Functional Construction of the Anti--Mucin Core Protein (MUC1) Antibody MUSE11 Variable Regions in a Bacterial Expression System
Bibliographic record
Abstract
A bacterial expression system for the variable region fragments (Fvs) of the anti-MUC1 tumor antigen antibody MUSE11 has been constructed. The Fv fragment showed binding specificity toward TFK-1 cells, with slightly reduced affinity compared to its parent IgG. The single-chain Fv fragment was arranged in two orders, VH-linker-VL and VL-linker-VH. However, linking the regions with a flexible peptide linker (GGGGS)(3) or with a shorter linker (GGGGS) led to a dramatic decrease in the biological activity toward the target antigen in both arrangements, suggesting that the MUSE11 antibody loses its activity when the domains are linked with polypeptide linkers. These results indicate that the variable region domains of the anti-MUC1 antibody MUSE11 have specificity only in the Fv form, and that linking the domains strongly reduces the association with its target antigen. Gel filtration analysis indicates that the scFv has a dimeric structure, suggesting that the inactivation of MUSE11 scFv is due to unfavorable intermolecular associations of the scFv chains. To our knowledge, this is the first report of a significant reduction in affinity caused by linking the variable domains in both arrangements, i.e., VH-VL and VL-VH.
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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".