CD4+CD25+ Regulatory T Cells Attenuate Lipopolysaccharide-Induced Systemic Inflammatory Responses and Promotes Survival in Murine Escherichia coli Infection
Bibliographic record
Abstract
It is well established that CD4CD25 regulatory T cells (Tregs) downregulate inflammatory immune responses and help to maintain immune homeostasis. Recent reports have shown that ligation of germline encoded pattern recognition receptors such as Toll-like receptors can stimulate Tregs and therefore implicate Tregs in the pathophysiology of sepsis and other inflammatory diseases. In this report, we show that injection of lipopolysaccharide (LPS) leads to expansion of CD4CD25FoxP3 Tregs, suggesting that these cells may play an important role in immune regulation in LPS-induced acute inflammation. Indeed, genetic or immunological inhibition of Treg function using mice lacking functional Tregs (CD25 KO mice) or anti-CD25 monoclonal antibody (anti-CD25 mAb), respectively, led to acute death in an otherwise nonlethal LPS challenge. This was accompanied by exaggerated production of proinflammatory cytokines. Strikingly, adoptive transfer of CD4CD25 Tregs to CD25 KO mice before LPS challenge rescues mice from death. Unlike LPS, depletion of Tregs followed by concanavalin A (Con A) challenge does not result in mortality, suggesting that Treg depletion does not globally influence all models of acute inflammation. We authenticate our findings by showing that depletion of Tregs leads to mortality in a nonlethal Escherichia coli challenge accompanied by elevated serum levels of proinflammatory cytokines. Collectively, our results indicate that in addition to regulation of LPS-induced acute inflammation, Tregs help to improve bacterial clearance and promote survival in an acute model of bacterial infection.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".