Modulating Effect of Passive Immunization with Anti-Mycobacterium tuberculosis Antibodies on Humoral Response in BCG-Infected Mice
Bibliographic record
Abstract
Previous work has shown that the passive immunization with rabbit anti-Mycobacterium tuberculosis H37Rv antiserum of Mycobacterium bovis BCG-infected mice promotes the growth of bacilli in their spleen and induces a late production of antimycobacterial antibodies in their serum. The effect of the passive immunization on the early antibody response in infected mice has now been investigated. It was found that passive immunization with H37Rv antiserum of BCG-infected mice depressed the early humoral response as determined by the plaque-forming cell response to BCG extract when compared with BCG-infected mice treated with the antiserum freed from its mycobacterial antibodies as controls. In the BCG-infected mice treated with the rabbit antiserum freed from mycobacterial antibodies or treated with saline, the antibodies were present in the serum as soluble immune complexes which reached a peak 4 days after infection. These immune complexes were formed with mice antimycobacterial antibodies as determined with an antimouse immunoglobulin serum in the double diffusion test. On the other hand, in BCG-infected mice passively immunized with rabbit antimycobacterial serum, the immune complexes detected were mainly composed of transfer rabbit antimycobacterial antibodies as established with an antirabbit immunoglobulin serm. Comparison of the biphasic humoral response in passively-enhanced mycobacterial infection and allotransplanted normal tissue in the host is discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 |
| 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".