Abnormal Solvent Effects on Hydrogen Atom Abstraction. 2. Resolution of the Curcumin Antioxidant Controversy. The Role of Sequential Proton Loss Electron Transfer
Bibliographic record
Abstract
The rates of reaction of 1,1-diphenyl-2-picrylhydrazyl (dpph*) radicals with curcumin (CU, 1,7-bis(4-hydroxy-3-methoxyphenyl)-1,6-heptadiene-3,5-dione), dehydrozingerone (DHZ, "half-curcumin"), and isoeugenol (IE) have been measured in methanol and ethanol and in two non-hydroxylic solvents, dioxane and ethyl acetate, which have about the same hydrogen-bond-accepting abilities as the alcohols. The reactions of all three substrates are orders of magnitude faster in the alcohols, but these high rates can be suppressed to values essentially equal to those in the two non-hydroxylic solvents by the addition of acetic acid. The fast reactions in alcohols are attributed to the reaction of dpph* with the CU, DHZ, and IE anions (see J. Org. Chem. 2003, 68, 3433), a process which we herein name sequential proton loss electron transfer (SPLET). The most acidic group in CU is the central keto-enol moiety. Following CU's ionization to a monoanion, ET from the [-(O)CCHC(O)-](-) moiety to dpph* yields the neutral [-(O)CCHC(O)-]* radical moiety which will be strongly electron withdrawing. Consequently, a phenolic proton is quickly lost into the alcohol solvent. The phenoxide anion so formed undergoes charge migration to produce a neutral phenoxyl radical and the keto-enol anion, i.e., the same product as would be formed by a hydrogen atom transfer (HAT) from the phenolic group of the CU monoanion. The SPLET process cannot occur in a nonionizing solvent. The controversy as to whether the central keto-enol moiety or the peripheral phenolic hydroxyl groups of CU are involved in its radical trapping (antioxidant) activity is therefore resolved. In ionizing solvents, electron-deficient radicals will react with CU by a rapid SPLET process but in nonionizing solvents, or in the presence of acid, they will react by a slower HAT process involving one of the phenolic hydroxyl groups.
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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) | 0.003 | 0.001 |
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".