Enhancing Specific-Antibody Production to the ragB Vaccine with GITRL That Expand Tfh, IFN-γ+ T Cells and Attenuates Porphyromonas gingivalis Infection in Mice
Bibliographic record
Abstract
The outer membrane protein RagB is one of the major virulence factors of the periodontal pathogen Porphyromonas gingivalis (P. gingivalis). In order to induce protective immune response against P. gingivalis infection, an mGITRL gene-linked ragB DNA vaccine (pIRES-ragB-mGITRL ) was constructed. Six-week-old female BALB/c mice were immunized with pIRES-ragB-mGITRL through intramuscular injection and then challenged by subcutaneous injection in the abdomen with P. gingivalis. RagB-specific antibody-forming cells were evaluated by an Enzyme-linked immunosorbent spot, and specific antibody was determined by enzyme-linked immunosorbent assay. In addition, the frequencies of Tfh and IFN-γ(+) T cells in spleen were measured using flow cytometer, and the levels of IL-21 and IFN-γ mRNA or proteins were detected by real time RT-PCR or ELISA. The data showed that the mGITRL-linked ragB DNA vaccine induced higher levels of RagB-specific IgG in serum and RagB-specific antibody-forming cells in spleen. The frequencies of Tfh and IFN-γ(+) T cells were obviously expanded in mice immunized by pIRES-ragB-mGITRL compared with other groups (pIRES or pIRES-ragB ). The levels of Tfh and IFN-γ(+) T cells associated cytokines were also significantly increased in pIRES-ragB-mGITRL group. Therefore, the mice immunized with ragB plus mGITRL showed the stronger resistant to P. gingivalis infection and a significant reduction of the lesion size caused by P. gingivalis infection comparing with other groups. Taken together, our findings demonstrated that intramuscular injection of DNA vaccine ragB together with mGITRL induced protective immune response dramatically by increasing Tfh and IFN-γ(+) T cells and antibody production to P. gingivalis.
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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".