NK T Cell Activation Promotes <i>Chlamydia trachomatis</i> Infection In Vivo
Bibliographic record
Abstract
We used two approaches to examine the role of NK T cells (NKT) in an intracellular bacterial (Chlamydia trachomatis mouse pneumonitis (C. muridarum)) infection. One is to use CD1 gene knockout (KO) mice, which lack NKT, and the other is to activate NKT using alpha-galactosylceramide (alpha-GalCer), a natural ligand of these cells. The data showed a promoting effect of NKT activation on Chlamydia lung infection. Specifically, CD1 KO mice exhibited significantly lower levels of body weight loss, less severe pathological change and lower chlamydial in vivo growth than wild-type mice. Immunological analysis showed that CD1 KO mice exhibited significantly lower C. muridarum-specific IL-4 and serum IgE Ab responses as well as more pronounced delayed-type hypersensitivity response compared with wild-type controls. In line with the finding in KO mice, the in vivo stimulation of NKT using alpha-GalCer enhanced chlamydial growth in vivo, which were correlated with reduced delayed-type hypersensitivity response and increased C. muridarum-driven IL-4/IgE production. Moreover, neutralization of IL-4 activity in the alpha-GalCer-treated BALB/c mice significantly reduced the promoting effect of alpha-GalCer treatment on chlamydial growth in vivo. These data provide in vivo evidence for the involvement of NKT in a bacterial pathogenesis and its role in promoting Th2 responses during 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) | 0.000 | 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) | 0.001 | 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".