Expression of fusion IL2-B7.1(IgV+C) and effects on T lymphocytes
Bibliographic record
Abstract
The search for an effective immunotherapeutic treatment for tumors is an important area of cancer research. To prepare a more effective form of the bifunctional fusion protein IL2-B7.1(IgV+C) and analyze its effect on the stimulation of T lymphocyte proliferation, we used DNAStar 5.03 software to predict the structural diversity and biochemical character of IL2-B7.1(IgV+C). We then prepared fusion protein IL2-B7.1(IgV+C) by establishing its prokaryotic expression system, and tested its effect on the stimulation of T lymphocytes in vitro. The results indicated that IL2-B7.1(IgV+C) correctly formed a secondary structure in which both IL2 and B7.1(IgV+C) maintained their original hydrophilicity and epitopes. Western blot analysis revealed that IL2-B7.1(IgV+C) was efficiently expressed. Our analysis of CTLL-2 and T-cell proliferation showed that recombinant human (rh) IL2-B7.1(IgV+C) exerted the combined stimulating effects of both rhIL2 and rh B7.1(IgV+C) on cell proliferation, and that these effects could be blocked by adding either anti-IL2 or anti-B7.1 monoclonal antibodies. A >2-fold increase in [3H]TdR incorporation compared with that of cells treated with recombinant protein IL2, or B7.1(IgV+C) alone, revealed that rhIL2-B7.1(IgV+C) had dose-dependent synergetic effects on T-cell activation in the presence of anti-CD3 monoclonal antibody. We concluded that the augmented potency of rhIL2-B7.1(IgV+C) resulted in a stronger stimulation of T-cell proliferation than either rhB7.1(IgV+C) or rhIL2 alone.
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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 | 0.001 | 0.001 |
| 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".