Innate host responses to enteric bacterial pathogens: a balancing act between resistance and tolerance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Infection by enteric bacterial pathogens activates pathogen recognition receptors, leading to innate responses that promote host defence. While responses that promote host 'resistance' to infection, through the release of antimicrobial mediators, or the recruitment of inflammatory cells aimed at clearing the infection are best known, recent studies have begun to identify additional innate driven responses that instead promote intestinal tissue repair and host survival. Described as infection 'tolerance' responses, we and others have primarily studied these responses in the Citrobacter rodentium infection model. In this review we discuss the impact of innate resistance mechanisms on host defence, and describe how 'tolerance' responses act primarily on the intestinal epithelium, triggering epithelial cell proliferation, repair or promoting barrier function. Resistance and tolerance responses appear to work together, with tolerance repairing the tissue injury caused by resistance driven inflammation. Tolerance responses fit a pattern where innate immunity and inflammation are tightly regulated in the gastrointestinal tract. Moreover, tolerance may have developed due to the successful subversion and avoidance of host resistance by enteric bacterial pathogens. Further studies are needed to clarify the contribution of different pathogen recognition receptors to tolerance and resistance responses against bacterial pathogens, in the gut or in other host tissues.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 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 it