Functional expression of a single-chain antibody fragment against human epidermal growth factor receptor 2 (HER2) in<i>Escherichia coli</i>
Bibliographic record
Abstract
The human epidermal growth factor receptor (HER) family plays an important role in cell growth and signaling and alteration of its function has been demonstrated in many different kinds of cancer. Receptor dimerization is necessary for the HER signal transduction pathway and tyrosine kinase activity. Recently, several monoclonal antibodies have been developed to directly interfere with ligand-HER receptor binding and receptor dimerization. A single chain variable fragment (ScFv) is a valuable alternative to an intact antibody. This report describes the production and purification of an ScFv specific for domain II of the HER2 receptor in Escherichia coli BL21 (DE3) cytoplasm. The majority of expressed of anti-her2his-ScFv protein was produced as inclusion bodies. A Ni-NTA affinity column was used to purify the anti-her2his-ScFv protein. The molecular weight of anti-her2his-ScFv protein was estimated to be approximately 27 kDa, as confirmed by SDS-PAGE and Western blotting assay. The anti-her2his-ScFv showed near 95 % purity and reached a yield of approximately 29 mg/l in flask fermentation. The purified anti-her2his-ScFv showed its biological activity by binding to HER2 receptor on the surface of BT-474 cells. This ScFv may be a potential pharmaceutical candidate for targeting tumour cells overexpressing HER2 receptor.
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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 | 0.001 |
| 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".