Aspartame-Sweetened Tap Water: Transformation Products and 2,6-Dichloro-1,4-Benzoquinone Formation
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Aspartame (APM), a dipeptide of aspartic acid (ASP) and phenylalanine (PHE), is a widely used artificial sweetener in beverages. It is unclear whether residual chlorine in tap water can react with APM to form disinfection byproducts (DBPs). Therefore, we investigated the formation of DBPs from the reaction of APM with residual chlorine in authentic tap water. APM and a commercial sweetener (CS) packet containing APM were studied under authentic and simulated tap water conditions. Eight chlorinated products of APM were detected using solid-phase extraction (SPE) and high performance liquid chromatography quadrupole time-of-flight mass spectrometry (HPLC-QTOF-MS). These new chloro-products were tentatively identified based on accurate masses, isotopic patterns of 35,37 Cl, and MS/MS spectra. Furthermore, we identified APM as a precursor to 2,6-dichloro-1,4-benzoquinone (DCBQ). DCBQ significantly increased to 2.3–12 ng/L with the addition of APM or CS in tap waters collected from different locations compared to 1.4–1.8 ng/L in the same tap water samples without sweetener. DCBQ and two of the chlorinated transformation products were identified in cold prepared tea containing APM. DCBQ formation was eliminated when the residual chlorine in tap water was reduced by ascorbic acid or boiling prior to the addition of APM or CS. This study found that eight new DBPs and DCBQ were produced by the reactions of residual chlorine with APM and CS. These findings show an unintended exposure source of emerging DBPs via APM sweetened beverages.
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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".