Construction of recombinant lactobacilli expressing the core neutralizing epitope (COE) of porcine epidemic diarrhea virus and a fusion protein consisting of COE and<i>Escherichia coli</i>heat-labile enterotoxin B, and comparison of the immune responses by orogastric immunization
Bibliographic record
Abstract
The core neutralizing epitope (COE) region of porcine epidemic diarrhea virus (PEDV) plays an important role in the development of the subunit vaccine against PEDV infection. To enhance the vaccine's immunogenicity, Escherichia coli heat-labile enterotoxin B (LTB) has usually been adopted as a molecular adjuvant. In this study, the COE and LTB-COE genes were engineered into the Lactobacillus -Escherichia coli shuttle vectors pSAPG1 (surface-displaying) and pSAPG2 (secreting) followed by electrotransformation into Lactobacillus casei (Lc) to yield the following recombinant strains: Lc:PG1-LTB-COE, Lc:PG2-LTB-COE, Lc:PG1-COE, and Lc:PG2-COE. Our results showed that mice immunized orogastrically with L. casei expressing COE or LTB-COE produced secretory immunoglobulin A and immunoglobulin G with the ability to neutralize PEDV in sera and mucus. Moreover, higher levels of interleukin-4 and gamma interferon were also exhibited compared with negative control. These data displayed the tendency of Lc:PG2-LTB-COE > Lc:PG1-LTB-COE > Lc:PG2-COE > Lc:PG1-COE at the same time point. Taken together, LTB-COE is more suitable for Lactobacillus expressing system to engineer mucosal vaccine against PEDV infection.
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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 | 0.001 | 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 | 0.001 |
| 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".