Impaired innate immune response and enhanced pathology during Citrobacter rodentium infection in mice lacking functional P-selectin
Bibliographic record
Abstract
The selectin family of adhesion molecules mediates recruitment of immune cells to sites of inflammation which is critical for host resistance against infection. To characterize the role of selectins in host defence against Citrobacter rodentium infection, wild-type (WT) mice and mice lacking P-selectin glycoprotein ligand-1 (PSGL-1), P-, E- and L-selectin were infected using a Citrobacter-induced colitis model. Infected mice lacking PSGL-1 or P-selectin showed a more pronounced morbidity associated with higher bacterial load, elevated IL-12 p70, TNF-alpha, IFN-gamma, MCP-1 and IL-6 production, more severe inflammation and surprisingly higher leucocyte infiltration in the guts than WT control. Recruitment of neutrophils and macrophages and caecal inflammation were drastically reduced in infected P-selectin knockout mice receiving blocking monoclonal antibodies to ICAM-1 or LFA-1, indicating that these adhesion molecules may compensate for the loss of selectins in leucocyte recruitment. Furthermore, the adaptive immune response in mice lacking PSGL-1 or P-selectin remained functional since these infected mice were capable of eradicating the bacteria and being protected upon re-challenge with C. rodentium. These data demonstrate a definitive phenotypic impairment of innate response in mice lacking PSGL-1 or P-selectin, and suggest that these adhesion molecules are important in host innate immune response against Citrobacter infection.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".