The role of polyamines, Na+ and K+ in the formation of triple helices between purine oligonucleotides and the promoter region of the human c-src proto-oncogene
Bibliographic record
Abstract
Binding constants for triplex formation between purine-rich oligonucleotides and a pyrimidine.purine tract of the human c-src proto-oncogene were measured by fluorescence polarization in the presence of polyamines, Na(+) and K(+). In both the hexamine and tetramine series, the longer polyamines had the larger binding constants for triplex formation at low concentrations of polyamine. At higher concentrations all values tended to plateau in the 10(9)/M range. In contrast to previous reports, K(+) did not inhibit triplex formation and at 150 mM the binding constants were again in the 10(9)/M range for both an 11mer and 22mer oligonucleotide. At 150 mM K(+) the addition of polyamines did not lead to any significant increase in the binding constants. It was determined that the lack of inhibition by K(+) was due to the low concentration (1 nM) of purine oligonucleotide required for the fluorescence polarization technique. At higher concentrations (1 microM) self-association of the oligonucleotide was observed. These results suggest that in vivo, at least for the c-src promoter, the inhibition of triplex formation by K(+) may not be detrimental. However, it may be difficult to achieve binding constants above approximately 10(9)/M even in the presence of polycations.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".