PSA Fluoroimmunoassays Using Anti-PSA ScFv and Quantum-Dot Conjugates
Why this work is in the frame
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Bibliographic record
Abstract
AIMS: The conjugates of monoclonal antibodies and luminescent nanoparticles (quantum dots [Qdots]) have a large number of potential applications in both fluoroimmunoassays and biological imaging; however, conjugating full-length antibody monoclonal antibodies directly to Qdots or other inorganic nanoparticles often results in the irreversible formation of oligomeric monoclonal antibody-nanoparticle complexes, which leads to dramatically reduced binding activities. This study demonstrated that the use of single-chain antibody fragments (scFvs) appears to have a number of advantages, in terms of solubility, activity, ease of preparation and ease of structure-based genetic engineering. MATERIALS & METHODS: Two antiprostate-specific antigen scFvs mutants--one with an 11-residue c-myc (referred as scFvB80-M1) and the other with a lysine-enriched His 6-tagging peptide attached to their C-termini (referred as scFvB80-M2)--were prepared. These two scFv mutants were conjugated directly with CdSe/ZnS Qdots and their binding activities were measured and compared. RESULTS & DISCUSSION: Both scFv mutants can be conjugated covalently with CdSe/ZnS Qdots; however, the resulting conjugates exhibit significantly different affinities in the prostate-specific antigen fluoroimmunoassays--the binding activity of scFvB80-M2/Qdots is equivalent of that of free scFvB80 and four times of that of scFvB80-M1/Qdots. CONCLUSION: This study demonstrates that binding activity of scFv/Qdot conjugates can be improved through structure-based genetic engineering of the scFv.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it