Bibliographic record
Abstract
Some of the studies employing nonantigenic, nonallergenic and tolerogenic derivatives of antigens and allergens, synthesized by coupling onto them an optimal number (n) of molecules of monomethoxy-polyethylene glycol (mPEG), are briefly reviewed. Administration of antigen (mPEG)n conjugates into mice resulted in specific immunosuppression, which was mediated by antigen-specific suppressor T (Ts) cells and by suppressor factor(s) (TsF) produced by these cells. These Ts cells were cloned and shown to be Thy-1.2+, CD3+, CD4––, CD5––, CD8+, and expressed the αβ heterodimer of conventional T cell receptors (TCR). The TsF had the functional activity of Ts cells and possessed at least one epitope related to the α-chain of TCR. The results of clinical trials of mPEG conjugates of common allergens are briefly referred to; it is suggested that the time is opportune for the evaluation of the therapeutic efficacy of mPEG conjugates of pure allergens which can be synthesized on an industrial scale by recombinant DNA technology. Finally, possible applications of tolerogenic mPEG conjugates of xenogeneic monoclonal antibodies, immunotoxins and immunogenic recombinant lymphokines to the development of immunotherapeutic strategies in oncology, transplantation, autoimmunity and acquired immunodeficiency syndrome are 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.175 | 0.103 |
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".