The impact of national systems of innovation on therapeutic cloning : a comparison between the UK and China in the clinical area of diabetes.
Bibliographic record
Abstract
Common approaches for purification of RNAs synthesized in vitro by the T7 RNA polymerase often denature the RNA and produce RNAs with chemically heterogeneous 5'- and 3'-ends. Thus, native affinity purification strategies that incorporate 5' and 3' trimming technologies provide a solution to two main disadvantages that arise from standard approaches for RNA purification. This chapter describes procedures for nondenaturing affinity purification of in vitro transcribed RNA using a 3'-ARiBo tag, which yield RNAs with a homogeneous 3'-end. The applicability of the method to RNAs of different sequences, secondary structures, and sizes (29-614 nucleotides) is described, including suggestions for troubleshooting common problems. In addition, this chapter presents three complementary approaches to producing 5'-homogeneity of the affinity-purified RNA: (1) selection of the starting sequence; (2) Cse3 endoribonuclease cleavage of a 5'-CRISPR tag; or (3) self-cleavage of a 5'-hammerhead ribozyme tag. The additional steps to express and purify the Cse3 endonuclease are detailed. In light of recent results, the advantages and limitations of current approaches to achieve 5'-homogeneity of affinity-purified RNA are discussed, such that one can select a suitable strategy to purify the RNA of interest.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".