Bibliographic record
Abstract
Abstract We present new data showing that normal IgG immune responses comprise the production of two kinds of antibodies, namely anti-foreign and anti-anti-self antibodies. For example, immunization of C3H mice by two rounds of BL/6 skin grafting results in the production of anti-BL/6 antibodies plus antiidiotypic antibodies (C3H anti-anti-C3H) with the latter being detected using antibodies produced in a BL/6 anti-C3H immune response. Similarly, the IgG immune response of C3H mice to tetanus toxoid includes the production of C3H anti-anti-C3H antibodies. Antigen-specific antibodies produced in one alloimmunization plus antiidiotypic antibodies produced in the converse immunization can be used to synergistically induce specific tolerance. We show that infusions of anti-BL/6 antibodies together with BL/6 anti-anti-BL/6 antibodies specifically suppress an immune response to BL/6 lymphocytes in C3H mice. Specific tolerance was measured as suppression of the induction of BL/6-specific cytotoxic T cells. The two kinds of antibodies with complementary specificity are believed to stimulate two populations of T lymphocytes, and co-selection (mutual selection) of these two populations leads to a new stable steady state of the system that has specifically diminished reactivity to BL/6 tissue. Stimulation with a combination of anti-C3H and C3H anti-anti-C3H IgG antibodies furthermore down-regulates inflammation in a mouse model of inflammatory bowel disease. An analogous combination of C3H anti-BL/6 and BL/6 anti-anti-BL/6 antibodies significantly down-regulates tumour growth and metastases in BALB/c mice in the EMT6 transplantable breast cancer model. We conclude that a combination of certain antigen-specific and antiidiotypic antibodies has potential as a new class of vaccines based on the symmetrical immune network theory. This new kind of vaccine does not involve the production of antibodies. The prevention of two important degenerative diseases makes this a potential anti-aging technology.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".