Trained immunity of intestinal tuft cells during infancy enhances host defense against enteroviral infections in mice
Bibliographic record
Abstract
Innate immune cells have been acknowledged as trainable in recent years. While intestinal tuft cells are recognized for their crucial roles in the host defense against intestinal pathogens, there remains uncertainty regarding their trainability. Enterovirus 71 (EV71), a prevalent enterovirus that primarily infects children but rarely infects adults. At present, there is a significant expansion of intestinal tuft cells in the EV71-infected mouse model, which is associated with EV71-induced interleukin-25 (IL-25) production. Further, we found that IL-25 pre-treatment at 2 weeks old mouse enabled tuft cells to acquire immune memory. This was evidenced by the rapid expansion and stronger response of IL-25-trained tuft cells in response to EV71 infection at 6 weeks old, surpassing the reactivity of naïve tuft cells in mice without IL-25-trained progress. Interestingly, IL-25-trained intestinal tuft cells exhibit anti-enteroviral effect via producing a higher level of IL-25. Mechanically, IL-25 treatment upregulates spermidine/spermine acetyl-transferase enzyme (SAT1) expression, mediates intracellular polyamine deficiency, further inhibits enterovirus replication. In summary, tuft cells can be trained by IL-25, which supports faster and higher level IL-25 production in response to EV71 infection and further exhibits anti-enteroviral effect via SAT1-mediated intracellular polyamine deficiency. Given that IL-25 can be induced by multiple gut microbes during human growth and development, including shifts in gut flora abundance, which may partially explain the different susceptibility to enteroviral infections between adults and children.
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 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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".