Enantioselective Electrochemical Detection of Tyrosine Isomers Using Chiral Crown Ether–Modified MWCNTs Electrodes
Bibliographic record
Abstract
An electrochemical method for enantiorecognition of tyrosine isomers (D-TYR and L-TYR) using a carbon paste electrode modified with SSSS-TCA-embedded MWCNTs has been developed. The nanocavity of SSSS-TCA serves as a host-guest interaction site where the amino group of TYR forms tripodal intermolecular hydrogen bonds that account for the difference in electrode potential. Complexation is taken as a measure of enantioselectivity, with SSSS-TCA forming a 1:1 inclusion complex with D-TYR and L-TYR, exhibiting stability constant values of 552 M −1 and 343 M −1 , respectively. Sensor shows the discernible difference in the oxidation peak potential for TYR isomers (ΔE p(L-TYR–D-TYR) = 102 mV) employing differential pulse voltammetry. Consequently, the sensor can distinguish TYR enantiomers by achieving an enantiomeric electrochemical difference ratio (I L /I D ) of 4.3. A linear relationship was observed between the TYR peak current and its concentration over the range of 2.1 to 140 μM. The limits of detection were 0.51 μM for L-TYR and 0.264 μM for D-TYR, indicating high sensitivity of the sensor. Moreover, the sensor demonstrated excellent selectivity, showing minimal interference from structurally similar compounds and other potential interfering species. The sensor was applied to estimate the amount of TYR isomers in the racemic mixture and biological fluids.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".