Interleukin-15 and NK1.1<sup>+</sup>Cells Provide Innate Protection against Acute<i>Salmonella enterica</i>Serovar Typhimurium Infection in the Gut and in Systemic Tissues
Bibliographic record
Abstract
Control of bacterial colonization at mucosal surfaces depends on rapid activation of the innate immune system. Interleukin-15 (IL-15) directs the development, maturation, and function of a population of cells positive for NK1.1, such as natural killer (NK) cells, which are critical components of the innate immune defense against several viral and bacterial pathogens. Using IL-15-deficient mice, in vivo depletion of NK1.1(+) cells from wild-type mice, and in vivo overexpression of IL-15 from a recombinant adenovirus, we tested the role of IL-15 and NK1.1(+) cells in innate protection of the murine gut and reticuloendothelial system from Salmonella enterica serovar Typhimurium infection. IL-15 and the NK1.1(+) cell population provided innate protection from serovar Typhimurium in mice at the enteric mucosae and in the reticuloendothelial system during murine typhoid. Interestingly, serovar Typhimurium extensively colonized the gut of IL-15(-/-) mice and wild-type C57BL/6 mice depleted of NK1.1(+) cells prior to infection, even though the animals were not pretreated with antibiotics to reduce colonization resistance and there was an absence of overt inflammation in the colon and cecum. Enhanced dissemination of Salmonella from the gut of mice depleted of NK1.1(+) cells correlated with a localized disruption of IL-17 in the colon. These data suggest a relationship between the gut ecosystem and the innate mucosal immune system, which may be linked via IL-15 and NK1.1(+) cells.
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 | 0.000 |
| 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 | 0.001 |
| 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".