A novel platform for biologically active recombinant human interleukin‐13 production
Bibliographic record
Abstract
Interleukin-13 (IL-13) is a pleiotropic regulatory cytokine with the potential for treating several human diseases, including type-1 diabetes. Thus far, conventional expression systems for recombinant IL-13 production have proven difficult and are limited by efficiency. In this study, transgenic plants were used as a novel expression platform for the production of human IL-13 (hIL-13). DNA constructs containing hIL-13 cDNA were introduced into tobacco plants. Transcriptional expression of the hIL-13 gene in transgenic plants was confirmed by reverse transcriptase-polymerase chain reaction and Northern blotting. Western blot analysis showed that the hIL-13 protein was efficiently accumulated in transgenic plants and present in multiple molecular forms, with an expression level as high as 0.15% of total soluble protein in leaves. The multiple forms of plant-derived recombinant hIL-13 (rhIL-13) are a result of differential N-linked glycosylation, as revealed by enzymatic and chemical deglycosylation, but not of disulphide-linked oligomerization. In vitro trypsin digestion indicated that plant rhIL-13 was more resistant than unglycosylated control rhIL-13 to proteolysis. The stability of plant rhIL-13 to digestion was further supported with simulated gastric and intestinal fluid digestion. In vitro bioassays using a factor-dependent human erythroleukaemic cell line (TF-1 cells) showed that plant rhIL-13 retained the biological functions of the authentic hIL-13 protein. These results demonstrate that transgenic plants are superior to conventional cell-based expression systems for the production of rhIL-13. Moreover, transgenic plants synthesizing high levels of rhIL-13 may prove to be an attractive delivery system for direct oral administration of IL-13 in the treatment of clinical diseases such as type-1 diabetes.
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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".