TLR2, but not TLR4, plays a predominant role in the immune responses to cholera vaccines
Bibliographic record
Abstract
Vibrio cholerae can cause severe diarrhea and dehydration leading to high mortality and morbidity. Current cholera vaccines are formulated with KVC. Although the innate immune responses following vaccination deeply influence the induction of adaptive immunity, the initial recognition of cholera vaccines by the host innate immune system is not well characterized. In this study, the ability of KVC to induce innate immune responses was investigated. Unlike typical Gram-negative bacteria stimulating TLR2 and TLR4, KVC activated TLR2 but hardly TLR4. However, purified V. cholerae LPS preferentially stimulated TLR4, although not as potently as LPS of other Gram-negative bacteria, implying that LPS is not a major immunostimulatory component of KVC. Instead, MPFs were similar to KVC in the capacity to activate TLR2, transcription factors, and cytokine expression. Furthermore, OmpU is an abundant membrane protein of V. cholerae and could interact with TLR2 for inducing cytokine expression. Notably, cholera vaccine-induced immune responses are impaired in TLR2(-/-) mice. Conclusively, TLR2 is essential for the immune responses to cholera vaccination, and OmpU is the major immunostimulatory component of cholera vaccines.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".