Protective efficacy of recombinant exotoxin A — flagellin fusion protein against <i>Pseudomonas aeruginosa</i> infection
Bibliographic record
Abstract
Pseudomonas aeruginosa is an opportunistic bacterium that causes serious nosocomial infection in immunocompromised patients. The aim of this study was to prepare a fusion protein consisting of exotoxin A (ExoA) and flagellin (Fla) from P. aeruginosa and to evaluate its potential as a vaccine candidate against P. aeruginosa infection. The genes encoding for ExoA and Fla proteins were cloned in-frame and expressed in Escherichia coli. The recombinant ExoA-Fla fusion protein was purified by Ni-NTA affinity chromatography. Mice were immunized subcutaneously with ExoA, Fla, and ExoA-Fla fusion proteins, and the humoral immune response was evaluated by ELISA method. The immunized and control group mice were challenged with a 2× LD50 (7.5 × 10(7) CFU) of P. aeruginosa for the protection assay. The results indicated that vaccination with Fla, ExoA, and ExoA-Fla fusion proteins produced a significant amount of specific immunoglobulin G antibodies. Immunization of mice with ExoA-Fla fusion protein showed significant protection against intraperitoneal challenge with 7.5 × 10(7) CFU (2× LD50) P. aeruginosa. Results of this study suggest that recombinant ExoA-Fla fusion protein is a highly immunogenic protective protein showing promise as a vaccine candidate against P. aeruginosa.
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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 | 0.000 |
| 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".