Organotellurium scaffolds for mass cytometry reagent development
Bibliographic record
Abstract
Mass cytometry (MC) is a powerful tool for studying heterogeneous cell populations. In previous work, our laboratory has developed an MC probe for hypoxia bearing a methyl telluride mass tag. The methyl telluride was unoptimized, displaying stability and toxicity limitations. Here, we investigate three classes of organotelluriums as MC mass tags: methyl tellurides, trifluoromethyl tellurides and 2-alkyl-tellurophenes. NMR was used to compare the stability of these compounds in aqueous and organic solutions and the compounds were analysed for toxicity in Jurkat cells. The methyl tellurides were moderately stable to aerobic oxidation in organic solution under dry ambient conditions. The trifluoromethyl tellurides were stable to aerobic oxidation in organic solution but decomposed in aqueous solution. The 2-alkyl-tellurophenes proved to be stable in both organic and aqueous solutions under ambient conditions and showed limited toxicity (IC50 > 200 μM) in cell based assays. The synthetic feasibility, chemically stability, and limited toxicity of tellurophenes suggests these groups will be good choices for MC reagent development.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".