Identification of complexes involving toxic heavy metals with amino acid ligands by electrospray ionization mass spectrometry
Bibliographic record
Abstract
Electrospray ionization mass spectra (ESI-MS) of reaction mixtures containing ions of the heavy metals, cadmium, mercury, thallium, lead, and bismuth with each of the naturally occurring amino acids allows for definitive identification of monocationic complexes in the gas phase. Prominent m/z peaks are assigned to ions of the type [E(Am) xH] + (x = 0, 1, 2), [E(Am) 2 xH] + (x = 0, 1, 2), [E 2 (Am) xH] + (x = 1, 2, 3), and (or) [E 2 (Am) 2 xH] + (x = 1, 3, 5) for all amino acids studied (Am) with all metals studied (E = Cd, Hg, Tl, Pb) except bismuth, which shows complexes with only seven amino acids (Am = His, Thr, Met, Cys, Hcys, Asn, Gln). The results demonstrate the potential application of ESI-MS as a versatile and efficient approach to study toxic heavy metals in biological systems.Key words: heavy metals, amino acids, electrospray ionization mass spectrometry.
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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 | 0.001 |
| 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".