B subunit of<i>Escherichia coli</i>heat-labile enterotoxin as adjuvant of humoral immune response in recombinant BCG vaccination
Bibliographic record
Abstract
The B subunit of Escherichia coli heat-labile enterotoxin (LTB), a nontoxic molecule with potent biological properties, is a powerful mucosal and parenteral adjuvant that induces a strong immune response against co-administered or coupled antigens. In this paper, the effect of LTB on the humoral immune response to recombinant BCG (rBCG) vaccination was evaluated. Isogenic mice were immunized with rBCG expressing the R1 repeat region of the P97 adhesin of Mycoplasma hyopneumoniae alone (rBCG/R1) or fused to LTB (rBCG/LTBR1). Anti-R1 systemic antibody levels (IgG1, IgG2a, IgG2b, IgG3, IgM, and IgA) were measured by ELISA using recombinant R1 as antigen. With the exception of IgM, LTB doubled the anti-R1 antibody levels in rBCG vaccination. The IgG1/IgG2a mean ratio showed that both rBCG/LTBR1 and rBCG/R1 induced a mixed Th1/Th2 immune response. Interestingly, anti-R1 serum IgA was induced only by rBCG/LTBR1. These results demonstrate that LTB has an adjuvant effect on the humoral immune response to recombinant antigens expressed in BCG.
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) | 0.000 | 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) | 0.001 | 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".