Electrochemical characterization of Cu(II) complexes of brain-related tau peptides
Bibliographic record
Abstract
Metal ion dyshomeostasis plays an important role in diseases, including neurodegeneration. Tau protein is a known neurodegeneration biomarker, but its interactions with biologically relevant metal ions, such as Cu(II), are not fully understood. Herein, the Cu(II) complexes of four tau R peptides, based on the tau repeat domains, R1, R2, R3, and R4, were characterized by electrochemical methods, including cyclic voltammetry, square-wave voltammetry, and differential pulse voltammetry in solution under aerobic conditions. The current and potential associated with Cu(II)/(I) redox couple was modulated as a function of R peptide sequence and concentration. All R peptides coordinated Cu(II) resulting in a dramatic decrease in the current associated with free Cu(II), and the appearance of a new redox couple due to metallo–peptide complex. The metallo–peptide complexes were characterized by the irreversible redox couple at more positive potentials and slower electron-transfer rates compared with the free Cu(II). The competition binding studies between R peptides with Cu(II) indicated that the strongest binding affinity was observed for the R3 peptide, which contained 2 His and 1 Cys residues. The formation of complexes was also evaluated as a function of peptide concentration and in the presence of competing Zn(II) ions. Data indicate that all metallo–peptides remain redox active pointing to the potential importance of the interactions between tau protein with metal ions in a biological setting.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".