Salmonella expressing a T-cell epitope from Sendai virus are able to induce anti-infection immunity
Bibliographic record
Abstract
Bacterial fimbriae can accept foreign peptides and display them on the cell surface. A highly efficient gene replacement method was used to generate peptide vaccines based on Salmonella enterica subsp. enterica serovar Typhimurium LT2. DNA encoding an epitope from Sendai virus, SV9 (Sendai virus nucleoprotein peptide 324-332, FAPGNYPAL), which is known to induce cytotoxic T lymphocytes, was incorporated into the gene encoding AgfA (the major subunit protein of thin aggregative fimbriae of Salmonella) by replacing an equal length DNA segment. To improve cytotoxic T lymphocyte recognition, both termini of the peptide were flanked by double alanine (AA) or arginine (RR) residues. Western blotting and immunofluorescence microscopy using AgfA-specific antiserum verified the expression of chimeric AgfA; expression was also proved by a Congo red binding assay. Oral immunizations of C57BL/6 mice with the four strains induced an epitope-specific T-cell response (detected by enzyme-linked immunosorbent spot assay). When the mice were challenged with the Sendai virus, the magnitude of the infection was significantly reduced in the immunized groups compared with the controls. The Salmonella fimbrial display system efficiently induces a cellular immune response and anti-infection immunity in vivo, providing a new strategy for the development of efficient peptide vaccination.
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".