Construction of pPIC9 Recombinant Vector Containing Human Stem Cell Factor
Bibliographic record
Abstract
PURPOSE: Various cytokine regulates hematopoesis; they promote number of stages in stem cells biology such as proliferation, differentiation and endurance. Biological effects of SCF, as a hematopoietic cytokine; is triggered by binding to its ligand c-kit. Potential therapeutic applications of SCF include hematopoietic stem cell mobilization, exvivo stem/progenitor cell expansion, gene therapy, and immunotherapy. In this study we tried to construct of pPIC9 recombinant vector containing human SCF. METHODS: hSCF cDNA was amplified by PCR and both hSCF cDNA and pPIC9 as yeast expression vector (shuttle vector) digested by EcoR I and Xho I restriction enzymes. Subsequent the digestion reaction, ligation reaction was carried out. In order to verifying of pPIC9 recombinant vector containing hSCF, PCR and sequence analysis was performed. RESULTS: The construction of recombinant expression vector of pPIC9 containing hSCF cDNA was confirmed by sequencing method successfully. CONCLUSION: rhSCF/pPIC9 vector can be transformed into the Picha pastoris yeast as a eukaryotic host in order to produce human SCF at industrial scale.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".