Cell Surface Modifications with Trifluoromethyl Dinitrophenyl-Soluble Protein Conjugates: Immunogenic Role of Noncovalently Bound Hapten
Bibliographic record
Abstract
Bovine serum albumin (BSA) was derivatized, under mild conditions, with trifluoromethyl-dinitrophenyl (CF3-DNP), a haptenic group cross-reacting with trinitrophenyl (TNP). High-field nuclear magnetic resonance of fluorine (19F-NMR) permitted to calculate the number of covalently and noncovalently bound haptenic groups per BSA molecule. Further dialysis against paratoluene sulfonic acid permitted to obtain CF3-DNP-BSA conjugates from which noncovalently bound hapten had been removed. Soluble conjugates containing 4 covalently bound plus 1 noncovalently bound hapten groups, or only 4 covalently bound groups, were added to splenocytes in culture. These splenocytes, after such treatments, were added to effector lymphocytes in a 5-day culture aimed at the generation of cytotoxic T lymphocytes (CTL) against the CF3-DNP-induced cell surface modification antigens. It was found that only the BSA conjugates that contained noncovalently bound haptens were able to generate CTL against target cells whose surface had been directly modified with CF3-DNP, whereas BSA bearing only covalently bound hapten groups were not. Replacing BSA by human serum albumin, or CF3-DNP by TNP, gave comparable results. Thus, under the conditions used, haptenic groups covalently bound to their soluble carrier protein did not generate hapten-dependent CTL, but noncovalently bound or free haptenic groups at very low concentration were able to do so.
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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) | 0.000 | 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".