Effect of Anti-DNP IgG1- and lgG2a-Secreting Hybridomas in vivo on the Development of an Anti-DNP IgE Antibody Response in Mice
Bibliographic record
Abstract
We reported previously that CBA mice pretreated with dinitrophenyl-Bordetella pertussis (DNP-BP) conjugates exhibited sharply decreased anti-DNP IgE, and increased IgG2a antibodies following immunization with DNP-ovalbumin (DNP-OA) in alum. The objective of the present experiments was to determine whether the decrease in anti-DNP IgE was attributed to a regulatory effect exerted by IgG2a antibodies. Anti-DNP monoclonal antibodies (Mab) of the IgG1 or IgG2a isotype were passively transferred to mice, 24 h before a primary immunization with DNP-OA in alum. Anti-DNP IgE production was drastically suppressed in recipients of IgG1 but not of IgG2a Mab. Similar results were obtained when the Mab were endogenously produced by intraperitoneal implantation of anti-DNP-secreting hybridomas into (BALB/cxCBA)F1 (BCF1) mice. However, neither IgG1 nor IgG2a isotypes suppressed IgE antibody production if the hybridoma implantation took place 10 days after hapten priming. These results are, to our knowledge, the first to show a clear dissociation between the effect of either passively transferred or endogenously secreted IgG1 and IgG2a antibodies in their ability to inhibit a primary anti-hapten IgE antibody 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".