Experimental evaluation of protection and immunogenicity of Streptococcus suis bacterin-based vaccines formulated with different commercial adjuvants in weaned piglets
Bibliographic record
Abstract
Streptococcus suis is an important swine pathogen responsible for economic losses to the swine industry worldwide. There is no effective commercial vaccine against S. suis. The use of autogenous ("bacterin") vaccines to control S. suis outbreaks is a frequent preventive measure in the field, although scientific data on immunogenicity and reduction in mortality and morbidity are scarce. The goal of our study is to experimentally evaluate the immunogenicity and protective efficacy against homologous challenge in weaned piglets of a S. suis serotype 2 bacterin-based vaccine formulated with six different commercial adjuvants (Alhydrogel®, Emulsigen®-D, Quil-A®, Montanide™ ISA 206 VG, Montanide™ ISA 61 VG, and Montanide™ ISA 201 VG). The vaccine formulated with Montanide™ ISA 61 VG induced a significant increase in anti-S. suis antibodies, including both IgG1 and IgG2 subclasses, protected against mortality and significantly reduced morbidity and severity of clinical signs. Vaccines formulated with Montanide ISA 206 VG or Montanide ISA 201 VG also induced a significant increase in anti-S. suis antibodies and showed partial protection and reduction of clinical signs severity. Vaccines formulated with Alhydrogel®, Emulsigen®-D, or Quil-A® induced a low and IgG1-shifted antibody response and failed to protect vaccinated piglets against a homologous challenge. In conclusion, the type of adjuvant used in the vaccine formulation significantly influenced the immune response and efficacy of the vaccine against a homologous challenge.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.002 |
| 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".