Potential Therapeutic Efficacy of Allergen-Monomethoxypolyethylene Glycol Conjugates for in vivo Inactivation of Sensitized Mast Cells Responsible for Common Allergies and Asthma
Bibliographic record
Abstract
Skin sites of rats, which had been systemically sensitized to ovalbumin (OVA) were injected intradermally with murine anti-DNP IgE mAbs or with murine polyspecific IgE to recombinant Bet v 1. Injection of OVA(mPEG)10-11 conjugates into these skin sites inhibited passive cutaneous anaphylaxis (PCA) on subsequent intravenous challenge with DNP44-BSA and rBet v 1; by contrast, neither OVA nor an unrelated mPEG conjugate affected the PCA reactions. In dogs sensitized to both OVA and ragweed pollen extract (RAG), inhalation of either allergen (AL) caused a dramatic increase in airway resistance (Rrs). By contrast, administration of an aerosol of OVA(mPEG) caused no change in Rrs. Moreover, thereafter, (1) in spite of repeated challenges with aerosolized OVA over many months, the increase in Rrs on inhalation of OVA was blocked and (2) insufflation of RAG resulted in increase in Rrs of only about 50% in relation to that prior to inhalation of the conjugate; this dog's anti-RAG hyperreactivity remained blunted over many months. It is concluded that AL-mPEG conjugates of optimal composition inactivate sensitized mast cells and basophils, as manifested by a significant decrease of cutaneous or airway responses on subsequent challenge with the respective AL(s).
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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".