Analysis of Aspartame and its Degradation Using HPLC-MS/MS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Disinfectants (e.g. chlorine) are used to inactivate pathogens, such as E. coli, in drinking water in order to prevent the transmission of waterborne disease. Unfortunately, disinfection by-products (DBPs) are formed when natural organic matter, present in raw water, reacts with the disinfectant. Many disinfection by-products are regulated in finished drinking water by Health Canada. However, these regulated DBPs do not explain the observed risk of developing bladder cancer. Halobenzoquinones (HBQs) are an emerging class of drinking water disinfection by-products (DBPs) detected frequently in Canadian tap water with an in vitro cytotoxicity up to 1000 times greater than regulated DBPs. Preliminary investigations show that aromatic amino acids, such as phenylalanine, act as HBQ precursors under disinfection conditions. Phenylalanine is a building block of aspartame (APM), a common artificial sweetener. Drinking water treatment processes can remove portions of natural organic matter, present in raw water that may act as HBQ precursors. However residual chlorine, present in tap water, may react with organic matter used in food and drink preparation, potentially forming HBQs in situ, prior to consumption. The main objective for this project is to investigate locally available foodstuffs containing APM that are prepared with tap water such as instant drink mixes and packaged sweeteners. Next, the concentration of APM, and its degradation products, in the prepared foodstuff will be determined. APM, and its degradation products, will be separated from the food matrix using high performance liquid chromatography (HPLC) and then detected with mass spectrometry (MS). Though a method was successfully developed, aspartame’s degradation products, phenylalanine (PHE) and 5-benzyl-3,6-dioxo-2-piperazieacetic acid (DKP), the leading precursors for HBQs, were found to be below quantification limits in all samples. Regardless, this project provides a foundation for future studies regarding in-situ formation of HBQs. *Indicates presenter
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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) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 it