Characterization of Protection Against Coronavirus Infection by Noninternal Image Antiidiotypic Antibody
Bibliographic record
Abstract
Previously, we have reported protective vaccination of mice against a coronavirus infection using rabbit polyclonal noninternal image Ab2gamma anti-idiotypic (anti-Id) antibody specific for a virus-neutralizing and protective monoclonal antibody (mAb) 7-10A against the viral surface S glycoprotein. To characterize further the mechanisms involved in the induction of protective immunity by this noninternal image anti-Id, plasma and splenocytes from Ab2gamma-immunized BALB/c mice were passively transferred to naive BALB/c mice, followed by viral challenge. A reproducible significant delay in mortality observed in mice to which plasma was passively transferred, together with the presence of specific in vitro neutralizing antiviral Ab3 identified the humoral immune response as the major element responsible for protection. The activation of specific and cross-reactive T lymphocytes by both virus and anti-Id in immunized mice and the absence of adoptive transfer of protection by splenocytes suggested the participation of T helper activity in the induction of protective virus-neutralizing Ab3. To obtain more defined monoclonal reagents for a better understanding of anti-Id-induced protection, mAb2 were generated against the same mAb1 7-10A and characterized. We report the successful generation of mAb2 of the gamma type. However, unlike the polyclonal Ab2gamma, they were not capable of inducing a protective immune response.
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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".