The immune responses elicited by six recombinant antigens of Mycoplasma hyopneumoniae in mice
Bibliographic record
Abstract
Mycoplasma hyopneumoniae (M. hyopneumoniae) is the causative agent of swine enzootic pneumonia, resulting in substantial economic losses in global pig farming. Although vaccination is the primary strategy for controlling M. hyopneumoniae infection, current vaccines fall short in preventing transmission of this pathogen or protecting the body from secondary infection. This study aimed to assess the immunogenicity of six recombinant antigens (P97R1, P46, GAPDH, PdhA, DnaK, and EF-Tu) of M. hyopneumoniae through intramuscular immunization in mice. The results showed that the six antigens elicited high levels of serum IgG. Among them, P97R1, P46, PdhA, and DnaK stimulated robust antigen-specific IgA mucosal immune responses. CCK-8 assays revealed that both P97R1 and DnaK significantly increased the proliferation of mononuclear cells from spleen and lung, and DnaK also promoted the proliferation of blood mononuclear cells. Additionally, PdhA induced Th17-type immune response with a high level of IL-17 level in serum. Flow cytometry analysis indicated that P97R1 and PdhA increased the ratio of CD8+/CD4+ T lymphocyte, favoring cytotoxic T lymphocyte (CTL) immune responses. Notably, P97R1 immunization significantly decreased the percentages of CD4+ T cells while increased the percentages of CD8+ T cells. The present findings demonstrate that the candidate antigens P97R1, PdhA, and DnaK of M. hyopneumoniae induce specific humoral and mucosal immunity; P97R1 and DnaK also stimulated intense cellular immunity, and PdhA induced CTL and Th17-type immune responses. In conclusion, P97R1, PdhA, and DnaK emerge as potential candidate antigens for the future development of a more effective subunit vaccine against M. hyopneumoniae.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".