Bibliographic record
Abstract
In this work, we discussed the importance of heat capacity in evaluation of thermodynamic parameters such as ΔG, ΔH and ΔS. We used DSC to measure directly changes in heat capacity accompanying unfolding of DNA from the promoters of the c-MYC, VEGF and Bcl-2 oncogenes. The most accurate means of determining heat capacity changes accompanying GQ unfolding is provided by DSC measurements. Although DSC has been used to determine changes in heat capacity accompanying duplex-to-single strand transitions, there has been a lack of similar studies of GQ. This study provided conclusive evidence of the existence of ΔCP in GQ unfolding. To further reiterate the dramatic effect that ΔCP has on thermodynamic parameters, the extrapolated values of ΔG, ΔH and ΔS were compared for ΔCP = 0 and ΔCP ≠ 0. When extrapolated to biologically relevant temperatures, the value of ΔG, when ΔCP is neglected, the error margin may be as large as 140%. Moreover, we designed a hairpin-based monomolecular DNA construct to further understand duplex-tetraplex equilibria. The sequence of the hairpin is derived from the c-MYC oncogene with the G-rich and C-rich strands by a T11 link. We used a CD-based approach to characterize the distribution of conformational states as a function of environmental conditions. Our work further reiterated the notion that both GQs and iM can exist in tandem.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".