Tetrodotoxin Detection by a Surface Plasmon Resonance Sensor in Pufferfish Matrices and Urine
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
Tetrodotoxin (TTX) poisoning is most commonly associated with consumption of pufferfish. TTX is a low molecular weight (~319 Da) neurotoxin that selectively blocks voltage-sensitive Na + -gated ion channels. The standard method accepted worldwide for monitoring TTX toxicity in food matrices is the mouse bioassay. Ethical concerns from live animal testing, low sample throughput, and analytical inaccuracies have led to the need for an alternative method. We have previously established that surface plasmon resonance (SPR) sensors can quantify TTX in aqueous buffer samples by an antibody-based inhibition assay. In this paper, we report the extension of the assay for the detection of TTX in both clinical- and food-relevant matrices. The assay was optimized for application to three relevant complex matrices: pufferfish liver extract, pufferfish muscle extract, and human urine. Matrix effects are discussed and calibration curves are presented. Naturally contaminated pufferfish liver and muscle extracts were analyzed by the SPR method, and the data is compared to liquid-chromatography electrospray-ionization multiple reactions monitoring mass spectrometry (LC/ESI/MRM/MS) data. Ten samples, including three from a poisoning incident, two control monkfish samples, and five toxic pufferfish samples, were analyzed using this method, and the data is compared to LC/ESI/MRM/MS analysis of the samples.
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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 | 0.001 | 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 it