected i.p. with Lymphocytic Choriomeningitis Virus (LCMV). At day 7 post-infection, gnotobiotic mice exhibited a significant reduction in the frequency and number of LCMV-specific CD8+ T cells in multiple tissues including the spleen and intraepithelial compartment. Furthermore, LCMV-specific CD8+ T cells from gnotobiotic mice were less capable of producing IFN-γ following LCMV peptide stimulation. In addition, at day 36 post-infection, when conventionally-housed mice have established a LCMV-specific CD8+ memory T cell population, gnotobiotic mice had a significantly impaired population of LCMV-specific CD8+ memory T cells. Diminished LCMV-specific CD8+ effector and memory T cell responses were not the result of inherent defects in gnotobiotic mice as oral administration of a cocktail of antibiotics to conventionally-housed mice also displayed a defective LCMV-specific CD8+ T cell response following infection. Collectively, these data suggest an integral role of commensal bacteria in influencing virus specific CD8+ T cell effector and memory responses.
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) | 0.002 | 0.001 |
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".