Unfolding of Helical Poly(L-Glutamic Acid) in N,N-Dimethylformamide Probed by Pyrene Excimer Fluorescence (PEF)
Bibliographic record
Abstract
The denaturation undergone by α–helical poly(L-glutamic acid) (PLGA) in N,N-dimethylformamide upon addition of guanidine hydrochloride (GdHCl) was characterized by comparing the fluorescence of a series of PLGA constructs randomly labeled with the dye pyrene (Py-PLGA) to that of a series of Py-PDLGA samples prepared from a racemic mixture of D,L-glutamic acid. The process of pyrene excimer formation (PEF) was taken advantage of to probe changes in the conformation of α–helical Py-PLGA. Fluorescence Blob Model (FBM) analysis of the fluorescence decays of the Py-PLGA and Py-PDLGA constructs yielded the average number ( ) of glutamic acids located inside a blob, which represented the volume probed by an excited pyrenyl label. remained constant for randomly coiled Py-PDLGA but decreased from ~20 to ~10 glutamic acids for the Py-PLGA samples as GdHCl was added to the solution. The decrease in reflected the decrease in the local density of PLGA as the α–helix unraveled in solution. The changes in with GdHCl concentration was used to determine the change in Gibbs energy required to denature the PLGA α–helix in DMF. The relationship between and the local density of macromolecules can now be applied to characterize the conformation of macromolecules in solution.
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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 | 0.000 |
| 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".