Mucosal and systemic immune responses induced by a single time vaccination strategy in mice
Bibliographic record
Abstract
Vaccination is considered by the World Health Organization as the most cost-effective strategy for controlling infectious diseases. In spite of great successes with vaccines, many infectious diseases are still leading killers, because of the inadequate coverage of many vaccines. Several factors have been responsible: number of doses, high vaccine reactogenicity, vaccine costs, vaccination policy, among others. Contradictorily, few vaccines are of single dose and even less of mucosal administration. However, more common infections occur via mucosa, where secretory immunoglobulin A plays an essential role. As an alternative, we proposed a novel protocol of vaccination called Single Time Vaccination Strategy (SinTimVaS) by immunizing 2 priming doses at the same time: one by mucosal route and the other by parenteral route. Here, the mucosal and systemic responses induced by Finlay adjuvants (AF Proteoliposome 1 and AF Cochleate 1) implementing SinTimVaS in BALB/c mice were evaluated. One intranasal dose of AF Cochleate 1 and an intramuscular dose of AF Proteoliposome 1 adsorbed onto aluminum hydroxide, with bovine serum albumin or tetanus toxoid as model antigens, administrated at the same time, induced potent specific mucosal and systemic immune responses. Also, we demonstrated that SinTimVaS using other mucosal routes like oral and sublingual, in combination with the subcutaneous route elicits immune responses. SinTimVaS, as a new immunization strategy, could increase vaccination coverage and reduce time-cost vaccines campaigns, adding the benefits of immune response in mucosa.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".